Patrick Deelen

Human genetics implicates a BACH2-NRF2 axis in fetal hemoglobin activation

This study identifies a BACH2-NRF2 axis regulating fetal hemoglobin activation through genetic and functional analyses in a large multi-ancestry cohort.

Trans-eQTLs reveal the architecture of human gene regulatory networks

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

Trans-eQTL mapping prioritises USP18 as a negative regulator of interferon response at a lupus risk locus

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

Disease-associated variants are enriched for altering cell-type-specific gene co-expression relationships

The paper identifies co-eQTLs that alter gene co-expression relationships in specific cell types, linking these variants to immune disease associations.

Linking common and rare disease genetics through gene regulatory networks

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.

Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data

The paper develops interpretable neural networks for multi-omics data to predict smoking status, age, and LDL levels, showing improved performance and generalizability across cohorts.

Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes

The paper links genes in cancer-susceptibility loci to known somatic driver genes through tissue-specific co-expression networks derived from non-cancer samples.

Multi-ancestry polygenic risk scores for venous thromboembolism

This study develops multi-ancestry polygenic risk scores for venous thromboembolism using diverse GWAS data and shows improved predictive performance across European- and African-ancestry populations.

Leveraging functional genomic annotations and genome coverage to improve polygenic prediction of complex traits within and between ancestries

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.

Multi-layered genetic approaches to identify approved drug targets

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

OTTERS: A powerful TWAS framework leveraging summary-level reference data

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.

Brain expression quantitative trait locus and network analysis reveals downstream effects and putative drivers for brain-related diseases

The paper integrates brain RNA-seq and genotype data to identify eQTLs and their downstream effects on brain-related diseases.

KidneyNetwork: Using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease

KidneyNetwork predicts kidney-specific gene functions and disease phenotypes using co-expression networks, identifying ALG6 as a candidate gene for kidney and liver cysts in undiagnosed patients.

Phenotypic and genetic factors are associated with absence of cardiomyopathy symptoms in PLN c.40_42delAGA carriers

The paper identifies shorter QRS duration in asymptomatic PLN c.40_42delAGA carriers and links it to genetic sensitivity in symptomatic carriers.

Global biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

This study evaluates polygenic risk score methods across diverse biobanks and ancestries, finding that European reference panels often yield better performance, while PRS-CS outperforms P+T for high-heritability traits.

Unbiased identification of unknown cellular and environmental factors that mediate eQTLs using principal interaction component analysis

This paper introduces PICALO, a method to identify unknown contexts influencing eQTLs, finding 31 and 21 PICs in blood and brain datasets, respectively, associated with cell type, RNA quality, and environmental factors.

Effect of host genetics on the gut microbiome in 7,738 participants of the Dutch Microbiome Project

The paper identifies host genetic loci associated with gut microbiome composition and function in a large cohort, finding significant associations near LCT and ABO genes.

Integration of public DNA methylation and expression networks via eQTMs improves prediction of functional gene-gene associations

The paper integrates DNA methylation and gene expression networks to improve prediction of functional gene-gene associations using eQTMs and a novel integration pipeline.

Idefix: identifying accidental sample mix-ups in biobanks using polygenic scores

Idefix identifies sample mix-ups in biobanks using polygenic scores, achieving an AUC of 0.90 compared to 0.75 with sex alone.

Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis

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.

Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility

The paper uses symptom-based case predictions to conduct a GWAS on COVID-19, finding new genetic susceptibility insights and suggesting different genetic architectures for severity and susceptibility.

Mapping the human genetic architecture of COVID-19 by worldwide meta-analysis

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.

Imbalanced expression for predicted high-impact, autosomal-dominant variants in a cohort of 3,818 healthy samples

The paper uses allele-specific expression analysis in a large cohort to identify high-impact, autosomal-dominant variants that are compensated by imbalanced expression.

Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference

The paper identifies 818 genes influencing DNA methylation in blood using genetic anchors and causal inference, revealing both transcription factors and non-DNA-binding proteins with regulatory roles.

CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations

CAPICE is a machine learning method that prioritizes pathogenic variants in exomes, outperforming existing tools for rare and ultra-rare variants.

Deconvolution of bulk blood eQTL effects into immune cell subpopulations

The paper introduces Decon2, a method to deconvolute bulk blood eQTL effects into immune cell subpopulations, showing high concordance with experimental and single-cell studies.

Lack of association between genetic variants at ACE2 and TMPRSS2 genes involved in SARS-CoV-2 infection and human quantitative phenotypes

This study investigates genetic variants in ACE2 and TMPRSS2 genes for associations with quantitative phenotypes and medication use in a population cohort, finding suggestive links with hypertension and inflammation-related drugs.

Mendelian Randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical 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.

Improving the diagnostic yield of exome-sequencing, by predicting gene-phenotype associations using large-scale gene expression analysis

This paper introduces GADO, a tool that uses gene expression data to predict gene-phenotype associations and improve diagnostic yield in exome sequencing by prioritizing variants in patients with unknown genetic diagnoses.

Integrated Clinical and Omics Approach to Rare Diseases: Novel Genes and Oligogenic Inheritance in Holoprosencephaly

This study identifies novel HPE genes and oligogenic inheritance patterns in holoprosencephaly by integrating clinical data with exome sequencing and gene prioritization.