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Han AL, Sands CF, Matelska D, Butts JC, Ravanmehr V, Hu F, Villavicencio Gonzalez E, Katsanis N, Bustamante CD, Wang Q, Petrovski S, Vitsios D, Dhindsa RS. Diverse ancestral representation improves genetic intolerance metrics. Nat Commun 2025; 16:2648. [PMID: 40102419 PMCID: PMC11920395 DOI: 10.1038/s41467-025-57885-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Accepted: 03/05/2025] [Indexed: 03/20/2025] Open
Abstract
The unprecedented scale of genomic databases has revolutionized our ability to identify regions in the human genome intolerant to variation-regions often implicated in disease. However, these datasets remain constrained by limited ancestral diversity. Here, we analyze whole-exome sequencing data from 460,551 UK Biobank and 125,748 Genome Aggregation Database (gnomAD) participants across multiple ancestries to test several key intolerance metrics, including the Residual Variance Intolerance Score (RVIS), Missense Tolerance Ratio (MTR), and Loss-of-Function Observed/Expected ratio (LOF O/E). We demonstrate that increasing ancestral representation, rather than sample size alone, critically drives their performance. Scores trained on variation observed in African and Admixed American ancestral groups show higher resolution in detecting haploinsufficient and neurodevelopmental disease risk genes compared to scores trained on European ancestry groups. Most strikingly, MTR trained on 43,000 multi-ancestry exomes demonstrates greater predictive power than when trained on a nearly 10-fold larger dataset of 440,000 non-Finnish European exomes. We further find that European ancestry group-based scores are likely approaching saturation. These findings highlight the need for enhanced population representation in genomic resources to fully realize the potential of precision medicine and drug discovery. Ancestry group-specific scores are publicly available through an interactive portal: http://intolerance.public.cgr.astrazeneca.com/ .
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Affiliation(s)
- Alexander L Han
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Chloe F Sands
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Dorota Matelska
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Jessica C Butts
- Department of Bioengineering, George R. Brown School of Engineering, Rice University, Houston, TX, USA
- Rice Neuroengineering Initiative, George R. Brown School of Engineering, Rice University, Houston, TX, USA
| | - Vida Ravanmehr
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Fengyuan Hu
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Esmeralda Villavicencio Gonzalez
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Quanli Wang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
| | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.
- Department of Medicine, Austin Health, University of Melbourne, Melbourne, VIC, Australia.
| | - Dimitrios Vitsios
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Ryan S Dhindsa
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA.
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA.
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
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2
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Ciantar J, Marttila S, Rajić S, Kostiniuk D, Mishra PP, Lyytikäinen LP, Mononen N, Kleber ME, März W, Kähönen M, Raitakari O, Lehtimäki T, Raitoharju E. Identification and functional characterisation of DNA methylation differences between East- and West-originating Finns. Epigenetics 2024; 19:2397297. [PMID: 39217505 PMCID: PMC11382697 DOI: 10.1080/15592294.2024.2397297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 08/14/2024] [Accepted: 08/22/2024] [Indexed: 09/04/2024] Open
Abstract
Eastern and Western Finns show a striking difference in coronary heart disease-related mortality; genetics is a known contributor for this discrepancy. Here, we discuss the potential role of DNA methylation in mediating the discrepancy in cardiometabolic disease-risk phenotypes between the sub-populations. We used data from the Young Finns Study (n = 969) to compare the genome-wide DNA methylation levels of East- and West-originating Finns. We identified 21 differentially methylated loci (FDR < 0.05; Δβ >2.5%) and 7 regions (smoothed FDR < 0.05; CpGs ≥ 5). Methylation at all loci and regions associates with genetic variants (p < 5 × 10-8). Independently of genetics, methylation at 11 loci and 4 regions associates with transcript expression, including genes encoding zinc finger proteins. Similarly, methylation at 5 loci and 4 regions associates with cardiometabolic disease-risk phenotypes including triglycerides, glucose, cholesterol, as well as insulin treatment. This analysis was also performed in LURIC (n = 2371), a German cardiovascular patient cohort, and results replicated for the association of methylation at cg26740318 and DMR_11p15 with diabetes-related phenotypes and methylation at DMR_22q13 with triglyceride levels. Our results indicate that DNA methylation differences between East and West Finns may have a functional role in mediating the cardiometabolic disease discrepancy between the sub-populations.
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Affiliation(s)
- Joanna Ciantar
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Saara Marttila
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Gerontology Research Center, Tampere University, Tampere, Finland
- Tays Research Services, Wellbeing Services County of Pirkanmaa, Tampere University Hospital, Tampere, Finland
| | - Sonja Rajić
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Daria Kostiniuk
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Nina Mononen
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Marcus E Kleber
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, Heidelberg University, Mannheim, Germany
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Winfried März
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, Heidelberg University, Mannheim, Germany
- Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim, Germany
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Emma Raitoharju
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories, Tampere, Finland
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3
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Deal M, Kar A, Lee SHT, Alvarez M, Rajkumar S, Arasu UT, Kaminska D, Männistö V, Heinonen S, van der Kolk BW, Säiläkivi U, Saarinen T, Juuti A, Pihlajamäki J, Kaikkonen MU, Laakso M, Pietiläinen KH, Pajukanta P. An abdominal obesity missense variant in the adipocyte thermogenesis gene TBX15 is implicated in adaptation to cold in Finns. Am J Hum Genet 2024; 111:2542-2560. [PMID: 39515300 PMCID: PMC11568758 DOI: 10.1016/j.ajhg.2024.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Revised: 09/26/2024] [Accepted: 10/01/2024] [Indexed: 11/16/2024] Open
Abstract
Mechanisms of abdominal obesity GWAS variants have remained largely unknown. To elucidate these mechanisms, we leveraged subcutaneous adipose tissue (SAT) single nucleus RNA-sequencing and genomics data. After discovering that heritability of abdominal obesity is enriched in adipocytes, we focused on a SAT unique adipocyte marker gene, the transcription factor TBX15, and its abdominal obesity-associated deleterious missense variant, rs10494217. The allele frequency of rs10494217 revealed a north-to-south decreasing gradient, with consistent significant FST values observed for 25 different populations when compared to Finns, a population with a history of genetic isolation. Given the role of Tbx15 in mouse thermogenesis, the frequency may have increased as an adaptation to cold in Finns. Our selection analysis provided significant evidence of selection for the abdominal obesity risk allele T of rs10494217 in Finns, with a north-to-south decreasing trend in other populations, and demonstrated that latitude significantly predicts the allele frequency. We also discovered that the risk allele status significantly affects SAT adipocyte expression of multiple adipocyte marker genes in trans in two cohorts. Two of these trans genes have been connected to thermogenesis, supporting the thermogenic effect of the TBX15 missense variant as a possible cause of its selection. Adipose expression of one trans gene, a lncRNA, AC002066.1, was strongly associated with adipocyte size, implicating it in metabolically unhealthy adipocyte hypertrophy. In summary, the abdominal obesity variant rs10494217 was selected in Finns, and individuals with the risk allele have trans effects on adipocyte expression of genes relating to thermogenesis and adipocyte hypertrophy.
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Affiliation(s)
- Milena Deal
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Asha Kar
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA; Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA
| | - Seung Hyuk T Lee
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Marcus Alvarez
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sandhya Rajkumar
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Uma Thanigai Arasu
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Dorota Kaminska
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland; Department of Medicine, Division of Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Ville Männistö
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Sini Heinonen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Birgitta W van der Kolk
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Ulla Säiläkivi
- Department of Abdominal Surgery, Abdominal Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Tuure Saarinen
- Department of Abdominal Surgery, Abdominal Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Anne Juuti
- Department of Abdominal Surgery, Abdominal Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Jussi Pihlajamäki
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland; Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, Kuopio, Finland
| | - Minna U Kaikkonen
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland; HealthyWeightHub, Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Päivi Pajukanta
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA; Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA; Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
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4
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Kumpula TA, Vorimo S, Mattila TT, O’Gorman L, Astuti G, Tervasmäki A, Koivuluoma S, Mattila TM, Grip M, Winqvist R, Kuismin O, Moilanen J, Hoischen A, Gilissen C, Mantere T, Pylkäs K. Exome sequencing identified rare recurrent copy number variants and hereditary breast cancer susceptibility. PLoS Genet 2023; 19:e1010889. [PMID: 37578974 PMCID: PMC10449128 DOI: 10.1371/journal.pgen.1010889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 08/24/2023] [Accepted: 07/27/2023] [Indexed: 08/16/2023] Open
Abstract
Copy number variants (CNVs) are a major source of genetic variation and can disrupt genes or affect gene dosage. They are known to be causal or underlie predisposition to various diseases. However, the role of CNVs in inherited breast cancer susceptibility has not been thoroughly investigated. To address this, we performed whole-exome sequencing based analysis of rare CNVs in 98 high-risk Northern Finnish breast cancer cases. After filtering, selected candidate alleles were validated and characterized with a combination of orthogonal methods, including PCR-based approaches, optical genome mapping and long-read sequencing. This revealed three recurrent alterations: a 31 kb deletion co-occurring with a retrotransposon insertion (delins) in RAD52, a 13.4 kb deletion in HSD17B14 and a 64 kb partial duplication of RAD51C. Notably, all these genes encode proteins involved in pathways previously identified as essential for breast cancer development. Variants were genotyped in geographically matched cases and controls (altogether 278 hereditary and 1983 unselected breast cancer cases, and 1229 controls). The RAD52 delins and HSD17B14 deletion both showed significant enrichment among cases with indications of hereditary disease susceptibility. RAD52 delins was identified in 7/278 cases (2.5%, P = 0.034, OR = 2.86, 95% CI = 1.10-7.45) and HSD17B14 deletion in 8/278 cases (2.9%, P = 0.014, OR = 3.28, 95% CI = 1.31-8.23), the frequency of both variants in the controls being 11/1229 (0.9%). This suggests a role for RAD52 and HSD17B14 in hereditary breast cancer susceptibility. The RAD51C duplication was very rare, identified only in 2/278 of hereditary cases and 2/1229 controls (P = 0.157, OR = 4.45, 95% CI = 0.62-31.70). The identification of recurrent CNVs in these genes, and especially the relatively high frequency of RAD52 and HSD17B14 alterations in the Finnish population, highlights the importance of studying CNVs alongside single nucleotide variants when searching for genetic factors underlying hereditary disease predisposition.
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Affiliation(s)
- Timo A. Kumpula
- Laboratory of Cancer Genetics and Tumor Biology, Research Unit of Translational Medicine and Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Sandra Vorimo
- Laboratory of Cancer Genetics and Tumor Biology, Research Unit of Translational Medicine and Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Taneli T. Mattila
- Department of Pathology, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Luke O’Gorman
- Department of Human Genetics and Radboud Institute of Medical Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Galuh Astuti
- Department of Human Genetics and Radboud Institute of Medical Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Anna Tervasmäki
- Laboratory of Cancer Genetics and Tumor Biology, Research Unit of Translational Medicine and Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Susanna Koivuluoma
- Laboratory of Cancer Genetics and Tumor Biology, Research Unit of Translational Medicine and Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Tiina M. Mattila
- Laboratory of Cancer Genetics and Tumor Biology, Research Unit of Translational Medicine and Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Mervi Grip
- Department of Surgery, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Research Unit of Translational Medicine and Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Outi Kuismin
- Department of Clinical Genetics, Medical Research Center Oulu and PEDEGO Research Unit, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Jukka Moilanen
- Department of Clinical Genetics, Medical Research Center Oulu and PEDEGO Research Unit, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Alexander Hoischen
- Department of Human Genetics and Radboud Institute of Medical Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, the Netherlands
| | - Christian Gilissen
- Department of Human Genetics and Radboud Institute of Medical Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Tuomo Mantere
- Laboratory of Cancer Genetics and Tumor Biology, Research Unit of Translational Medicine and Biocenter Oulu, University of Oulu, Oulu, Finland
- Department of Human Genetics and Radboud Institute of Medical Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Katri Pylkäs
- Laboratory of Cancer Genetics and Tumor Biology, Research Unit of Translational Medicine and Biocenter Oulu, University of Oulu, Oulu, Finland
- Northern Finland Laboratory Centre Nordlab, Oulu, Finland
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5
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Nag A, Dhindsa RS, Mitchell J, Vasavda C, Harper AR, Vitsios D, Ahnmark A, Bilican B, Madeyski-Bengtson K, Zarrouki B, Zoghbi AW, Wang Q, Smith KR, Alegre-Díaz J, Kuri-Morales P, Berumen J, Tapia-Conyer R, Emberson J, Torres JM, Collins R, Smith DM, Challis B, Paul DS, Bohlooly-Y M, Snowden M, Baker D, Fritsche-Danielson R, Pangalos MN, Petrovski S. Human genetics uncovers MAP3K15 as an obesity-independent therapeutic target for diabetes. SCIENCE ADVANCES 2022; 8:eadd5430. [PMID: 36383675 PMCID: PMC9668288 DOI: 10.1126/sciadv.add5430] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 09/27/2022] [Indexed: 05/30/2023]
Abstract
We performed collapsing analyses on 454,796 UK Biobank (UKB) exomes to detect gene-level associations with diabetes. Recessive carriers of nonsynonymous variants in MAP3K15 were 30% less likely to develop diabetes (P = 5.7 × 10-10) and had lower glycosylated hemoglobin (β = -0.14 SD units, P = 1.1 × 10-24). These associations were independent of body mass index, suggesting protection against insulin resistance even in the setting of obesity. We replicated these findings in 96,811 Admixed Americans in the Mexico City Prospective Study (P < 0.05)Moreover, the protective effect of MAP3K15 variants was stronger in individuals who did not carry the Latino-enriched SLC16A11 risk haplotype (P = 6.0 × 10-4). Separately, we identified a Finnish-enriched MAP3K15 protein-truncating variant associated with decreased odds of both type 1 and type 2 diabetes (P < 0.05) in FinnGen. No adverse phenotypes were associated with protein-truncating MAP3K15 variants in the UKB, supporting this gene as a therapeutic target for diabetes.
