There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Laure ROUCH |
| Institution: | Toulouse University Hospital |
| Department: | Institute of Aging |
| Country: | |
| Proposed Analysis: | Proposal of research project: “Associations between erythrocyte omega-3 and cognitive outcomes in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3)” Developed by: Kelly Virecoulon Giudici, Sophie Guyonnet, Christelle Cantet, Laure Rouch, Philipe de Souto Barreto, Bruno Vellas (Institute of Aging, Gérontopôle, Toulouse University Hospital) 1. BACKGROUND Omega-3 (ω-3) polyunsaturated fatty acids (PUFA) have received significant research attention in relation to their beneficial effects on cognition, mainly docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA). DHA is the major fatty acid in neuronal membranes and is involved in multiple inter-related brain functions including cell membrane fluidity, signal transduction and neurotransmission (1-3). Cerebral DHA levels are known to be deficient specifically in brain regions associated with Alzheimer’s disease (AD) (4,5), and also to decrease in the brain in the process of normal human aging (6). Many observational studies have provided support for the therapeutic use of ω-3 in AD (7), and randomized controlled trials (RCT) have demonstrated a benefit of ω-3 supplementation in patients with mild cognitive impairment (MCI), particularly in terms of immediate recall, attention and processing speed (8). Potential benefic mechanisms of ω-3 PUFA involve the promotion of long term potentiation (LTP), a process related to functional plasticity, intimately related with learning and memory (9). There is also evidence suggesting that DHA confers neuro-protection in part through the direct inhibition of tau phosphorylation at the phospho-specific epitopes AT270, AT180 and Ser422 through mechanisms involving c-Jun N-terminal kinase (JNK) (10,11), or indirectly through the modulation of microglial activity and the suppression of neuroinflammation (12-14). Moreover, DHA and EPA have been shown to alter amyloid precursor protein (APP) processing, reducing amyloid-β peptide production (15-19). Based on this evidence, it is plausible that cognitive decline might also be influenced by ω-3 bio-status, which can be easily measured by erythrocyte ω-3 index (20,21). Fatty acids concentration in red blood cells (RBC) represent a more reliable measurement of dietary habits compared to plasma measurements, considering that fatty acids are stable in RBC membranes for up to 3 months (corresponding to the lifespan of an erythrocyte) (22). RBC fatty acid concentrations have also been shown to reflect peripheral tissue concentrations and thus represents the best current clinical correlate of ω-3 status (23). Identifying older adults at risk of cognitive decline is important to enable timely treatment before AD pathology becomes irreversible; as such ω-3 PUFA might offer a potential well tolerated, inexpensive treatment in the early stages of AD, particularly in subjects with sub-optimal erythrocyte ω-3 levels. Furthermore, consumption of ω-3 PUFA (DHA and EPA) has been suggested to potentially benefit cardiovascular health, particularly hypertension. These beneficial effects have been explained by the capacity to prevent arrythmias, to improve vascular reactivity, to decrease atherosclerosis and inflammation and even more importantly, to decrease blood pressure levels (24-26). Moreover, hypertension has been associated with cognitive decline and incident dementia, both AD and vascular dementia, in several epidemiological studies (27-28). According to experimental animal studies, there is a plausible pathway by which hypertension and low dietary ω-3 intake may interact in increasing the risk of cognitive decline and dementia. In fact, hypertensive rats tended to have lower brain ω-3 PUFA than normotensive rats (29), possibly due to pressure-induced endothelial dysfunction at the blood-brain barrier or exhausted astrocytic metabolism. Oxidative stress which accompanies high blood pressure leads to increased peroxidation of unsaturated fatty acids and a reduction in their concentration in the brain represents an alternative explanation. Despite animal experimental evidence for a possible biological interaction between ω-3 PUFA and hypertensive status in affecting cognitive decline (29-32), only one research to date, conducted in the Atherosclerosis Risk in Communities (ARIC) Study, has attempted to test this hypothesis (33). Although no statistically significant interactions were found, the results suggested that hypertensive subjects may benefit in terms of cognition from supplementation in ω-3 to a larger extent than the normotensive group. Finally, previous studies reported that the presence of ApoE ε4 allele may modify the relationship between ω-3 PUFA and cognitive functioning. It has been hypothesized that the absorption and transportation of PUFA were probably different depending on the genotype (34). Some studies showed a greater benefit of fatty fish on dementia risk in patients without ApoE ε4 (35, 36). On the contrary, other findings reported slower rates of cognitive decline with PUFA from food in ApoE ε4 carriers (37). Thus, the potential role of ApoE ε4 status in the relationship between ω-3 PUFA and cognitive function warrants further research investigation. 2. HYPOTHESES 2.1. Main hypothesis We hypothesized that erythrocyte ω-3 index (used as both dichotomous variable and continuous variable) may be a predictor of cognitive decline in older adults, and that subjects exhibiting a low ω-3 index would undergo significantly more cognitive decline compared to those subjects exhibiting a higher ω-3 index. 2.2. Specific hypotheses 2.2.1. Analyses ready to be run • Cross-sectional (using baseline data from ADNI 3): participants with low ω-3 index (defined as those in the lowest quartile) would present lower cognitive function*, higher brain amyloid (measured by PET scan), lower hippocampal volume, higher white matter hyperintensities, higher tau accumulation. Also, we hypothesized that participants with AD would present lower ω-3 index (as a continuous variable), compared to MCI and cognitively normal, and that MCI would present lower ω-3 index, compared to cognitively normal subjects. We also hypothesized that participants with both low ω-3 index and hypertension would have worse cognitive outcomes: lower cognitive functions (especially lower executive functions), higher amyloid and tau accumulation, lower hippocampal volume and higher white matter hyperintensities, compared to participants with low ω-3 index but without hypertension. • Retrospective (using data from ADNI 1, ADNI 2 and baseline ADNI 3): participants with low ω-3 index would present previous over time decrease in cognitive function, increase in brain amyloid, decrease in hippocampal volume, increase in white matter hyperintensities and increase in tau accumulation compared to participants with normal ω-3 index. In addition, participants who developed MCI and AD over time would present lower ω-3 index (as a continuous variable), compared to subjects who remained cognitively normal. Similarly, participants with both low ω-3 index and hypertension would present greater previous over time decrease in cognitive function, amyloid and tau accumulation, decrease in hippocampal volume and increase in white matter hyperintensities compared to participants with low ω-3 index but without hypertension. 2.2.2. Future analyses (waiting for prospective data from ADNI 3) • Prospective (using baseline and future post-baseline data from ADNI 3): participants with low ω-3 index would present higher impairment in cognitive outcomes compared to participants with normal ω-3 index over time (lower cognitive function, higher hippocampal atrophy, higher deposit of brain amyloid, higher white matter hyperintensities and increased tau accumulation. In addition, more pronounced impairments would be observed among participants with MCI and AD, compared to cognitively normal subjects. Similarly, participants with both low ω-3 index and hypertension would develop worse cognitive outcomes (cognitive function, brain imaging, amyloid and tau accumulation) over time compared to participants with low ω-3 index but without hypertension. 3. OBJECTIVES 3.1. Overall aim We therefore aim to analyze the associations between baseline erythrocyte ω-3 index and cognitive outcomes (clinical tests, brain imaging, β-amyloid load, tau accumulation) among older adults, participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3). 3.2. Specific aims • To evaluate if the erythrocyte ω-3 index (as continuous variable) differs according to the cognitive status of participants (cognitively normal, MCI or AD). • To explore, cross-sectionally, if subjects with low ω-3 index would present higher brain amyloid β load (measured as standard uptake value ratio – SUVr), higher levels of hyper-phosphorylated tau, lower hippocampal volume and higher white matter hyperintensities, compared to participants with normal ω-3 index. • To explore if low ω-3 index would lead to increased brain Aβ load (measured as standard uptake value ratio – SUVr), increased levels of hyper-phosphorylated tau accumulation, higher hippocampal atrophy and higher white matter hyperintensities over time. • To investigate if the relationship between erythrocyte ω-3 index and cognitive outcomes differs according to the initial cognitive status of participants (cognitively normal, MCI or AD). • To evaluate if participants with pathological levels of brain amyloid (amyloid positive; SUVr ≥ 1.17) would present lower ω-3 index, compared to amyloid negative subjects. • To analyze the extent of AD related pathology associated with ω-3 index and cognitive decline, in the subsample of participants with AD. • To investigate the relationship between erythrocyte ω-3 index and retrospective cognitive outcomes. • To investigate whether the relationship between erythrocyte ω-3 index and cognitive outcomes (cognitive function, brain imaging, amyloid and Tau accumulation) differs according to the presence of hypertension status. • To investigate whether the presence of low erythrocyte ω-3 index and hypertension results in a predominantly “vascular” pattern of cognitive impairment (worse executive functions, greater white matter hyperintensities). • To determine how ApoE ε4 genotype can modify the relationship between erythrocyte ω-3 index and cognitive outcomes. 4. METHODS 4.1. Study population Participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3) (38) were adults aged 55 to 90 years with cognitively normal status (with or without subjective memory concerns), MCI (both early and late MCI) or AD. ADNI3 was registered in ClinicalTrials.gov under the protocol NCT02854033. All subjects were informed about the aims of this multi-center, non-randomized, natural history non-treatment study, and signed a consent form. 4.2. Isolation of erythrocytes and fatty acids measurement RBC collected at baseline were isolated from whole blood (5ml) collected into ethylenediamine tetraacetic acid (EDTA) tubes, according to the standardized procedures at ADNI sites (the ω-3 PUFA measurement is not affected by the presence of anti-coagulant). The blood was centrifuged at 2000 gravitational force (g) for 15 minutes at 4°C. This results in the formation of a RBC pellet an intermediate layer containing the leukocytes and platelets (buffy coat) and an upper phase comprising plasma. Following removal of the plasma and buffy coat, RBC was stored immediately at -80°C in EDTA tubes before shipment in batches on dry ice. After receipt of coded samples, fatty acids analysis will be performed in the Biochemistry Laboratory of Agrocampus-Ouest at Rennes by the team coordinated by Dr. Philippe Legrand. Lipids will be extracted from RBC samples (500 mg) with a mixture of hexane/isopropanol (3:2 v/v), after acidification with 1 mL HCl 3 M1. Margaric acid will be added as internal standard. Total lipid extracts will be saponified with 1 mL of 0.5 M NaOH in methanol for 30 min at 70 °C and methylated with 1 mL of BF3 for 15 min at 70°C. Fatty acid methyl esters (FAME) will be extracted twice with pentane and analyzed by GC using an Agilent Technologies 6890N gas chromatograph (Bios Analytic, L’union, France) with a split injector (260°C, 10:1, injection volume 2µL); a bonded silica capillary column (BPX 70, 60 m x 0.25 mm; 0.25 µm film thickness; SGE, Villeneuve-St Georges, France) and a flame ionization detector (260°C, air: 450 mL/min; hydrogen: 40 mL/min). Helium will be used as a carrier gas (constant flow: 1.5 mL/min, average velocity: 24 cm/s). The column temperature program will start at 150 °C, increase by 1.3 °C/min to 220 °C and be held at 220 °C for 10 min. Identification of FAME will be based on retention times obtained for FAME prepared from fatty acid standards. The area under the peaks will be determined using ChemStation software (Agilent) and results will be expressed as % of total fatty acids. DHA concentration will be calculated using the internal standard and expressed as µg/g for RBC samples. The ω-3 index will be calculated as the sum of %EPA and %DHA, and thus also expressed in % from total fatty acids. Low ω-3 index will be characterized by the lowest quartile within the population investigated in this study. 4.3. Outcomes In cognitively normal and MCI subjects, primary outcome will be the changes in cognition over 5 years as measured by a modified form of the Alzheimer Disease Cooperative Study Preclinical Alzheimer Cognitive Composite (ADCS-PACC) (39), where the total recall from the FCSRT will be substituted for the delayed word recall from the Alzheimer’s disease assessment scale cognitive subscale (ADAS-Cog) and the Digit Symbol Substitution Test (DSST) will be replaced by the Trail Making Test A (TMT-A). The modified composite will include: the delayed recall from the ADAS-cog, the delayed recall from the logical memory IIa subset from the Wechsler Memory Scale, the TMT-A and the MMSE total score. For subjects with AD, cognitive changes over 2 years will be measured by the ADAS-Cog. The different cognitive tests will also be examined separately, especially the Trail Making Test A (TMT-A) and the Montreal Cognitive Assessment MoCA to determine a potential vascular pattern of cognitive impairment (executive functions) in participants having low ω-3 index and hypertension. Secondary outcomes include changes in cognitive measures given by the Clinical Dementia Rating Sum of Boxes (CDR-SB), brain amyloid and hyper-phosphorylated paired helical filaments (PHF) tau (as measured by positron-emission tomography (PET) imaging), and changes in hippocampal volume and white matter hyperintensities assessed by magnetic resonance imaging (MRI). 4.4. Power calculations In MAPT Study, a mean difference of -0.295 in the change in composite cognitive score at year 3 was estimated between subjects with a low ω-3 index and superior ω-3 index receiving placebo with CDR=0. In ADNI, sample sizes of 400 cognitively normal, 400 MCI and 200 AD will be enrolled at baseline (minimal estimates of new + rollover recruits) with an expected drop-out rate of 40% at year 5 for the normal and MCI groups and 50% at year 2 for the AD group. Given these numbers, the smallest differences in cognition between ω-3 index subgroups that could be detected with 80% power considering a standard deviation of 0.57 estimated using MAPT data will be -0.169 at year 5 for analysis on normal and MCI together (120 subjects ≤Q1 and 360>Q1), -0.239 at year 5 for analysis on normal or MCI separately (60 subjects ≤Q1 and 180>Q1) and -0.372 at year 2 for AD subjects (25 subjects≤Q1 and 75>Q1) with a significance level of 0.05 (two-sided t-test). 