651
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Gomez-Raya L, Rodríguez C, Barragán C, Silió L. Genomic inbreeding coefficients based on the distribution of the length of runs of homozygosity in a closed line of Iberian pigs. Genet Sel Evol 2015; 47:81. [PMID: 26475049 PMCID: PMC4608316 DOI: 10.1186/s12711-015-0153-1] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2014] [Accepted: 09/13/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The increasing availability of DNA markers provides new metrics of inbreeding based on single nucleotide polymorphisms (SNPs), i.e. molecular inbreeding or the proportion of runs of homozygosity (ROH), as alternatives to traditional pedigree-based inbreeding coefficients. However, none of these metrics incorporate the length of ROH as an indicator of recent inbreeding. Novel inbreeding coefficients that incorporate length of ROH as a random variable with an associated density are investigated. METHODS New inbreeding metrics based on the distribution of the length of ROH are proposed: (1) the Kolmolgorov-Smirnov test, (2) a function of the quantiles of the cumulative distribution function of an individual versus the population, and (3) fitting of an exponential distribution to ROH lengths (mean, variance, and the probability of drawing at random a ROH larger than a given threshold). The new inbreeding and pedigree-based metrics were compared using 217 sows of an Iberian line that belong to three groups: C1 (conservation), C2 (conservation derived from C1), and S (selected and derived from C1), with complete pedigrees and genotyped for 35,023 SNPs. RESULTS Correlations between pedigree-based and the new genomic inbreeding coefficients ranged from 0.22 to 0.72 but most ranged from 0.60 to 0.70. The correlation between quantile chromosomal inbreeding coefficients (using molecular information of just one chromosome at the time) and chromosomal length was 0.84 (SE = 0.14), supporting the hypothesis that these coefficients incorporate information on ROH length as an indication of recent inbreeding. Kolmogorov-Smirnov and exponential chromosomal inbreeding coefficients were also correlated with chromosomal length (0.57). Chromosome 1 had the largest quantile ROH inbreeding coefficient (largest ROH sizes), whereas chromosome 10 had the lowest (shortest ROH sizes). Selection for lean growth increased ROH-based inbreeding coefficients for group S when compared to unselected groups C1 and C2. At the chromosomal level, this comparison showed that the level of autozygosity and the length of ROH for most of the autosomes increased in the selection line. CONCLUSIONS Quantile and exponential probability inbreeding coefficients using ROH length as a random variable provide additional information about recent inbreeding compared to existing inbreeding coefficients such as molecular, pedigree-based or total ROH content inbreeding coefficients.
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Affiliation(s)
- Luis Gomez-Raya
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Ctra. de La Coruña km 7, 28040, Madrid, Spain.
| | - Carmen Rodríguez
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Ctra. de La Coruña km 7, 28040, Madrid, Spain.
| | - Carmen Barragán
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Ctra. de La Coruña km 7, 28040, Madrid, Spain.
| | - Luis Silió
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Ctra. de La Coruña km 7, 28040, Madrid, Spain.
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652
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Iourov IY, Vorsanova SG, Korostelev SA, Zelenova MA, Yurov YB. Long contiguous stretches of homozygosity spanning shortly the imprinted loci are associated with intellectual disability, autism and/or epilepsy. Mol Cytogenet 2015; 8:77. [PMID: 26478745 PMCID: PMC4608298 DOI: 10.1186/s13039-015-0182-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Accepted: 09/27/2015] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Long contiguous stretches of homozygosity (LCSH) (regions/runs of homozygosity) are repeatedly detected by single-nucleotide polymorphism (SNP) chromosomal microarrays. Providing important clues regarding parental relatedness (consanguinity), uniparental disomy, chromosomal recombination or rearrangements, LCSH are rarely considered as a possible epigenetic cause of neurodevelopmental disorders. Additionally, despite being relevant to imprinting, LCSH at imprinted loci have not been truly addressed in terms of pathogenicity. In this study, we examined LCSH in children with unexplained intellectual disability, autism, congenital malformations and/or epilepsy focusing on chromosomal regions which harbor imprinted disease genes. RESULTS Out of 267 cases, 14 (5.2 %) were found to have LCSH at imprinted loci associated with a clinical outcome. There were 5 cases of LCSH at 15p11.2, 4 cases of LCSH at 7q31.2, 3 cases of LCSH at 11p15.5, and 2 cases of LCSH at 7q21.3. Apart from a case of LCSH at 7q31.33q32.3 (~4 Mb in size), all causative LCSH were 1-1.5 Mb in size. Clinically, these cases were characterized by a weak resemblance to corresponding imprinting diseases (i.e., Silver-Russell, Beckwith-Wiedemann, and Prader-Willi/Angelman syndromes), exhibiting distinctive intellectual disability, autistic behavior, developmental delay, seizures and/or facial dysmorphisms. Parental consanguinity was detected in 8 cases (3 %), and these cases did not exhibit LCSH at imprinted loci. CONCLUSIONS This study demonstrates that shorter LCSH at chromosomes 7q21.3, 7q31.2, 11p15.5, and 15p11.2 occur with a frequency of about 5 % in the children with intellectual disability, autism, congenital malformations and/or epilepsy. Consequently, this type of epigenetic mutations appears to be the most common one among children with neurodevelopmental diseases. Finally, since LCSH less than 2.5-10 Mb in size are generally ignored in diagnostic SNP microarray studies, one can conclude that an important epigenetic cause of intellectual disability, autism or epilepsy is actually overlooked.
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Affiliation(s)
- Ivan Y. Iourov
- />Mental Health Research Center, 117152 Moscow, Russia
- />Separated Structural Unit “Clinical Research Institute of Pediatrics”, Russian National Research Medical University named after N.I. Pirogov, Ministry of Health of Russian Federation, 125412 Moscow, Russia
- />Department of Medical Genetics, Russian Medical Academy of Postgraduate Education, 123995 Moscow, Russia
| | - Svetlana G. Vorsanova
- />Mental Health Research Center, 117152 Moscow, Russia
- />Separated Structural Unit “Clinical Research Institute of Pediatrics”, Russian National Research Medical University named after N.I. Pirogov, Ministry of Health of Russian Federation, 125412 Moscow, Russia
| | | | - Maria A. Zelenova
- />Mental Health Research Center, 117152 Moscow, Russia
- />Separated Structural Unit “Clinical Research Institute of Pediatrics”, Russian National Research Medical University named after N.I. Pirogov, Ministry of Health of Russian Federation, 125412 Moscow, Russia
| | - Yuri B. Yurov
- />Mental Health Research Center, 117152 Moscow, Russia
- />Separated Structural Unit “Clinical Research Institute of Pediatrics”, Russian National Research Medical University named after N.I. Pirogov, Ministry of Health of Russian Federation, 125412 Moscow, Russia
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653
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Metzger J, Karwath M, Tonda R, Beltran S, Águeda L, Gut M, Gut IG, Distl O. Runs of homozygosity reveal signatures of positive selection for reproduction traits in breed and non-breed horses. BMC Genomics 2015; 16:764. [PMID: 26452642 PMCID: PMC4600213 DOI: 10.1186/s12864-015-1977-3] [Citation(s) in RCA: 83] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2015] [Accepted: 10/03/2015] [Indexed: 11/24/2022] Open
Abstract
Background Modern horses represent heterogeneous populations specifically selected for appearance and performance. Genomic regions under high selective pressure show characteristic runs of homozygosity (ROH) which represent a low genetic diversity. This study aims at detecting the number and functional distribution of ROHs in different horse populations using next generation sequencing data. Methods Next generation sequencing was performed for two Sorraia, one Dülmen Horse, one Arabian, one Saxon-Thuringian Heavy Warmblood, one Thoroughbred and four Hanoverian. After quality control reads were mapped to the reference genome EquCab2.70. ROH detection was performed using PLINK, version 1.07 for a trimmed dataset with 11,325,777 SNPs and a mean read depth of 12. Stretches with homozygous genotypes of >40 kb as well as >400 kb were defined as ROHs. SNPs within consensus ROHs were tested for neutrality. Functional classification was done for genes annotated within ROHs using PANTHER gene list analysis and functional variants were tested for their distribution among breed or non-breed groups. Results ROH detection was performed using whole genome sequences of ten horses of six populations representing various breed types and non-breed horses. In total, an average number of 3492 ROHs were detected in windows of a minimum of 50 consecutive homozygous SNPs and an average number of 292 ROHs in windows of 500 consecutive homozygous SNPs. Functional analyses of private ROHs in each horse revealed a high frequency of genes affecting cellular, metabolic, developmental, immune system and reproduction processes. In non-breed horses, 198 ROHs in 50-SNP windows and seven ROHs in 500-SNP windows showed an enrichment of genes involved in reproduction, embryonic development, energy metabolism, muscle and cardiac development whereas all seven breed horses revealed only three common ROHs in 50-SNP windows harboring the fertility-related gene YES1. In the Hanoverian, a total of 18 private ROHs could be shown to be located in the region of genes potentially involved in neurologic control, signaling, glycogen balance and reproduction. Comparative analysis of homozygous stretches common in all ten horses displayed three ROHs which were all located in the region of KITLG, the ligand of KIT known to be involved in melanogenesis, haematopoiesis and gametogenesis. Conclusions The results of this study give a comprehensive insight into the frequency and number of ROHs in various horses and their potential influence on population diversity and selection pressures. Comparisons of breed and non-breed horses suggest a significant artificial as well as natural selection pressure on reproduction performance in all types of horse populations. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1977-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Julia Metzger
- Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover, Bünteweg 17p, 30559, Hannover, Germany.
| | - Matthias Karwath
- Lower Saxony State Office for the Environment, Agriculture and Geology, Unit 74, Animal Breeding and Hygiene, Schlossallee 1, 01468, Moritzburg, Germany.
| | - Raul Tonda
- Centro Nacional de Análisis Genómico, Parc Científic de Barcelona, Torre I Baldiri Reixac, 4, 08028, Barcelona, Spain.
| | - Sergi Beltran
- Centro Nacional de Análisis Genómico, Parc Científic de Barcelona, Torre I Baldiri Reixac, 4, 08028, Barcelona, Spain.
| | - Lídia Águeda
- Centro Nacional de Análisis Genómico, Parc Científic de Barcelona, Torre I Baldiri Reixac, 4, 08028, Barcelona, Spain.
| | - Marta Gut
- Centro Nacional de Análisis Genómico, Parc Científic de Barcelona, Torre I Baldiri Reixac, 4, 08028, Barcelona, Spain.
| | - Ivo Glynne Gut
- Centro Nacional de Análisis Genómico, Parc Científic de Barcelona, Torre I Baldiri Reixac, 4, 08028, Barcelona, Spain.
| | - Ottmar Distl
- Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover, Bünteweg 17p, 30559, Hannover, Germany.
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654
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Knopp C, Rudnik-Schöneborn S, Eggermann T, Bergmann C, Begemann M, Schoner K, Zerres K, Ortiz Brüchle N. Syndromic ciliopathies: From single gene to multi gene analysis by SNP arrays and next generation sequencing. Mol Cell Probes 2015; 29:299-307. [DOI: 10.1016/j.mcp.2015.05.008] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Revised: 05/13/2015] [Accepted: 05/19/2015] [Indexed: 01/23/2023]
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655
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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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656
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Somatic mosaicism for copy-neutral loss of heterozygosity and DNA copy number variations in the human genome. BMC Genomics 2015; 16:703. [PMID: 26376747 PMCID: PMC4573927 DOI: 10.1186/s12864-015-1916-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2015] [Accepted: 09/09/2015] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Somatic mosaicism denotes the presence of genetically distinct populations of somatic cells in one individual who has developed from a single fertilised oocyte. Mosaicism may result from a mutation that occurs during postzygotic development and is propagated to only a subset of the adult cells. Our aim was to investigate both somatic mosaicism for copy-neutral loss of heterozygosity (cn-LOH) events and DNA copy number variations (CNVs) in fully differentiated tissues. RESULTS We studied panels of tissue samples (11-12 tissues per individual) from four autopsy subjects using high-resolution Illumina HumanOmniExpress-12 BeadChips to reveal the presence of possible intra-individual tissue-specific cn-LOH and CNV patterns. We detected five mosaic cn-LOH regions >5 Mb in some tissue samples in three out of four individuals. We also detected three CNVs that affected only a portion of the tissues studied in one out of four individuals. These three somatic CNVs range from 123 to 796 kb and are also found in the general population. An attempt was made to explain the succession of genomic events that led to the observed somatic genetic mosaicism under the assumption that the specific mosaic patterns of CNV and cn-LOH changes reflect their formation during the postzygotic embryonic development of germinal layers and organ systems. CONCLUSIONS Our results give further support to the idea that somatic mosaicism for CNVs, and also cn-LOHs, is a common phenomenon in phenotypically normal humans. Thus, the examination of only a single tissue might not provide enough information to diagnose potentially deleterious CNVs within an individual. During routine CNV and cn-LOH analysis, DNA derived from a buccal swab can be used in addition to blood DNA to get information about the CNV/cn-LOH content in tissues of both mesodermal and ectodermal origin. Currently, the real frequency and possible phenotypic consequences of both CNVs and cn-LOHs that display somatic mosaicism remain largely unknown. To answer these questions, future studies should involve larger cohorts of individuals and a range of tissues.
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657
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Binzer S, Stenager E, Binzer M, Kyvik KO, Hillert J, Imrell K. Genetic analysis of the isolated Faroe Islands reveals SORCS3 as a potential multiple sclerosis risk gene. Mult Scler 2015; 22:733-40. [DOI: 10.1177/1352458515602338] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Accepted: 07/21/2015] [Indexed: 11/15/2022]
Abstract
Background: In search of the missing heritability in multiple sclerosis (MS), additional approaches adding to the genetic discoveries of large genome-wide association studies are warranted. Objective: The objective of this research paper is to search for rare genetic MS risk variants in the genetically homogenous population of the isolated Faroe Islands. Methods: Twenty-nine Faroese MS cases and 28 controls were genotyped with the HumanOmniExpressExome-chip. The individuals make up 1596 pair-combinations in which we searched for identical-by-descent shared segments using the PLINK-program. Results: A segment spanning 63 SNPs with excess case-case-pair sharing was identified (0.00173 < p > 0.00212). A haplotype consisting of 42 of the 63 identified SNPs which spanned the entire the Sortilin-related vacuolar protein sorting 10 domain containing receptor 3 ( SORCS3) gene had a carrier frequency of 0.34 in cases but was not present in any controls ( p = 0.0008). Conclusion: This study revealed an oversharing in case-case-pairs of a segment spanning 63 SNPs and the entire SORCS3. While not previously associated with MS, SORCS3 appears to be important in neuronal plasticity through its binding of neurotrophin factors and involvement in glutamate homeostasis. Although additional work is needed to scrutinise the genetic effect of the SORCS3-covering haplotype, this study suggests that SORCS3 may also be important in MS pathogenesis.
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Affiliation(s)
- S Binzer
- Institute of Regional Health Research, University of Southern Denmark, Denmark/Hospital of Southern Jutland, Denmark/Odense Patient data Explorative Network (OPEN), University of Southern Denmark, Denmark/ Torshavn National Hospital, Faroe Islands
| | - E Stenager
- Institute of Regional Health Research, University of Southern Denmark, Denmark/Hospital of Southern Jutland, Denmark/ MS Clinic of Southern Jutland (Sønderborg, Esbjerg, Vejle), Department of Neurology, Denmark
| | - M Binzer
- Institute of Regional Health Research, University of Southern Denmark, Denmark
| | - KO Kyvik
- Department of Clinical Research, University of Southern Denmark, Denmark/Odense Patient data Explorative Network (OPEN), University of Southern Denmark, Denmark
| | - J Hillert
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - K Imrell
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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658
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Polašek O. Global mobility and the break-up of human population isolates - neglected mechanisms in health, demographics, and anthropology. Croat Med J 2015; 56:324-5. [PMID: 26321024 PMCID: PMC4576745 DOI: 10.3325/cmj.2015.56.324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Affiliation(s)
- Ozren Polašek
- Ozren Polašek, Medical School, University of Split, Split, Croatia,
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659
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Pajusalu S, Žilina O, Yakoreva M, Tammur P, Kuuse K, Mölter-Väär T, Nõukas M, Reimand T, Õunap K. The Diagnostic Utility of Single Long Contiguous Stretches of Homozygosity in Patients without Parental Consanguinity. Mol Syndromol 2015; 6:135-40. [PMID: 26733775 DOI: 10.1159/000438776] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/30/2015] [Indexed: 01/13/2023] Open
Abstract
We present data from our clinical department's experience with chromosomal microarray analysis (CMA) regarding the diagnostic utility of 1 or 2 long contiguous stretches of homozygosity (LCSHs) in an outbred population. The study group consisted of 2,110 consecutive patients from 2011 to 2014 for whom CMA was performed. The minimum cut-off size for defining a homozygous stretch was 5 Mb. To focus on cases with no parental consanguinity, we further studied only patients in whom the total length of homozygous stretches did not exceed 28 Mb or 1% of the autosomal genome length. We identified 6 chromosomal regions where homozygous stretches appeared in at least 3 patients and excluded these from further analysis. In 2 out of 120 patients with an isolated finding of 1 or 2 non-recurrent LCSHs, a plausible candidate gene associated with their phenotype was identified within the homozygous stretch. In both of these cases, a pathogenic mutation was detected, leading to diagnoses of pyruvate kinase deficiency and Marinesco-Sjögren syndrome. To clarify whether previously found homozygous stretches could be important for the interpretation of genome-wide sequencing data, we report 7 cases in which homozygous stretches not encompassing a clinically associated gene were first found on CMA, followed by the diagnostic whole-exome sequencing. The diagnostic utility of single LCSHs, unlikely to be caused by uniparental disomy, is discussed in detail.
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Affiliation(s)
- Sander Pajusalu
- Department of Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia; Department of Biomedicine, Institute of Biomedicine and Translational Medicine, Tartu, Estonia
| | - Olga Žilina
- Department of Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia; Institute of Molecular and Cell Biology, Tartu, Estonia
| | - Maria Yakoreva
- Department of Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia; Department of Pediatrics, University of Tartu, Tartu, Estonia
| | - Pille Tammur
- Department of Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Kati Kuuse
- Department of Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Triin Mölter-Väär
- Department of Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Margit Nõukas
- Institute of Molecular and Cell Biology, Tartu, Estonia; Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Tiia Reimand
- Department of Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia; Department of Biomedicine, Institute of Biomedicine and Translational Medicine, Tartu, Estonia; Department of Pediatrics, University of Tartu, Tartu, Estonia
| | - Katrin Õunap
- Department of Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia; Department of Pediatrics, University of Tartu, Tartu, Estonia
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660
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Christofidou P, Nelson CP, Nikpay M, Qu L, Li M, Loley C, Debiec R, Braund PS, Denniff M, Charchar FJ, Arjo AR, Trégouët DA, Goodall AH, Cambien F, Ouwehand WH, Roberts R, Schunkert H, Hengstenberg C, Reilly MP, Erdmann J, McPherson R, König IR, Thompson JR, Samani NJ, Tomaszewski M. Runs of Homozygosity: Association with Coronary Artery Disease and Gene Expression in Monocytes and Macrophages. Am J Hum Genet 2015; 97:228-37. [PMID: 26166477 PMCID: PMC4573243 DOI: 10.1016/j.ajhg.2015.06.001] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2014] [Accepted: 06/04/2015] [Indexed: 02/07/2023] Open
Abstract
Runs of homozygosity (ROHs) are recognized signature of recessive inheritance. Contributions of ROHs to the genetic architecture of coronary artery disease and regulation of gene expression in cells relevant to atherosclerosis are not known. Our combined analysis of 24,320 individuals from 11 populations of white European ethnicity showed an association between coronary artery disease and both the count and the size of ROHs. Individuals with coronary artery disease had approximately 0.63 (95% CI: 0.4-0.8) excess of ROHs when compared to coronary-artery-disease-free control subjects (p = 1.49 × 10(-9)). The average total length of ROHs was approximately 1,046.92 (95% CI: 634.4-1,459.5) kb greater in individuals with coronary artery disease than control subjects (p = 6.61 × 10(-7)). None of the identified individual ROHs was associated with coronary artery disease after correction for multiple testing. However, in aggregate burden analysis, ROHs favoring increased risk of coronary artery disease were much more common than those showing the opposite direction of association with coronary artery disease (p = 2.69 × 10(-33)). Individual ROHs showed significant associations with monocyte and macrophage expression of genes in their close proximity-subjects with several individual ROHs showed significant differences in the expression of 44 mRNAs in monocytes and 17 mRNAs in macrophages when compared to subjects without those ROHs. This study provides evidence for an excess of homozygosity in coronary artery disease in outbred populations and suggest the potential biological relevance of ROHs in cells of importance to the pathogenesis of atherosclerosis.
