Peter Louis Kovacs

The paper compiles and analyzes a complete set of octopamine receptor mutant lines in Drosophila melanogaster to study their expression, function, and role in development and behavior.

This study re-examines the role of octopamine in learning and memory in Drosophila larvae, showing it modulates dopaminergic neurons to orchestrate memory processes.

This study identifies diet-temperature interactions that shape DNA methylation and gene regulation in brown adipose tissue, showing obesity limits cold-induced transcriptional responses.

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

The paper investigates how maternal thyroid hormone exposure affects DNA methylation at a leptin upstream enhancer in adipose tissue, with sex-specific impacts on body fat percentage.

This study investigates how obesity affects working memory gating and finds that dopaminergic gene variants and amino acid ratios influence cognitive flexibility in high-BMI individuals.

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.

The paper examines how lifestyle factors affect DNA methylation in blood, identifying DMPs and DMRs linked to lifestyle categories and biological pathways.

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 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.

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 16 causal coding variants in type 2 diabetes using fine-mapping and shows that one third of signals are false leads.