In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 18, Heft 6, S. 670-679
Identification of individuals within pairs of monozygotic (MZ) twins remains unresolved using common forensic DNA typing technology. For some criminal cases involving MZ twins as suspects, the twins had to be released due to inability to identify which of the pair was the perpetrator. In this study, we performed a genome-wide scan on whole blood-derived DNA from four pairs of healthy phenotypically concordant MZ twins using the methylated DNA immunoprecipitation sequencing technology to identify candidate DNA methylation markers with capacity to distinguish MZ twins within a pair. We identified 38 differential methylation regions showing within-pair methylation differences in all four MZ pairs. These are all located in CpG islands, 17 of which are promoter-associated, 17 are intergenic islands, and four are intragenic islands. Genes associated with these markers are related with cell proliferation, differentiation, and growth and development, including zinc finger proteins, PRRX2, RBBP9, or are involved in G-protein signaling, such as the regulator of G-protein signaling 16. Further validation studies on additional MZ twins are now required to evaluate the broader utility of these 38 markers for forensic use.
BACKGROUND: Genome-wide methylation of cytosine can be modulated in the presence of TET and thymine DNA glycosylase (TDG) enzymes. TET is able to oxidise 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC). TDG can excise the oxidative products 5fC and 5caC, initiating base excision repair. These modified bases are stable and detectable in the genome, suggesting that they could have epigenetic functions in their own right. However, functional investigation of the genome-wide distribution of 5fC has been restricted to cell culture-based systems, while its in vivo profile remains unknown. RESULTS: Here, we describe the first analysis of the in vivo genome-wide profile of 5fC across a range of tissues from both wild-type and Tdg-deficient E11.5 mouse embryos. Changes in the formylation profile of cytosine upon depletion of TDG suggest TET/TDG-mediated active demethylation occurs preferentially at intron-exon boundaries and reveals a major role for TDG in shaping 5fC distribution at CpG islands. Moreover, we find that active enhancer regions specifically exhibit high levels of 5fC, resulting in characteristic tissue-diagnostic patterns, which suggest a role in embryonic development. CONCLUSIONS: The tissue-specific distribution of 5fC can be regulated by the collective contribution of TET-mediated oxidation and excision by TDG. The in vivo profile of 5fC during embryonic development resembles that of embryonic stem cells, sharing key features including enrichment of 5fC in enhancer and intragenic regions. Additionally, by investigating mouse embryo 5fC profiles in a tissue-specific manner, we identify targeted enrichment at active enhancers involved in tissue development. ; MI is supported by the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007-2013/under REA grant agreement no. 290123. GRM was supported by Trinity College and Herchel Smith studentships. MB was supported by the CRUK PhD Training Programme in Chemical Biology and Molecular Medicine. DB is supported by funding from the Wellcome Trust and Herchel Smith. The WR lab is supported by BBSRC, MRC, the Wellcome Trust, EU EpiGeneSys and BLUEPRINT. The SB lab is supported by core funding from Cancer Research UK and a Wellcome Trust Senior Investigator Award. ; This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13059-016-1001-5.
Abstract Background A recent, large genome-wide association study (GWAS) of European ancestry individuals has identified multiple genetic variants influencing serum lipids. Studies of the transferability of these associations to African Americans remain few, an important limitation given interethnic differences in serum lipids and the disproportionate burden of lipid-associated metabolic diseases among African Americans. Methods We attempted to evaluate the transferability of 95 lipid-associated loci recently identified in European ancestry individuals to 887 non-diabetic, unrelated African Americans from a population-based sample in the Washington, DC area. Additionally, we took advantage of the generally reduced linkage disequilibrium among African ancestry populations in comparison to European ancestry populations to fine-map replicated GWAS signals. Results We successfully replicated reported associations for 10 loci ( CILP2/SF4 , STARD3 , LPL , CYP7A1 , DOCK7 / ANGPTL3 , APOE , SORT1 , IRS1 , CETP , and UBASH3B ). Through trans-ethnic fine-mapping, we were able to reduce associated regions around 75% of the loci that replicated. Conclusions Between this study and previous work in African Americans, 40 of the 95 loci reported in a large GWAS of European ancestry individuals also influence lipid levels in African Americans. While there is now evidence that the lipid-influencing role of a number of genetic variants is observed in both European and African ancestry populations, the still considerable lack of concordance highlights the importance of continued ancestry-specific studies to elucidate the genetic underpinnings of these traits.