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Affiliation(s)
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE3 9QP, UK; NIHR Biomedical Research Unit in Cardiovascular Disease, Leicester LE3 9QP, UK
| | - Majid Nikpay
- Ruddy Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, ON K1Y 4W7, Canada; Atherogenomics Laboratory, University of Ottawa Heart Institute, Ottawa, ON K1Y 3V5, Canada
| | - Liming Qu
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Mingyao Li
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Christina Loley
- Institute of Medical Biometry and Statistics, University of Lübeck, Lübeck 23562, Germany
| | - Radoslaw Debiec
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE3 9QP, UK
| | - Peter S Braund
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE3 9QP, UK
| | - Matthew Denniff
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE3 9QP, UK
| | - Fadi J Charchar
- Faculty of Science and Technology, School of Applied and Biomedical Sciences, Federation University Australia, Ballarat, VIC 3350, Australia
| | - Ares Rocanin Arjo
- ICAN Institute for Cardiometabolism and Nutrition, Paris 75013, France; INSERM, UMR_S 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris 75013, France; Sorbonne Universités, UPMC University, Paris 06, UMR_S 1166, Paris 75013, France
| | - David-Alexandre Trégouët
- ICAN Institute for Cardiometabolism and Nutrition, Paris 75013, France; INSERM, UMR_S 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris 75013, France; Sorbonne Universités, UPMC University, Paris 06, UMR_S 1166, Paris 75013, France
| | - Alison H Goodall
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE3 9QP, UK; NIHR Biomedical Research Unit in Cardiovascular Disease, Leicester LE3 9QP, UK
| | - Francois Cambien
- ICAN Institute for Cardiometabolism and Nutrition, Paris 75013, France; INSERM, UMR_S 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris 75013, France; Sorbonne Universités, UPMC University, Paris 06, UMR_S 1166, Paris 75013, France
| | - Willem H Ouwehand
- Department of Haematology, Cambridge Biomedical Campus, University of Cambridge and NHS Blood and Transplant, Cambridge CB2 0PT, UK; Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK
| | - Robert Roberts
- Ruddy Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, ON K1Y 4W7, Canada; Atherogenomics Laboratory, University of Ottawa Heart Institute, Ottawa, ON K1Y 3V5, Canada
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Technische Universität München, Munich 80636, Germany; Deutsches Zentrum für Herz- und Kreislauf-Forschung (DZHK), Munich 80636, Germany
| | - Christian Hengstenberg
- Deutsches Herzzentrum München, Technische Universität München, Munich 80636, Germany; Deutsches Zentrum für Herz- und Kreislauf-Forschung (DZHK), Munich 80636, Germany
| | - Muredach P Reilly
- Cardiovascular Institute, University of Pennsylvania, Philadelphia, PA 19148, USA
| | - Jeanette Erdmann
- Institute for Integrative and Experimental Genomics, University of Lübeck, Lübeck 23562, Germany
| | - Ruth McPherson
- Ruddy Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, ON K1Y 4W7, Canada; Atherogenomics Laboratory, University of Ottawa Heart Institute, Ottawa, ON K1Y 3V5, Canada
| | - Inke R König
- Institute of Medical Biometry and Statistics, University of Lübeck, Lübeck 23562, Germany
| | - John R Thompson
- Department of Health Sciences, University of Leicester, Leicester LE1 7RH, UK
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE3 9QP, UK; NIHR Biomedical Research Unit in Cardiovascular Disease, Leicester LE3 9QP, UK
| | - Maciej Tomaszewski
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE3 9QP, UK; NIHR Biomedical Research Unit in Cardiovascular Disease, Leicester LE3 9QP, UK.
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661
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Multicohort analysis of the maternal age effect on recombination. Nat Commun 2015; 6:7846. [PMID: 26242864 PMCID: PMC4580993 DOI: 10.1038/ncomms8846] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Accepted: 06/18/2015] [Indexed: 11/09/2022] Open
Abstract
Several studies have reported that the number of crossovers increases with maternal age in humans, but others have found the opposite. Resolving the true effect has implications for understanding the maternal age effect on aneuploidies. Here, we revisit this question in the largest sample to date using single nucleotide polymorphism (SNP)-chip data, comprising over 6,000 meioses from nine cohorts. We develop and fit a hierarchical model to allow for differences between cohorts and between mothers. We estimate that over 10 years, the expected number of maternal crossovers increases by 2.1% (95% credible interval (0.98%, 3.3%)). Our results are not consistent with the larger positive and negative effects previously reported in smaller cohorts. We see heterogeneity between cohorts that is likely due to chance effects in smaller samples, or possibly to confounders, emphasizing that care should be taken when interpreting results from any specific cohort about the effect of maternal age on recombination.
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662
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Taylor HR. The use and abuse of genetic marker-based estimates of relatedness and inbreeding. Ecol Evol 2015; 5:3140-50. [PMID: 26357542 PMCID: PMC4559056 DOI: 10.1002/ece3.1541] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2015] [Revised: 05/05/2015] [Accepted: 05/18/2015] [Indexed: 01/10/2023] Open
Abstract
Genetic marker-based estimators remain a popular tool for measuring relatedness (r xy ) and inbreeding (F) coefficients at both the population and individual level. The performance of these estimators fluctuates with the number and variability of markers available, and the relatedness composition and demographic history of a population. Several methods are available to evaluate the reliability of the estimates of r xy and F, some of which are implemented in the program COANCESTRY. I used the simulation module in COANCESTRY since assess the performance of marker-based estimators of r xy and F in a species with very low genetic diversity, New Zealand's little spotted kiwi (Apteryx owenii). I also conducted a review of published papers that have used COANCESTRY as its release to assess whether and how the reliability of the estimates of r xy and F produced by genetic markers are being measured and reported in published studies. My simulation results show that even when the correlation between true (simulated) and estimated r xy or F is relatively high (Pearson's r = 0.66-0.72 and 0.81-0.85, respectively) the imprecision of the estimates renders them highly unreliable on an individual basis. The literature review demonstrates that the majority of studies do not report the reliability of marker-based estimates of r xy and F. There is currently no standard practice for selecting the best estimator for a given data set or reporting an estimator's performance. This could lead to experimental results being interpreted out of context and render the robustness of conclusions based on measures of r xy and F debatable.
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Affiliation(s)
- Helen R Taylor
- Allan Wilson Centre, School of Biological Sciences, Victoria University of WellingtonKelburn Parade, Wellington, New Zealand
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663
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Karimi K, Esmailizadeh Koshkoiyeh A, Asadi Fozi M, Porto-Neto LR, Gondro C. Prioritization for conservation of Iranian native cattle breeds based on genome-wide SNP data. CONSERV GENET 2015. [DOI: 10.1007/s10592-015-0762-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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664
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Joshi PK, Esko T, Mattsson H, Eklund N, Gandin I, Nutile T, Jackson AU, Schurmann C, Smith AV, Zhang W, Okada Y, Stančáková A, Faul JD, Zhao W, Bartz TM, Concas MP, Franceschini N, Enroth S, Vitart V, Trompet S, Guo X, Chasman DI, O'Connel JR, Corre T, Nongmaithem SS, Chen Y, Mangino M, Ruggiero D, Traglia M, Farmaki AE, Kacprowski T, Bjonnes A, van der Spek A, Wu Y, Giri AK, Yanek LR, Wang L, Hofer E, Rietveld CA, McLeod O, Cornelis MC, Pattaro C, Verweij N, Baumbach C, Abdellaoui A, Warren HR, Vuckovic D, Mei H, Bouchard C, Perry JRB, Cappellani S, Mirza SS, Benton MC, Broeckel U, Medland SE, Lind PA, Malerba G, Drong A, Yengo L, Bielak LF, Zhi D, van der Most PJ, Shriner D, Mägi R, Hemani G, Karaderi T, Wang Z, Liu T, Demuth I, Zhao JH, Meng W, Lataniotis L, van der Laan SW, Bradfield JP, Wood AR, Bonnefond A, Ahluwalia TS, Hall LM, Salvi E, Yazar S, Carstensen L, de Haan HG, Abney M, Afzal U, Allison MA, Amin N, Asselbergs FW, Bakker SJL, Barr RG, Baumeister SE, Benjamin DJ, Bergmann S, Boerwinkle E, Bottinger EP, Campbell A, Chakravarti A, Chan Y, Chanock SJ, Chen C, Chen YDI, et alJoshi PK, Esko T, Mattsson H, Eklund N, Gandin I, Nutile T, Jackson AU, Schurmann C, Smith AV, Zhang W, Okada Y, Stančáková A, Faul JD, Zhao W, Bartz TM, Concas MP, Franceschini N, Enroth S, Vitart V, Trompet S, Guo X, Chasman DI, O'Connel JR, Corre T, Nongmaithem SS, Chen Y, Mangino M, Ruggiero D, Traglia M, Farmaki AE, Kacprowski T, Bjonnes A, van der Spek A, Wu Y, Giri AK, Yanek LR, Wang L, Hofer E, Rietveld CA, McLeod O, Cornelis MC, Pattaro C, Verweij N, Baumbach C, Abdellaoui A, Warren HR, Vuckovic D, Mei H, Bouchard C, Perry JRB, Cappellani S, Mirza SS, Benton MC, Broeckel U, Medland SE, Lind PA, Malerba G, Drong A, Yengo L, Bielak LF, Zhi D, van der Most PJ, Shriner D, Mägi R, Hemani G, Karaderi T, Wang Z, Liu T, Demuth I, Zhao JH, Meng W, Lataniotis L, van der Laan SW, Bradfield JP, Wood AR, Bonnefond A, Ahluwalia TS, Hall LM, Salvi E, Yazar S, Carstensen L, de Haan HG, Abney M, Afzal U, Allison MA, Amin N, Asselbergs FW, Bakker SJL, Barr RG, Baumeister SE, Benjamin DJ, Bergmann S, Boerwinkle E, Bottinger EP, Campbell A, Chakravarti A, Chan Y, Chanock SJ, Chen C, Chen YDI, Collins FS, Connell J, Correa A, Cupples LA, Smith GD, Davies G, Dörr M, Ehret G, Ellis SB, Feenstra B, Feitosa MF, Ford I, Fox CS, Frayling TM, Friedrich N, Geller F, Scotland G, Gillham-Nasenya I, Gottesman O, Graff M, Grodstein F, Gu C, Haley C, Hammond CJ, Harris SE, Harris TB, Hastie ND, Heard-Costa NL, Heikkilä K, Hocking LJ, Homuth G, Hottenga JJ, Huang J, Huffman JE, Hysi PG, Ikram MA, Ingelsson E, Joensuu A, Johansson Å, Jousilahti P, Jukema JW, Kähönen M, Kamatani Y, Kanoni S, Kerr SM, Khan NM, Koellinger P, Koistinen HA, Kooner MK, Kubo M, Kuusisto J, Lahti J, Launer LJ, Lea RA, Lehne B, Lehtimäki T, Liewald DCM, Lind L, Loh M, Lokki ML, London SJ, Loomis SJ, Loukola A, Lu Y, Lumley T, Lundqvist A, Männistö S, Marques-Vidal P, Masciullo C, Matchan A, Mathias RA, Matsuda K, Meigs JB, Meisinger C, Meitinger T, Menni C, Mentch FD, Mihailov E, Milani L, Montasser ME, Montgomery GW, Morrison A, Myers RH, Nadukuru R, Navarro P, Nelis M, Nieminen MS, Nolte IM, O'Connor GT, Ogunniyi A, Padmanabhan S, Palmas WR, Pankow JS, Patarcic I, Pavani F, Peyser PA, Pietilainen K, Poulter N, Prokopenko I, Ralhan S, Redmond P, Rich SS, Rissanen H, Robino A, Rose LM, Rose R, Sala C, Salako B, Salomaa V, Sarin AP, Saxena R, Schmidt H, Scott LJ, Scott WR, Sennblad B, Seshadri S, Sever P, Shrestha S, Smith BH, Smith JA, Soranzo N, Sotoodehnia N, Southam L, Stanton AV, Stathopoulou MG, Strauch K, Strawbridge RJ, Suderman MJ, Tandon N, Tang ST, Taylor KD, Tayo BO, Töglhofer AM, Tomaszewski M, Tšernikova N, Tuomilehto J, Uitterlinden AG, Vaidya D, van Hylckama Vlieg A, van Setten J, Vasankari T, Vedantam S, Vlachopoulou E, Vozzi D, Vuoksimaa E, Waldenberger M, Ware EB, Wentworth-Shields W, Whitfield JB, Wild S, Willemsen G, Yajnik CS, Yao J, Zaza G, Zhu X, Project TBJ, Salem RM, Melbye M, Bisgaard H, Samani NJ, Cusi D, Mackey DA, Cooper RS, Froguel P, Pasterkamp G, Grant SFA, Hakonarson H, Ferrucci L, Scott RA, Morris AD, Palmer CNA, Dedoussis G, Deloukas P, Bertram L, Lindenberger U, Berndt SI, Lindgren CM, Timpson NJ, Tönjes A, Munroe PB, Sørensen TIA, Rotimi CN, Arnett DK, Oldehinkel AJ, Kardia SLR, Balkau B, Gambaro G, Morris AP, Eriksson JG, Wright MJ, Martin NG, Hunt SC, Starr JM, Deary IJ, Griffiths LR, Tiemeier H, Pirastu N, Kaprio J, Wareham NJ, Pérusse L, Wilson JG, Girotto G, Caulfield MJ, Raitakari O, Boomsma DI, Gieger C, van der Harst P, Hicks AA, Kraft P, Sinisalo J, Knekt P, Johannesson M, Magnusson PKE, Hamsten A, Schmidt R, Borecki IB, Vartiainen E, Becker DM, Bharadwaj D, Mohlke KL, Boehnke M, van Duijn CM, Sanghera DK, Teumer A, Zeggini E, Metspalu A, Gasparini P, Ulivi S, Ober C, Toniolo D, Rudan I, Porteous DJ, Ciullo M, Spector TD, Hayward C, Dupuis J, Loos RJF, Wright AF, Chandak GR, Vollenweider P, Shuldiner A, Ridker PM, Rotter JI, Sattar N, Gyllensten U, North KE, Pirastu M, Psaty BM, Weir DR, Laakso M, Gudnason V, Takahashi A, Chambers JC, Kooner JS, Strachan DP, Campbell H, Hirschhorn JN, Perola M, Polašek O, Wilson JF. Directional dominance on stature and cognition in diverse human populations. Nature 2015; 523:459-462. [PMID: 26131930 PMCID: PMC4516141 DOI: 10.1038/nature14618] [Show More Authors] [Citation(s) in RCA: 123] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2015] [Accepted: 05/28/2015] [Indexed: 01/13/2023]
Abstract
Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
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Affiliation(s)
- Peter K Joshi
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Tonu Esko
- Estonian Genome Center, University of Tartu, Riia 23b, 51010, Tartu, Estonia
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Cambridge, 02141, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge Center 7, Cambridge, 02242, MA, USA
- Department of Genetics, Harvard Medical School, 25 Shattuck St, Boston, 02115, MA, USA
| | - Hannele Mattsson
- Unit of Public Health Genomics, National Institute for Health and Welfare, P.O. Box 104, Helsinki, FI-00251, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, P.O. Box 20, Helsinki, FI-00014, Finland
| | - Niina Eklund
- Unit of Public Health Genomics, National Institute for Health and Welfare, P.O. Box 104, Helsinki, FI-00251, Finland
| | - Ilaria Gandin
- Department of Medical Sciences, University of Trieste, Strada di Fiume 447 - Osp. di Cattinara, Trieste, 34149, Italy
| | - Teresa Nutile
- Institute of Genetics and Biophysics "A. Buzzati-Traverso" CNR, via Pietro Castellino, 111, Naples, 80131, Italy
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, 48109, MI, USA
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, 10029, USA
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, 10029, USA
| | - Albert V Smith
- Icelandic Heart Association, Holtasmari 1, 201, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital NHS Trust, Uxbridge Road, Southall, Middlesex, UB1 3HW, UK
| | - Yukinori Okada
- Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyoku, Tokyo, 113-8510, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Alena Stančáková
- Department of Medicine, University of Eastern Finland, 70210 Kuopio, Finland
| | - Jessica D Faul
- Institute for Social Research, University of Michigan, 426 Thompson Street, 48104, Ann Arbor, MI, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, 1415 Washington Heights, 48109, Ann Arbor, MI, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Biostatistics and Medicine, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, 98101, WA, USA
| | - Maria Pina Concas
- Institute of Population Genetics, National Research Council, Trav. La Crucca n. 3 - Reg. Baldinca, Sassari, 07100, Italy
| | - Nora Franceschini
- Epidemiology, University of North Carolina, 137 E. Franklin St., Suite 306, 27599-8050, Chapel Hill, USA
| | - Stefan Enroth
- Immunology, Genetics & Pathology, Uppsala University, Husargatan 3, Box 815, Uppsala, SE-751 08, Sweden
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, Edinburgh, UK
| | - Stella Trompet
- Department of Gerontology and Geriatrics, Leiden University Medical Center , PO Box 9600, Leiden, Netherlands
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences , Los Angeles Biomedical Research Institute, 1124 W. Carson Street, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, 900 Commonwealth Avenue, East, Harvard Medical School, Boston, Boston, MA 02215, USA
| | - Jeffery R O'Connel
- Division of Endocrinology, Diabetes, and Nutrition and Program for Personalised and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, 685 Baltimore St. MSTF, Baltimore, 21201, USA
| | - Tanguy Corre
- Department of Medical Genetics, University of Lausanne, Rue du Bugnon 27, Lausanne, 1005, Switzerland
- Swiss Institute of Bioinformatics, Quartier Sorge - batiment génopode, Lausanne, 1015, Switzerland
| | - Suraj S Nongmaithem
- Genomic Research on Complex Diseases (GRC) Group, CSIR-Centre for Cellular and Molecular Biology, Habshiguda, Uppal Road, Hyderabad, 500007, India
| | - Yuning Chen
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, 02118, MA, USA
| | - Massimo Mangino
- Department of Twin Research & Genetic Epidemiology, King's College London, South Wing, Block D, 3rd Floor, Westminster Bridge Road, London, SE1 7EH, UK
- NIHR Biomedical Research Centre , Guy's and St. Thomas' Foundation Trust, Westminster Bridge Road, London, SE1 7EH, UK
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics "A. Buzzati-Traverso" CNR, via Pietro Castellino, 111, Naples, 80131, Italy
| | - Michela Traglia
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Via Olgettina 58, Milano, 20132, Italy
| | - Aliki-Eleni Farmaki
- Department of Nutrition and Dietetics, Harokopio University of Athens, 70, El. Venizelou Ave, Athens, 17671, Greece
| | - Tim Kacprowski
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Friedrich-Ludwig-Jahn-Str. 15A, Greifswald, 17475, Germany
| | - Andrew Bjonnes
- Center for Human Genetic Research , 55 Fruit Street, Massachusetts General Hospital, 2114, USA
| | - Ashley van der Spek
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, Rotterdam, 3000 CA, The Netherlands
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, 27599, NC, USA
| | - Anil K Giri
- Genomics and Molecular Medicine, CSIR-Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India
| | - Lisa R Yanek
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, 21287, Maryland, USA
| | - Lihua Wang
- Department of Genetics, Washington University School of Medicine, 4444 Forest Park Boulevard, Saint Louis, 63108, MO, USA
| | - Edith Hofer
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Auenbruggerplatz 22, Graz, A-8036, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz2, Graz, A-8036, Austria
| | - Cornelius A Rietveld
- Erasmus School of Economics, Erasmus University Rotterdam, Burgemeester Oudlaan 50, Rotterdam, 3000 DR, The Netherlands
| | - Olga McLeod
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, CMM L8:03, Karolinska University Hospital, Solna, Stockholm, 171 76, Sweden
| | - Marilyn C Cornelis
- Channing Division of Network Medicine, Brigham & Women's Hospital, 181 Longwood, Boston, 02115, USA
- Nutrition, Harvard School of Public Health, 401 Park Drive, Boston, 02215, USA
| | - Cristian Pattaro
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy - Affiliated Institute of the University of Lübeck, Lübeck, Germany
| | - Niek Verweij
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Hanzeplein 1, Groningen, 9700RB, The Netherlands
| | - Clemens Baumbach
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
| | - Abdel Abdellaoui
- Department of Biological Psychology, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, Netherlands
| | - Helen R Warren
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Dragana Vuckovic
- Department of Medical Sciences, University of Trieste, Strada di Fiume 447 - Osp. di Cattinara, Trieste, 34149, Italy
| | - Hao Mei
- Department of Medicine, University of Mississippi Medical Center, 2500 N. State St., Jackson, 39216, MS, USA
| | - Claude Bouchard
- Pennington Biomedical Research Center, 6400 Perkins Rd, Baton Rouge, LA 70808, USA
| | - John R B Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Stefania Cappellani
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", via dell'Istria 65, Trieste, 34137, Italy
| | - Saira S Mirza
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, Rotterdam, 3000 CA, The Netherlands
| | - Miles C Benton
- Institute of Health and Biomedical Innovation, Queensland University of Technology, 60 Musk Avenue, Kelvin Grove, GPO Box 2434, Brisbane Qld 4001, Brisbane, Australia
| | - Ulrich Broeckel
- Department of Pediatrics, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, 53226, WI, USA
| | - Sarah E Medland
- Quantitative Genetics, QIMR Berghofer Medical Research Institute, 300 Herston Rd, Herston, Brisbane, 4006, Australia
| | - Penelope A Lind
- Quantitative Genetics, QIMR Berghofer Medical Research Institute, 300 Herston Rd, Herston, Brisbane, 4006, Australia
| | - Giovanni Malerba
- Dipartimento di Scienze della Vita e della Riproduzione, University of Verona, Strada Le Grazie 15, Verona, 37134, Italy
| | - Alexander Drong
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Loic Yengo
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Lille 2 University, 1 Rue du Professeur Calmette, 59000, Lille, France
| | - Lawrence F Bielak
- Department of Epidemiology, University of Michigan, 1415 Washington Heights, 48109, Ann Arbor, MI, USA
| | - Degui Zhi
- Department of Biostatistics, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, 35294, AL, USA
