Tuomo Kiiskinen

This study identifies ultra-rare damaging variants in schizophrenia risk genes and shows they are associated with earlier hospitalizations, greater childhood adversity, and poorer neuropsychological outcomes across psychotic disorders.

The paper uses information theory to show that biological organization cannot be fully specified by an organism's own program, but instead arises from a coarse-grained specification by a shared physical background.

CuGen is a GPU-accelerated framework for large-scale genomics that enables efficient GWAS and fine-mapping with robust confounding control.

A low-rank covariance probe on Evo 2 embeddings predicts ClinVar pathogenicity across SNVs and indels, while annotation probes plus an LLM produce mechanistic hypotheses; scores released for 4.2 million variants.

This study identifies genetic loci associated with antihypertensive medication switching, implicating neurotensin-NTSR1 signaling in ACE inhibitor-induced cough and CYP3A4*22 in dCCB intolerance.

The paper uses genome-wide meta-analysis and machine learning to study prescription opioid use in 860,000 individuals, identifying genetic loci and distinguishing between pain-related and dose-intensity traits.

This study identifies 93 genetic loci associated with alcohol-related diseases using FinnGen data and shows polygenic risk scores can stratify risk for these diseases and related outcomes.

The paper identifies regulatory variation at HTR1F associated with sleep apnea risk and arousals, particularly in non-obese individuals.

The paper demonstrates the feasibility of conducting clinical recall studies from the FinnGen biobank to collect customized clinical data from participants with Alzheimer's disease or mild cognitive disorder.

This study identifies eight genes associated with adult cognitive function through rare coding variants and shows how KDM5B dosage affects cognitive traits in mice and humans.

This study identifies 43 genomic loci associated with reproductive success in 785,604 individuals, showing ongoing natural selection at the FADS 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.

Finnish-enriched low-frequency variants, often coding, underlie many GWAS signals across 1,932 register endpoints in 218,792 Finns; a 15-disease meta-analysis with Estonian and UK biobanks adds 30 unreported associations.

The paper identifies protein-truncating variants in ANGPTL8, ANGPTL4, and LIPG associated with lipid levels and cardiometabolic disease risk, and reports their associations with type 2 diabetes, coronary artery disease, and other adverse effects.

This study combines multiple GWAS of ageing traits to identify genetic components associated with human ageing and finds LPA and VCAM1 as potential drug targets.

This study identifies five genetic loci associated with obstructive sleep apnoea and finds a causal link between BMI and OSA through polygenic risk scores and Mendelian randomization.

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

The paper introduces a frailty model for genome-wide survival analysis in large biobanks, handling population structure and relatedness, and demonstrates its performance on real-world datasets.

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 identifies a missense variant in the MARC1 gene associated with protection against cirrhosis and lower liver enzyme and cholesterol levels.

The paper evaluates polygenic risk scores and clinical risk factors for predicting early-onset cardiometabolic diseases and cancers, showing comparable performance to clinical scores.

This study identifies 14 genome-wide significant loci and a polygenic signature for myeloproliferative neoplasms, implicating hematopoietic stem cell function and self-renewal in disease risk.

The paper conducts GWAS and PheWAS on plasma lipid species to identify genetic associations and their links to diseases beyond traditional lipid measures.