Markus Perola

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

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.

The paper develops metabolomic risk scores from half a million blood samples to predict 12 common diseases, showing they outperform polygenic scores and benefit from repeat measurements.

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.

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.

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

The paper examines the association between BMI and epigenetic aging in twin pairs, finding BMI increases are linked to accelerated epigenetic age using GrimAge.

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.

The paper introduces a multivariate GWAS framework that identifies functional variants and disease associations by transforming multivariate results into univariate phenotypes for follow-up analysis.

This study identifies 118 genetic loci associated with 2,319 metabolite features and finds 46 causal effects of metabolites on common diseases using genome-wide association and Mendelian randomization.

The paper identifies rare protein-altering variants in ANGPTL7 that lower intraocular pressure and reduce glaucoma risk by analyzing genotyping data from UK Biobank and FinnGen.

The paper examines the effects of CETP and HMGCR genetic inhibition on lipoprotein profiles and CHD risk, finding distinct impacts on cholesterol and triglyceride compositions.

This study identifies genetic variants with pleiotropic effects on cytokines and related traits using a multivariate genome-wide association analysis.

The paper identifies alpha-1 antitrypsin as a key contributor to GlycA's predictive power for disease risk and mortality across multiple conditions.

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 conducts a large GWAS on heart failure, identifying 12 genetic loci with associations to CAD, atrial fibrillation, and reduced left ventricular function, and provides causal evidence for several risk factors.

This study identifies seven novel genetic loci associated with circulating cytokines and cell adhesion molecules in Finns through GWAS and meta-analysis.

This study examines geographic variation and bias in polygenic scores for complex traits in Finland, finding that population genetic structure may cause apparent geographic patterns rather than direct genotype-phenotype associations.

The paper identifies genetic risk variants associated with vaccination-related narcolepsy using genomic data from cases and controls.

The paper analyzes rare coding variants in smoking and drinking behavior using exome chip data, finding that they contribute to phenotypic variation but require larger samples for individual variant associations.

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.

This study identifies genetic risk loci for narcolepsy, showing enrichment in immune cells and suggesting autoimmune modulation via T cell receptor chains and influenza-A infection.

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 uses haplotype sharing among Finns to reconstruct recent population history and identify regions with increased rare disease variant sharing.

The paper integrates transcriptomic, metabolomic, and genomic data to identify gene networks and their genetic regulation linked to immune function and circulating metabolites.

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

This study identifies metabolic signatures linked to birth weight in adolescents and adults, finding that lower birth weight is associated with adverse cardiometabolic biomarkers similar to higher BMI, but with weaker effects.

This study develops a genomic risk score for coronary heart disease and shows it improves risk prediction beyond clinical scores, particularly in older adults.

This study examines the metabolic effects of alcohol consumption in young adults, finding associations with multiple cardiometabolic risk markers and a complex metabolic signature.

This study identifies 17 new genetic loci associated with circulating cytokine and growth factor concentrations in Finns, linking them to immune-related diseases and potential drug targets.