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: | Taps Maiti |
Institution: | Michigan State University |
Department: | Statistics and Probability |
Country: | |
Proposed Analysis: | Hidden behind the fMRI data, a Brain network describing the functional connectivity evolutes with time. The natural characteristic of high dimensional data intrigues our interest to build a spatial and temporal model. As we know, a precision matrix (reflects partial correlations between nodes) is a popular and accurate way to model the network. Therefore, a graphical model integrating with multilevels like dimension deduction off nodes and connectivity and transition of precision matrix would be considered. |
Additional Investigators | |
Investigator's Name: | Liangliang Zhang |
Proposed Analysis: | Background: The transition from mild cognitive impairment (MCI) to dementia is of great interest to clinical research on Alzheimer's disease and related dementias. This phenomenon also serves as a valuable data source for quantitative methodological researchers developing new approaches for classification. However, the growth of machine learning (ML) approaches for classification may falsely lead many clinical researchers to underestimate the value of logistic regression (LR), which often demonstrates classification accuracy equivalent or superior to other ML methods. Further, when faced with many potential features that could be used for classifying the transition, clinical researchers are often unaware of the relative value of different approaches for variable selection. Objective: The present study sought to compare different methods for statistical classification and for automated and theoretically guided feature selection techniques in the context of predicting conversion from MCI to dementia. Methods: We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to evaluate different influences of automated feature preselection on LR and support vector machine (SVM) classification methods, in classifying conversion from MCI to dementia. |
Investigator's Name: | Hossam Sarhan |
Proposed Analysis: | Type 2 diabetics (T2DM) have a 25-91% elevated risk of dementia in many cohorts. This research proposal addresses a critical knowledge gap in the identification of molecular factors that underlie the relationship between T2DM and future risk of mixed dementia. Triggering receptor expressed on myeloid cells 2 (TREM2) regulates microglial lipid metabolism and is a risk factor of AD. Animal models have noted a relationship between TREM2, plasma ceramides and insulin resistance. Ceramides are fatty acid-derived lipids involved in insulin resistance, cellular stress and inflammation. Our proposed research among humans builds on these studies to expand and establish among T2DM and preclinical AD subjects, if plasma levels of specific Ceramide species associate with TREM2 levels and is a significant factor mediating biomarker correlates of cognitive change. By delineation of the interaction between TREM2, ceramides, AD biomarkers, and measures of insulin resistance and cognitive decline. |
Investigator's Name: | Xinyi Wang |
Proposed Analysis: | Type 2 diabetics (T2DM) have a 25-91% elevated risk of dementia in many cohorts. This research proposal addresses a critical knowledge gap in the identification of molecular factors that underlie the relationship between T2DM and future risk of mixed dementia. Triggering receptor expressed on myeloid cells 2 (TREM2) regulates microglial lipid metabolism and is a risk factor of AD. Animal models have noted a relationship between TREM2, plasma ceramides and insulin resistance. Ceramides are fatty acid-derived lipids involved in insulin resistance, cellular stress and inflammation. Our proposed research among humans builds on these studies to expand and establish among T2DM and preclinical AD subjects, if plasma levels of specific Ceramide species associate with TREM2 levels and is a significant factor mediating biomarker correlates of cognitive change. By delineation of the interaction between TREM2, ceramides, AD biomarkers, and measures of insulin resistance and cognitive decline. |
Investigator's Name: | Yifan Wang |
Proposed Analysis: | Type 2 diabetics (T2DM) have a 25-91% elevated risk of dementia in many cohorts. This research proposal addresses a critical knowledge gap in the identification of molecular factors that underlie the relationship between T2DM and future risk of mixed dementia. Triggering receptor expressed on myeloid cells 2 (TREM2) regulates microglial lipid metabolism and is a risk factor of AD. Animal models have noted a relationship between TREM2, plasma ceramides and insulin resistance. Ceramides are fatty acid-derived lipids involved in insulin resistance, cellular stress and inflammation. Our proposed research among humans builds on these studies to expand and establish among T2DM and preclinical AD subjects, if plasma levels of specific Ceramide species associate with TREM2 levels and is a significant factor mediating biomarker correlates of cognitive change. By delineation of the interaction between TREM2, ceramides, AD biomarkers, and measures of insulin resistance and cognitive decline. |
Investigator's Name: | Hancheng Zheng |
Proposed Analysis: | Type 2 diabetics (T2DM) have a 25-91% elevated risk of dementia in many cohorts. This research proposal addresses a critical knowledge gap in the identification of molecular factors that underlie the relationship between T2DM and future risk of mixed dementia. Triggering receptor expressed on myeloid cells 2 (TREM2) regulates microglial lipid metabolism and is a risk factor of AD. Animal models have noted a relationship between TREM2, plasma ceramides and insulin resistance. Ceramides are fatty acid-derived lipids involved in insulin resistance, cellular stress and inflammation. Our proposed research among humans builds on these studies to expand and establish among T2DM and preclinical AD subjects, if plasma levels of specific Ceramide species associate with TREM2 levels and is a significant factor mediating biomarker correlates of cognitive change. By delineation of the interaction between TREM2, ceramides, AD biomarkers, and measures of insulin resistance and cognitive decline. |