4.5. Statistical analysis Baseline characteristics will be summarized as mean and standard deviation (SD) for continuous variables and as frequencies and percentages for categorical variables. In order to evaluate the cross-sectional relationship between the levels of baseline ω-3 index (1st quartile vs the others) and primary and secondary outcomes, t-tests for continuous variables with a Gaussian distribution or the non-parametric Kruskal-Wallis test for others quantitative variables will be performed, as also chi-squared tests for qualitative variables or Fisher’s exact test if there is an expected frequency <5. To test if the relationship between the ω-3 index and outcomes is different according to cognitive status groups (cognitively normal, MCI and AD) we will perform linear regressions with cognitive outcomes as the dependent variable and the ω-3 index, the cognitive status group and the interaction between these two parameters as the independent variables. To determine how APOE4 genotype can modify the relationship between omega 3 and cognitive outcomes, we will also test the statistical interaction and run analyses stratified on the presence of APOE4 genotype. Linear mixed models will be performed to study changes in cognitive performance (dependent variables: modified ADCS-PACC score among cognitively normal and MCI subjects at 5 years, and ADAS-Cog for AD subjects at 2 years) over time according to ω-3 index at baseline (independent variable) including all available data (baseline values and each time of follow-up). For each mixed model the following fixed effects will be included: ω-3 index group, time (as a continuous variable) and the interaction between the group and time. Subject-specific random effects will be included to take into account the intra-subject correlation; a random intercept to take into account the heterogeneity of the cognitive outcomes at baseline; and a random slope to take into account the heterogeneity of the slopes between subjects if this parameter is significant. Given the multicenter characteristic of the study, a center-specific random intercept can be introduced to take into account the intra-center correlation if this parameter is significant. All analyses for primary outcomes will be adjusted for potential confounders (age, sex, education, ApoE4 status, alcohol, smoking, BMI, cardiovascular risk factors, and brain amyloid and tau levels). Similar mixed models for secondary outcomes will be conducted to examine the relationship between ω-3 index at baseline and CDR-SB, brain amyloid, tau levels, hippocampal volume and white matter hyperintensities. To determine whether hypertension status can modify the relationship between erythrocyte ω-3 index and cognitive outcomes, we will test the statistical interaction and run analyses stratified on the presence and/or severity of hypertension. Analyses will be performed using the Statistical Analysis Software (SAS) version 9.4 (Cary, NC, USA), with a significance level established as 5%. References 1. Guixà-González, R. et al. Membrane omega-3 fatty acids modulate the oligomerisation kinetics of adenosine A2A and dopamine D2 receptors. Sci. Rep. 6, 19839 (2016). 2. McGahon, B. M., Martin, D. S., Horrobin, D. F. & Lynch, M. A. Age-related changes in synaptic function: analysis of the effect of dietary supplementation with omega-3 fatty acids. Neuroscience 94, 305–314 (1999). 3. Lin, Q., Ruuska, S. E., Shaw, N. S., Dong, D. & Noy, N. Ligand selectivity of the peroxisome proliferator-activated receptor alpha. Biochemistry (Mosc.) 38, 185–190 (1999). 4. Prasad, M. R., Lovell, M. A., Yatin, M., Dhillon, H. & Markesbery, W. R. Regional membrane phospholipid alterations in Alzheimer’s disease. Neurochem. Res. 23, 81–88 (1998). 5. Söderberg, M., Edlund, C., Kristensson, K. & Dallner, G. Fatty acid composition of brain phospholipids in aging and in Alzheimer’s disease. Lipids 26, 421–425 (1991). 6. McNamara, R. K., Liu, Y., Jandacek, R., Rider, T. & Tso, P. 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A polyunsaturated fatty acid diet lowers blood pressure and improves antioxidant status in spontaneously hypertensive rats. J Nutr. janv 2001;131(1):39‑45. 31. Bellenger-Germain S, Poisson JP, Narce M. Antihypertensive effects of a dietary unsaturated FA mixture in spontaneously hypertensive rats. Lipids. juin 2002;37(6):561‑7. 32. Engler MM, Engler MB, Pierson DM, Molteni LB, Molteni A. Effects of docosahexaenoic acid on vascular pathology and reactivity in hypertension. Exp Biol Med Maywood NJ. mars 2003;228(3):299‑307. 33. Beydoun MA, Kaufman JS, Sloane PD, Heiss G, Ibrahim J. n-3 Fatty acids, hypertension and risk of cognitive decline among older adults in the Atherosclerosis Risk in Communities (ARIC) study. Public Health Nutr. janv 2008;11(1):17‑29. 34. Barberger-Gateau P1, Raffaitin C, Letenneur L, Berr C, Tzourio C, Dartigues JF, Alpérovitch A. Dietary patterns and risk of dementia: the Three-City cohort study. Neurology. 2007 Nov 13;69(20):1921-30. 35. Huang TL1, Zandi PP, Tucker KL, Fitzpatrick AL, Kuller LH, Fried LP, Burke GL, Carlson MC. Benefits of fatty fish on dementia risk are stronger for those without APOE epsilon4. Neurology. 2005 Nov 8;65(9):1409-14 36. Whalley LJ1, Deary IJ, Starr JM, Wahle KW, Rance KA, Bourne VJ, Fox HC. n-3 Fatty acid erythrocyte membrane content, APOE varepsilon4, and cognitive variation: an observational follow-up study in late adulthood. Am J Clin Nutr. 2008 Feb;87(2):449-54. 37. van de Rest O1, Wang Y2, Barnes LL2, Tangney C2, Bennett DA2, Morris MC2. APOE ε4 and the associations of seafood and long-chain omega-3 fatty acids with cognitive decline. Neurology. 2016 May 31;86(22):2063-70 38. Weiner, M.W., Veitch, D.P., Aisen, P.S., Beckett, L.A., Cairns, N.J., Green, R.C., Harvey, D., Jack, C.R. Jr, Jagust, W., Morris, J.C., Petersen, R.C., Salazar, J., Saykin, A.J., Shaw, L.M., Toga, A.W., Trojanowski, J.Q.; Alzheimer's Disease Neuroimaging Initiative. The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement. Alzheimers Dement.13(5), 561-571 (2017). 39 Donohue, M. C. et al. The preclinical Alzheimer cognitive composite: measuring amyloid-related decline. JAMA Neurol. 71, 961–970 (2014). |
| Additional Investigators | |
| Investigator's Name: | Kelly GUIDICI |
| Proposed Analysis: | Proposal of research project: “Associations between erythrocyte omega-3 and cognitive outcomes in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3)” Developed by: Kelly Virecoulon Giudici, Sophie Guyonnet, Christelle Cantet, Laure Rouch, Philipe de Souto Barreto, Bruno Vellas (Institute of Aging, Gérontopôle, Toulouse University Hospital) 1. BACKGROUND Omega-3 (ω-3) polyunsaturated fatty acids (PUFA) have received significant research attention in relation to their beneficial effects on cognition, mainly docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA). DHA is the major fatty acid in neuronal membranes and is involved in multiple inter-related brain functions including cell membrane fluidity, signal transduction and neurotransmission (1-3). Cerebral DHA levels are known to be deficient specifically in brain regions associated with Alzheimer’s disease (AD) (4,5), and also to decrease in the brain in the process of normal human aging (6). Many observational studies have provided support for the therapeutic use of ω-3 in AD (7), and randomized controlled trials (RCT) have demonstrated a benefit of ω-3 supplementation in patients with mild cognitive impairment (MCI), particularly in terms of immediate recall, attention and processing speed (8). Potential benefic mechanisms of ω-3 PUFA involve the promotion of long term potentiation (LTP), a process related to functional plasticity, intimately related with learning and memory (9). There is also evidence suggesting that DHA confers neuro-protection in part through the direct inhibition of tau phosphorylation at the phospho-specific epitopes AT270, AT180 and Ser422 through mechanisms involving c-Jun N-terminal kinase (JNK) (10,11), or indirectly through the modulation of microglial activity and the suppression of neuroinflammation (12-14). Moreover, DHA and EPA have been shown to alter amyloid precursor protein (APP) processing, reducing amyloid-β peptide production (15-19). Based on this evidence, it is plausible that cognitive decline might also be influenced by ω-3 bio-status, which can be easily measured by erythrocyte ω-3 index (20,21). Fatty acids concentration in red blood cells (RBC) represent a more reliable measurement of dietary habits compared to plasma measurements, considering that fatty acids are stable in RBC membranes for up to 3 months (corresponding to the lifespan of an erythrocyte) (22). RBC fatty acid concentrations have also been shown to reflect peripheral tissue concentrations and thus represents the best current clinical correlate of ω-3 status (23). Identifying older adults at risk of cognitive decline is important to enable timely treatment before AD pathology becomes irreversible; as such ω-3 PUFA might offer a potential well tolerated, inexpensive treatment in the early stages of AD, particularly in subjects with sub-optimal erythrocyte ω-3 levels. Furthermore, consumption of ω-3 PUFA (DHA and EPA) has been suggested to potentially benefit cardiovascular health, particularly hypertension. These beneficial effects have been explained by the capacity to prevent arrythmias, to improve vascular reactivity, to decrease atherosclerosis and inflammation and even more importantly, to decrease blood pressure levels (24-26). Moreover, hypertension has been associated with cognitive decline and incident dementia, both AD and vascular dementia, in several epidemiological studies (27-28). According to experimental animal studies, there is a plausible pathway by which hypertension and low dietary ω-3 intake may interact in increasing the risk of cognitive decline and dementia. In fact, hypertensive rats tended to have lower brain ω-3 PUFA than normotensive rats (29), possibly due to pressure-induced endothelial dysfunction at the blood-brain barrier or exhausted astrocytic metabolism. Oxidative stress which accompanies high blood pressure leads to increased peroxidation of unsaturated fatty acids and a reduction in their concentration in the brain represents an alternative explanation. Despite animal experimental evidence for a possible biological interaction between ω-3 PUFA and hypertensive status in affecting cognitive decline (29-32), only one research to date, conducted in the Atherosclerosis Risk in Communities (ARIC) Study, has attempted to test this hypothesis (33). Although no statistically significant interactions were found, the results suggested that hypertensive subjects may benefit in terms of cognition from supplementation in ω-3 to a larger extent than the normotensive group. Finally, previous studies reported that the presence of ApoE ε4 allele may modify the relationship between ω-3 PUFA and cognitive functioning. It has been hypothesized that the absorption and transportation of PUFA were probably different depending on the genotype (34). Some studies showed a greater benefit of fatty fish on dementia risk in patients without ApoE ε4 (35, 36). On the contrary, other findings reported slower rates of cognitive decline with PUFA from food in ApoE ε4 carriers (37). Thus, the potential role of ApoE ε4 status in the relationship between ω-3 PUFA and cognitive function warrants further research investigation. 2. HYPOTHESES 2.1. Main hypothesis We hypothesized that erythrocyte ω-3 index (used as both dichotomous variable and continuous variable) may be a predictor of cognitive decline in older adults, and that subjects exhibiting a low ω-3 index would undergo significantly more cognitive decline compared to those subjects exhibiting a higher ω-3 index. 2.2. Specific hypotheses 2.2.1. Analyses ready to be run • Cross-sectional (using baseline data from ADNI 3): participants with low ω-3 index (defined as those in the lowest quartile) would present lower cognitive function*, higher brain amyloid (measured by PET scan), lower hippocampal volume, higher white matter hyperintensities, higher tau accumulation. Also, we hypothesized that participants with AD would present lower ω-3 index (as a continuous variable), compared to MCI and cognitively normal, and that MCI would present lower ω-3 index, compared to cognitively normal subjects. We also hypothesized that participants with both low ω-3 index and hypertension would have worse cognitive outcomes: lower cognitive functions (especially lower executive functions), higher amyloid and tau accumulation, lower hippocampal volume and higher white matter hyperintensities, compared to participants with low ω-3 index but without hypertension. • Retrospective (using data from ADNI 1, ADNI 2 and baseline ADNI 3): participants with low ω-3 index would present previous over time decrease in cognitive function, increase in brain amyloid, decrease in hippocampal volume, increase in white matter hyperintensities and increase in tau accumulation compared to participants with normal ω-3 index. In addition, participants who developed MCI and AD over time would present lower ω-3 index (as a continuous variable), compared to subjects who remained cognitively normal. Similarly, participants with both low ω-3 index and hypertension would present greater previous over time decrease in cognitive function, amyloid and tau accumulation, decrease in hippocampal volume and increase in white matter hyperintensities compared to participants with low ω-3 index but without hypertension. 2.2.2. Future analyses (waiting for prospective data from ADNI 3) • Prospective (using baseline and future post-baseline data from ADNI 3): participants with low ω-3 index would present higher impairment in cognitive outcomes compared to participants with normal ω-3 index over time (lower cognitive function, higher hippocampal atrophy, higher deposit of brain amyloid, higher white matter hyperintensities and increased tau accumulation. In addition, more pronounced impairments would be observed among participants with MCI and AD, compared to cognitively normal subjects. Similarly, participants with both low ω-3 index and hypertension would develop worse cognitive outcomes (cognitive function, brain imaging, amyloid and tau accumulation) over time compared to participants with low ω-3 index but without hypertension. 3. OBJECTIVES 3.1. Overall aim We therefore aim to analyze the associations between baseline erythrocyte ω-3 index and cognitive outcomes (clinical tests, brain imaging, β-amyloid load, tau accumulation) among older adults, participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3). 3.2. Specific aims • To evaluate if the erythrocyte ω-3 index (as continuous variable) differs according to the cognitive status of participants (cognitively normal, MCI or AD). • To explore, cross-sectionally, if subjects with low ω-3 index would present higher brain amyloid β load (measured as standard uptake value ratio – SUVr), higher levels of hyper-phosphorylated tau, lower hippocampal volume and higher white matter hyperintensities, compared to participants with normal ω-3 index. • To explore if low ω-3 index would lead to increased brain Aβ load (measured as standard uptake value ratio – SUVr), increased levels of hyper-phosphorylated tau accumulation, higher hippocampal atrophy and higher white matter hyperintensities over time. • To investigate if the relationship between erythrocyte ω-3 index and cognitive outcomes differs according to the initial cognitive status of participants (cognitively normal, MCI or AD). • To evaluate if participants with pathological levels of brain amyloid (amyloid positive; SUVr ≥ 1.17) would present lower ω-3 index, compared to amyloid negative subjects. • To analyze the extent of AD related pathology associated with ω-3 index and cognitive decline, in the subsample of participants with AD. • To investigate the relationship between erythrocyte ω-3 index and retrospective cognitive outcomes. • To investigate whether the relationship between erythrocyte ω-3 index and cognitive outcomes (cognitive function, brain imaging, amyloid and Tau accumulation) differs according to the presence of hypertension status. • To investigate whether the presence of low erythrocyte ω-3 index and hypertension results in a predominantly “vascular” pattern of cognitive impairment (worse executive functions, greater white matter hyperintensities). • To determine how ApoE ε4 genotype can modify the relationship between erythrocyte ω-3 index and cognitive outcomes. 4. METHODS 4.1. Study population Participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3) (38) were adults aged 55 to 90 years with cognitively normal status (with or without subjective memory concerns), MCI (both early and late MCI) or AD. ADNI3 was registered in ClinicalTrials.gov under the protocol NCT02854033. All subjects were informed about the aims of this multi-center, non-randomized, natural history non-treatment study, and signed a consent form. 4.2. Isolation of erythrocytes and fatty acids measurement RBC collected at baseline were isolated from whole blood (5ml) collected into ethylenediamine tetraacetic acid (EDTA) tubes, according to the standardized procedures at ADNI sites (the ω-3 PUFA measurement is not affected by the presence of anti-coagulant). The blood was centrifuged at 2000 gravitational force (g) for 15 minutes at 4°C. This results in the formation of a RBC pellet an intermediate layer containing the leukocytes and platelets (buffy coat) and an upper phase comprising plasma. Following removal of the plasma and buffy coat, RBC was stored immediately at -80°C in EDTA tubes before shipment in batches on dry ice. After receipt of coded samples, fatty acids analysis will be performed in the Biochemistry Laboratory of Agrocampus-Ouest at Rennes by the team coordinated by Dr. Philippe Legrand. Lipids will be extracted from RBC samples (500 mg) with a mixture of hexane/isopropanol (3:2 v/v), after acidification with 1 mL HCl 3 M1. Margaric acid will be added as internal standard. Total lipid extracts will be saponified with 1 mL of 0.5 M NaOH in methanol for 30 min at 70 °C and methylated with 1 mL of BF3 for 15 min at 70°C. Fatty acid methyl esters (FAME) will be extracted twice with pentane and analyzed by GC using an Agilent Technologies 6890N gas chromatograph (Bios Analytic, L’union, France) with a split injector (260°C, 10:1, injection volume 2µL); a bonded silica capillary column (BPX 70, 60 m x 0.25 mm; 0.25 µm film thickness; SGE, Villeneuve-St Georges, France) and a flame ionization detector (260°C, air: 450 mL/min; hydrogen: 40 mL/min). Helium will be used as a carrier gas (constant flow: 1.5 mL/min, average velocity: 24 cm/s). The column temperature program will start at 150 °C, increase by 1.3 °C/min to 220 °C and be held at 220 °C for 10 min. Identification of FAME will be based on retention times obtained for FAME prepared from fatty acid standards. The area under the peaks will be determined using ChemStation software (Agilent) and results will be expressed as % of total fatty acids. DHA concentration will be calculated using the internal standard and expressed as µg/g for RBC samples. The ω-3 index will be calculated as the sum of %EPA and %DHA, and thus also expressed in % from total fatty acids. Low ω-3 index will be characterized by the lowest quartile within the population investigated in this study. 