Cross-ancestry genome-wide association study and systems-level integrative analyses implicate new risk genes and therapeutic targets for depression
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Genome-wide analysis identifies novel shared loci between depression and white matter microstructure
Depression, a complex and heritable psychiatric disorder, is associated with alterations in white matter microstructure, yet their shared genetic basis remains largely unclear. Utilizing the largest available genome-wide association study (GWAS) datasets for depression (N = 674,452) and white matter microstructure (N = 33,224), assessed through diffusion tensor imaging metrics such as fractional anisotropy (FA) and mean diffusivity (MD), we employed linkage disequilibrium score regression method to estimate global genetic correlations, local analysis of [co]variant association approach to pinpoint genomic regions with local genetic correlations, and conjunctional false discovery rate analysis to identify shared variants. Our findings revealed that depression showed significant local genetic correlations with FA in 37 genomic regions and with MD in 59 regions, while global genetic correlations were weak. Variant-level analysis identified 78 distinct loci jointly associated with depression (25 novel loci) and FA (35 novel loci), and 41 distinct loci associated with depression (17 novel loci) and MD (25 novel loci). Further analyses showed that these shared loci exhibited both concordant and discordant effect directions between depression and white matter traits, as well as distinct yet overlapping hemispheric patterns in their genetic architecture. Enrichment analysis of these shared loci implicated biological processes related to metabolism and regulation. This study provides evidence of a mixed-direction shared genetic architecture between depression and white matter microstructure. The identification of specific loci and pathways offers potential insights for developing targeted interventions to improve white matter integrity and alleviate depressive symptoms.
Depression symptom-specific genetic associations in clinically diagnosed and proxy case Alzheimer’s disease
Depression is a risk factor for the later development of Alzheimer’s disease (AD), but evidence for the genetic relationship is mixed. Assessing depression symptom-specific genetic associations may better clarify this relationship. To address this, we conducted genome-wide meta-analysis (a genome-wide association study, GWAS) of the nine depression symptom items, plus their sum score, on the Patient Health Questionnaire (PHQ-9) (GWAS-equivalent N: 224,535–308,421) using data from UK Biobank, the GLAD study and PROTECT, identifying 37 genomic risk loci. Using six AD GWASs with varying proportions of clinical and proxy (family history) case ascertainment, we identified 20 significant genetic correlations with depression/depression symptoms. However, only one of these was identified with a clinical AD GWAS. Local genetic correlations were detected in 14 regions. No statistical colocalization was identified in these regions. However, the region of the transmembrane protein 106B gene (TMEM106B) showed colocalization between multiple depression phenotypes and both clinical-only and clinical + proxy AD. Mendelian randomization and polygenic risk score analyses did not yield significant results after multiple testing correction in either direction. Our findings do not demonstrate a causal role of depression/depression symptoms on AD and suggest that previous evidence of genetic overlap between depression and AD may be driven by the inclusion of family history-based proxy cases/controls. However, colocalization at TMEM106B warrants further investigation.
Comparative analysis of the Mexico City Prospective Study and the UK Biobank identifies ancestry-specific effects on clonal hematopoiesis
The impact of genetic ancestry on the development of clonal hematopoiesis (CH) remains largely unexplored. Here, we compared CH in 136,401 participants from the Mexico City Prospective Study (MCPS) to 416,118 individuals from the UK Biobank (UKB) and observed CH to be significantly less common in MCPS compared to UKB (adjusted odds ratio = 0.59, 95% confidence interval (CI) = [0.57, 0.61], P = 7.31 × 10−185). Among MCPS participants, CH frequency was positively correlated with the percentage of European ancestry (adjusted beta = 0.84, 95% CI = [0.66, 1.03], P = 7.35 × 10−19). Genome-wide and exome-wide association analyses in MCPS identified ancestry-specific variants in the TCL1B locus with opposing effects on DNMT3A-CH versus non-DNMT3A-CH. Meta-analysis of MCPS and UKB identified five novel loci associated with CH, including polymorphisms at PARP11/CCND2, MEIS1 and MYCN. Our CH study, the largest in a non-European population to date, demonstrates the power of cross-ancestry comparisons to derive novel insights into CH pathogenesis.
Not all who integrate are academics: zooming in on extra-academic integrative expertise
Solving complex problems requires integrating knowledge and skills from various domains. The importance of cross-domain integration has motivated researchers to study integrative expertise: what knowledge and skills help achieve cross-domain integration? Much of the existing research focuses on the integrative expertise of academic researchers who perform inter- and transdisciplinary research. However, academics are not the only ones facilitating integration. In transdisciplinary research, where academics collaborate with professionals, stakeholders, and policymakers, these extra-academic actors can contribute significantly to cross-domain integration. Moreover, many complex problems are addressed entirely outside of universities. This paper contributes to a broader, more inclusive understanding of integrative expertise by drawing attention to the diversity of extra-academic integrative expertise, providing examples of what this expertise looks like in practice, and reflecting on differences with its academic counterpart. The contributions are based on a case study of integrative expertise in Oosterweel Link, a large urban development project in Antwerp, Belgium.
Group arts interventions for depression and anxiety among older adults: a systematic review and meta-analysis
In this systematic review and meta-analysis, we assessed the efficacy of group arts interventions, where individuals engage together in a shared artistic experience (for example, dance or painting), for reducing depression and anxiety among older adults (> 55 yr without dementia). Fifty controlled studies were identified via electronic databases searched to February 2024 (randomised: 42, non-randomised: 8). Thirty-nine studies were included. Thirty-six studies investigated the impact of group arts interventions on depression (n = 3,360) and ten studies investigated anxiety (n = 949). Subgroup analyses assessed whether participant, contextual, intervention and study characteristics moderated the intervention–outcome relationship. Risk of bias was assessed with appropriate tools (RoB-2, ROBINS-1). Group arts interventions were associated with a moderate reduction in depression (Cohen’s d = 0.70, 95% confidence interval (CI) = 0.54–0.87, P < 0.001) and a moderate reduction in anxiety (d = 0.76, 95% CI = 0.37–1.52, P < 0.001), although there was publication bias in the depression studies. After a trim and fill adjustment, the effect for depression remained (d = 0.42; CI = 0.35–0.50; P < 0.001). Context moderated this effect: There was a greater reduction in depression when group arts interventions were delivered in care homes (d = 1.07, 95% CI = 0.72–1.42, P < 0.001) relative to the community (d = 0.51, 95% CI = 0.32–0.70, P < 0.001). Findings indicate that group arts are an effective intervention for addressing depression and anxiety among older adults.
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