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Affiliation(s)
- Abhishek Nag
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Ryan S. Dhindsa
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
| | - Jonathan Mitchell
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Chirag Vasavda
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
| | - Andrew R. Harper
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Dimitrios Vitsios
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Andrea Ahnmark
- Bioscience Metabolism, Early CVRM, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Bilada Bilican
- Discovery Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Katja Madeyski-Bengtson
- Discovery Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Bader Zarrouki
- Bioscience Metabolism, Early CVRM, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Anthony W. Zoghbi
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
| | - Quanli Wang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
| | - Katherine R. Smith
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Jesus Alegre-Díaz
- Faculty of Medicine, National Autonomous University of Mexico, Copilco Universidad, Coyoacán, 4360 Ciudad de México, Mexico
| | - Pablo Kuri-Morales
- Faculty of Medicine, National Autonomous University of Mexico, Copilco Universidad, Coyoacán, 4360 Ciudad de México, Mexico
| | - Jaime Berumen
- Faculty of Medicine, National Autonomous University of Mexico, Copilco Universidad, Coyoacán, 4360 Ciudad de México, Mexico
| | - Roberto Tapia-Conyer
- Faculty of Medicine, National Autonomous University of Mexico, Copilco Universidad, Coyoacán, 4360 Ciudad de México, Mexico
| | - Jonathan Emberson
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, England, UK
| | - Jason M. Torres
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, England, UK
| | - Rory Collins
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, England, UK
| | - David M. Smith
- Emerging Innovations, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Benjamin Challis
- Translational Science and Experimental Medicine, Early CVRM, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Dirk S. Paul
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Mohammad Bohlooly-Y
- Discovery Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Mike Snowden
- Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - David Baker
- Bioscience Metabolism, Early CVRM, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | | | | | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
- Department of Medicine, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
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6
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Oill AMT, Handley C, Howell EK, Stone AC, Mathew S, Wilson MA. Genomic analysis reveals geography rather than culture as the predominant factor shaping genetic variation in northern Kenyan human populations. AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY 2022; 178:488-503. [PMID: 36790743 PMCID: PMC9949739 DOI: 10.1002/ajpa.24521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 02/04/2022] [Accepted: 02/21/2022] [Indexed: 11/08/2022]
Abstract
OBJECTIVES The aim of this study was to characterize the genetic relationships within and among four neighboring ethnolinguistic groups in northern Kenya in light of cultural relationships to understand the extent to which geography and culture shape patterns of genetic variation. MATERIALS AND METHODS We collected DNA and demographic information pertaining to aspects of social identity and heritage from 572 individuals across the Turkana, Samburu, Waso Borana, and Rendille of northern Kenya. We sampled individuals across a total of nine clans from these four groups and, additionally, three territorial sections within the Turkana and successfully genotyped 376 individuals. RESULTS Here we report that geography predominately shapes genetic variation within and among human groups in northern Kenya. We observed a clinal pattern of genetic variation that mirrors the overall geographic distribution of the individuals we sampled. We also found relatively higher rates of intermarriage between the Rendille and Samburu and evidence of gene flow between them that reflect these higher rates of intermarriage. Among the Turkana, we observed strong recent genetic substructuring based on territorial section affiliation. Within ethnolinguistic groups, we found that Y chromosome haplotypes do not consistently cluster by natal clan affiliation. Finally, we found that sampled populations that are geographically closer have lower genetic differentiation, and that cultural similarity does not predict genetic similarity as a whole across these northern Kenyan populations. DISCUSSION Overall, the results from this study highlight the importance of geography, even on a local geographic scale, in shaping observed patterns of genetic variation in human populations.
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Affiliation(s)
- Angela M. Taravella Oill
- School of Life Sciences, Arizona State University, Tempe, AZ 85287 USA,Center for Evolution and Medicine, Arizona State University, Tempe, AZ 85287 USA
| | - Carla Handley
- School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287 USA
| | - Emma K. Howell
- School of Life Sciences, Arizona State University, Tempe, AZ 85287 USA,Center for Evolution and Medicine, Arizona State University, Tempe, AZ 85287 USA
| | - Anne C. Stone
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ 85287 USA,School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287 USA,Institute of Human Origins, Arizona State University, Tempe, AZ 85287, USA
| | - Sarah Mathew
- School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287 USA,Institute of Human Origins, Arizona State University, Tempe, AZ 85287, USA,Co-corresponding authors
| | - Melissa A. Wilson
- School of Life Sciences, Arizona State University, Tempe, AZ 85287 USA,Center for Evolution and Medicine, Arizona State University, Tempe, AZ 85287 USA,Co-corresponding authors
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7
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Fan C, Mancuso N, Chiang CWK. A genealogical estimate of genetic relationships. Am J Hum Genet 2022; 109:812-824. [PMID: 35417677 PMCID: PMC9118131 DOI: 10.1016/j.ajhg.2022.03.016] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 03/25/2022] [Indexed: 12/23/2022] Open
Abstract
The application of genetic relationships among individuals, characterized by a genetic relationship matrix (GRM), has far-reaching effects in human genetics. However, the current standard to calculate the GRM treats linked markers as independent and does not explicitly model the underlying genealogical history of the study sample. Here, we propose a coalescent-informed framework, namely the expected GRM (eGRM), to infer the expected relatedness between pairs of individuals given an ancestral recombination graph (ARG) of the sample. Through extensive simulations, we show that the eGRM is an unbiased estimate of latent pairwise genome-wide relatedness and is robust when computed with ARG inferred from incomplete genetic data. As a result, the eGRM better captures the structure of a population than the canonical GRM, even when using the same genetic information. More importantly, our framework allows a principled approach to estimate the eGRM at different time depths of the ARG, thereby revealing the time-varying nature of population structure in a sample. When applied to SNP array genotypes from a population sample from Northern and Eastern Finland, we find that clustering analysis with the eGRM reveals population structure driven by subpopulations that would not be apparent via the canonical GRM and that temporally the population model is consistent with recent divergence and expansion. Taken together, our proposed eGRM provides a robust tree-centric estimate of relatedness with wide application to genetic studies.
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Affiliation(s)
- Caoqi Fan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA; Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
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8
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Celinšćak Ž, Zajc Petranović M, Šetinc M, Stojanović Marković A, Peričić Salihović M, Marija Zeljko H, Janićijević B, Smolej Narančić N, Škarić-Jurić T. Pharmacogenetic distinction of the Croatian population from the European average. Croat Med J 2022; 63:117-125. [PMID: 35505645 PMCID: PMC9086818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 02/09/2022] [Indexed: 09/17/2023] Open
Abstract
AIM To compare the Croatian and European population in terms of allele frequencies of clinically relevant polymorphisms in drug absorption, distribution, metabolism, and excretion (ADME) genes. METHODS In 429 Croatian participants, we genotyped 27 loci in 20 ADME genes. The obtained frequencies were merged with the published frequencies for the Croatian population by sample size weighting. The study sample obtained in this way was compared with the average data for the European population from the gnomAD database. RESULTS Variant allele frequencies in the Croatian population were higher in three and lower in two polymorphisms (Benjamini-Hochberg-corrected P values: 0.0027 for CYP2B6*4 rs2279343, CYP2C9*2 rs1799853, and VKORC1 rs9923231; 0.0297 for GSTP1 rs1695; 0.0455 for CYP2A6 rs1801272) compared with the European population. The most marked difference was observed for CYP2B6*4 (9.3% in Europe vs 24.3% in Croatia). The most clinically relevant findings were higher variant allele frequencies in two polymorphisms related to lower warfarin requirements: VKORC1*2 (34.9% in Europe vs 40.1% in Croatia) and CYP2C9*2 (12.3% in Europe vs 14.7% in Croatia). This indicates that three-quarters of Croatian people have at least one variant allele at these loci. Variants in genes GSTP1 and CYP2A6 were significantly less frequently observed in Croatia. CONCLUSIONS Croatian population has a higher bleeding and over-anticoagulation risk, which is why we recommend the prescription of lower doses of anticoagulation drugs such as warfarin and acenocoumarol. Lower phenytoin, and higher bupropion and efavirenz doses are also recommended in the Croatian population.
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Affiliation(s)
- Željka Celinšćak
- Željka Celinšćak, Institute for Anthropological Research, Gajeva ulica 32, 10000 Zagreb, Croatia,
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9
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Yin X, Chan LS, Bose D, Jackson AU, VandeHaar P, Locke AE, Fuchsberger C, Stringham HM, Welch R, Yu K, Fernandes Silva L, Service SK, Zhang D, Hector EC, Young E, Ganel L, Das I, Abel H, Erdos MR, Bonnycastle LL, Kuusisto J, Stitziel NO, Hall IM, Wagner GR, Kang J, Morrison J, Burant CF, Collins FS, Ripatti S, Palotie A, Freimer NB, Mohlke KL, Scott LJ, Wen X, Fauman EB, Laakso M, Boehnke M. Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci. Nat Commun 2022; 13:1644. [PMID: 35347128 PMCID: PMC8960770 DOI: 10.1038/s41467-022-29143-5] [Citation(s) in RCA: 103] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 02/23/2022] [Indexed: 01/13/2023] Open
Abstract
Few studies have explored the impact of rare variants (minor allele frequency < 1%) on highly heritable plasma metabolites identified in metabolomic screens. The Finnish population provides an ideal opportunity for such explorations, given the multiple bottlenecks and expansions that have shaped its history, and the enrichment for many otherwise rare alleles that has resulted. Here, we report genetic associations for 1391 plasma metabolites in 6136 men from the late-settlement region of Finland. We identify 303 novel association signals, more than one third at variants rare or enriched in Finns. Many of these signals identify genes not previously implicated in metabolite genome-wide association studies and suggest mechanisms for diseases and disease-related traits.
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Affiliation(s)
- Xianyong Yin
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Lap Sum Chan
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Debraj Bose
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Peter VandeHaar
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Adam E Locke
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, 63108, USA
| | - Christian Fuchsberger
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
- Institute for Biomedicine, Eurac Research, Bolzano, 39100, Italy
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Ryan Welch
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Ketian Yu
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Lilian Fernandes Silva
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, 70210, Finland
| | - Susan K Service
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, 90024, USA
| | - Daiwei Zhang
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Emily C Hector
- Department of Statistics, North Carolina State University, Raleigh, NC, 27695, USA
| | - Erica Young
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, 63108, USA
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St Louis, MO, 63110, USA
| | - Liron Ganel
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, 63108, USA
| | - Indraniel Das
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, 63108, USA
| | - Haley Abel
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Michael R Erdos
- Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Lori L Bonnycastle
- Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, 70210, Finland
- Center for Medicine and Clinical Research, Kuopio University Hospital, Kuopio, 70210, Finland
| | - Nathan O Stitziel
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, 63108, USA
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St Louis, MO, 63110, USA
- Department of Genetics, Washington University School of Medicine, St Louis, MO, 63110, USA
| | - Ira M Hall
- Center for Genomic Health, Department of Genetics, Yale University, New Haven, CT, 06510, USA
| | | | - Jian Kang
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Jean Morrison
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Charles F Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Francis S Collins
- Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00290, Finland
- Department of Public Health, University of Helsinki, Helsinki, 00014, Finland
- Broad Institute of MIT & Harvard, Cambridge, MA, 02142, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00290, Finland
- Department of Public Health, University of Helsinki, Helsinki, 00014, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology, and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Nelson B Freimer
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, 90024, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Xiaoquan Wen
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Eric B Fauman
- Internal Medicine Research Unit, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, 02139, USA.
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, 70210, Finland.
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA.
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10
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Wu D, Wong P, Lam SHM, Li EK, Qin L, Tam LS, Gu J. The causal effect of interleukin-17 on the risk of psoriatic arthritis: a Mendelian randomization study. Rheumatology (Oxford) 2021; 60:1963-1973. [PMID: 33188428 DOI: 10.1093/rheumatology/keaa629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Revised: 07/24/2020] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVE To determine causal associations between genetically predicted TNF-α, IL-12p70 and IL-17 levels and risk of PsA. METHODS The publicly available summary-level findings from genome-wide association studies (GWAS) was used to identify loci influencing normal physiological concentrations of TNF-α, IL-12p70 and IL-17 (n = 8293) among healthy individuals as exposure and a GWAS for PsA from the UK Biobank (PsA = 900, control = 462 033) as the outcome. A two-sample Mendelian randomization (MR) analysis was performed using the inverse-variance weighted (IVW), weighted median and MR-Egger regression methods. Sensitivity analysis and MR-Egger regression analysis were performed to evaluate the heterogeneity and pleiotropic effects of each variant. RESULTS Single-nucleotide polymorphisms (SNPs) at genome-wide significance from GWASs on TNF-α, IL-12p70 and IL-17 were identified as the instrumental variables. The IVW method indicated a causal association between increased IL-17 level and risk of PsA (β = -0.00186 per allele, s.e. = 0.00043, P = 0.002). Results were consistent in the weighted median method (β = -0.00145 per allele, s.e. = 0.00059, P = 0.014) although the MR-Egger method suggested a non-significant association (β = -0.00133 per allele, s.e. = 0.00087; P = 0.087). Single SNP MR results revealed that the C allele of rs117556572 was robustly associated with risk of PsA (β = 0.00210, s.e. = 0.00069, P = 0.002). However, no evidence for a causal effect was observed between TNF-α, IL-12p70, decreased IL-17 levels and risk of PsA. CONCLUSION Our findings provide preliminary evidence that genetic variants predisposing to higher physiological IL-17 level are associated with decreased risk of PsA.