4.3. Outcomes In cognitively normal and MCI subjects, primary outcome will be the changes in cognition over 5 years as measured by a modified form of the Alzheimer Disease Cooperative Study Preclinical Alzheimer Cognitive Composite (ADCS-PACC) (39), where the total recall from the FCSRT will be substituted for the delayed word recall from the Alzheimer’s disease assessment scale cognitive subscale (ADAS-Cog) and the Digit Symbol Substitution Test (DSST) will be replaced by the Trail Making Test A (TMT-A). The modified composite will include: the delayed recall from the ADAS-cog, the delayed recall from the logical memory IIa subset from the Wechsler Memory Scale, the TMT-A and the MMSE total score. For subjects with AD, cognitive changes over 2 years will be measured by the ADAS-Cog. The different cognitive tests will also be examined separately, especially the Trail Making Test A (TMT-A) and the Montreal Cognitive Assessment MoCA to determine a potential vascular pattern of cognitive impairment (executive functions) in participants having low ω-3 index and hypertension. Secondary outcomes include changes in cognitive measures given by the Clinical Dementia Rating Sum of Boxes (CDR-SB), brain amyloid and hyper-phosphorylated paired helical filaments (PHF) tau (as measured by positron-emission tomography (PET) imaging), and changes in hippocampal volume and white matter hyperintensities assessed by magnetic resonance imaging (MRI). 4.4. Power calculations In MAPT Study, a mean difference of -0.295 in the change in composite cognitive score at year 3 was estimated between subjects with a low ω-3 index and superior ω-3 index receiving placebo with CDR=0. In ADNI, sample sizes of 400 cognitively normal, 400 MCI and 200 AD will be enrolled at baseline (minimal estimates of new + rollover recruits) with an expected drop-out rate of 40% at year 5 for the normal and MCI groups and 50% at year 2 for the AD group. Given these numbers, the smallest differences in cognition between ω-3 index subgroups that could be detected with 80% power considering a standard deviation of 0.57 estimated using MAPT data will be -0.169 at year 5 for analysis on normal and MCI together (120 subjects ≤Q1 and 360>Q1), -0.239 at year 5 for analysis on normal or MCI separately (60 subjects ≤Q1 and 180>Q1) and -0.372 at year 2 for AD subjects (25 subjects≤Q1 and 75>Q1) with a significance level of 0.05 (two-sided t-test). 4.5. Statistical analysis Baseline characteristics will be summarized as mean and standard deviation (SD) for continuous variables and as frequencies and percentages for categorical variables. In order to evaluate the cross-sectional relationship between the levels of baseline ω-3 index (1st quartile vs the others) and primary and secondary outcomes, t-tests for continuous variables with a Gaussian distribution or the non-parametric Kruskal-Wallis test for others quantitative variables will be performed, as also chi-squared tests for qualitative variables or Fisher’s exact test if there is an expected frequency <5. To test if the relationship between the ω-3 index and outcomes is different according to cognitive status groups (cognitively normal, MCI and AD) we will perform linear regressions with cognitive outcomes as the dependent variable and the ω-3 index, the cognitive status group and the interaction between these two parameters as the independent variables. To determine how APOE4 genotype can modify the relationship between omega 3 and cognitive outcomes, we will also test the statistical interaction and run analyses stratified on the presence of APOE4 genotype. Linear mixed models will be performed to study changes in cognitive performance (dependent variables: modified ADCS-PACC score among cognitively normal and MCI subjects at 5 years, and ADAS-Cog for AD subjects at 2 years) over time according to ω-3 index at baseline (independent variable) including all available data (baseline values and each time of follow-up). For each mixed model the following fixed effects will be included: ω-3 index group, time (as a continuous variable) and the interaction between the group and time. Subject-specific random effects will be included to take into account the intra-subject correlation; a random intercept to take into account the heterogeneity of the cognitive outcomes at baseline; and a random slope to take into account the heterogeneity of the slopes between subjects if this parameter is significant. Given the multicenter characteristic of the study, a center-specific random intercept can be introduced to take into account the intra-center correlation if this parameter is significant. All analyses for primary outcomes will be adjusted for potential confounders (age, sex, education, ApoE4 status, alcohol, smoking, BMI, cardiovascular risk factors, and brain amyloid and tau levels). Similar mixed models for secondary outcomes will be conducted to examine the relationship between ω-3 index at baseline and CDR-SB, brain amyloid, tau levels, hippocampal volume and white matter hyperintensities. To determine whether hypertension status can modify the relationship between erythrocyte ω-3 index and cognitive outcomes, we will test the statistical interaction and run analyses stratified on the presence and/or severity of hypertension. Analyses will be performed using the Statistical Analysis Software (SAS) version 9.4 (Cary, NC, USA), with a significance level established as 5%. 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| Investigator's Name: | Christelle Cantet |
| Proposed Analysis: | Proposal of research project: “Associations between erythrocyte omega-3 and cognitive outcomes in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3)” Developed by: Kelly Virecoulon Giudici, Sophie Guyonnet, Christelle Cantet, Laure Rouch, Philipe de Souto Barreto, Bruno Vellas (Institute of Aging, Gérontopôle, Toulouse University Hospital) 1. BACKGROUND Omega-3 (ω-3) polyunsaturated fatty acids (PUFA) have received significant research attention in relation to their beneficial effects on cognition, mainly docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA). DHA is the major fatty acid in neuronal membranes and is involved in multiple inter-related brain functions including cell membrane fluidity, signal transduction and neurotransmission (1-3). Cerebral DHA levels are known to be deficient specifically in brain regions associated with Alzheimer’s disease (AD) (4,5), and also to decrease in the brain in the process of normal human aging (6). Many observational studies have provided support for the therapeutic use of ω-3 in AD (7), and randomized controlled trials (RCT) have demonstrated a benefit of ω-3 supplementation in patients with mild cognitive impairment (MCI), particularly in terms of immediate recall, attention and processing speed (8). Potential benefic mechanisms of ω-3 PUFA involve the promotion of long term potentiation (LTP), a process related to functional plasticity, intimately related with learning and memory (9). There is also evidence suggesting that DHA confers neuro-protection in part through the direct inhibition of tau phosphorylation at the phospho-specific epitopes AT270, AT180 and Ser422 through mechanisms involving c-Jun N-terminal kinase (JNK) (10,11), or indirectly through the modulation of microglial activity and the suppression of neuroinflammation (12-14). Moreover, DHA and EPA have been shown to alter amyloid precursor protein (APP) processing, reducing amyloid-β peptide production (15-19). Based on this evidence, it is plausible that cognitive decline might also be influenced by ω-3 bio-status, which can be easily measured by erythrocyte ω-3 index (20,21). Fatty acids concentration in red blood cells (RBC) represent a more reliable measurement of dietary habits compared to plasma measurements, considering that fatty acids are stable in RBC membranes for up to 3 months (corresponding to the lifespan of an erythrocyte) (22). RBC fatty acid concentrations have also been shown to reflect peripheral tissue concentrations and thus represents the best current clinical correlate of ω-3 status (23). Identifying older adults at risk of cognitive decline is important to enable timely treatment before AD pathology becomes irreversible; as such ω-3 PUFA might offer a potential well tolerated, inexpensive treatment in the early stages of AD, particularly in subjects with sub-optimal erythrocyte ω-3 levels. Furthermore, consumption of ω-3 PUFA (DHA and EPA) has been suggested to potentially benefit cardiovascular health, particularly hypertension. These beneficial effects have been explained by the capacity to prevent arrythmias, to improve vascular reactivity, to decrease atherosclerosis and inflammation and even more importantly, to decrease blood pressure levels (24-26). Moreover, hypertension has been associated with cognitive decline and incident dementia, both AD and vascular dementia, in several epidemiological studies (27-28). According to experimental animal studies, there is a plausible pathway by which hypertension and low dietary ω-3 intake may interact in increasing the risk of cognitive decline and dementia. In fact, hypertensive rats tended to have lower brain ω-3 PUFA than normotensive rats (29), possibly due to pressure-induced endothelial dysfunction at the blood-brain barrier or exhausted astrocytic metabolism. Oxidative stress which accompanies high blood pressure leads to increased peroxidation of unsaturated fatty acids and a reduction in their concentration in the brain represents an alternative explanation. Despite animal experimental evidence for a possible biological interaction between ω-3 PUFA and hypertensive status in affecting cognitive decline (29-32), only one research to date, conducted in the Atherosclerosis Risk in Communities (ARIC) Study, has attempted to test this hypothesis (33). Although no statistically significant interactions were found, the results suggested that hypertensive subjects may benefit in terms of cognition from supplementation in ω-3 to a larger extent than the normotensive group. Finally, previous studies reported that the presence of ApoE ε4 allele may modify the relationship between ω-3 PUFA and cognitive functioning. It has been hypothesized that the absorption and transportation of PUFA were probably different depending on the genotype (34). Some studies showed a greater benefit of fatty fish on dementia risk in patients without ApoE ε4 (35, 36). On the contrary, other findings reported slower rates of cognitive decline with PUFA from food in ApoE ε4 carriers (37). Thus, the potential role of ApoE ε4 status in the relationship between ω-3 PUFA and cognitive function warrants further research investigation. 2. HYPOTHESES 2.1. Main hypothesis We hypothesized that erythrocyte ω-3 index (used as both dichotomous variable and continuous variable) may be a predictor of cognitive decline in older adults, and that subjects exhibiting a low ω-3 index would undergo significantly more cognitive decline compared to those subjects exhibiting a higher ω-3 index. 2.2. Specific hypotheses 2.2.1. Analyses ready to be run • Cross-sectional (using baseline data from ADNI 3): participants with low ω-3 index (defined as those in the lowest quartile) would present lower cognitive function*, higher brain amyloid (measured by PET scan), lower hippocampal volume, higher white matter hyperintensities, higher tau accumulation. Also, we hypothesized that participants with AD would present lower ω-3 index (as a continuous variable), compared to MCI and cognitively normal, and that MCI would present lower ω-3 index, compared to cognitively normal subjects. We also hypothesized that participants with both low ω-3 index and hypertension would have worse cognitive outcomes: lower cognitive functions (especially lower executive functions), higher amyloid and tau accumulation, lower hippocampal volume and higher white matter hyperintensities, compared to participants with low ω-3 index but without hypertension. • Retrospective (using data from ADNI 1, ADNI 2 and baseline ADNI 3): participants with low ω-3 index would present previous over time decrease in cognitive function, increase in brain amyloid, decrease in hippocampal volume, increase in white matter hyperintensities and increase in tau accumulation compared to participants with normal ω-3 index. In addition, participants who developed MCI and AD over time would present lower ω-3 index (as a continuous variable), compared to subjects who remained cognitively normal. Similarly, participants with both low ω-3 index and hypertension would present greater previous over time decrease in cognitive function, amyloid and tau accumulation, decrease in hippocampal volume and increase in white matter hyperintensities compared to participants with low ω-3 index but without hypertension. 2.2.2. Future analyses (waiting for prospective data from ADNI 3) • Prospective (using baseline and future post-baseline data from ADNI 3): participants with low ω-3 index would present higher impairment in cognitive outcomes compared to participants with normal ω-3 index over time (lower cognitive function, higher hippocampal atrophy, higher deposit of brain amyloid, higher white matter hyperintensities and increased tau accumulation. In addition, more pronounced impairments would be observed among participants with MCI and AD, compared to cognitively normal subjects. Similarly, participants with both low ω-3 index and hypertension would develop worse cognitive outcomes (cognitive function, brain imaging, amyloid and tau accumulation) over time compared to participants with low ω-3 index but without hypertension. 3. OBJECTIVES 3.1. Overall aim We therefore aim to analyze the associations between baseline erythrocyte ω-3 index and cognitive outcomes (clinical tests, brain imaging, β-amyloid load, tau accumulation) among older adults, participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3). 3.2. Specific aims • To evaluate if the erythrocyte ω-3 index (as continuous variable) differs according to the cognitive status of participants (cognitively normal, MCI or AD). • To explore, cross-sectionally, if subjects with low ω-3 index would present higher brain amyloid β load (measured as standard uptake value ratio – SUVr), higher levels of hyper-phosphorylated tau, lower hippocampal volume and higher white matter hyperintensities, compared to participants with normal ω-3 index. • To explore if low ω-3 index would lead to increased brain Aβ load (measured as standard uptake value ratio – SUVr), increased levels of hyper-phosphorylated tau accumulation, higher hippocampal atrophy and higher white matter hyperintensities over time. • To investigate if the relationship between erythrocyte ω-3 index and cognitive outcomes differs according to the initial cognitive status of participants (cognitively normal, MCI or AD). • To evaluate if participants with pathological levels of brain amyloid (amyloid positive; SUVr ≥ 1.17) would present lower ω-3 index, compared to amyloid negative subjects. • To analyze the extent of AD related pathology associated with ω-3 index and cognitive decline, in the subsample of participants with AD. • To investigate the relationship between erythrocyte ω-3 index and retrospective cognitive outcomes. • To investigate whether the relationship between erythrocyte ω-3 index and cognitive outcomes (cognitive function, brain imaging, amyloid and Tau accumulation) differs according to the presence of hypertension status. • To investigate whether the presence of low erythrocyte ω-3 index and hypertension results in a predominantly “vascular” pattern of cognitive impairment (worse executive functions, greater white matter hyperintensities). • To determine how ApoE ε4 genotype can modify the relationship between erythrocyte ω-3 index and cognitive outcomes. 