Veikko V Salomaa

The paper identifies pulmonary primary oxysterol and bile acid synthesis as a prognostic biomarker for pulmonary arterial hypertension, outperforming current clinical risk scores.

This study analyzes microbiome data from multiple OA cohorts and finds no significant differences between OA patients and controls, attributing microbiome changes to age and BMI instead of OA.

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.

This study integrates polygenic risk scores and gut metagenomic data to improve prediction of common diseases, showing enhanced predictive performance over conventional risk factors.

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.

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.

Greengenes2 aligns 16S rRNA and shotgun metagenomic data using a whole-genome phylogeny, showing agreement in principal coordinates, taxonomy, and phenotype effect size.

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

This study uses gut microbiome data and machine learning to improve liver disease risk prediction, showing that combining microbiome features with conventional risk factors enhances model performance.

This study evaluates the impact of communicating polygenic and clinical risk scores for ASCVD via a web tool, finding that high-risk individuals made more health behavior changes.

In 5,959 Finns with genotypes and stool metagenomes, GWAS found 583 independent SNP-taxon associations; dairy intake modified LCT effects on Bifidobacterium, and ABO-linked Faecalicatena lactaris tracked secretor status.

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 paper introduces OGUs, a metagenome analysis method that uses sequence alignment hits to reference genomes for community analysis, showing better performance in predicting biological traits than taxonomic or 16S rRNA methods.

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

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

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.

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

This study compares the effectiveness of ethnically matched and mixed reference panels for imputing rare variants in GWAS, showing improved detection of rare variant associations with matched panels.

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

The paper analyzes whole genome sequences from 16,324 individuals to identify genetic variants associated with blood lipid levels and develops a polygenic score for LDL-C.

This study evaluates the genetic architecture of sudden cardiac arrest through GWAS and Mendelian randomization, finding genetic correlations with CAD, height, BMI, and electrical instability traits.

The paper uses whole genome sequencing to identify genetic variants associated with plasma lipoprotein(a) levels and finds high heritability and inter-ethnic differences in Lp(a) risk.