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, P.O. box 30.001, 9700 RB, Groningen, The Netherlands
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Building 12A/Room 4047, 12 South Dr., Bethesda, 20892, Maryland, USA
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Riia 23b, 51010, Tartu, Estonia
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Tugce Karaderi
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Zhaoming Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, 20850, MD, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, SAIC-Frederick, Inc., Frederick National Laboratory for Cancer Research, Frederick,MD, USA
| | - Tian Liu
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, Berlin, 14195, Germany
- Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 72, Berlin, 14195, Germany
| | - Ilja Demuth
- Charité Research Group on Geriatrics, Charité - Universitätsmedizin Berlin, Reinickendorferstr. 61, 13347, Berlin, Germany
- Institute of Medical and Human Genetics, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany
| | - Jing Hua Zhao
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Weihua Meng
- Division of Population Health Sciences, Medical Research Institute, University of Dundee, Ninewells hospital and School of Medicine, Dundee, DD2 4BF, Scotland
| | - Lazaros Lataniotis
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Sander W van der Laan
- Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Jonathan P Bradfield
- Center for Applied Genomics, Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA 19104, USA
| | - Andrew R Wood
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
| | - Amelie Bonnefond
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Lille 2 University, 1 Rue du Professeur Calmette, 59000, Lille, France
| | - Tarunveer S Ahluwalia
- Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Danish Pediatric Asthma Center, Gentofte Hospital, The Capital Region, Copenhagen, Denmark
- Novo Nordisk Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, Copenhagen, 2100, Denmark
| | - Leanne M Hall
- Department of Cardiovascular Sciences, University of Leicester, BHF Cardiovascular Research Centre, Glenfield Hospital, Groby Road, Leicester, LE3 9QP, UK
| | - Erika Salvi
- Department of Health Sciences, University of Milan, via A. di Rudinì 8, 20142 Milan, Italy
| | - Seyhan Yazar
- Centre for Ophthalmology and Visual Science, University of Western Australia, Lions Eye Institute, 2 Verdun St, Perth, 6009, Australia
| | - Lisbeth Carstensen
- Department of Epidemiology Research, Statens Serum Institut, Artillerivej 5, Copenhagen, 2300, Denmark
| | - Hugoline G de Haan
- Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, Leiden, 2300RC, The Netherlands
| | - Mark Abney
- Department of Human Genetics, University of Chicago, 920 E. 58th Street, Chicago, IL, USA
| | - Uzma Afzal
- Department of Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital NHS Trust, Uxbridge Road, Southall, Middlesex, UB1 3HW, UK
| | - Matthew A Allison
- Department of Family and Preventive Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, 92093, USA
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, Rotterdam, 3000 CA, The Netherlands
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
- Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Catharijnesingel 52, Utrecht, 3501 DG, The Netherlands
- Institute of Cardiovascular Science, faculty of Population Health Sciences, University College London, Gower Street, London, WC1E 6BT, UK
| | - Stephan J L Bakker
- University of Groningen, University Medical Center Groningen, Department of Internal Medicine, Hanzeplein 1, Groningen, 9700RB, The Netherlands
| | - R Graham Barr
- Department of Medicine, Columbia University, 622 W. 168th Street, New York, 10032, NY, USA
| | - Sebastian E Baumeister
- Institute for Community Medicine, University Medicine Greifswald, W.-Rathenau-Str. 48, Greifswald, 17475, Germany
| | - Daniel J Benjamin
- Department of Economics, Cornell University, 480 Uris Hall, Ithaca, NY, 14853, USA
- Department of Economics and Center for Economic and Social Research, University of Southern California, 314C Dauterive Hall, 635 Downey Way, Los Angeles, CA, 90089, USA
| | - Sven Bergmann
- Department of Medical Genetics, University of Lausanne, Rue du Bugnon 27, Lausanne, 1005, Switzerland
- Swiss Institute of Bioinformatics, Quartier Sorge - batiment génopode, Lausanne, 1015, Switzerland
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, 1200 Pressler St., Suite 453E, Houston, Texas, 77030, USA
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, 10029, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Aravinda Chakravarti
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, 21205, MD, USA
| | - Yingleong Chan
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Cambridge, 02141, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge Center 7, Cambridge, 02242, MA, USA
- Department of Genetics, Harvard Medical School, 25 Shattuck St, Boston, 02115, MA, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, 20850, MD, USA
| | - Constance Chen
- Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, 665 Huntington Ave, Boston, 02115, USA
| | - Y-D Ida Chen
- Institute for Translational Genomics and Population Sciences , Los Angeles Biomedical Research Institute, 1124 W. Carson Street, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Francis S Collins
- Genome Technology Branch, National Human Genome Research Institute, NIH, Bethesda, 20892, MD, USA
| | - John Connell
- College of Medicine, Dentistry and Nursing, Ninewells Hospital and Medical School, College Office, Level 10, Dundee, DD1 9SY, UK
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, 2500 N. State St., Jackson, 39216, MS, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, 02118, MA, USA
- National Heart, Lung, and Blood Institute's Framingham Heart Study, 73 Mt. Wayte Ave, Framingham, 01702, MA, USA
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Gail Davies
- Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Marcus Dörr
- Department of Internal Medicine B, University Medicine Greifswald, Ferdinand-Sauerbruch-Str. NK, Greifswald, 17475, Germany
| | - Georg Ehret
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, 21205, MD, USA
- Cardiology, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil, 4, Genève 14, 1211, Switzerland
| | - Stephen B Ellis
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, 10029, USA
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Artillerivej 5, Copenhagen, 2300, Denmark
| | - Mary F Feitosa
- Department of Genetics, Washington University School of Medicine, 4444 Forest Park Boulevard, Saint Louis, 63108, MO, USA
| | - Ian Ford
- Robertson Centre, University of Glasgow, Boyd Orr Building, Glasgow, G12 8QQ, Scotland
| | - Caroline S Fox
- National Heart, Lung, and Blood Institute's Framingham Heart Study, 73 Mt. Wayte Ave, Framingham, 01702, MA, USA
- Division of Endocrinology, Brigham and Women's Hospital and Harvard Medical School , 75 Francis St, Boston, 02115, MA, USA
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
| | - Nele Friedrich
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Str. NK, 17475, Greifswald, Germany
| | - Frank Geller
- Department of Epidemiology Research, Statens Serum Institut, Artillerivej 5, Copenhagen, 2300, Denmark
| | - Generation Scotland
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Irina Gillham-Nasenya
- Department of Twin Research & Genetic Epidemiology, King's College London, South Wing, Block D, 3rd Floor, Westminster Bridge Road, London, SE1 7EH, UK
| | - Omri Gottesman
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, 10029, USA
| | - Misa Graff
- Epidemiology, University of North Carolina, 137 E Franklin St., Suite 306, USA
| | - Francine Grodstein
- Nutrition, Harvard School of Public Health, 401 Park Drive, Boston, 02215, USA
| | - Charles Gu
- Division of Biostatistics, Washington University, 660 S Euclid, St Louis, 63110, MO, USA
| | - Chris Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, Edinburgh, UK
- Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, Scotland
| | - Christopher J Hammond
- Department of Twin Research & Genetic Epidemiology, King's College London, South Wing, Block D, 3rd Floor, Westminster Bridge Road, London, SE1 7EH, UK
| | - Sarah E Harris
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Tamara B Harris
- National Institutes on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Nicholas D Hastie
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, Edinburgh, UK
| | - Nancy L Heard-Costa
- National Heart, Lung, and Blood Institute's Framingham Heart Study, 73 Mt. Wayte Ave, Framingham, 01702, MA, USA
- Department of Neurology, Boston University School of Medicine, 72 E Concord St, Boston, 02118, MA, USA
| | - Kauko Heikkilä
- Department of Public Health, University of Helsinki, Hjelt Institute, P.O.Box 41, Mannerheimintie 172, Helsinki, FI-00014, Finland
| | - Lynne J Hocking
- Musculoskeletal Research Programme, Division of Applied Medicine, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, UK
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Friedrich-Ludwig-Jahn-Str. 15A, Greifswald, 17475, Germany
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, Netherlands
| | - Jinyan Huang
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Rui Jin Hospital Affiliated with Shanghai Jiao Tong University School of Medicine, 197 Rui Jin Er Road, Shanghai, 200025 China
| | - Jennifer E Huffman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, Edinburgh, UK
| | - Pirro G Hysi
- Department of Twin Research & Genetic Epidemiology, King's College London, South Wing, Block D, 3rd Floor, Westminster Bridge Road, London, SE1 7EH, UK
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, Rotterdam, 3000 CA, The Netherlands
- Department of Radiology, Erasmus Medical Center, PO Box 2040, Rotterdam, 3000 CA, The Netherlands
| | - Erik Ingelsson
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Anni Joensuu
- Unit of Public Health Genomics, National Institute for Health and Welfare, P.O. Box 104, Helsinki, FI-00251, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, P.O. Box 20, Helsinki, FI-00014, Finland
| | - Åsa Johansson
- Immunology, Genetics & Pathology, Uppsala University, Husargatan 3, Box 815, Uppsala, SE-751 08, Sweden
- Uppsala Clinical Research Center, Uppsala University, Uppsala, SE-75237, Sweden
| | - Pekka Jousilahti
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, P.O. Box 30, Helsinki, FI-00271, Finland
| | - J Wouter Jukema
- Department of Cardiology C5-P , Leiden University Medical Center, PO Box 9600, Leiden, Netherlands
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere and Tampere University Hospital, P.O. Box 2000, Tampere, 33521, Finland
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Shona M Kerr
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, Edinburgh, UK
| | - Nazir M Khan
- Genomics and Molecular Medicine, CSIR-Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India
| | - Philipp Koellinger
- Erasmus School of Economics, Erasmus University Rotterdam, Burgemeester Oudlaan 50, Rotterdam, 3000 DR, The Netherlands
| | - Heikki A Koistinen
- Diabetes Prevention Unit, National Institute for Health and Welfare, P.O. Box 30, FI-00271 Helsinki, Finland
- Department of Medicine, Division of Endocrinology, Helsinki University Central Hospital, P.O.Box 340, Haartmaninkatu 4, Helsinki, FI-00029, Finland
- Minerva Foundation Institute for Medical Research, Biomedicum 2U, Tukholmankatu 8, Helsinki, FI-00290, Finland
| | - Manraj K Kooner
- Department of Cardiology, Ealing Hospital NHS Trust, Uxbridge Road, Southall, Middlesex, UB1 3HW, UK
| | - Michiaki Kubo
- Laboratory for Genotyping Development RCfIMS, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, 70210, Finland
| | - Jari Lahti
- Institute of Behavioural Sciences, University of Helsinki, P.O. Box 9, FI-00014 University of Helsinki, Helsinki, Finland
- Folkhälsan Reasearch Centre, PB 63, Helsinki, FI-00014 University of Helsinki, Finland
| | - Lenore J Launer
- National Institutes on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Rodney A Lea
- Institute of Health and Biomedical Innovation, Queensland University of Technology, 60 Musk Avenue, Kelvin Grove, GPO Box 2434, Brisbane Qld 4001, Brisbane, Australia
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London, W2 1PG, UK
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine University of Tampere, Tampere, 33520, Finland
| | - David C M Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Lars Lind
- Department of Medical Sciences, University Hospital, Uppsala, 75185, Sweden
| | - Marie Loh
- Department of Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London, W2 1PG, UK
| | - Marja-Liisa Lokki
- Transplantation laboratory, Haartman Institute, University of Helsinki, P.O. Box 21, Helsinki, FI-00014, Finland
| | - Stephanie J London
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, RTP, NC, USA
| | - Stephanie J Loomis
- Ophthalmology, Massachusetts Eye and Ear, 243 Charles St, Boston, 02114, USA
| | - Anu Loukola
- Department of Public Health, University of Helsinki, Hjelt Institute, P.O.Box 41, Mannerheimintie 172, Helsinki, FI-00014, Finland
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, 10029, USA
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, 10029, USA
| | - Thomas Lumley
- Department of Statistics, University of Auckland, 303.325 Science Centre, Private Bag 92019, Auckland, 1142, New Zealand
| | - Annamari Lundqvist
- Department of Health, Functional Capacity and Welfare, National Institute for Health and Welfare, P.O. Box 30, Helsinki, FI-00271, Finland
| | - Satu Männistö
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, P.O. Box 30, Helsinki, FI-00271, Finland
| | - Pedro Marques-Vidal
- Department of Internal Medicine, University Hospital, Route du Bugnon 44, Lausanne, 1011, Switzerland
| | - Corrado Masciullo
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Via Olgettina 58, Milano, 20132, Italy
| | - Angela Matchan
- Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1HH, UK
| | - Rasika A Mathias
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, 21287, Maryland, USA
- Division of Allergy and Clinical Immunology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, 21224, USA
| | - Koichi Matsuda
- Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan
| | - James B Meigs
- Division of General Internal Medicine, Massachusetts General Hospital , 50 Staniford St, Boston, 02114, MA, USA
| | - Christa Meisinger
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764 Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, München, 81675, Germany
| | - Cristina Menni
- Department of Twin Research & Genetic Epidemiology, King's College London, South Wing, Block D, 3rd Floor, Westminster Bridge Road, London, SE1 7EH, UK
| | - Frank D Mentch
- Center for Applied Genomics, Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA 19104, USA
| | - Evelin Mihailov
- Estonian Genome Center, University of Tartu, Riia 23b, 51010, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Riia 23b, 51010, Tartu, Estonia
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition and Program for Personalised and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, 685 Baltimore St. MSTF, Baltimore, 21201, USA
| | - Grant W Montgomery
- Molecular Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Rd, Herston, Brisbane, 4006, Australia
| | - Alanna Morrison
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, 1200 Pressler St., Suite 453E, Houston, Texas, 77030, USA
| | - Richard H Myers
- Genome Science Institute, Boston University School of Medicine, 72 East Concord Street, E-304, Boston, 2118, MA, USA
| | - Rajiv Nadukuru
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, 10029, USA
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, Edinburgh, UK
| | - Mari Nelis
- Estonian Genome Center, University of Tartu, Riia 23b, 51010, Tartu, Estonia
| | - Markku S Nieminen
- HUCH Heart and Lung center, Helsinki University Central Hospital, P.O. Box 340, Helsinki, FI-00029, Finland
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, P.O. box 30.001, 9700 RB, Groningen, The Netherlands
| | - George T O'Connor
- National Heart, Lung, and Blood Institute's Framingham Heart Study, 73 Mt. Wayte Ave, Framingham, 01702, MA, USA
- Pulmonary Center and Department of Medicine, Boston University School of Medicine, 72 E Concord St, Boston, 02118, MA, USA
| | | | | | - Walter R Palmas
- Department of Medicine, Columbia University, 622 W. 168th Street, New York, 10032, NY, USA
| | - James S Pankow
- Division of Epidemiology and Community Health , University of Minnesota , 1300 S 2nd Street, Minneapolis, 55454, USA
| | - Inga Patarcic
- Centre for Global Health and Department of Public Health, School of Medicine, University of Split, Soltanska 2, 21000 Split, Croatia
| | - Francesca Pavani
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy - Affiliated Institute of the University of Lübeck, Lübeck, Germany
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan, 1415 Washington Heights, 48109, Ann Arbor, MI, USA
| | - Kirsi Pietilainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, P.O. Box 20, Helsinki, FI-00014, Finland
- Department of Medicine, Division of Endocrinology, Helsinki University Central Hospital, P.O.Box 340, Haartmaninkatu 4, Helsinki, FI-00029, Finland
- Obesity Research Unit, Research Programs Unit, Diabetes and Obesity, University of Helsinki, P.O.Box 63, Haartmaninkatu 8, FI-00014, Helsinki, Finland
| | - Neil Poulter
- International Centre for Circulatory Health, Imperial College London, London, W2 1LA, UK
| | - Inga Prokopenko
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, SW7 2AZ, UK
| | - Sarju Ralhan
- Department of Cardiology and Cardio thoracic Surgery Hero DMC Heart Institute, Civil Lines, 141001, Ludhiana, India
| | - Paul Redmond
- Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Stephen S Rich
- Department Public Health Sciences, University of Virginia School of Medicine, 3232 West Complex, Charlottesville, 22908, USA
| | - Harri Rissanen
- Department of Health, Functional Capacity and Welfare, National Institute for Health and Welfare, P.O. Box 30, Helsinki, FI-00271, Finland
| | - Antonietta Robino
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", via dell'Istria 65, Trieste, 34137, Italy
| | - Lynda M Rose
- Division of Preventive Medicine, Brigham and Women's Hospital, 900 Commonwealth Avenue, East, Harvard Medical School, Boston, Boston, MA 02215, USA
| | - Richard Rose
- Department of Psychological & Brain Sciences, Indiana University Bloomington, 1101 E. 10th St., Bloomington, IN 47405, USA
| | - Cinzia Sala
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Via Olgettina 58, Milano, 20132, Italy
| | | | - Veikko Salomaa
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, P.O. Box 30, Helsinki, FI-00271, Finland
| | - Antti-Pekka Sarin
- Unit of Public Health Genomics, National Institute for Health and Welfare, P.O. Box 104, Helsinki, FI-00251, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, P.O. Box 20, Helsinki, FI-00014, Finland
| | - Richa Saxena
- Center for Human Genetic Research , 55 Fruit Street, Massachusetts General Hospital, 2114, USA
| | - Helena Schmidt
- Institute of Molecular Biology and Biochemistry, Medical University Graz, Harrachgasse 21, Graz, A-8010, Austria
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, 48109, MI, USA
| | - William R Scott
- Department of Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital NHS Trust, Uxbridge Road, Southall, Middlesex, UB1 3HW, UK
| | - Bengt Sennblad
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, CMM L8:03, Karolinska University Hospital, Solna, Stockholm, 171 76, Sweden
- Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden
| | - Sudha Seshadri
- National Heart, Lung, and Blood Institute's Framingham Heart Study, 73 Mt. Wayte Ave, Framingham, 01702, MA, USA
- Department of Neurology, Boston University School of Medicine, 72 E Concord St, Boston, 02118, MA, USA
| | - Peter Sever
- International Centre for Circulatory Health, Imperial College London, London, W2 1LA, UK
| | - Smeeta Shrestha
- Genomic Research on Complex Diseases (GRC) Group, CSIR-Centre for Cellular and Molecular Biology, Habshiguda, Uppal Road, Hyderabad, 500007, India
| | - Blair H Smith
- University of Dundee, Kirsty Semple Way, Dundee, DD2 4DB, UK
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, 1415 Washington Heights, 48109, Ann Arbor, MI, USA
| | - Nicole Soranzo
- Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1HH, UK
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, 98101, WA, USA
| | - Lorraine Southam
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
- Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1HH, UK
| | - Alice V Stanton
- Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, St. Stephen's Green, Dublin 2, Ireland
| | - Maria G Stathopoulou
- UMR INSERM U1122; IGE-PCV "Interactions Gène-Environnement en Physiopathologie Cardio-Vasculaire", INSERM, University of Lorraine, 30 Rue Lionnois, Nancy, 54000, France
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
| | - Rona J Strawbridge
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, CMM L8:03, Karolinska University Hospital, Solna, Stockholm, 171 76, Sweden
| | - Matthew J Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Nikhil Tandon
- Department of Endocrinology, All India Institute of Medical Sciences, Ansari Nagar East, New Delhi, 110029, India
| | - Sian-Tsun Tang
