Browsing by Subject "RARE VARIANTS"

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  • JSCRG; TSRHCCG (2018)
    Adolescent idiopathic scoliosis (AIS) is the most common type of spinal deformity and has a significant genetic background. Genome-wide association studies (GWASs) identified several susceptibility loci associated with AIS. Among them is a locus on chromosome 6q24.1 that we identified by a GWAS in a Japanese cohort. The locus is represented by rs6570507 located within GPR126. To ensure the association of rs6570507 with AIS, we conducted a meta-analysis using eight cohorts from East Asia, Northern Europe and USA. The analysis included a total of 6,873 cases and 38,916 controls and yielded significant association (combined P = 2.95 x 10(-20); odds ratio = 1.22), providing convincing evidence of the worldwide association between rs6570507 and AIS susceptibility. In silico analyses strongly suggested that GPR126 is a susceptibility gene at this locus.
  • Rivas, Manuel A.; Graham, Daniel; Sulem, Patrick; Stevens, Christine; Desch, A. Nicole; Goyette, Philippe; Gudbjartsson, Daniel; Jonsdottir, Ingileif; Thorsteinsdottir, Unnur; Degenhardt, Frauke; Mucha, Soeren; Kurki, Mitja I.; Li, Dalin; D'Amato, Mauro; Annese, Vito; Vermeire, Severine; Weersma, Rinse K.; Halfvarson, Jonas; Paavola-Sakki, Anu Liisa Paulina; Lappalainen, Anne Maarit; Lek, Monkol; Cummings, Beryl; Tukiainen, Taru; Haritunians, Talin; Halme, Leena; Koskinen, Lotta L. E.; Ananthakrishnan, Ashwin N.; Luo, Yang; Heap, Graham A.; Visschedijk, Marijn C.; MacArthur, Daniel G.; Neale, Benjamin M.; Ahmad, Tariq; Anderson, Carl A.; Brant, Steven R.; Duerr, Richard H.; Silverberg, Mark S.; Cho, Judy H.; Palotie, Aarno; Saavalainen, Paivi; Kontula, Kimmo; Farkkila, Martti; McGovern, Dermot P. B.; Franke, Andre; Stefansson, Kari; Rioux, John D.; Xavier, Ramnik J.; Daly, Mark J. (2016)
    Protein-truncating variants protective against human disease provide in vivo validation of therapeutic targets. Here we used targeted sequencing to conduct a search for protein-truncating variants conferring protection against inflammatory bowel disease exploiting knowledge of common variants associated with the same disease. Through replication genotyping and imputation we found that a predicted protein-truncating variant (rs36095412, p.R179X, genotyped in 11,148 ulcerative colitis patients and 295,446 controls, MAF = up to 0.78%) in RNF186, a single-exon ring finger E3 ligase with strong colonic expression, protects against ulcerative colitis (overall P = 6.89 x 10(-7), odds ratio = 0.30). We further demonstrate that the truncated protein exhibits reduced expression and altered subcellular localization, suggesting the protective mechanism may reside in the loss of an interaction or function via mislocalization and/or loss of an essential transmembrane domain.