WOS: 000373197500020 ; PubMed ID: 27016271 ; BACKGROUND AND OBJECTIVE: Developmental language disorder (DLD) is a highly prevalent neurodevelopmental disorder associated with negative outcomes in different domains; the etiology of DLD is unknown. To investigate the genetic underpinnings of DLD, we performed genome-wide association and whole exome sequencing studies in a geographically isolated population with a substantially elevated prevalence of the disorder (ie, the AZ sample). METHODS: DNA samples were collected from 359 individuals for the genome-wide association study and from 12 severely affected individuals for whole exome sequencing. Multifaceted phenotypes, representing major domains of expressive language functioning, were derived from collected speech samples. RESULTS: Gene-based analyses revealed a significant association between SETBP1 and complexity of linguistic output (P = 5.47 x 10(-7)). The analysis of exome variants revealed coding sequence variants in 14 genes, most of which play a role in neural development. Targeted enrichment analysis implicated myocyte enhancer factor-2 (MEF2)-regulated genes in DLD in the AZ population. The main findings were successfully replicated in an independent cohort of children at risk for related disorders (n = 37). CONCLUSIONS: MEF2-regulated pathways were identified as potential candidate pathways in the etiology of DLD. Several genes (including the candidate SETBP1 and other MEF2-related genes) seem to jointly influence certain, but not all, facets of the DLD phenotype. Even when genetic and environmental diversity is reduced, DLD is best conceptualized as etiologically complex. Future research should establish whether the signals detected in the AZ population can be replicated in other samples and languages and provide further characterization of the identified pathway. ; National Institute of Health [R01 DC007665, P50 HD052120]; NIH Centers for Mendelian Genomics [5U54HG006504]; National Science Foundation Integrative Graduate Education and Research Traineeship grant [114399]; Government of the Russian Federation [14.Z50.31.0027]; National Institutes of Health (NIH) ; Supported by National Institute of Health grants R01 DC007665 (Dr Grigorenko, Principal Investigator) and P50 HD052120 (Richard Wagner, Principal Investigator), NIH Centers for Mendelian Genomics (5U54HG006504), National Science Foundation Integrative Graduate Education and Research Traineeship grant 114399 (Dr Magnuson, Principal Investigator), and grant 14.Z50.31.0027 from the Government of the Russian Federation (Dr Grigorenko, Principal Investigator). Funded by the National Institutes of Health (NIH).
WOS: 000373197500020 ; PubMed ID: 27016271 ; BACKGROUND AND OBJECTIVE: Developmental language disorder (DLD) is a highly prevalent neurodevelopmental disorder associated with negative outcomes in different domains; the etiology of DLD is unknown. To investigate the genetic underpinnings of DLD, we performed genome-wide association and whole exome sequencing studies in a geographically isolated population with a substantially elevated prevalence of the disorder (ie, the AZ sample). METHODS: DNA samples were collected from 359 individuals for the genome-wide association study and from 12 severely affected individuals for whole exome sequencing. Multifaceted phenotypes, representing major domains of expressive language functioning, were derived from collected speech samples. RESULTS: Gene-based analyses revealed a significant association between SETBP1 and complexity of linguistic output (P = 5.47 x 10(-7)). The analysis of exome variants revealed coding sequence variants in 14 genes, most of which play a role in neural development. Targeted enrichment analysis implicated myocyte enhancer factor-2 (MEF2)-regulated genes in DLD in the AZ population. The main findings were successfully replicated in an independent cohort of children at risk for related disorders (n = 37). CONCLUSIONS: MEF2-regulated pathways were identified as potential candidate pathways in the etiology of DLD. Several genes (including the candidate SETBP1 and other MEF2-related genes) seem to jointly influence certain, but not all, facets of the DLD phenotype. Even when genetic and environmental diversity is reduced, DLD is best conceptualized as etiologically complex. Future research should establish whether the signals detected in the AZ population can be replicated in other samples and languages and provide further characterization of the identified pathway. ; National Institute of Health [R01 DC007665, P50 HD052120]; NIH Centers for Mendelian Genomics [5U54HG006504]; National Science Foundation Integrative Graduate Education and Research Traineeship grant [114399]; Government of the Russian Federation [14.Z50.31.0027]; National Institutes of Health (NIH) ; Supported by National Institute of Health grants R01 DC007665 (Dr Grigorenko, Principal Investigator) and P50 HD052120 (Richard Wagner, Principal Investigator), NIH Centers for Mendelian Genomics (5U54HG006504), National Science Foundation Integrative Graduate Education and Research Traineeship grant 114399 (Dr Magnuson, Principal Investigator), and grant 14.Z50.31.0027 from the Government of the Russian Federation (Dr Grigorenko, Principal Investigator). Funded by the National Institutes of Health (NIH).
