Browsing by Subject "GENOTYPE IMPUTATION"

Sort by: Order: Results:

Now showing items 1-20 of 22
  • Hannon, Eilis; Dempster, Emma; Viana, Joana; Burrage, Joe; Smith, Adam R.; Macdonald, Ruby; St Clair, David; Mustard, Colette; Breen, Gerome; Therman, Sebastian; Kaprio, Jaakko; Toulopoulou, Timothea; Pol, Hilleke E. Hulshoff; Bohlken, Marc M.; Kahn, Rene S.; Nenadic, Igor; Hultman, Christina M.; Murray, Robin M.; Collier, David A.; Bass, Nick; Gurling, Hugh; McQuillin, Andrew; Schalkwyk, Leonard; Mill, Jonathan (2016)
    Background: Schizophrenia is a highly heritable, neuropsychiatric disorder characterized by episodic psychosis and altered cognitive function. Despite success in identifying genetic variants associated with schizophrenia, there remains uncertainty about the causal genes involved in disease pathogenesis and how their function is regulated. Results: We performed a multi-stage epigenome-wide association study, quantifying genome-wide patterns of DNA methylation in a total of 1714 individuals from three independent sample cohorts. We have identified multiple differentially methylated positions and regions consistently associated with schizophrenia across the three cohorts; these effects are independent of important confounders such as smoking. We also show that epigenetic variation at multiple loci across the genome contributes to the polygenic nature of schizophrenia. Finally, we show how DNA methylation quantitative trait loci in combination with Bayesian co-localization analyses can be used to annotate extended genomic regions nominated by studies of schizophrenia, and to identify potential regulatory variation causally involved in disease. Conclusions: This study represents the first systematic integrated analysis of genetic and epigenetic variation in schizophrenia, introducing a methodological approach that can be used to inform epigenome-wide association study analyses of other complex traits and diseases. We demonstrate the utility of using a polygenic risk score to identify molecular variation associated with etiological variation, and of using DNA methylation quantitative trait loci to refine the functional and regulatory variation associated with schizophrenia risk variants. Finally, we present strong evidence for the co-localization of genetic associations for schizophrenia and differential DNA methylation.
  • Japan Scoliosis Clinical Res Grp; Texas Scottish Rite Hosp Children (2018)
    Adolescent idiopathic scoliosis (AIS) is a common spinal deformity with the prevalence of approximately 3%. We previously conducted a genome-wide association study (GWAS) using a Japanese cohort and identified a novel locus on chromosome 9p22.2. However, a replication study using multi-population cohorts has not been conducted. To confirm the association of 9p22.2 locus with AIS in multi-ethnic populations, we conducted international meta-analysis using eight cohorts. In total, we analyzed 8,756 cases and 27,822 controls. The analysis showed a convincing evidence of association between rs3904778 and AIS. Seven out of eight cohorts had significant P value, and remaining one cohort also had the same trend as the seven. The combined P was 3.28 x 10(-18) (odds ratio = 1.19, 95% confidence interval = 1.14-1.24). In silico analyses suggested that BNC2 is the AIS susceptibility gene in this locus.
