Julia Sidorenko

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.

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

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.

This study examines the genetic and phenotypic links between neonatal C3 and C4 protein concentrations and psychiatric and autoimmune disorders, finding no strong causal associations with mental disorders but evidence of lower autoimmune risk with higher C4 levels.

A genome-wide association study of 69,369 schizophrenia cases and 236,642 controls identifies 270 risk loci, prioritizes 130 genes, and links common and rare risk variants to neuronal synaptic biology.

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 introduces a Bayesian model, BayesRR-RC, to infer the genetic architecture of complex traits and finds that most genetic variance is attributed to non-proximal regulatory and coding regions.

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.

This study identifies genetic loci for gastrointestinal disorders and finds a link between the nervous system and the gastrointestinal tract.

The paper compares GLM and LMM approaches for mass-univariate vertex-wise analysis, showing LMMs reduce false positives and cluster size but increase computation.

This study identifies 143 genetic loci associated with 25 hydroxyvitamin D concentration in Europeans, revealing biological pathways and causal relationships with health outcomes.

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 how X-linked dosage compensation affects genetic variation in complex traits, finding more genetic variation in males than females for X-linked loci.

This paper performs a meta-analysis of GWAS for height and BMI in 700,000 individuals, identifying 3,290 and 716 SNPs, with increased prediction accuracy.

This study identifies 139 common and 4 rare genetic variants associated with type 2 diabetes through GWAS and integrates gene expression and epigenomic data to highlight potential functional genes and regulatory mechanisms.

The paper estimates the joint distribution of effect size and MAF for genetic variants in 28 complex traits and detects widespread negative selection signatures.