Cited by 4,233Genetic Associations and EpidemiologyGenomics and Rare DiseasesForensic and Genetic Research

FinnGen provides genetic insights from a well-phenotyped isolated population

Open access
Kurki, Mitja I., Karjalainen, Juha, Palta, Priit, Sipilä, Timo P., Kristiansson, Kati, Donner, Kati M., Reeve, Mary P., Laivuori, Hannele +161 more·2023·Nature

Abstract

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.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41586-022-05473-8

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • FinnGen is a biobank-scale cohort integrating genotype data from approximately 500,000 Finnish participants with longitudinal health information derived from national registries.

    “FinnGen is a biobank-scale cohort integrating genotype data from approximately 500,000 Finnish participants with longitudinal health information derived from national registries.”

    From Protective PLCG2 variants associate with a delayed onset of Alzheimer’s disease among heterozygous APOE ε4 carriers (2026) · cites this paper as [16]

    The Main section and Methods > Biobank samples confirm that FinnGen links genotype data from Finnish biobanks to longitudinal national health-register data. But the paper describes 500,000 participants as a goal, not the size of the genotyped cohort reported here: 412,000 samples had been collected and 224,737 participants were included in the study. (LLM, conf=0.91)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 64 · Cited by 4,233

Research works printed but not linked: 52

  1. [2]Xue Y Enrichment of low-frequency functional variants revealed by whole-genome sequencing of multiple isolated European populations Nat. Commun. 2017 8 15927 10.1038/ncomms15927 28643794 PMC5490002 · DOI
  2. [4]Norio R The Finnish Disease Heritage III: the individual diseases Hum. Genet. 2003 112 470 526 10.1007/s00439-002-0877-1 12627297 · DOI
  3. [6]Bycroft C The UK Biobank resource with deep phenotyping and genomic data Nature 2018 562 203 209 10.1038/s41586-018-0579-z 30305743 PMC6786975 · DOI · Paper page
  4. [7]Kerminen S Fine-scale genetic structure in Finland G3 2017 7 3459 3468 10.1534/g3.117.300217 28983069 PMC5633394 · DOI
  5. [8]Ritari, J., Koskela, S., Hyvärinen, K., FinnGen & Partanen, J. HLA-disease association and pleiotropy landscape in over 235,000 Finns. Hum. Immunol.83, 391–398 (2022). 35221124
  6. [9]Karczewski KJ The mutational constraint spectrum quantified from variation in 141,456 humans Nature 2020 581 434 443 10.1038/s41586-020-2308-7 32461654 PMC7334197 · DOI · Paper page
  7. [10]Kanai, M. et al. Insights from complex trait fine-mapping across diverse populations. Preprint at medRxiv10.1101/2021.09.03.21262975 (2021).
  8. [11]Sakaue S A cross-population atlas of genetic associations for 220 human phenotypes Nat. Genet. 2021 53 1415 1424 10.1038/s41588-021-00931-x 34594039 PMC12208603 · DOI
  9. [12]Sun BB Genetic associations of protein-coding variants in human disease Nature 2022 603 95 102 10.1038/s41586-022-04394-w 35197637 PMC8891017 · DOI
  10. [13]Heyne, H. O. et al. Mono- and biallelic effects of on disease at biobank scale. Nature10.1038/s41586-022-05420-7 (2022). PMC9849130 36653560
  11. [14]Patel KA Heterozygous RFX6 protein truncating variants are associated with MODY with reduced penetrance Nat. Commun. 2017 8 888 10.1038/s41467-017-00895-9 29026101 PMC5638866 · DOI
  12. [15]Norberg A Novel variants in Nordic patients referred for genetic testing of telomere-related disorders Eur. J. Hum. Genet. 2018 26 858 867 10.1038/s41431-018-0112-8 29483670 PMC5974393 · DOI
  13. [17]Jiang X-C Yu Y The role of phospholipid transfer protein in the development of atherosclerosis Curr. Atheroscler. Rep. 2021 23 9 10.1007/s11883-021-00907-6 33496859 PMC8006745 · DOI