- National Heart and Lung Institute, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences , Los Angeles Biomedical Research Institute, 1124 W. Carson Street, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Bamidele O Tayo
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, USA
| | - Anna Maria Töglhofer
- Institute of Molecular Biology and Biochemistry, Medical University Graz, Harrachgasse 21, Graz, A-8010, Austria
| | - Maciej Tomaszewski
- Department of Cardiovascular Sciences, University of Leicester, BHF Cardiovascular Research Centre, Glenfield Hospital, Groby Road, Leicester, LE3 9QP, UK
- NIHR Leicester Cardiovascular Biomedical Research Unit, University of Leicester, Glenfield Hospital, Groby Road, Leicester, LE3 9QP, UK
| | - Natalia Tšernikova
- Estonian Genome Center, University of Tartu, Riia 23b, 51010, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Riia 23, Tartu, 51010 Estonia
| | - Jaakko Tuomilehto
- Diabetes Prevention Unit, National Institute for Health and Welfare, P.O. Box 30, FI-00271 Helsinki, Finland
- Centre for Vascular Prevention, Danube-University Krems, 3500 Krems, Austria
- Diabetes Research Group, King Abdulaziz University, 21589 Jeddah, Saudi Arabia
| | - Andre G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, Rotterdam, 3000 CA, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, PO Box 2040, Rotterdam, 3000 CA, The Netherlands
| | - Dhananjay Vaidya
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, 21287, Maryland, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, 21205, USA
| | - Astrid van Hylckama Vlieg
- Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, Leiden, 2300RC, The Netherlands
| | - Jessica van Setten
- Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Tuula Vasankari
- Finnish Lung Health Association, Sibeliuksenkatu 11 A 1, Helsinki, FI-00250, Finland
| | - Sailaja Vedantam
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Cambridge, 02141, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge Center 7, Cambridge, 02242, MA, USA
- Department of Genetics, Harvard Medical School, 25 Shattuck St, Boston, 02115, MA, USA
| | - Efthymia Vlachopoulou
- Transplantation laboratory, Haartman Institute, University of Helsinki, P.O. Box 21, Helsinki, FI-00014, Finland
| | - Diego Vozzi
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", via dell'Istria 65, Trieste, 34137, Italy
| | - Eero Vuoksimaa
- Department of Public Health, University of Helsinki, Hjelt Institute, P.O.Box 41, Mannerheimintie 172, Helsinki, FI-00014, Finland
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
| | - Erin B Ware
- Department of Epidemiology, University of Michigan, 1415 Washington Heights, 48109, Ann Arbor, MI, USA
| | | | - John B Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Rd, Herston, Brisbane, 4006, Australia
| | - Sarah Wild
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Gonneke Willemsen
- Department of Biological Psychology, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, Netherlands
| | | | - Jie Yao
- Institute for Translational Genomics and Population Sciences , Los Angeles Biomedical Research Institute, 1124 W. Carson Street, Torrance, 90502, USA
| | - Gianluigi Zaza
- Renal Unit, Department of Medicine, Piazzale A. Stefani 1, Verona, 37124, Italy
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, USA
| | - The BioBank Japan Project
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Rany M Salem
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Cambridge, 02141, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge Center 7, Cambridge, 02242, MA, USA
- Department of Genetics, Harvard Medical School, 25 Shattuck St, Boston, 02115, MA, USA
| | - Mads Melbye
- Department of Epidemiology Research, Statens Serum Institut, Artillerivej 5, Copenhagen, 2300, Denmark
- Department of Medicine, Stanford University, 300 Pasteur Drive, Stanford, 94305, CA, USA
| | - Hans Bisgaard
- Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, BHF Cardiovascular Research Centre, Glenfield Hospital, Groby Road, Leicester, LE3 9QP, UK
- NIHR Leicester Cardiovascular Biomedical Research Unit, University of Leicester, Glenfield Hospital, Groby Road, Leicester, LE3 9QP, UK
| | - Daniele Cusi
- Department of Health Sciences, University of Milan, via A. di Rudinì 8, 20142 Milan, Italy
| | - David A Mackey
- Centre for Ophthalmology and Visual Science, University of Western Australia, Lions Eye Institute, 2 Verdun St, Perth, 6009, Australia
| | - Richard S Cooper
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, USA
| | - Philippe Froguel
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Lille 2 University, 1 Rue du Professeur Calmette, 59000, Lille, France
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, SW7 2AZ, UK
| | - Gerard Pasterkamp
- Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Struan F A Grant
- Center for Applied Genomics, Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, The University of Pennsylvania, 3615 Civic Center Boulevard, Philadelphia, PA 19104, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, The University of Pennsylvania, 3615 Civic Center Boulevard, Philadelphia, PA 19104, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National institute on Aging, Baltimore, 21225, Maryland, USA
| | - Robert A Scott
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Andrew D Morris
- Jacqui Wood Cancer Centre, Medical Research Insitute, University of Dundee, Ninewells hospital and School of Medicine, Dundee, DD1 9SY, Scotland
| | - Colin N A Palmer
- Centre for Pharmacogenetics and Pharmacogenomics, Medical Research Institute, University of Dundee, Ninewells hospital and School of Medicine, Dundee, DD1 9SY, Scotland
| | - George Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, 70, El. Venizelou Ave, Athens, 17671, Greece
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, 21589, Saudi Arabia
| | - Lars Bertram
- Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 72, Berlin, 14195, Germany
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| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, Berlin, 14195, Germany
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, 20850, MD, USA
| | - Cecilia M Lindgren
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- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Nicholas J Timpson
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| | - Anke Tönjes
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
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| | - Thorkild I A Sørensen
- Novo Nordisk Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, Copenhagen, 2100, Denmark
- Institute of Preventive Medicine, Bispebjerg and Frederiksberg Hospital , The Capital Region, Copenhagen, 2000, Denmark
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Building 12A/Room 4047, 12 South Dr., Bethesda, 20892, Maryland, USA
| | - Donna K Arnett
- Department of Epidemiology, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, 35294, AL, USA
| | - Albertine J Oldehinkel
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, P.O. box 30.001, Groningen, 9700 RB, The Netherlands
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, 1415 Washington Heights, 48109, Ann Arbor, MI, USA
| | - Beverley Balkau
- Epidemiology of diabetes, obesity and chronic kidney disease over the lifecourse, Inserm, CESP Center for Research in Epidemiology and Population Health U1018, 16 Avenue Paul Vaillant Couturier, Villejuif, 94807, France
| | - Giovanni Gambaro
- Dipartimento di Scienze Mediche, Catholic University of the Sacred Heart, Via G. Moscati 31/34, Roma, 00168, Italy
| | - Andrew P Morris
- Estonian Genome Center, University of Tartu, Riia 23b, 51010, Tartu, Estonia
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
- Department of Biostatistics, University of Liverpool, Duncan Building, Daulby Stree, Liverpool, L69 3GA, UK
| | - Johan G Eriksson
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, P.O. Box 30, Helsinki, FI-00271, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, P.O. Box 20, University of Helsinki, Helsinki, FI-00014, Finland
- Vasa Central Hospital, Sandviksgatan 2-4, Vasa, 65130, Finland
- Folkhälsan Reasearch Centre, PB 63, University of Helsinki, Helsinki, FI-00014, Finland
- Unit of General Practice, Helsinki University Central Hospital, Haartmaninkatu 4, Helsinki, FI-00290, Finland
| | - Margie J Wright
- Neuro-Imaging Genetics, QIMR Berghofer Medical Research Institute, 300 Herston Rd, Herston, Brisbane, 4006 Australia
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Rd, Herston, Brisbane, 4006, Australia
| | - Steven C Hunt
- Cardiovascular Genetics Division, University of Utah, 420 Chipeta Way, Room 1160, Salt Lake City, 84117, Utah, USA
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Alzheimer Scotland Research Centre, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Ian J Deary
- Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Lyn R Griffiths
- Institute of Health and Biomedical Innovation, Queensland University of Technology, 60 Musk Avenue, Kelvin Grove, GPO Box 2434, Brisbane Qld 4001, Brisbane, Australia
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, Rotterdam, 3000 CA, The Netherlands
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| | - Nicola Pirastu
- Department of Medical Sciences, University of Trieste, Strada di Fiume 447 - Osp. di Cattinara, Trieste, 34149, Italy
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", via dell'Istria 65, Trieste, 34137, Italy
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, P.O. Box 20, Helsinki, FI-00014, Finland
- Department of Public Health, University of Helsinki, Hjelt Institute, P.O.Box 41, Mannerheimintie 172, Helsinki, FI-00014, Finland
- National Institute for Health and Welfare (THL), P.O.Box 30, Mannerheimintie 166, Helsinki, FI-00271, Finland
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Louis Pérusse
- Department of kinesiology, Laval University, 2300 rue de la Terrasse, Quebec, G1V 0A6, Canada
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, 2500 N. State St., Jackson, 39216, MS, USA
| | - Giorgia Girotto
- Department of Medical Sciences, University of Trieste, Strada di Fiume 447 - Osp. di Cattinara, Trieste, 34149, Italy
| | - Mark J Caulfield
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Olli Raitakari
- Department of Clinical Physiology and Nuclear Medicine, University of Turku and Turku University Hospital, Turku, 20521, Finland
- Research Center of Applied and Preventive Cardiovascular medicine, University of Turku, Turku, 20521, Finland
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, Netherlands
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
| | - Pim van der Harst
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Hanzeplein 1, Groningen, 9700RB, The Netherlands
- Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Catharijnesingel 52, Utrecht, 3501 DG, The Netherlands
- University of Groningen, University Medical Center Groningen, Department of Genetics, Hanzeplein 1, Groningen, 9700RB, The Netherlands
| | - Andrew A Hicks
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy - Affiliated Institute of the University of Lübeck, Lübeck, Germany
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, 665 Huntington Ave, Boston, 02115, USA
| | - Juha Sinisalo
- HUCH Heart and Lung center, Helsinki University Central Hospital, P.O. Box 340, Helsinki, FI-00029, Finland
| | - Paul Knekt
- Department of Health, Functional Capacity and Welfare, National Institute for Health and Welfare, P.O. Box 30, Helsinki, FI-00271, Finland
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Box 6501, Stockholm, SE-113 83, Sweden
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Box 281, Stockholm, SE-171 77, Sweden
| | - Anders Hamsten
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, CMM L8:03, Karolinska University Hospital, Solna, Stockholm, 171 76, Sweden
| | - Reinhold Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Auenbruggerplatz 22, Graz, A-8036, Austria
| | - Ingrid B Borecki
- Department of Genetics and Biostatistics, Washington University School of Medicine, 4444 Forest Park Boulevard, Saint Louis, 63108, MO, USA
| | - Erkki Vartiainen
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, P.O. Box 30, Helsinki, FI-00271, Finland
| | - Diane M Becker
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, 21287, Maryland, USA
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, 21205, Maryland, USA
| | - Dwaipayan Bharadwaj
- Genomics and Molecular Medicine, CSIR-Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, 27599, NC, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, 48109, MI, USA
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, Rotterdam, 3000 CA, The Netherlands
| | - Dharambir K Sanghera
- Department of Pediatrics, University of Oklahoma Health Sciences Center, 940 Stanton Young Boulevard, Oklahoma City, 73104, OK , USA
- Department of Pharmaceutical Sciences , University of Oklahoma Health Sceienecs Center, Oklahoma City , 73104, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, W.-Rathenau-Str. 48, Greifswald, 17475, Germany
| | - Eleftheria Zeggini
- Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1HH, UK
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Riia 23b, 51010, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Riia 23, Tartu, 51010 Estonia
| | - Paolo Gasparini
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", via dell'Istria 65, Trieste, 34137, Italy
| | - Sheila Ulivi
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", via dell'Istria 65, Trieste, 34137, Italy
| | - Carole Ober
- Department of Human Genetics, University of Chicago, 920 E. 58th Street, Chicago, IL, USA
| | - Daniela Toniolo
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Via Olgettina 58, Milano, 20132, Italy
| | - Igor Rudan
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Marina Ciullo
- Institute of Genetics and Biophysics "A. Buzzati-Traverso" CNR, via Pietro Castellino, 111, Naples, 80131, Italy
| | - Tim D Spector
- Department of Twin Research & Genetic Epidemiology, King's College London, South Wing, Block D, 3rd Floor, Westminster Bridge Road, London, SE1 7EH, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, Edinburgh, UK
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, 02118, MA, USA
- National Heart, Lung, and Blood Institute's Framingham Heart Study, 73 Mt. Wayte Ave, Framingham, 01702, MA, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, 10029, USA
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, 10029, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, 10029, USA
| | - Alan F Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, Edinburgh, UK
| | - Giriraj R Chandak
- Genomic Research on Complex Diseases (GRC) Group, CSIR-Centre for Cellular and Molecular Biology, Habshiguda, Uppal Road, Hyderabad, 500007, India
- Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore, 138672, Singapore
| | - Peter Vollenweider
- Department of Internal Medicine, University Hospital, Route du Bugnon 44, Lausanne, 1011, Switzerland
| | - Alan Shuldiner
- Division of Endocrinology, Diabetes, and Nutrition and Program for Personalised and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, 685 Baltimore St. MSTF, Baltimore, 21201, USA
- Program for Personalised and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, 685 Baltimore St. MSTF, Baltimore, 21201, USA
- Geriatric Research and Education Clinical Center, Veterans Administration Medical Center, 685 W Baltimore MSTF, Baltimore, 21201, USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, 900 Commonwealth Avenue, East, Harvard Medical School, Boston, Boston, MA 02215, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences , Los Angeles Biomedical Research Institute, 1124 W. Carson Street, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Naveed Sattar
- BHF centre, University of Glasgow, 126 University Avenue, Glasgow, G12 8TA, Scotland
| | - Ulf Gyllensten
- Immunology, Genetics & Pathology, Uppsala University, Husargatan 3, Box 815, Uppsala, SE-751 08, Sweden
| | - Kari E North
- Epidemiology, University of North Carolina, 137 E Franklin St., Suite 306, USA
- Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, 137 E. Franklin St., Suite 306, Chapel Hill, USA
| | - Mario Pirastu
- Institute of Population Genetics, National Research Council, Trav. La Crucca n. 3 - Reg. Baldinca, Sassari, 07100, Italy
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Services, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, 98101, WA, USA
- Group Health Research Institute, Group Health Cooperative, 1730 Minor Ave, Suite 1360, Seattle, 98101, WA, USA
| | - David R Weir
- Institute for Social Research, University of Michigan, 426 Thompson Street, 48104, Ann Arbor, MI, USA
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, 70210, Finland
| | - Vilmundur Gudnason
- Icelandic Heart Association, Holtasmari 1, 201, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
| | - Atsushi Takahashi
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital NHS Trust, Uxbridge Road, Southall, Middlesex, UB1 3HW, UK
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| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital NHS Trust, Uxbridge Road, Southall, Middlesex, UB1 3HW, UK
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| | - David P Strachan
- Population Health Research Institute, St George's, University of London, Cranmer Terrace, London, SW17 0RE, UK
| | - Harry Campbell
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Joel N Hirschhorn
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Cambridge, 02141, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge Center 7, Cambridge, 02242, MA, USA
- Department of Genetics, Harvard Medical School, 25 Shattuck St, Boston, 02115, MA, USA
| | - Markus Perola
- Estonian Genome Center, University of Tartu, Riia 23b, 51010, Tartu, Estonia
- Unit of Public Health Genomics, National Institute for Health and Welfare, P.O. Box 104, Helsinki, FI-00251, Finland
| | - Ozren Polašek
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
- Centre for Global Health and Department of Public Health, School of Medicine, University of Split, Soltanska 2, 21000 Split, Croatia
| | - James F Wilson
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, Edinburgh, UK
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Zhang Q, Calus MPL, Guldbrandtsen B, Lund MS, Sahana G. Estimation of inbreeding using pedigree, 50k SNP chip genotypes and full sequence data in three cattle breeds. BMC Genet 2015. [PMID: 26195126 PMCID: PMC4509611 DOI: 10.1186/s12863-015-0227-7] [Citation(s) in RCA: 115] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Background Levels of inbreeding in cattle populations have increased in the past due to the use of a limited number of bulls for artificial insemination. High levels of inbreeding lead to reduced genetic diversity and inbreeding depression. Various estimators based on different sources, e.g., pedigree or genomic data, have been used to estimate inbreeding coefficients in cattle populations. However, the comparative advantage of using full sequence data to assess inbreeding is unknown. We used pedigree and genomic data at different densities from 50k to full sequence variants to compare how different methods performed for the estimation of inbreeding levels in three different cattle breeds. Results Five different estimates for inbreeding were calculated and compared in this study: pedigree based inbreeding coefficient (FPED); run of homozygosity (ROH)-based inbreeding coefficients (FROH); genomic relationship matrix (GRM)-based inbreeding coefficients (FGRM); inbreeding coefficients based on excess of homozygosity (FHOM) and correlation of uniting gametes (FUNI). Estimates using ROH provided the direct estimated levels of autozygosity in the current populations and are free effects of allele frequencies and incomplete pedigrees which may increase in inaccuracy in estimation of inbreeding. The highest correlations were observed between FROH estimated from the full sequence variants and the FROH estimated from 50k SNP (single nucleotide polymorphism) genotypes. The estimator based on the correlation between uniting gametes (FUNI) using full genome sequences was also strongly correlated with FROH detected from sequence data. Conclusions Estimates based on ROH directly reflected levels of homozygosity and were not influenced by allele frequencies, unlike the three other estimates evaluated (FGRM, FHOM and FUNI), which depended on estimated allele frequencies. FPED suffered from limited pedigree depth. Marker density affects ROH estimation. Detecting ROH based on 50k chip data was observed to give estimates similar to ROH from sequence data. In the absence of full sequence data ROH based on 50k can be used to access homozygosity levels in individuals. However, genotypes denser than 50k are required to accurately detect short ROH that are most likely identical by descent (IBD).
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Affiliation(s)
- Qianqian Zhang
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, DK-8830, Denmark. .,Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Wageningen, 6700 AH, The Netherlands.
| | - Mario P L Calus
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Wageningen, 6700 AH, The Netherlands.
| | - Bernt Guldbrandtsen
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, DK-8830, Denmark.
| | - Mogens S Lund
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, DK-8830, Denmark.
| | - Goutam Sahana
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, DK-8830, Denmark.
