FinnGen provides genetic insights from a well-phenotyped isolated population.
Mitja I KurkiJuha KarjalainenPriit PaltaTimo P SipiläKati KristianssonKati M DonnerMary P ReeveHannele LaivuoriMervi AavikkoMari A KaunistoAnu LoukolaElisa LahtelaHannele MattssonPäivi LaihoPietro Della Briotta ParoloArto A LehistoMasahiro KanaiNina MarsJoel RämöTuomo KiiskinenHenrike O HeyneKumar VeerapenSina RüegerSusanna LemmeläWei ZhouSanni RuotsalainenKalle PärnTero HiekkalinnaSami KoskelainenTeemu PaajanenVincent LlorensJavier Gracia-TabuencaHarri SiirtolaKadri ReisAbdelrahman G ElnahasBenjamin SunChristopher N FoleyKatriina Aalto-SetäläKaur AlasooMikko ArvasKirsi AuroShameek BiswasArgyro Bizaki-VallaskangasOlli CarpenChia-Yen ChenOluwaseun A DadaZhihao DingMargaret G EhmKari EklundMartti FärkkiläHilary FinucaneAndrea GannaAwaisa GhazalRobert R GrahamEric M GreenAntti HakanenMarco HautalahtiÅsa K HedmanMikko HiltunenReetta HinttalaIiris HovattaXinli HuAdriana Huertas-VazquezLaura HuilajaJulie HunkapillerHoward JacobJan-Nygaard JensenHeikki JoensuuSally JohnValtteri JulkunenMarc JungJuhani JunttilaKai KaarnirantaMika KähönenRisto KajanneLila KallioReetta KälviäinenJaakko Kaprionull nullNurlan KerimovJohannes KettunenElina KilpeläinenTerhi KilpiKatherine KlingerVeli-Matti KosmaTeijo KuopioVenla KurraTriin LaiskJari LaukkanenNathan LawlessAoxing LiuSimonne LongerichReedik MägiJohanna MäkeläAntti MäkitieAnders MalarstigArto MannermaaJoseph MaranvilleAthena MatakidouTuomo MeretojaSahar V MozaffariMari E K NiemiMarianna NiemiTeemu NiiranenChristopher J O DonnellMa En ObeidatGeorge OkafoHanna M OllilaAntti PalomäkiTuula PalotieJukka PartanenDirk S PaulMargit PelkonenRion K PendergrassSlavé PetrovskiAnne PitkärantaAdam PlattDavid PulfordEero PunkkaPirkko PussinenNeha RaghavanFedik RahimovDeepak RajpalNicole A RenaudBridget Riley-GillisRodosthenis RodosthenousElmo SaarentausAino SalminenEveliina SalminenVeikko SalomaaJohanna SchleutkerRaisa SerpiHuei-Yi ShenRichard SiegelKaisa SilanderSanna SiltanenSirpa SoiniHilkka SoininenJae Hoon SulIoanna TachmazidouKaisa TasanenPentti TienariSanna Toppila-SalmiTaru TukiainenTiinamaija TuomiJoni A TurunenJacob C UlirschFelix VauraPetri VirolainenJeffrey WaringDawn WaterworthRobert YangMari NelisAnu ReigoAndres MetspaluLili MilaniTõnu EskoCaroline FoxAki S HavulinnaMarkus PerolaSamuli RipattiAnu JalankoTarja LaitinenTomi P MäkeläRobert PlengeMark McCarthyHeiko RunzMark J DalyAarno PalotiePublished in: Nature (2023)
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.