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Affiliation(s)
- Dongze Wu
- Department of Rheumatology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Department of Medicine & Therapeutics, The Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Priscilla Wong
- Department of Medicine & Therapeutics, The Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Steven H M Lam
- Department of Medicine & Therapeutics, The Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Edmund K Li
- Department of Medicine & Therapeutics, The Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Ling Qin
- Bone Quality and Health Centre of the Department of Orthopedics & Traumatology, The Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Lai-Shan Tam
- Department of Medicine & Therapeutics, The Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Jieruo Gu
- Department of Rheumatology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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11
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Moreno-Grau S, Fernández MV, de Rojas I, Garcia-González P, Hernández I, Farias F, Budde JP, Quintela I, Madrid L, González-Pérez A, Montrreal L, Alarcón-Martín E, Alegret M, Maroñas O, Pineda JA, Macías J, Marquié M, Valero S, Benaque A, Clarimón J, Bullido MJ, García-Ribas G, Pástor P, Sánchez-Juan P, Álvarez V, Piñol-Ripoll G, García-Alberca JM, Royo JL, Franco-Macías E, Mir P, Calero M, Medina M, Rábano A, Ávila J, Antúnez C, Real LM, Orellana A, Carracedo Á, Sáez ME, Tárraga L, Boada M, Cruchaga C, Ruiz A. Long runs of homozygosity are associated with Alzheimer's disease. Transl Psychiatry 2021; 11:142. [PMID: 33627629 PMCID: PMC7904832 DOI: 10.1038/s41398-020-01145-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 11/27/2020] [Accepted: 12/04/2020] [Indexed: 11/12/2022] Open
Abstract
Long runs of homozygosity (ROH) are contiguous stretches of homozygous genotypes, which are a footprint of inbreeding and recessive inheritance. The presence of recessive loci is suggested for Alzheimer's disease (AD); however, their search has been poorly assessed to date. To investigate homozygosity in AD, here we performed a fine-scale ROH analysis using 10 independent cohorts of European ancestry (11,919 AD cases and 9181 controls.) We detected an increase of homozygosity in AD cases compared to controls [βAVROH (CI 95%) = 0.070 (0.037-0.104); P = 3.91 × 10-5; βFROH (CI95%) = 0.043 (0.009-0.076); P = 0.013]. ROHs increasing the risk of AD (OR > 1) were significantly overrepresented compared to ROHs increasing protection (p < 2.20 × 10-16). A significant ROH association with AD risk was detected upstream the HS3ST1 locus (chr4:11,189,482‒11,305,456), (β (CI 95%) = 1.09 (0.48 ‒ 1.48), p value = 9.03 × 10-4), previously related to AD. Next, to search for recessive candidate variants in ROHs, we constructed a homozygosity map of inbred AD cases extracted from an outbred population and explored ROH regions in whole-exome sequencing data (N = 1449). We detected a candidate marker, rs117458494, mapped in the SPON1 locus, which has been previously associated with amyloid metabolism. Here, we provide a research framework to look for recessive variants in AD using outbred populations. Our results showed that AD cases have enriched homozygosity, suggesting that recessive effects may explain a proportion of AD heritability.
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Affiliation(s)
- Sonia Moreno-Grau
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
| | - Maria Victoria Fernández
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States of America
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Itziar de Rojas
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
| | - Pablo Garcia-González
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Isabel Hernández
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Fabiana Farias
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States of America
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, United States of America
| | - John P Budde
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States of America
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Inés Quintela
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Laura Madrid
- CAEBI. Centro Andaluz de Estudios Bioinformáticos, Sevilla, Spain
| | | | - Laura Montrreal
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Emilio Alarcón-Martín
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Montserrat Alegret
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Olalla Maroñas
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Juan Antonio Pineda
- Unidad Clínica de Enfermedades Infecciosas y Microbiología. Hospital Universitario de Valme, Sevilla, Spain
| | - Juan Macías
- Unidad Clínica de Enfermedades Infecciosas y Microbiología. Hospital Universitario de Valme, Sevilla, Spain
| | - Marta Marquié
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
| | - Sergi Valero
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
| | - Alba Benaque
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Jordi Clarimón
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
- Memory Unit, Neurology Department and Sant Pau Biomedical Research Institute, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Maria Jesus Bullido
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
- Centro de Biología Molecular Severo Ochoa (C.S.I.C.-U.A.M.), Universidad Autónoma de Madrid, Madrid, Spain
- Instituto de Investigación Sanitaria "Hospital la Paz" (IdIPaz), Madrid, Spain
| | | | - Pau Pástor
- Fundació per la Recerca Biomèdica i Social Mútua Terrassa, and Memory Disorders Unit, Department of Neurology, Hospital Universitari Mútua de Terrassa, University of Barcelona School of Medicine, Terrassa, Barcelona, Spain
| | - Pascual Sánchez-Juan
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
- Neurology Service "Marqués de Valdecilla" University Hospital (University of Cantabria and IDIVAL), Santander, Spain
| | - Victoria Álvarez
- Laboratorio de Genética Hospital Universitario Central de Asturias, Oviedo, Spain
- Instituto de Investigación Biosanitaria del Principado de Asturias (ISPA), Oviedo, Spain
| | - Gerard Piñol-Ripoll
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
- Unitat Trastorns Cognitius, Hospital Universitari Santa Maria de Lleida, Institut de Recerca Biomédica de Lleida (IRBLLeida), Lleida, Spain
| | | | - José Luis Royo
- Dep. of Surgery, Biochemistry and Molecular Biology, School of Medicine, University of Málaga, Málaga, Spain
| | - Emilio Franco-Macías
- Unidad de Demencias, Servicio de Neurología y Neurofisiología. Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| | - Pablo Mir
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología. Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| | - Miguel Calero
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
- CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid, Spain
- Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Miguel Medina
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
- CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Alberto Rábano
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
- CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid, Spain
- BT-CIEN, Madrid, Spain
| | - Jesús Ávila
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
- Department of Molecular Neuropathology, Centro de Biología Molecular "Severo Ochoa" (CBMSO), Consejo Superior de Investigaciones Científicas (CSIC)/Universidad Autónoma de Madrid (UAM), Madrid, Spain
| | - Carmen Antúnez
- Unidad de Demencias, Hospital Clínico Universitario Virgen de la Arrixaca, Madrid, Spain
| | - Luis Miguel Real
- Unidad Clínica de Enfermedades Infecciosas y Microbiología. Hospital Universitario de Valme, Sevilla, Spain
- Dep. of Surgery, Biochemistry and Molecular Biology, School of Medicine, University of Málaga, Málaga, Spain
| | - Adelina Orellana
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Ángel Carracedo
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Fundación Pública Galega de Medicina Xenómica- CIBERER-IDIS, Santiago de Compostela, Spain
| | | | - Lluís Tárraga
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
| | - Mercè Boada
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States of America
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Agustín Ruiz
- Research Center and Memory clinic Fundació ACE. Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain.
- CIBERNED, Center for Networked Biomedical Research on Neurodegenerative Diseases, Carlos III Institute of Health, Madrid, Spain.
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12
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Napolioni V, Scelsi MA, Khan RR, Altmann A, Greicius MD. Recent Consanguinity and Outbred Autozygosity Are Associated With Increased Risk of Late-Onset Alzheimer's Disease. Front Genet 2021; 11:629373. [PMID: 33584820 PMCID: PMC7879576 DOI: 10.3389/fgene.2020.629373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Accepted: 12/31/2020] [Indexed: 11/13/2022] Open
Abstract
Prior work in late-onset Alzheimer's disease (LOAD) has resulted in discrepant findings as to whether recent consanguinity and outbred autozygosity are associated with LOAD risk. In the current study, we tested the association between consanguinity and outbred autozygosity with LOAD in the largest such analysis to date, in which 20 LOAD GWAS datasets were retrieved through public databases. Our analyses were restricted to eight distinct ethnic groups: African-Caribbean, Ashkenazi-Jewish European, European-Caribbean, French-Canadian, Finnish European, North-Western European, South-Eastern European, and Yoruba African for a total of 21,492 unrelated subjects (11,196 LOAD and 10,296 controls). Recent consanguinity determination was performed using FSuite v1.0.3, according to subjects' ancestral background. The level of autozygosity in the outbred population was assessed by calculating inbreeding estimates based on the proportion (FROH) and the number (NROH) of runs of homozygosity (ROHs). We analyzed all eight ethnic groups using a fixed-effect meta-analysis, which showed a significant association of recent consanguinity with LOAD (N = 21,481; OR = 1.262, P = 3.6 × 10-4), independently of APOE ∗4 (N = 21,468, OR = 1.237, P = 0.002), and years of education (N = 9,257; OR = 1.274, P = 0.020). Autozygosity in the outbred population was also associated with an increased risk of LOAD, both for F ROH (N = 20,237; OR = 1.204, P = 0.030) and N ROH metrics (N = 20,237; OR = 1.019, P = 0.006), independently of APOE ∗4 [(F ROH, N = 20,225; OR = 1.222, P = 0.029) (N ROH, N = 20,225; OR = 1.019, P = 0.007)]. By leveraging the Alzheimer's Disease Sequencing Project (ADSP) whole-exome sequencing (WES) data, we determined that LOAD subjects do not show an enrichment of rare, risk-enhancing minor homozygote variants compared to the control population. A two-stage recessive GWAS using ADSP data from 201 consanguineous subjects in the discovery phase followed by validation in 10,469 subjects led to the identification of RPH3AL p.A303V (rs117190076) as a rare minor homozygote variant increasing the risk of LOAD [discovery: Genotype Relative Risk (GRR) = 46, P = 2.16 × 10-6; validation: GRR = 1.9, P = 8.0 × 10-4]. These results confirm that recent consanguinity and autozygosity in the outbred population increase risk for LOAD. Subsequent work, with increased samples sizes of consanguineous subjects, should accelerate the discovery of non-additive genetic effects in LOAD.
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Affiliation(s)
- Valerio Napolioni
- Genomic and Molecular Epidemiology (GAME) Lab, School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Marzia A. Scelsi
- Computational Biology in Imaging and Genetics (COMBINE) Lab, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Raiyan R. Khan
- Department of Computer Science, Columbia University, New York, NY, United States
| | - Andre Altmann
- Computational Biology in Imaging and Genetics (COMBINE) Lab, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Michael D. Greicius
- Functional Imaging in Neuropsychiatric Disorders (FIND) Lab, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
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Tam V, Patel N, Turcotte M, Bossé Y, Paré G, Meyre D. Benefits and limitations of genome-wide association studies. Nat Rev Genet 2019; 20:467-484. [PMID: 31068683 DOI: 10.1038/s41576-019-0127-1] [Citation(s) in RCA: 1122] [Impact Index Per Article: 187.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Genome-wide association studies (GWAS) involve testing genetic variants across the genomes of many individuals to identify genotype-phenotype associations. GWAS have revolutionized the field of complex disease genetics over the past decade, providing numerous compelling associations for human complex traits and diseases. Despite clear successes in identifying novel disease susceptibility genes and biological pathways and in translating these findings into clinical care, GWAS have not been without controversy. Prominent criticisms include concerns that GWAS will eventually implicate the entire genome in disease predisposition and that most association signals reflect variants and genes with no direct biological relevance to disease. In this Review, we comprehensively assess the benefits and limitations of GWAS in human populations and discuss the relevance of performing more GWAS.
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Affiliation(s)
- Vivian Tam
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Nikunj Patel
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Michelle Turcotte
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Yohan Bossé
- Institut Universitaire de Cardiologie et de Pneumologie de Québec-Université Laval, Québec City, Québec, Canada.,Department of Molecular Medicine, Laval University, Québec City, Quebec, Canada
| | - Guillaume Paré
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada. .,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada. .,Inserm UMRS 954 N-GERE (Nutrition-Genetics-Environmental Risks), University of Lorraine, Faculty of Medicine, Nancy, France.
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15
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Chakchouk I, Zhang D, Zhang Z, Francioli LC, Santos-Cortez RLP, Schrauwen I, Leal SM. Disparities in discovery of pathogenic variants for autosomal recessive non-syndromic hearing impairment by ancestry. Eur J Hum Genet 2019; 27:1456-1465. [PMID: 31053783 PMCID: PMC6777454 DOI: 10.1038/s41431-019-0417-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 04/01/2019] [Accepted: 04/16/2019] [Indexed: 12/22/2022] Open
Abstract
Hearing impairment (HI) is characterized by extensive genetic heterogeneity. To determine the population-specific contribution of known autosomal recessive nonsyndromic (ARNS)HI genes and variants to HI etiology; pathogenic and likely pathogenic (PLP) ARNSHI variants were selected from ClinVar and the Deafness Variation Database and their frequencies were obtained from gnomAD for seven populations. ARNSHI prevalence due to PLP variants varies greatly by population ranging from 96.9 affected per 100,000 individuals for Ashkenazi Jews to 5.2 affected per 100,000 individuals for Africans/African Americans. For Europeans, Finns have the lowest prevalence due to ARNSHI PLP variants with 9.5 affected per 100,000 individuals. For East Asians, Latinos, non-Finish Europeans, and South Asians, ARNSHI prevalence due to PLP variants ranges from 17.1 to 33.7 affected per 100,000 individuals. ARNSHI variants that were previously reported in a single ancestry or family were observed in additional populations, e.g., USH1C p.(Q723*) reported in a Chinese family was the most prevalent pathogenic variant observed in gnomAD for African/African Americans. Variability between populations is due to how extensively ARNSHI has been studied, ARNSHI prevalence and ancestry specific ARNSHI variant architecture which is impacted by population history. Our study demonstrates that additional gene and variant discovery studies are necessary for all populations and particularly for individuals of African ancestry.
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Affiliation(s)
- Imen Chakchouk
- Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Di Zhang
- Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Zhihui Zhang
- Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Center for Statistical Genetics, Department of Neurology, Gertrude H. Sergievsky Center, Columbia University Medical Center, New York, NY, USA
| | - Laurent C Francioli
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | | | - Isabelle Schrauwen
- Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Center for Statistical Genetics, Department of Neurology, Gertrude H. Sergievsky Center, Columbia University Medical Center, New York, NY, USA
| | - Suzanne M Leal
- Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
- Center for Statistical Genetics, Department of Neurology, Gertrude H. Sergievsky Center, Columbia University Medical Center, New York, NY, USA.
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16
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Locke AE, Steinberg KM, Chiang CWK, Service SK, Havulinna AS, Stell L, Pirinen M, Abel HJ, Chiang CC, Fulton RS, Jackson AU, Kang CJ, Kanchi KL, Koboldt DC, Larson DE, Nelson J, Nicholas TJ, Pietilä A, Ramensky V, Ray D, Scott LJ, Stringham HM, Vangipurapu J, Welch R, Yajnik P, Yin X, Eriksson JG, Ala-Korpela M, Järvelin MR, Männikkö M, Laivuori H, Dutcher SK, Stitziel NO, Wilson RK, Hall IM, Sabatti C, Palotie A, Salomaa V, Laakso M, Ripatti S, Boehnke M, Freimer NB. Exome sequencing of Finnish isolates enhances rare-variant association power. Nature 2019; 572:323-328. [PMID: 31367044 PMCID: PMC6697530 DOI: 10.1038/s41586-019-1457-z] [Citation(s) in RCA: 124] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 07/02/2019] [Indexed: 12/30/2022]
Abstract
Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power.