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 15, Heft 6, S. 767-774
As part of the Genes, Environment and Development Initiative, the Minnesota Center for Twin and Family Research (MCTFR) undertook a genome-wide association study, which we describe here. A total of 8,405 research participants, clustered in four-member families, have been successfully genotyped on 527,829 single nucleotide polymorphism (SNP) markers using Illumina's Human660W-Quad array. Quality control screening of samples and markers as well as SNP imputation procedures are described. We also describe methods for ancestry control and how the familial clustering of the MCTFR sample can be accounted for in the analysis using a Rapid Feasible Generalized Least Squares algorithm. The rich longitudinal MCTFR assessments provide numerous opportunities for collaboration.
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 18, Heft 1, S. 61-72
Breastfeeding has been an important survival trait during human history, though it has long been recognized that individuals differ in their exact breastfeeding behavior. Here our aims were, first, to explore to what extent genetic and environmental influences contributed to the individual differences in breastfeeding behavior; second, to detect possible genetic variants related to breastfeeding; and lastly, to test if the genetic variants associated with breastfeeding have been previously found to be related with breast size. Data were collected from a large community-based cohort of Australian twins, with 3,364 women participating in the twin modelling analyses and 1,521 of them included in the genome-wide association study (GWAS). Monozygotic (MZ) twin correlations (rMZ = 0.52, 95% CI 0.46–0.57) were larger than dizygotic (DZ) twin correlations (rDZ = 0.35, 95% CI 0.25–0.43) and the best-fitting model was the one composed by additive genetics and unique environmental factors, explaining 53% and 47% of the variance in breastfeeding behavior, respectively. No breastfeeding-related genetic variants reached genome-wide significance. The polygenic risk score analyses showed no significant results, suggesting breast size does not influence breastfeeding. This study confers a replication of a previous one exploring the sources of variance of breastfeeding and, to our knowledge, is the first one to conduct a GWAS on breastfeeding and look at the overlap with variants for breast size.
Altres ajuts: The Stroke Genetics Network (SiGN) study was funded by a cooperative agreement grant from the US National Institute of Neurological Disorders and Stroke (NINDS), NIH (U01 NS069208 and R01 NS100178). SAHLSIS was supported by the Swedish Heart and Lung Foundation (HLF-20160316), the Swedish Research Council (K2014-64X-14605-12-5), the Swedish Stroke Association, the Swedish state (under the "Avtal om Läkarutbildning och Medicinsk Forskning, ALF") (ALFGBG-720081). Australian Stroke Genetics Collaboration study was supported by the National Health and Medical Research Council, Australia. Stroke Pharmacogenomics and Genetics group was supported by Invictus plus network, Generation project, and Miguel Servet programme from Instituto de Salud Carlos III, GODs project and Epigenesis project from Marató de TV3 Foundation and Agaur from Generalitat de Catalunya Government. Arne Lindgren was supported by the Swedish Heart and Lung Foundation, Region Skåne, Skåne University Hospital, the Freemasons Lodge of Instruction EOS in Lund, Lund University, the Foundation of Färs & Frosta-one of Spar-banken Skåne's ownership Foundations, and the Swedish Stroke Association. Martin Söderholm was supported by grants from the Swedish Stroke Association, the Foundation of Färs & Frosta-one of Sparbanken Skåne's ownership Foundations, and the Swedish government (under the "Avtal om Läkarutbildning och Medicinsk Forskning, ALF"). Annie Pedersen was supported by grants from the Swedish government (under the "Avtal om Läkarutbildning och Medi-cinsk Forskning, ALF") and the Gothenburg Foundation for Neurological Research. Natalia Rost was in part supported by NIH-NINDS (R01NS086905 and R01NS082285). Daniel Strbian was supported by the Finnish Subsidiary Governmental Fund (VTR). The authors thank NINDS for funding the genotyping of patients included in the SiGN study (U01 NS069208 and R01 NS100178) and Sólveig Grétarsdóttir for genotyping a subsample of the SAHLSIS cohort. ; ObjectiveTo discover common genetic variants ...
Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery. ; The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Funding for this study was provided by the Aase and Ejner Danielsens Foundation; Academy of Finland (102318; 104781, 120315, 123885, 129619, 286284, 134309, 126925, 121584, 124282, 129378, 117787, 250207, 258753, 41071, 77299, 124243, 1114194, 24300796); Accare Center for Child and Adolescent Psychiatry; Action on Hearing Loss (G51); Agence Nationale de la Recherche; Agency for Health Care Policy Research (HS06516); Age UK Research into Ageing Fund; Åke Wiberg Foundation; ALF/LUA Research Grant in Gothenburg; ALFEDIAM; ALK-Abello´ A/S (Hørsholm, Denmark); American Heart Association (13POST16500011, 10SDG269004); Ardix Medical; Arthritis Research UK; Association Diabète Risque Vasculaire; AstraZeneca; Australian Associated Brewers; Australian National Health and Medical Research Council (241944, 339462, 389927, 389875, 389891, 389892, 389938, 442915, 442981, 496739, 552485, 552498); Avera Research Institute; Bayer Diagnostics; Becton Dickinson; Biobanking and Biomolecular Resources Research Infrastructure (BBMRI –NL, 184.021.007); Biocentrum Helsinki; Boston Obesity Nutrition Research Center (DK46200); British Heart Foundation (RG/10/12/28456, SP/04/002); Canada Foundation for Innovation; Canadian Institutes of Health Research (FRN-CCT-83028); Cancer Research UK; Cardionics; Center for Medical Systems Biology; Center of Excellence in Complex Disease Genetics and SALVECenter of Excellence in Genomics (EXCEGEN); Chief Scientist Office of the Scottish Government; City of Kuopio; Cohortes Santé TGIR; Contrat de Projets État-Région; Croatian Science Foundation (8875); Danish Agency for Science, Technology and Innovation; Danish Council for Independent Research (DFF–1333-00124, DFF–1331-007308); Danish Diabetes Academy; Danish Medical Research Council; Department of Psychology and Education of the VU University Amsterdam; Diabetes Hilfs- und Forschungsfonds Deutschland; Dutch Brain Foundation; Dutch Ministry of Justice; Emil Aaltonen Foundation; Erasmus Medical Center; Erasmus University; Estonian Government (IUT20-60, IUT24-6); Estonian Ministry of Education and Research (3.2.0304.11-0312); European Commission (230374, 284167, 323195, 692145, FP7 EurHEALTHAgeing-277849, FP7 BBMRI-LPC 313010, nr 602633, HEALTH-F2-2008-201865-GEFOS, HEALTH-F4-2007-201413, FP6 LSHM-CT-2004-005272, FP5 QLG2-CT-2002-01254, FP6 LSHG-CT-2006-01947, FP7 HEALTH-F4-2007-201413, FP7 279143, FP7 201668, FP7 305739, FP6 LSHG-CT-2006-018947, HEALTH-F4-2007-201413, QLG1-CT-2001-01252); European Regional Development Fund; European Science Foundation (EuroSTRESS project FP-006, ESF, EU/QLRT-2001-01254); Faculty of Biology and Medicine of Lausanne; Federal Ministry of Education and Research (01ZZ9603, 01ZZ0103, 01ZZ0403, 03ZIK012, 03IS2061A); Federal State of Mecklenburg - West Pomerania; Fédération Française de Cardiologie; Finnish Cultural Foundation; Finnish Diabetes Association; Finnish Foundation of Cardiovascular Research; Finnish Heart Association; Food Standards Agency; Fondation de France; Fonds Santé; Genetic Association Information Network of the Foundation for the National Institutes of Health; German Diabetes Association; German Federal Ministry of Education and Research (BMBF, 01ER1206, 01ER1507); German Research Council (SFB-1052, SPP 1629 TO 718/2-1); GlaxoSmithKline; Göran Gustafssons Foundation; Göteborg Medical Society; Health and Safety Executive; Heart Foundation of Northern Sweden; Icelandic Heart Association; Icelandic