  • Einarsdottir, Elisabet; Grauers, Anna; Wang, Jingwen; Jiao, Hong; Escher, Stefan A.; Danielsson, Aina; Simony, Ane; Andersen, Mikkel; Christensen, Steen Bach; Åkesson, Kristina; Kou, Ikuyo; Khanshour, Anas M.; Ohlin, Acke; Wise, Carol; Ikegawa, Shiro; Kere, Juha; Gerdhem, Paul (2017)
    A Swedish pedigree with an autosomal dominant inheritance of idiopathic scoliosis was initially studied by genetic linkage analysis, prioritising genomic regions for further analysis. This revealed a locus on chromosome 1 with a putative risk haplotype shared by all affected individuals. Two affected individuals were subsequently exome-sequenced, identifying a rare, non-synonymous variant in the CELSR2 gene. This variant is rs141489111, a c. G6859A change in exon 21 (NM_001408), leading to a predicted p. V2287I (NP_001399.1) change. This variant was found in all affected members of the pedigree, but showed reduced penetrance. Analysis of tagging variants in CELSR1-3 in a set of 1739 Swedish-Danish scoliosis cases and 1812 controls revealed significant association (p = 0.0001) to rs2281894, a common synonymous variant in CELSR2. This association was not replicated in case-control cohorts from Japan and the US. No association was found to variants in CELSR1 or CELSR3. Our findings suggest a rare variant in CELSR2 as causative for idiopathic scoliosis in a family with dominant segregation and further highlight common variation in CELSR2 in general susceptibility to idiopathic scoliosis in the Swedish-Danish population. Both variants are located in the highly conserved GAIN protein domain, which is necessary for the auto-proteolysis of CELSR2, suggesting its functional importance.
  • Tukiainen, Taru; Pirinen, Matti; Sarin, Antti-Pekka; Ladenvall, Claes; Kettunen, Johannes; Lehtimaeki, Terho; Lokki, Marja-Liisa; Perola, Markus; Sinisalo, Juha; Vlachopoulou, Efthymia; Eriksson, Johan G.; Groop, Leif; Jula, Antti; Jaervelin, Marjo-Riitta; Raitakari, Olli T.; Salomaa, Veikko; Ripatti, Samuli (2014)
  • Horikoshi, Momoko; Maegi, Reedik; van de Bunt, Martijn; Surakka, Ida; Sarin, Antti-Pekka; Mahajan, Anubha; Marullo, Letizia; Thorleifsson, Gudmar; Haegg, Sara; Hottenga, Jouke-Jan; Ladenvall, Claes; Ried, Janina S.; Winkler, Thomas W.; Willems, Sara M.; Tsernikova, Natalia; Esko, Tonu; Beekman, Marian; Nelson, Christopher P.; Willenborg, Christina; Wiltshire, Steven; Ferreira, Teresa; Fernandez, Juan; Gaulton, Kyle J.; Steinthorsdottir, Valgerdur; Hamsten, Anders; Magnusson, Patrik K. E.; Willemsen, Gonneke; Milaneschi, Yuri; Robertson, Neil R.; Groves, Christopher J.; Bennett, Amanda J.; Lehtimaeki, Terho; Viikari, Jorma S.; Rung, Johan; Lyssenko, Valeriya; Perola, Markus; Heid, Iris M.; Herder, Christian; Grallert, Harald; Mueller-Nurasyid, Martina; Roden, Michael; Hypponen, Elina; Isaacs, Aaron; van Leeuwen, Elisabeth M.; Karssen, Lennart C.; Mihailov, Evelin; Kaprio, Jaakko; Eriksson, Johan G.; Groop, Leif; Ripatti, Samuli; ENGAGE Consortium (2015)
    Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency >= 0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.
  • Salo, Perttu P.; Vaara, Satu; Kettunen, Johannes; Pirinen, Matti; Sarin, Antti-Pekka; Huikuri, Heikki; Karhunen, Pekka J.; Eskola, Markku; Nikus, Kjell; Lokki, Marja-Liisa; Ripatti, Samuli; Havulinna, Aki S.; Salomaa, Veikko; Palotie, Aarno; Nieminen, Markku S.; Sinisalo, Juha; Perola, Markus (2015)
    Myocardial infarction (MI) is divided into either ST elevation MI (STEMI) or non-ST elevation MI (NSTEMI), differing in a number of clinical characteristics. We sought to identify genetic variants conferring risk to NSTEMI or STEMI by conducting a genome-wide association study (GWAS) of MI stratified into NSTEMI and STEMI in a consecutive sample of 1,579 acute MI cases with 1,576 controls. Subsequently, we followed the results in an independent population-based sample of 562 cases and 566 controls, a partially independent prospective cohort (N = 16,627 with 163 incident NSTEMI cases), and examined the effect of disease-associated variants on gene expression in 513 healthy participants. Genetic variants on chromosome 1p13.3 near the damage-regulated autophagy modulator 2 gene DRAM2 associated with NSTEMI (rs656843; odds ratio 1.57, P = 3.11 x 10(-10)) in the case-control analysis with a consistent but not statistically significant effect in the prospective cohort (rs656843; hazard ratio 1.13, P = 0.43). These variants were not associated with STEMI (rs656843; odds ratio, 1.11, P = 0.20; hazard ratio 0.97, P = 0.87), appearing to have a pronounced effect on NSTEMI risk. A majority of the variants at 1p13.3 associated with NSTEMI were also associated with the expression level of DRAM2 in blood leukocytes of healthy controls (top-ranked variant rs325927, P = 1.50 x 10(-12)). The results suggest that genetic factors may in part influence whether coronary artery disease results in NSTEMI rather than STEMI.
