Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10–11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.

Clinical laboratory tests are a critical component of the continuum of care. We evaluate the genetic basis of 35 blood and urine laboratory measurements in the UK Biobank (n=363,228 individuals). We identify 1,857 loci associated with at least one trait, containing 3,374 fine-mapped associations, and additional sets of large-effect (> 0.1 sd) protein-altering, HLA, and copy-number variant associations. Through Mendelian Randomization analysis, we discover 51 causal relationships, including previously known agonistic effects of urate on gout and cystatin C on stroke. Finally, we develop polygenic risk scores for each biomarker and built ‘multi-PRS’ models for diseases using 35 PRSs simultaneously, which improved chronic kidney disease, type 2 diabetes, gout, and alcoholic cirrhosis genetic risk stratification in an independent dataset (FinnGen; n=135,500) relative to single-disease PRSs. Together, our results delineate the genetic basis of biomarkers, their causal influences on diseases, and improve genetic risk stratification for common diseases.

Polygenic risk scores (PRS) have shown promise in predicting susceptibility to common diseases. 1-3 We estimated their added value in clinical risk prediction of five common diseases, using largescale biobank data (FinnGen; N=135,300), and the FINRISK study with clinical risk factors to test genome-wide PRSs for coronary heart disease (CHD), type 2 diabetes (T2D), atrial fibrillation (AF), and breast and prostate cancer. We evaluated the lifetime risk at different PRS levels, and the impact on disease onset and on prediction together with clinical risk scores. Compared to average PRS, having a high PRS contributed to 21% to 38% higher lifetime risk, and 4 to 9 years earlier disease onset. PRS improved model discrimination over age and sex in T2D, AF, breast cancer, and prostate cancer, and over clinical risk in T2D, breast cancer, and prostate cancer. In all diseases, PRS improved reclassification over clinical thresholds, with largest net reclassification improvements for early-onset CHD, AF, and prostate cancer. This study provides evidence for the additional value of PRS in clinical disease prediction. The practical applications of polygenic risk information for stratified screening or for guiding lifestyle and medical interventions in the clinical setting remain to be defined in further studies.

Population isolates such as Finland provide benefits in genetic studies because the allelic spectrum of damaging alleles in any gene is often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%), which survived the founding bottleneck, as opposed to being distributed over a much larger number of ultra--rare variants. While this advantage is well-- established in Mendelian genetics, its value in common disease genetics has been less explored. FinnGen aims to study the genome and national health register data of 500,000 Finns, already reaching 224,737 genotyped and phenotyped participants. Given the relatively high median age of participants (63 years) and dominance of hospital-based recruitment, FinnGen is enriched for many disease endpoints often underrepresented in population-based studies (e.g., rarer immune-mediated diseases and late onset degenerative and ophthalmologic endpoints). We report here a genome-wide association study (GWAS) of 1,932 clinical endpoints defined from nationwide health registries. We identify genome--wide significant associations at 2,491 independent loci. Among these, finemapping implicates 148 putatively causal coding variants associated with 202 endpoints, 104 with low allele frequency (AF<10%) of which 62 were over two-fold enriched in Finland.We studied a benchmark set of 15 diseases that had previously been investigated in large genome-wide association studies. FinnGen discovery analyses were meta-analysed in Estonian and UK biobanks. We identify 30 novel associations, primarily low-frequency variants strongly enriched, in or specific to, the Finnish population and Uralic language family neighbors in Estonia and Russia.These findings demonstrate the power of bottlenecked populations to find unique entry points into the biology of common diseases through low-frequency, high impact variants. Such high impact variants have a potential to contribute to medical translation including drug discovery.

Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10−8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.

Myeloproliferative neoplasms (MPNs) are blood cancers characterized by excessive production of mature myeloid cells, which result from the acquisition of somatic driver mutations in hematopoietic stem cells (HSCs). Epidemiologic studies indicate a substantial disease heritability that is among the highest known for cancers 1 . However, only a limited set of genetic risk loci have been identified, and the underlying biological mechanisms leading to MPN acquisition remain unexplained. Here, we conducted a large-scale genome-wide association study (3,797 cases and 1,152,977 controls) to identify 17 MPN risk loci (p < 5.0 × 10 −8 ), seven of which have not been previously reported. We find a shared genetic architecture between MPN risk and several hematopoietic traits spanning distinct lineages, an enrichment for risk variants mapping to accessible chromatin in HSCs, and associations of increased MPN risk with longer leukocyte telomere length and other clonal hematopoietic states, collectively implicating HSC function and self-renewal. Gene mapping identifies modulators of HSC biology and targeted variant-to-function assays suggest likely roles for CHEK2 and GFI1B in altering HSC function to confer disease risk. Overall, we demonstrate the power of human genetic studies to illuminate a previously unappreciated mechanism for inherited MPN risk through modulation of HSC function.

Analyzing 5770 all-cause cirrhosis cases and 572,850 controls from seven cohorts, we identify a missense variant in the Mitochondrial Amidoxime Reducing Component 1 gene (MARC1 p.A165T) that associates with protection from all-cause cirrhosis (OR 0.88, p=2.1*10−8). This same variant also associates with lower levels of hepatic fat on computed tomographic imaging and lower odds of physician-diagnosed fatty liver as well as lower blood levels of alanine transaminase (−0.012 SD, 1.4*10−8), alkaline phosphatase (−0.019 SD, 6.6*10−9), total cholesterol (−0.037 SD, p=1*10−18) and LDL cholesterol (−0.035 SD, p=7.3*10−16). Carriers of rare protein-truncating variants in MARC1 had lower liver enzyme levels, cholesterol levels, and reduced odds of liver disease (OR 0.19, p= 0.04) suggesting that deficiency of the MARC1 enzyme protects against cirrhosis.

Analyzing 12,361 all-cause cirrhosis cases and 790,095 controls from eight cohorts, we identify a common missense variant in the Mitochondrial Amidoxime Reducing Component