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: | David Verbel |
| Institution: | Eisai Medical Research |
| Department: | Biostatistics |
| Country: | |
| Proposed Analysis: | Review and summary of ADNI database (collected to date). |
| Additional Investigators | |
| Investigator's Name: | Junro Kuromitsu |
| Proposed Analysis: | Exploring ADNI data to identify potential targets and biomarkers for AD drug development. |
| Investigator's Name: | Junichi Ito |
| Proposed Analysis: | Exploring ADNI data to identify potential targets and biomarkers for AD drug development. |
| Investigator's Name: | Ken Aoshima |
| Proposed Analysis: | Ad biomarker analysis |
| Investigator's Name: | Hiroki Terauchi |
| Proposed Analysis: | Deep learning for image analysis |
| Investigator's Name: | Michio Kanekiyo |
| Proposed Analysis: | Compare US-ADNI with J-ADNI |
| Investigator's Name: | Amir Abbas Tahami Monfared |
| Proposed Analysis: | Clinical meaningfulness of cognitive endpoints (including ADAS-Cog and CDR-SB) and correlation of disease progression and staging of AD. |
| Investigator's Name: | Feifei Tao |
| Proposed Analysis: | Use large-scale genotype and phenotype data to analyze genetic association in Alzheimer’s disease. The focus here is on identifying novel genetic associations as well as further characterizing known associations. |
| Investigator's Name: | Kentaro Takahashi |
| Proposed Analysis: | Finding AD drug target gene by all biomarker QTL analysis |
| Investigator's Name: | Makoto Hamaguchi |
| Proposed Analysis: | Perform data mining of the ADNI data. |
| Investigator's Name: | Kenichi Anabuki |
| Proposed Analysis: | Perform data mining of the ADNI data. |
| Investigator's Name: | Ryo Dairiki |
| Proposed Analysis: | Exploratory analysis of ADNI data |
| Investigator's Name: | Senthilkumar Karuppiah |
| Proposed Analysis: | Compare progression of clinical outcomes to that seen in other cohorts. |
| Investigator's Name: | Pallavi Sachdev |
| Proposed Analysis: | Evaluate longitudinal ADNI datasets to gain further insights on the temporal natural progression of biomarkers of AD |
| Investigator's Name: | Roy Ronen |
| Proposed Analysis: | Evaluate longitudinal ADNI datasets to gain further insights on the temporal natural progression of biomarkers of AD |
| Investigator's Name: | Karol Nienaltowski |
| Proposed Analysis: | Evaluate longitudinal ADNI datasets to gain further insights on the temporal natural progression of biomarkers of AD |
| Investigator's Name: | Janusz Dutkowski |
| Proposed Analysis: | Evaluate longitudinal ADNI datasets to gain further insights on the temporal natural progression of biomarkers of AD |
| Investigator's Name: | Xin Qi |
| Proposed Analysis: | Setup an internal pipeline to use MRI and fMRI images to extract image features and to integrate with clinical factors and other features to build some ML/DL classification/prediction models for drug response |
| Investigator's Name: | Takatoshi Kawai |
| Proposed Analysis: | Analysis of genetic and biochemical biomarkers in ADNI cohort |
| Investigator's Name: | Tomoki Aota |
| Proposed Analysis: | Identification of SNPs associated with AD progression in ADNI cohort |
| Investigator's Name: | Yoshitaka Nakamura |
| Proposed Analysis: | 1) To analyze relationship among CSF/PET/blood biomarkers, neurocognitive testing, and MCI/AD; and 2) To create prediction model of progression of MCI/AD. |
| Investigator's Name: | Todd Nelson |
| Proposed Analysis: | 1) To quantify regional volumes, surface area and other imaging parameters from MRI images; and 2) to identify which clinical and imaging parameters are associated with AD diagnosis and progression. |
| Investigator's Name: | Taylor Gosselin |
| Proposed Analysis: | To develop and evaluate tools for generating super-resolved T1-weighted (T1w) MRI images in order to characterize changes within the basal forebrain (BF) region in Alzheimer’s disease (AD) |
| Investigator's Name: | Leema Krishna Murali |
| Proposed Analysis: | Use LONI data to build machine learning models for assisting in patient selection, disease progression and therapy prediction for Alzheimer's disease |
| Investigator's Name: | Momoka Tsuneyoshi |
| Proposed Analysis: | To create the prediction model of disease progression in MCI / AD using CSF, imaging and blood biomarkers, and Neuropsychological-tests data, etc. |
| Investigator's Name: | Prateek Soanker |
| Proposed Analysis: | Analysis of baseline and change from baseline variables and their relationship to endpoints across a variety of domains supporting a variety of internal programs. |
| Investigator's Name: | Susan De Santi |
| Proposed Analysis: | To explore the relationship between biomarkers (PET, MRI, fMRI, CSF and blood) and cognitive measures of decline and progression |
| Investigator's Name: | Gang Li |
| Proposed Analysis: | To explore the relationship between biomarkers (PET, MRI, fMRI, CSF and blood) and cognitive measures of decline and progression |
| Investigator's Name: | Arnaud Charil |
| Proposed Analysis: | Investigate the relationships between MRI/PET imaging and other biomarkers/cognition; disease progression modelling and subtyping for disease understanding |
| Investigator's Name: | Chizuru Kobayashi |
| Proposed Analysis: | To create the prediction model of disease progression in MCI / AD using CSF, imaging and blood biomarkers, and Neuropsychological-tests data, etc. |
| Investigator's Name: | Kotaro Sasaki |
| Proposed Analysis: | To create the prediction model of disease progression in MCI / AD using CSF, imaging and blood biomarkers, and Neuropsychological-tests data, etc. |
| Investigator's Name: | Emiko Segawa |
