Inga Prokopenko

This study identifies genetic associations between COMT, ADH1B-ADH1C, and HTR2A loci and substance use disorders in Ukrainians, replicating some findings and providing new evidence for hallucinogen use.

This study shows GLP-1R agonists improve mitochondrial health in beta-cells by forming a complex with VAPB and SPHKAP at ER-mitochondria MCSs, leading to mitochondrial remodelling and improved function.

The paper identifies genetic clusters underlying T2D and hypertension comorbidity using partitioned polygenic scores, improving risk prediction for individuals with heightened susceptibility.

The paper introduces a framework for time-varying GWAS to identify age-varying genetic effects on BMI across childhood, finding 28 genome-wide significant variants, including a novel one in DAOA.

This study identifies DNA methylation changes associated with extreme obesity and finds causal effects on obesity and metabolic disturbances using Mendelian Randomisation.

The paper identifies hypermethylation of PNLIPRP1 in T2D patients and shows its association with acinar-to-ductal metaplasia and PDAC risk.

The paper identifies enriched gut microbiome genera in Kashmiri women with PCOS, linking them to metabolic and hormonal factors.

This study performs a GWAS on random glucose measurements in 493,036 individuals, identifying 128 loci associated with glycaemic traits and providing insights into diabetes biology and treatment.

The paper evaluates a genetic risk score for recurrent pregnancy loss in a Ukrainian population, finding it significantly associated with increased risk.

This study identifies 48 genetic variants associated with handedness using a large GWAS, highlighting polygenic nature and genetic links to neuropsychiatric traits.

The paper links diabetes-associated enhancers with their target genes using 3D chromatin architecture in human pancreatic islets, revealing genetic variants that impact insulin secretion heritability.

The paper introduces methylSCOPA and META-methylSCOPA software for multi-phenotype epigenome-wide association studies, identifying significant methylation sites associated with fasting glucose and insulin levels.

The paper uses GWIS to analyze genetic correlations between HOMA-B/-IR and inflammatory markers, identifying novel loci and strong genetic links with PAI-1 and C-reactive protein.

The paper uses machine learning to predict glycaemic traits from multi-omics data in longitudinal cohorts, identifying key predictors like methylation marks and metabolic variables.

This study identifies novel rare genetic variants associated with heritable pulmonary arterial hypertension through whole genome sequencing of cases and controls.

This study identifies genetic loci associated with early childhood growth phenotypes and links them to later adiposity traits, suggesting potential targets for obesity prevention.