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666
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Kelmemi W, Teeuw ME, Bochdanovits Z, Ouburg S, Jonker MA, Alkuraya F, Hashem M, Kayserili H, van Haeringen A, Sheridan E, Masri A, Cobben JM, Rizzu P, Kostense PJ, Dommering CJ, Henneman L, Bouhamed-Chaabouni H, Heutink P, Ten Kate LP, Cornel MC. Determining the genome-wide kinship coefficient seems unhelpful in distinguishing consanguineous couples with a high versus low risk for adverse reproductive outcome. BMC MEDICAL GENETICS 2015; 16:50. [PMID: 26188928 PMCID: PMC4557855 DOI: 10.1186/s12881-015-0191-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2014] [Accepted: 06/17/2015] [Indexed: 11/25/2022]
Abstract
Background Offspring of consanguineous couples are at increased risk of congenital disorders. The risk increases as parents are more closely related. Individuals that have the same degree of relatedness according to their pedigree, show variable genomic kinship coefficients. To investigate whether we can differentiate between couples with high- and low risk for offspring with congenital disorders, we have compared the genomic kinship coefficient of consanguineous parents with a child affected with an autosomal recessive disorder with that of consanguineous parents with only healthy children, corrected for the degree of pedigree relatedness. Methods 151 consanguineous couples (73 cases and 78 controls) from 10 different ethnic backgrounds were genotyped on the Affymetrix platform and passed quality control checks. After pruning SNPs in linkage disequilibrium, 57,358 SNPs remained. Kinship coefficients were calculated using three different toolsets: PLINK, King and IBDelphi, yielding five different estimates (IBDelphi, PLINK (all), PLINK (by population), King robust (all) and King homo (by population)). We performed a one-sided Mann Whitney test to investigate whether the median relative difference regarding observed and expected kinship coefficients is bigger for cases than for controls. Furthermore, we fitted a mixed effects linear model to correct for a possible population effect. Results Although the estimated degrees of genomic relatedness with the different toolsets show substantial variability, correlation measures between the different estimators demonstrated moderate to strong correlations. Controls have higher point estimates for genomic kinship coefficients. The one-sided Mann Whitney test did not show any evidence for a higher median relative difference for cases compared to controls. Neither did the regression analysis exhibit a positive association between case–control status and genomic kinship coefficient. Conclusions In this case–control setting, in which we compared consanguineous couples corrected for degree of pedigree relatedness, a higher degree of genomic relatedness was not significantly associated with a higher likelihood of having an affected child. Further translational research should focus on which parts of the genome and which pathogenic mutations couples are sharing. Looking at relatedness coefficients by determining genome-wide SNPs does not seem to be an effective measure for prospective risk assessment in consanguineous parents. Electronic supplementary material The online version of this article (doi:10.1186/s12881-015-0191-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- W Kelmemi
- Laboratory of Human Genetics, Faculty of Medicine, University of Tunis El Manar, Tunis, Tunisia
| | - M E Teeuw
- Department of Clinical Genetics, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.,EMGO Institute for Health and Care Research, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Z Bochdanovits
- Department of Clinical Genetics, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - S Ouburg
- Laboratory of Immunogenetics, Medical Microbiology and Infection Control, Research School V-ICI, VU University Medical Center, Amsterdam, The Netherlands
| | - M A Jonker
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - F Alkuraya
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - M Hashem
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - H Kayserili
- Medical Genetics Department, Istanbul Medical Faculty, Istanbul University, Istanbul, Turkey
| | - A van Haeringen
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands.,Juliana Children's Hospital, Hague, The Netherlands
| | - E Sheridan
- Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK.,Department of Genetics, Wellcome Trust Brenner Building, St James's University Hospital, Leeds, UK
| | - A Masri
- Division of Child Neurology, Department of Pediatrics, University of Jordan, Amman, Jordan
| | - J M Cobben
- Department of Pediatric Genetics, AMC University Hospital, Amsterdam, The Netherlands
| | - P Rizzu
- Department of Clinical Genetics, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.,Genome Biology of Neurodegenerative Diseases, German Center for Neurodegenerative Diseases, Tübingen, Germany
| | - P J Kostense
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - C J Dommering
- Department of Clinical Genetics, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - L Henneman
- Department of Clinical Genetics, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.,EMGO Institute for Health and Care Research, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - H Bouhamed-Chaabouni
- Laboratory of Human Genetics, Faculty of Medicine, University of Tunis El Manar, Tunis, Tunisia
| | - P Heutink
- Department of Clinical Genetics, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.,Genome Biology of Neurodegenerative Diseases, German Center for Neurodegenerative Diseases, Tübingen, Germany
| | - L P Ten Kate
- Department of Clinical Genetics, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.,EMGO Institute for Health and Care Research, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - M C Cornel
- Department of Clinical Genetics, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands. .,EMGO Institute for Health and Care Research, VU University Medical Center, Mail BS7, D450, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.
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667
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Kaiser VB, Svinti V, Prendergast JG, Chau YY, Campbell A, Patarcic I, Barroso I, Joshi PK, Hastie ND, Miljkovic A, Taylor MS, Enroth S, Memari Y, Kolb-Kokocinski A, Wright AF, Gyllensten U, Durbin R, Rudan I, Campbell H, Polašek O, Johansson Å, Sauer S, Porteous DJ, Fraser RM, Drake C, Vitart V, Hayward C, Semple CA, Wilson JF. Homozygous loss-of-function variants in European cosmopolitan and isolate populations. Hum Mol Genet 2015; 24:5464-74. [PMID: 26173456 PMCID: PMC4572071 DOI: 10.1093/hmg/ddv272] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2015] [Accepted: 07/07/2015] [Indexed: 12/30/2022] Open
Abstract
Homozygous loss of function (HLOF) variants provide a valuable window on gene function in humans, as well as an inventory of the human genes that are not essential for survival and reproduction. All humans carry at least a few HLOF variants, but the exact number of inactivated genes that can be tolerated is currently unknown—as are the phenotypic effects of losing function for most human genes. Here, we make use of 1432 whole exome sequences from five European populations to expand the catalogue of known human HLOF mutations; after stringent filtering of variants in our dataset, we identify a total of 173 HLOF mutations, 76 (44%) of which have not been observed previously. We find that population isolates are particularly well suited to surveys of novel HLOF genes because individuals in such populations carry extensive runs of homozygosity, which we show are enriched for novel, rare HLOF variants. Further, we make use of extensive phenotypic data to show that most HLOFs, ascertained in population-based samples, appear to have little detectable effect on the phenotype. On the contrary, we document several genes directly implicated in disease that seem to tolerate HLOF variants. Overall HLOF genes are enriched for olfactory receptor function and are expressed in testes more often than expected, consistent with reduced purifying selection and incipient pseudogenisation.
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Affiliation(s)
- Vera B Kaiser
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine and
| | - Victoria Svinti
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine and
| | - James G Prendergast
- The Roslin Institute, The University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK
| | - You-Ying Chau
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine and
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK
| | - Inga Patarcic
- Medical School, University of Split, Soltanska 2, Split 21000, Croatia
| | - Inês Barroso
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Peter K Joshi
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, UK
| | - Nicholas D Hastie
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine and
| | - Ana Miljkovic
- Medical School, University of Split, Soltanska 2, Split 21000, Croatia
| | - Martin S Taylor
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine and
| | | | | | - Stefan Enroth
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, Uppsala SE-75108, Sweden and
| | - Yasin Memari
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | | | - Alan F Wright
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine and
| | - Ulf Gyllensten
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, Uppsala SE-75108, Sweden and
| | - Richard Durbin
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Igor Rudan
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, UK
| | - Harry Campbell
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, UK
| | - Ozren Polašek
- Medical School, University of Split, Soltanska 2, Split 21000, Croatia, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, UK
| | - Åsa Johansson
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, Uppsala SE-75108, Sweden and
| | - Sascha Sauer
- Max-Planck-Institute for Molecular Genetics, Otto-Warburg-Laboratory, Berlin, Germany
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK
| | - Ross M Fraser
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, UK
| | - Camilla Drake
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine and
| | - Veronique Vitart
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine and
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine and
| | - Colin A Semple
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine and
| | - James F Wilson
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine and Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, UK
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668
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Kim ES, Sonstegard TS, Van Tassell CP, Wiggans G, Rothschild MF. The Relationship between Runs of Homozygosity and Inbreeding in Jersey Cattle under Selection. PLoS One 2015; 10:e0129967. [PMID: 26154171 PMCID: PMC4496098 DOI: 10.1371/journal.pone.0129967] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2014] [Accepted: 05/14/2015] [Indexed: 11/19/2022] Open
Abstract
Inbreeding is often an inevitable outcome of strong directional artificial selection but on average it reduces population fitness with increased frequency of recessive deleterious alleles. Runs of homozygosity (ROH) representing genomic autozygosity that occur from mating between selected and genomically related individuals may be able to reveal the regions affecting fitness. To examine the influence of genomic autozygosity on fitness, we used a genome-wide association test to evaluate potential negative correlations between ROH and daughter pregnancy rate (DPR) or somatic cell score (SCS) in US Jersey cattle. In addition, relationships between changes of local ROH and inbreeding coefficients (F) were assessed to locate genomic regions with increased inbreeding. Despite finding some decreases in fertility associated with incremental increases in F, most emerging local ROH were not significantly associated with DPR or SCS. Furthermore, the analyses of ROH could be approximated with the most frequent haplotype(s), including the associations of ROH and F or traits. The analysis of the most frequent haplotype revealed that associations of ROH and fertility could be accounted for by the additive genetic effect on the trait. Thus, we suggest that a change of autozygosity is more likely to demonstrate footprints of selected haplotypes for production rather than highlight the possible increased local autozygosity of a recessive detrimental allele resulting from the mating between closely related animals in Jersey cattle.
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Affiliation(s)
- Eui-Soo Kim
- Animal Genomics & Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America
- Department of Animal Science, Iowa State University, Ames, Iowa, United States of America
| | - Tad S. Sonstegard
- Animal Genomics & Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America
| | - Curtis P. Van Tassell
- Animal Genomics & Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America
| | - George Wiggans
- Animal Genomics & Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America
| | - Max F. Rothschild
- Department of Animal Science, Iowa State University, Ames, Iowa, United States of America
- * E-mail:
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669
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Taylor JC, Martin HC, Lise S, Broxholme J, Cazier JB, Rimmer A, Kanapin A, Lunter G, Fiddy S, Allan C, Aricescu AR, Attar M, Babbs C, Becq J, Beeson D, Bento C, Bignell P, Blair E, Buckle VJ, Bull K, Cais O, Cario H, Chapel H, Copley RR, Cornall R, Craft J, Dahan K, Davenport EE, Dendrou C, Devuyst O, Fenwick AL, Flint J, Fugger L, Gilbert RD, Goriely A, Green A, Greger IH, Grocock R, Gruszczyk AV, Hastings R, Hatton E, Higgs D, Hill A, Holmes C, Howard M, Hughes L, Humburg P, Johnson D, Karpe F, Kingsbury Z, Kini U, Knight JC, Krohn J, Lamble S, Langman C, Lonie L, Luck J, McCarthy D, McGowan SJ, McMullin MF, Miller KA, Murray L, Németh AH, Nesbit MA, Nutt D, Ormondroyd E, Oturai AB, Pagnamenta A, Patel SY, Percy M, Petousi N, Piazza P, Piret SE, Polanco-Echeverry G, Popitsch N, Powrie F, Pugh C, Quek L, Robbins PA, Robson K, Russo A, Sahgal N, van Schouwenburg PA, Schuh A, Silverman E, Simmons A, Sørensen PS, Sweeney E, Taylor J, Thakker RV, Tomlinson I, Trebes A, Twigg SR, Uhlig HH, Vyas P, Vyse T, Wall SA, Watkins H, Whyte MP, Witty L, et alTaylor JC, Martin HC, Lise S, Broxholme J, Cazier JB, Rimmer A, Kanapin A, Lunter G, Fiddy S, Allan C, Aricescu AR, Attar M, Babbs C, Becq J, Beeson D, Bento C, Bignell P, Blair E, Buckle VJ, Bull K, Cais O, Cario H, Chapel H, Copley RR, Cornall R, Craft J, Dahan K, Davenport EE, Dendrou C, Devuyst O, Fenwick AL, Flint J, Fugger L, Gilbert RD, Goriely A, Green A, Greger IH, Grocock R, Gruszczyk AV, Hastings R, Hatton E, Higgs D, Hill A, Holmes C, Howard M, Hughes L, Humburg P, Johnson D, Karpe F, Kingsbury Z, Kini U, Knight JC, Krohn J, Lamble S, Langman C, Lonie L, Luck J, McCarthy D, McGowan SJ, McMullin MF, Miller KA, Murray L, Németh AH, Nesbit MA, Nutt D, Ormondroyd E, Oturai AB, Pagnamenta A, Patel SY, Percy M, Petousi N, Piazza P, Piret SE, Polanco-Echeverry G, Popitsch N, Powrie F, Pugh C, Quek L, Robbins PA, Robson K, Russo A, Sahgal N, van Schouwenburg PA, Schuh A, Silverman E, Simmons A, Sørensen PS, Sweeney E, Taylor J, Thakker RV, Tomlinson I, Trebes A, Twigg SR, Uhlig HH, Vyas P, Vyse T, Wall SA, Watkins H, Whyte MP, Witty L, Wright B, Yau C, Buck D, Humphray S, Ratcliffe PJ, Bell JI, Wilkie AO, Bentley D, Donnelly P, McVean G. Factors influencing success of clinical genome sequencing across a broad spectrum of disorders. Nat Genet 2015; 47:717-726. [PMID: 25985138 PMCID: PMC4601524 DOI: 10.1038/ng.3304] [Show More Authors] [Citation(s) in RCA: 268] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2014] [Accepted: 04/22/2015] [Indexed: 12/12/2022]
Abstract
To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.
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Affiliation(s)
- Jenny C Taylor
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Hilary C Martin
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Stefano Lise
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - John Broxholme
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Andy Rimmer
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Alexander Kanapin
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Gerton Lunter
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Simon Fiddy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Chris Allan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - A Radu Aricescu
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Moustafa Attar
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Christian Babbs
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | | | - David Beeson
- Neurosciences Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Celeste Bento
- Hematology Department, Centro Hospitalar e Universitário de Coimbra, Portugal
| | - Patricia Bignell
- Molecular Haematology Department, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Edward Blair
- Department of Clinical Genetics, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Veronica J Buckle
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Katherine Bull
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Centre for Cellular and Molecular Physiology, University of Oxford, Oxford, UK
| | - Ondrej Cais
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Holger Cario
- Department of Pediatrics and Adolescent Medicine, University Medical Center, Ulm, Germany
| | - Helen Chapel
- Primary Immunodeficiency Unit, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Richard R Copley
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Richard Cornall
- Centre for Cellular and Molecular Physiology, University of Oxford, Oxford, UK
| | - Jude Craft
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Karin Dahan
- Centre de Génétique Humaine, Institut de Génétique et de Pathologie, Gosselies, Belgium
- Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
| | - Emma E Davenport
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Calliope Dendrou
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Olivier Devuyst
- Institute of Physiology, Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Aimée L Fenwick
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Jonathan Flint
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Lars Fugger
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Rodney D Gilbert
- University Hospital Southampton NHS Foundation Trust, University of Southampton, Southampton, UK
| | - Anne Goriely
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Angie Green
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Ingo H Greger
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
| | | | - Anja V Gruszczyk
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Robert Hastings
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Edouard Hatton
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Doug Higgs
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Adrian Hill
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- The Jenner Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Chris Holmes
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Malcolm Howard
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Linda Hughes
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Peter Humburg
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - David Johnson
- Craniofacial Unit, Department of Plastic and Reconstructive Surgery, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Fredrik Karpe
- Oxford Laboratory for Integrative Physiology, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | | | - Usha Kini
- Department of Clinical Genetics, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Julian C Knight
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Jonathan Krohn
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Sarah Lamble
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Craig Langman
- Kidney Diseases, Feinberg School of Medicine, Northwestern University and the Ann and Robert H Lurie Children's Hospital of Chicago, Chicago, Illinois, USA
| | - Lorne Lonie
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Joshua Luck
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Davis McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Simon J McGowan
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | | | - Kerry A Miller
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Lisa Murray
- Illumina Cambridge Limited, Saffron Walden, UK
| | - Andrea H Németh
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - M Andrew Nesbit
- Academic Endocrine Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | - David Nutt
- Centre for Neuropsychopharmacology, Division of Brain Sciences, Imperial College, London, UK
| | - Elizabeth Ormondroyd
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Annette Bang Oturai
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Alistair Pagnamenta
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Smita Y Patel
- Primary Immunodeficiency Unit, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Melanie Percy
- Department of Haematology, Belfast City Hospital, Belfast, UK
| | - Nayia Petousi
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Paolo Piazza
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Sian E Piret
- Academic Endocrine Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | | | - Niko Popitsch
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Fiona Powrie
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Chris Pugh
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Lynn Quek
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Peter A Robbins
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Kathryn Robson
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Alexandra Russo
- Department of Pediatrics, University Hospital, Mainz, Germany
| | - Natasha Sahgal
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Anna Schuh
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Department of Oncology, University of Oxford, Oxford, UK
| | - Earl Silverman
- Division of Rheumatology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Alison Simmons
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Per Soelberg Sørensen
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Elizabeth Sweeney
- Department of Clinical Genetics, Liverpool Women's NHS Foundation Trust, Liverpool, UK
| | - John Taylor
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Oxford NHS Regional Molecular Genetics Laboratory, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Rajesh V Thakker
- Academic Endocrine Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | - Ian Tomlinson
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Amy Trebes
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Stephen Rf Twigg
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Holm H Uhlig
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Paresh Vyas
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Tim Vyse
- Division of Genetics, King's College London, Guy's Hospital, London, UK
| | - Steven A Wall
- Craniofacial Unit, Department of Plastic and Reconstructive Surgery, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Michael P Whyte
- Center for Metabolic Bone Disease and Molecular Research, Shriners Hospital for Children, St Louis, Missouri, USA
| | - Lorna Witty
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Ben Wright
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Chris Yau
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - David Buck
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | | | - John I Bell
- Office of the Regius Professor of Medicine, University of Oxford, Oxford, UK
| | - Andrew Om Wilkie
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | | | - Peter Donnelly
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Gilean McVean
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
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670
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Amador C, Huffman J, Trochet H, Campbell A, Porteous D, Wilson JF, Hastie N, Vitart V, Hayward C, Navarro P, Haley CS. Recent genomic heritage in Scotland. BMC Genomics 2015; 16:437. [PMID: 26048416 PMCID: PMC4458001 DOI: 10.1186/s12864-015-1605-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2014] [Accepted: 05/01/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The Generation Scotland Scottish Family Health Study (GS:SFHS) includes 23,960 participants from across Scotland with records for many health-related traits and environmental covariates. Genotypes at ~700 K SNPs are currently available for 10,000 participants. The cohort was designed as a resource for genetic and health related research and the study of complex traits. In this study we developed a suite of analyses to disentangle the genomic differentiation within GS:SFHS individuals to describe and optimise the sample and methods for future analyses. RESULTS We combined the genotypic information of GS:SFHS with 1092 individuals from the 1000 Genomes project and estimated their genomic relationships. Then, we performed Principal Component Analyses of the resulting relationships to investigate the genomic origin of different groups. We characterised two groups of individuals: those with a few sparse rare markers in the genome, and those with several large rare haplotypes which might represent relatively recent exogenous ancestors. We identified some individuals with likely Italian ancestry and a group with some potential African/Asian ancestry. An analysis of homozygosity in the GS:SFHS sample revealed a very similar pattern to other European populations. We also identified an individual carrying a chromosome 1 uniparental disomy. We found evidence of local geographic stratification within the population having impact on the genomic structure. CONCLUSIONS These findings illuminate the history of the Scottish population and have implications for further analyses such as the study of the contributions of common and rare variants to trait heritabilities and the evaluation of genomic and phenotypic prediction of disease.
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Affiliation(s)
- Carmen Amador
- MRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK.
| | | | - Holly Trochet
- MRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK.
| | | | - David Porteous
- MRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK.
| | | | - James F Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, EH8 9AG, UK.
| | - Nick Hastie
- MRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK.
| | | | | | - Pau Navarro
- MRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK.
| | - Chris S Haley
- MRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. .,Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, EH25 9RG, UK.
