David Hinds | Search bioRxiv

bioRxiv2016

Genome-wide analyses of empathy and systemizing: heritability and correlates with sex, education, and psychiatric risk

Empathy is the ability to recognize and respond to the emotional states of other individuals. It is an important psychological process that facilitates navigating social interactions and maintaining relationships, which are important for wellbeing. Several psychological studies have identified difficulties in both self-report and performance-based measures of empathy in a range of psychiatric conditions. To date, no study has systematically investigated the genetic architecture of empathy using genome-wide association studies (GWAS). Here we report the results of the largest GWAS of empathy to date using a well-validated self-report measure of empathy, the Empathy Quotient (EQ), in 46,861 research participants from 23andMe, Inc. We identify 11 suggestive loci (P < 1x10-6), though none were significant at P < 2.5x10-8 after correcting for multiple testing. The most significant SNP was identified in the non-stratified analysis (rs4882760; P = 4.29x10-8), and is an intronic SNP in TMEM132C. The EQ had a modest but significant narrow-sense heritability (0.11{+/-}0.014; P = 1.7x10-14). As predicted, based on earlier work, we confirmed a significant female-advantage on the EQ (P < 2x10-16 Cohens d = 0.65). We identified similar SNP heritability and high genetic correlation between the sexes. Also, as predicted, we identified a significant negative genetic correlation between autism and the EQ (rg = -0.27{+/-}0.07, P = 1.63x10-4). We also identified a significant positive genetic correlation between the EQ and risk for schizophrenia (rg = 0.19{+/-}0.04; P= 1.36x10-5), risk for anorexia nervosa (rg = 0.32{+/-}0.09; P = 6x10-4), and extraversion (rg = 0.45{+/-}0.08; 5.7x10-8). This is the first GWAS of self-reported empathy. The results suggest that the genetic variations associated with empathy also play a role in psychiatric conditions and psychological traits.

Genomics↗

bioRxiv2015

Detection and interpretation of shared genetic influences on 40 human traits

We performed a genome-wide scan for genetic variants that influence multiple human phenotypes by comparing large genome-wide association studies (GWAS) of 40 traits or diseases, including anthropometric traits (e.g. nose size and male pattern baldness), immune traits (e.g. susceptibility to childhood ear infections and Crohns disease), metabolic phenotypes (e.g. type 2 diabetes and lipid levels), and psychiatric diseases (e.g. schizophrenia and Parkinsons disease). First, we identified 307 loci (at a false discovery rate of 10%) that influence multiple traits (excluding \"trivial\" phenotype pairs like type 2 diabetes and fasting glucose). Several loci influence a large number of phenotypes; for example, variants near the blood group gene ABO influence eleven of these traits, including risk of childhood ear infections (rs635634: log-odds ratio = 0.06, P = 1.4 x 10-8) and allergies (log-odds ratio = 0.05, P = 2.5 x 10-8), among others. Similarly, a nonsynonymous variant in the zinc transporter SLC39A8 influences seven of these traits, including risk of schizophrenia (rs13107325: log-odds ratio = 0.15, P = 2 x 10-12) and Parkinsons disease (log-odds ratio = -0.15, P = 1.6 x 10-7), among others. Second, we used these loci to identify traits that share multiple genetic causes in common. For example, genetic variants that delay age of menarche in women also, on average, delay age of voice drop in men, decrease body mass index (BMI), increase adult height, and decrease risk of male pattern baldness. Finally, we identified four pairs of traits that show evidence of a causal relationship. For example, we show evidence that increased BMI causally increases triglyceride levels, and that increased liability to hypothyroidism causally decreases adult height.

Genomics↗