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Affiliation(s)
- Adam E Locke
- Department of Medicine, Washington University School of Medicine, St Louis, MO, USA
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Karyn Meltz Steinberg
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA
| | - Charleston W K Chiang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Quantitative and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
| | - Susan K Service
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Laurel Stell
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Helsinki Institute for Information Technology HIIT and Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Haley J Abel
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
| | - Colby C Chiang
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
| | - Robert S Fulton
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Chul Joo Kang
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
| | - Krishna L Kanchi
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
| | - Daniel C Koboldt
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- The Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
- Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, USA
| | - David E Larson
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
| | - Joanne Nelson
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
| | - Thomas J Nicholas
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- USTAR Center for Genetic Discovery and Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Arto Pietilä
- National Institute for Health and Welfare, Helsinki, Finland
| | - Vasily Ramensky
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
- Federal State Institution "National Medical Research Center for Preventive Medicine" of the Ministry of Healthcare of the Russian Federation, Moscow, Russia
| | - Debashree Ray
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Departments of Epidemiology and Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Jagadish Vangipurapu
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Ryan Welch
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Pranav Yajnik
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Xianyong Yin
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Johan G Eriksson
- Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Mika Ala-Korpela
- Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, University of Oulu, Oulu, Finland
- NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia
| | - Marjo-Riitta Järvelin
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
| | - Minna Männikkö
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Northern Finland Birth Cohorts, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Hannele Laivuori
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Department of Obstetrics and Gynecology, Tampere University Hospital and University of Tampere, Faculty of Medicine and Health Technology, Tampere, Finland
| | - Susan K Dutcher
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
| | - Nathan O Stitziel
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St Louis, MO, USA
| | - Richard K Wilson
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- The Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
- Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, USA
| | - Ira M Hall
- Department of Medicine, Washington University School of Medicine, St Louis, MO, USA
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
| | - Chiara Sabatti
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Analytical and Translational Genetics Unit (ATGU), Psychiatric & Neurodevelopmental Genetics Unit, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
| | - Nelson B Freimer
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA.
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17
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Kerminen S, Martin AR, Koskela J, Ruotsalainen SE, Havulinna AS, Surakka I, Palotie A, Perola M, Salomaa V, Daly MJ, Ripatti S, Pirinen M. Geographic Variation and Bias in the Polygenic Scores of Complex Diseases and Traits in Finland. Am J Hum Genet 2019; 104:1169-1181. [PMID: 31155286 PMCID: PMC6562021 DOI: 10.1016/j.ajhg.2019.05.001] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 04/29/2019] [Indexed: 12/12/2022] Open
Abstract
Polygenic scores (PSs) are becoming a useful tool to identify individuals with high genetic risk for complex diseases, and several projects are currently testing their utility for translational applications. It is also tempting to use PSs to assess whether genetic variation can explain a part of the geographic distribution of a phenotype. However, it is not well known how the population genetic properties of the training and target samples affect the geographic distribution of PSs. Here, we evaluate geographic differences, and related biases, of PSs in Finland in a geographically well-defined sample of 2,376 individuals from the National FINRISK study. First, we detect geographic differences in PSs for coronary artery disease (CAD), rheumatoid arthritis, schizophrenia, waist-hip ratio (WHR), body-mass index (BMI), and height, but not for Crohn disease or ulcerative colitis. Second, we use height as a model trait to thoroughly assess the possible population genetic biases in PSs and apply similar approaches to the other phenotypes. Most importantly, we detect suspiciously large accumulations of geographic differences for CAD, WHR, BMI, and height, suggesting bias arising from the population's genetic structure rather than from a direct genotype-phenotype association. This work demonstrates how sensitive the geographic patterns of current PSs are for small biases even within relatively homogeneous populations and provides simple tools to identify such biases. A thorough understanding of the effects of population genetic structure on PSs is essential for translational applications of PSs.
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Affiliation(s)
- Sini Kerminen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland
| | - Alicia R Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, 02142, USA
| | - Jukka Koskela
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland
| | - Sanni E Ruotsalainen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; National Institute of Health and Welfare, Helsinki 00271, Finland
| | - Ida Surakka
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Markus Perola
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; National Institute of Health and Welfare, Helsinki 00271, Finland
| | - Veikko Salomaa
- National Institute of Health and Welfare, Helsinki 00271, Finland
| | - Mark J Daly
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, 02142, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland
| | - Matti Pirinen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland; Helsinki Institute for Information Technology and Department of Mathematics and Statistics, University of Helsinki, Helsinki 00014, Finland.
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18
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Vergara-Lope A, Ennis S, Vorechovsky I, Pengelly RJ, Collins A. Heterogeneity in the extent of linkage disequilibrium among exonic, intronic, non-coding RNA and intergenic chromosome regions. Eur J Hum Genet 2019; 27:1436-1444. [PMID: 31053778 DOI: 10.1038/s41431-019-0419-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Revised: 03/04/2019] [Accepted: 04/16/2019] [Indexed: 11/09/2022] Open
Abstract
Whole-genome sequence data enable construction of high-resolution linkage disequilibrium (LD) maps revealing the LD structure of functional elements within genic and subgenic sequences. The Malecot-Morton model defines LD map distances in linkage disequilibrium units (LDUs), analogous to the centimorgan scale of linkage maps. For whole-genome sequence-derived LD maps, we introduce the ratio of corresponding map lengths kilobases/LDU to describe the extent of LD within genome components. The extent of LD is highly variable across the genome ranging from ~38 kb for intergenic sequences to ~858 kb for centromeric regions. LD is ~16% more extensive in genic, compared with intergenic sequences, reflecting relatively increased selection and/or reduced recombination in genes. The LD profile across 18,268 autosomal genes reveals reduced extent of LD, consistent with elevated recombination, in exonic regions near the 5' end of genes but more extensive LD, compared with intronic sequences, across more centrally located exons. Genes classified as essential and genes linked to Mendelian phenotypes show more extensive LD compared with genes associated with complex traits, perhaps reflecting differences in selective pressure. Significant differences between exonic, intronic and intergenic components demonstrate that fine-scale LD structure provides important insights into genome function, which cannot be revealed by LD analysis of much lower resolution array-based genotyping and conventional linkage maps.
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Affiliation(s)
- Alejandra Vergara-Lope
- Human Genetics, Faculty of Medicine, University of Southampton, Duthie Building (808), Southampton General Hospital, Tremona Road, Southampton, SO16 6YD, UK
| | - Sarah Ennis
- Human Genetics, Faculty of Medicine, University of Southampton, Duthie Building (808), Southampton General Hospital, Tremona Road, Southampton, SO16 6YD, UK
| | - Igor Vorechovsky
- Human Genetics, Faculty of Medicine, University of Southampton, Duthie Building (808), Southampton General Hospital, Tremona Road, Southampton, SO16 6YD, UK
| | - Reuben J Pengelly
- Human Genetics, Faculty of Medicine, University of Southampton, Duthie Building (808), Southampton General Hospital, Tremona Road, Southampton, SO16 6YD, UK
| | - Andrew Collins
- Human Genetics, Faculty of Medicine, University of Southampton, Duthie Building (808), Southampton General Hospital, Tremona Road, Southampton, SO16 6YD, UK.
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A genome-wide association study of tramadol metabolism from post-mortem samples. THE PHARMACOGENOMICS JOURNAL 2019; 20:94-103. [PMID: 30971809 DOI: 10.1038/s41397-019-0088-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Revised: 01/08/2019] [Accepted: 03/27/2019] [Indexed: 11/09/2022]
Abstract
Phase I tramadol metabolism requires cytochrome p450 family 2, subfamily D, polypeptide 6 (CYP2D6) to form O-desmethyltramadol (M1). CYP2D6 genetic variants may infer metabolizer phenotype; however, drug ADME (absorption, distribution, metabolism, and excretion) and response depend on protein pathway(s), not CYP2D6 alone. There is a paucity of data regarding the contribution of trans-acting proteins to idiosyncratic phenotypes following drug exposure. A genome-wide association study identified five markers (rs79983226/kgp11274252, rs9384825, rs62435418/kgp10370907, rs72732317/kgp3743668, and rs184199168/exm1592932) associated with the conversion of tramadol to M1 (M1:T). These SNPs reside within five genes previously implicated with adverse reactions. Analysis of accompanying toxicological meta-data revealed a significant positive linear relationship between M1:T and degree of sample polypharmacy. Taken together, these data identify candidate loci for potential clinical inferences of phenotype following exposure to tramadol and highlight sample polypharmacy as a possible diagnostic covariate in post-mortem genetic studies.
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Kurki MI, Saarentaus E, Pietiläinen O, Gormley P, Lal D, Kerminen S, Torniainen-Holm M, Hämäläinen E, Rahikkala E, Keski-Filppula R, Rauhala M, Korpi-Heikkilä S, Komulainen-Ebrahim J, Helander H, Vieira P, Männikkö M, Peltonen M, Havulinna AS, Salomaa V, Pirinen M, Suvisaari J, Moilanen JS, Körkkö J, Kuismin O, Daly MJ, Palotie A. Contribution of rare and common variants to intellectual disability in a sub-isolate of Northern Finland. Nat Commun 2019; 10:410. [PMID: 30679432 PMCID: PMC6345990 DOI: 10.1038/s41467-018-08262-y] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Accepted: 12/20/2018] [Indexed: 01/19/2023] Open
Abstract
The contribution of de novo variants in severe intellectual disability (ID) has been extensively studied whereas the genetics of mild ID has been less characterized. To elucidate the genetics of milder ID we studied 442 ID patients enriched for mild ID (>50%) from a population isolate of Finland. Using exome sequencing, we show that rare damaging variants in known ID genes are observed significantly more often in severe (27%) than in mild ID (13%) patients. We further observe a significant enrichment of functional variants in genes not yet associated with ID (OR: 2.1). We show that a common variant polygenic risk significantly contributes to ID. The heritability explained by polygenic risk score is the highest for educational attainment (EDU) in mild ID (2.2%) but lower for more severe ID (0.6%). Finally, we identify a Finland enriched homozygote variant in the CRADD ID associated gene.
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Affiliation(s)
- Mitja I Kurki
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00014, Helsinki, Finland
| | - Elmo Saarentaus
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00014, Helsinki, Finland
| | - Olli Pietiläinen
- The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Department of Stem Cell and Regenerative Biology, University of Harvard, Cambridge, MA, 02138, USA
| | - Padhraig Gormley
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Dennis Lal
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Sini Kerminen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00014, Helsinki, Finland
| | - Minna Torniainen-Holm
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00014, Helsinki, Finland
- National Institute for Health and Welfare, 00271, Helsinki, Finland
| | - Eija Hämäläinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00014, Helsinki, Finland
| | - Elisa Rahikkala
- PEDEGO Research Unit, University of Oulu, FI-90014, Oulu, Finland
- Medical Research Center, Oulu University Hospital,, University of Oulu, FI-90014, Oulu, Finland
- Department of Clinical Genetics, Oulu University Hospital, 90220, Oulu, Finland
| | - Riikka Keski-Filppula
- PEDEGO Research Unit, University of Oulu, FI-90014, Oulu, Finland
- Medical Research Center, Oulu University Hospital,, University of Oulu, FI-90014, Oulu, Finland
- Department of Clinical Genetics, Oulu University Hospital, 90220, Oulu, Finland
| | - Merja Rauhala
- Northern Ostrobothnia Hospital District, Center for Intellectual Disability Care, 90220, Oulu, Finland
| | - Satu Korpi-Heikkilä
- Northern Ostrobothnia Hospital District, Center for Intellectual Disability Care, 90220, Oulu, Finland
| | - Jonna Komulainen-Ebrahim
- Department of Children and Adolescents, Oulu University Hospital, Medical Research Center Oulu, University of Oulu, FI-90029, Oulu, Finland
| | - Heli Helander
- Department of Children and Adolescents, Oulu University Hospital, Medical Research Center Oulu, University of Oulu, FI-90029, Oulu, Finland
| | - Päivi Vieira
- Department of Children and Adolescents, Oulu University Hospital, Medical Research Center Oulu, University of Oulu, FI-90029, Oulu, Finland
| | - Minna Männikkö
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Infrastructure for population studies, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Markku Peltonen
- National Institute for Health and Welfare, 00271, Helsinki, Finland
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00014, Helsinki, Finland
- National Institute for Health and Welfare, 00271, Helsinki, Finland
| | - Veikko Salomaa
- National Institute for Health and Welfare, 00271, Helsinki, Finland
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00014, Helsinki, Finland
| | - Jaana Suvisaari
- National Institute for Health and Welfare, 00271, Helsinki, Finland
| | - Jukka S Moilanen
- PEDEGO Research Unit, University of Oulu, FI-90014, Oulu, Finland
- Medical Research Center, Oulu University Hospital,, University of Oulu, FI-90014, Oulu, Finland
- Department of Clinical Genetics, Oulu University Hospital, 90220, Oulu, Finland
| | - Jarmo Körkkö
- Northern Ostrobothnia Hospital District, Center for Intellectual Disability Care, 90220, Oulu, Finland
| | - Outi Kuismin
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00014, Helsinki, Finland
- PEDEGO Research Unit, University of Oulu, FI-90014, Oulu, Finland
- Medical Research Center, Oulu University Hospital,, University of Oulu, FI-90014, Oulu, Finland
- Department of Clinical Genetics, Oulu University Hospital, 90220, Oulu, Finland
| | - Mark J Daly
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00014, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Aarno Palotie
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA.
- The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00014, Helsinki, Finland.
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
- Department of Neurology, Massachusetts General Hospital, Boston, MA, 02114, USA.