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671
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Mészáros G, Boison SA, Pérez O'Brien AM, Ferenčaković M, Curik I, Da Silva MVB, Utsunomiya YT, Garcia JF, Sölkner J. Genomic analysis for managing small and endangered populations: a case study in Tyrol Grey cattle. Front Genet 2015; 6:173. [PMID: 26074948 PMCID: PMC4443735 DOI: 10.3389/fgene.2015.00173] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2014] [Accepted: 04/20/2015] [Indexed: 11/30/2022] Open
Abstract
Analysis of genomic data is increasingly becoming part of the livestock industry. Therefore, the routine collection of genomic information would be an invaluable resource for effective management of breeding programs in small, endangered populations. The objective of the paper was to demonstrate how genomic data could be used to analyse (1) linkage disequlibrium (LD), LD decay and the effective population size (NeLD); (2) Inbreeding level and effective population size (NeROH) based on runs of homozygosity (ROH); (3) Prediction of genomic breeding values (GEBV) using small within-breed and genomic information from other breeds. The Tyrol Grey population was used as an example, with the goal to highlight the potential of genomic analyses for small breeds. In addition to our own results we discuss additional use of genomics to assess relatedness, admixture proportions, and inheritance of harmful variants. The example data set consisted of 218 Tyrol Grey bull genotypes, which were all available AI bulls in the population. After standard quality control restrictions 34,581 SNPs remained for the analysis. A separate quality control was applied to determine ROH levels based on Illumina GenCall and Illumina GenTrain scores, resulting into 211 bulls and 33,604 SNPs. LD was computed as the squared correlation coefficient between SNPs within a 10 mega base pair (Mb) region. ROHs were derived based on regions covering at least 4, 8, and 16 Mb, suggesting that animals had common ancestors approximately 12, 6, and 3 generations ago, respectively. The corresponding mean inbreeding coefficients (FROH) were 4.0% for 4 Mb, 2.9% for 8 Mb and 1.6% for 16 Mb runs. With an average generation interval of 5.66 years, estimated NeROH was 125 (NeROH>16 Mb), 186 (NeROH>8 Mb) and 370 (NeROH>4 Mb) indicating strict avoidance of close inbreeding in the population. The LD was used as an alternative method to infer the population history and the Ne. The results show a continuous decrease in NeLD, to 780, 120, and 80 for 100, 10, and 5 generations ago, respectively. Genomic selection was developed for and is working well in large breeds. The same methodology was applied in Tyrol Grey cattle, using different reference populations. Contrary to the expectations, the accuracy of GEBVs with very small within breed reference populations were very high, between 0.13–0.91 and 0.12–0.63, when estimated breeding values and deregressed breeding values were used as pseudo-phenotypes, respectively. Subsequent analyses confirmed the high accuracies being a consequence of low reliabilities of pseudo-phenotypes in the validation set, thus being heavily influenced by parent averages. Multi-breed and across breed reference sets gave inconsistent and lower accuracies. Genomic information may have a crucial role in management of small breeds, even if its primary usage differs from that of large breeds. It allows to assess relatedness between individuals, trends in inbreeding and to take decisions accordingly. These decisions would be based on the real genome architecture, rather than conventional pedigree information, which can be missing or incomplete. We strongly suggest the routine genotyping of all individuals that belong to a small breed in order to facilitate the effective management of endangered livestock populations.
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Affiliation(s)
- Gábor Mészáros
- Division of Livestock Sciences, University of Natural Resources and Life Sciences Vienna, Austria
| | - Solomon A Boison
- Division of Livestock Sciences, University of Natural Resources and Life Sciences Vienna, Austria
| | - Ana M Pérez O'Brien
- Division of Livestock Sciences, University of Natural Resources and Life Sciences Vienna, Austria
| | | | - Ino Curik
- Department of Animal Science, University of Zagreb Zagreb, Croatia
| | | | | | - Jose F Garcia
- UNESP-Universidade Estadual Paulista Jaboticabal, Brazil
| | - Johann Sölkner
- Division of Livestock Sciences, University of Natural Resources and Life Sciences Vienna, Austria
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672
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Spiliopoulou A, Nagy R, Bermingham ML, Huffman JE, Hayward C, Vitart V, Rudan I, Campbell H, Wright AF, Wilson JF, Pong-Wong R, Agakov F, Navarro P, Haley CS. Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models. Hum Mol Genet 2015; 24:4167-82. [PMID: 25918167 PMCID: PMC4476450 DOI: 10.1093/hmg/ddv145] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2015] [Accepted: 04/19/2015] [Indexed: 01/02/2023] Open
Abstract
We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge.
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Affiliation(s)
- Athina Spiliopoulou
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK, Pharmatics Limited, Edinburgh EH16 4UX, UK
| | - Reka Nagy
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Mairead L Bermingham
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Jennifer E Huffman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK and
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK and
| | - Alan F Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - James F Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK and
| | - Ricardo Pong-Wong
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Midlothian EH25 9RG, UK
| | | | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Chris S Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Midlothian EH25 9RG, UK
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673
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Kim ES, Sonstegard TS, Rothschild MF. Recent artificial selection in U.S. Jersey cattle impacts autozygosity levels of specific genomic regions. BMC Genomics 2015; 16:302. [PMID: 25887761 PMCID: PMC4409734 DOI: 10.1186/s12864-015-1500-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2014] [Accepted: 03/30/2015] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Genome signatures of artificial selection in U.S. Jersey cattle were identified by examining changes in haplotype homozygosity for a resource population of animals born between 1953 and 2007. Genetic merit of this population changed dramatically during this period for a number of traits, especially milk yield. The intense selection underlying these changes was achieved through extensive use of artificial insemination (AI), which also increased consanguinity of the population to a few superior Jersey bulls. As a result, allele frequencies are shifted for many contemporary animals, and in numerous cases to a homozygous state for specific genomic regions. The goal of this study was to identify those selection signatures that occurred after extensive use of AI since the 1960, using analyses of shared haplotype segments or Runs of Homozygosity. When combined with animal birth year information, signatures of selection associated with economically important traits were identified and compared to results from an extended haplotype homozygosity analysis. RESULTS Overall, our results reveal that more recent selection increased autozygosity across the entire genome, but some specific regions increased more than others. A genome-wide scan identified more than 15 regions with a substantial change in autozygosity. Haplotypes found to be associated with increased milk, fat and protein yield in U.S. Jersey cattle also consistently increased in frequency. CONCLUSIONS The analyses used in this study was able to detect directional selection over the last few decades when individual production records for Jersey animals were available.
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Affiliation(s)
- Eui-Soo Kim
- United States Department of Agriculture, Animal Genomics & Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, Beltsville, MD, 20705, USA.
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA.
| | - Tad S Sonstegard
- United States Department of Agriculture, Animal Genomics & Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, Beltsville, MD, 20705, USA.
| | - Max F Rothschild
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA.
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674
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Calderón R, Hernández CL, Cuesta P, Dugoujon JM. Surnames and Y-chromosomal markers reveal low relationships in Southern Spain. PLoS One 2015; 10:e0123098. [PMID: 25860017 PMCID: PMC4393112 DOI: 10.1371/journal.pone.0123098] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2014] [Accepted: 02/27/2015] [Indexed: 11/21/2022] Open
Abstract
A sample of 416 males from western and eastern Andalusia has been jointly analyzed for surnames and Y-chromosome haplogroups and haplotypes. The observed number of different surnames was 222 (353 when the second surname of the Spanish system of naming is considered). The great majority of recorded surnames have a Castilian-Leonese origin, while Catalan or Basque surnames have not been found. A few Arab-related surnames appear but none discernible of Sephardic-Jewish descent. Low correlation among surnames with different population frequencies and Y-chromosome markers, at different levels of genetic resolution, has been observed in Andalusia. This finding could be explained mainly by the very low rate of monophyletic surnames because of the historical process of surname ascription and the resulting high frequencies of the most common Spanish surnames. The introduction of surnames in Spain during the Middle Ages coincided with Reconquest of the territories under Islamic rule, and Muslims and Jews progressively adopted the present male line surname system. Sampled surnames and Y-chromosome lineages fit well a power-law distribution and observed isonymy is very close to that of the general population. Besides, our data and results show that the reliability of the isonymy method should be questioned because of the high rate of polyphyletic surnames, even in small geographic regions and autochthonous populations. Random isonymy would be consistently dependent of the most common surname frequencies in the population.
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Affiliation(s)
- Rosario Calderón
- Departamento de Zoología y Antropología Física, Facultad de Biología, Universidad Complutense, Madrid, Spain
- * E-mail:
| | - Candela L. Hernández
- Departamento de Zoología y Antropología Física, Facultad de Biología, Universidad Complutense, Madrid, Spain
| | - Pedro Cuesta
- Centro de Proceso de Datos, Universidad Complutense, Madrid, Spain
| | - Jean Michel Dugoujon
- CNRS UMR 5288 Laboratoire d’Anthropologie Moléculaire et d’Imagerie de Synthèse (AMIS), Université Paul Sabatier Toulouse III, Toulouse, France
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675
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Pfahler S, Distl O. Effective population size, extended linkage disequilibrium and signatures of selection in the rare dog breed lundehund. PLoS One 2015; 10:e0122680. [PMID: 25860808 PMCID: PMC4393028 DOI: 10.1371/journal.pone.0122680] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2014] [Accepted: 02/24/2015] [Indexed: 12/29/2022] Open
Abstract
The Lundehund is an old dog breed with remarkable anatomical features including polydactyly in all four limbs and extraordinary flexibility of the spine. We genotyped 28 Lundehund using the canine Illumina high density beadchip to estimate the effective population size (Ne) and inbreeding coefficients as well as to identify potential regions of positive selection. The decay of linkage disequilibrium was slow with r2 = 0.95 in 50 kb distance. The last 7-200 generations ago, Ne was at 10-13. An increase of Ne was noted in the very recent generations with a peak value of 19 for Ne at generation 4. The FROH estimated for 50-, 65- and 358-SNP windows were 0.87, 087 and 0.81, respectively. The most likely estimates for FROH after removing identical-by-state segments due to linkage disequilibria were at 0.80-0.81. The extreme loss of heterozygosity has been accumulated through continued inbreeding over 200 generations within a probably closed population with a small effective population size. The mean inbreeding coefficient based on pedigree data for the last 11 generations (FPed = 0.10) was strongly biased downwards due to the unknown coancestry of the founders in this pedigree data. The long-range haplotype test identified regions with genes involved in processes of immunity, olfaction, woundhealing and neuronal development as potential targets of selection. The genes QSOX2, BMPR1B and PRRX2 as well as MYOM1 are candidates for selection on the Lundehund characteristics small body size, increased number of digits per paw and extraordinary mobility, respectively.
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Affiliation(s)
- Sophia Pfahler
- Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover, Bünteweg 17p, 30559 Hannover, Germany
| | - Ottmar Distl
- Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover, Bünteweg 17p, 30559 Hannover, Germany
- * E-mail:
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676
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McLaughlin RL, Kenna KP, Vajda A, Heverin M, Byrne S, Donaghy CG, Cronin S, Bradley DG, Hardiman O. Homozygosity mapping in an Irish ALS case–control cohort describes local demographic phenomena and points towards potential recessive risk loci. Genomics 2015; 105:237-41. [DOI: 10.1016/j.ygeno.2015.01.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2014] [Revised: 01/07/2015] [Accepted: 01/16/2015] [Indexed: 12/19/2022]
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677
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Abstract
We describe the scientific enterprise at the intersection of evolutionary psychology and behavioral genetics-a field that could be termed Evolutionary Behavioral Genetics-and how modern genetic data is revolutionizing our ability to test questions in this field. We first explain how genetically informative data and designs can be used to investigate questions about the evolution of human behavior, and describe some of the findings arising from these approaches. Second, we explain how evolutionary theory can be applied to the investigation of behavioral genetic variation. We give examples of how new data and methods provide insight into the genetic architecture of behavioral variation and what this tells us about the evolutionary processes that acted on the underlying causal genetic variants.
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Affiliation(s)
- Brendan P Zietsch
- School of Psychology, University of Queensland, Brisbane, Queensland, Australia ; Genetic Epidemiology Laboratory, QIMR Berghofer, Brisbane, Queensland, Australia
| | - Teresa R de Candia
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado, United States of America ; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States of America
| | - Matthew C Keller
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado, United States of America ; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States of America
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678
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Ciancanelli MJ, Huang SXL, Luthra P, Garner H, Itan Y, Volpi S, Lafaille FG, Trouillet C, Schmolke M, Albrecht RA, Israelsson E, Lim HK, Casadio M, Hermesh T, Lorenzo L, Leung LW, Pedergnana V, Boisson B, Okada S, Picard C, Ringuier B, Troussier F, Chaussabel D, Abel L, Pellier I, Notarangelo LD, García-Sastre A, Basler CF, Geissmann F, Zhang SY, Snoeck HW, Casanova JL. Infectious disease. Life-threatening influenza and impaired interferon amplification in human IRF7 deficiency. Science 2015; 348:448-53. [PMID: 25814066 DOI: 10.1126/science.aaa1578] [Citation(s) in RCA: 362] [Impact Index Per Article: 36.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2014] [Accepted: 03/12/2015] [Indexed: 12/24/2022]
Abstract
Severe influenza disease strikes otherwise healthy children and remains unexplained. We report compound heterozygous null mutations in IRF7, which encodes the transcription factor interferon regulatory factor 7, in an otherwise healthy child who suffered life-threatening influenza during primary infection. In response to influenza virus, the patient's leukocytes and plasmacytoid dendritic cells produced very little type I and III interferons (IFNs). Moreover, the patient's dermal fibroblasts and induced pluripotent stem cell (iPSC)-derived pulmonary epithelial cells produced reduced amounts of type I IFN and displayed increased influenza virus replication. These findings suggest that IRF7-dependent amplification of type I and III IFNs is required for protection against primary infection by influenza virus in humans. They also show that severe influenza may result from single-gene inborn errors of immunity.
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Affiliation(s)
- Michael J Ciancanelli
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Sarah X L Huang
- Columbia Center for Translational Immunology, Columbia University Medical Center, New York, NY, USA. Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Priya Luthra
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hannah Garner
- Centre for Molecular and Cellular Biology of Inflammation (CMCBI), King's College London, London SE1 1UL, UK
| | - Yuval Itan
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Stefano Volpi
- Division of Immunology and Manton Center for Orphan Disease Research, Children's Hospital, Harvard Medical School, Boston, MA, USA. Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132 Genoa, Italy
| | - Fabien G Lafaille
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Céline Trouillet
- Centre for Molecular and Cellular Biology of Inflammation (CMCBI), King's College London, London SE1 1UL, UK
| | - Mirco Schmolke
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Randy A Albrecht
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Elisabeth Israelsson
- Department of Systems Immunology, Benaroya Research Institute at Virginia Mason, Seattle, WA, USA
| | - Hye Kyung Lim
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Melina Casadio
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Tamar Hermesh
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Lazaro Lorenzo
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris, France. University Paris Descartes, Imagine Institute, Paris, France
| | - Lawrence W Leung
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vincent Pedergnana
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris, France. University Paris Descartes, Imagine Institute, Paris, France
| | - Bertrand Boisson
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Satoshi Okada
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA. Department of Pediatrics, Hiroshima University Graduate School of Biomedical & Health Sciences, Hiroshima, Japan
| | - Capucine Picard
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA. Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris, France. University Paris Descartes, Imagine Institute, Paris, France. Study Centre for Primary Immunodeficiencies, AP-HP, Necker Hospital, Paris, France
| | | | | | - Damien Chaussabel
- Department of Systems Immunology, Benaroya Research Institute at Virginia Mason, Seattle, WA, USA. Department of Systems Biology, Sidra Medical and Research Center, Doha, Qatar
| | - Laurent Abel
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA. Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris, France. University Paris Descartes, Imagine Institute, Paris, France
| | - Isabelle Pellier
- Pediatric Immunology, Hematology and Oncology Unit, University Hospital Centre of Angers, Angers, France. INSERM U892, CNRS U6299, Angers, France
| | - Luigi D Notarangelo
- Division of Immunology and Manton Center for Orphan Disease Research, Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Adolfo García-Sastre
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Department of Medicine, Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Christopher F Basler
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Frédéric Geissmann
- Centre for Molecular and Cellular Biology of Inflammation (CMCBI), King's College London, London SE1 1UL, UK
| | - Shen-Ying Zhang
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA. Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris, France. University Paris Descartes, Imagine Institute, Paris, France
| | - Hans-Willem Snoeck
- Columbia Center for Translational Immunology, Columbia University Medical Center, New York, NY, USA. Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Jean-Laurent Casanova
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA. Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris, France. University Paris Descartes, Imagine Institute, Paris, France. Pediatric Immuno-Hematology Unit, Necker Hospital for Sick Children, AP-HP, Paris, France. Howard Hughes Medical Institute, New York, NY, USA.
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679
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Kim ES, Sonstegard TS, da Silva MVGB, Gasbarre LC, Van Tassell CP. Genome-wide scan of gastrointestinal nematode resistance in closed Angus population selected for minimized influence of MHC. PLoS One 2015; 10:e0119380. [PMID: 25803687 PMCID: PMC4372334 DOI: 10.1371/journal.pone.0119380] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2014] [Accepted: 01/30/2015] [Indexed: 12/03/2022] Open
Abstract
Genetic markers associated with parasite indicator traits are ideal targets for study of marker assisted selection aimed at controlling infections that reduce herd use of anthelminthics. For this study, we collected gastrointestinal (GI) nematode fecal egg count (FEC) data from post-weaning animals of an Angus resource population challenged to a 26 week natural exposure on pasture. In all, data from 487 animals was collected over a 16 year period between 1992 and 2007, most of which were selected for a specific DRB1 allele to reduce the influence of potential allelic variant effects of the MHC locus. A genome-wide association study (GWAS) based on BovineSNP50 genotypes revealed six genomic regions located on bovine Chromosomes 3, 5, 8, 15 and 27; which were significantly associated (-log10 p=4.3) with Box-Cox transformed mean FEC (BC-MFEC). DAVID analysis of the genes within the significant genomic regions suggested a correlation between our results and annotation for genes involved in inflammatory response to infection. Furthermore, ROH and selection signature analyses provided strong evidence that the genomic regions associated BC-MFEC have not been affected by local autozygosity or recent experimental selection. These findings provide useful information for parasite resistance prediction for young grazing cattle and suggest new candidate gene targets for development of disease-modifying therapies or future studies of host response to GI parasite infection.
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Affiliation(s)
- Eui-Soo Kim
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
| | - Tad S. Sonstegard
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
- * E-mail:
| | | | - Louis C. Gasbarre
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
| | - Curtis P. Van Tassell
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
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680
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Measuring individual inbreeding in the age of genomics: marker-based measures are better than pedigrees. Heredity (Edinb) 2015; 115:63-72. [PMID: 26059970 DOI: 10.1038/hdy.2015.17] [Citation(s) in RCA: 192] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2014] [Revised: 02/03/2015] [Accepted: 02/13/2015] [Indexed: 12/15/2022] Open
Abstract
Inbreeding (mating between relatives) can dramatically reduce the fitness of offspring by causing parts of the genome to be identical by descent. Thus, measuring individual inbreeding is crucial for ecology, evolution and conservation biology. We used computer simulations to test whether the realized proportion of the genome that is identical by descent (IBDG) is predicted better by the pedigree inbreeding coefficient (FP) or by genomic (marker-based) measures of inbreeding. Genomic estimators of IBDG included the increase in individual homozygosity relative to mean Hardy-Weinberg expected homozygosity (FH), and two measures (FROH and FE) that use mapped genetic markers to estimate IBDG. IBDG was more strongly correlated with FH, FE and FROH than with FP across a broad range of simulated scenarios when thousands of SNPs were used. For example, IBDG was more strongly correlated with FROH, FH and FE (estimated with ⩾10 000 SNPs) than with FP (estimated with 20 generations of complete pedigree) in populations with a recent reduction in the effective populations size (from Ne=500 to Ne=75). FROH, FH and FE generally explained >90% of the variance in IBDG (among individuals) when 35 K or more SNPs were used. FP explained <80% of the variation in IBDG on average in all simulated scenarios, even when pedigrees included 20 generations. Our results demonstrate that IBDG can be more precisely estimated with large numbers of genetic markers than with pedigrees. We encourage researchers to adopt genomic marker-based measures of IBDG as thousands of loci can now be genotyped in any species.
