Biology subjects

Hinds, D.

Publications and source records attributed to Hinds, D..

4 recordsLinked to original sources

bioRxiv2018

Tendency towards being a “Morning person” increases risk of Parkinson’s disease: evidence from Mendelian randomisation

BackgroundCircadian rhythm may play a role in neurodegenerative diseases such as Parkinsons disease (PD). Chronotype is the behavioural manifestation of circadian rhythm and Mendelian randomisation (MR) involves the use of genetic variants to explore causal effects of exposures on outcomes. This study aimed to explore a causal relationship between chronotype and coffee consumption on risk of PD.\n\nMethodsTwo-sample MR was undertaken using publicly available GWAS data. Associations between genetic instrumental variables (IV) and \"morning person\" (one extreme of chronotype) were obtained from the personal genetics company 23andMe, Inc., and UK Biobank, and consisted of the per-allele odds ratio of being a \"morning person\" for 15 independent variants. The per-allele difference in log-odds of PD for each variant was estimated from a recent meta-analysis. The inverse variance weight method was used to estimate an odds ratio (OR) for the effect of being a \"morning person\" on PD. Additional MR methods were used to check for bias in the IVW estimate, arising through violation of MR assumptions. The results were compared to analyses employing a genetic instrument of coffee consumption, because coffee consumption has been previously inversely linked to PD.\n\nFindingsBeing a \"morning person\" was causally linked with risk of PD (OR 1*27; 95% confidence interval 1*06-1*51; p=0*012). Sensitivity analyses did not suggest that invalid instruments were biasing the effect estimate and there was no evidence for a reverse causal relationship between liability for PD and chronotype. There was no robust evidence for a causal effect of high coffee consumption using IV analysis, but the effect was imprecisely estimated (OR 1*12; 95% CI 0*89-1*42; p=0*22).\n\nInterpretationWe observed causal evidence to support the notion that being a \"morning person\", a phenotype driven by the circadian clock, is associated with a higher risk of PD. Further work on the mechanisms is warranted and may lead to novel therapeutic targets.\n\nFundingNo specific funding source.

epidemiology↗

bioRxiv2017

Systemizing is genetically correlated with autism and is genetically distinct from social autistic traits

The core diagnostic criteria for autism comprise two symptom domains - social and communication difficulties, and unusually repetitive and restricted behaviour, interests and activities. There is some evidence to suggest that these two domains are dissociable, yet, this hypothesis has not been tested using molecular genetics. We test this using a GWAS of a non-social autistic trait, systemizing (N = 51,564), defined as the drive to analyse and build systems. We demonstrate that systemizing is heritable and genetically correlated with autism. In contrast, we do not identify significant genetic correlations between social autistic traits and systemizing. Supporting this, polygenic scores for systemizing are significantly positively associated with restricted and repetitive behaviour but not with social difficulties in autistic individuals. These findings strongly suggest that the two core domains of autism are genetically dissociable, and point at how to fractionate the genetics of autism.

genetics↗

bioRxiv2017

Phenome-wide association studies (PheWAS) across large "real-world data" population cohorts support drug target validation

Phenome-wide association studies (PheWAS), which assess whether a genetic variant is associated with multiple phenotypes across a phenotypic spectrum, have been proposed as a possible aid to drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we evaluate whether PheWAS can inform target validation during drug development. We selected 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease therapeutic indications. We independently interrogated these SNPs through PheWAS in four large \"real-world data\" cohorts (23andMe, UK Biobank, FINRISK, CHOP) for association with a total of 1,892 binary endpoints. We then conducted meta-analyses for 145 harmonized disease endpoints in up to 697,815 individuals and joined results with summary statistics from 57 published GWAS. Our analyses replicate 70% of known GWAS associations and identify 10 novel associations with study-wide significance after multiple test correction (P<1.8x10-6; out of 72 novel associations with FDR<0.1). By leveraging directionality and point estimate of the effect sizes, we describe new associations that may predict ADEs, e.g., acne, high cholesterol, gout and gallstones for rs738409 (p.I148M) in PNPLA3; or asthma for rs1990760 (p.T946A) in IFIH1. We further propose how quantitative estimates of genetic safety/efficacy profiles can be used to help prioritize candidate targets for a specific indication. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery.\n\nOne Sentence SummaryMatching genetics with phenotypes in 800,000 individuals predicts efficacy and on-target safety of future drugs.

genetics↗

bioRxiv2017

Replication and characterization of CADM2 and MSRA genes on human behavior

Progress identifying the genetic determinants of personality has historically been slow, with candidate gene studies and small-scale genome-wide association studies yielding few reproducible results. In the UK Biobank study, genetic variants in CADM2 and MSRA were recently shown to influence risk taking behavior and irritability respectively, representing some of the first genomic loci to be associated with aspects of personality. We extend this observation by performing a personality \"phenome-scan\" across 16 traits in up to 140,487 participants from 23andMe for these two genes. Heritability estimates for these traits ranged from 5-19%, with both CADM2 and MSRA demonstrating significant effects on multiple personality types. These associations covered all aspects of the big five personality domains, including specific facet traits such as compliance, altruism, anxiety and activity / energy. This study both confirms and extends the original observations, highlighting the role of genetics in aspects of mental health and behavior.

genetics↗