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21
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Karlsson L, Tolvanen M, Scheinin NM, Uusitupa HM, Korja R, Ekholm E, Tuulari JJ, Pajulo M, Huotilainen M, Paunio T, Karlsson H. Cohort Profile: The FinnBrain Birth Cohort Study (FinnBrain). Int J Epidemiol 2019; 47:15-16j. [PMID: 29025073 DOI: 10.1093/ije/dyx173] [Citation(s) in RCA: 165] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/02/2017] [Indexed: 12/29/2022] Open
Affiliation(s)
- Linnea Karlsson
- Institute of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study.,Department of Child Psychiatry
| | - Mimmi Tolvanen
- Institute of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study.,Department of Community Dentistry
| | - Noora M Scheinin
- Institute of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study.,Department of Psychiatry
| | - Henna-Maria Uusitupa
- Institute of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study
| | - Riikka Korja
- Institute of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study.,Department of Psychology, University of Turku
| | - Eeva Ekholm
- Institute of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study.,Department of Obstetrics and Gynecology, University of Turku and Turku University Hospital, Turku, Finland
| | - Jetro J Tuulari
- Institute of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study
| | - Marjukka Pajulo
- Institute of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study.,Department of Child Psychiatry
| | - Minna Huotilainen
- Institute of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study.,University of Helsinki, Cognitive Brain Research Unit and CICERO Learning Network, Helsinki, Finland
| | - Tiina Paunio
- National Institute for Health and Welfare, the Genomics and Biomarkers Unit, Helsinki, Finland.,University of Helsinki and Helsinki University Hospital, Department of Psychiatry, Helsinki, Finland
| | - Hasse Karlsson
- Institute of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study.,Department of Psychiatry
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22
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Cameron-Christie SR, Wilde J, Gray A, Tankard R, Bahlo M, Markie D, Evans HM, Robertson SP. Genetic investigation into an increased susceptibility to biliary atresia in an extended New Zealand Māori family. BMC Med Genomics 2018; 11:121. [PMID: 30563518 PMCID: PMC6299523 DOI: 10.1186/s12920-018-0440-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Accepted: 11/27/2018] [Indexed: 12/11/2022] Open
Abstract
Background Biliary atresia (BA), a fibrosing disorder of the developing biliary tract leading to liver failure in infancy, has an elevated incidence in indigenous New Zealand (NZ) Māori. We investigated a high rate of BA in a group of children (n = 12) belonging to a single Māori iwi (or ‘tribe’, related through a remote ancestor). Methods Population and geographical data was used to estimate the rate of BA in Māori sub-groups, and a pedigree linking most of the affected children was constructed from oral and documented history. Array genotyping was used to examine hypotheses about the inheritance of a possible genetic risk factor, and the history of the affected population, and Exome Sequencing to search for candidate genes. Results Most of these affected children (n = 7) link to a self-reported pedigree and carry a 50-fold increase in BA risk over unrelated Māori (χ2 = 296P < 0.001, 95% CI 23–111). Genetic analysis using FEstim and SNP array genotypes revealed no evidence for elevated consanguinity between parents of affected children (FEstim: F (2,21) = 0.469, P > 0.63). Genome-wide quantitation of intervals of contiguous, homozygous-by-state markers reached a similar conclusion (F (2,399) = 1.99, P = 0.138). Principal component analysis and investigation with STRUCTURE found no evidence of increased allele frequency of either a recessive variant, or additive, low-risk variants due to reproductive isolation. To identify candidate causal factors, Exome Sequencing datasets were scrutinised for shared rare coding variants across 8 affected individuals. No rare, non-synonymous, phylogenetically conserved variants were common to 6 or more affected children. Conclusion The substantially elevated risk for development of BA in this subgroup could be mediated by genetic factors, but the iwi exhibits no properties indicative of recent or remote reproductive isolation. Resolution of any risk loci may rely on extensive genomic sequencing studies in this iwi or investigation of other mechnaisms such as copy number variation. Electronic supplementary material The online version of this article (10.1186/s12920-018-0440-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sophia R Cameron-Christie
- Department of Women's and Children's Health, Dunedin School of Medicine, University of Otago, Dunedin, 9054, New Zealand
| | - Justin Wilde
- Department of Paediatrics, Tauranga Hospital, Tauranga, New Zealand
| | - Andrew Gray
- Department of Preventive and Social Medicine, University of Otago, Dunedin, 9054, New Zealand
| | - Rick Tankard
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC, 3052, Australia.,Department of Medical Biology, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Melanie Bahlo
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC, 3052, Australia.,Department of Medical Biology, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - David Markie
- Department of Pathology, University of Otago, Dunedin, 9054, New Zealand
| | - Helen M Evans
- Paediatric Gastroenterology and Hepatology, Starship Children's Health, 2 Park Road, Grafton, Auckland, 1023, New Zealand
| | - Stephen P Robertson
- Department of Women's and Children's Health, Dunedin School of Medicine, University of Otago, Dunedin, 9054, New Zealand.
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23
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Sanghera DK, Bejar C, Sapkota B, Wander GS, Ralhan S. Frequencies of poor metabolizer alleles of 12 pharmacogenomic actionable genes in Punjabi Sikhs of Indian Origin. Sci Rep 2018; 8:15742. [PMID: 30356105 PMCID: PMC6200732 DOI: 10.1038/s41598-018-33981-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 09/28/2018] [Indexed: 12/28/2022] Open
Abstract
Diversity in drug response is attributed to both genetic and non-genetic factors. However, there is paucity of pharmacogenetics information across ethnically and genetically diverse populations of India. Here, we have analyzed 21 SNPs from 12 pharmacogenomics genes in Punjabi Sikhs of Indian origin (N = 1,616), as part of the Sikh Diabetes Study (SDS). We compared the allele frequency of poor metabolism (PM) phenotype among Sikhs across other major global populations from the Exome Aggregation Consortium and 1000 Genomes. The PM phenotype of CYP1A2*1 F for slow metabolism of caffeine and carcinogens was significantly higher in Indians (SDS 42%, GIH [Gujarati] 51%, SAS [Pakistani] 45%) compared to Europeans 29% (pgenotype = 5.3E-05). Similarly, South Asians had a significantly higher frequency of CYP2C9*3 (12% SDS, 13% GIH, 11% SAS) vs. 7% in Europeans (pgenotype = <1.0E-05) and 'T' allele of CYP4F2 (36%) SDS, (43%) GIH, 40% (SAS) vs. (29%) in Europeans (pgenotype = <1.0E-05); both associated with a higher risk of bleeding with warfarin. All South Asians -the Sikhs (0.36), GIH (0.34), and SAS (0.36) had a higher frequency of the NAT2*6 allele (linked with slow acetylation of isoniazid) compared to Europeans (0.29). Additionally, the prevalence of the low activity 'C' allele of MTHFR (rs1801131) was highest in Sikhs compared to all other ethnic groups [SDS (44%), GIH (39%), SAS (42%) and European (32%) (pgenotype = <1.0E-05)]. SNPs in MTHFR affect metabolism of statins, 5-fluorouracil and methotrexate-based cancer drugs. These findings underscore the need for evaluation of other endogamous ethnic groups of India and beyond for establishing a global benchmark for pre-emptive genotyping in drug metabolizing genes before beginning therapeutic intervention.
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Affiliation(s)
- Dharambir K Sanghera
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA.
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Oklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
| | - Cynthia Bejar
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Bishwa Sapkota
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | | | - Sarju Ralhan
- Hero DMC Heart Institute, Ludhiana, Punjab, India
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24
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Martin AR, Karczewski KJ, Kerminen S, Kurki MI, Sarin AP, Artomov M, Eriksson JG, Esko T, Genovese G, Havulinna AS, Kaprio J, Konradi A, Korányi L, Kostareva A, Männikkö M, Metspalu A, Perola M, Prasad RB, Raitakari O, Rotar O, Salomaa V, Groop L, Palotie A, Neale BM, Ripatti S, Pirinen M, Daly MJ. Haplotype Sharing Provides Insights into Fine-Scale Population History and Disease in Finland. Am J Hum Genet 2018; 102:760-775. [PMID: 29706349 DOI: 10.1016/j.ajhg.2018.03.003] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Accepted: 02/28/2018] [Indexed: 01/23/2023] Open
Abstract
Finland provides unique opportunities to investigate population and medical genomics because of its adoption of unified national electronic health records, detailed historical and birth records, and serial population bottlenecks. We assembled a comprehensive view of recent population history (≤100 generations), the timespan during which most rare-disease-causing alleles arose, by comparing pairwise haplotype sharing from 43,254 Finns to that of 16,060 Swedes, Estonians, Russians, and Hungarians from geographically and linguistically adjacent countries with different population histories. We find much more extensive sharing in Finns, with at least one ≥ 5 cM tract on average between pairs of unrelated individuals. By coupling haplotype sharing with fine-scale birth records from more than 25,000 individuals, we find that although haplotype sharing broadly decays with geographical distance, there are pockets of excess haplotype sharing; individuals from northeast Finland typically share several-fold more of their genome in identity-by-descent segments than individuals from southwest regions. We estimate recent effective population-size changes through time across regions of Finland, and we find that there was more continuous gene flow as Finns migrated from southwest to northeast between the early- and late-settlement regions than was dichotomously described previously. Lastly, we show that haplotype sharing is locally enriched by an order of magnitude among pairs of individuals sharing rare alleles and especially among pairs sharing rare disease-causing variants. Our work provides a general framework for using haplotype sharing to reconstruct an integrative view of recent population history and gain insight into the evolutionary origins of rare variants contributing to disease.
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Affiliation(s)
- Alicia R Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
| | - Konrad J Karczewski
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Sini Kerminen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland
| | - Mitja I Kurki
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; National Institute for Health and Welfare of Finland, Helsinki 00271, Finland
| | - Mykyta Artomov
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Johan G Eriksson
- National Institute for Health and Welfare of Finland, Helsinki 00271, Finland; Folkhälsan Research Center, Helsinki 00290, Finland; Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki 00014, Finland
| | - Tõnu Esko
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Estonian Genome Center, University of Tartu, Tartu 50090, Estonia
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; National Institute for Health and Welfare of Finland, Helsinki 00271, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland
| | - Alexandra Konradi
- Almazov National Medical Research Centre, Saint Petersburg 197341, Russia; National Research University of Information Technologies, Mechanics, and Optics, Saint Petersburg 197101, Russia
| | - László Korányi
- Heart Center Foundation, Drug Research Centre, Balatonfured H-8230, Hungary
| | - Anna Kostareva
- Almazov National Medical Research Centre, Saint Petersburg 197341, Russia; National Research University of Information Technologies, Mechanics, and Optics, Saint Petersburg 197101, Russia
| | - Minna Männikkö
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu 90014, Finland
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 50090, Estonia
| | - Markus Perola
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Estonian Genome Center, University of Tartu, Tartu 50090, Estonia; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku University Hospital, Turku 20520, Finland
| | - Rashmi B Prasad
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University CRC, Skåne University Hospital Malmö, SE-205 02, Malmö, Sweden
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku University Hospital, Turku 20520, Finland; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland
| | - Oxana Rotar
- Almazov National Medical Research Centre, Saint Petersburg 197341, Russia
| | - Veikko Salomaa
- National Institute for Health and Welfare of Finland, Helsinki 00271, Finland
| | - Leif Groop
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Lund University Diabetes Centre, Department of Clinical Sciences, Lund University CRC, Skåne University Hospital Malmö, SE-205 02, Malmö, Sweden
| | - Aarno Palotie
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland; Helsinki Institute for Information Technology and Department of Mathematics and Statistics, University of Helsinki, 00014 Helsinki, Finland
| | - Mark J Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland.
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25
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Van den Eynden J, Descamps T, Delporte E, Roosens NHC, De Keersmaecker SCJ, De Wit V, Vermeesch JR, Goetghebeur E, Tafforeau J, Demarest S, Van den Bulcke M, Van Oyen H. The genetic structure of the Belgian population. Hum Genomics 2018; 12:6. [PMID: 29394955 PMCID: PMC5796395 DOI: 10.1186/s40246-018-0136-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 01/23/2018] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND National and international efforts like the 1000 Genomes Project are leading to increasing insights in the genetic structure of populations worldwide. Variation between different populations necessitates access to population-based genetic reference datasets. These data, which are important not only in clinical settings but also to potentiate future transitions towards a more personalized public health approach, are currently not available for the Belgian population. RESULTS To obtain a representative genetic dataset of the Belgian population, participants in the 2013 National Health Interview Survey (NHIS) were invited to donate saliva samples for DNA analysis. DNA was isolated and single nucleotide polymorphisms (SNPs) were determined using a genome-wide SNP array of around 300,000 sites, resulting in a high-quality dataset of 189 samples that was used for further analysis. A principal component analysis demonstrated the typical European genetic constitution of the Belgian population, as compared to other continents. Within Europe, the Belgian population could be clearly distinguished from other European populations. Furthermore, obvious signs from recent migration were found, mainly from Southern Europe and Africa, corresponding with migration trends from the past decades. Within Belgium, a small north-west to south-east gradient in genetic variability was noted, with differences between Flanders and Wallonia. CONCLUSIONS This is the first study on the genetic structure of the Belgian population and its regional variation. The Belgian genetic structure mirrors its geographic location in Europe with regional differences and clear signs of recent migration.
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Affiliation(s)
- Jimmy Van den Eynden
- Scientific Institute of Public Health, Brussels, Belgium.
- Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
| | - Tine Descamps
- Scientific Institute of Public Health, Brussels, Belgium
| | - Els Delporte
- Scientific Institute of Public Health, Brussels, Belgium
| | | | | | - Vanessa De Wit
- Scientific Institute of Public Health, Brussels, Belgium
| | - Joris Robert Vermeesch
- Laboratory of Cytogenetics and Genome Research, Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Els Goetghebeur
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
| | - Jean Tafforeau
- Scientific Institute of Public Health, Brussels, Belgium
| | | | | | - Herman Van Oyen
- Scientific Institute of Public Health, Brussels, Belgium.
- Department of Public Health, Ghent University, Ghent, Belgium.
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26
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Pelttari LM, Shimelis H, Toiminen H, Kvist A, Törngren T, Borg Å, Blomqvist C, Bützow R, Couch F, Aittomäki K, Nevanlinna H. Gene-panel testing of breast and ovarian cancer patients identifies a recurrent RAD51C duplication. Clin Genet 2018; 93:595-602. [PMID: 28802053 DOI: 10.1111/cge.13123] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 07/20/2017] [Accepted: 08/08/2017] [Indexed: 11/24/2022]
Abstract
Gene-panel sequencing allows comprehensive analysis of multiple genes simultaneously and is now routinely used in clinical mutation testing of high-risk breast and ovarian cancer patients. However, only BRCA1 and BRCA2 are often analyzed also for large genomic changes. Here, we have analyzed 10 clinically relevant susceptibility genes in 95 breast or ovarian cancer patients with gene-panel sequencing including also copy number variants (CNV) analysis for genomic changes. We identified 12 different pathogenic BRCA1, BRCA2, TP53, PTEN, CHEK2, or RAD51C mutations in 18 of 95 patients (19%). BRCA1/2 mutations were observed in 8 patients (8.4%) and CHEK2 protein-truncating mutations in 7 patients (7.4%). In addition, we identified a novel duplication encompassing most of the RAD51C gene. We further genotyped the duplication in breast or ovarian cancer families (n = 1149), in unselected breast (n = 1729) and ovarian cancer cohorts (n = 553), and in population controls (n = 1273). Seven additional duplication carries were observed among cases but none among controls. The duplication associated with ovarian cancer risk (3/590 of all ovarian cancer patients, 0.5%, P = .032 compared with controls) and was found to represent a large fraction of all identified RAD51C mutations in the Finnish population. Our data emphasizes the importance of comprehensive mutation analysis including CNV detection in all the relevant genes.