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681
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Yingjun X, Yi Z, Jianzhu W, Yunxia S, Yongzhen C, Liangying Z, Xiangyi J, Qun F. Prader-Willi syndrome with a long-contiguous stretch of homozygosity not covering the critical region. J Child Neurol 2015; 30:371-7. [PMID: 24859787 DOI: 10.1177/0883073814535492] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Prader-Willi syndrome is a common and complex disorder affecting multiple systems. Its main manifestations are infantile hypotonia with a poor sucking reflex, a characteristic facial appearance, mild mental retardation, hypogonadism and early-onset obesity. Prader-Willi syndrome is due to the absence of paternally expressed imprinted genes at 15q11.2-13, and 3 main mechanisms are known to be involved in its pathogenesis: paternal microdeletions, maternal uniparental disomy events, and imprinting defects. DNA methylation analysis can detect almost all individuals with Prader-Willi syndrome but is unable to distinguish between the molecular classes of the disease. Thus, additional methods are necessary to identify the molecular classes. Here, we employed chromosomal microarray analysis-single nucleotide polymorphism for diagnosis and detected a long-contiguous stretch of homozygosity on chromosome 15, which is highly predictive of maternal uniparental disomy on chromosome 15. Other methods, including fluorescence in situ hybridization, chromosomal microarray analysis-comparative genomic hybridization, genotyping and family linkage analysis, were performed for further validation. In conclusion, our study highlights the use of long-contiguous stretch of homozygosity detection for the diagnosis of Prader-Willi syndrome.
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Affiliation(s)
- Xie Yingjun
- Fetal Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Zhou Yi
- Fetal Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Wu Jianzhu
- Fetal Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Sun Yunxia
- Department of Neonatology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Chen Yongzhen
- Fetal Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Zhong Liangying
- Department of Laboratory Medicine, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Jing Xiangyi
- Department of Medical Genetics, Zhongshan School of Medicine and Center for Genome Research, Sun Yat-Sen University, Guangzhou, China
| | - Fang Qun
- Fetal Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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682
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Zavarez LB, Utsunomiya YT, Carmo AS, Neves HHR, Carvalheiro R, Ferenčaković M, Pérez O'Brien AM, Curik I, Cole JB, Van Tassell CP, da Silva MVGB, Sonstegard TS, Sölkner J, Garcia JF. Assessment of autozygosity in Nellore cows (Bos indicus) through high-density SNP genotypes. Front Genet 2015; 6:5. [PMID: 25688258 PMCID: PMC4310349 DOI: 10.3389/fgene.2015.00005] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2014] [Accepted: 01/07/2015] [Indexed: 11/18/2022] Open
Abstract
The use of relatively low numbers of sires in cattle breeding programs, particularly on those for carcass and weight traits in Nellore beef cattle (Bos indicus) in Brazil, has always raised concerns about inbreeding, which affects conservation of genetic resources and sustainability of this breed. Here, we investigated the distribution of autozygosity levels based on runs of homozygosity (ROH) in a sample of 1,278 Nellore cows, genotyped for over 777,000 SNPs. We found ROH segments larger than 10 Mb in over 70% of the samples, representing signatures most likely related to the recent massive use of few sires. However, the average genome coverage by ROH (>1 Mb) was lower than previously reported for other cattle breeds (4.58%). In spite of 99.98% of the SNPs being included within a ROH in at least one individual, only 19.37% of the markers were encompassed by common ROH, suggesting that the ongoing selection for weight, carcass and reproductive traits in this population is too recent to have produced selection signatures in the form of ROH. Three short-range highly prevalent ROH autosomal hotspots (occurring in over 50% of the samples) were observed, indicating candidate regions most likely under selection since before the foundation of Brazilian Nellore cattle. The putative signatures of selection on chromosomes 4, 7, and 12 may be involved in resistance to infectious diseases and fertility, and should be subject of future investigation.
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Affiliation(s)
- Ludmilla B Zavarez
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista Jaboticabal, São Paulo, Brazil
| | - Yuri T Utsunomiya
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista Jaboticabal, São Paulo, Brazil
| | - Adriana S Carmo
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista Jaboticabal, São Paulo, Brazil
| | - Haroldo H R Neves
- GenSys Consultores Associados Porto Alegre, Rio Grande do Sul, Brazil ; Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista Jaboticabal, São Paulo, Brazil
| | - Roberto Carvalheiro
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista Jaboticabal, São Paulo, Brazil
| | - Maja Ferenčaković
- Department of Animal Science, Faculty of Agriculture, University of Zagreb Zagreb, Croatia
| | - Ana M Pérez O'Brien
- Division of Livestock Sciences, Department of Sustainable Agricultural Systems, BOKU - University of Natural Resources and Life Sciences Vienna, Austria
| | - Ino Curik
- Department of Animal Science, Faculty of Agriculture, University of Zagreb Zagreb, Croatia
| | - John B Cole
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service Beltsville, MD, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service Beltsville, MD, USA
| | - Marcos V G B da Silva
- Bioinformatics and Animal Genomics Laboratory, Embrapa Dairy Cattle Juiz de Fora, Minas Gerais, Brazil
| | - Tad S Sonstegard
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service Beltsville, MD, USA
| | - Johann Sölkner
- Division of Livestock Sciences, Department of Sustainable Agricultural Systems, BOKU - University of Natural Resources and Life Sciences Vienna, Austria
| | - José F Garcia
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista Jaboticabal, São Paulo, Brazil ; Laboratório de Bioquímica e Biologia Molecular Animal, Departamento de Apoio, Produção e Saúde Animal, Faculdade de Medicina Veterinária de Araçatuba, UNESP - Univ Estadual Paulista Araçatuba, São Paulo, Brazil
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683
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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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684
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Saura M, Fernández A, Varona L, Fernández AI, de Cara MÁR, Barragán C, Villanueva B. Detecting inbreeding depression for reproductive traits in Iberian pigs using genome-wide data. Genet Sel Evol 2015; 47:1. [PMID: 25595431 PMCID: PMC4297446 DOI: 10.1186/s12711-014-0081-5] [Citation(s) in RCA: 115] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2014] [Accepted: 12/05/2014] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND The current availability of genotypes for very large numbers of single nucleotide polymorphisms (SNPs) is leading to more accurate estimates of inbreeding coefficients and more detailed approaches for detecting inbreeding depression. In the present study, genome-wide information was used to detect inbreeding depression for two reproductive traits (total number of piglets born and number of piglets born alive) in an ancient strain of Iberian pigs (the Guadyerbas strain) that is currently under serious danger of extinction. METHODS A total of 109 sows with phenotypic records were genotyped with the PorcineSNP60 BeadChip v1. Inbreeding depression was estimated using a bivariate animal model in which the inbreeding coefficient was included as a covariate. We used two different measures of genomic inbreeding to perform the analyses: inbreeding estimated on a SNP-by-SNP basis and inbreeding estimated from runs of homozygosity. We also performed the analyses using pedigree-based inbreeding. RESULTS Significant inbreeding depression was detected for both traits using all three measures of inbreeding. Genome-wide information allowed us to identify one region on chromosome 13 associated with inbreeding depression. This region spans from 27 to 54 Mb and overlaps with a previously detected quantitative trait locus and includes the inter-alpha-trypsin inhibitor gene cluster that is involved with embryo implantation. CONCLUSIONS Our results highlight the value of high-density SNP genotyping for providing new insights on where genes causing inbreeding depression are located in the genome. Genomic measures of inbreeding obtained on a SNP-by-SNP basis or those based on the presence/absence of runs of homozygosity represent a suitable alternative to pedigree-based measures to detect inbreeding depression, and a useful tool for mapping studies. To our knowledge, this is the first study in domesticated animals using the SNP-by-SNP inbreeding coefficient to map specific regions within chromosomes associated with inbreeding depression.
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Affiliation(s)
- María Saura
- />Departamento de Mejora Genética Animal, INIA, Carretera de la Coruña km 7.5, 28040 Madrid, Spain
| | - Almudena Fernández
- />Departamento de Mejora Genética Animal, INIA, Carretera de la Coruña km 7.5, 28040 Madrid, Spain
| | - Luis Varona
- />Unidad de Genética Cuantitativa y Mejora Animal, Facultad de Veterinaria, Universidad de Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain
| | - Ana I Fernández
- />Departamento de Mejora Genética Animal, INIA, Carretera de la Coruña km 7.5, 28040 Madrid, Spain
| | - Maria Ángeles R de Cara
- />Laboratoire d’Eco-anthropologie et Ethnobiologie, UMR 7206 CNRS/MNHN/Université Paris 7, Muséum National d’Histoire Naturelle, CP 139, 57 rue Cuvier, F-75231 Paris, France
| | - Carmen Barragán
- />Departamento de Mejora Genética Animal, INIA, Carretera de la Coruña km 7.5, 28040 Madrid, Spain
| | - Beatriz Villanueva
- />Departamento de Mejora Genética Animal, INIA, Carretera de la Coruña km 7.5, 28040 Madrid, Spain
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685
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Knief U, Hemmrich-Stanisak G, Wittig M, Franke A, Griffith SC, Kempenaers B, Forstmeier W. Quantifying realized inbreeding in wild and captive animal populations. Heredity (Edinb) 2015; 114:397-403. [PMID: 25585923 DOI: 10.1038/hdy.2014.116] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2014] [Revised: 11/10/2014] [Accepted: 11/14/2014] [Indexed: 12/19/2022] Open
Abstract
Most molecular measures of inbreeding do not measure inbreeding at the scale that is most relevant for understanding inbreeding depression-namely the proportion of the genome that is identical-by-descent (IBD). The inbreeding coefficient FPed obtained from pedigrees is a valuable estimator of IBD, but pedigrees are not always available, and cannot capture inbreeding loops that reach back in time further than the pedigree. We here propose a molecular approach to quantify the realized proportion of the genome that is IBD (propIBD), and we apply this method to a wild and a captive population of zebra finches (Taeniopygia guttata). In each of 948 wild and 1057 captive individuals we analyzed available single-nucleotide polymorphism (SNP) data (260 SNPs) spread over four different genomic regions in each population. This allowed us to determine whether any of these four regions was completely homozygous within an individual, which indicates IBD with high confidence. In the highly nomadic wild population, we did not find a single case of IBD, implying that inbreeding must be extremely rare (propIBD=0-0.00094, 95% CI). In the captive population, a five-generation pedigree strongly underestimated the average amount of realized inbreeding (FPed=0.013<propIBD=0.064), as expected given that pedigree founders were already related. We suggest that this SNP-based technique is generally useful for quantifying inbreeding at the individual or population level, and we show analytically that it can capture inbreeding loops that reach back up to a few hundred generations.
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Affiliation(s)
- U Knief
- Department of Behavioural Ecology and Evolutionary Genetics, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - G Hemmrich-Stanisak
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - M Wittig
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - A Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - S C Griffith
- 1] Department of Biological Sciences, Macquarie University, Sydney, New South Wales, Australia [2] School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - B Kempenaers
- Department of Behavioural Ecology and Evolutionary Genetics, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - W Forstmeier
- Department of Behavioural Ecology and Evolutionary Genetics, Max Planck Institute for Ornithology, Seewiesen, Germany
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686
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Jalkh N, Sahbatou M, Chouery E, Megarbane A, Leutenegger AL, Serre JL. Genome-wide inbreeding estimation within Lebanese communities using SNP arrays. Eur J Hum Genet 2014; 23:1364-9. [PMID: 25424710 DOI: 10.1038/ejhg.2014.246] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2014] [Revised: 08/29/2014] [Accepted: 09/19/2014] [Indexed: 12/14/2022] Open
Abstract
Consanguineous marriages have been widely practiced in several global communities with varying rates depending on religion, culture, and geography. In consanguineous marriages, parents pass to their children autozygous segments known as homozygous by descent segments. In this study, single-nucleotide polymorphisms were analyzed in 165 unrelated Lebanese people from Greek Orthodox, Maronite, Shiite and Sunni communities. Runs of homozygosity, total inbreeding levels, remote consanguinity, and population admixture and structure were estimated. The inbreeding coefficient value was estimated to be 1.61% in offspring of unrelated parents over three generations and 8.33% in offspring of first cousins. From these values, remote consanguinity values, resulting from genetic drift or recurrent consanguineous unions, were estimated in offspring of unrelated and first-cousin parents to be 0.61 and 1.2%, respectively. This remote consanguinity value suggests that for any unrelated marriages in Lebanon, the mates could be related as third cousins or as second cousins once removed. Under the assumption that 25% of marriages occur between first cousins, the mean inbreeding value of 2.3% may explain the increased incidence of recessive disease in offspring. Our analysis reveals a common ancestral population in the four Lebanese communities we studied.
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Affiliation(s)
- Nadine Jalkh
- Unité de Génétique Médicale et Laboratoire associé INSERM à l'Unité UMR_S910, Faculté de Médecine, Université Saint-Joseph, Beirut, Lebanon.,EA 2493 « pathologie cellulaire & génétique, de la conception à la naissance », Université de Versailles-Saint Quentin en Yvelines, Yvelines, France
| | | | - Eliane Chouery
- Unité de Génétique Médicale et Laboratoire associé INSERM à l'Unité UMR_S910, Faculté de Médecine, Université Saint-Joseph, Beirut, Lebanon
| | - André Megarbane
- Unité de Génétique Médicale et Laboratoire associé INSERM à l'Unité UMR_S910, Faculté de Médecine, Université Saint-Joseph, Beirut, Lebanon
| | | | - Jean-Louis Serre
- EA 2493 « pathologie cellulaire & génétique, de la conception à la naissance », Université de Versailles-Saint Quentin en Yvelines, Yvelines, France
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687
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Álvarez G, Ceballos FC, Berra TM. Darwin was right: inbreeding depression on male fertility in the Darwin family. Biol J Linn Soc Lond 2014. [DOI: 10.1111/bij.12433] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Affiliation(s)
- Gonzalo Álvarez
- Department of Genetics; Faculty of Biology; University of Santiago de Compostela; 15782 Santiago de Compostela Spain
| | - Francisco C. Ceballos
- Department of Genetics; Faculty of Biology; University of Santiago de Compostela; 15782 Santiago de Compostela Spain
| | - Tim M. Berra
- Department of Evolution; Ecology and Organismal Biology; The Ohio State University; 1760 University Dr.; Mansfield OH 44906 USA
- Research Institute for the Environment and Livelihoods; Charles Darwin University; Darwin NT Australia
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688
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Bonner JD, Fisher R, Klein J, Lu Q, Wilch E, Friderici KH, Elfenbein JL, Schutte DL, Schutte BC. Pedigree structure and kinship measurements of a mid-Michigan community: a new North American population isolate identified. Hum Biol 2014; 86:59-68. [PMID: 25401987 DOI: 10.3378/027.086.0103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/09/2014] [Indexed: 11/05/2022]
Abstract
Previous studies identified a cluster of individuals with an autosomal recessive form of deafness that reside in a small region of mid-Michigan. We hypothesized that affected members from this community descend from a defined founder population. Using public records and personal interviews, we constructed a genealogical database that includes the affected individuals and their extended families as descendants of 461 settlers who emigrated from the Eifel region of Germany between 1836 and 1875. The genealogical database represents a 13-generation pedigree that includes 27,747 descendants of these settlers. Among these descendants, 13,784 are presumed living. Many of the extant descendants reside in a 90-square-mile area, and 52% were born to parents who share at least one common ancestor. Among those born to related parents, the median kinship coefficient is 3.7 × 10(-3). While the pedigree contains 2,510 founders, 344 of the 461 settlers accounted for 67% of the genome in the extant population. These data suggest that we identified a new population isolate in North America and that, as demonstrated for congenital hearing loss, this rural mid-Michigan community is a new resource to discover heritable factors that contribute to common health-related conditions.
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Affiliation(s)
- Joseph D Bonner
- Department of Comparative Medicine and Integrative Biology, East Lansing, Michigan, USA
| | - Rachel Fisher
- Department of Pediatrics and Human Development, East Lansing, Michigan, USA
| | | | - Qing Lu
- Department of Epidemiology and Biostatistics, East Lansing, Michigan, USA
| | - Ellen Wilch
- Department of Microbiology and Molecular Genetics, East Lansing, Michigan, USA
| | - Karen H Friderici
- Department of Comparative Medicine and Integrative Biology, East Lansing, Michigan, USA; Department of Pediatrics and Human Development, East Lansing, Michigan, USA; Department of Microbiology and Molecular Genetics, East Lansing, Michigan, USA
| | - Jill L Elfenbein
- Department of Communicative Sciences and Disorders, Michigan State University, East Lansing, Michigan, USA, now deceased
| | - Debra L Schutte
- College of Nursing, Wayne State University, Detroit, Michigan, USA
| | - Brian C Schutte
- Department of Comparative Medicine and Integrative Biology, East Lansing, Michigan, USA; Department of Pediatrics and Human Development, East Lansing, Michigan, USA; Department of Microbiology and Molecular Genetics, East Lansing, Michigan, USA
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689
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Binzer S, Imrell K, Binzer M, Kyvik KO, Hillert J, Stenager E. High inbreeding in the Faroe Islands does not appear to constitute a risk factor for multiple sclerosis. Mult Scler 2014; 21:996-1002. [DOI: 10.1177/1352458514557305] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2014] [Accepted: 10/06/2014] [Indexed: 11/16/2022]
Abstract
Background: Large population-based genome-wide association studies have identified several multiple sclerosis (MS) genetic risk variants, but the existing missing heritability warrants different strategies. Isolated populations offer an alternative way of searching for rare genetic variants and evaluating the possible role of consanguinity in the development of MS. Studies of consanguinity and MS risk have yielded conflicting results. Objectives: In this study we investigated the role of consanguinity on MS risk in the relatively isolated Faroe Islands, which have a presumed high level of inbreeding. Methods: A total of 29 cases and 28 matched controls were genotyped and assessed for inbreeding coefficients, number of runs of homozygosity (ROH) at different lengths and observed number of homozygotes as measures of relatedness. Parametric and non-parametric statistical models were applied. Results: Both cases and controls exhibited considerable relatedness demonstrated by very high inbreeding coefficients, large number of observed homozygotes and many long ROH. However, apart from the number of ROH ≥ 2.5 mega base pairs, no significant differences between the two groups were observed. Conclusions: Overall, no significant difference between cases and controls were found, indicating that consanguinity in itself does not appear to be an important risk factor for MS in the population of the Faroe Islands.
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Affiliation(s)
- S Binzer
- Institute of Regional Health Services Research, University of Southern Denmark, Denmark/MS Clinic of Southern Jutland (Sønderborg, Esbjerg, Vejle), Department of Neurology, Denmark/Torshavn National Hospital, Torshavn, Faroe Islands Odense Patient data explorative network (OPEN)
| | - K Imrell
- Karolinska Institute, Clinical Neuroscience, Division of Neurology, Department of Clinical Neuroscience, Sweden
| | - M Binzer
- Institute of Regional Health Services Research, University of Southern Denmark, Denmark
| | - K. O Kyvik
- Institute of Regional Health Services Research, University of Southern Denmark, Denmark/Odense Patient data Explorative Network (OPEN), Odense University Hospital, Denmark
| | - J Hillert
- Karolinska Institute, Clinical Neuroscience, Division of Neurology, Department of Clinical Neuroscience, Sweden
| | - E Stenager
- Institute of Regional Health Services Research, University of Southern Denmark, Denmark/MS Clinic of Southern Jutland (Sønderborg, Esbjerg, Vejle), Department of Neurology, Denmark
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690
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Panoutsopoulou K, Hatzikotoulas K, Xifara DK, Colonna V, Farmaki AE, Ritchie GRS, Southam L, Gilly A, Tachmazidou I, Fatumo S, Matchan A, Rayner NW, Ntalla I, Mezzavilla M, Chen Y, Kiagiadaki C, Zengini E, Mamakou V, Athanasiadis A, Giannakopoulou M, Kariakli VE, Nsubuga RN, Karabarinde A, Sandhu M, McVean G, Tyler-Smith C, Tsafantakis E, Karaleftheri M, Xue Y, Dedoussis G, Zeggini E. Genetic characterization of Greek population isolates reveals strong genetic drift at missense and trait-associated variants. Nat Commun 2014; 5:5345. [PMID: 25373335 PMCID: PMC4242463 DOI: 10.1038/ncomms6345] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2014] [Accepted: 09/22/2014] [Indexed: 11/09/2022] Open
Abstract
Isolated populations are emerging as a powerful study design in the search for low-frequency and rare variant associations with complex phenotypes. Here we genotype 2,296 samples from two isolated Greek populations, the Pomak villages (HELIC-Pomak) in the North of Greece and the Mylopotamos villages (HELIC-MANOLIS) in Crete. We compare their genomic characteristics to the general Greek population and establish them as genetic isolates. In the MANOLIS cohort, we observe an enrichment of missense variants among the variants that have drifted up in frequency by more than fivefold. In the Pomak cohort, we find novel associations at variants on chr11p15.4 showing large allele frequency increases (from 0.2% in the general Greek population to 4.6% in the isolate) with haematological traits, for example, with mean corpuscular volume (rs7116019, P=2.3 × 10(-26)). We replicate this association in a second set of Pomak samples (combined P=2.0 × 10(-36)). We demonstrate significant power gains in detecting medical trait associations.