  14. [19]van der Harst P Verweij N Identification of 64 novel genetic loci provides an expanded view on the genetic architecture of coronary artery disease Circ. Res. 2018 122 433 443 10.1161/CIRCRESAHA.117.312086 29212778 PMC5805277 · DOI · Paper page
  15. [20]Shadrina AS Prioritization of causal genes for coronary artery disease based on cumulative evidence from experimental and in silico studies Sci. Rep. 2020 10 10486 10.1038/s41598-020-67001-w 32591598 PMC7320185 · DOI
  16. [21]Dimitra A HHIPL1, a gene at the 14q32 coronary artery disease locus, positively regulates hedgehog signaling and promotes atherosclerosis Circulation 2019 140 500 513 10.1161/CIRCULATIONAHA.119.041059 31163988 PMC6686954 · DOI
  17. [22]Bindesbøll C NBEAL1 controls SREBP2 processing and cholesterol metabolism and is a susceptibility locus for coronary artery disease Sci. Rep. 2020 10 4528 10.1038/s41598-020-61352-0 32161285 PMC7066131 · DOI
  18. [23]Graydon, C. G., Mohideen, S. & Fowke, K. R. LAG3’s enigmatic mechanism of action. Front. Immunol.10.3389/fimmu.2020.615317 (2021). PMC7820757 33488626 · DOI
  19. [24]No authors listed. FDA approves anti-LAG3 checkpoint Nat. Biotechnol. 2022 40 625 10.1038/s41587-022-01331-0 35577946 · DOI
  20. [25]Boer CG Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations Cell 2021 184 4784 4818.e17 10.1016/j.cell.2021.07.038 34450027 PMC8459317 · DOI
  21. [26]Sliz E Uniting biobank resources reveals novel genetic pathways modulating susceptibility for atopic dermatitis J. Allergy Clin. Immunol. 2022 149 1105 1112.e9 10.1016/j.jaci.2021.07.043 34454985 · DOI
  22. [27]Li J Utility of basophil activation test for predicting the outcome of wheezing in children: a pilot study BMC Immunol. 2021 22 4 10.1186/s12865-020-00395-4 33407109 PMC7788708 · DOI
  23. [28]Chakraborti S Natarajan K Curiel J Janke C Liu J The emerging role of the tubulin code: from the tubulin molecule to neuronal function and disease Cytoskeleton 2016 73 521 550 10.1002/cm.21290 26934450 · DOI
  24. [29]Sharifinejad N Clinical, immunological, and genetic features in 49 patients with ZAP-70 deficiency: a systematic review Front. Immunol. 2020 11 831 10.3389/fimmu.2020.00831 32431715 PMC7214800 · DOI
  25. [30]Mulford AJ Wing C Dolan ME Wheeler HE Genetically regulated expression underlies cellular sensitivity to chemotherapy in diverse populations Hum. Mol. Genet. 2021 30 305 317 10.1093/hmg/ddab029 33575800 PMC8248963 · DOI
  26. [31]Mafra F Copy number variation analysis reveals additional variants contributing to endometriosis development J. Assist. Reprod. Genet. 2017 34 117 124 10.1007/s10815-016-0822-1 27817035 PMC5330977 · DOI
  27. [32]Koskela, J. T. et al. Genetic variant in SPDL1 reveals novel mechanism linking pulmonary fibrosis risk and cancer protection. Preprint at medRxiv10.1101/2021.05.07.21255988 (2021).
  28. [33]Ruotsalainen SE Inframe insertion and splice site variants in MFGE8 associate with protection against coronary atherosclerosis Commun. Biol. 2022 5 802 10.1038/s42003-022-03552-0 35978133 PMC9385630 · DOI
  29. [34]Rämö, J. T. et al. Genome-wide screen of otosclerosis in population biobanks: 27 loci and shared associations with skeletal structure. Nat. Commun.10.1038/s41467-022-32936-3 (2023). PMC9849444 36653343 · DOI
  30. [35]Tanigawa Y Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma PLoS Genet. 2020 16 e1008682 10.1371/journal.pgen.1008682 32369491 PMC7199928 · DOI
  31. [36]Surakka I The impact of low-frequency and rare variants on lipid levels Nat. Genet. 2015 47 589 597 10.1038/ng.3300 25961943 PMC4757735 · DOI · Paper page
  32. [37]Ehrhardt N Hepatic Tm6sf2 overexpression affects cellular ApoB-trafficking, plasma lipid levels, hepatic steatosis and atherosclerosis Hum. Mol. Genet. 2017 26 2719 2731 10.1093/hmg/ddx159 28449094 PMC5886214 · DOI
  33. [38]Prill S The TM6SF2 E167K genetic variant induces lipid biosynthesis and reduces apolipoprotein B secretion in human hepatic 3D spheroids Sci. Rep. 2019 9 11585 10.1038/s41598-019-47737-w 31406127 PMC6690969 · DOI