  • Guo, Yan; Andersen, Shaneda Warren; Shu, Xiao-Ou; Michailidou, Kyriaki; Bolla, Manjeet K.; Wang, Qin; Garcia-Closas, Montserrat; Milne, Roger L.; Schmidt, Marjanka K.; Chang-Claude, Jenny; Dunning, Allison; Bojesen, Stig E.; Ahsan, Habibul; Aittomäki, Kristiina; Andrulis, Irene L.; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W.; Beeghly-Fadiel, Alicia; Benitez, Javier; Bogdanova, Natalia V.; Bonanni, Bernardo; Borresen-Dale, Anne-Lise; Brand, Judith; Brauch, Hiltrud; Brenner, Hermann; Bruening, Thomas; Burwinkel, Barbara; Casey, Graham; Chenevix-Trench, Georgia; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Czene, Kamila; Devilee, Peter; Doerk, Thilo; Dumont, Martine; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gammon, Marilie; Giles, Graham G.; Guenel, Pascal; Haiman, Christopher A.; Hamann, Ute; Hooning, Maartje J.; Hopper, John L.; Jakubowska, Anna; Jasmine, Farzana; Jenkins, Mark; John, Esther M.; Johnson, Nichola; Jones, Michael E.; Kabisch, Maria; Kibriya, Muhammad; Knight, Julia A.; Koppert, Linetta B.; Kosma, Veli-Matti; Kristensen, Vessela; Le Marchand, Loic; Lee, Eunjung; Li, Jingmei; Lindblom, Annika; Luben, Robert; Lubinski, Jan; Malone, Kathi E.; Mannermaa, Arto; Margolin, Sara; Marme, Frederik; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Neuhausen, Susan L.; Nevanlinna, Heli; Neven, Patrick; Olson, Janet E.; Perez, Jose I. A.; Perkins, Barbara; Peterlongo, Paolo; Phillips, Kelly-Anne; Pylkas, Katri; Rudolph, Anja; Santella, Regina; Sawyer, Elinor J.; Schmutzler, Rita K.; Seynaeve, Caroline; Shah, Mitul; Shrubsole, Martha J.; Southey, Melissa C.; Swerdlow, Anthony J.; Toland, Amanda E.; Tomlinson, Ian; Torres, Diana; Truong, Therese; Ursin, Giske; Van Der Luijt, Rob B.; Verhoef, Senno; Whittemore, Alice S.; Winqvist, Robert; Zhao, Hui; Zhao, Shilin; Hall, Per; Simard, Jacques; Kraft, Peter; Pharoah, Paul; Hunter, David; Easton, Douglas F.; Zheng, Wei (2016)
    Background Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors. Methods We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases = 46,325, controls = 42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively. Results In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR] = 0.65 per 5 kg/m(2) increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32 x 10(-10)). The associations were similar for both premenopausal (OR = 0.44, 95% CI: 0.31-0.62, p = 9.91x10(-8)) and postmenopausal breast cancer (OR = 0.57, 95% CI: 0.46-0.71, p = 1.88x10(-8)). This association was replicated in the data from the DRIVE consortium (OR = 0.72, 95% CI: 0.60-0.84, p = 1.64 x 10(-7)). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p <0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk. Conclusions BMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.