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Affiliation(s)
- L M Pelttari
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - H Shimelis
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - H Toiminen
- Department of Clinical Genetics, University of Helsinki and HUSLAB, Helsinki University Hospital, Helsinki, Finland
| | - A Kvist
- Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Lund, Sweden
| | - T Törngren
- Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Lund, Sweden
| | - Å Borg
- Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Lund, Sweden
| | - C Blomqvist
- Department of Oncology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - R Bützow
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - F Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - K Aittomäki
- Department of Clinical Genetics, University of Helsinki and HUSLAB, Helsinki University Hospital, Helsinki, Finland
| | - H Nevanlinna
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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27
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Blant A, Kwong M, Szpiech ZA, Pemberton TJ. Weighted likelihood inference of genomic autozygosity patterns in dense genotype data. BMC Genomics 2017; 18:928. [PMID: 29191164 PMCID: PMC5709839 DOI: 10.1186/s12864-017-4312-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Accepted: 11/16/2017] [Indexed: 12/14/2022] Open
Abstract
Background Genomic regions of autozygosity (ROA) arise when an individual is homozygous for haplotypes inherited identical-by-descent from ancestors shared by both parents. Over the past decade, they have gained importance for understanding evolutionary history and the genetic basis of complex diseases and traits. However, methods to infer ROA in dense genotype data have not evolved in step with advances in genome technology that now enable us to rapidly create large high-resolution genotype datasets, limiting our ability to investigate their constituent ROA patterns. Methods We report a weighted likelihood approach for inferring ROA in dense genotype data that accounts for autocorrelation among genotyped positions and the possibilities of unobserved mutation and recombination events, and variability in the confidence of individual genotype calls in whole genome sequence (WGS) data. Results Forward-time genetic simulations under two demographic scenarios that reflect situations where inbreeding and its effect on fitness are of interest suggest this approach is better powered than existing state-of-the-art methods to infer ROA at marker densities consistent with WGS and popular microarray genotyping platforms used in human and non-human studies. Moreover, we present evidence that suggests this approach is able to distinguish ROA arising via consanguinity from ROA arising via endogamy. Using subsets of The 1000 Genomes Project Phase 3 data we show that, relative to WGS, intermediate and long ROA are captured robustly with popular microarray platforms, while detection of short ROA is more variable and improves with marker density. Worldwide ROA patterns inferred from WGS data are found to accord well with those previously reported on the basis of microarray genotype data. Finally, we highlight the potential of this approach to detect genomic regions enriched for autozygosity signals in one group relative to another based upon comparisons of per-individual autozygosity likelihoods instead of inferred ROA frequencies. Conclusions This weighted likelihood ROA inference approach can assist population- and disease-geneticists working with a wide variety of data types and species to explore ROA patterns and to identify genomic regions with differential ROA signals among groups, thereby advancing our understanding of evolutionary history and the role of recessive variation in phenotypic variation and disease. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-4312-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Alexandra Blant
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, Canada
| | - Michelle Kwong
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, Canada
| | - Zachary A Szpiech
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA
| | - Trevor J Pemberton
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, Canada.
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28
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Abstract
Coupling dense genotype data with new computational methods offers unprecedented opportunities for individual-level ancestry estimation once geographically precisely defined reference data sets become available. We study such a reference data set for Finland containing 2376 such individuals from the FINRISK Study survey of 1997 both of whose parents were born close to each other. This sampling strategy focuses on the population structure present in Finland before the 1950s. By using the recent haplotype-based methods ChromoPainter (CP) and FineSTRUCTURE (FS) we reveal a highly geographically clustered genetic structure in Finland and report its connections to the settlement history as well as to the current dialectal regions of the Finnish language. The main genetic division within Finland shows striking concordance with the 1323 borderline of the treaty of Nöteborg. In general, we detect genetic substructure throughout the country, which reflects stronger regional genetic differences in Finland compared to, for example, the UK, which in a similar analysis was dominated by a single unstructured population. We expect that similar population genetic reference data sets will become available for many more populations in the near future with important applications, for example, in forensic genetics and in genetic association studies. With this in mind, we report those extensions of the CP + FS approach that we found most useful in our analyses of the Finnish data.
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29
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Genetics in an isolated population like Finland: a different basis for genomic medicine? J Community Genet 2017; 8:319-326. [PMID: 28730583 PMCID: PMC5614886 DOI: 10.1007/s12687-017-0318-4] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Accepted: 06/29/2017] [Indexed: 11/24/2022] Open
Abstract
A unique genetic background in an isolated population like that of Finland offers special opportunities for genetic research as well as for applying the genetic developments to the health care. On the other hand, the different genetic background may require local attempts to develop diagnostics and treatment as the selection of diseases and mutations differs from that in the other populations. In this review, we describe the experiences of research and health care in this genetic isolate starting from the identification of specific monogenic diseases enriched in the Finnish population all the way to implementing the knowledge of the unique genetic background to genomic medicine at population level.
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30
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Donner I, Katainen R, Tanskanen T, Kaasinen E, Aavikko M, Ovaska K, Artama M, Pukkala E, Aaltonen LA. Candidate susceptibility variants for esophageal squamous cell carcinoma. Genes Chromosomes Cancer 2017; 56:453-459. [PMID: 28165652 DOI: 10.1002/gcc.22448] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Revised: 01/20/2017] [Accepted: 01/30/2017] [Indexed: 01/01/2023] Open
Abstract
Esophageal cancer is common worldwide, and often fatal. The major histological subtype is esophageal squamous cell carcinoma (ESCC). ESCC shows familial aggregation and high heritability. Mutations in RHBDF2 cause tylosis, a very rare disorder characterized by high life-time risk of ESCC, but no other well-established predisposition genes have been identified. To identify candidate susceptibility variants for ESCC we utilized the Population Information System and the Finnish cancer registry to find study materials by clustering ESCC patients by family name at birth and municipality at birth. We collected archival tissue material and exome sequenced a total of 30 ESCC cases. We prioritized shared, deleterious and rare variants that were significantly enriched in our sample set compared to Finnish and population subset specific controls. Six variants passed filtering, the most frequent being a nonsense mutation in DNAH9 (p.Tyr1573Ter) found in four unrelated patients. DNAH9 has been reported to be frequently lost in ESCC tumors. In this study, one patient's tumor showed loss of the wild type allele of DNAH9 suggesting a tumor suppressive function. A missense variant in GKAP1 was shared by three patients, and missense variants in BAG1, NFX1, FUK, and DDOST by two each. EP300 which has previously been implicated in the genesis of ESCC had a missense variant segregating in three affected individuals in a single family. If validated in independent patient sets, these variants could serve as a tool towards prevention and early diagnosis of ESCC.
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Affiliation(s)
- Iikki Donner
- Department of Medical and Clinical Genetics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Genome Scale Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Riku Katainen
- Department of Medical and Clinical Genetics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Genome Scale Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Tomas Tanskanen
- Department of Medical and Clinical Genetics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Genome Scale Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Eevi Kaasinen
- Department of Medical and Clinical Genetics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Genome Scale Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Mervi Aavikko
- Department of Medical and Clinical Genetics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Genome Scale Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Kristian Ovaska
- Genome Scale Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Miia Artama
- Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Helsinki, Finland
| | - Eero Pukkala
- Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Helsinki, Finland
| | - Lauri A Aaltonen
- Department of Medical and Clinical Genetics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Genome Scale Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
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31
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Chheda H, Palta P, Pirinen M, McCarthy S, Walter K, Koskinen S, Salomaa V, Daly M, Durbin R, Palotie A, Aittokallio T, Ripatti S. Whole-genome view of the consequences of a population bottleneck using 2926 genome sequences from Finland and United Kingdom. Eur J Hum Genet 2017; 25:477-484. [PMID: 28145424 PMCID: PMC5346294 DOI: 10.1038/ejhg.2016.205] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Revised: 12/05/2016] [Accepted: 12/14/2016] [Indexed: 12/14/2022] Open
Abstract
Isolated populations with enrichment of variants due to recent population bottlenecks provide a powerful resource for identifying disease-associated genetic variants and genes. As a model of an isolate population, we sequenced the genomes of 1463 Finnish individuals as part of the Sequencing Initiative Suomi (SISu) Project. We compared the genomic profiles of the 1463 Finns to a sample of 1463 British individuals that were sequenced in parallel as part of the UK10K Project. Whereas there were no major differences in the allele frequency of common variants, a significant depletion of variants in the rare frequency spectrum was observed in Finns when comparing the two populations. On the other hand, we observed >2.1 million variants that were twice as frequent among Finns compared with Britons and 800 000 variants that were more than 10 times more frequent in Finns. Furthermore, in Finns we observed a relative proportional enrichment of variants in the minor allele frequency range between 2 and 5% (P<2.2 × 10−16). When stratified by their functional annotations, loss-of-function variants showed the highest proportional enrichment in Finns (P=0.0291). In the non-coding part of the genome, variants in conserved regions (P=0.002) and promoters (P=0.01) were also significantly enriched in the Finnish samples. These functional categories represent the highest a priori power for downstream association studies of rare variants using population isolates.
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Affiliation(s)
- Himanshu Chheda
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Priit Palta
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Shane McCarthy
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Klaudia Walter
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Seppo Koskinen
- Department of Health, National Institute for Health and Welfare, Helsinki, Finland
| | - Veikko Salomaa
- Department of Health, National Institute for Health and Welfare, Helsinki, Finland
| | - Mark Daly
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.,Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Richard Durbin
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.,Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Tero Aittokallio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Department of Mathematics and Statistics, University of Turku, Turku, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK.,Public Health, Clinicum, University of Helsinki, Helsinki, Finland
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33
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The effects of resource availability and the demographic transition on the genetic correlation between number of children and grandchildren in humans. Heredity (Edinb) 2016; 118:186-192. [PMID: 27624115 DOI: 10.1038/hdy.2016.81] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Revised: 07/29/2016] [Accepted: 08/01/2016] [Indexed: 11/08/2022] Open
Abstract
Studies of evolutionary change require an estimate of fitness, and lifetime reproductive success is widely used for this purpose. However, many species face a trade-off between the number and quality of offspring and in such cases number of grandoffspring may better represent the genetic contribution to future generations. Here, we apply quantitative genetic methods to a genealogical data set on humans from Finland to address how the genetic correlation between number of children and grandchildren is influenced by the severity of the trade-off between offspring quality and quantity, as estimated by different levels of resource access among individuals in the population. Further, we compare the genetic correlation before and after the demographic transition to low mortality and fertility rates. The genetic correlation was consistently high (0.79-0.92) with the strongest correlations occurring in individuals with higher access to resources and before the demographic transition, and a tendency for lower correlations in resource poor individuals and after the transition. These results indicate that number of grandoffspring is a slightly better predictor of long-term genetic fitness than number of offspring in a human population across a range of environmental conditions, and more generally, that patterns of resource availability need to be taken into account when estimating genetic covariances with fitness.
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34
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Sun H. A multi-layer microchip for high-throughput single-cell gene expression profiling. Anal Biochem 2016; 508:1-8. [DOI: 10.1016/j.ab.2016.05.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2016] [Revised: 05/21/2016] [Accepted: 05/23/2016] [Indexed: 10/21/2022]
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35
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Nationwide Genomic Study in Denmark Reveals Remarkable Population Homogeneity. Genetics 2016; 204:711-722. [PMID: 27535931 DOI: 10.1534/genetics.116.189241] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Accepted: 07/30/2016] [Indexed: 02/07/2023] Open
Abstract
Denmark has played a substantial role in the history of Northern Europe. Through a nationwide scientific outreach initiative, we collected genetic and anthropometrical data from ∼800 high school students and used them to elucidate the genetic makeup of the Danish population, as well as to assess polygenic predictions of phenotypic traits in adolescents. We observed remarkable homogeneity across different geographic regions, although we could still detect weak signals of genetic structure reflecting the history of the country. Denmark presented genomic affinity with primarily neighboring countries with overall resemblance of decreasing weight from Britain, Sweden, Norway, Germany, and France. A Polish admixture signal was detected in Zealand and Funen, and our date estimates coincided with historical evidence of Wend settlements in the south of Denmark. We also observed considerably diverse demographic histories among Scandinavian countries, with Denmark having the smallest current effective population size compared to Norway and Sweden. Finally, we found that polygenic prediction of self-reported adolescent height in the population was remarkably accurate (R2 = 0.639 ± 0.015). The high homogeneity of the Danish population could render population structure a lesser concern for the upcoming large-scale gene-mapping studies in the country.
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36
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Exome sequencing in pooled DNA samples to identify maternal pre-eclampsia risk variants. Sci Rep 2016; 6:29085. [PMID: 27384325 PMCID: PMC4935848 DOI: 10.1038/srep29085] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2016] [Accepted: 06/14/2016] [Indexed: 02/04/2023] Open
Abstract
Pre-eclampsia is a common pregnancy disorder that is a major cause for maternal and perinatal mortality and morbidity. Variants predisposing to pre-eclampsia might be under negative evolutionary selection that is likely to keep their population frequencies low. We exome sequenced samples from a hundred Finnish pre-eclamptic women in pools of ten to screen for low-frequency, large-effect risk variants for pre-eclampsia. After filtering and additional genotyping steps, we selected 28 low-frequency missense, nonsense and splice site variants that were enriched in the pre-eclampsia pools compared to reference data, and genotyped the variants in 1353 pre-eclamptic and 699 non-pre-eclamptic women to test the association of them with pre-eclampsia and quantitative traits relevant for the disease. Genotypes from the SISu project (n = 6118 exome sequenced Finnish samples) were included in the binary trait association analysis as a population reference to increase statistical power. In these analyses, none of the variants tested reached genome-wide significance. In conclusion, the genetic risk for pre-eclampsia is likely complex even in a population isolate like Finland, and larger sample sizes will be necessary to detect risk variants.
