Joseph Maranville

VIDRA models genetic dose-response relationships to predict drug mechanisms, therapeutic potential, and adverse events using phenotypically associated variants.

This study uses deep mutational scanning to analyze TYK2 variants and their impact on function and drug response, identifying novel therapeutic targets and degradation strategies.

The paper develops a proteomic polygenic score to predict IL-18 levels and IBD risk, identifying ~30% of IBD patients as IL-18 High.

The paper performs whole exome sequencing on 44,028 British South Asians to identify gene-phenotype associations and knockout genes, finding novel links and implications for drug development.

This study shows that plasma protein quantitative trait loci (pQTL) support therapeutic hypotheses more effectively than other genetic evidence, increasing the likelihood of drug development success.

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 identifies 1,242 novel genetic variants and 31 novel genes associated with frailty through genome-wide association and proteomics integration.

This study uses proteome-wide Mendelian randomization to identify 221 candidate causal proteins and 16 biomarkers for cardiovascular diseases, distinguishing between direct causes and consequences of CVD.

This study conducts a genome-wide meta-analysis across three biobanks to identify new genetic loci associated with lumbar disc herniation, expanding the known genetic landscape.

This study conducts a GWAS of preeclampsia and hypertensive disorders of pregnancy, identifying 18 genome-wide significant loci, including novel associations with blood pressure and placental function.

Finnish-enriched low-frequency variants, often coding, underlie many GWAS signals across 1,932 register endpoints in 218,792 Finns; a 15-disease meta-analysis with Estonian and UK biobanks adds 30 unreported associations.

This paper uses Mendelian randomization and colocalization to identify causal relationships between plasma proteins and disease phenotypes, finding 111 putatively causal effects.

The paper identifies 279 new genetic signals for lung function across multiple ancestries, showing associations with COPD and pleiotropic effects.

The paper identifies 1,927 genetic associations with 1,478 plasma proteins using 10.6 million DNA variants and 3,301 individuals, revealing new drug targets and safety concerns.

The paper uses PheWAS across large cohorts to identify genetic associations with drug targets and predict drug safety and efficacy.