  • ITALSGEN Consortium; Genomic Translation ALS Care GTAC; ALS Sequencing Consortium; NYGC ALS Consortium; Answer ALS Fdn; Clinical Res ALS Related Disorders; SLAGEN Consortium; French ALS Consortium; Project MinE ALS Sequencing Consor (2018)
    To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS.
  • NEIGHBORHOOD Consortium; ANZRAG Consortium; FinnGen Study; BioBank Japan Project; UK Biobank Eye Vision Consortium; GIGA Study Grp; 23 Me Res Team; Gharahkhani, Puya; Jorgenson, Eric; Karjalainen, Juha; Palotie, Aarno; Loukola, Anu (2021)
    Primary open-angle glaucoma (POAG), is a heritable common cause of blindness world-wide. To identify risk loci, we conduct a large multi-ethnic meta-analysis of genome-wide association studies on a total of 34,179 cases and 349,321 controls, identifying 44 previously unreported risk loci and confirming 83 loci that were previously known. The majority of loci have broadly consistent effects across European, Asian and African ancestries. Cross-ancestry data improve fine-mapping of causal variants for several loci. Integration of multiple lines of genetic evidence support the functional relevance of the identified POAG risk loci and highlight potential contributions of several genes to POAG pathogenesis, including SVEP1, RERE, VCAM1, ZNF638, CLIC5, SLC2A12, YAP1, MXRA5, and SMAD6. Several drug compounds targeting POAG risk genes may be potential glaucoma therapeutic candidates. Primary open-angle glaucoma (POAG) is highly heritable, yet not well understood from a genetic perspective. Here, the authors perform a meta-analysis of genome-wide association studies in 34,179 POAG cases, identifying 44 previously unreported risk loci and mapping effects across multiple ethnicities.
  • Hancock, D. B.; Reginsson, G. W.; Gaddis, N. C.; Chen, X.; Saccone, N. L.; Lutz, S. M.; Qaiser, Beenish; Sherva, R.; Steinberg, S.; Zink, F.; Stacey, S. N.; Glasheen, C.; Chen, J.; Gu, F.; Frederiksen, B. N.; Loukola, A.; Gudbjartsson, D. F.; Brueske, I.; Landi, M. T.; Bickeboeller, H.; Madden, P.; Farrer, L.; Kaprio, J.; Kranzler, H. R.; Gelernter, J.; Baker, T. B.; Kraft, P.; Amos, C. I.; Caporaso, N. E.; Hokanson, J. E.; Bierut, L. J.; Thorgeirsson, T. E.; Johnson, E. O.; Stefansson, K. (2015)
    We conducted a 1000 Genomes-imputed genome-wide association study (GWAS) meta-analysis for nicotine dependence, defined by the Fagerstrom Test for Nicotine Dependence in 17 074 ever smokers from five European-ancestry samples. We followed up novel variants in 7469 ever smokers from five independent European-ancestry samples. We identified genome-wide significant association in the alpha-4 nicotinic receptor subunit (CHRNA4) gene on chromosome 20q13: lowest P = 8.0 x 10(-9) across all the samples for rs2273500-C (frequency = 0.15; odds ratio = 1.12 and 95% confidence interval = 1.08-1.17 for severe vs mild dependence). rs2273500-C, a splice site acceptor variant resulting in an alternate CHRNA4 transcript predicted to be targeted for nonsense-mediated decay, was associated with decreased CHRNA4 expression in physiologically normal human brains (lowest P = 7.3 x 10(-4)). Importantly, rs2273500-C was associated with increased lung cancer risk (N = 28 998, odds ratio = 1.06 and 95% confidence interval = 1.00-1.12), likely through its effect on smoking, as rs2273500-C was no longer associated with lung cancer after adjustment for smoking. Using criteria for smoking behavior that encompass more than the single 'cigarettes per day' item, we identified a common CHRNA4 variant with important regulatory properties that contributes to nicotine dependence and smoking-related consequences.