Parliament; Imperial College Healthcare NHS Trust; INSERM, Réseaux en Santé Publique, Interactions entre les déterminants de la santé; Interreg IV Oberrhein Program (A28); Italian Ministry of Economy and Finance; Italian Ministry of Health (ICS110.1/RF97.71); John D and Catherine T MacArthur Foundation; Juho Vainio Foundation; King's College London; Kjell och Märta Beijers Foundation; Kuopio University Hospital; Kuopio, Tampere and Turku University Hospital Medical Funds (X51001); Leiden University Medical Center; Lilly; LMUinnovativ; Lundbeck Foundation; Lundberg Foundation; Medical Research Council of Canada; MEKOS Laboratories (Denmark); Merck Santé; Mid-Atlantic Nutrition Obesity Research Center (P30 DK72488); Ministère de l'Économie, de l'Innovation et des Exportations; Ministry for Health, Welfare and Sports of the Netherlands; Ministry of Cultural Affairs of the Federal State of Mecklenburg-West Pomerania; Ministry of Education and Culture of Finland (627;2004-2011); Ministry of Education, Culture and Science of the Netherlands; MRC Human Genetics Unit; MRC-GlaxoSmithKline Pilot Programme Grant (G0701863); Municipality of Rotterdam; Netherlands Bioinformatics Centre (2008.024); Netherlands Consortium for Healthy Aging (050-060-810); Netherlands Genomics Initiative; Netherlands Organisation for Health Research and Development (904-61-090, 985-10-002, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, Middelgroot-911-09-032, Spinozapremie 56-464-14192); Netherlands Organisation for Health Research and Development (2010/31471/ZONMW); Netherlands Organisation for Scientific Research (10-000-1002, GB-MW 940-38-011, 100-001-004, 60-60600-97-118, 261-98-710, GB-MaGW 480-01-006, GB-MaGW 480-07-001, GB-MaGW 452-04-314, GB-MaGW 452-06-004, 175.010.2003.005, 175.010.2005.011, 481-08-013, 480-05-003, 911-03-012); Neuroscience Campus Amsterdam; NHS Foundation Trust; Novartis Pharmaceuticals; Novo Nordisk; Office National Interprofessionel des Vins; Paavo Nurmi Foundation; Påhlssons Foundation; Päivikki and Sakari Sohlberg Foundation; Pierre Fabre; Republic of Croatia Ministry of Science, Education and Sport (108-1080315-0302); Research Centre for Prevention and Health, the Capital Region for Denmark; Research Institute for Diseases in the Elderly (014-93-015, RIDE2); Roche; Russian Foundation for Basic Research (NWO-RFBR 047.017.043); Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06); Sanofi-Aventis; Scottish Executive Health Department (CZD/16/6); Siemens Healthcare; Social Insurance Institution of Finland (4/26/2010); Social Ministry of the Federal State of Mecklenburg-West Pomerania; Société Francophone du Diabète; State of Bavaria; Stroke Association; Swedish Diabetes Association; Swedish Foundation for Strategic Research; Swedish Heart-Lung Foundation (20140543); Swedish Research Council (2015-03657); Swedish Medical Research Council (K2007-66X-20270-01-3, 2011-2354); Swedish Society for Medical Research; Swiss National Science Foundation (33CSCO-122661, 33CS30-139468, 33CS30-148401); Tampere Tuberculosis Foundation; The Marcus Borgström Foundation; The Royal Society; The Wellcome Trust (084723/Z/08/Z, 088869/B/09/Z); Timber Merchant Vilhelm Bangs Foundation; Topcon; Torsten and Ragnar Söderberg's Foundation; UK Department of Health; UK Diabetes Association; UK Medical Research Council (MC_U106179471, G0500539, G0600705, G0601966, G0700931, G1002319, K013351, MC_UU_12019/1); UK National Institute for Health Research BioResource Clinical Research Facility and Biomedical Research Centre; UK National Institute for Health Research (NIHR) Comprehensive Biomedical Research Centre; UK National Institute for Health Research (RP-PG-0407-10371); Umeå University Career Development Award; United States – Israel Binational Science Foundation Grant (2011036); University Hospital Oulu (75617); University Medical Center Groningen; University of Tartu (SP1GVARENG); National Institutes of Health (AG13196, CA047988, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSC271201100004C, HHSN268200900041C, HHSN268201300025C, HHSN268201300026C, HHSN268201300027C, HHSN268201300028C, HHSN268201300029C, HHSN268201500001I, HL36310, HG002651, HL034594, HL054457, HL054481, HL071981, HL084729, HL119443, HL126024, N01-AG12100, N01-AG12109, N01-HC25195, N01-HC55015, N01-HC55016, N01-HC55018, N01-HC55019, N01-HC55020, N01-HC55021, N01-HC55022, N01-HD95159, N01-HD95160, N01-HD95161, N01-HD95162, N01-HD95163, N01-HD95164, N01-HD95165, N01-HD95166, N01-HD95167, N01-HD95168, N01-HD95169, N01-HG65403, N02-HL64278, R01-HD057194, R01-HL087641, R01-HL59367, R01HL-086694, R01-HL088451, R24-HD050924, U01-HG-004402, HHSN268200625226C, UL1-RR025005, UL1-RR025005, UL1-TR-001079, UL1-TR-00040, AA07535, AA10248, AA11998, AA13320, AA13321, AA13326, AA14041, AA17688, DA12854, MH081802, MH66206, R01-D004215701A, R01-DK075787, R01-DK089256, R01-DK8925601, R01-HL088451, R01-HL117078, R01-DK062370, R01-DK072193, DK091718, DK100383, DK078616, 1Z01-HG000024, HL087660, HL100245, R01DK089256, 2T32HL007055-36, U01-HL072515-06, U01-HL84756, NIA-U01AG009740, RC2-AG036495, RC4-AG039029, R03 AG046389, 263-MA-410953, 263-MD-9164, 263-MD-821336, U01-HG004802, R37CA54281, R01CA63, P01CA33619, U01-CA136792, U01-CA98758, RC2-MH089951, MH085520, R01-D0042157-01A, MH081802, 1RC2-MH089951, 1RC2-MH089995, 1RL1MH08326801, U01-HG007376, 5R01-HL08767902, 5R01MH63706:02, HG004790, N01-WH22110, U01-HG007033, UM1CA182913, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 42107-26, 42129-32, 44221); USDA National Institute of Food and Agriculture (2007-35205-17883); Västra Götaland Foundation; Velux Foundation; Veterans Affairs (1 IK2 BX001823); Vleugels Foundation; VU University's Institute for Health and Care Research (EMGO+, HEALTH-F4-2007-201413) and Neuroscience Campus Amsterdam; Wellcome Trust (090532, 091551, 098051, 098381); Wissenschaftsoffensive TMO; and Yrjö Jahnsson Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ; Peer Reviewed
In: Ecotoxicology and environmental safety: EES ; official journal of the International Society of Ecotoxicology and Environmental safety, Band 183, S. 109485
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 8, Heft 1, S. 16-21
AbstractGenome-wide linkage analysis using multiple traits and statistical software packages is a tedious process which requires a significant amount of manual file manipulation. Different linkage analysis programs require different input file formats, making the task of analyzing data with multiple methods even more time-consuming. We have developed a software tool, AUTOGSCAN, that automates file formatting, the running of statistical analyses, and the summarizing of resulting statistics for whole genome scans with a push of a button, using several independent, and often idiosyncratic, statistical software packages such as MERLIN, SOLAR and GENEHUNTER. We also describe a program, ANALYZE, designed to run qualitative linkage analysis with several different statistical strategies and programs to efficiently screen for linkage and linkage disequilibrium for a given discrete trait. The ANALYZE program can also be used by AUTOGSCAN in a genome-wide sense.
