Mélanie Waldenberger

This study conducts an epigenome-wide association study (EWAS) meta-analysis of wellbeing using DNA methylation data, finding no significant methylation sites but suggesting the need for larger studies.

The paper identifies a variant in DSP associated with QRS interval and shows that DSP-AS1 regulates DSP expression through functional and Mendelian randomization analyses.

This study identifies novel and known genetic contributors to hypertension using RNA-seq and eQTL analyses, highlighting potential drug targets and pathways.

The paper develops an interpretable multimodal machine learning framework to predict distal sensorimotor polyneuropathy using clinical and molecular data, identifying key biomarkers and improving prediction accuracy with additional molecular modalities.

The paper identifies DNA methylation and gene expression changes in human blood after a meal, linking them to cardiometabolic health and obesity-related genes.

This paper introduces RTFS, a method for pre-selecting CpGs for disease prediction models, and shows it performs well for predicting type 2 diabetes onset risk.

The paper reconstructs regulatory networks underlying trans-QTL hotspots using human multi-omics data and biological priors, identifying novel networks related to schizophrenia and lean body mass.

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

The paper examines nc886 methylation across populations and tissues, finding stable levels except in specific tissues and some discordance in dizygotic twins.

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

The paper develops epigenetic scores (EpiScores) for plasma proteins to predict disease risk, finding 137 associations with incident morbidities independent of known factors.

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

The paper identifies novel genetic loci associated with blood pressure that interact with sleep duration across multiple ancestries.

This study performs a large GWAS on dilated cardiomyopathy, identifying two new loci and confirming two existing ones, with potential therapeutic implications.

The paper identifies a DNA methylation site in the LPA promoter associated with Lp(a) levels and shows that a SNP at this site influences Lp(a) through direct genetic effect, not methylation.

DeepWAS integrates regulatory effect predictions of variants into GWAS to identify regulatory SNPs associated with diseases and traits.

This study identifies 210 genetic loci associated with the PR interval through multi-ancestry GWAS, highlighting their role in cardiac conduction and cardiovascular disease.

The paper identifies FKBP5 epigenetic derepression by aging and stress as a driver of NF-kB-driven inflammation and cardiovascular risk through in vitro and cohort studies.

This paper introduces SAPPHO methods to detect pleiotropy in GWAS by modeling shared patterns of genetic associations, finding 16 additional and 124 novel loci in meta-analysis.

This study identifies 47 novel genetic loci associated with PR interval through genome-wide association meta-analysis across multiple populations.

RL-SKAT improves the accuracy of score tests for heritability and set-based genetic association by calculating exact p-values, avoiding the inflation or deflation of p-values seen in traditional methods.

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

This paper shows that DNA methylation data can capture ancestry information and introduces a method to infer ancestry from methylation data without genetic data.