Multi-Omics Characterization of Early- and Adult-Onset Major Depressive Disorder.

Caroline W Grant,Madhukar H Trivedi,Paul E Croarkin,Taryn Mayes,Arjun P Athreya,Joanna Biernacka,Michelle Skime,Thomas Carmody,Erin F Barreto,Rakesh Kumar,William V Bobo,Liewei Wang,Rima Kaddurah-Daouk,Richard Weinshilboum

doi:10.3390/jpm12030412

Abstract

Age at depressive onset (AAO) corresponds to unique symptomatology and clinical outcomes. Integration of genome-wide association study (GWAS) results with additional “omic” measures to evaluate AAO has not been reported and may reveal novel markers of susceptibility and/or resistance to major depressive disorder (MDD). To address this gap, we integrated genomics with metabolomics using data-driven network analysis to characterize and differentiate MDD based on AAO. This study first performed two GWAS for AAO as a continuous trait in (a) 486 adults from the Pharmacogenomic Research Network-Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS), and (b) 295 adults from the Combining Medications to Enhance Depression Outcomes (CO-MED) study. Variants from top signals were integrated with 153 p180-assayed metabolites to establish multi-omics network characterizations of early (<age 18) and adult-onset depression. The most significant variant (p = 8.77 × 10−8) localized to an intron of SAMD3. In silico functional annotation of top signals (p < 1 × 10−5) demonstrated gene expression enrichment in the brain and during embryonic development. Network analysis identified differential associations between four variants (in/near INTU, FAT1, CNTN6, and TM9SF2) and plasma metabolites (phosphatidylcholines, carnitines, biogenic amines, and amino acids) in early- compared with adult-onset MDD. Multi-omics integration identified differential biosignatures of early- and adult-onset MDD. These biosignatures call for future studies to follow participants from childhood through adulthood and collect repeated -omics and neuroimaging measures to validate and deeply characterize the biomarkers of susceptibility and/or resistance to MDD development.

Highlights

Major depressive disorder (MDD) etiology and prognosis vary by the age at depressive onset
Several genome-wide association studies (GWAS) and one exome-wide association study have been performed to understand the genomics of MDD specific to age at onset [8,12–15]
Two GWAS investigating the age at depressive onset (N = 2746 [14]) and (N = 9238 [13]) did not identify overlapping top signals (p < 1 × 10−5), highlighting phenotypic heterogeneity that may require additional biological measures to understand

Summary

Introduction

Major depressive disorder (MDD) etiology and prognosis vary by the age at depressive onset. Onset is characterized by poorer quality of life, greater psychiatric and medical comorbidity, higher heritability, and increased suicidality [1–5]. This suggests that individuals with early-onset MDD may benefit from a tailored pharmacologic treatment approach [6–10]. No integrative genomic and metabolomic approaches have been undertaken to identify multi-omics signatures which best characterize and differentiate patients with early- and late-onset depression. Such an analysis may yield insights into heritable (genomic) and downstream (metabolomic) differences between age groups

Objectives

Methods

Results