  34. [39]Pirola CJ Sookoian S The dual and opposite role of the TM6SF2-rs58542926 variant in protecting against cardiovascular disease and conferring risk for nonalcoholic fatty liver: a meta-analysis Hepatology 2015 62 1742 1756 10.1002/hep.28142 26331730 · DOI
  35. [41]Tang S Association of TM6SF2 rs58542926 T/C gene polymorphism with hepatocellular carcinoma: a meta-analysis BMC Cancer 2019 19 1128 10.1186/s12885-019-6173-4 31752753 PMC6868855 · DOI
  36. [42]Kim DS Novel association of TM6SF2 rs58542926 genotype with increased serum tyrosine levels and decreased apoB-100 particles in Finns J. Lipid Res. 2017 58 1471 1481 10.1194/jlr.P076034 28539357 PMC5496043 · DOI
  37. [43]Mars N Polygenic and clinical risk scores and their impact on age at onset and prediction of cardiometabolic diseases and common cancers Nat. Med. 2020 26 549 557 10.1038/s41591-020-0800-0 32273609 · DOI
  38. [44]Kiiskinen T Genomic prediction of alcohol-related morbidity and mortality Transl Psychiatry 2020 10 23 10.1038/s41398-019-0676-2 32066667 PMC7026428 · DOI
  39. [45]Strausz S Genetic analysis of obstructive sleep apnoea discovers a strong association with cardiometabolic health Eur. Respir. J. 2021 57 2003091 10.1183/13993003.03091-2020 33243845 · DOI · Paper page
  40. [46]Helkkula, P. et al. ANGPTL8 protein-truncating variant associated with lower serum triglycerides and risk of coronary disease. PLoS Genet.17, e1009501 (2021). PMC8109807 33909604
  41. [47]Rahimov, F. et al. High incidence and regional distribution of cleft palate in Finns are associated with a functional variant in an IRF6 enhancer. Preprint at Research Square10.21203/rs.3.rs-941741/v1 (2021).
  42. [48]Niemi, M. E. K. et al. Mapping the human genetic architecture of COVID-19. Nature10.1038/s41586-021-03767-x (2021). PMC8674144 34237774
  43. [49]Zhou, W. et al. Global Biobank Meta-analysis Initiative: powering genetic discovery across human disease. Cell Genom.2, 100192 (2022). PMC9903716 36777996
  44. [50]Broekema RV Bakker OB Jonkers IH A practical view of fine-mapping and gene prioritization in the post-genome-wide association era Open Biol. 2020 10 190221 10.1098/rsob.190221 31937202 PMC7014684 · DOI
  45. [51]Fry A Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population Am. J. Epidemiol. 2017 186 1026 1034 10.1093/aje/kwx246 28641372 PMC5860371 · DOI · Paper page
  46. [54]Zhou W Efficiently controlling for case–control imbalance and sample relatedness in large-scale genetic association studies Nat. Genet. 2018 50 1335 1341 10.1038/s41588-018-0184-y 30104761 PMC6119127 · DOI
  47. [55]Wang G Sarkar A Carbonetto P Stephens M A simple new approach to variable selection in regression, with application to genetic fine mapping J. R. Stat. Soc. Ser. B Stat. Methodol. 2020 82 1273 1300 10.1111/rssb.12388 PMC10201948 37220626 · DOI · Paper page
  48. [56]Gagliano Taliun SA Exploring and visualizing large-scale genetic associations by using PheWeb Nat. Genet. 2020 52 550 552 10.1038/s41588-020-0622-5 32504056 PMC7754083 · DOI
  49. [57]Mitt M Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel Eur. J. Hum. Genet. 2017 25 869 876 10.1038/ejhg.2017.51 28401899 PMC5520064 · DOI
  50. [61]Kerimov N A compendium of uniformly processed human gene expression and splicing quantitative trait loci Nat. Genet. 2021 53 1290 1299 10.1038/s41588-021-00924-w 34493866 PMC8423625 · DOI · Paper page
  51. [62]Ochoa D Open Targets Platform: supporting systematic drug–target identification and prioritisation Nucleic Acids Res. 2021 49 D1302 D1310 10.1093/nar/gkaa1027 33196847 PMC7779013 · DOI
  52. [64]Buniello A The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019 Nucleic Acids Res. 2019 47 D1005 D1012 10.1093/nar/gky1120 30445434 PMC6323933 · DOI · Paper page

