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: | Svetlana Oukraintseva |
| Institution: | Duke University |
| Department: | SSRI |
| Country: | |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. |
| Additional Investigators | |
| Investigator's Name: | Deqing Wu |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. |
| Investigator's Name: | Mikhail Kovtun |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. |
| Investigator's Name: | Anatoliy Yashin |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. |
| Investigator's Name: | Matt Duan |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. |
| Investigator's Name: | Olivia Bagley |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. |
| Investigator's Name: | Igor Akushevich |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. |
| Investigator's Name: | Arseniy Yashkin |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. |
| Investigator's Name: | Konstantin Arbeev |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. |
| Investigator's Name: | Galina Gorbunova |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. |
| Investigator's Name: | Stanislav Kolpakov Nikitin |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and ADrelated traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. |
| Investigator's Name: | Vladimir Popov |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. UPDATED (2020-07-15) :We will also investigate common regulatory and rare functional variants involved in both aging and AD. We will leverage the whole exome sequencing data to find the functional variants associated with aging and AD. We will place additional focuses on evaluating joint effects of genetic interactions using recently developed in our group Interaction Polygenic Risk Score (IPRS), and on genetic regulators of translation, such as MicroRNAs. |
| Investigator's Name: | Rachel Holmes |
| Proposed Analysis: | This project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal brain aging and AD. For this, we will identify sets of genetic variants that can protect against both the decline in brain resilience and the increase in AD risk with age, by conducting the secondary analyses of genetic and phenotypic data collected in several human studies, including ADNI, and will further validate the findings (candidate genetic targets) using preclinical biomarkers of AD pathology available in ADNI data. Specific Aims: (1) Select pleiotropic genetic variants associated with both aging- and AD-related traits, and evaluate their combined influence on AD risk and survival. (2) Evaluate joint effects of candidate genes from the selected aging-related pathways on AD risk and survival. (3) Preclinically validate the findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. For this, we will estimate joint effects of the genetic variants that influenced AD risk and/or survival in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI data, such as hippocampal volume and CSF and metabolic biomarkers, considering other covariates (gender, race, education, smoking). We will also explore the causal relationships between genetic factors found in Aims 1 and 2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD, and help find new genetic targets for AD personalized prevention. UPDATED (2020-07-15) :We will also investigate common regulatory and rare functional variants involved in both aging and AD. We will leverage the whole exome sequencing data to find the functional variants associated with aging and AD. We will place additional focuses on evaluating joint effects of genetic interactions using recently developed in our group Interaction Polygenic Risk Score (IPRS), and on genetic regulators of translation, such as MicroRNAs. UPDATED (2020-08-11) :*Proposed analyses are part of two projects with IRB numbers: Pro00105166 and Pro00105389 |
| Investigator's Name: | Aravind Lathika Rajendrakumar |
| Proposed Analysis: | The research activities described in the Proposed Analysis are part of the three projects with the IRB numbers Pro00105166, Pro00105389, and Pro00109279. The Pro00105166 project objective is to significantly improve our understanding of the heterogeneity of Alzheimer's disease (AD) and the shared genetic mechanisms between normal aging and AD. For this, we will identify sets of genetic variants that may be protective against declining brain resilience and raising AD risk with age, by conducting secondary analyses of genetic and phenotypic data collected in several human studies, including in ADNI, and will further validate the candidate genetic targets, using preclinical biomarkers of AD pathology available in ADNI and other data. Specific Aims: (1) Select genetic variants associated with both aging- and AD-related traits, and evaluate their joint influence on AD risk and survival. (2) Evaluate effects of candidate genes from aging-related pathways on AD risk and survival. (3) Preclinically validate findings from Aims 1 and 2, and further explore mechanisms of the observed genetic associations. We will estimate effects of genetic variants selected in Aims 1 and 2 - on preclinical biomarkers of AD pathology in ADNI and other data. We will also explore causal relationships between genetic variants selected in Aims 1,2, and AD, using Mendelian Randomization and related approaches. Results of this project will contribute to a better understanding of the heterogeneous and shared genetic mechanisms of aging and AD. In Pro00105389, we'll investigate regulatory and functional variants involved in both aging and AD. We'll leverage the whole exome sequencing data to find the functional variants associated with aging and AD. We will place additional focus on evaluating joint effects of genetic interactions using recently developed in our group Interaction Polygenic Risk Score (IPRS), and on genetic regulators of translation. The Pro00109279 focuses on mechanisms connecting Alzheimer's disease and infections. We will estimate associations between candidate genes involved in response to infections and AD traits. We will also evaluate associations between infection-related health events in Medical History of ADNI participants and AD traits, taking into account genetic risk factors that may modify such associations. This new co-investigator is covered by all three IRB protocols: Pro00105166, Pro00105389, and Pro00109279. |
