Sanni Ruotsalainen

Abstract 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 explored 1,2 . 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.

ABSTRACT 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.

Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. Here, we performed a genome-wide association study of 102,084 migraine cases and 771,257 controls and identified 123 loci, of which 86 are previously unknown. These loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. Stratification of the risk loci using 29,679 cases with subtype information indicated three risk variants that seem specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that seem specific for migraine without aura (near SPINK2 and near FECH) and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types, supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.

AIMS: The metabolic syndrome (MetS) is defined as a clustering of cardiovascular risk factors characterized by insulin resistance. We investigated the relationship of the MetS and its single components, defined by all six different criteria, with coronary heart disease (CHD), cardiovascular disease (CVD), and all-cause mortality in a prospective population-based study. METHODS AND RESULTS: The MetS was defined according to the World Health Organization (WHO), the European Group for the Study of Insulin Resistance (EGIR), the National Cholesterol Education Program (NCEP), the American College of Endocrinology (ACE), the International Diabetes Federation (IDF), and the American Heart Association (updated NCEP) criteria. We investgated the relationship of the MetS defined by aforementioned six criteria with CHD, CVD, and all-cause mortality with Cox regression analyses in a non-diabetic Finnish population of 1025 subjects, aged 65-74 years, during the 13-year follow-up. The MetS defined by all aforementioned criteria was associated with a statistically significant risk for CVD mortality when adjusted for all confounding variables (Hazards Ratios, HRs from 1.31 to 1.51). The MetS defined by the WHO, ACE, and IDF criteria was associated with an increased risk of CHD mortality (HRs from 1.42 to 1.58). There was no association between the MetS by any criteria and all-cause mortality. Of the single components of the MetS, the following predicted CVD mortality in multivariable models: impaired fasting glucose by the WHO, NCEP, and ACE criteria (HR 1.34) and by the IDF and updated NCEP criteria (HR 1.29); impaired glucose tolerance by the WHO and ACE criteria (HR 1.55); low HDL cholesterol by the EGIR criteria (HR 1.50) and by the NCEP, IDF, and updated NCEP criteria (HR 1.29); and microalbuminuria according to the WHO definition (HR 1.86). CONCLUSION: The MetS defined by all six current criteria predicts CVD mortality in elderly subjects. However, of the single components of the MetS, IFG, IGT, low HDL cholesterol, and microalbuminuria predicted CVD mortality with equal or higher HRs when compared with the different definitions of the MetS. Therefore, our study suggests that the MetS is a marker of CVD risk, but not above and beyond the risk associated with its individual components.