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37
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Pietarinen P, Tornio A, Niemi M. High Frequency ofCYP2D6Ultrarapid Metabolizer Genotype in the Finnish Population. Basic Clin Pharmacol Toxicol 2016; 119:291-6. [DOI: 10.1111/bcpt.12590] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2016] [Accepted: 03/17/2016] [Indexed: 11/27/2022]
Affiliation(s)
- Paavo Pietarinen
- Department of Clinical Pharmacology; University of Helsinki and Helsinki University Hospital; Helsinki Finland
| | - Aleksi Tornio
- Department of Clinical Pharmacology; University of Helsinki and Helsinki University Hospital; Helsinki Finland
| | - Mikko Niemi
- Department of Clinical Pharmacology; University of Helsinki and Helsinki University Hospital; Helsinki Finland
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38
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Zhai G, Zhou J, Woods MO, Green JS, Parfrey P, Rahman P, Green RC. Genetic structure of the Newfoundland and Labrador population: founder effects modulate variability. Eur J Hum Genet 2015; 24:1063-70. [PMID: 26669659 DOI: 10.1038/ejhg.2015.256] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2015] [Revised: 11/16/2015] [Accepted: 11/18/2015] [Indexed: 01/30/2023] Open
Abstract
The population of the province of Newfoundland and Labrador (NL) has been a resource for genetic studies because of its historical isolation and increased prevalence of several monogenic disorders. Controversy remains regarding the genetic substructure and the extent of genetic homogeneity, which have implications for disease gene mapping. Population substructure has been reported from other isolated populations such as Iceland, Finland and Sardinia. We undertook this study to further our understanding of the genetic architecture of the NL population. We enrolled 494 individuals randomly selected from NL. Genome-wide SNP data were analyzed together with that from 14 other populations including HapMap3, Ireland, Britain and Native American samples from the Human Genome Diversity Project. Using multidimensional scaling and admixture analysis, we observed that the genetic structure of the NL population resembles that of the British population but can be divided into three clusters that correspond to religious/ethnic origins: Protestant English, Roman Catholic Irish and North American aboriginals. We observed reduced heterozygosity and an increased inbreeding coefficient (mean=0.005), which corresponds to that expected in the offspring of third-cousin marriages. We also found that the NL population has a significantly higher number of runs of homozygosity (ROH) and longer lengths of ROH segments. These results are consistent with our understanding of the population history and indicate that the NL population may be ideal for identifying recessive variants for complex diseases that affect populations of European origin.
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Affiliation(s)
- Guangju Zhai
- Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St John's, Newfoundland and Labrador, Canada
| | - Jiayi Zhou
- Discipline of Medicine, Faculty of Medicine, Memorial University, St John's, Newfoundland and Labrador, Canada
| | - Michael O Woods
- Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St John's, Newfoundland and Labrador, Canada
| | - Jane S Green
- Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St John's, Newfoundland and Labrador, Canada
| | - Patrick Parfrey
- Discipline of Medicine, Faculty of Medicine, Memorial University, St John's, Newfoundland and Labrador, Canada
| | - Proton Rahman
- Discipline of Medicine, Faculty of Medicine, Memorial University, St John's, Newfoundland and Labrador, Canada
| | - Roger C Green
- Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St John's, Newfoundland and Labrador, Canada
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39
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Ben Halim N, Nagara M, Regnault B, Hsouna S, Lasram K, Kefi R, Azaiez H, Khemira L, Saidane R, Ammar SB, Besbes G, Weil D, Petit C, Abdelhak S, Romdhane L. Estimation of Recent and Ancient Inbreeding in a Small Endogamous Tunisian Community Through Genomic Runs of Homozygosity. Ann Hum Genet 2015; 79:402-17. [PMID: 26420437 DOI: 10.1111/ahg.12131] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2014] [Accepted: 07/08/2015] [Indexed: 01/21/2023]
Abstract
Runs of homozygosity (ROHs) are extended genomic regions of homozygous genotypes that record populations' mating patterns in the past. We performed microarray genotyping on 15 individuals from a small isolated Tunisian community. We estimated the individual and population genome-wide level of homozygosity from data on ROH above 0.5 Mb in length. We found a high average number of ROH per individual (48.2). The smallest ROH category (0.5-1.49 Mb) represents 0.93% of the whole genome, while medium-size (1.5-4.99 Mb) and long-size ROH (≥5 Mb) cover 1.18% and 0.95%, respectively. We found that genealogical individual inbreeding coefficients (Fped ) based on three- to four-generation pedigrees are not reliable indicators of the current proportion of genome-wide homozygosity inferred from ROH (FROH ) either for 0.5 or 1.5 Mb ROH length thresholds, while identity-by-descent sharing is a function of shared coancestry. This study emphasizes the effect of reproductive isolation and a prolonged practice of consanguinity that limits the genetic heterogeneity. It also provides evidence of both recent and ancient parental relatedness contribution to the current level of genome-wide homozygosity in the studied population. These findings may be useful for evaluation of long-term effects of inbreeding on human health and for future applications of ROHs in identifying recessive susceptibility genes.
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Affiliation(s)
- Nizar Ben Halim
- Laboratory of Biomedical Genomics and Oncogenetics, Pasteur Institute of Tunis, Tunis, Le Belvédère, Tunisia
| | - Majdi Nagara
- Laboratory of Biomedical Genomics and Oncogenetics, Pasteur Institute of Tunis, Tunis, Le Belvédère, Tunisia
| | | | - Sana Hsouna
- Laboratory of Biomedical Genomics and Oncogenetics, Pasteur Institute of Tunis, Tunis, Le Belvédère, Tunisia
| | - Khaled Lasram
- Laboratory of Biomedical Genomics and Oncogenetics, Pasteur Institute of Tunis, Tunis, Le Belvédère, Tunisia
| | - Rym Kefi
- Laboratory of Biomedical Genomics and Oncogenetics, Pasteur Institute of Tunis, Tunis, Le Belvédère, Tunisia
| | - Hela Azaiez
- Laboratory of Biomedical Genomics and Oncogenetics, Pasteur Institute of Tunis, Tunis, Le Belvédère, Tunisia
| | - Laroussi Khemira
- Laboratory of Biomedical Genomics and Oncogenetics, Pasteur Institute of Tunis, Tunis, Le Belvédère, Tunisia
| | - Rachid Saidane
- Laboratory of Biomedical Genomics and Oncogenetics, Pasteur Institute of Tunis, Tunis, Le Belvédère, Tunisia
| | - Slim Ben Ammar
- Clinical Biochemistry Laboratory, Pasteur Institute of Tunis, Tunis, Le Belvédère, Tunisia
| | - Ghazi Besbes
- ENT Department, la Rabta Hospital, Tunis, Tunisia
| | - Dominique Weil
- Inserm UMRS587, Unité de Génétique et Physiologie de l'Audition, Institut Pasteur, Paris Cedex 15, France
| | - Christine Petit
- Inserm UMRS587, Unité de Génétique et Physiologie de l'Audition, Institut Pasteur, Paris Cedex 15, France
| | - Sonia Abdelhak
- Laboratory of Biomedical Genomics and Oncogenetics, Pasteur Institute of Tunis, Tunis, Le Belvédère, Tunisia
| | - Lilia Romdhane
- Laboratory of Biomedical Genomics and Oncogenetics, Pasteur Institute of Tunis, Tunis, Le Belvédère, Tunisia
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40
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Karjalainen MK, Ojaniemi M, Haapalainen AM, Mahlman M, Salminen A, Huusko JM, Määttä TA, Kaukola T, Anttonen J, Ulvila J, Haataja R, Teramo K, Kingsmore SF, Palotie A, Muglia LJ, Rämet M, Hallman M. CXCR3 Polymorphism and Expression Associate with Spontaneous Preterm Birth. THE JOURNAL OF IMMUNOLOGY 2015. [PMID: 26209629 DOI: 10.4049/jimmunol.1501174] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Spontaneous preterm birth (SPTB) is a major factor associating with deaths and with lowered quality of life in humans. Environmental and genetic factors influence the susceptibility. Previously, by analyzing families with recurrent SPTB in linkage analysis, we identified a linkage peak close to the gene encoding CXCR3. Present objectives were to investigate the association of CXCR3 with SPTB in Finnish mothers (n = 443) and infants (n = 747), to analyze CXCR3 expression levels in human placenta and levels of its ligands in umbilical cord blood, and to verify the influence of Cxcr3 on SPTB-associating cytokines in mice. We detected an association between an intronic CXCR3 polymorphism, rs2280964, and SPTB in infants from families with recurrent preterm births (p = 0.009 versus term controls, odds ratio 0.52, 95% confidence interval 0.32-0.86). The minor allele was protective and undertransmitted to SPTB infants (p = 0.007). In the placenta and fetal membranes, the rs2280964 major allele homozygotes had higher expression levels than minor allele homozygotes; decidual trophoblasts showed strong CXCR3 immunoreactivity. Expression was higher in SPTB placentas compared with those from elective deliveries. Concentration of a CXCR3 ligand, CXCL9, was increased in cord blood from SPTB, and the protective rs2280964 allele was associated with low CXCL9. In CXCR3-deficient mice (Mus musculus), SPTB-associating cytokines were not acutely increased in amniotic fluid after preterm birth-inducing dose of maternal LPS. Our results indicate that CXCR3 contributes to SPTB. Activation of CXCR3 signaling may disturb the maternal-fetal tolerance, and this may promote labor.
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Affiliation(s)
- Minna K Karjalainen
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland;
| | - Marja Ojaniemi
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland
| | - Antti M Haapalainen
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland
| | - Mari Mahlman
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland
| | - Annamari Salminen
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland
| | - Johanna M Huusko
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland
| | - Tomi A Määttä
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland
| | - Tuula Kaukola
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland
| | - Julia Anttonen
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland
| | - Johanna Ulvila
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland
| | - Ritva Haataja
- Biocenter Oulu, University of Oulu, 90014 Oulu, Finland
| | - Kari Teramo
- Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland
| | | | - Aarno Palotie
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142; Institute for Molecular Medicine Finland, University of Helsinki, 00014 Helsinki, Finland; Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114; Department of Neurology, Massachusetts General Hospital, Boston, MA 02114
| | - Louis J Muglia
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229
| | - Mika Rämet
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland; BioMediTech, University of Tampere, 33014 Tampere, Finland; and Department of Pediatrics, Tampere University Hospital, 33521 Tampere, Finland
| | - Mikko Hallman
- PEDEGO Research Center and Medical Research Center Oulu, University of Oulu, 90014 Oulu, Finland; Department of Children and Adolescents, Oulu University Hospital, 90029 Oulu, Finland
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Reyes Fernández B, Rosero-Bixby L, Koivumaa-Honkanen H. Effects of Self-Rated Health and Self-Rated Economic Situation on Depressed Mood Via Life Satisfaction Among Older Adults in Costa Rica. J Aging Health 2015; 28:225-43. [PMID: 26092651 PMCID: PMC4748543 DOI: 10.1177/0898264315589577] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Objective: The study examined the relationship of self-rated health and self-rated economic situation with depressed mood, and life satisfaction as mediator of this relationship among older adults in Costa Rica. Method: A longitudinal study was conducted with a subsample (N = 1,618) from the Costa Rican Longevity and Healthy Aging Study (CRELES). Self-rated health, self-rated economic situation, depressed mood, and life satisfaction were measured at baseline, and depressed mood was reassessed 18 months later. Putative mechanisms for changes in depressed mood were examined by means of conditional process analysis. Results: Self-rated health was negatively associated to depressed mood. This effect took place via life satisfaction. An interaction showed that better economic situation compensated the effect of a low self-rated health on life satisfaction. Discussion: This study suggests that subjective variables such as self-rated health, economic situation, and life satisfaction should be considered when addressing the onset of depressed mood.
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Affiliation(s)
| | - Luis Rosero-Bixby
- Universidad de Costa Rica, Costa Rica University of California, Berkeley
| | - Heli Koivumaa-Honkanen
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio Department of Psychiatry, Kuopio University Hospital, Finland Department of Psychiatry, South-Savonia Hospital District, Mikkeli, Finland Department of Psychiatry, North Karelia Central Hospital, Joensuu, Finland Department of Psychiatry, SOSTERI, Savonlinna, Finland Department of Psychiatry, SOTE, Iisalmi, Finland Department of Psychiatry, Lapland Hospital District, Rovaniemi, Finland Clinic of Child Psychiatry, Oulu University Hospital, Oulu, Finland
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42
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Cousminer DL, Leinonen JT, Sarin AP, Chheda H, Surakka I, Wehkalampi K, Ellonen P, Ripatti S, Dunkel L, Palotie A, Widén E. Targeted resequencing of the pericentromere of chromosome 2 linked to constitutional delay of growth and puberty. PLoS One 2015; 10:e0128524. [PMID: 26030606 PMCID: PMC4452275 DOI: 10.1371/journal.pone.0128524] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2015] [Accepted: 04/28/2015] [Indexed: 01/30/2023] Open
Abstract
Constitutional delay of growth and puberty (CDGP) is the most common cause of pubertal delay. CDGP is defined as the proportion of the normal population who experience pubertal onset at least 2 SD later than the population mean, representing 2.3% of all adolescents. While adolescents with CDGP spontaneously enter puberty, they are at risk for short stature, decreased bone mineral density, and psychosocial problems. Genetic factors contribute heavily to the timing of puberty, but the vast majority of CDGP cases remain biologically unexplained, and there is no definitive test to distinguish CDGP from pathological absence of puberty during adolescence. Recently, we published a study identifying significant linkage between a locus at the pericentromeric region of chromosome 2 (chr 2) and CDGP in Finnish families. To investigate this region for causal variation, we sequenced chr 2 between the genomic coordinates of 79-124 Mb (genome build GRCh37) in the proband and affected parent of the 13 families contributing most to this linkage signal. One gene, DNAH6, harbored 6 protein-altering low-frequency variants (< 6% in the Finnish population) in 10 of the CDGP probands. We sequenced an additional 135 unrelated Finnish CDGP subjects and utilized the unique Sequencing Initiative Suomi (SISu) population reference exome set to show that while 5 of these variants were present in the CDGP set, they were also present in the Finnish population at similar frequencies. Additional variants in the targeted region could not be prioritized for follow-up, possibly due to gaps in sequencing coverage or lack of functional knowledge of non-genic genomic regions. Thus, despite having a well-characterized sample collection from a genetically homogeneous population with a large population-based reference sequence dataset, we were unable to pinpoint variation in the linked region predisposing delayed puberty. This study highlights the difficulties of detecting genetic variants under linkage regions for complex traits and suggests that advancements in annotation of gene function and regulatory regions of the genome will be critical for solving the genetic background of complex phenotypes like CDGP.