4. METHODS 4.1. Study population Participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3) (38) were adults aged 55 to 90 years with cognitively normal status (with or without subjective memory concerns), MCI (both early and late MCI) or AD. ADNI3 was registered in ClinicalTrials.gov under the protocol NCT02854033. All subjects were informed about the aims of this multi-center, non-randomized, natural history non-treatment study, and signed a consent form. 4.2. Isolation of erythrocytes and fatty acids measurement RBC collected at baseline were isolated from whole blood (5ml) collected into ethylenediamine tetraacetic acid (EDTA) tubes, according to the standardized procedures at ADNI sites (the ω-3 PUFA measurement is not affected by the presence of anti-coagulant). The blood was centrifuged at 2000 gravitational force (g) for 15 minutes at 4°C. This results in the formation of a RBC pellet an intermediate layer containing the leukocytes and platelets (buffy coat) and an upper phase comprising plasma. Following removal of the plasma and buffy coat, RBC was stored immediately at -80°C in EDTA tubes before shipment in batches on dry ice. After receipt of coded samples, fatty acids analysis will be performed in the Biochemistry Laboratory of Agrocampus-Ouest at Rennes by the team coordinated by Dr. Philippe Legrand. Lipids will be extracted from RBC samples (500 mg) with a mixture of hexane/isopropanol (3:2 v/v), after acidification with 1 mL HCl 3 M1. Margaric acid will be added as internal standard. Total lipid extracts will be saponified with 1 mL of 0.5 M NaOH in methanol for 30 min at 70 °C and methylated with 1 mL of BF3 for 15 min at 70°C. Fatty acid methyl esters (FAME) will be extracted twice with pentane and analyzed by GC using an Agilent Technologies 6890N gas chromatograph (Bios Analytic, L’union, France) with a split injector (260°C, 10:1, injection volume 2µL); a bonded silica capillary column (BPX 70, 60 m x 0.25 mm; 0.25 µm film thickness; SGE, Villeneuve-St Georges, France) and a flame ionization detector (260°C, air: 450 mL/min; hydrogen: 40 mL/min). Helium will be used as a carrier gas (constant flow: 1.5 mL/min, average velocity: 24 cm/s). The column temperature program will start at 150 °C, increase by 1.3 °C/min to 220 °C and be held at 220 °C for 10 min. Identification of FAME will be based on retention times obtained for FAME prepared from fatty acid standards. The area under the peaks will be determined using ChemStation software (Agilent) and results will be expressed as % of total fatty acids. DHA concentration will be calculated using the internal standard and expressed as µg/g for RBC samples. The ω-3 index will be calculated as the sum of %EPA and %DHA, and thus also expressed in % from total fatty acids. Low ω-3 index will be characterized by the lowest quartile within the population investigated in this study. 4.3. Outcomes In cognitively normal and MCI subjects, primary outcome will be the changes in cognition over 5 years as measured by a modified form of the Alzheimer Disease Cooperative Study Preclinical Alzheimer Cognitive Composite (ADCS-PACC) (39), where the total recall from the FCSRT will be substituted for the delayed word recall from the Alzheimer’s disease assessment scale cognitive subscale (ADAS-Cog) and the Digit Symbol Substitution Test (DSST) will be replaced by the Trail Making Test A (TMT-A). The modified composite will include: the delayed recall from the ADAS-cog, the delayed recall from the logical memory IIa subset from the Wechsler Memory Scale, the TMT-A and the MMSE total score. For subjects with AD, cognitive changes over 2 years will be measured by the ADAS-Cog. The different cognitive tests will also be examined separately, especially the Trail Making Test A (TMT-A) and the Montreal Cognitive Assessment MoCA to determine a potential vascular pattern of cognitive impairment (executive functions) in participants having low ω-3 index and hypertension. Secondary outcomes include changes in cognitive measures given by the Clinical Dementia Rating Sum of Boxes (CDR-SB), brain amyloid and hyper-phosphorylated paired helical filaments (PHF) tau (as measured by positron-emission tomography (PET) imaging), and changes in hippocampal volume and white matter hyperintensities assessed by magnetic resonance imaging (MRI). 4.4. Power calculations In MAPT Study, a mean difference of -0.295 in the change in composite cognitive score at year 3 was estimated between subjects with a low ω-3 index and superior ω-3 index receiving placebo with CDR=0. In ADNI, sample sizes of 400 cognitively normal, 400 MCI and 200 AD will be enrolled at baseline (minimal estimates of new + rollover recruits) with an expected drop-out rate of 40% at year 5 for the normal and MCI groups and 50% at year 2 for the AD group. Given these numbers, the smallest differences in cognition between ω-3 index subgroups that could be detected with 80% power considering a standard deviation of 0.57 estimated using MAPT data will be -0.169 at year 5 for analysis on normal and MCI together (120 subjects ≤Q1 and 360>Q1), -0.239 at year 5 for analysis on normal or MCI separately (60 subjects ≤Q1 and 180>Q1) and -0.372 at year 2 for AD subjects (25 subjects≤Q1 and 75>Q1) with a significance level of 0.05 (two-sided t-test). 4.5. Statistical analysis Baseline characteristics will be summarized as mean and standard deviation (SD) for continuous variables and as frequencies and percentages for categorical variables. In order to evaluate the cross-sectional relationship between the levels of baseline ω-3 index (1st quartile vs the others) and primary and secondary outcomes, t-tests for continuous variables with a Gaussian distribution or the non-parametric Kruskal-Wallis test for others quantitative variables will be performed, as also chi-squared tests for qualitative variables or Fisher’s exact test if there is an expected frequency <5. To test if the relationship between the ω-3 index and outcomes is different according to cognitive status groups (cognitively normal, MCI and AD) we will perform linear regressions with cognitive outcomes as the dependent variable and the ω-3 index, the cognitive status group and the interaction between these two parameters as the independent variables. To determine how APOE4 genotype can modify the relationship between omega 3 and cognitive outcomes, we will also test the statistical interaction and run analyses stratified on the presence of APOE4 genotype. Linear mixed models will be performed to study changes in cognitive performance (dependent variables: modified ADCS-PACC score among cognitively normal and MCI subjects at 5 years, and ADAS-Cog for AD subjects at 2 years) over time according to ω-3 index at baseline (independent variable) including all available data (baseline values and each time of follow-up). For each mixed model the following fixed effects will be included: ω-3 index group, time (as a continuous variable) and the interaction between the group and time. Subject-specific random effects will be included to take into account the intra-subject correlation; a random intercept to take into account the heterogeneity of the cognitive outcomes at baseline; and a random slope to take into account the heterogeneity of the slopes between subjects if this parameter is significant. Given the multicenter characteristic of the study, a center-specific random intercept can be introduced to take into account the intra-center correlation if this parameter is significant. All analyses for primary outcomes will be adjusted for potential confounders (age, sex, education, ApoE4 status, alcohol, smoking, BMI, cardiovascular risk factors, and brain amyloid and tau levels). Similar mixed models for secondary outcomes will be conducted to examine the relationship between ω-3 index at baseline and CDR-SB, brain amyloid, tau levels, hippocampal volume and white matter hyperintensities. To determine whether hypertension status can modify the relationship between erythrocyte ω-3 index and cognitive outcomes, we will test the statistical interaction and run analyses stratified on the presence and/or severity of hypertension. Analyses will be performed using the Statistical Analysis Software (SAS) version 9.4 (Cary, NC, USA), with a significance level established as 5%. References 1. Guixà-González, R. et al. Membrane omega-3 fatty acids modulate the oligomerisation kinetics of adenosine A2A and dopamine D2 receptors. Sci. Rep. 6, 19839 (2016). 2. McGahon, B. M., Martin, D. S., Horrobin, D. F. & Lynch, M. A. Age-related changes in synaptic function: analysis of the effect of dietary supplementation with omega-3 fatty acids. Neuroscience 94, 305–314 (1999). 3. Lin, Q., Ruuska, S. E., Shaw, N. S., Dong, D. & Noy, N. Ligand selectivity of the peroxisome proliferator-activated receptor alpha. Biochemistry (Mosc.) 38, 185–190 (1999). 4. Prasad, M. R., Lovell, M. A., Yatin, M., Dhillon, H. & Markesbery, W. R. Regional membrane phospholipid alterations in Alzheimer’s disease. Neurochem. Res. 23, 81–88 (1998). 5. Söderberg, M., Edlund, C., Kristensson, K. & Dallner, G. Fatty acid composition of brain phospholipids in aging and in Alzheimer’s disease. Lipids 26, 421–425 (1991). 6. McNamara, R. K., Liu, Y., Jandacek, R., Rider, T. & Tso, P. 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Effect of long-term omega 3 polyunsaturated fatty acid supplementation with or without multidomain intervention on cognitive function in elderly adults with memory complaints (MAPT): a randomised, placebo-controlled trial. Lancet Neurol. 16(5), 377-389 (2017). 21. Hooper C., De Souto Barreto P., Coley N., Cantet C., Cesari M., Andrieu S., Vellas B. Cognitive changes with omega-3 polyunsaturated fatty acids in non-demented older adults with low omega-3 index. J. Nutr. Health Aging (2017). 22. Arab, L. Biomarkers of fat and fatty acid intake. J. Nutr. 133 Suppl 3, 925S–932S (2003). 23. Harris, W. S. et al. Omega-3 fatty acids in cardiac biopsies from heart transplantation patients: correlation with erythrocytes and response to supplementation. Circulation 110, 1645–1649 (2004). 24. Hooijmans CR, Kiliaan AJ. Fatty acids, lipid metabolism and Alzheimer pathology. Eur J Pharmacol. 6 mai 2008;585(1):176‑96. 25. Colussi G, Catena C, Novello M, Bertin N, Sechi LA. 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Huang TL1, Zandi PP, Tucker KL, Fitzpatrick AL, Kuller LH, Fried LP, Burke GL, Carlson MC. Benefits of fatty fish on dementia risk are stronger for those without APOE epsilon4. Neurology. 2005 Nov 8;65(9):1409-14 36. Whalley LJ1, Deary IJ, Starr JM, Wahle KW, Rance KA, Bourne VJ, Fox HC. n-3 Fatty acid erythrocyte membrane content, APOE varepsilon4, and cognitive variation: an observational follow-up study in late adulthood. Am J Clin Nutr. 2008 Feb;87(2):449-54. 37. van de Rest O1, Wang Y2, Barnes LL2, Tangney C2, Bennett DA2, Morris MC2. APOE ε4 and the associations of seafood and long-chain omega-3 fatty acids with cognitive decline. Neurology. 2016 May 31;86(22):2063-70 38. Weiner, M.W., Veitch, D.P., Aisen, P.S., Beckett, L.A., Cairns, N.J., Green, R.C., Harvey, D., Jack, C.R. Jr, Jagust, W., Morris, J.C., Petersen, R.C., Salazar, J., Saykin, A.J., Shaw, L.M., Toga, A.W., Trojanowski, J.Q.; Alzheimer's Disease Neuroimaging Initiative. The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement. Alzheimers Dement.13(5), 561-571 (2017). 39 Donohue, M. C. et al. The preclinical Alzheimer cognitive composite: measuring amyloid-related decline. JAMA Neurol. 71, 961–970 (2014). |
| Investigator's Name: | Philipe De Souto Barreto |
| Proposed Analysis: | Proposal of research project: “Associations between erythrocyte omega-3 and cognitive outcomes in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3)” Developed by: Kelly Virecoulon Giudici, Sophie Guyonnet, Christelle Cantet, Laure Rouch, Philipe de Souto Barreto, Bruno Vellas (Institute of Aging, Gérontopôle, Toulouse University Hospital) 1. BACKGROUND Omega-3 (ω-3) polyunsaturated fatty acids (PUFA) have received significant research attention in relation to their beneficial effects on cognition, mainly docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA). DHA is the major fatty acid in neuronal membranes and is involved in multiple inter-related brain functions including cell membrane fluidity, signal transduction and neurotransmission (1-3). Cerebral DHA levels are known to be deficient specifically in brain regions associated with Alzheimer’s disease (AD) (4,5), and also to decrease in the brain in the process of normal human aging (6). Many observational studies have provided support for the therapeutic use of ω-3 in AD (7), and randomized controlled trials (RCT) have demonstrated a benefit of ω-3 supplementation in patients with mild cognitive impairment (MCI), particularly in terms of immediate recall, attention and processing speed (8). Potential benefic mechanisms of ω-3 PUFA involve the promotion of long term potentiation (LTP), a process related to functional plasticity, intimately related with learning and memory (9). There is also evidence suggesting that DHA confers neuro-protection in part through the direct inhibition of tau phosphorylation at the phospho-specific epitopes AT270, AT180 and Ser422 through mechanisms involving c-Jun N-terminal kinase (JNK) (10,11), or indirectly through the modulation of microglial activity and the suppression of neuroinflammation (12-14). Moreover, DHA and EPA have been shown to alter amyloid precursor protein (APP) processing, reducing amyloid-β peptide production (15-19). Based on this evidence, it is plausible that cognitive decline might also be influenced by ω-3 bio-status, which can be easily measured by erythrocyte ω-3 index (20,21). Fatty acids concentration in red blood cells (RBC) represent a more reliable measurement of dietary habits compared to plasma measurements, considering that fatty acids are stable in RBC membranes for up to 3 months (corresponding to the lifespan of an erythrocyte) (22). RBC fatty acid concentrations have also been shown to reflect peripheral tissue concentrations and thus represents the best current clinical correlate of ω-3 status (23). Identifying older adults at risk of cognitive decline is important to enable timely treatment before AD pathology becomes irreversible; as such ω-3 PUFA might offer a potential well tolerated, inexpensive treatment in the early stages of AD, particularly in subjects with sub-optimal erythrocyte ω-3 levels. Furthermore, consumption of ω-3 PUFA (DHA and EPA) has been suggested to potentially benefit cardiovascular health, particularly hypertension. These beneficial effects have been explained by the capacity to prevent arrythmias, to improve vascular reactivity, to decrease atherosclerosis and inflammation and even more importantly, to decrease blood pressure levels (24-26). Moreover, hypertension has been associated with cognitive decline and incident dementia, both AD and vascular dementia, in several epidemiological studies (27-28). According to experimental animal studies, there is a plausible pathway by which hypertension and low dietary ω-3 intake may interact in increasing the risk of cognitive decline and dementia. In fact, hypertensive rats tended to have lower brain ω-3 PUFA than normotensive rats (29), possibly due to pressure-induced endothelial dysfunction at the blood-brain barrier or exhausted astrocytic metabolism. Oxidative stress which accompanies high blood pressure leads to increased peroxidation of unsaturated fatty acids and a reduction in their concentration in the brain represents an alternative explanation. Despite animal experimental evidence for a possible biological interaction between ω-3 PUFA and hypertensive status in affecting cognitive decline (29-32), only one research to date, conducted in the Atherosclerosis Risk in Communities (ARIC) Study, has attempted to test this hypothesis (33). Although no statistically significant interactions were found, the results suggested that hypertensive subjects may benefit in terms of cognition from supplementation in ω-3 to a larger extent than the normotensive group. Finally, previous studies reported that the presence of ApoE ε4 allele may modify the relationship between ω-3 PUFA and cognitive functioning. It has been hypothesized that the absorption and transportation of PUFA were probably different depending on the genotype (34). Some studies showed a greater benefit of fatty fish on dementia risk in patients without ApoE ε4 (35, 36). On the contrary, other findings reported slower rates of cognitive decline with PUFA from food in ApoE ε4 carriers (37). Thus, the potential role of ApoE ε4 status in the relationship between ω-3 PUFA and cognitive function warrants further research investigation. 2. HYPOTHESES 2.1. Main hypothesis We hypothesized that erythrocyte ω-3 index (used as both dichotomous variable and continuous variable) may be a predictor of cognitive decline in older adults, and that subjects exhibiting a low ω-3 index would undergo significantly more cognitive decline compared to those subjects exhibiting a higher ω-3 index. 