Zoltán Kutalik

This paper evaluates the feasibility of re-identifying individuals using polygenic predictions and finds that real-world effectiveness is limited due to low priors and poor sensitivity for sensitive genotypes.

The paper detects stabilizing selection on human plasma proteins by integrating genetic and fitness-related evidence across multiple approaches.

The paper identifies rare variants in CSMD2 associated with neurodevelopmental disorders, showing both recessive and dominant inheritance patterns and functional impairments.

This study identifies genetic loci associated with childhood eating behaviour and shows they mediate obesity risk through distinct pathways, primarily driven by the child's own genotype.

This study characterizes spatial variation in corpus callosum structure and its developmental, genetic, and cognitive correlates using multimodal data from youth.

The paper identifies sex-different phenotypic correlations in the UK Biobank and decomposes them into genetic and environmental contributions, finding environmental factors dominate.

The paper integrates genetic signals to improve drug target identification by comparing prioritization strategies across traits and showing that combining related disease data enhances performance.

This study performs a large-scale GWAS on 249 metabolic traits in 619,372 individuals, identifying 88,604 associations and using MR to explore causal links between metabolites and diseases.

This study identifies CYP4F2 as a key enzyme mediating ω-hydroxylation of 1-deoxySLs, revealing a new hepatic detoxification pathway that reduces their cytotoxicity.

This study identifies 58 genomic regions associated with meiotic recombination, 24 of which are sex-specific, and finds a moderate genetic correlation between male and female recombination rates.

The paper investigates BLTP1's role in neocortical lamination by analyzing patients and mouse models, finding lipid transport defects cause structural brain abnormalities.

The paper estimates genetic assortative mating using haplotype reconstruction in large biobank cohorts, revealing recent trends in mate choice and its genetic impact.

The paper investigates how polygenic scores and copy-number variants interact, finding that assortative mating explains their positive correlation and contributes to genetic risk compounding.

The paper infers parent-of-origin effects in ~265,000 individuals using a novel method, identifying over 30 novel POEs and confirming known associations, supporting the parental conflict hypothesis.

The paper uses EHRs and biobanks to identify pharmacogenetic associations with drug response in cardiometabolic diseases, finding novel genetic predictors for personalized treatment.

This paper links common and rare disease genetics by identifying key genes affected by common variants through gene regulatory networks, finding many key genes are outside GWAS loci.

The paper identifies pleiotropic effects of 16p11.2 BP4-5 CNVs on 46 phenotypes, showing BMI-dependent and indirect associations through mediation and Mendelian randomization.

This study investigates genetic factors influencing weight loss from GLP1-RA and bariatric surgery in 10,960 individuals across 9 biobanks, finding no strong genetic associations with GLP1-RA effectiveness but a modest link between BMI polygenic scores and reduced bariatric surgery weight loss.

This study identifies widespread stabilizing selection on metabolite levels in humans, with implications for cardiometabolic health and evolutionary conservation.

This study investigates the relationship between telomere length and health outcomes using UK Biobank data, identifying factors that influence telomere attrition and its effects on disease risk and lifespan.

Delphi is a deep learning method for polygenic risk prediction that outperforms traditional models and improves performance for under-represented ancestries.

The paper introduces causality-enriched epigenetic clocks, DamAge and AdaptAge, to track detrimental and adaptive methylation changes linked to aging, showing their association with adverse outcomes and beneficial adaptations.

This study identifies genetic variants associated with income and shows they correlate with health outcomes and educational attainment.

This study identifies 73 CNV-related disease signals in 331,522 UK Biobank participants, showing CNVs increase disease risk and earlier onset, with polygenic effects and gene dosage impacts.

The paper compares gene-prioritization methods for identifying drug targets across 30 traits, finding GWAS performs best with an AUC of 54.3%.

This paper evaluates the impact of participation bias in the UK Biobank by applying inverse probability weighting to genome-wide association analyses, revealing significant distortions in genetic correlations and Mendelian Randomization estimates.

This paper introduces MRlap, a method to correct bias in IVW-MR by addressing weak instruments and winner's curse, improving causal effect estimation in Mendelian randomization.

The paper identifies age-specific genetic effects on age at natural menopause using UK Biobank data, revealing varying biological pathways and health outcomes across menopause timing.

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 investigates the phenotypic effects of 22q11.2 copy number variants in the general population using UK Biobank data, finding associations with BMI, platelet volume, and other traits.