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Affiliation(s)
- Diana L. Cousminer
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- * E-mail:
| | - Jaakko T. Leinonen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Himanshu Chheda
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Ida Surakka
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Karoliina Wehkalampi
- Diabetes Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
- Children’s Hospital, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Pekka Ellonen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki, Finland
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Leo Dunkel
- Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, London, United Kingdom
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
- The Medical and Population Genomics Program, Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
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Pugach I, Stoneking M. Genome-wide insights into the genetic history of human populations. INVESTIGATIVE GENETICS 2015; 6:6. [PMID: 25834724 PMCID: PMC4381409 DOI: 10.1186/s13323-015-0024-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/25/2014] [Accepted: 03/05/2015] [Indexed: 12/21/2022]
Abstract
Although mtDNA and the non-recombining Y chromosome (NRY) studies continue to provide valuable insights into the genetic history of human populations, recent technical, methodological and computational advances and the increasing availability of large-scale, genome-wide data from contemporary human populations around the world promise to reveal new aspects, resolve finer points, and provide a more detailed look at our past demographic history. Genome-wide data are particularly useful for inferring migrations, admixture, and fine structure, as well as for estimating population divergence and admixture times and fluctuations in effective population sizes. In this review, we highlight some of the stories that have emerged from the analyses of genome-wide SNP genotyping data concerning the human history of Southern Africa, India, Oceania, Island South East Asia, Europe and the Americas and comment on possible future study directions. We also discuss advantages and drawbacks of using SNP-arrays, with a particular focus on the ascertainment bias, and ways to circumvent it.
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Affiliation(s)
- Irina Pugach
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D04103 Leipzig, Germany
| | - Mark Stoneking
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D04103 Leipzig, Germany
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Kainu A, Timonen KL, Toikka J, Qaiser B, Pitkäniemi J, Kotaniemi JT, Lindqvist A, Vanninen E, Länsimies E, Sovijärvi ARA. Reference values of spirometry for Finnish adults. Clin Physiol Funct Imaging 2015; 36:346-58. [PMID: 25817817 DOI: 10.1111/cpf.12237] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2014] [Accepted: 01/27/2015] [Indexed: 12/01/2022]
Abstract
BACKGROUND Diagnostic assessment of lung function necessitates up-to-date reference values. The aim of this study was to estimate reference values for spirometry for the Finnish population between 18 and 80 years and to compare them with the existing Finnish, European and the recently published global GLI2012 reference values. METHODS Spirometry was performed for 1380 adults in the population-based FinEsS studies and for 662 healthy non-smoking volunteer adults. Detailed predefined questionnaire screening of diseases and symptoms, and quality control of spirometry yielded a sample of 1000 native Finns (387 men) healthy non-smokers aged 18-83 years. Sex-specific reference values, which are estimated using the GAMLSS method and adjusted for age and height, are provided. RESULTS The predicted values for lung volumes are larger than those obtained by GLI2012 prediction for the Caucasian subgroup for forced vital capacity (FVC) by an average 6·2% and 5·1% and forced expiratory volume in 1 s (FEV1) by an average 4·2% and 3·0% in men and women, respectively. GLI2012 slightly overestimated the ratio FEV1/FVC with an age-dependent trend. Most reference equations from other European countries, with the exception of the Swiss SAPALDIA study, showed an underestimation of FVC and FEV1 to varying degrees, and a slight overestimation of FEV1/FVC. CONCLUSION This study offers up-to-date reference values of spirometry for native Finns with a wide age range. The GLI2012 predictions seem not to be suitable for clinical use for native Finns due to underestimation of lung volumes.
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Affiliation(s)
- A Kainu
- Department of Pulmonary Medicine, HUCH Heart and Lung Center, Peijas Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - K L Timonen
- Department of Clinical Physiology, Central Hospital of Central Finland, Jyväskylä, Finland.,Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland
| | - J Toikka
- Department of Clinical Physiology, Turku University Hospital, Turku, Finland.,Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - B Qaiser
- Department of Public Health, Hjelt -institute, University of Helsinki, Helsinki, Finland
| | - J Pitkäniemi
- Department of Public Health, Hjelt -institute, University of Helsinki, Helsinki, Finland
| | - J T Kotaniemi
- Department of Respiratory Diseases, Tampere University Hospital, Tampere, Finland
| | - A Lindqvist
- Research Unit of Pulmonary Diseases, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - E Vanninen
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland
| | - E Länsimies
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland
| | - A R A Sovijärvi
- Department of Clinical Physiology and Nuclear Medicine, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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Huusko JM, Mahlman M, Karjalainen MK, Kaukola T, Haataja R, Marttila R, Toldi G, Szabó M, Kingsmore SF, Rämet M, Lavoie PM, Hallman M. Polymorphisms of the gene encoding Kit ligand are associated with bronchopulmonary dysplasia. Pediatr Pulmonol 2015; 50:260-270. [PMID: 24610823 DOI: 10.1002/ppul.23018] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Accepted: 01/17/2014] [Indexed: 12/21/2022]
Abstract
UNLABELLED Bronchopulmonary dysplasia (BPD) is a chronic inflammatory lung disease that affects infants born preterm. Family studies indicate that BPD has a significant genetic component. RATIONALE We assessed the gene encoding Kit ligand (KITLG) as a candidate for genetic predisposition to moderate-to-severe BPD (controls were infants with no or mild BPD). STUDY DESIGN Eight KITLG-tagging single nucleotide polymorphisms (SNPs) were analyzed in cohorts of very preterm infants originating from northern Finland (56 cases and 197 controls), southern Finland (n = 59 + 52), and Canada (n = 58 + 68). Additional replication populations included infants born in Finland (n = 41 + 241) and Hungary (n = 29 + 40). All infants were of European origin. Results were controlled for risk factors of BPD. Kit ligand concentration in umbilical cord blood, collected from very preterm infants (n = 120), was studied. RESULTS Six SNPs of KITLG and a haplotype including all eight genotyped SNPs were associated with moderate-to-severe BPD in the northern Finnish population. When all the populations were combined, SNP rs11104948 was significantly associated with BPD. Kit ligand concentration in umbilical cord blood of infants born very preterm was an independent risk factor of BPD. CONCLUSIONS We show that KITLG polymorphisms are associated with susceptibility to moderate-to-severe BPD. In addition, higher Kit ligand concentrations were observed in infants that subsequently developed BPD. These results support the possibility that KITLG gene is involved in predisposition to BPD. Pediatr Pulmonol. 2015; 50:260-270. © 2014 Wiley Periodicals, Inc.
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Affiliation(s)
- Johanna M Huusko
- Department of Pediatrics, Institute of Clinical Medicine, and Medical Research Center Oulu, University of Oulu, Oulu, Finland.,Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Mari Mahlman
- Department of Pediatrics, Institute of Clinical Medicine, and Medical Research Center Oulu, University of Oulu, Oulu, Finland.,Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Minna K Karjalainen
- Department of Pediatrics, Institute of Clinical Medicine, and Medical Research Center Oulu, University of Oulu, Oulu, Finland.,Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Tuula Kaukola
- Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Ritva Haataja
- Department of Pediatrics, Institute of Clinical Medicine, and Medical Research Center Oulu, University of Oulu, Oulu, Finland
| | - Riitta Marttila
- Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Gergely Toldi
- First Department of Pediatrics, Semmelweis University, Budapest, Hungary
| | - Miklós Szabó
- First Department of Pediatrics, Semmelweis University, Budapest, Hungary
| | | | - Mika Rämet
- Department of Pediatrics, Institute of Clinical Medicine, and Medical Research Center Oulu, University of Oulu, Oulu, Finland.,Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland.,Institute of Biomedical Technology, and BioMediTech, University of Tampere, Finland.,Department of Pediatrics, Tampere University Hospital, Tampere, Finland
| | - Pascal M Lavoie
- Child & Family Research Institute of British Columbia, Vancouver, Canada
| | - Mikko Hallman
- Department of Pediatrics, Institute of Clinical Medicine, and Medical Research Center Oulu, University of Oulu, Oulu, Finland.,Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
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LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet 2015; 47:291-5. [PMID: 25642630 DOI: 10.1038/ng.3211] [Citation(s) in RCA: 3421] [Impact Index Per Article: 342.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2014] [Accepted: 01/07/2015] [Indexed: 12/16/2022]
Abstract
Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.
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Karafet TM, Bulayeva KB, Bulayev OA, Gurgenova F, Omarova J, Yepiskoposyan L, Savina OV, Veeramah KR, Hammer MF. Extensive genome-wide autozygosity in the population isolates of Daghestan. Eur J Hum Genet 2015; 23:1405-12. [PMID: 25604856 DOI: 10.1038/ejhg.2014.299] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2014] [Revised: 12/09/2014] [Accepted: 12/19/2014] [Indexed: 01/01/2023] Open
Abstract
Isolated populations are valuable resources for mapping disease genes, as inbreeding increases genome-wide homozygosity and enhances the ability to map disease alleles on a genetically uniform background within a relatively homogenous environment. The populations of Daghestan are thought to have resided in the Caucasus Mountains for hundreds of generations and are characterized by a high prevalence of certain complex diseases. To explore the extent to which their unique population history led to increased levels of inbreeding, we genotyped >550 000 autosomal single-nucleotide polymorphisms (SNPs) in a set of 14 population isolates speaking Nakh-Daghestanian (ND) languages. The ND-speaking populations showed greatly elevated coefficients of inbreeding, very high numbers and long lengths of Runs of Homozygosity, and elevated linkage disequilibrium compared with surrounding groups from the Caucasus, the Near East, Europe, Central and South Asia. These results are consistent with the hypothesis that most ND-speaking groups descend from a common ancestral population that fragmented into a series of genetic isolates in the Daghestanian highlands. They have subsequently maintained a long-term small effective population size as a result of constant inbreeding and very low levels of gene flow. Given these findings, Daghestanian population isolates are likely to be useful for mapping genes associated with complex diseases.
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Affiliation(s)
- Tatiana M Karafet
- ARL Division of Biotechnology, University of Arizona, Tucson, AZ, USA
| | - Kazima B Bulayeva
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Oleg A Bulayev
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Farida Gurgenova
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Jamilia Omarova
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Levon Yepiskoposyan
- Institute of Molecular Biology, National Academy of Sciences, Yerevan, Armenia
| | - Olga V Savina
- ARL Division of Biotechnology, University of Arizona, Tucson, AZ, USA
| | | | - Michael F Hammer
- ARL Division of Biotechnology, University of Arizona, Tucson, AZ, USA
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Mahlman M, Huusko JM, Karjalainen MK, Kaukola T, Marttila R, Ojaniemi M, Haataja R, Lavoie PM, Rämet M, Hallman M. Genes Encoding Vascular Endothelial Growth Factor A (VEGF-A) and VEGF Receptor 2 (VEGFR-2) and Risk for Bronchopulmonary Dysplasia. Neonatology 2015; 108:53-9. [PMID: 25998098 DOI: 10.1159/000381279] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Accepted: 02/26/2015] [Indexed: 11/19/2022]
Abstract
BACKGROUND Bronchopulmonary dysplasia (BPD) is one of the main consequences of prematurity, with notably high heritability. Vascular endothelial growth factor A (VEGF-A) and its main receptor, vascular endothelial growth factor receptor 2 (VEGFR-2), have been implicated in the pathogenesis of BPD. OBJECTIVE To study whether common polymorphisms of the genes encoding VEGF-A and VEGFR-2 are associated with BPD. METHODS In this association study, six tagging single nucleotide polymorphism (tSNPs) for VEGFA and 25 tSNPs for VEGFR2 were genotyped in a prospectively collected, genetically homogeneous discovery population of 160 infants (44 infants with grade 2-3 BPD) born before 30 completed gestational weeks. The replication population of 328 infants included 120 cases of BPD. RESULTS VEGFR2 SNP rs4576072 was associated with BPD grade 2-3 with a minor allele frequency in 23.9% of the cases compared to 9.1% in controls (p = 0.0005, odds ratio 3.15, 95% CI: 1.62-6.12) in the discovery population. This association was not observed in the more heterogeneous replication population. CONCLUSIONS In line with the results of recent large-scale genetic studies, our findings indicate that common polymorphisms of the genes encoding VEGF-A and VEGFR-2 are not consistently associated with BPD. This finding does not rule out the involvement of VEGFA and VEGFR2 in BPD pathogenesis since, in addition to common variations within the gene region, other mechanisms also play important roles in the regulation of gene function.
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Affiliation(s)
- Mari Mahlman
- PEDEGO Research Center, and Medical Research Center Oulu, University of Oulu, Oulu, Finland
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Huusko JM, Karjalainen MK, Mahlman M, Haataja R, Kari MA, Andersson S, Toldi G, Tammela O, Rämet M, Lavoie PM, Hallman M. A study of genes encoding cytokines (IL6, IL10, TNF), cytokine receptors (IL6R, IL6ST), and glucocorticoid receptor (NR3C1) and susceptibility to bronchopulmonary dysplasia. BMC MEDICAL GENETICS 2014; 15:120. [PMID: 25409741 PMCID: PMC4258941 DOI: 10.1186/s12881-014-0120-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 06/24/2014] [Accepted: 10/13/2014] [Indexed: 11/23/2022]
Abstract
Background Bronchopulmonary dysplasia (BPD) is a common chronic lung disease associated with very preterm birth. The major risk factors include lung inflammation and lung immaturity. In addition, genetic factors play an important role in susceptibility to moderate-to-severe BPD. In this study, the aim was to investigate whether common polymorphisms of specific genes that are involved in inflammation or differentiation of the lung have influence on BPD susceptibility. Methods Genes encoding interleukin-6 (IL6) and its receptors (IL6R and IL6ST), IL-10 (IL10), tumor necrosis factor (TNF), and glucocorticoid receptor (NR3C1) were assessed for associations with moderate-to-severe BPD susceptibility. Five IL6, nine IL6R, four IL6ST, one IL10, two TNF, and 23 NR3C1 single nucleotide polymorphisms (SNPs) were analyzed in very preterm infants born in northern Finland (56 cases and 197 controls) and Canada (58 cases and 68 controls). IL-6, TNF and gp130 contents in umbilical cord blood, collected from very preterm infants, were studied for associations with the polymorphisms. Epistasis (i.e., interactions between SNPs in BPD susceptibility) was also examined. SNPs showing suggestive associations were analyzed in additional replication populations from Finland (39 cases and 188 controls) and Hungary (29 cases and 40 controls). Results None of the studied SNPs were associated with BPD nor were the IL6, TNF or IL6ST SNPs associated with cord blood IL-6, TNF and gp130, respectively. However, epistasis analysis suggested that SNPs in IL6ST and IL10 were associated interactively with risk of BPD in the northern Finnish population; however, this finding did not remain significant after correction for multiple testing and the finding was not replicated in the other populations. Conclusions We conclude that the analyzed SNPs within IL6, IL6R, IL6ST, IL10, TNF, and NR3C1 were not associated with BPD. Furthermore, there was no evidence that the studied SNPs directly contribute to the cord blood protein contents. Electronic supplementary material The online version of this article (doi:10.1186/s12881-014-0120-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Johanna M Huusko
- Department of Pediatrics, Institute of Clinical Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland.
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