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David A Hinds

Publications and source records attributed to David A Hinds.

4 recordsLinked to original sources
bioRxiv2016

Genome-wide association analyses in >119,000 individuals identifies thirteen morningness and two sleep duration loci

Disrupted circadian rhythms and reduced sleep duration are associated with several human diseases, particularly obesity and type 2 diabetes, but little is known about the genetic factors influencing these heritable traits. We performed genome-wide association studies of self-reported chronotype (morning/evening person) and self-reported sleep duration in 128,266 White British individuals from the UK Biobank study. Sixteen variants were associated with chronotype (P<5x10-8), including variants near the known circadian rhythm genes RGS16 (1.21 odds of morningness [95%CI 1.15, 1.27], P=3x10-12) and PER2 (1.09 odds of morningness [95%CI 1.06, 1.12], P=4x10-10). The PER2 signal has previously been associated with iris function. We sought replication using self-reported data from 89,823 23andMe participants; thirteen of the chronotype signals remained significant at P<5x10-8 on meta-analysis and eleven of these reached P<0.05 in the same direction in the 23andMe study. For sleep duration, we replicated one known signal in PAX8 (2.6 [95%CIs 1.9, 3.2] minutes per allele P=5.7x10-16) and identified and replicated two novel associations at VRK2 (2.0 [95% CI: 1.3, 2.7] minutes per allele, P=1.2x10-9; and 1.6 [95% CI: 1.1, 2.2] minutes per allele, P=7.6x10-9). Although we found genetic correlation between chronotype and BMI (rG=0.056, P=0.048); undersleeping and BMI (rG=0.147, P=1x10-5) and oversleeping and BMI (rG=0.097, P=0.039), Mendelian Randomisation analyses provided no consistent evidence of causal associations between BMI or type 2 diabetes and chronotype or sleep duration. Our study provides new insights into the biology of sleep and circadian rhythms in humans.

Genetics↗
bioRxiv2016

Genetic and environmental risk for chronic pain and the contribution of risk variants for psychiatric disorders. Results from Generation Scotland: Scottish Family Health Study and UK Biobank

BackgroundChronic pain is highly prevalent worldwide and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with psychiatric illness, and major depressive disorder (MDD) in particular, is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS). We then sought to replicate any significant findings in the UK Biobank study.\n\nMethodsUsing family-based mixed-model analyses, we examined the contribution of genetics and environment to chronic pain using spouse, sibling and household groups as measures of shared environment. We then examined the correlation between chronic pain and MDD and estimated the contribution of genetic factors and shared environment. Finally, we used data from two independent genome-wide association studies to test whether chronic pain has a polygenic risk architecture and examine whether genomic risk of psychiatric disorder predicted chronic pain and whether genomic risk of chronic pain predicted MDD.\n\nResultsChronic pain is a moderately heritable trait (narrow sense heritability = 38.4%) which is more likely to be concordant in spouses and partners (variance explained 18.7%). Chronic pain is positively correlated with depression (rho = 0.13, p = 2.72x10-68) and it shows a tendency to cluster within families for genetic reasons (genetic correlation rho = 0.51, p = 8.24x10-19). Polygenic risk profiles for pain, generated using independent GWAS data, predicted chronic pain in both GS:SFHS (maximum {beta} = 6.18x10-2, p = 4.3x10-4) and UK Biobank (maximum {beta} = 5.68 x 10-2, p < 3x10-4). Genomic risk of MDD is also significantly associated with chronic pain in both GS:SFHS (maximum {beta} = 6.62x10-2, p = 4.3x10-4) and UK Biobank (maximum {beta} = 2.56x10-2, p < 3x10-4).\n\nConclusionsGenetic factors and chronic pain in a partner or spouse contribute substantially to the risk of chronic pain in the general population. Chronic pain is genetically correlated with MDD, has a polygenic architecture and is predicted by polygenic risk of MDD.

Genomics↗
bioRxiv2015

Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine

Migraine is a debilitating neurological disorder affecting around 1 in 7 people worldwide, but its molecular mechanisms remain poorly understood. Some debate exists over whether migraine is a disease of vascular dysfunction, or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we performed the largest genetic study of migraine to date, comprising 59,674 cases and 316,078 controls from 22 GWA studies. We identified 45 independent single nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 x 10-8) that map to 38 distinct genomic loci, including 28 loci not previously reported and the first locus identified on chromosome X. Furthermore, a subset analysis for migraine without aura (MO) identified seven of the same loci as from the full sample, whereas no loci reached genome-wide significance in the migraine with aura (MA) subset. In subsequent computational analyzes, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies.

Genetics↗
bioRxiv2014

Genetic variants associated with motion sickness point to roles for inner ear development, neurological processes, and glucose homeostasis

Roughly one in three individuals is highly susceptible to motion sickness and yet the underlying causes of this condition are not well understood. Despite high heritability, no associated genetic factors have been discovered to date. Here, we conducted the first genome-wide association study on motion sickness in 80,494 individuals from the 23andMe database who were surveyed about car sickness. Thirty-five single-nucleotide polymorphisms (SNPs) were associated with motion sickness at a genome-wide-significant level (p< 5e-8). Many of these SNPs are near genes involved in balance, and eye, ear, and cranial development (e.g., PVRL3, TSHZ1, MUTED, HOXB3, HOXD3). Other SNPs may affect motion sickness through nearby genes with roles in the nervous system, glucose homeostasis, or hypoxia. We show that several of these SNPs display sex-specific effects, with as much as three times stronger effects in women. We searched for comorbid phenotypes with motion sickness, confirming associations with known comorbidities including migraines, postoperative nausea and vomiting (PONV), vertigo, and morning sickness, and observing new associations with altitude sickness and many gastrointestinal conditions. We also show that two of these related phenotypes (PONV and migraines) share underlying genetic factors with motion sickness. These results point to the importance of the nervous system in motion sickness and suggest a role for glucose levels in motion-induced nausea and vomiting, a finding that may provide insight into other nausea-related phenotypes such as PONV. They also highlight personal characteristics (e.g., being a poor sleeper) that correlate with motion sickness, findings that could help identify risk factors or treatments.

Genetics↗