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.

There is currently limited understanding of the genetic aetiology of obstructive sleep apnoea (OSA). We aimed at identifying genetic loci associated with OSA risk and to test if OSA and its comorbidities share a common genetic background.We conducted the first large-scale genome-wide association study of OSA using FinnGen Study (217 955 individuals) with 16 761 OSA patients identified using nationwide health registries.We estimated 8.3% [0.06–0.11] heritability and identified five loci associated with OSA (p<5.0×10−8): rs4837016 near GTPase activating protein and VPS9 domains 1 (GAPVD1), rs10928560 near C-X-C motif chemokine receptor 4 (CXCR4), rs185932673 near Calcium/calmodulin-dependent protein kinase ID (CAMK1D) and rs9937053 near Fat mass and obesity-associated protein (FTO) - a variant previously associated with body mass index (BMI). In a BMI-adjusted analysis, an association was observed for rs10507084 near Rhabdomyosarcoma 2 associated transcript (RMST)/NEDD1 gamma-tubulin ring complex targeting factor (NEDD1). We found high genetic correlations between OSA and BMI (rg=0.72 [0.62–0.83]) and with comorbidities including hypertension, type 2 diabetes (T2D), coronary heart disease (CHD), stroke, depression, hypothyroidism, asthma and inflammatory rheumatic diseases (IRD) (rg>0.30). Polygenic risk score (PRS) for BMI showed 1.98-fold increased OSA risk between the highest and the lowest quintile and Mendelian randomisation supported a causal relationship between BMI and OSA.Our findings support the causal link between obesity and OSA and joint genetic basis between OSA and comorbidities.

Background: Hyperlipidemia is a highly heritable risk factor for coronary artery disease (CAD). While monogenic familial hypercholesterolemia associates with severely increased CAD risk, it remains less clear to what extent a high polygenic load of a large number of LDL (low-density lipoprotein) cholesterol (LDL-C) or triglyceride (TG)-increasing variants associates with increased CAD risk. Methods: We derived polygenic risk scores (PRSs) with ≈6M variants separately for LDL-C and TG with weights from a UK Biobank–based genome-wide association study with ≈324K samples. We evaluated the impact of polygenic hypercholesterolemia and hypertriglyceridemia to lipid levels in 27 039 individuals from the National FINRISK Study (FINRISK) cohort and to CAD risk in 135 638 individuals (13 753 CAD cases) from the FinnGen project (FinnGen). Results: In FINRISK, median LDL-C was 3.39 (95% CI, 3.38–3.40) mmol/L, and it ranged from 2.87 (95% CI, 2.82–2.94) to 3.78 (95% CI, 3.71–3.83) mmol/L between the lowest and highest 5% of the LDL-C PRS distribution. Median TG was 1.19 (95% CI, 1.18–1.20) mmol/L, ranging from 0.97 (95% CI, 0.94–1.00) to 1.55 (95% CI, 1.48–1.61) mmol/L with the TG PRS. In FinnGen, comparing the highest 5% of the PRS to the lowest 95%, CAD odds ratio was 1.36 (95% CI, 1.24–1.49) for the LDL-C PRS and 1.31 (95% CI, 1.19–1.43) for the TG PRS. These estimates were only slightly attenuated when adjusting for a CAD PRS (odds ratio, 1.26 [95% CI, 1.16–1.38] for LDL-C and 1.24 [95% CI, 1.13–1.36] for TG PRS). Conclusions: The CAD risk associated with a high polygenic load for lipid-increasing variants was proportional to their impact on lipid levels and partially overlapping with a CAD PRS. In contrast with a PRS for CAD, the lipid PRSs point to known and directly modifiable risk factors providing additional guidance for clinical translation.