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Elson, S.

Publications and source records attributed to Elson, S..

2 recordsLinked to original sources

Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness

AO_SCPLOWBSTRACTC_SCPLOWHumans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. While the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. While it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition towards loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we conducted a genome-wide association (GWAS) meta-analysis of loneliness (N=475,661), report 12 associated loci (two novel) and significant genetic correlations with 34 other complex traits. The polygenic basis for loneliness was significantly enriched for evolutionary constrained genes and genes expressed in specific brain tissues: (frontal) cortex, cerebellum, anterior cingulate cortex, and substantia nigra. We built polygenic scores based on this GWAS meta-analysis to explore the genetic association between loneliness and health outcomes in an independent sample of 18,498 individuals for whom electronic health records were available. A genetic predisposition towards loneliness predicted cardiovascular, psychiatric, and metabolic disorders, and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, effect of body fat on loneliness, and a similar weaker causal effect of BMI. Our results provide a framework for ongoing studies of the genetic basis of loneliness and its role in mental and physical health.

genetics↗

Genome-wide association study meta-analysis of the Alcohol Use Disorder Identification Test (AUDIT) in two population-based cohorts (N=141,958)

Alcohol use disorders (AUD) are common conditions that have enormous social and economic consequences. We obtained quantitative measures using the Alcohol Use Disorder Identification Test (AUDIT) from two population-based cohorts of European ancestry: UK Biobank (UKB; N=121,604) and 23andMe (N=20,328) and performed a genome-wide association study (GWAS) meta-analysis. We also performed GWAS for AUDIT items 1-3, which focus on consumption (AUDIT-C), and for items 4-10, which focus on the problematic consequences of drinking (AUDIT-P). The GWAS meta-analysis of AUDIT total score identified 10 associated risk loci. Novel associations localized to genes including JCAD and SLC39A13; we also replicated previously identified signals in the genes ADH1B, ADH1C, KLB, and GCKR. The dimensions of AUDIT showed positive genetic correlations with alcohol consumption (rg=0.76-0.92) and Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) alcohol dependence (rg=0.33-0.63). AUDIT-P and AUDIT-C showed significantly different patterns of association across a number of traits, including psychiatric disorders. AUDIT-P was positively genetically correlated with schizophrenia (rg=0.22, p=3.0x10-10), major depressive disorder (rg=0.26, p=5.6x10-3), and attention-deficit/hyperactivity disorder (ADHD; rg=0.23, p=1.1x10-5), whereas AUDIT-C was negatively genetically correlated with major depressive disorder (rg=-0.24, p=3.7x10-3) and ADHD (rg=-0.10, p=1.8x10-2). We also used the AUDIT data in the UKB to identify thresholds for dichotomizing AUDIT total score that optimize genetic correlations with DSM-IV alcohol dependence. Coding individuals with AUDIT total score of [≤]4 as controls and [≥]12 as cases produced a high genetic correlation with DSM-IV alcohol dependence (rg=0.82, p=3.2x10-6) while retaining most subjects. We conclude that AUDIT scores ascertained in population-based cohorts can be used to explore the genetic basis of both alcohol consumption and AUD.

genetics↗