Authors
Kurki, M. I., Karjalainen, J., Palta, P., Sipilä, T. P., Kristiansson, K., Donner, K. M., Reeve, M. P., Laivuori, H., Aavikko, M., Kaunisto, M. A., Loukola, A., Lahtela, E., Mattsson, H., Laiho, P., Della Briotta Parolo, P., Lehisto, A. A., Kanai, M., Mars, N., Rämö, J., Kiiskinen, T., Heyne, H. O., Veerapen, K., Rüeger, S., Lemmelä, S., Zhou, W., Ruotsalainen, S., Pärn, K., Hiekkalinna, T., Koskelainen, S., Paajanen, T., Llorens, V., Gracia-Tabuenca, J., Siirtola, H., Reis, K., Elnahas, A. G., Sun, B., Foley, C. N., Aalto-Setälä, K., Alasoo, K., Arvas, M., Auro, K., Biswas, S., Bizaki-Vallaskangas, A., Carpen, O., Chen, C.-Y., Dada, O. A., Ding, Z., Ehm, M. G., Eklund, K., Färkkilä, M., Finucane, H., Ganna, A., Ghazal, A., Graham, R. R., Green, E. M., Hakanen, A., Hautalahti, M., Hedman, Å. K., Hiltunen, M., Hinttala, R., Hovatta, I., Hu, X., Huertas-Vazquez, A., Huilaja, L., Hunkapiller, J., Jacob, H., Jensen, J.-N., Joensuu, H., John, S., Julkunen, V., Jung, M., Junttila, J., Kaarniranta, K., Kähönen, M., Kajanne, R., Kallio, L., Kälviäinen, R., Kaprio, J., FinnGen, Kerimov, N., Kettunen, J., Kilpeläinen, E., Kilpi, T., Klinger, K., Kosma, V.-M., Kuopio, T., Kurra, V., Laisk, T., Laukkanen, J., Lawless, N., Liu, A., Longerich, S., Mägi, R., Mäkelä, J., Mäkitie, A., Malarstig, A., Mannermaa, A., Maranville, J., Matakidou, A., Meretoja, T., Mozaffari, S. V., Niemi, M. E. K., Niemi, M., Niiranen, T., O´Donnell, C. J., Obeidat, M., Okafo, G., Ollila, H. M., Palomäki, A., Palotie, T., Partanen, J., Paul, D. S., Pelkonen, M., Pendergrass, R. K., Petrovski, S., Pitkäranta, A., Platt, A., Pulford, D., Punkka, E., Pussinen, P., Raghavan, N., Rahimov, F., Rajpal, D., Renaud, N. A., Riley-Gillis, B., Rodosthenous, R., Saarentaus, E., Salminen, A., Salminen, E., Salomaa, V., Schleutker, J., Serpi, R., Shen, H.-Y., Siegel, R., Silander, K., Siltanen, S., Soini, S., Soininen, H., Sul, J. H., Tachmazidou, I., Tasanen, K., Tienari, P., Toppila-Salmi, S., Tukiainen, T., Tuomi, T., Turunen, J. A., Ulirsch, J. C., Vaura, F., Virolainen, P., Waring, J., Waterworth, D., Yang, R., Nelis, M., Reigo, A., Metspalu, A., Milani, L., Esko, T., Fox, C., Havulinna, A. S., Perola, M., Ripatti, S., Jalanko, A., Laitinen, T., Mäkelä, T. P., Plenge, R., McCarthy, M., Runz, H., Daly, M. J., & Palotie, A.
Affiliations
  • Broad Institute (US)
  • University of Helsinki (FI)
  • Finnish Institute for Health and Welfare (FI)
  • Tampere University (FI)
  • University of Tartu (EE)
  • Biogen (United States) (US)
  • University of Cambridge (GB)
  • Finnish Red Cross (FI)
  • Glaxosmithkline (Finland) (FI)
  • Bristol-Myers Squibb (United States) (US)
  • Tampere University Hospital (FI)
  • Boehringer Ingelheim (Germany) (DE)
  • GlaxoSmithKline (United States) (US)
  • Helsinki University Hospital (FI)
  • Maze (United States) (US)
  • University of Turku (FI)
  • Pfizer (United States) (US)
  • Oulu University Hospital (FI)
  • Genentech (US)
  • AbbVie (United States) (US)
  • University of Eastern Finland (FI)
  • Northern Ostrobothnia Hospital District (FI)
  • Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
  • AstraZeneca (United Kingdom) (GB)
  • Janssen (Belgium) (BE)
Corresponding author
Palotie, Aarno
ORCID
Venue
Nature
Published
2023-01-18
Volume
613
Issue
7944
Pages
508-518
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W4317390883
Cited by
4,233
References
64
Citations by year
2026: 900 · 2025: 1498 · 2024: 1455 · 2023: 376 · 2022: 1 · 2016: 1
FWCI
721.84
Type
journal article
Language
en
Open access
Locations
  • Nature (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Työväentutkimus Vuosikirja (submittedVersion)
  • Tampere University Institutional Repository (Tampere University) (submittedVersion, cc-by)
  • STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
  • Apollo
  • Apollo (cc-by)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
Keywords
FinnGen, isolated populations, founder effect, low-frequency variants, phenome-wide association study, fine mapping, disease loci, Finnish population
MeSH terms
Disease, Estonia, Finland, Gene Frequency, United Kingdom, Humans, Middle Aged, Phenotype, Meta-Analysis as Topic, Genetic Predisposition to Disease, White People, Genome-Wide Association Study

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review