# Measuring Depression: Using biomarkers to investigate the biology of depression

> **NIH NIH F31** · VANDERBILT UNIVERSITY · 2021 · $30,776

## Abstract

Abstract
Depression is a leading cause of disability worldwide, affecting 1 in 6 individuals. Despite the global burden,
biology of depression remains poorly understood. Laboratory testing provides physicians with targeted
biochemical measurements, biomarkers, to aid in diagnosing and treating patients for a variety of diseases.
Biomarker results stored in electronic health records (EHRs) are a largely untapped resource for research.
Previous epidemiologic studies identified associations between depression status and various biomarkers,
most notably immune markers. However, the direction of association and underlying biology between
depression and the immune system has not been described. We hypothesize that integrating genetics of
depression with EHR-based biomarker and mediation data will help inform biological processes occurring in
depression. In previous analyses, we created a lab-wide association study (LabWAS) framework as a
hypothesis-generating approach to scan for associations between polygenic scores (PGS) and biomarkers
stored in EHRs. Our method allows for an investigation of biomarkers at an unprecedented scale with both the
number of individuals and the number of biomarkers included in the analyses, giving us the opportunity to
replicate previous biomarker associations as well as identify novel ones. We discovered an association
between depression PGS and an increased immune marker, white blood cell count (WBC) which replicated
across multiple biobanks. We plan to further investigate this relationship throughout the proposal. We plan to
investigate our hypothesis using two aims: Aim 1 will evaluate whether a phenotype or genetic factors
explains the association between depression genetics and WBC. Depression diagnosis is often comorbid
with other medical conditions that have known effects on WBC results. We will first conduct sensitivity analyses
by covarying for potentially confounding diagnoses in the analysis between depression PGS and WBC. We will
then perform conditional analyses to parse the direction of association and underlying genetic regions driving
the association. Aim 2 will characterize the role of depression genetics in moderating the relationships
between depression diagnosis and antidepressant usage with WBC. Antidepressant treatment with
antidepressants has previously been associated with changes in circulating biomarkers. By leveraging
medication information in EHRs, we plan to examine the effect of antidepressants on immune biomarker levels,
determine the moderating role of depression PGS, and determine if immune biomarker levels associate with
treatment response. Successful completion of this project would be the first to analyze the effect of depression
genetics on the landscape of biomarkers at scale, parse the direction of association and identify genetic
mediators between depression and the immune system, and investigate the effects of genetics on changes in
immune system from depression treatment. The futu...

## Key facts

- **NIH application ID:** 10313696
- **Project number:** 1F31MH124306-01A1
- **Recipient organization:** VANDERBILT UNIVERSITY
- **Principal Investigator:** Julia Sealock
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $30,776
- **Award type:** 1
- **Project period:** 2021-07-01 → 2022-05-13

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10313696

## Citation

> US National Institutes of Health, RePORTER application 10313696, Measuring Depression: Using biomarkers to investigate the biology of depression (1F31MH124306-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10313696. Licensed CC0.

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