  • Psychiat Genomics Consortium; 23andMe Res Team; Psychosis Endopheno-types Int Cons; Wellcome Trust Case Control Consor; Lee, Phil H.; Anttila, Verneri; Won, Hyejung; Kaprio, Jaakko; Keski-Rahkonen, Anna; Churchhouse, Claire; Rehnström, Karola; Raevuori, Anu; Palotie, Aarno; Daly, Mark J.; Neale, Benjamin M. (2019)
    Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.
  • Guo, Qi; Schmidt, Marjanka K.; Kraft, Peter; Canisius, Sander; Chen, Constance; Khan, Sofia; Tyrer, Jonathan; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Michailidou, Kyriaki; Lush, Michael; Kar, Siddhartha; Beesley, Jonathan; Dunning, Alison M.; Shah, Mitul; Czene, Kamila; Darabi, Hatef; Eriksson, Mikael; Lambrechts, Diether; Weltens, Caroline; Leunen, Karin; Bojesen, Stig E.; Nordestgaard, Borge G.; Nielsen, Sune F.; Flyger, Henrik; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Blomqvist, Carl; Aittomäki, Kristiina; Fagerholm, Rainer; Muranen, Taru A.; Couch, Fergus J.; Olson, Janet E.; Vachon, Celine; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Mulligan, Anna Marie; Broeks, Annegien; Hogervorst, Frans B.; Haiman, Christopher A.; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Hopper, John L.; Tsimiklis, Helen; Nevanlinna, Heli; kConFab Investigators (2015)
    Background: Survival after a diagnosis of breast cancer varies considerably between patients, and some of this variation may be because of germline genetic variation. We aimed to identify genetic markers associated with breast cancer-specific survival. Methods: We conducted a large meta-analysis of studies in populations of European ancestry, including 37 954 patients with 2900 deaths from breast cancer. Each study had been genotyped for between 200 000 and 900 000 single nucleotide polymorphisms (SNPs) across the genome; genotypes for nine million common variants were imputed using a common reference panel from the 1000 Genomes Project. We also carried out subtype-specific analyses based on 6881 estrogen receptor (ER)-negative patients (920 events) and 23 059 ER-positive patients (1333 events). All statistical tests were two-sided. Results: We identified one new locus (rs2059614 at 11q24.2) associated with survival in ER-negative breast cancer cases (hazard ratio [HR] = 1.95, 95% confidence interval [CI] = 1.55 to 2.47, P = 1.91 x 10(-8)). Genotyping a subset of 2113 case patients, of which 300 were ER negative, provided supporting evidence for the quality of the imputation. The association in this set of case patients was stronger for the observed genotypes than for the imputed genotypes. A second locus (rs148760487 at 2q24.2) was associated at genome-wide statistical significance in initial analyses; the association was similar in ER-positive and ER-negative case patients. Here the results of genotyping suggested that the finding was less robust. Conclusions: This is currently the largest study investigating genetic variation associated with breast cancer survival. Our results have potential clinical implications, as they confirm that germline genotype can provide prognostic information in addition to standard tumor prognostic factors.