2.2. Specific hypotheses 2.2.1. Analyses ready to be run • Cross-sectional (using baseline data from ADNI 3): participants with low ω-3 index (defined as those in the lowest quartile) would present lower cognitive function*, higher brain amyloid (measured by PET scan), lower hippocampal volume, higher white matter hyperintensities, higher tau accumulation. Also, we hypothesized that participants with AD would present lower ω-3 index (as a continuous variable), compared to MCI and cognitively normal, and that MCI would present lower ω-3 index, compared to cognitively normal subjects. We also hypothesized that participants with both low ω-3 index and hypertension would have worse cognitive outcomes: lower cognitive functions (especially lower executive functions), higher amyloid and tau accumulation, lower hippocampal volume and higher white matter hyperintensities, compared to participants with low ω-3 index but without hypertension. • Retrospective (using data from ADNI 1, ADNI 2 and baseline ADNI 3): participants with low ω-3 index would present previous over time decrease in cognitive function, increase in brain amyloid, decrease in hippocampal volume, increase in white matter hyperintensities and increase in tau accumulation compared to participants with normal ω-3 index. In addition, participants who developed MCI and AD over time would present lower ω-3 index (as a continuous variable), compared to subjects who remained cognitively normal. Similarly, participants with both low ω-3 index and hypertension would present greater previous over time decrease in cognitive function, amyloid and tau accumulation, decrease in hippocampal volume and increase in white matter hyperintensities compared to participants with low ω-3 index but without hypertension. 2.2.2. Future analyses (waiting for prospective data from ADNI 3) • Prospective (using baseline and future post-baseline data from ADNI 3): participants with low ω-3 index would present higher impairment in cognitive outcomes compared to participants with normal ω-3 index over time (lower cognitive function, higher hippocampal atrophy, higher deposit of brain amyloid, higher white matter hyperintensities and increased tau accumulation. In addition, more pronounced impairments would be observed among participants with MCI and AD, compared to cognitively normal subjects. Similarly, participants with both low ω-3 index and hypertension would develop worse cognitive outcomes (cognitive function, brain imaging, amyloid and tau accumulation) over time compared to participants with low ω-3 index but without hypertension. 3. OBJECTIVES 3.1. Overall aim We therefore aim to analyze the associations between baseline erythrocyte ω-3 index and cognitive outcomes (clinical tests, brain imaging, β-amyloid load, tau accumulation) among older adults, participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3). 3.2. Specific aims • To evaluate if the erythrocyte ω-3 index (as continuous variable) differs according to the cognitive status of participants (cognitively normal, MCI or AD). • To explore, cross-sectionally, if subjects with low ω-3 index would present higher brain amyloid β load (measured as standard uptake value ratio – SUVr), higher levels of hyper-phosphorylated tau, lower hippocampal volume and higher white matter hyperintensities, compared to participants with normal ω-3 index. • To explore if low ω-3 index would lead to increased brain Aβ load (measured as standard uptake value ratio – SUVr), increased levels of hyper-phosphorylated tau accumulation, higher hippocampal atrophy and higher white matter hyperintensities over time. • To investigate if the relationship between erythrocyte ω-3 index and cognitive outcomes differs according to the initial cognitive status of participants (cognitively normal, MCI or AD). • To evaluate if participants with pathological levels of brain amyloid (amyloid positive; SUVr ≥ 1.17) would present lower ω-3 index, compared to amyloid negative subjects. • To analyze the extent of AD related pathology associated with ω-3 index and cognitive decline, in the subsample of participants with AD. • To investigate the relationship between erythrocyte ω-3 index and retrospective cognitive outcomes. • To investigate whether the relationship between erythrocyte ω-3 index and cognitive outcomes (cognitive function, brain imaging, amyloid and Tau accumulation) differs according to the presence of hypertension status. • To investigate whether the presence of low erythrocyte ω-3 index and hypertension results in a predominantly “vascular” pattern of cognitive impairment (worse executive functions, greater white matter hyperintensities). • To determine how ApoE ε4 genotype can modify the relationship between erythrocyte ω-3 index and cognitive outcomes. 4. METHODS 4.1. Study population Participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3) (38) were adults aged 55 to 90 years with cognitively normal status (with or without subjective memory concerns), MCI (both early and late MCI) or AD. ADNI3 was registered in ClinicalTrials.gov under the protocol NCT02854033. All subjects were informed about the aims of this multi-center, non-randomized, natural history non-treatment study, and signed a consent form. 4.2. Isolation of erythrocytes and fatty acids measurement RBC collected at baseline were isolated from whole blood (5ml) collected into ethylenediamine tetraacetic acid (EDTA) tubes, according to the standardized procedures at ADNI sites (the ω-3 PUFA measurement is not affected by the presence of anti-coagulant). The blood was centrifuged at 2000 gravitational force (g) for 15 minutes at 4°C. This results in the formation of a RBC pellet an intermediate layer containing the leukocytes and platelets (buffy coat) and an upper phase comprising plasma. Following removal of the plasma and buffy coat, RBC was stored immediately at -80°C in EDTA tubes before shipment in batches on dry ice. After receipt of coded samples, fatty acids analysis will be performed in the Biochemistry Laboratory of Agrocampus-Ouest at Rennes by the team coordinated by Dr. Philippe Legrand. Lipids will be extracted from RBC samples (500 mg) with a mixture of hexane/isopropanol (3:2 v/v), after acidification with 1 mL HCl 3 M1. Margaric acid will be added as internal standard. Total lipid extracts will be saponified with 1 mL of 0.5 M NaOH in methanol for 30 min at 70 °C and methylated with 1 mL of BF3 for 15 min at 70°C. Fatty acid methyl esters (FAME) will be extracted twice with pentane and analyzed by GC using an Agilent Technologies 6890N gas chromatograph (Bios Analytic, L’union, France) with a split injector (260°C, 10:1, injection volume 2µL); a bonded silica capillary column (BPX 70, 60 m x 0.25 mm; 0.25 µm film thickness; SGE, Villeneuve-St Georges, France) and a flame ionization detector (260°C, air: 450 mL/min; hydrogen: 40 mL/min). Helium will be used as a carrier gas (constant flow: 1.5 mL/min, average velocity: 24 cm/s). The column temperature program will start at 150 °C, increase by 1.3 °C/min to 220 °C and be held at 220 °C for 10 min. Identification of FAME will be based on retention times obtained for FAME prepared from fatty acid standards. The area under the peaks will be determined using ChemStation software (Agilent) and results will be expressed as % of total fatty acids. DHA concentration will be calculated using the internal standard and expressed as µg/g for RBC samples. The ω-3 index will be calculated as the sum of %EPA and %DHA, and thus also expressed in % from total fatty acids. Low ω-3 index will be characterized by the lowest quartile within the population investigated in this study. 4.3. Outcomes In cognitively normal and MCI subjects, primary outcome will be the changes in cognition over 5 years as measured by a modified form of the Alzheimer Disease Cooperative Study Preclinical Alzheimer Cognitive Composite (ADCS-PACC) (39), where the total recall from the FCSRT will be substituted for the delayed word recall from the Alzheimer’s disease assessment scale cognitive subscale (ADAS-Cog) and the Digit Symbol Substitution Test (DSST) will be replaced by the Trail Making Test A (TMT-A). The modified composite will include: the delayed recall from the ADAS-cog, the delayed recall from the logical memory IIa subset from the Wechsler Memory Scale, the TMT-A and the MMSE total score. For subjects with AD, cognitive changes over 2 years will be measured by the ADAS-Cog. The different cognitive tests will also be examined separately, especially the Trail Making Test A (TMT-A) and the Montreal Cognitive Assessment MoCA to determine a potential vascular pattern of cognitive impairment (executive functions) in participants having low ω-3 index and hypertension. Secondary outcomes include changes in cognitive measures given by the Clinical Dementia Rating Sum of Boxes (CDR-SB), brain amyloid and hyper-phosphorylated paired helical filaments (PHF) tau (as measured by positron-emission tomography (PET) imaging), and changes in hippocampal volume and white matter hyperintensities assessed by magnetic resonance imaging (MRI). 4.4. Power calculations In MAPT Study, a mean difference of -0.295 in the change in composite cognitive score at year 3 was estimated between subjects with a low ω-3 index and superior ω-3 index receiving placebo with CDR=0. In ADNI, sample sizes of 400 cognitively normal, 400 MCI and 200 AD will be enrolled at baseline (minimal estimates of new + rollover recruits) with an expected drop-out rate of 40% at year 5 for the normal and MCI groups and 50% at year 2 for the AD group. Given these numbers, the smallest differences in cognition between ω-3 index subgroups that could be detected with 80% power considering a standard deviation of 0.57 estimated using MAPT data will be -0.169 at year 5 for analysis on normal and MCI together (120 subjects ≤Q1 and 360>Q1), -0.239 at year 5 for analysis on normal or MCI separately (60 subjects ≤Q1 and 180>Q1) and -0.372 at year 2 for AD subjects (25 subjects≤Q1 and 75>Q1) with a significance level of 0.05 (two-sided t-test). 4.5. Statistical analysis Baseline characteristics will be summarized as mean and standard deviation (SD) for continuous variables and as frequencies and percentages for categorical variables. In order to evaluate the cross-sectional relationship between the levels of baseline ω-3 index (1st quartile vs the others) and primary and secondary outcomes, t-tests for continuous variables with a Gaussian distribution or the non-parametric Kruskal-Wallis test for others quantitative variables will be performed, as also chi-squared tests for qualitative variables or Fisher’s exact test if there is an expected frequency <5. To test if the relationship between the ω-3 index and outcomes is different according to cognitive status groups (cognitively normal, MCI and AD) we will perform linear regressions with cognitive outcomes as the dependent variable and the ω-3 index, the cognitive status group and the interaction between these two parameters as the independent variables. To determine how APOE4 genotype can modify the relationship between omega 3 and cognitive outcomes, we will also test the statistical interaction and run analyses stratified on the presence of APOE4 genotype. Linear mixed models will be performed to study changes in cognitive performance (dependent variables: modified ADCS-PACC score among cognitively normal and MCI subjects at 5 years, and ADAS-Cog for AD subjects at 2 years) over time according to ω-3 index at baseline (independent variable) including all available data (baseline values and each time of follow-up). For each mixed model the following fixed effects will be included: ω-3 index group, time (as a continuous variable) and the interaction between the group and time. Subject-specific random effects will be included to take into account the intra-subject correlation; a random intercept to take into account the heterogeneity of the cognitive outcomes at baseline; and a random slope to take into account the heterogeneity of the slopes between subjects if this parameter is significant. Given the multicenter characteristic of the study, a center-specific random intercept can be introduced to take into account the intra-center correlation if this parameter is significant. All analyses for primary outcomes will be adjusted for potential confounders (age, sex, education, ApoE4 status, alcohol, smoking, BMI, cardiovascular risk factors, and brain amyloid and tau levels). Similar mixed models for secondary outcomes will be conducted to examine the relationship between ω-3 index at baseline and CDR-SB, brain amyloid, tau levels, hippocampal volume and white matter hyperintensities. To determine whether hypertension status can modify the relationship between erythrocyte ω-3 index and cognitive outcomes, we will test the statistical interaction and run analyses stratified on the presence and/or severity of hypertension. Analyses will be performed using the Statistical Analysis Software (SAS) version 9.4 (Cary, NC, USA), with a significance level established as 5%. References 1. Guixà-González, R. et al. Membrane omega-3 fatty acids modulate the oligomerisation kinetics of adenosine A2A and dopamine D2 receptors. Sci. Rep. 6, 19839 (2016). 2. McGahon, B. M., Martin, D. S., Horrobin, D. F. & Lynch, M. A. Age-related changes in synaptic function: analysis of the effect of dietary supplementation with omega-3 fatty acids. Neuroscience 94, 305–314 (1999). 3. Lin, Q., Ruuska, S. E., Shaw, N. S., Dong, D. & Noy, N. Ligand selectivity of the peroxisome proliferator-activated receptor alpha. Biochemistry (Mosc.) 38, 185–190 (1999). 4. Prasad, M. R., Lovell, M. A., Yatin, M., Dhillon, H. & Markesbery, W. R. Regional membrane phospholipid alterations in Alzheimer’s disease. Neurochem. Res. 23, 81–88 (1998). 5. Söderberg, M., Edlund, C., Kristensson, K. & Dallner, G. Fatty acid composition of brain phospholipids in aging and in Alzheimer’s disease. Lipids 26, 421–425 (1991). 6. McNamara, R. K., Liu, Y., Jandacek, R., Rider, T. & Tso, P. The aging human orbitofrontal cortex: decreasing polyunsaturated fatty acid composition and associated increases in lipogenic gene expression and stearoyl-CoA desaturase activity. Prostaglandins Leukot. Essent. Fatty Acids 78, 293–304 (2008). 7. Cederholm, T., Salem, N. & Palmblad, J. ω-3 fatty acids in the prevention of cognitive decline in humans. Adv. Nutr. Bethesda Md 4, 672–676 (2013). 8. Mazereeuw, G., Lanctôt, K. L., Chau, S. A., Swardfager, W. & Herrmann, N. Effects of ω-3 fatty acids on cognitive performance: a meta-analysis. Neurobiol. Aging 33, 1482.e17-29 (2012). 9. Cutuli, D. Functional and Structural Benefits Induced by Omega-3 Polyunsaturated Fatty Acids During Aging. Curr Neuropharmacol. 5(4), 534-542 (2017). 10. Ma, Q.-L. et al. Beta-amyloid oligomers induce phosphorylation of tau and inactivation of insulin receptor substrate via c-Jun N-terminal kinase signaling: suppression by omega-3 fatty acids and curcumin. J. Neurosci. Off. J. Soc. Neurosci. 29, 9078–9089 (2009). 11. Green, K. N. et al. Dietary docosahexaenoic acid and docosapentaenoic acid ameliorate amyloid-beta and tau pathology via a mechanism involving presenilin 1 levels. J. Neurosci. Off. J. Soc. Neurosci. 27, 4385–4395 (2007). 12. Lee, D. C. et al. LPS- induced inflammation exacerbates phospho-tau pathology in rTg4510 mice. J. Neuroinflammation 7, 56 (2010). 13. Kitazawa, M., Oddo, S., Yamasaki, T. R., Green, K. N. & LaFerla, F. M. Lipopolysaccharide-induced inflammation exacerbates tau pathology by a cyclin-dependent kinase 5-mediated pathway in a transgenic model of Alzheimer’s disease. J. Neurosci. Off. J. Soc. Neurosci. 25, 8843–8853 (2005). 14. Hjorth, E. et al. Omega-3 fatty acids enhance phagocytosis of Alzheimer’s disease-related amyloid-β42 by human microglia and decrease inflammatory markers. J. Alzheimers Dis. JAD 35, 697–713 (2013). 15. Lukiw, W. J. et al. A role for docosahexaenoic acid–derived neuroprotectin D1 in neural cell survival and Alzheimer disease. J. Clin. Invest. 115, 2774–2783 (2005). 16. Grimm, M. O. W. et al. Docosahexaenoic acid reduces amyloid beta production via multiple pleiotropic mechanisms. J. Biol. Chem. 286, 14028–14039 (2011). 17. Perez, S. E. et al. DHA diet reduces AD pathology in young APPswe/PS1 Delta E9 transgenic mice: possible gender effects. J. Neurosci. Res. 88, 1026–1040 (2010). 18. Lim, G. P. et al. A diet enriched with the omega-3 fatty acid docosahexaenoic acid reduces amyloid burden in an aged Alzheimer mouse model. J. Neurosci. Off. J. Soc. Neurosci. 25, 3032–3040 (2005). 19. Yang, X., Sheng, W., Sun, G. Y. & Lee, J. C.-M. Effects of fatty acid unsaturation numbers on membrane fluidity and α-secretase-dependent amyloid precursor protein processing. Neurochem. Int. 58, 321–329 (2011). 20. Andrieu, S. et al. Effect of long-term omega 3 polyunsaturated fatty acid supplementation with or without multidomain intervention on cognitive function in elderly adults with memory complaints (MAPT): a randomised, placebo-controlled trial. Lancet Neurol. 16(5), 377-389 (2017). 21. Hooper C., De Souto Barreto P., Coley N., Cantet C., Cesari M., Andrieu S., Vellas B. Cognitive changes with omega-3 polyunsaturated fatty acids in non-demented older adults with low omega-3 index. J. Nutr. Health Aging (2017). 22. Arab, L. Biomarkers of fat and fatty acid intake. J. Nutr. 133 Suppl 3, 925S–932S (2003). 23. Harris, W. S. et al. Omega-3 fatty acids in cardiac biopsies from heart transplantation patients: correlation with erythrocytes and response to supplementation. Circulation 110, 1645–1649 (2004). 