Nicola Pirastu

The paper maps RNA-DNA interactions in 16 human cell types, showing cell-type-specific and dynamic networks that correlate with gene regulation and disease traits.

This study expands the human plasma proteome analysis using an enhanced SomaScan platform, identifying new genetic associations and disease mechanisms beyond the classical secretome.

This study uses 3D diffusion autoencoders to derive latent cardiac MRI phenotypes, finds they share a genetic basis with cardiometabolic traits, and shows predictive power for disease risk.

The paper combines natural and engineered genetic variation to identify 22 non-coding variants affecting haematological traits and shows how a CUX1 variant impacts megakaryopoiesis.

This study identifies genetic determinants of endothelial cell molecular traits and their overlap with disease GWAS loci, revealing shared and unique mechanisms in non-communicable diseases.

SAFE-LD estimates linkage disequilibrium from GWAS summary statistics using pseudo-genotypes that preserve in-sample LD while protecting privacy.

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.

The paper develops genetic scores for 17,227 molecular traits using multi-omic data from INTERVAL and validates them across ancestries, demonstrating their utility in pathway analysis and disease association discovery.

The paper identifies sex-specific genetic loci associated with plasma bile acid levels using GWAS in a population-based cohort.

This study uses genomic SEM on GWAS data to identify three distinct immune disease groups and their associated genetic loci, showing convergence on common pathways.

This study identifies 19 genome-wide significant loci associated with liking of physical activity traits using UK Biobank data and validates findings in twin cohorts.

The paper defines a standard format for GWAS summary statistics to improve data sharing and analysis.

The paper uses genetic variation to assess the causal impact of food choices on health outcomes, identifying robust associations between eating patterns and several diseases.

The paper identifies four genetic loci associated with risk across seven cardiometabolic traits using GWAS in the UK Biobank and replication in independent meta-analyses.

The paper identifies genetic loci associated with survey nonresponse behaviors and shows their genetic correlation with education and health.

This study uses Mendelian randomization to identify 417 potential causal links between dietary patterns and blood metabolites, including novel associations and replication of known ones.

This study conducts a large-scale GWAS of food liking in 161,625 UK Biobank participants, identifying 1401 associations and revealing genetic correlations with brain traits.

The paper identifies sex-differential participation bias in genetic studies by performing GWAS on sex in 3.3 million individuals, finding 158 loci associated with sex and highlighting traits like BMI that may influence participation.

The paper identifies SNPs with sex-specific effects on lung function traits using UK Biobank data, finding a significant interaction at rs7697189 near HHIP.

This paper estimates narrow-sense heritability using identity-by-descent information in unrelated individuals and finds that IBD-based methods can capture rare variant contributions but are affected by stratification.

This study analyzes the genetic structure of six Central Asian populations along the Silk Road, revealing admixture patterns and migration events linked to historical expansions.