Timothy M. Frayling

This study identifies genetic variants causal for multiple long-term conditions, revealing shared biological pathways and potential drug targets while highlighting adverse effects of interventions.

This study uses whole-genome sequencing in 672,976 individuals to show rare and common variants converge in genetic associations for anthropometric traits, with ultra-rare variants explaining less than 10% of heritability.

The paper uses a federated approach to conditionally analyze genetic variants across biobanks, identifying LDL-C lowering effects of DNAJC13 haploinsufficiency and LDLR regulation.

The paper maps cis- and trans-eQTLs in blood samples to infer gene regulatory networks and prioritize trait-relevant pathways.

The paper reduces error rates in population-scale whole-genome sequencing by applying genotype-level quality control, demonstrating its effectiveness using UK Biobank and All of Us datasets.

The paper identifies USP18 as a negative regulator of interferon response at a lupus risk locus through trans-eQTL analysis in lymphoblastoid cell lines.

This study integrates primary care and genetic data to identify multimorbidity patterns and shared genetics across 72 chronic conditions, revealing both concordant and discordant relationships.

The paper develops a multivariate methylation risk score using blood DNA methylation data to predict dementia risk and cognitive impairment in Alzheimer's and Parkinson's disease cohorts.

The paper uses whole-genome sequencing data from UK Biobank participants to identify rare non-coding variants and regions associated with circulating protein levels.

The paper identifies individuals deviating from genetically predicted phenotypes using UK Biobank data and shows they are enriched for rare genetic variants and clinical conditions.

OTTERS is a TWAS framework that uses summary-level eQTL reference data to estimate eQTL weights and perform omnibus TWAS, showing improved power and applicability.

This study examines the impact of Mendelian sleep and circadian genetic variants in population cohorts and finds no strong associations with extreme sleep traits, though some variants show minor effects.

The paper investigates the phenotypic effects of rare variants in developmental disorder genes in the general population, finding milder related traits in carriers.

This paper identifies a genetic association between NK3R (TACR3) and menopausal vasomotor symptoms (VMS) using GWAS, while finding no link between rare NK3R variants and VMS despite the efficacy of NK3R antagonists.

This study examines genetic scores for birth weight in South Asians, finding associations with birth size, childhood body size, and adult cardiometabolic markers.

The paper examines the effect of fetal genetic predispositions to metabolically favourable adult adiposity and BMI on birth weight and other anthropometric traits, finding stronger associations with birth weight for the adiposity alleles.

This paper introduces revTWMR, a method to determine causal relationships between gene expression and complex traits, finding that traits more strongly influence gene expression than vice versa.

This study uses Mendelian Randomisation to show that maternal metabolically favourable adiposity is associated with lower offspring birth weight compared to general adiposity indexed by BMI.

The paper uses blood eQTL meta-analysis to explore the polygenic architecture of complex traits, finding that trans-eQTLs are more informative for identifying causal genes than cis-eQTLs.

The paper identifies genetic variants and phenotypes associated with participation in optional UK Biobank components and shows common participation bias across studies.

The paper develops a deep learning method for adipocyte phenotyping and finds adipocyte area correlates with BMI but no genome-wide significant genetic associations.

The paper examines genetic clustering of complex traits and disease risk in Great Britain, finding that socio-economic status influences allele distribution and regional outcomes.

This study identifies 42 genetic loci associated with excessive daytime sleepiness and links them to phenotypic subgroups and related traits.

This paper introduces TWMR, a Mendelian Randomization method that identifies gene-trait associations by integrating GWAS and eQTL data, revealing 3,913 novel associations across 43 human phenotypes.

The paper identifies 57 genomic regions associated with insomnia symptoms, linking them to phototransduction, ubiquitination, and potential causal relationships with coronary heart disease and depression.

This study uses UK Biobank data to assess the penetrance and pathogenicity of rare variants, finding reduced penetrance and variable expressivity for some clinically relevant variants.

This study identifies 47 genetic associations with sleep traits using accelerometer data from 85,670 individuals, including novel variants for sleep quality and duration.