Marios Arvanitis

The paper conducts a genome-wide analysis of clinical obesity, identifies distinct genetic loci, and shows that a clinical obesity polygenic score improves cardiovascular risk prediction compared to BMI-based scores.

The paper develops a graph neural network framework that integrates biological knowledge to predict phenotypes from proteomics data, outperforming linear models and other architectures.

The paper identifies novel non-coding driver mutations in clonal hematopoiesis using whole genome sequences from the UK Biobank and links them to common diseases.

This study identifies CCRL2 as a driver of IFN-γ signaling in TP53-mutated AML with erythroid differentiation, linking it to disease progression and poor outcomes.

This paper introduces GLEANR, a method for sparse matrix factorization of GWAS summary statistics that accounts for sample sharing and identifies interpretable genetic factors.

The paper develops a method to quantify somatic mutation burden in whole-genome sequencing data without paired-tissue samples and identifies genetic and phenotypic correlates of clonal hematopoiesis without known driver mutations.

The paper identifies impactful rare variants by integrating multi-omic data from MESA, showing that combining expression and protein data increases the detection of rare stop and frameshift variants.

The paper validates novel telomere length regulation genes POP5 and KBTBD6 identified through trans-ancestry GWAS using functional experiments in blood cells.

This study introduces ARCHIE, a method to identify trait-specific gene sets through trans-eQTL analysis, finding 71 gene networks with significant trans-associations across 29 traits.

The paper introduces CAFEH, a method to better identify causal regulatory variants across tissues by accounting for allelic heterogeneity and linkage disequilibrium in eQTL data.

This study identifies 59 sentinel variants and two novel genes associated with telomere length using whole genome sequences from 109,122 trans-ethnic individuals.

This study uses Mendelian randomization to examine if ACE inhibitors or cardiometabolic risk factors affect lung ACE2 and TMPRSS2 expression or plasma ACE2 levels, finding no overall association.

This study identifies one known and two novel genetic variants associated with heart failure through GWAS and multi-omic analyses, revealing potential causal mechanisms and shared heritability with musculoskeletal traits.

The paper analyzes de novo mutations in 1,465 genomes to show similar mutation rates across ancestries but reduced rates in the Amish population, with environmental factors possibly influencing mutation rates.

The paper uses matrix factorization to analyze eQTLs across 49 human tissues, identifying tissue-specific and shared genetic regulation patterns and their potential transcription factor drivers.