  • Häkkinen, Katja; Kiiski, Johanna I.; Lähteenvuo, Markku; Jukuri, Tuomas; Suokas, Kimmo; Niemi-Pynttäri, Jussi; Kieseppä, Tuula; Männynsalo, Teemu; Wegelius, Asko; Haaki, Willehard; Lahdensuo, Kaisla; Kajanne, Risto; Kaunisto, Mari A.; Tuulio-Henriksson, Annamari; Kampman, Olli; Hietala, Jarmo; Veijola, Juha; Lönnqvist, Jouko; Isometsä, Erkki; Paunio, Tiina; Suvisaari, Jaana; Kalso, Eija; Niemi, Mikko; Tiihonen, Jari; Daly, Mark; Palotie, Aarno; Ahola-Olli, Ari V. (2022)
    We demonstrate that CYP2D6 copy-number variation (CNV) can be imputed using existing imputation algorithms. Additionally, we report frequencies of key pharmacogenetic variants in individuals with a psychotic disorder from the genetically bottle-necked population of Finland. We combined GWAS chip and CYP2D6 CNV data from the Breast Cancer Pain Genetics study to construct an imputation panel (n = 902) for CYP2D6 CNV. The resulting data set was used as a CYP2D6 CNV imputation panel in 9262 non-related individuals from the SUPER-Finland study. Based on imputation of 9262 individuals we confirm the higher frequency of CYP2D6 ultrarapid metabolizers and a 22-fold enrichment of the UGT1A1 decreased function variant rs4148323 (UGT1A1*6) in Finland compared with non-Finnish Europeans. Similarly, the NUDT15 variant rs116855232 was highly enriched in Finland. We demonstrate that imputation of CYP2D6 CNV is possible and the methodology enables studying CYP2D6 in large biobanks with genome-wide data.
  • Mitt, Mario; Kals, Mart; Parn, Kalle; Gabriel, Stacey B.; Lander, Eric S.; Palotie, Aarno; Ripatti, Samuli; Morris, Andrew P.; Metspalu, Andres; Esko, Tonu; Magi, Reedik; Palta, Priit (2017)
    Genetic imputation is a cost-efficient way to improve the power and resolution of genome-wide association (GWA) studies. Current publicly accessible imputation reference panels accurately predict genotypes for common variants with minor allele frequency (MAF) >= 5% and low-frequency variants (0.5
  • Huang, Jie; Howie, Bryan; McCarthy, Shane; Memari, Yasin; Walter, Klaudia; Min, Josine L.; Danecek, Petr; Malerba, Giovanni; Trabetti, Elisabetta; Zheng, Hou-Feng; Gambaro, Giovanni; Richards, J. Brent; Durbin, Richard; Timpson, Nicholas J.; Marchini, Jonathan; Soranzo, Nicole; UK10K Consortium; Paunio, Tiina (2015)
    Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants.
  • Castel, Stephane E.; Cervera, Alejandra; Mohammadi, Pejman; Aguet, Francois; Reverter, Ferran; Wolman, Aaron; Guigo, Roderic; Iossifov, Ivan; Vasileva, Ana; Lappalainen, Tuuli (2018)
    Coding variants represent many of the strongest associations between genotype and phenotype; however, they exhibit interindividual differences in effect, termed 'variable penetrance'. Here, we study how cis-regulatory variation modifies the penetrance of coding variants. Using functional genomic and genetic data from the Genotype-Tissue Expression Project (GTEx), we observed that in the general population, purifying selection has depleted haplotype combinations predicted to increase pathogenic coding variant penetrance. Conversely, in cancer and autism patients, we observed an enrichment of penetrance increasing haplotype configurations for pathogenic variants in disease-implicated genes, providing evidence that regulatory haplotype configuration of coding variants affects disease risk. Finally, we experimentally validated this model by editing a Mendelian single-nucleotide polymorphism (SNP) using CRISPR/Cas9 on distinct expression haplotypes with the transcriptome as a phenotypic readout. Our results demonstrate that joint regulatory and coding variant effects are an important part of the genetic architecture of human traits and contribute to modified penetrance of disease-causing variants.