24. Hooijmans CR, Kiliaan AJ. Fatty acids, lipid metabolism and Alzheimer pathology. Eur J Pharmacol. 6 mai 2008;585(1):176‑96. 25. Colussi G, Catena C, Novello M, Bertin N, Sechi LA. Impact of omega-3 polyunsaturated fatty acids on vascular function and blood pressure: Relevance for cardiovascular outcomes. Nutr Metab Cardiovasc Dis NMCD. mars 2017;27(3):191‑200. 26. Miller PE, Van Elswyk M, Alexander DD. Long-chain omega-3 fatty acids eicosapentaenoic acid and docosahexaenoic acid and blood pressure: a meta-analysis of randomized controlled trials. Am J Hypertens. juill 2014;27(7):885‑96. 27. Hughes TM, Sink KM. Hypertension and Its Role in Cognitive Function: Current Evidence and Challenges for the Future. Am J Hypertens. févr 2016;29(2):149‑57. 28. Qiu C, Winblad B, Fratiglioni L. The age-dependent relation of blood pressure to cognitive function and dementia. Lancet Neurol. août 2005;4(8):487‑99. 29. de Wilde MC, Hogyes E, Kiliaan AJ, Farkas T, Luiten PGM, Farkas E. Dietary fatty acids alter blood pressure, behavior and brain membrane composition of hypertensive rats. Brain Res. 24 oct 2003;988(1‑2):9‑19. 30. Frenoux JM, Prost ED, Belleville JL, Prost JL. A polyunsaturated fatty acid diet lowers blood pressure and improves antioxidant status in spontaneously hypertensive rats. J Nutr. janv 2001;131(1):39‑45. 31. Bellenger-Germain S, Poisson JP, Narce M. Antihypertensive effects of a dietary unsaturated FA mixture in spontaneously hypertensive rats. Lipids. juin 2002;37(6):561‑7. 32. Engler MM, Engler MB, Pierson DM, Molteni LB, Molteni A. Effects of docosahexaenoic acid on vascular pathology and reactivity in hypertension. Exp Biol Med Maywood NJ. mars 2003;228(3):299‑307. 33. Beydoun MA, Kaufman JS, Sloane PD, Heiss G, Ibrahim J. n-3 Fatty acids, hypertension and risk of cognitive decline among older adults in the Atherosclerosis Risk in Communities (ARIC) study. Public Health Nutr. janv 2008;11(1):17‑29. 34. Barberger-Gateau P1, Raffaitin C, Letenneur L, Berr C, Tzourio C, Dartigues JF, Alpérovitch A. Dietary patterns and risk of dementia: the Three-City cohort study. Neurology. 2007 Nov 13;69(20):1921-30. 35. Huang TL1, Zandi PP, Tucker KL, Fitzpatrick AL, Kuller LH, Fried LP, Burke GL, Carlson MC. Benefits of fatty fish on dementia risk are stronger for those without APOE epsilon4. Neurology. 2005 Nov 8;65(9):1409-14 36. Whalley LJ1, Deary IJ, Starr JM, Wahle KW, Rance KA, Bourne VJ, Fox HC. n-3 Fatty acid erythrocyte membrane content, APOE varepsilon4, and cognitive variation: an observational follow-up study in late adulthood. Am J Clin Nutr. 2008 Feb;87(2):449-54. 37. van de Rest O1, Wang Y2, Barnes LL2, Tangney C2, Bennett DA2, Morris MC2. APOE ε4 and the associations of seafood and long-chain omega-3 fatty acids with cognitive decline. Neurology. 2016 May 31;86(22):2063-70 38. Weiner, M.W., Veitch, D.P., Aisen, P.S., Beckett, L.A., Cairns, N.J., Green, R.C., Harvey, D., Jack, C.R. Jr, Jagust, W., Morris, J.C., Petersen, R.C., Salazar, J., Saykin, A.J., Shaw, L.M., Toga, A.W., Trojanowski, J.Q.; Alzheimer's Disease Neuroimaging Initiative. The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement. Alzheimers Dement.13(5), 561-571 (2017). 39 Donohue, M. C. et al. The preclinical Alzheimer cognitive composite: measuring amyloid-related decline. JAMA Neurol. 71, 961–970 (2014). |
| Investigator's Name: | Bruno Vellas |
| Proposed Analysis: | Proposal of research project: “Associations between erythrocyte omega-3 and cognitive outcomes in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3)” Developed by: Kelly Virecoulon Giudici, Sophie Guyonnet, Christelle Cantet, Laure Rouch, Philipe de Souto Barreto, Bruno Vellas (Institute of Aging, Gérontopôle, Toulouse University Hospital) 1. BACKGROUND Omega-3 (ω-3) polyunsaturated fatty acids (PUFA) have received significant research attention in relation to their beneficial effects on cognition, mainly docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA). DHA is the major fatty acid in neuronal membranes and is involved in multiple inter-related brain functions including cell membrane fluidity, signal transduction and neurotransmission (1-3). Cerebral DHA levels are known to be deficient specifically in brain regions associated with Alzheimer’s disease (AD) (4,5), and also to decrease in the brain in the process of normal human aging (6). Many observational studies have provided support for the therapeutic use of ω-3 in AD (7), and randomized controlled trials (RCT) have demonstrated a benefit of ω-3 supplementation in patients with mild cognitive impairment (MCI), particularly in terms of immediate recall, attention and processing speed (8). Potential benefic mechanisms of ω-3 PUFA involve the promotion of long term potentiation (LTP), a process related to functional plasticity, intimately related with learning and memory (9). There is also evidence suggesting that DHA confers neuro-protection in part through the direct inhibition of tau phosphorylation at the phospho-specific epitopes AT270, AT180 and Ser422 through mechanisms involving c-Jun N-terminal kinase (JNK) (10,11), or indirectly through the modulation of microglial activity and the suppression of neuroinflammation (12-14). Moreover, DHA and EPA have been shown to alter amyloid precursor protein (APP) processing, reducing amyloid-β peptide production (15-19). Based on this evidence, it is plausible that cognitive decline might also be influenced by ω-3 bio-status, which can be easily measured by erythrocyte ω-3 index (20,21). Fatty acids concentration in red blood cells (RBC) represent a more reliable measurement of dietary habits compared to plasma measurements, considering that fatty acids are stable in RBC membranes for up to 3 months (corresponding to the lifespan of an erythrocyte) (22). RBC fatty acid concentrations have also been shown to reflect peripheral tissue concentrations and thus represents the best current clinical correlate of ω-3 status (23). Identifying older adults at risk of cognitive decline is important to enable timely treatment before AD pathology becomes irreversible; as such ω-3 PUFA might offer a potential well tolerated, inexpensive treatment in the early stages of AD, particularly in subjects with sub-optimal erythrocyte ω-3 levels. Furthermore, consumption of ω-3 PUFA (DHA and EPA) has been suggested to potentially benefit cardiovascular health, particularly hypertension. These beneficial effects have been explained by the capacity to prevent arrythmias, to improve vascular reactivity, to decrease atherosclerosis and inflammation and even more importantly, to decrease blood pressure levels (24-26). Moreover, hypertension has been associated with cognitive decline and incident dementia, both AD and vascular dementia, in several epidemiological studies (27-28). According to experimental animal studies, there is a plausible pathway by which hypertension and low dietary ω-3 intake may interact in increasing the risk of cognitive decline and dementia. In fact, hypertensive rats tended to have lower brain ω-3 PUFA than normotensive rats (29), possibly due to pressure-induced endothelial dysfunction at the blood-brain barrier or exhausted astrocytic metabolism. Oxidative stress which accompanies high blood pressure leads to increased peroxidation of unsaturated fatty acids and a reduction in their concentration in the brain represents an alternative explanation. Despite animal experimental evidence for a possible biological interaction between ω-3 PUFA and hypertensive status in affecting cognitive decline (29-32), only one research to date, conducted in the Atherosclerosis Risk in Communities (ARIC) Study, has attempted to test this hypothesis (33). Although no statistically significant interactions were found, the results suggested that hypertensive subjects may benefit in terms of cognition from supplementation in ω-3 to a larger extent than the normotensive group. Finally, previous studies reported that the presence of ApoE ε4 allele may modify the relationship between ω-3 PUFA and cognitive functioning. It has been hypothesized that the absorption and transportation of PUFA were probably different depending on the genotype (34). Some studies showed a greater benefit of fatty fish on dementia risk in patients without ApoE ε4 (35, 36). On the contrary, other findings reported slower rates of cognitive decline with PUFA from food in ApoE ε4 carriers (37). Thus, the potential role of ApoE ε4 status in the relationship between ω-3 PUFA and cognitive function warrants further research investigation. 2. HYPOTHESES 2.1. Main hypothesis We hypothesized that erythrocyte ω-3 index (used as both dichotomous variable and continuous variable) may be a predictor of cognitive decline in older adults, and that subjects exhibiting a low ω-3 index would undergo significantly more cognitive decline compared to those subjects exhibiting a higher ω-3 index. 2.2. Specific hypotheses 2.2.1. Analyses ready to be run • Cross-sectional (using baseline data from ADNI 3): participants with low ω-3 index (defined as those in the lowest quartile) would present lower cognitive function*, higher brain amyloid (measured by PET scan), lower hippocampal volume, higher white matter hyperintensities, higher tau accumulation. Also, we hypothesized that participants with AD would present lower ω-3 index (as a continuous variable), compared to MCI and cognitively normal, and that MCI would present lower ω-3 index, compared to cognitively normal subjects. We also hypothesized that participants with both low ω-3 index and hypertension would have worse cognitive outcomes: lower cognitive functions (especially lower executive functions), higher amyloid and tau accumulation, lower hippocampal volume and higher white matter hyperintensities, compared to participants with low ω-3 index but without hypertension. • Retrospective (using data from ADNI 1, ADNI 2 and baseline ADNI 3): participants with low ω-3 index would present previous over time decrease in cognitive function, increase in brain amyloid, decrease in hippocampal volume, increase in white matter hyperintensities and increase in tau accumulation compared to participants with normal ω-3 index. In addition, participants who developed MCI and AD over time would present lower ω-3 index (as a continuous variable), compared to subjects who remained cognitively normal. Similarly, participants with both low ω-3 index and hypertension would present greater previous over time decrease in cognitive function, amyloid and tau accumulation, decrease in hippocampal volume and increase in white matter hyperintensities compared to participants with low ω-3 index but without hypertension. 2.2.2. Future analyses (waiting for prospective data from ADNI 3) • Prospective (using baseline and future post-baseline data from ADNI 3): participants with low ω-3 index would present higher impairment in cognitive outcomes compared to participants with normal ω-3 index over time (lower cognitive function, higher hippocampal atrophy, higher deposit of brain amyloid, higher white matter hyperintensities and increased tau accumulation. In addition, more pronounced impairments would be observed among participants with MCI and AD, compared to cognitively normal subjects. Similarly, participants with both low ω-3 index and hypertension would develop worse cognitive outcomes (cognitive function, brain imaging, amyloid and tau accumulation) over time compared to participants with low ω-3 index but without hypertension. 3. OBJECTIVES 3.1. Overall aim We therefore aim to analyze the associations between baseline erythrocyte ω-3 index and cognitive outcomes (clinical tests, brain imaging, β-amyloid load, tau accumulation) among older adults, participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3). 3.2. Specific aims • To evaluate if the erythrocyte ω-3 index (as continuous variable) differs according to the cognitive status of participants (cognitively normal, MCI or AD). • To explore, cross-sectionally, if subjects with low ω-3 index would present higher brain amyloid β load (measured as standard uptake value ratio – SUVr), higher levels of hyper-phosphorylated tau, lower hippocampal volume and higher white matter hyperintensities, compared to participants with normal ω-3 index. • To explore if low ω-3 index would lead to increased brain Aβ load (measured as standard uptake value ratio – SUVr), increased levels of hyper-phosphorylated tau accumulation, higher hippocampal atrophy and higher white matter hyperintensities over time. • To investigate if the relationship between erythrocyte ω-3 index and cognitive outcomes differs according to the initial cognitive status of participants (cognitively normal, MCI or AD). • To evaluate if participants with pathological levels of brain amyloid (amyloid positive; SUVr ≥ 1.17) would present lower ω-3 index, compared to amyloid negative subjects. • To analyze the extent of AD related pathology associated with ω-3 index and cognitive decline, in the subsample of participants with AD. • To investigate the relationship between erythrocyte ω-3 index and retrospective cognitive outcomes. • To investigate whether the relationship between erythrocyte ω-3 index and cognitive outcomes (cognitive function, brain imaging, amyloid and Tau accumulation) differs according to the presence of hypertension status. • To investigate whether the presence of low erythrocyte ω-3 index and hypertension results in a predominantly “vascular” pattern of cognitive impairment (worse executive functions, greater white matter hyperintensities). • To determine how ApoE ε4 genotype can modify the relationship between erythrocyte ω-3 index and cognitive outcomes. 4. METHODS 4.1. Study population Participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3) (38) were adults aged 55 to 90 years with cognitively normal status (with or without subjective memory concerns), MCI (both early and late MCI) or AD. ADNI3 was registered in ClinicalTrials.gov under the protocol NCT02854033. All subjects were informed about the aims of this multi-center, non-randomized, natural history non-treatment study, and signed a consent form. 4.2. Isolation of erythrocytes and fatty acids measurement RBC collected at baseline were isolated from whole blood (5ml) collected into ethylenediamine tetraacetic acid (EDTA) tubes, according to the standardized procedures at ADNI sites (the ω-3 PUFA measurement is not affected by the presence of anti-coagulant). The blood was centrifuged at 2000 gravitational force (g) for 15 minutes at 4°C. This results in the formation of a RBC pellet an intermediate layer containing the leukocytes and platelets (buffy coat) and an upper phase comprising plasma. Following removal of the plasma and buffy coat, RBC was stored immediately at -80°C in EDTA tubes before shipment in batches on dry ice. After receipt of coded samples, fatty acids analysis will be performed in the Biochemistry Laboratory of Agrocampus-Ouest at Rennes by the team coordinated by Dr. Philippe Legrand. Lipids will be extracted from RBC samples (500 mg) with a mixture of hexane/isopropanol (3:2 v/v), after acidification with 1 mL HCl 3 M1. Margaric acid will be added as internal standard. Total lipid extracts will be saponified with 1 mL of 0.5 M NaOH in methanol for 30 min at 70 °C and methylated with 1 mL of BF3 for 15 min at 70°C. Fatty acid methyl esters (FAME) will be extracted twice with pentane and analyzed by GC using an Agilent Technologies 6890N gas chromatograph (Bios Analytic, L’union, France) with a split injector (260°C, 10:1, injection volume 2µL); a bonded silica capillary column (BPX 70, 60 m x 0.25 mm; 0.25 µm film thickness; SGE, Villeneuve-St Georges, France) and a flame ionization detector (260°C, air: 450 mL/min; hydrogen: 40 mL/min). Helium will be used as a carrier gas (constant flow: 1.5 mL/min, average velocity: 24 cm/s). The column temperature program will start at 150 °C, increase by 1.3 °C/min to 220 °C and be held at 220 °C for 10 min. Identification of FAME will be based on retention times obtained for FAME prepared from fatty acid standards. The area under the peaks will be determined using ChemStation software (Agilent) and results will be expressed as % of total fatty acids. DHA concentration will be calculated using the internal standard and expressed as µg/g for RBC samples. The ω-3 index will be calculated as the sum of %EPA and %DHA, and thus also expressed in % from total fatty acids. Low ω-3 index will be characterized by the lowest quartile within the population investigated in this study. 