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Affiliation(s)
| | | | - Dionysia Kiara Xifara
- 1] Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK [2] Department of Statistics, University of Oxford, Oxford OX1 3TG, UK
| | - Vincenza Colonna
- Institute of Genetics and Biophysics 'A. Buzzati-Traverso', National Research Council (CNR), Naples 80131, Italy
| | - Aliki-Eleni Farmaki
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens 17671, Greece
| | - Graham R S Ritchie
- 1] Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK [2] European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK
| | - Lorraine Southam
- 1] Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK [2] Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Arthur Gilly
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK
| | - Ioanna Tachmazidou
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK
| | - Segun Fatumo
- 1] Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK [2] H3Africa Bioinformatics Network (H3ABioNet) Node, National Biotechnology Development Agency (NABDA), Federal Ministry of Science and Technology (FMST), Abuja 900107, Nigeria [3] International Health Research Group, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8NR, UK
| | - Angela Matchan
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK
| | - Nigel W Rayner
- 1] Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK [2] Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK [3] Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK
| | - Ioanna Ntalla
- 1] Department of Nutrition and Dietetics, Harokopio University of Athens, Athens 17671, Greece [2] Department of Health Sciences, University of Leicester, Leicester LE1 7RH, UK
| | - Massimo Mezzavilla
- 1] Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK [2] Division of Medical Genetics, Department of Reproductive Sciences and Development, IRCCS-Burlo Garofolo, University of Trieste, Trieste 34137, Italy
| | - Yuan Chen
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK
| | | | - Eleni Zengini
- 1] Dromokaiteio Psychiatric Hospital of Athens, Chaidari, Athens 12461, Greece [2] Department of Human Metabolism, University of Sheffield, Sheffield S10 2TN, UK
| | - Vasiliki Mamakou
- 1] Dromokaiteio Psychiatric Hospital of Athens, Chaidari, Athens 12461, Greece [2] School of Medicine, National and Kapodistrian University of Athens, Goudi, Athens 11527, Greece
| | | | - Margarita Giannakopoulou
- School of Health Sciences, Faculty of Nursing, National and Kapodistrian University of Athens, Goudi, Athens 11527, Greece
| | | | - Rebecca N Nsubuga
- Medical Research Council/Uganda Virus Research Institute, Uganda Research Unit on AIDS, PO Box 49, Entebbe, Uganda
| | - Alex Karabarinde
- Medical Research Council/Uganda Virus Research Institute, Uganda Research Unit on AIDS, PO Box 49, Entebbe, Uganda
| | - Manjinder Sandhu
- 1] Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK [2] International Health Research Group, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8NR, UK
| | - Gil McVean
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Chris Tyler-Smith
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK
| | | | | | - Yali Xue
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK
| | - George Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens 17671, Greece
| | - Eleftheria Zeggini
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1HH, UK
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691
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Sung YJ, Korthauer KD, Swartz MD, Engelman CD. Methods for collapsing multiple rare variants in whole-genome sequence data. Genet Epidemiol 2014; 38 Suppl 1:S13-20. [PMID: 25112183 DOI: 10.1002/gepi.21820] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Genetic Analysis Workshop 18 provided whole-genome sequence data in a pedigree-based sample and longitudinal phenotype data for hypertension and related traits, presenting an excellent opportunity for evaluating analysis choices. We summarize the nine contributions to the working group on collapsing methods, which evaluated various approaches for the analysis of multiple rare variants. One contributor defined a variant prioritization scheme, whereas the remaining eight contributors evaluated statistical methods for association analysis. Six contributors chose the gene as the genomic region for collapsing variants, whereas three contributors chose nonoverlapping sliding windows across the entire genome. Statistical methods spanned most of the published methods, including well-established burden tests, variance-components-type tests, and recently developed hybrid approaches. Lesser known methods, such as functional principal components analysis, higher criticism, and homozygosity association, and some newly introduced methods were also used. We found that performance of these methods depended on the characteristics of the genomic region, such as effect size and direction of variants under consideration. Except for MAP4 and FLT3, the performance of all statistical methods to identify rare casual variants was disappointingly poor, providing overall power almost identical to the type I error. This poor performance may have arisen from a combination of (1) small sample size, (2) small effects of most of the causal variants, explaining a small fraction of variance, (3) use of incomplete annotation information, and (4) linkage disequilibrium between causal variants in a gene and noncausal variants in nearby genes. Our findings demonstrate challenges in analyzing rare variants identified from sequence data.
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Affiliation(s)
- Yun Ju Sung
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
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692
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Lamb MJE, Byrne CD, Wilson JF, Wild SH. Evaluation of bioelectrical impedance analysis for identifying overweight individuals at increased cardiometabolic risk: a cross-sectional study. PLoS One 2014; 9:e106134. [PMID: 25243464 PMCID: PMC4171089 DOI: 10.1371/journal.pone.0106134] [Citation(s) in RCA: 10] [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: 10/30/2013] [Accepted: 08/03/2014] [Indexed: 01/10/2023] Open
Abstract
OBJECTIVE To investigate whether bioelectrical impedance analysis could be used to identify overweight individuals at increased cardiometabolic risk, defined as the presence of metabolic syndrome and/or diabetes. DESIGN AND METHODS Cross-sectional study of a Scottish population including 1210 women and 788 men. The diagnostic performance of thresholds of percentage body fat measured by bioelectrical impedance analysis to identify people at increased cardiometabolic risk was assessed using receiver-operating characteristic curves. Odds ratios for increased cardiometabolic risk in body mass index categories associated with values above compared to below sex-specific percentage body fat thresholds with optimal diagnostic performance were calculated using multivariable logistic regression analyses. The validity of bioelectrical impedance analysis to measure percentage body fat in this population was tested by examining agreement between bioelectrical impedance analysis and dual-energy X-ray absorptiometry in a subgroup of individuals. RESULTS Participants were aged 16-91 years and the optimal bioelectrical impedance analysis cut-points for percentage body fat for identifying people at increased cardiometabolic risk were 25.9% for men and 37.1% for women. Stratifying by these percentage body fat cut-points, the prevalence of increased cardiometabolic risk was 48% and 38% above the threshold and 24% and 19% below these thresholds for men and women, respectively. By comparison, stratifying by percentage body fat category had little impact on identifying increased cardiometabolic risk in normal weight and obese individuals. Fully adjusted odds ratios of being at increased cardiometabolic risk among overweight people with percentage body fat ≥ 25.9/37.1% compared with percentage body fat <25.9/37.1% as a reference were 1.93 (95% confidence interval: 1.20-3.10) for men and 1.79 (1.10-2.92) for women. CONCLUSION Percentage body fat measured using bioelectrical impedance analysis above a sex-specific threshold could be used in overweight people to identify individuals at increased cardiometabolic risk, who could benefit from risk factor management.
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Affiliation(s)
- Maxine J. E. Lamb
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Christopher D. Byrne
- Nutrition and Metabolism, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
- Southampton National Institute for Health Research Biomedical Research Centre, University Hospital Southampton, Southampton, United Kingdom
| | - James F. Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
- MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Sarah H. Wild
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
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693
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Gao X, Gotway G, Rathjen K, Johnston C, Sparagana S, Wise CA. Genomic Analyses of Patients With Unexplained Early-Onset Scoliosis. Spine Deform 2014; 2:324-332. [PMID: 27927329 PMCID: PMC4228381 DOI: 10.1016/j.jspd.2014.04.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2013] [Revised: 03/17/2014] [Accepted: 04/21/2014] [Indexed: 12/20/2022]
Abstract
STUDY DESIGN To test for rare genetic mutations, a cohort of patients with unexplained early-onset scoliosis (EOS) was screened using high-density microarray genotyping. A cohort of patients with adolescent idiopathic scoliosis (AIS) was similarly screened and the results were compared. SUMMARY OF BACKGROUND DATA Patients with scoliosis in infancy or early childhood (EOS) are at high risk for progressive deformity and associated problems including respiratory compromise. Early-onset scoliosis is frequently associated with genetic disorders but many patients present with nonspecific clinical features and without an associated diagnosis. The authors hypothesized that EOS in these patients may be caused by rare genetic mutations detectable by next-generation genomic methods. METHODS The researchers identified 24 patients with unexplained EOS from pediatric orthopedic clinics. They genotyped them, along with 39 connecting family members, using the Illumina OmniExpress-12, version 1.0 beadchip. Resulting genotypes were analyzed for chromosomal changes, specifically copy number variation and absence of heterozygosity. They screened 482 adolescent idiopathic scoliosis (AIS) patients and 744 healthy controls, who were similarly genotyped with the same beadchip, for chromosomal changes identified in the EOS cohort. RESULTS Copy number variation and absence of heterozygosity analyses revealed a genetic diagnosis of chromosome 15q24 microdeletion syndrome in 1 patient and maternal uniparental disomy of chromosome 14 in a second one. Prior genetic testing and clinical evaluations had been negative in both cases. A large novel chromosome 10 deletion was likely causal in a third EOS patient. These mutations identified in the EOS patients were absent in AIS patients and controls, and thus were not associated with AIS or found in asymptomatic individuals. CONCLUSIONS These data underscore the usefulness of updated genetic evaluations including high-density microarray-based genotyping and other next-generation methods in patients with unexplained EOS, even when prior genetic studies were negative. These data also suggest the intriguing possibility that other mutations detectable by whole genome sequencing, as well as epigenetic effects, await discovery in the EOS population.
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Affiliation(s)
- Xiaochong Gao
- Sarah M. and Charles E. Seay Center for Musculoskeletal Research, Texas Scottish Rite Hospital for Children. Dallas, TX
| | - Garrett Gotway
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX
| | - Karl Rathjen
- Department of Orthopedic Surgery, Texas Scottish Rite Hospital for Children. Dallas, TX,Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX
| | - Charles Johnston
- Department of Orthopedic Surgery, Texas Scottish Rite Hospital for Children. Dallas, TX,Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX
| | - Steven Sparagana
- Department of Neurology, Texas Scottish Rite Hospital for Children. Dallas, TX,Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, TX
| | - Carol A. Wise
- Sarah M. and Charles E. Seay Center for Musculoskeletal Research, Texas Scottish Rite Hospital for Children. Dallas, TX,Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX,McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX,To whom correspondence should be directed. Telephone: 214-559-7861 Fax: 214-559-7872
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694
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Melhem NM, Lu C, Dresbold C, Middleton FA, Klei L, Wood S, Faraone SV, Vinogradov S, Tiobech J, Yano V, Roeder K, Byerley W, Myles-Worsley M, Devlin B. Characterizing runs of homozygosity and their impact on risk for psychosis in a population isolate. Am J Med Genet B Neuropsychiatr Genet 2014; 165B:521-30. [PMID: 24980794 PMCID: PMC5058445 DOI: 10.1002/ajmg.b.32255] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2014] [Accepted: 06/04/2014] [Indexed: 11/12/2022]
Abstract
An increased abundance of runs of homozygosity (ROH) has been associated with risk for various diseases, including schizophrenia. Here we investigate the characteristics of ROH in Palau, an Oceanic population, evaluating whether these characteristics are related to risk for psychotic disorders and the nature of this association. To accomplish these aims we evaluate a sample of 203 cases with schizophrenia and related psychotic disorders-representing almost complete ascertainment of affected individuals in the population-and contrast their ROH to that of 125 subjects chosen to function as controls. While Palauan diagnosed with psychotic disorders tend to have slightly more ROH regions than controls, the distinguishing features are that they have longer ROH regions, greater total length of ROH, and their ROH tends to co-occur more often at the same locus. The nature of the sample allows us to investigate whether rare, highly penetrant recessive variants generate such case-control differences in ROH. Neither rare, highly penetrant recessive variants nor individual common variants of large effect account for a substantial proportion of risk for psychosis in Palau. These results suggest a more nuanced model for risk is required to explain patterns of ROH for this population.
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Affiliation(s)
- Nadine M. Melhem
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Cong Lu
- Department of Statistics, Carnegie Mellon University, Pittsburgh, PA
| | - Cara Dresbold
- Department of Human Genetics, University of Pittsburgh
| | | | | | - Shawn Wood
- University of Pittsburgh Medical Center, Pittsburgh, PA
| | - Stephen V Faraone
- Department of Psychiatry, SUNY Upstate Medical University; Syracuse NY
| | | | | | - Victor Yano
- Palauan Ministry of Health, Republic of Palau
| | - Kathryn Roeder
- Department of Statistics, Carnegie Mellon University, Pittsburgh, PA
| | - William Byerley
- Department of Psychiatry, University of California San Francisco
| | | | - Bernie Devlin
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA
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695
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Regions of homozygosity identified by oligonucleotide SNP arrays: evaluating the incidence and clinical utility. Eur J Hum Genet 2014; 23:663-71. [PMID: 25118026 DOI: 10.1038/ejhg.2014.153] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2013] [Revised: 06/03/2014] [Accepted: 07/10/2014] [Indexed: 11/09/2022] Open
Abstract
Copy neutral segments with allelic homozygosity, also known as regions of homozygosity (ROHs), are frequently identified in cases interrogated by oligonucleotide single-nucleotide polymorphism (oligo-SNP) microarrays. Presence of ROHs may be because of parental relatedness, chromosomal recombination or rearrangements and provides important clues regarding ancestral homozygosity, consanguinity or uniparental disomy. In this study of 14 574 consecutive cases, 832 (6%) were found to harbor one or more ROHs over 10 Mb, of which 651 cases (78%) had multiple ROHs, likely because of identity by descent (IBD), and 181 cases (22%) with ROHs involving a single chromosome. Parental relatedness was predicted to be first degree or closer in 5%, second in 9% and third in 19%. Of the 181 cases, 19 had ROHs for a whole chromosome revealing uniparental isodisomy (isoUPD). In all, 25 cases had significant ROHs involving a single chromosome; 5 cases were molecularly confirmed to have a mixed iso- and heteroUPD15 and 1 case each with segmental UPD9pat and segmental UPD22mat; 17 cases were suspected to have a mixed iso- and heteroUPD including 2 cases with small supernumerary marker and 2 cases with mosaic trisomy. For chromosome 15, 12 (92%) of 13 molecularly studied cases had either Prader-Willi or Angelman syndrome. Autosomal recessive disorders were confirmed in seven of nine cases from eight families because of the finding of suspected gene within a ROH. This study demonstrates that ROHs are much more frequent than previously recognized and often reflect parental relatedness, ascertain autosomal recessive diseases or unravel UPD in many cases.
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696
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697
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Toro MA, Villanueva B, Fernández J. Genomics applied to management strategies in conservation programmes. Livest Sci 2014. [DOI: 10.1016/j.livsci.2014.04.020] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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698
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Senapati S, Gutierrez-Achury J, Sood A, Midha V, Szperl A, Romanos J, Zhernakova A, Franke L, Alonso S, Thelma BK, Wijmenga C, Trynka G. Evaluation of European coeliac disease risk variants in a north Indian population. Eur J Hum Genet 2014; 23:530-5. [PMID: 25052311 PMCID: PMC4666579 DOI: 10.1038/ejhg.2014.137] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2013] [Revised: 06/10/2014] [Accepted: 06/18/2014] [Indexed: 01/06/2023] Open
Abstract
Studies in European populations have contributed to a better understanding of the genetics of complex diseases, for example, in coeliac disease (CeD), studies of over 23 000 European samples have reported association to the HLA locus and another 39 loci. However, these associations have not been evaluated in detail in other ethnicities. We sought to better understand how disease-associated loci that have been mapped in Europeans translate to a disease risk for a population with a different ethnic background. We therefore performed a validation of European risk loci for CeD in 497 cases and 736 controls of north Indian origin. Using a dense-genotyping platform (Immunochip), we confirmed the strong association to the HLA region (rs2854275, P=8.2 × 10−49). Three loci showed suggestive association (rs4948256, P=9.3 × 10−7, rs4758538, P=8.6 × 10−5 and rs17080877, P=2.7 × 10−5). We directly replicated five previously reported European variants (P<0.05; mapping to loci harbouring FASLG/TNFSF18, SCHIP1/IL12A, PFKFB3/PRKCQ, ZMIZ1 and ICOSLG). Using a transferability test, we further confirmed association at PFKFB3/PRKCQ (rs2387397, P=2.8 × 10−4) and PTPRK/THEMIS (rs55743914, P=3.4 × 10−4). The north Indian population has a higher degree of consanguinity than Europeans and we therefore explored the role of recessively acting variants, which replicated the HLA locus (rs9271850, P=3.7 × 10−23) and suggested a role of additional four loci. To our knowledge, this is the first replication study of CeD variants in a non-European population.
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Affiliation(s)
| | - Javier Gutierrez-Achury
- Department of Genetics, University of Groningen, University Medical Hospital Groningen, Groningen, The Netherlands
| | - Ajit Sood
- Department of Gastroenterology, Dayanand Medical College and Hospital, Ludhiana, India
| | - Vandana Midha
- Department of Medicine, Dayanand Medical College and Hospital, Ludhiana, India
| | - Agata Szperl
- Department of Genetics, University of Groningen, University Medical Hospital Groningen, Groningen, The Netherlands
| | - Jihane Romanos
- Department of Genetics, University of Groningen, University Medical Hospital Groningen, Groningen, The Netherlands
| | - Alexandra Zhernakova
- Department of Genetics, University of Groningen, University Medical Hospital Groningen, Groningen, The Netherlands
| | - Lude Franke
- Department of Genetics, University of Groningen, University Medical Hospital Groningen, Groningen, The Netherlands
| | - Santos Alonso
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country, Leioa, Spain
| | - B K Thelma
- Department of Genetics, University of Delhi South Campus, New Delhi, India
| | - Cisca Wijmenga
- Department of Genetics, University of Groningen, University Medical Hospital Groningen, Groningen, The Netherlands
| | - Gosia Trynka
- Department of Genetics, University of Groningen, University Medical Hospital Groningen, Groningen, The Netherlands
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699
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Abstract
The great ape families are the species most closely related to our own, comprising chimpanzees, bonobos, gorillas, and orangutans. They live exclusively in tropical rainforests in Central Africa and the islands of Southeast Asia. Due to their close evolutionary relationship with humans, great apes share many cognitive, physiological, and morphological similarities with humans. The members of the great ape family make obvious models to facilitate the further understanding about humans' biology and history. This review will discuss how the recent addition of genome-wide data from great apes has furthered humans' understanding of these species and humanity, especially in the realm of evolutionary genetics.
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700
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Dipierri J, Rodríguez-Larralde A, Barrai I, Camelo JL, Redomero EG, Rodríguez CA, Ramallo V, Bronberg R, Alfaro E. Random inbreeding, isonymy, and population isolates in Argentina. J Community Genet 2014; 5:241-8. [PMID: 24500769 PMCID: PMC4059845 DOI: 10.1007/s12687-013-0181-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2013] [Accepted: 12/29/2013] [Indexed: 12/20/2022] Open
Abstract
Population isolates are an important tool in identifying and mapping genes of Mendelian diseases and complex traits. The geographical identification of isolates represents a priority from a genetic and health care standpoint. The purpose of this study is to analyze the spatial distribution of consanguinity by random isonymy (F ST) in Argentina and its relationship with the isolates previously identified in the country. F ST was estimated from the surname distribution of 22.6 million electors registered for the year 2001 in the 24 provinces, 5 geographical regions, and 510 departments of the country. Statistically significant spatial clustering of F ST was determined using the SaTScan V5.1 software. F ST exhibited a marked regional and departamental variation, showing the highest values towards the North and West of Argentina. The clusters of high consanguinity by random isonymy followed the same distribution. Recognized Argentinean genetic isolates are mainly localized at the north of the country, in clusters of high inbreeding. Given the availability of listings of surnames in high-capacity storage devices for different countries, estimating F ST from them can provide information on inbreeding for all levels of administrative subdivisions, to be used as a demographic variable for the identification of isolates within the country for public health purposes.
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Affiliation(s)
- José Dipierri
- Instituto de Biología de la Altura, Universidad Nacional de Jujuy, Avda. Bolivia 1661, 4600, San Salvador de Jujuy, Argentina,
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