| Proposed Analysis: | To create the prediction model of disease progression in MCI / AD using CSF, imaging and blood biomarkers, and Neuropsychological-tests data, etc. |
| Investigator's Name: | Emiko Yamauchi |
| Proposed Analysis: | Explore involvement of abnormality of authentic orexin level and its metabolism against sleep-disorders often observed in AD, and to explore feasibility of measured hypothalamus volume as a surrogate marker of low level of authentic orexin and orexin neuron abnormality-related symptom |
| Investigator's Name: | Misato Kaishima |
| Proposed Analysis: | Analysis of WGS data and biomarkers to find drug targets for AD |
| Investigator's Name: | Brian Willis |
| Proposed Analysis: | Use imaging and cognition data to explore various methods of developing disease progression models, linking imaging changes (and potentially other covariates) with changes in clinical outcomes |
| Investigator's Name: | Han Yin |
| Proposed Analysis: | Biomarker identification and predictive modeling |
| Investigator's Name: | Michael Nagle |
| Proposed Analysis: | Exploring ADNI data to identify potential targets and biomarkers for AD drug development. |
| Investigator's Name: | Pei Li |
| Proposed Analysis: | Analysis of baseline and change from baseline variables and their relationship to endpoints across a variety of domains supporting a variety of internal programs. |
| Investigator's Name: | Xiaoyan Wang |
| Proposed Analysis: | Analysis of baseline and change from baseline variables and their relationship to endpoints across a variety of domains supporting a variety of internal programs. |
| Investigator's Name: | Sibabrata Banerjee |
| Proposed Analysis: | Analysis of baseline and change from baseline variables and their relationship to endpoints across a variety of domains supporting a variety of internal programs. |
| Investigator's Name: | Bin Shi |
| Proposed Analysis: | Analysis of baseline and change from baseline variables and their relationship to endpoints across a variety of domains supporting a variety of internal programs. |
| Investigator's Name: | David Li |
| Proposed Analysis: | Analysis of baseline and change from baseline variables and their relationship to endpoints across a variety of domains supporting a variety of internal programs. |
| Investigator's Name: | John Williams |
| Proposed Analysis: | Use large-scale genotype and phenotype data to analyze genetic association in Alzheimer’s disease. The focus here is on identifying novel genetic associations as well as further characterizing known associations. |
| Investigator's Name: | Viswanath Devanarayan |
| Proposed Analysis: | Use LONI data to build machine learning models for assisting in patient selection, disease progression and therapy prediction for Alzheimer's disease |
| Investigator's Name: | Youfang Cao |
| Proposed Analysis: | Using ADNI dataset to develop quantitative systems pharmacology (QSP) models to help understand the disease progression of Alzheimer's disease and effect of treatment. |
| Investigator's Name: | Hiroshi Tsugawa |
| Proposed Analysis: | 1. Plasma Untargeted metabolomics data published in ADNI will be used to determine the Hydrophilic metabolomics profile of patients with dementia. 2. Untargeted metabolomics contains raw data, which will be analyzed by MS-DIAL4 developed by Dr. Tsugawa. Containing Batch-to-batch correction using internal standards and Drugs are removed and only pure metabolites are extracted by structural information database in MS-DIAL4. 3. We will create the prediction model of disease progression in MCI/ AD using lipid profile and hydrophilic metabolomic profile. |
| Investigator's Name: | Takaki Oka |
| Proposed Analysis: | 1. Plasma Untargeted metabolomics data published in ADNI will be used to determine the Hydrophilic metabolomics profile of patients with dementia. 2. Untargeted metabolomics contains raw data, which will be analyzed by MS-DIAL4 developed by Dr. Tsugawa. Containing Batch-to-batch correction using internal standards and Drugs are removed and only pure metabolites are extracted by structural information database in MS-DIAL4. 3. We will create the prediction model of disease progression in MCI/ AD using lipid profile and hydrophilic metabolomic profile. |
| Investigator's Name: | Anthonin Reilhac-Laborde |
| Proposed Analysis: | Investigate the relationships between MRI/PET imaging and other biomarkers/cognition; disease progression modeling and subtyping for disease understanding |
| Investigator's Name: | Kenichi Saito |
| Proposed Analysis: | To create the prediction model of disease progression in MCI / AD using CSF, imaging and blood biomarkers, and Neuropsychological-tests data, etc. |
| Investigator's Name: | Kohei Ishikawa |
| Proposed Analysis: | To create the prediction model of disease progression in MCI / AD using CSF, imaging and blood biomarkers, and Neuropsychological-tests data, etc. |
| Investigator's Name: | Ippei Suzuki |
| Proposed Analysis: | To create the prediction model of disease progression in MCI / AD using CSF, imaging and blood biomarkers, and Neuropsychological-tests data, etc. |
| Investigator's Name: | Takuma Sato |
| Proposed Analysis: | To create the prediction model of disease progression in MCI / AD using CSF, imaging and blood biomarkers, and Neuropsychological-tests data, etc. |
| Investigator's Name: | Yuji Miura |
| Proposed Analysis: | To create the prediction model of disease progression in MCI / AD using CSF, imaging and blood biomarkers, and Neuropsychological-tests data, etc. |
| Investigator's Name: | Keishi Akada |
| Proposed Analysis: | To create the prediction model of disease progression in MCI / AD using CSF, imaging and blood biomarkers, and Neuropsychological-tests data, etc. |
