Matti Pirinen

Phenome-wide scan of Y-chromosomal variants against 1,426 traits in 104,334 Finnish men finds no significant hits; kin-based validation supports haplogroup I1 increasing coronary heart disease risk.

KANN estimates genetic ancestry profiles using k-nearest neighbor regression on principal components, showing strong agreement with haplotype-based methods in large-scale genomic data.

This study fine-maps genome-wide association study results for migraine, identifying 181 credible sets of candidate causal variants across 102 regions.

FINEMAP-miss improves fine-mapping in GWAS meta-analyses by addressing variant-specific missingness, outperforming standard methods in low imputation information and complex settings.

The paper estimates heritability for 2,321 plasma proteins using twin data and finds that SNP-based heritability accounts for only half of the total genetic effects.

This study performs a genome-wide association study for Long COVID, identifying a significant association with the FOXP4 locus and highlighting the role of pulmonary dysfunction and COVID-19 severity.

This study assesses the contribution of the X chromosome to complex trait heritability and finds evidence of dosage compensation mechanisms affecting its genetic influence.

This paper improves fine-mapping by estimating effect sizes and regional heritability using FINEMAP, showing it captures more heritability than BOLT and provides better precision.

The paper identifies genetic loci associated with female infertility through a GWAS, revealing a rare recessive mutation in TBPL2 and age-dependent risk factors.

The study analyzes Y-chromosome sequencing data from Finland to identify sublineages and geographic patterns within major haplogroups, suggesting dual migration routes for haplogroup N1a1.

The paper uses Mendelian Randomization to assess the causal link between maternal influences on birth weight and five health outcomes in 36,211 genotyped mother-child pairs.

This study identifies 495 genetic associations with plasma lipid species using genome-wide analysis in 7,174 Finnish individuals and fine-mapping in 377,277 participants, revealing 9 novel loci and disease links.

This study identifies proteins and genes associated with BMI and its changes in twins, showing shared genetic and environmental factors across proteome, transcriptome, and metabolome layers.

This study identifies genetic drivers and cellular selection signatures of mosaic X chromosome loss in women using large-scale population data and polygenic scores.

The paper examines sex differences in circulatory lipids and their genetic determinants using lipidomics and genome-wide association studies across multiple cohorts.

This study performs a large multi-ancestry meta-analysis of IPF genetics, identifying seven novel genome-wide significant loci and highlighting pleiotropy with severe COVID-19 and sex-heterogeneity at the MUC5B locus.

This study estimates the impact of genetic risk factors on disease burden using disability-adjusted life years (DALYs) and finds that both common and rare variants significantly contribute to healthy life years lost.

The paper identifies genetic risk factors for tuberculosis, including HLA alleles and INPP5A variants, and shows smoking as a lifestyle risk factor.

This study updates the genetic architecture of COVID-19 by adding 11 new genome-wide significant loci through a large GWAS meta-analysis.

This GWAS identifies 123 migraine risk loci, including subtype-specific variants and novel targets, supporting neurovascular mechanisms in migraine.

The paper introduces a Bayesian model comparison approach, MRP, for rare variant association studies using summary statistics, demonstrating improved power and discovery of gene-trait associations across multiple phenotypes.

This study identifies genetic loci associated with SARS-CoV-2 susceptibility and disease severity using GWAS and colocalization, and links them to eQTLs in various tissues.

The paper introduces a Bayesian mixture model to cluster rare-variant effects across multiple phenotypes and demonstrates its application using UK Biobank data.

This study uses genetic data to examine testosterone's effects on health, finding sex-specific impacts on female reproductive health and complex associations with disease risk.

The paper maps high-resolution recombination rates in Finns and compares their impact on phasing and imputation to non-Finnish Europeans, finding minimal effect on accuracy.

This paper introduces PolyFun, a method that improves fine-mapping accuracy by integrating genome-wide functional data, leading to more causal variant identifications and polygenic localization of trait heritability.

This study identifies 15 new risk loci for otosclerosis and replicates known associations, highlighting shared genetic links with skeletal structure and bone-related disorders.

MetaPhat decomposes multivariate GWAS associations into central traits using BIC and P-value statistics, improving interpretation of genotype-phenotype links.

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.

Exome sequencing in Finnish populations identifies rare trait-associated alleles with higher frequencies and geographical clustering, revealing 30 novel associations with quantitative traits.