  • Loley, Christina; Alver, Maris; Assimes, Themistocles L.; Bjonnes, Andrew; Goel, Anuj; Gustafsson, Stefan; Hernesniemi, Jussi; Hopewell, Jemma C.; Kanoni, Stavroula; Kleber, Marcus E.; Lau, King Wai; Lu, Yingchang; Lyytikainen, Leo-Pekka; Nelson, Christopher P.; Nikpay, Majid; Qu, Liming; Salfati, Elias; Scholz, Markus; Tukiainen, Taru; Willenborg, Christina; Won, Hong-Hee; Zeng, Lingyao; Zhang, Weihua; Anand, Sonia S.; Beutner, Frank; Bottinger, Erwin P.; Clarke, Robert; Dedoussis, George; Do, Ron; Esko, Tonu; Eskola, Markku; Farrall, Martin; Gauguier, Dominique; Giedraitis, Vilmantas; Granger, Christopher B.; Hall, Alistair S.; Hamsten, Anders; Hazen, Stanley L.; Huang, Jie; Kahonen, Mika; Kyriakou, Theodosios; Laaksonen, Reijo; Lind, Lars; Lindgren, Cecilia; Magnusson, Patrik K. E.; Marouli, Eirini; Mihailov, Evelin; Morris, Andrew P.; Nikus, Kjell; Pedersen, Nancy; Rallidis, Loukianos; Salomaa, Veikko; Shah, Svati H.; Stewart, Alexandre F. R.; Thompson, John R.; Zalloua, Pierre A.; Chambers, John C.; Collins, Rory; Ingelsson, Erik; Iribarren, Carlos; Karhunen, Pekka J.; Kooner, Jaspal S.; Lehtimaki, Terho; Loos, Ruth J. F.; Maerz, Winfried; McPherson, Ruth; Metspalu, Andres; Reilly, Muredach P.; Ripatti, Samuli; Sanghera, Dharambir K.; Thiery, Joachim; Watkins, Hugh; Deloukas, Panos; Kathiresan, Sekar; Samani, Nilesh J.; Schunkert, Heribert; Erdmann, Jeanette; Koenig, Inke R. (2016)
    In recent years, genome-wide association studies have identified 58 independent risk loci for coronary artery disease (CAD) on the autosome. However, due to the sex-specific data structure of the X chromosome, it has been excluded from most of these analyses. While females have 2 copies of chromosome X, males have only one. Also, one of the female X chromosomes may be inactivated. Therefore, special test statistics and quality control procedures are required. Thus, little is known about the role of X-chromosomal variants in CAD. To fill this gap, we conducted a comprehensive X-chromosome-wide meta-analysis including more than 43,000 CAD cases and 58,000 controls from 35 international study cohorts. For quality control, sex-specific filters were used to adequately take the special structure of X-chromosomal data into account. For single study analyses, several logistic regression models were calculated allowing for inactivation of one female X-chromosome, adjusting for sex and investigating interactions between sex and genetic variants. Then, meta-analyses including all 35 studies were conducted using random effects models. None of the investigated models revealed genome-wide significant associations for any variant. Although we analyzed the largest-to-date sample, currently available methods were not able to detect any associations of X-chromosomal variants with CAD.
  • Kujala, Urho M.; Palviainen, Teemu; Pesonen, Paula; Waller, Katja; Sillanpää, Elina; Niemelä, Maisa; Kangas, Maarit; Vähä-Ypyä, Henri; Sievänen, Harri; Korpelainen, Raija; Jämsä, Timo; Männikkö, Minna; Kaprio, Jaakko (2020)
    Purpose Polygenic risk scores (PRS) summarize genome-wide genotype data into a single variable that produces an individual-level risk score for genetic liability. PRS has been used for prediction of chronic diseases and some risk factors. As PRS has been studied less for physical activity (PA), we constructed PRS for PA and studied how much variation in PA can be explained by this PRS in independent population samples. Methods We calculated PRS for self-reported and objectively measured PA using UK Biobank genome-wide association study summary statistics, and analyzed how much of the variation in self-reported (MET-hours per day) and measured (steps and moderate-to-vigorous PA minutes per day) PA could be accounted for by the PRS in the Finnish Twin Cohorts (FTC;N= 759-11,528) and the Northern Finland Birth Cohort 1966 (NFBC1966;N= 3263-4061). Objective measurement of PA was done with wrist-worn accelerometer in UK Biobank and NFBC1966 studies, and with hip-worn accelerometer in the FTC. Results The PRS accounted from 0.07% to 1.44% of the variation (R-2) in the self-reported and objectively measured PA volumes (Pvalue range = 0.023 to