4.3. Outcomes In cognitively normal and MCI subjects, primary outcome will be the changes in cognition over 5 years as measured by a modified form of the Alzheimer Disease Cooperative Study Preclinical Alzheimer Cognitive Composite (ADCS-PACC) (39), where the total recall from the FCSRT will be substituted for the delayed word recall from the Alzheimer’s disease assessment scale cognitive subscale (ADAS-Cog) and the Digit Symbol Substitution Test (DSST) will be replaced by the Trail Making Test A (TMT-A). The modified composite will include: the delayed recall from the ADAS-cog, the delayed recall from the logical memory IIa subset from the Wechsler Memory Scale, the TMT-A and the MMSE total score. For subjects with AD, cognitive changes over 2 years will be measured by the ADAS-Cog. The different cognitive tests will also be examined separately, especially the Trail Making Test A (TMT-A) and the Montreal Cognitive Assessment MoCA to determine a potential vascular pattern of cognitive impairment (executive functions) in participants having low ω-3 index and hypertension. Secondary outcomes include changes in cognitive measures given by the Clinical Dementia Rating Sum of Boxes (CDR-SB), brain amyloid and hyper-phosphorylated paired helical filaments (PHF) tau (as measured by positron-emission tomography (PET) imaging), and changes in hippocampal volume and white matter hyperintensities assessed by magnetic resonance imaging (MRI). 4.4. Power calculations In MAPT Study, a mean difference of -0.295 in the change in composite cognitive score at year 3 was estimated between subjects with a low ω-3 index and superior ω-3 index receiving placebo with CDR=0. In ADNI, sample sizes of 400 cognitively normal, 400 MCI and 200 AD will be enrolled at baseline (minimal estimates of new + rollover recruits) with an expected drop-out rate of 40% at year 5 for the normal and MCI groups and 50% at year 2 for the AD group. Given these numbers, the smallest differences in cognition between ω-3 index subgroups that could be detected with 80% power considering a standard deviation of 0.57 estimated using MAPT data will be -0.169 at year 5 for analysis on normal and MCI together (120 subjects ≤Q1 and 360>Q1), -0.239 at year 5 for analysis on normal or MCI separately (60 subjects ≤Q1 and 180>Q1) and -0.372 at year 2 for AD subjects (25 subjects≤Q1 and 75>Q1) with a significance level of 0.05 (two-sided t-test). 4.5. Statistical analysis Baseline characteristics will be summarized as mean and standard deviation (SD) for continuous variables and as frequencies and percentages for categorical variables. In order to evaluate the cross-sectional relationship between the levels of baseline ω-3 index (1st quartile vs the others) and primary and secondary outcomes, t-tests for continuous variables with a Gaussian distribution or the non-parametric Kruskal-Wallis test for others quantitative variables will be performed, as also chi-squared tests for qualitative variables or Fisher’s exact test if there is an expected frequency <5. To test if the relationship between the ω-3 index and outcomes is different according to cognitive status groups (cognitively normal, MCI and AD) we will perform linear regressions with cognitive outcomes as the dependent variable and the ω-3 index, the cognitive status group and the interaction between these two parameters as the independent variables. To determine how APOE4 genotype can modify the relationship between omega 3 and cognitive outcomes, we will also test the statistical interaction and run analyses stratified on the presence of APOE4 genotype. Linear mixed models will be performed to study changes in cognitive performance (dependent variables: modified ADCS-PACC score among cognitively normal and MCI subjects at 5 years, and ADAS-Cog for AD subjects at 2 years) over time according to ω-3 index at baseline (independent variable) including all available data (baseline values and each time of follow-up). For each mixed model the following fixed effects will be included: ω-3 index group, time (as a continuous variable) and the interaction between the group and time. Subject-specific random effects will be included to take into account the intra-subject correlation; a random intercept to take into account the heterogeneity of the cognitive outcomes at baseline; and a random slope to take into account the heterogeneity of the slopes between subjects if this parameter is significant. Given the multicenter characteristic of the study, a center-specific random intercept can be introduced to take into account the intra-center correlation if this parameter is significant. All analyses for primary outcomes will be adjusted for potential confounders (age, sex, education, ApoE4 status, alcohol, smoking, BMI, cardiovascular risk factors, and brain amyloid and tau levels). Similar mixed models for secondary outcomes will be conducted to examine the relationship between ω-3 index at baseline and CDR-SB, brain amyloid, tau levels, hippocampal volume and white matter hyperintensities. To determine whether hypertension status can modify the relationship between erythrocyte ω-3 index and cognitive outcomes, we will test the statistical interaction and run analyses stratified on the presence and/or severity of hypertension. Analyses will be performed using the Statistical Analysis Software (SAS) version 9.4 (Cary, NC, USA), with a significance level established as 5%. References 1. Guixà-González, R. et al. Membrane omega-3 fatty acids modulate the oligomerisation kinetics of adenosine A2A and dopamine D2 receptors. Sci. Rep. 6, 19839 (2016). 2. McGahon, B. M., Martin, D. S., Horrobin, D. F. & Lynch, M. A. Age-related changes in synaptic function: analysis of the effect of dietary supplementation with omega-3 fatty acids. Neuroscience 94, 305–314 (1999). 3. Lin, Q., Ruuska, S. E., Shaw, N. S., Dong, D. & Noy, N. Ligand selectivity of the peroxisome proliferator-activated receptor alpha. Biochemistry (Mosc.) 38, 185–190 (1999). 4. Prasad, M. R., Lovell, M. A., Yatin, M., Dhillon, H. & Markesbery, W. R. Regional membrane phospholipid alterations in Alzheimer’s disease. Neurochem. Res. 23, 81–88 (1998). 5. Söderberg, M., Edlund, C., Kristensson, K. & Dallner, G. Fatty acid composition of brain phospholipids in aging and in Alzheimer’s disease. Lipids 26, 421–425 (1991). 6. McNamara, R. K., Liu, Y., Jandacek, R., Rider, T. & Tso, P. The aging human orbitofrontal cortex: decreasing polyunsaturated fatty acid composition and associated increases in lipogenic gene expression and stearoyl-CoA desaturase activity. Prostaglandins Leukot. Essent. Fatty Acids 78, 293–304 (2008). 7. Cederholm, T., Salem, N. & Palmblad, J. ω-3 fatty acids in the prevention of cognitive decline in humans. Adv. Nutr. Bethesda Md 4, 672–676 (2013). 8. Mazereeuw, G., Lanctôt, K. L., Chau, S. A., Swardfager, W. & Herrmann, N. Effects of ω-3 fatty acids on cognitive performance: a meta-analysis. Neurobiol. Aging 33, 1482.e17-29 (2012). 9. Cutuli, D. Functional and Structural Benefits Induced by Omega-3 Polyunsaturated Fatty Acids During Aging. Curr Neuropharmacol. 5(4), 534-542 (2017). 10. Ma, Q.-L. et al. Beta-amyloid oligomers induce phosphorylation of tau and inactivation of insulin receptor substrate via c-Jun N-terminal kinase signaling: suppression by omega-3 fatty acids and curcumin. J. Neurosci. Off. J. Soc. Neurosci. 29, 9078–9089 (2009). 11. Green, K. N. et al. Dietary docosahexaenoic acid and docosapentaenoic acid ameliorate amyloid-beta and tau pathology via a mechanism involving presenilin 1 levels. J. Neurosci. Off. J. Soc. Neurosci. 27, 4385–4395 (2007). 12. Lee, D. C. et al. LPS- induced inflammation exacerbates phospho-tau pathology in rTg4510 mice. J. Neuroinflammation 7, 56 (2010). 13. Kitazawa, M., Oddo, S., Yamasaki, T. R., Green, K. N. & LaFerla, F. M. Lipopolysaccharide-induced inflammation exacerbates tau pathology by a cyclin-dependent kinase 5-mediated pathway in a transgenic model of Alzheimer’s disease. J. Neurosci. Off. J. Soc. Neurosci. 25, 8843–8853 (2005). 14. Hjorth, E. et al. Omega-3 fatty acids enhance phagocytosis of Alzheimer’s disease-related amyloid-β42 by human microglia and decrease inflammatory markers. J. Alzheimers Dis. JAD 35, 697–713 (2013). 15. Lukiw, W. J. et al. A role for docosahexaenoic acid–derived neuroprotectin D1 in neural cell survival and Alzheimer disease. J. Clin. Invest. 115, 2774–2783 (2005). 16. Grimm, M. O. W. et al. Docosahexaenoic acid reduces amyloid beta production via multiple pleiotropic mechanisms. J. Biol. Chem. 286, 14028–14039 (2011). 17. Perez, S. E. et al. DHA diet reduces AD pathology in young APPswe/PS1 Delta E9 transgenic mice: possible gender effects. J. Neurosci. Res. 88, 1026–1040 (2010). 18. Lim, G. P. et al. A diet enriched with the omega-3 fatty acid docosahexaenoic acid reduces amyloid burden in an aged Alzheimer mouse model. J. Neurosci. Off. J. Soc. Neurosci. 25, 3032–3040 (2005). 19. Yang, X., Sheng, W., Sun, G. Y. & Lee, J. C.-M. Effects of fatty acid unsaturation numbers on membrane fluidity and α-secretase-dependent amyloid precursor protein processing. Neurochem. Int. 58, 321–329 (2011). 20. Andrieu, S. et al. Effect of long-term omega 3 polyunsaturated fatty acid supplementation with or without multidomain intervention on cognitive function in elderly adults with memory complaints (MAPT): a randomised, placebo-controlled trial. Lancet Neurol. 16(5), 377-389 (2017). 21. Hooper C., De Souto Barreto P., Coley N., Cantet C., Cesari M., Andrieu S., Vellas B. Cognitive changes with omega-3 polyunsaturated fatty acids in non-demented older adults with low omega-3 index. J. Nutr. Health Aging (2017). 22. Arab, L. Biomarkers of fat and fatty acid intake. J. Nutr. 133 Suppl 3, 925S–932S (2003). 23. Harris, W. S. et al. Omega-3 fatty acids in cardiac biopsies from heart transplantation patients: correlation with erythrocytes and response to supplementation. Circulation 110, 1645–1649 (2004). 24. Hooijmans CR, Kiliaan AJ. Fatty acids, lipid metabolism and Alzheimer pathology. Eur J Pharmacol. 6 mai 2008;585(1):176‑96. 25. Colussi G, Catena C, Novello M, Bertin N, Sechi LA. Impact of omega-3 polyunsaturated fatty acids on vascular function and blood pressure: Relevance for cardiovascular outcomes. Nutr Metab Cardiovasc Dis NMCD. mars 2017;27(3):191‑200. 26. Miller PE, Van Elswyk M, Alexander DD. Long-chain omega-3 fatty acids eicosapentaenoic acid and docosahexaenoic acid and blood pressure: a meta-analysis of randomized controlled trials. Am J Hypertens. juill 2014;27(7):885‑96. 27. Hughes TM, Sink KM. Hypertension and Its Role in Cognitive Function: Current Evidence and Challenges for the Future. Am J Hypertens. févr 2016;29(2):149‑57. 28. Qiu C, Winblad B, Fratiglioni L. The age-dependent relation of blood pressure to cognitive function and dementia. Lancet Neurol. août 2005;4(8):487‑99. 29. de Wilde MC, Hogyes E, Kiliaan AJ, Farkas T, Luiten PGM, Farkas E. Dietary fatty acids alter blood pressure, behavior and brain membrane composition of hypertensive rats. Brain Res. 24 oct 2003;988(1‑2):9‑19. 30. Frenoux JM, Prost ED, Belleville JL, Prost JL. A polyunsaturated fatty acid diet lowers blood pressure and improves antioxidant status in spontaneously hypertensive rats. J Nutr. janv 2001;131(1):39‑45. 31. Bellenger-Germain S, Poisson JP, Narce M. Antihypertensive effects of a dietary unsaturated FA mixture in spontaneously hypertensive rats. Lipids. juin 2002;37(6):561‑7. 32. Engler MM, Engler MB, Pierson DM, Molteni LB, Molteni A. Effects of docosahexaenoic acid on vascular pathology and reactivity in hypertension. Exp Biol Med Maywood NJ. mars 2003;228(3):299‑307. 33. Beydoun MA, Kaufman JS, Sloane PD, Heiss G, Ibrahim J. n-3 Fatty acids, hypertension and risk of cognitive decline among older adults in the Atherosclerosis Risk in Communities (ARIC) study. Public Health Nutr. janv 2008;11(1):17‑29. 34. Barberger-Gateau P1, Raffaitin C, Letenneur L, Berr C, Tzourio C, Dartigues JF, Alpérovitch A. Dietary patterns and risk of dementia: the Three-City cohort study. Neurology. 2007 Nov 13;69(20):1921-30. 35. Huang TL1, Zandi PP, Tucker KL, Fitzpatrick AL, Kuller LH, Fried LP, Burke GL, Carlson MC. Benefits of fatty fish on dementia risk are stronger for those without APOE epsilon4. Neurology. 2005 Nov 8;65(9):1409-14 36. Whalley LJ1, Deary IJ, Starr JM, Wahle KW, Rance KA, Bourne VJ, Fox HC. n-3 Fatty acid erythrocyte membrane content, APOE varepsilon4, and cognitive variation: an observational follow-up study in late adulthood. Am J Clin Nutr. 2008 Feb;87(2):449-54. 37. van de Rest O1, Wang Y2, Barnes LL2, Tangney C2, Bennett DA2, Morris MC2. APOE ε4 and the associations of seafood and long-chain omega-3 fatty acids with cognitive decline. Neurology. 2016 May 31;86(22):2063-70 38. Weiner, M.W., Veitch, D.P., Aisen, P.S., Beckett, L.A., Cairns, N.J., Green, R.C., Harvey, D., Jack, C.R. Jr, Jagust, W., Morris, J.C., Petersen, R.C., Salazar, J., Saykin, A.J., Shaw, L.M., Toga, A.W., Trojanowski, J.Q.; Alzheimer's Disease Neuroimaging Initiative. The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement. Alzheimers Dement.13(5), 561-571 (2017). 39 Donohue, M. C. et al. The preclinical Alzheimer cognitive composite: measuring amyloid-related decline. JAMA Neurol. 71, 961–970 (2014). |
| Investigator's Name: | Sophie Guyonnet |
| Proposed Analysis: | Proposal of research project: “Associations between erythrocyte omega-3 and cognitive outcomes in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3)” Developed by: Kelly Virecoulon Giudici, Sophie Guyonnet, Christelle Cantet, Laure Rouch, Philipe de Souto Barreto, Bruno Vellas (Institute of Aging, Gérontopôle, Toulouse University Hospital) 1. BACKGROUND Omega-3 (ω-3) polyunsaturated fatty acids (PUFA) have received significant research attention in relation to their beneficial effects on cognition, mainly docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA). DHA is the major fatty acid in neuronal membranes and is involved in multiple inter-related brain functions including cell membrane fluidity, signal transduction and neurotransmission (1-3). Cerebral DHA levels are known to be deficient specifically in brain regions associated with Alzheimer’s disease (AD) (4,5), and also to decrease in the brain in the process of normal human aging (6). Many observational studies have provided support for the therapeutic use of ω-3 in AD (7), and randomized controlled trials (RCT) have demonstrated a benefit of ω-3 supplementation in patients with mild cognitive impairment (MCI), particularly in terms of immediate recall, attention and processing speed (8). Potential benefic mechanisms of ω-3 PUFA involve the promotion of long term potentiation (LTP), a process related to functional plasticity, intimately related with learning and memory (9). There is also evidence suggesting that DHA confers neuro-protection in part through the direct inhibition of tau phosphorylation at the phospho-specific epitopes AT270, AT180 and Ser422 through mechanisms involving c-Jun N-terminal kinase (JNK) (10,11), or indirectly through the modulation of microglial activity and the suppression of neuroinflammation (12-14). Moreover, DHA and EPA have been shown to alter amyloid precursor protein (APP) processing, reducing amyloid-β peptide production (15-19). Based on this evidence, it is plausible that cognitive decline might also be influenced by ω-3 bio-status, which can be easily measured by erythrocyte ω-3 index (20,21). Fatty acids concentration in red blood cells (RBC) represent a more reliable measurement of dietary habits compared to plasma measurements, considering that fatty acids are stable in RBC membranes for up to 3 months (corresponding to the lifespan of an erythrocyte) (22). RBC fatty acid concentrations have also been shown to reflect peripheral tissue concentrations and thus represents the best current clinical correlate of ω-3 status (23). Identifying older adults at risk of cognitive decline is important to enable timely treatment before AD pathology becomes irreversible; as such ω-3 PUFA might offer a potential well tolerated, inexpensive treatment in the early stages of AD, particularly in subjects with sub-optimal erythrocyte ω-3 levels. Furthermore, consumption of ω-3 PUFA (DHA and EPA) has been suggested to potentially benefit cardiovascular health, particularly hypertension. These beneficial effects have been explained by the capacity to prevent arrythmias, to improve vascular reactivity, to decrease atherosclerosis and inflammation and even more importantly, to decrease blood pressure levels (24-26). Moreover, hypertension has been associated with cognitive decline and incident dementia, both AD and vascular dementia, in several epidemiological studies (27-28). According to experimental animal studies, there is a plausible pathway by which hypertension and low dietary ω-3 intake may interact in increasing the risk of cognitive decline and dementia. In fact, hypertensive rats tended to have lower brain ω-3 PUFA than normotensive rats (29), possibly due to pressure-induced endothelial dysfunction at the blood-brain barrier or exhausted astrocytic metabolism. Oxidative stress which accompanies high blood pressure leads to increased peroxidation of unsaturated fatty acids and a reduction in their concentration in the brain represents an alternative explanation. Despite animal experimental evidence for a possible biological interaction between ω-3 PUFA and hypertensive status in affecting cognitive decline (29-32), only one research to date, conducted in the Atherosclerosis Risk in Communities (ARIC) Study, has attempted to test this hypothesis (33). Although no statistically significant interactions were found, the results suggested that hypertensive subjects may benefit in terms of cognition from supplementation in ω-3 to a larger extent than the normotensive group. Finally, previous studies reported that the presence of ApoE ε4 allele may modify the relationship between ω-3 PUFA and cognitive functioning. It has been hypothesized that the absorption and transportation of PUFA were probably different depending on the genotype (34). Some studies showed a greater benefit of fatty fish on dementia risk in patients without ApoE ε4 (35, 36). On the contrary, other findings reported slower rates of cognitive decline with PUFA from food in ApoE ε4 carriers (37). Thus, the potential role of ApoE ε4 status in the relationship between ω-3 PUFA and cognitive function warrants further research investigation. 