Biomedical subjects

Emma C Johnson

Publications and source records attributed to Emma C Johnson.

4 recordsLinked to original sources

PubMed2026

Multi-ancestral genome-wide association study of chronic pain reveals widespread genetic correlations with mental and physical health traits.

Chronic pain (CP) is common and debilitating, affecting 12-40% of people worldwide. In this study, we conducted a genome-wide association study (GWAS) of CP in the All of Us Research Program across six genetic ancestries (Ntotal = 313 931, Ncase = 64 894, Ncontrol = 249 037). In the cross-ancestral meta-analysis, one locus on chromosome 3 reached genome-wide (GW) significance (α = 5E-08; lead SNP: rs3849410, p = 2.64E-08,). This same lead SNP, rs3849410, also reached GW significance in the European subsample (p = 7.45E-10) and in European females (p = 4.25E-08). Two additional loci, with lead SNPs rs7652179 and rs4760489, reached GW significance (p = 8.57E-09, and 3.07E-08, respectively) in European ancestry. Sex-stratified analyses revealed one locus on chromosome 11 (lead SNP: rs77607049) in males (p = 1.13E-08); in females, two other loci on chromosomes 11 (lead SNP: rs368001205) and 12 were also identified (lead SNP: rs80043169; p = 1.58E-08, 9.14E-09, respectively; p < 2.5E-08). CP was genetically correlated with psychiatric, physical, and immune traits, including anxiety (rg = 0.72, p = 2.00E-46), generalized addiction risk (rg = 0.38, p = 2.08E-17), higher C-reactive protein levels (rg = 0.36, p = 6.38E-22) and greater body mass index (rg = 0.43, p = 8.03E-47). This study represents one of the largest cross-ancestral investigations of the genetics of CP to date and demonstrates shared genetic effects between CP and multiple health conditions. PERSPECTIVE: This article presents multi-ancestral cross-sex and sex-stratified GWAS of chronic pain (CP). One significant cross-ancestral locus and 3 sex-specific loci were identified; a previously published locus for multisite CP met traditional genome-wide significance in the current European ancestry GWAS. This study identifies 4 novel genetic loci associated with CP.

Chronic pain↗

PubMed2026

Suicidality phenotypes reflect both shared and distinct genetic factors.

Suicidality phenotypes, including suicidal ideation (SI), non-fatal suicide attempt (SA), and suicide death (SD), are heritable and exhibit both shared and phenotype-specific genetic influences. Using genomic structural equation modelling, we estimated the shared genetic architecture across GWAS of SI (176,147 cases, 1,010,300 controls), SA (53,919 cases, 1,063,988 controls), and SD (7,584 cases, 652,070 controls) and conducted a multivariate GWAS of a latent suicidality factor capturing their shared liability. This analysis identified 36 genome-wide significant loci, including seven not previously reported in any suicidality GWAS. Follow-up analyses identified residual genetic variance specific to each phenotype, including three SD-specific genomic risk loci. Conditioning suicidality phenotypes on genetic liability to psychiatric disorders revealed significant residual genetic variance across SI, SA, SD, and the suicidality common factor. Together, these results suggest that suicidality reflects both shared genetic liability and phenotype-specific contributions.

Journal Article↗

PubMed2026

Can Psychiatric Genetics Advance Without Incorporating a Life Course Perspective?

Psychiatric disorders unfold over the life course; however, genomic studies of these conditions overwhelmingly rely on phenotypes collected at a single time point, often in adulthood. Therefore, genome-wide association studies (GWASs) of psychiatric conditions may miss genetic variants with time-varying relevance to etiology, prevention, and treatment, such as those that influence trajectories of symptoms and behaviors, age at onset, course of treatment response, and the co-evolution of comorbidities. With recent advances in longitudinal biobanks and analytic tools, we posit that incorporating a life course perspective in psychiatric genetics will enable critically relevant insights into each of these areas of investigation. We propose that the current inconsistent portability of polygenic scores across age groups can be reconciled through the design of carefully considered longitudinal GWASs in age-diverse samples. Pioneering longitudinal GWASs in psychiatry have revealed novel genomic signals associated with time-dependent phenotypes that are distinct from those influencing lifetime diagnosis, suggesting that the study of longitudinal phenotypes will complement cross-sectional approaches and empower biological and therapeutic discoveries. Advances in post-GWAS functional annotation resources and analytic approaches now enable us to contextualize the genetic contributions to psychiatric disorders as dynamic age- and exposure-dependent processes. Although longitudinal GWASs pose unique challenges with regard to data availability, selection bias, and missing data, integrating temporality into psychiatric genetics at scale is now attainable and promises to reveal novel biology and therapeutic opportunities for psychiatric conditions.

Cohort study↗

PubMed2024

Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

Humans↗