Epigenetic modifications, including DNA methylation, represent a potential mechanism for environmental impacts on human disease. Maternal smoking in pregnancy remains an important public health problem that impacts child health in a myriad of ways and has potential lifelong consequences. The mechanisms are largely unknown, but epigenetics most likely plays a role. We formed the Pregnancy And Childhood Epigenetics (PACE) consortium and meta-analyzed, across 13 cohorts (n = 6,685), the association between maternal smoking in pregnancy and newborn blood DNA methylation at over 450,000 CpG sites (CpGs) by using the Illumina 450K BeadChip. Over 6,000 CpGs were differentially methylated in relation to maternal smoking at genome-wide statistical significance (false discovery rate, 5%), including 2,965 CpGs corresponding to 2,017 genes not previously related to smoking and methylation in either newborns or adults. Several genes are relevant to diseases that can be caused by maternal smoking (e.g., orofacial clefts and asthma) or adult smoking (e.g., certain cancers). A number of differentially methylated CpGs were associated with gene expression. We observed enrichment in pathways and processes critical to development. In older children (5 cohorts, n = 3,187), 100% of CpGs gave at least nominal levels of significance, far more than expected by chance (p value < 2.2 × 10−16). Results were robust to different normalization methods used across studies and cell type adjustment. In this large scale meta-analysis of methylation data, we identified numerous loci involved in response to maternal smoking in pregnancy with persistence into later childhood and provide insights into mechanisms underlying effects of this important exposure. ; The BAMSE cohort was supported by The Swedish Research Council, The Swedish Heart-Lung Foundation, Freemason Child House Foundation in Stockholm, MeDALL (Mechanisms of the Development of ALLergy), a collaborative project conducted within the European Union (grant agreement No. 261357), Centre for Allergy Research, Stockholm County Council (ALF), Swedish foundation for strategic research (SSF, RBc08-0027, EpiGene project), the Strategic Research Programme (SFO) in Epidemiology at Karolinska Institutet, The Swedish Research Council Formas and the Swedish Environment Protection Agency.
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 8, Heft 3, S. 185-197
Almost half of all individuals affected by intellectual disability (ID) remain undiagnosed. In the Solve-RD project, exome sequencing (ES) datasets from unresolved individuals with (syndromic) ID (n = 1,472 probands) are systematically reanalyzed, starting from raw sequencing files, followed by genome-wide variant calling and new data interpretation. This strategy led to the identification of a disease-causing de novo missense variant in TUBB3 in a girl with severe developmental delay, secondary microcephaly, brain imaging abnormalities, high hypermetropia, strabismus and short stature. Interestingly, the TUBB3 variant could only be identified through reanalysis of ES data using a genome-wide variant calling approach, despite being located in protein coding sequence. More detailed analysis revealed that the position of the variant within exon 5 of TUBB3 was not targeted by the enrichment kit, although consistent high-quality coverage was obtained at this position, resulting from nearby targets that provide off-target coverage. In the initial analysis, variant calling was restricted to the exon targets ± 200 bases, allowing the variant to escape detection by the variant calling algorithm. This phenomenon may potentially occur more often, as we determined that 36 established ID genes have robust off-target coverage in coding sequence. Moreover, within these regions, for 17 genes (likely) pathogenic variants have been identified before. Therefore, this clinical report highlights that, although compute-intensive, performing genome-wide variant calling instead of target-based calling may lead to the detection of diagnostically relevant variants that would otherwise remain unnoticed. ; This work was financially supported by Aspasia grants of the Dutch Research Council (015.014.036 to TK and 015.014.066 to LELMV) and Netherlands Organization for Health Research and Development (917.183.10 to TK). The Solve-RD project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 779257.