Loïc Yengo

This study identifies genetic regulators of transcriptomic rhythmicity using GTEx data and links them to phenotypes in the Pan-UK Biobank.

The paper estimates heritability for behavioural and disease traits using 500,000 sibling pairs across diverse ancestries, finding substantial genetic contributions for smoking, alcohol use, personality, and diseases like T2D and asthma.

This paper introduces a summary-statistics-based method to detect and quantify ascertainment bias in genetic studies using polygenic scores across multiple biobanks.

The paper identifies biases in estimating heritability from ultra-rare variants and shows that accounting for these biases reveals significant heritability estimates for several traits.

This paper improves causal variant identification by genome-wide fine-mapping, showing it outperforms existing methods and identifies new causal variants for complex traits.

This paper introduces SBayesAPP, a Bayesian model that estimates annotation-stratified pleiotropy and co-polygenicity between complex traits using GWAS summary statistics, revealing cell-type-specific genetic correlations.

This study identifies age-varying genetic contributions to BMI using longitudinal data from the ALSPAC cohort, showing distinct genetic profiles in infancy versus later childhood and adolescence.

This paper introduces Manc-COJO, a method for multi-ancestry conditional and joint analysis of GWAS summary statistics, improving detection of independent signals and reducing false positives.

The paper reassesses selection on height using GWAS and allele frequency data, finding positive selection at height-associated loci in Europe.

The paper estimates direct effects of genetic ancestry on complex traits in a Mexican population using family-based analyses and finds significant associations for height and type 2 diabetes but not for educational attainment.

DNACipher predicts variant effects across cell types and assays, identifying imVars at most GWAS loci with support from experimental data.

DINGO improves locus discovery in GWAS of perinatal traits by combining maternal and fetal GWAS data through meta-analysis and novel statistical tests, identifying more genetic loci than separate analyses.

Family-based GWAS meta-analysis of 34 phenotypes shows standard GWAS effects carry sizeable confounding uncorrelated with direct genetic effects, while assortative mating likely inflates SNP heritability and genetic correlations.

This paper introduces SBayesRC, a method that improves polygenic prediction of complex traits by integrating GWAS summary statistics with functional genomic annotations, showing significant accuracy gains across ancestries.

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.

This study identifies 565 genetic loci associated with sitting height ratio (SHR) in two populations, finding distinct genetic signals from height and highlighting ancestry-specific effects.

The paper examines how assortative mating, participation bias, and socioeconomic status affect polygenic risk scores for behavioral and psychiatric traits using genetic and demographic data.

The paper shows that marker-based heritability estimators are biased under assortative mating and proposes corrected estimators for traits under equilibrium assortative mating.

This study identifies 12,111 SNPs associated with height from 5.4 million individuals, explaining most common SNP-based heritability and showing ancestry-specific prediction accuracy.

The paper examines factors influencing consent to prescription record linkage in a depression genetics study, finding phenotypic and genetic associations with participation rates.

This study estimates non-additive genetic variance in human complex traits using a large sample of unrelated individuals and finds that additive variance is predominant while dominance and epistatic variances are negligible.

The paper quantifies genetic heterogeneity between European and African populations for height and BMI, finding high shared genetic variation suggesting GWAS findings in Europeans are applicable to non-Europeans.

This study identifies 13 genome-wide significant loci associated with SARS-CoV-2 infection or severe COVID-19 through a global meta-analysis of 49,562 patients.

Genome-wide association study and integrative analyses identify 27 genes in inflammation and coagulation pathways linked to COVID-19 hospitalization risk and symptomology.

This study uses human height GWAS data to prioritize genes and variants for cattle stature, finding some overlap but no added benefit over within-species data.

This paper quantifies the accuracy loss of polygenic scores in non-European populations by modeling linkage disequilibrium, allele frequencies, and effect size correlations.

This paper identifies 58 significant associations between grey matter structure and diverse human phenotypes using large neuroimaging datasets and shows body size factors explain part of these associations.

The paper reanalyzes Domingue et al. (2018) and shows their claims of social genetic effects and genetic similarity among friends are not supported by the data.

This paper introduces SBayesR, a Bayesian method for polygenic prediction using GWAS summary statistics, achieving higher accuracy and efficiency than existing methods.

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.