  • Tsai, Pei-Chien; Glastonbury, Craig A.; Eliot, Melissa N.; Bollepalli, Sailalitha; Yet, Idil; Castillo-Fernandez, Juan E.; Carnero-Montoro, Elena; Hardiman, Thomas; Martin, Tiphaine C.; Vickers, Alice; Mangino, Massimo; Ward, Kirsten; Pietilaeinen, Kirsi H.; Deloukas, Panos; Spector, Tim D.; Vinuela, Ana; Loucks, Eric B.; Ollikainen, Miina; Kelsey, Karl T.; Small, Kerrin S.; Bell, Jordana T. (2018)
    Background: Tobacco smoking is a risk factor for multiple diseases, including cardiovascular disease and diabetes. Many smoking-associated signals have been detected in the blood methylome, but the extent to which these changes are widespread to metabolically relevant tissues, and impact gene expression or metabolic health, remains unclear. Methods: We investigated smoking-associated DNA methylation and gene expression variation in adipose tissue biopsies from 542 healthy female twins. Replication, tissue specificity, and longitudinal stability of the smoking-associated effects were explored in additional adipose, blood, skin, and lung samples. We characterized the impact of adipose tissue smoking methylation and expression signals on metabolic disease risk phenotypes, including visceral fat. Results: We identified 42 smoking-methylation and 42 smoking-expression signals, where five genes (AHRR, CYP1A1, CYP1B1, CYTL1, F2RL3) were both hypo-methylated and upregulated in current smokers. CYP1A1 gene expression achieved 95% prediction performance of current smoking status. We validated and replicated a proportion of the signals in additional primary tissue samples, identifying tissue-shared effects. Smoking leaves systemic imprints on DNA methylation after smoking cessation, with stronger but shorter-lived effects on gene expression. Metabolic disease risk traits such as visceral fat and android-to-gynoid ratio showed association with methylation at smoking markers with functional impacts on expression, such as CYP1A1, and at tissue-shared smoking signals, such as NOTCH1. At smoking-signals, BHLHE40 and AHRR DNA methylation and gene expression levels in current smokers were predictive of future gain in visceral fat upon smoking cessation. Conclusions: Our results provide the first comprehensive characterization of coordinated DNA methylation arid gene expression markers of smoking in adipose tissue. The findings relate to human metabolic health and give insights into understanding the widespread health consequence of smoking outside of the lung.
  • Middeldorp, C. M.; de Moor, M. H. M.; McGrath, L. M.; Gordon, S. D.; Blackwood, D. H.; Costa, P. T.; Terracciano, A.; Krueger, R. F.; de Geus, E. J. C.; Nyholt, D. R.; Tanaka, T.; Esko, T.; Madden, P. A. F.; Derringer, J.; Amin, N.; Willemsen, G.; Hottenga, J-J; Distel, M. A.; Uda, M.; Sanna, S.; Spinhoven, P.; Hartman, C. A.; Ripke, S.; Sullivan, P. F.; Realo, A.; Allik, J.; Heath, A. C.; Pergadia, M. L.; Agrawal, A.; Lin, P.; Grucza, R. A.; Widen, E.; Cousminer, D. L.; Eriksson, J. G.; Palotie, A.; Barnett, J. H.; Lee, P. H.; Luciano, M.; Tenesa, A.; Davies, G.; Lopez, L. M.; Hansell, N. K.; Medland, S. E.; Ferrucci, L.; Schlessinger, D.; Montgomery, G. W.; Wright, M. J.; Aulchenko, Y. S.; Janssens, A. C. J. W.; Oostra, B. A.; Metspalu, A.; Abecasis, G. R.; Deary, I. J.; Räikkönen, Katri; Bierut, L. J.; Martin, N. G.; Wray, N. R.; van Duijn, C. M.; Smoller, J. W.; Penninx, B. W. J. H.; Boomsma, D. I. (2011)