2. HYPOTHESES 2.1. Main hypothesis We hypothesized that erythrocyte ω-3 index (used as both dichotomous variable and continuous variable) may be a predictor of cognitive decline in older adults, and that subjects exhibiting a low ω-3 index would undergo significantly more cognitive decline compared to those subjects exhibiting a higher ω-3 index. 2.2. Specific hypotheses 2.2.1. Analyses ready to be run • Cross-sectional (using baseline data from ADNI 3): participants with low ω-3 index (defined as those in the lowest quartile) would present lower cognitive function*, higher brain amyloid (measured by PET scan), lower hippocampal volume, higher white matter hyperintensities, higher tau accumulation. Also, we hypothesized that participants with AD would present lower ω-3 index (as a continuous variable), compared to MCI and cognitively normal, and that MCI would present lower ω-3 index, compared to cognitively normal subjects. We also hypothesized that participants with both low ω-3 index and hypertension would have worse cognitive outcomes: lower cognitive functions (especially lower executive functions), higher amyloid and tau accumulation, lower hippocampal volume and higher white matter hyperintensities, compared to participants with low ω-3 index but without hypertension. • Retrospective (using data from ADNI 1, ADNI 2 and baseline ADNI 3): participants with low ω-3 index would present previous over time decrease in cognitive function, increase in brain amyloid, decrease in hippocampal volume, increase in white matter hyperintensities and increase in tau accumulation compared to participants with normal ω-3 index. In addition, participants who developed MCI and AD over time would present lower ω-3 index (as a continuous variable), compared to subjects who remained cognitively normal. Similarly, participants with both low ω-3 index and hypertension would present greater previous over time decrease in cognitive function, amyloid and tau accumulation, decrease in hippocampal volume and increase in white matter hyperintensities compared to participants with low ω-3 index but without hypertension. 2.2.2. Future analyses (waiting for prospective data from ADNI 3) • Prospective (using baseline and future post-baseline data from ADNI 3): participants with low ω-3 index would present higher impairment in cognitive outcomes compared to participants with normal ω-3 index over time (lower cognitive function, higher hippocampal atrophy, higher deposit of brain amyloid, higher white matter hyperintensities and increased tau accumulation. In addition, more pronounced impairments would be observed among participants with MCI and AD, compared to cognitively normal subjects. Similarly, participants with both low ω-3 index and hypertension would develop worse cognitive outcomes (cognitive function, brain imaging, amyloid and tau accumulation) over time compared to participants with low ω-3 index but without hypertension. 3. OBJECTIVES 3.1. Overall aim We therefore aim to analyze the associations between baseline erythrocyte ω-3 index and cognitive outcomes (clinical tests, brain imaging, β-amyloid load, tau accumulation) among older adults, participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3). 3.2. Specific aims • To evaluate if the erythrocyte ω-3 index (as continuous variable) differs according to the cognitive status of participants (cognitively normal, MCI or AD). • To explore, cross-sectionally, if subjects with low ω-3 index would present higher brain amyloid β load (measured as standard uptake value ratio – SUVr), higher levels of hyper-phosphorylated tau, lower hippocampal volume and higher white matter hyperintensities, compared to participants with normal ω-3 index. • To explore if low ω-3 index would lead to increased brain Aβ load (measured as standard uptake value ratio – SUVr), increased levels of hyper-phosphorylated tau accumulation, higher hippocampal atrophy and higher white matter hyperintensities over time. • To investigate if the relationship between erythrocyte ω-3 index and cognitive outcomes differs according to the initial cognitive status of participants (cognitively normal, MCI or AD). • To evaluate if participants with pathological levels of brain amyloid (amyloid positive; SUVr ≥ 1.17) would present lower ω-3 index, compared to amyloid negative subjects. • To analyze the extent of AD related pathology associated with ω-3 index and cognitive decline, in the subsample of participants with AD. • To investigate the relationship between erythrocyte ω-3 index and retrospective cognitive outcomes. • To investigate whether the relationship between erythrocyte ω-3 index and cognitive outcomes (cognitive function, brain imaging, amyloid and Tau accumulation) differs according to the presence of hypertension status. • To investigate whether the presence of low erythrocyte ω-3 index and hypertension results in a predominantly “vascular” pattern of cognitive impairment (worse executive functions, greater white matter hyperintensities). • To determine how ApoE ε4 genotype can modify the relationship between erythrocyte ω-3 index and cognitive outcomes. 4. METHODS 4.1. Study population Participants from the in the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI 3) (38) were adults aged 55 to 90 years with cognitively normal status (with or without subjective memory concerns), MCI (both early and late MCI) or AD. ADNI3 was registered in ClinicalTrials.gov under the protocol NCT02854033. All subjects were informed about the aims of this multi-center, non-randomized, natural history non-treatment study, and signed a consent form. 4.2. Isolation of erythrocytes and fatty acids measurement RBC collected at baseline were isolated from whole blood (5ml) collected into ethylenediamine tetraacetic acid (EDTA) tubes, according to the standardized procedures at ADNI sites (the ω-3 PUFA measurement is not affected by the presence of anti-coagulant). The blood was centrifuged at 2000 gravitational force (g) for 15 minutes at 4°C. This results in the formation of a RBC pellet an intermediate layer containing the leukocytes and platelets (buffy coat) and an upper phase comprising plasma. Following removal of the plasma and buffy coat, RBC was stored immediately at -80°C in EDTA tubes before shipment in batches on dry ice. After receipt of coded samples, fatty acids analysis will be performed in the Biochemistry Laboratory of Agrocampus-Ouest at Rennes by the team coordinated by Dr. Philippe Legrand. Lipids will be extracted from RBC samples (500 mg) with a mixture of hexane/isopropanol (3:2 v/v), after acidification with 1 mL HCl 3 M1. Margaric acid will be added as internal standard. Total lipid extracts will be saponified with 1 mL of 0.5 M NaOH in methanol for 30 min at 70 °C and methylated with 1 mL of BF3 for 15 min at 70°C. Fatty acid methyl esters (FAME) will be extracted twice with pentane and analyzed by GC using an Agilent Technologies 6890N gas chromatograph (Bios Analytic, L’union, France) with a split injector (260°C, 10:1, injection volume 2µL); a bonded silica capillary column (BPX 70, 60 m x 0.25 mm; 0.25 µm film thickness; SGE, Villeneuve-St Georges, France) and a flame ionization detector (260°C, air: 450 mL/min; hydrogen: 40 mL/min). Helium will be used as a carrier gas (constant flow: 1.5 mL/min, average velocity: 24 cm/s). The column temperature program will start at 150 °C, increase by 1.3 °C/min to 220 °C and be held at 220 °C for 10 min. Identification of FAME will be based on retention times obtained for FAME prepared from fatty acid standards. The area under the peaks will be determined using ChemStation software (Agilent) and results will be expressed as % of total fatty acids. DHA concentration will be calculated using the internal standard and expressed as µg/g for RBC samples. The ω-3 index will be calculated as the sum of %EPA and %DHA, and thus also expressed in % from total fatty acids. Low ω-3 index will be characterized by the lowest quartile within the population investigated in this study. 4.3. Outcomes In cognitively normal and MCI subjects, primary outcome will be the changes in cognition over 5 years as measured by a modified form of the Alzheimer Disease Cooperative Study Preclinical Alzheimer Cognitive Composite (ADCS-PACC) (39), where the total recall from the FCSRT will be substituted for the delayed word recall from the Alzheimer’s disease assessment scale cognitive subscale (ADAS-Cog) and the Digit Symbol Substitution Test (DSST) will be replaced by the Trail Making Test A (TMT-A). The modified composite will include: the delayed recall from the ADAS-cog, the delayed recall from the logical memory IIa subset from the Wechsler Memory Scale, the TMT-A and the MMSE total score. For subjects with AD, cognitive changes over 2 years will be measured by the ADAS-Cog. The different cognitive tests will also be examined separately, especially the Trail Making Test A (TMT-A) and the Montreal Cognitive Assessment MoCA to determine a potential vascular pattern of cognitive impairment (executive functions) in participants having low ω-3 index and hypertension. Secondary outcomes include changes in cognitive measures given by the Clinical Dementia Rating Sum of Boxes (CDR-SB), brain amyloid and hyper-phosphorylated paired helical filaments (PHF) tau (as measured by positron-emission tomography (PET) imaging), and changes in hippocampal volume and white matter hyperintensities assessed by magnetic resonance imaging (MRI). 4.4. Power calculations In MAPT Study, a mean difference of -0.295 in the change in composite cognitive score at year 3 was estimated between subjects with a low ω-3 index and superior ω-3 index receiving placebo with CDR=0. In ADNI, sample sizes of 400 cognitively normal, 400 MCI and 200 AD will be enrolled at baseline (minimal estimates of new + rollover recruits) with an expected drop-out rate of 40% at year 5 for the normal and MCI groups and 50% at year 2 for the AD group. Given these numbers, the smallest differences in cognition between ω-3 index subgroups that could be detected with 80% power considering a standard deviation of 0.57 estimated using MAPT data will be -0.169 at year 5 for analysis on normal and MCI together (120 subjects ≤Q1 and 360>Q1), -0.239 at year 5 for analysis on normal or MCI separately (60 subjects ≤Q1 and 180>Q1) and -0.372 at year 2 for AD subjects (25 subjects≤Q1 and 75>Q1) with a significance level of 0.05 (two-sided t-test). 4.5. Statistical analysis Baseline characteristics will be summarized as mean and standard deviation (SD) for continuous variables and as frequencies and percentages for categorical variables. In order to evaluate the cross-sectional relationship between the levels of baseline ω-3 index (1st quartile vs the others) and primary and secondary outcomes, t-tests for continuous variables with a Gaussian distribution or the non-parametric Kruskal-Wallis test for others quantitative variables will be performed, as also chi-squared tests for qualitative variables or Fisher’s exact test if there is an expected frequency <5. To test if the relationship between the ω-3 index and outcomes is different according to cognitive status groups (cognitively normal, MCI and AD) we will perform linear regressions with cognitive outcomes as the dependent variable and the ω-3 index, the cognitive status group and the interaction between these two parameters as the independent variables. To determine how APOE4 genotype can modify the relationship between omega 3 and cognitive outcomes, we will also test the statistical interaction and run analyses stratified on the presence of APOE4 genotype. Linear mixed models will be performed to study changes in cognitive performance (dependent variables: modified ADCS-PACC score among cognitively normal and MCI subjects at 5 years, and ADAS-Cog for AD subjects at 2 years) over time according to ω-3 index at baseline (independent variable) including all available data (baseline values and each time of follow-up). For each mixed model the following fixed effects will be included: ω-3 index group, time (as a continuous variable) and the interaction between the group and time. Subject-specific random effects will be included to take into account the intra-subject correlation; a random intercept to take into account the heterogeneity of the cognitive outcomes at baseline; and a random slope to take into account the heterogeneity of the slopes between subjects if this parameter is significant. Given the multicenter characteristic of the study, a center-specific random intercept can be introduced to take into account the intra-center correlation if this parameter is significant. All analyses for primary outcomes will be adjusted for potential confounders (age, sex, education, ApoE4 status, alcohol, smoking, BMI, cardiovascular risk factors, and brain amyloid and tau levels). Similar mixed models for secondary outcomes will be conducted to examine the relationship between ω-3 index at baseline and CDR-SB, brain amyloid, tau levels, hippocampal volume and white matter hyperintensities. To determine whether hypertension status can modify the relationship between erythrocyte ω-3 index and cognitive outcomes, we will test the statistical interaction and run analyses stratified on the presence and/or severity of hypertension. Analyses will be performed using the Statistical Analysis Software (SAS) version 9.4 (Cary, NC, USA), with a significance level established as 5%. 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A role for docosahexaenoic acid–derived neuroprotectin D1 in neural cell survival and Alzheimer disease. J. Clin. Invest. 115, 2774–2783 (2005). 16. Grimm, M. O. W. et al. Docosahexaenoic acid reduces amyloid beta production via multiple pleiotropic mechanisms. J. Biol. Chem. 286, 14028–14039 (2011). 17. Perez, S. E. et al. DHA diet reduces AD pathology in young APPswe/PS1 Delta E9 transgenic mice: possible gender effects. J. Neurosci. Res. 88, 1026–1040 (2010). 18. Lim, G. P. et al. A diet enriched with the omega-3 fatty acid docosahexaenoic acid reduces amyloid burden in an aged Alzheimer mouse model. J. Neurosci. Off. J. Soc. Neurosci. 25, 3032–3040 (2005). 19. Yang, X., Sheng, W., Sun, G. Y. & Lee, J. C.-M. Effects of fatty acid unsaturation numbers on membrane fluidity and α-secretase-dependent amyloid precursor protein processing. Neurochem. Int. 58, 321–329 (2011). 20. Andrieu, S. et al. Effect of long-term omega 3 polyunsaturated fatty acid supplementation with or without multidomain intervention on cognitive function in elderly adults with memory complaints (MAPT): a randomised, placebo-controlled trial. Lancet Neurol. 16(5), 377-389 (2017). 21. Hooper C., De Souto Barreto P., Coley N., Cantet C., Cesari M., Andrieu S., Vellas B. Cognitive changes with omega-3 polyunsaturated fatty acids in non-demented older adults with low omega-3 index. J. Nutr. Health Aging (2017). 22. Arab, L. Biomarkers of fat and fatty acid intake. J. Nutr. 133 Suppl 3, 925S–932S (2003). 23. Harris, W. S. et al. Omega-3 fatty acids in cardiac biopsies from heart transplantation patients: correlation with erythrocytes and response to supplementation. Circulation 110, 1645–1649 (2004). 24. Hooijmans CR, Kiliaan AJ. Fatty acids, lipid metabolism and Alzheimer pathology. Eur J Pharmacol. 6 mai 2008;585(1):176‑96. 25. Colussi G, Catena C, Novello M, Bertin N, Sechi LA. Impact of omega-3 polyunsaturated fatty acids on vascular function and blood pressure: Relevance for cardiovascular outcomes. Nutr Metab Cardiovasc Dis NMCD. mars 2017;27(3):191‑200. 26. Miller PE, Van Elswyk M, Alexander DD. Long-chain omega-3 fatty acids eicosapentaenoic acid and docosahexaenoic acid and blood pressure: a meta-analysis of randomized controlled trials. Am J Hypertens. juill 2014;27(7):885‑96. 27. Hughes TM, Sink KM. Hypertension and Its Role in Cognitive Function: Current Evidence and Challenges for the Future. Am J Hypertens. févr 2016;29(2):149‑57. 28. Qiu C, Winblad B, Fratiglioni L. The age-dependent relation of blood pressure to cognitive function and dementia. Lancet Neurol. août 2005;4(8):487‑99. 29. de Wilde MC, Hogyes E, Kiliaan AJ, Farkas T, Luiten PGM, Farkas E. Dietary fatty acids alter blood pressure, behavior and brain membrane composition of hypertensive rats. Brain Res. 24 oct 2003;988(1‑2):9‑19. 30. Frenoux JM, Prost ED, Belleville JL, Prost JL. 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