Emotion network dysfunction and anxiety in early Alzheimer's disease

PROJECT SUMMARY / ABSTRACT
Alzheimer's Disease (AD) is the most common neurodegenerative disorder and a major cause of dementia
among the elderly. Affective symptoms, especially anxiety, manifest during the early stages and may reflect cortico-
limbic circuit changes in AD. Notably, healthy aging is associated with a “positivity” effect in affect, including
reduction in anxiety, despite age-related cognitive decline. Thus, it is critical to understand how people with AD risks
deviate from healthy aging and manifest higher levels of anxiety and whether these neural phenotypes may predict
cognitive decline in those at risk. We propose to address these questions by investigating the roles of the cortico-
limbic circuit dysfunction in manifesting anxiety in people with mild cognitive impairment (MCI) and subjective
cognitive decline (SCD).
We will use resting-state functional magnetic resonance imaging (fMRI) data of healthy participants of the
HCP-A and both healthy participants and people with MCI of the ADNI (K99 studies) and collect task-based fMRI
data on negative emotion processing in people SCD and healthy participants along with follow-up assessments
(R00 study) to address three specific aims. Our two K99 aims are to (Aim 1) characterize the functional
connectivities of emotion regulation circuit during healthy aging and (Aim 2) characterize the functional
connectivities of emotion regulation circuit in MCI and employ machine learning to identify the connectivity markers
that distinguish AD and HC. The R00 aim is to (Aim 3) investigate corticolimbic circuit dysfunction in emotion
perception, regulation, and memory in SCD vs. HC using task-based fMRI and employ connectome predictive
modeling to identify the predictors of cognitive changes during follow-up. Our overall goal is to understand emotion
circuit dysfunction and the neural markers of anxiety and how these processes contribute to changes in cognitive
function in early AD.
The K99/R00 study will prepare the candidate for an independent career in aging and AD neuroscience
research. The proposed study will support this goal by providing additional training in systems and clinical
neuroscience, machine learning, and statistical modeling for the candidate. The candidate has identified her training
needs, assembled a team of expert mentors and formulated a training plan that includes structured mentoring,
supervised research, formal coursework, presentations at scientific meetings, and professional development. The
study will also allow the candidate to collect critical pilot data for an R01 proposal in career development. Together,
the K99/R00 study will allow the candidate to receive ample guidance, broaden her knowledge, learn novel
techniques, and gain independence, while pursuing a research program of critical importance to public health.

Grant Number: 1K99AG088064-01A1
NIH Institute/Center: NIH
Principal Investigator: Shefali Chaudhary