# Multi-modal intersection of depression and genetic liability to Alzheimers disease

> **NIH NIH K99** · YALE UNIVERSITY · 2023 · $99,884

## Abstract

ABSTRACT
Depressive symptoms are present in up to 40% of individuals with Alzheimer’s disease (AD) and an ongoing
debate regarding whether they represent a risk factor or a prodromal sign of AD. Chronic conditions such as
depression impact the stress response and may accelerate biological aging further contributing to susceptibility
to age-related conditions specifically cognitive decline. However, genetics of psychiatric traits and AD have been
mostly studied separately.
 This proposal aims to identify coding and non-coding regulatory variants associated with shared genetic
risk for depression and AD in multiple cohorts: UK biobank, Million Veteran Program, Alzheimer’s Disease
Sequencing Project, National Health and Resilience in Veterans Study, and Yale-Penn study, and replicate
findings in PsycheMERGE, cumulatively studying more than 1 million individuals. We will assess two major risk
factors of AD - APOE-ε4 carrier status (Model-1) and parental history of AD (Model-2) with depression. Our
previous findings from the genetically regulated expression study of depression in 1.2 million individuals using
hippocampus-based expression quantitative trait loci (QTL) identified several genes which have roles in AD
pathology (e.g. PARK2, NEGR1, HSPA1A, ITPR3, NLGN1, and DRD2). Therefore, we hypothesize that
stratifying depression with AD phenotypes will uncover overlapping genetic contributions between depression
and AD and elucidate the shared molecular mechanisms, and potential therapeutic targets.
 To test theses hypotheses, this proposal aims to develop a multi-modal framework to study
neuropsychiatric comorbidities by investigating, Aim-1) whole exome profiles for coding regions associated with
depression and genetic risk for AD (K99 phase), Aim-2) transcriptomic profiles to identify a shared molecular
basis for depression and AD risk by integrating large-scale GWAS with brain tissue-based molecular QTL studies
(R00 phase), and Aim-3) epigenome profiles to identify methylation sites associated with a combined polygenic
score of depression and AD, and compare biological aging between depression and AD comorbidity, and either
disorder alone (R00 phase).
 The accompanying training includes didactic courses in i) data analysis from multiple high throughput
technologies, ii) developing biomarkers from large-scale datasets, iii) computational programming and iv)
gerontological studies. The professional development training will include writing workshops, building mentoring
portfolio, training opportunities to establish laboratory as an independent researcher. This training plan was
developed under advisory team comprised of five members who are experts in AD, psychiatry, aging, large-scale
genomics, and cohorts with electronic health records. Together they provide guidance on the proposed study
and support a multidisciplinary neuropsychiatric research career for the candidate.

## Key facts

- **NIH application ID:** 10697330
- **Project number:** 5K99AG078503-02
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Gita A Pathak
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $99,884
- **Award type:** 5
- **Project period:** 2022-09-15 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10697330

## Citation

> US National Institutes of Health, RePORTER application 10697330, Multi-modal intersection of depression and genetic liability to Alzheimers disease (5K99AG078503-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10697330. Licensed CC0.

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