Journal Club

Genome-wide meta-analysis of depression
identifies 102 independent variants and highlights the importance of the prefrontal brain regions

  • Howard et al., 2019

Introduction

  • Depression and Disability

    • Depression is the leading cause of worldwide disability.

    • Estimated 1 in 6 individuals will develop the disorder during their lifetime.

  • Heritability of Depression

    • Twin studies suggest a heritability estimate of approximately 30–40%.

    • Depression is a polygenic trait influenced by numerous genetic variants, each contributing a small effect.

  • Need for Large Samples

    • Challenges exist in obtaining detailed clinical diagnoses of major depressive disorder (MDD) in large cohorts due to time and expense.

Genetic Correlation Findings

  • Study by Howard et al.

    • Found a strong genetic correlation (rG = 0.86, s.e. = 0.05) between broader self-declared definitions of depression and clinically diagnosed MDD.

    • Indicates that analyzing larger samples with varied diagnosis approaches can offer significant insights.

Major Efforts in Identifying Genetic Variants

  • Mega-analyses

    • Included nine cohorts (total n = 18,759; 9,240 cases and 9,519 controls).

    • A meta-analysis of 17 cohorts (total n = 34,549) using a broader diagnostic scale identifies 102 independent variants.

Current Study Overview

  • Sample Size

    • Data meta-analyzed from 807,553 individuals (246,363 cases and 561,190 controls).

  • Identified Genetic Variants

    • 102 independent variants, 269 genes, and 15 gene sets identified.

    • Notably includes pathways associated with synaptic structure and neurotransmission.

  • Replication Sample

    • An independent replication sample comprising 1,306,354 individuals (414,055 cases and 892,299 controls) confirmed 87 of the 102 variants.

Methodological Approach

  • Mendelian Randomization Analysis

    • Utilized to explore potential causal relationships between depression and other traits.

  • Polygenic Risk Scores (PRS)

    • Explored the predictive ability of current findings in diagnosed MDD cohorts, with significant associations noted across three cohorts.

Genetic Results Summary

  • Independent Variants

    • Analysis conducted on 8,098,588 genetic variants resulted in 9,744 associated variants (P < 5 × 10^-8), of which 102 variants in 101 loci were independently segregating.

Genetic Correlation with Other Disorders

  • Assessment of Behavioral and Disease Traits

    • 41 traits were found to be significantly genetically correlated (PFDR < 0.01) with depression. Notable correlations include:

      • Schizophrenia (rG = 0.32, s.e. = 0.02)

      • Bipolar Disorder (rG = 0.33, s.e. = 0.03)

      • Body Fat (rG = 0.16, s.e. = 0.03)

  • Novel Genetic Correlations

    • Notable linkages observed with age at menopause (rG = -0.11, s.e. = 0.03).

Causal Relationships Insights

  • Two-sample Mendelian Randomization

    • Identified potential causal effects, notably linking depression to neuroticism.

  • Bidirectional Relationships

    • The study explored causal relationships in both directions across various traits.

Partitioning Heritability Component of Depression

  • SNP-Based Heritability Estimation

    • Calculated as 0.089 (s.e. = 0.003) using LDSC regression.

  • Significant Enrichment

    • Found in conserved, intronic, and H3K4me1 regions associated with depression.

Drug- Gene Interactions Analysis

  • Interaction Assessments

    • Identified 560 interactions between 57 genes associated with depression and 514 drugs, predominantly within the psycholeptic class.

Conclusions and Implications

  • Highlights the relevance of prefrontal brain regions in depression.

  • Additional insights into genetics open avenues for future treatments leveraging identified gene pathways.

  • Findings support continued research into defining distinct depression subtypes for targeted treatment approaches.