Joyce B. J. van Meurs

The paper integrates GWAS meta-analysis with human brain cell mapping to identify genetic loci and cell types involved in tinnitus, implicating the amygdala and midbrain.

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

This study shows that deleterious mitochondrial DNA mutations increase over time and are associated with higher mortality risk, suggesting positive selection rather than genetic drift.

This paper develops a quality control pipeline for human microbiome research in large population studies to improve data reliability and address standardization challenges.

This study identifies genetic variants influencing miRNA expression and links them to disease associations using genome-wide association studies and Mendelian randomization.

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.

This paper conducts a multi-ancestry time-to-event GWAS to identify genetic variants associated with incident cardiovascular disease in people with type 2 diabetes, finding three novel loci and confirming known CAD variants.

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 identifies genetic determinants of hip joint space width and finds they have opposing causal effects on hip osteoarthritis risk through distinct mechanisms.

This study identifies 400+ genetic loci associated with circulating metabolic traits and highlights pleiotropy and novel disease pathways.

The paper integrates DNA methylation with clinical risk factors to improve mortality prediction, identifying CpG biomarkers associated with all-cause, cardiovascular, and cancer mortality.

This study uses multivariable Mendelian randomization to show that higher bone mineral density causally increases osteoarthritis risk independently of body mass index.

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.

This study identifies DNA methylation sites associated with coffee and tea consumption using EWAS, finding potential links to fatty liver disease through PHGDH expression.

This study identifies three genetic loci associated with chronic widespread musculoskeletal pain, with the RNF123 locus replicated in independent cohorts.

This paper introduces MR-link, a Mendelian randomization method that identifies causal relationships between gene expression and LDL-C levels, finding 19 causally linked genes including PVRL2.

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.

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.

The paper uses RNA-Seq data from 296 family trios to identify genomic imprinting by analyzing allelic expression and parental haplotypes, finding 45 imprinted genes and one novel imprinted transcript.

This study identifies nine novel DNA methylation sites associated with fasting glucose and insulin levels by integrating cross-omics data from multiple cohorts.

This paper conducts a genome-wide meta-analysis of chronic back pain in 158,025 individuals, identifying three genetic loci associated with the condition.

The paper identifies 49 gene drivers of downstream transcriptional changes using population genomics data and RNA-sequencing from 3,072 individuals.

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 identifies gene targets for brain-related traits using transcriptomic and methylomic data from blood, finding strong correlations between genetic effects in brain and blood tissues.

This study identifies 9 new osteoarthritis loci using UK Biobank data and finds causal effects of higher body mass index on osteoarthritis.

This study investigates the association between CpG methylation and educational attainment, finding limited significant associations that may be influenced by confounding factors.