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Donohue, M. C.

Publications and source records attributed to Donohue, M. C..

2 recordsLinked to original sources

Blood-based Transcriptomics Reveal Sex- and Amyloid-Modulated Biology of Plasma pTau217 in Preclinical Alzheimer's Disease

Plasma pTau217, an emerging Alzheimers disease (AD) biomarker, may reflect a synaptic response to {beta}-amyloid (A{beta}) plaques before cortical tangle formation, but its broader biological correlates remain unclear. We sought to identify associations between whole blood gene expression and plasma pTau217, and to determine whether APOE{varepsilon}4, sex, and neocortical A{beta}-PET modify these associations in 724 participants from the Anti-Amyloid Treatment in Asymptomatic Alzheimers and accompanying LEARN studies (A4/LEARN, Agemean(SD)=72.2(4.6); 63%female). Of 20,621 genes tested (1,048 X-linked), none were directly associated with pTau217; one gene was moderated by APOE{varepsilon}4, 1,540 genes by A{beta}-PET, and 772 genes by both A{beta}-PET and sex. Over 100 of these significant associations were X-linked, supporting a role of the X chromosome in AD. Sex interactions were only observed in the presence of elevated A{beta}-PET. Our results underscore the complexity of molecular mechanisms that can be linked to plasma pTau217, particularly in the context of elevated A{beta}-PET.

neuroscience↗

Bayesian Multivariate Growth Mixture Modeling of Longitudinal Data: An Application to Alzheimer's Disease Study

Alzheimers disease (AD) studies often collect longitudinal biomarker measures of multiple cohorts at different stages of disease and follow these biomarkers with a relatively short period of time. The heterogeneity of the longitudinal patterns of biomarkers can be ubiquitous across both individual trajectories and cognitive domains. We propose a flexible Bayesian multivariate growth mixture model to identify distinct longitudinal patterns of data from the Alzheimers Disease Neuroimaging Initiative (ADNI) study. A Gibbs sampling is implemented for achieving the Bayesian inference. We perform a simulation study to demonstrate the adequate performance of our proposed approach and apply the model to identify three latent cognitive decline patterns among patients from the ADNI study.

neuroscience↗