  • Day-Williams, Aaron G.; McLay, Kirsten; Drury, Eleanor; Edkins, Sarah; Coffey, Alison J.; Palotie, Aarno; Zeggini, Eleftheria (2011)
  • Flannick, Jason; Fuchsberger, Christian; Mahajan, Anubha; Teslovich, Tanya M.; Agarwala, Vineeta; Gaulton, Kyle J.; Caulkins, Lizz; Koesterer, Ryan; Ma, Clement; Moutsianas, Loukas; McCarthy, Davis J.; Rivas, Manuel A.; Perry, John R. B.; Sim, Xueling; Blackwell, Thomas W.; Robertson, Neil R.; Rayner, N. William; Cingolani, Pablo; Locke, Adam E.; Tajes, Juan Fernandez; Highland, Heather M.; Dupuis, Josee; Chines, Peter S.; Lindgren, Cecilia M.; Hartl, Christopher; Jackson, Anne U.; Chen, Han; Huyghe, Jeroen R.; De Bunt, Martijn Van; Pearson, Richard D.; Kumar, Ashish; Muller-Nurasyid, Martina; Grarup, Niels; Stringham, Heather M.; Gamazon, Eric R.; Lee, Jaehoon; Chen, Yuhui; Scott, Robert A.; Below, Jennifer E.; Chen, Peng; Huang, Jinyan; Go, Min Jin; Stitzel, Michael L.; Pasko, Dorota; Parker, Stephen C. J.; Varga, Tibor V.; Green, Todd; Beer, Nicola L.; Day-Williams, Aaron G.; Ferreira, Teresa; Fingerlin, Tasha; Horikoshi, Momoko; Hu, Cheng; Huh, Iksoo; Ikram, Mohammad Kamran; Kim, Bong-Jo; Kim, Yongkang; Kim, Young Jin; Kwon, Min-Seok; Lee, Juyoung; Lee, Selyeong; Lin, Keng-Han; Maxwell, Taylor J.; Nagai, Yoshihiko; Wang, Xu; Welch, Ryan P.; Yoon, Joon; Zhang, Weihua; Barzilai, Nir; Voight, Benjamin F.; Han, Bok-Ghee; Jenkinson, Christopher P.; Kuulasmaa, Teemu; Kuusisto, Johanna; Manning, Alisa; Ng, Maggie C. Y.; Palmer, Nicholette D.; Balkau, Beverley; Stancakova, Alena; Abboud, Hanna E.; Boeing, Heiner; Giedraitis, Vilmantas; Prabhakaran, Dorairaj; Gottesman, Omri; Scott, James; Carey, Jason; Kwan, Phoenix; Grant, George; Smith, Joshua D.; Neale, Benjamin M.; Purcell, Shaun; Butterworth, Adam S.; Howson, Joanna M. M.; Lee, Heung Man; Lu, Yingchang; Kwak, Soo-Heon; Zhao, Wei; Danesh, John; Lam, Vincent K. L.; Park, Kyong Soo; Saleheen, Danish; So, Wing Yee; Tam, Claudia H. T.; Afzal, Uzma; Aguilar, David; Arya, Rector; Aung, Tin; Chan, Edmund; Navarro, Carmen; Cheng, Ching-Yu; Palli, Domenico; Correa, Adolfo; Curran, Joanne E.; Rybin, Dennis; Farook, Vidya S.; Fowler, Sharon P.; Freedman, Barry I.; Griswold, Michael; Hale, Daniel Esten; Hicks, Pamela J.; Khor, Chiea-Chuen; Kumar, Satish; Lehne, Benjamin; Thuillier, Dorothee; Lim, Wei Yen; Liu, Jianjun; Loh, Marie; Musani, Solomon K.; Puppala, Sobha; Scott, William R.; Yengo, Loic; Tan, Sian-Tsung; Taylor, Herman A.; Thameem, Farook; Wilson, Gregory; Wong, Tien Yin; Njolstad, Pal Rasmus; Levy, Jonathan C.; Mangino, Massimo; Bonnycastle, Lori L.; Schwarzmayr, Thomas; Fadista, Joao; Surdulescu, Gabriela L.; Herder, Christian; Groves, Christopher J.; Wieland, Thomas; Bork-Jensen, Jette; Brandslund, Ivan; Christensen, Cramer; Koistinen, Heikki A.; Doney, Alex S. F.; Kinnunen, Leena; Esko, Tonu; Farmer, Andrew J.; Hakaste, Liisa; Hodgkiss, Dylan; Kravic, Jasmina; Lyssenko, Valeriya; Hollensted, Mette; Jorgensen, Marit E.; Jorgensen, Torben; Ladenvall, Claes; Justesen, Johanne Marie; Karajamaki, Annemari; Kriebel, Jennifer; Rathmann, Wolfgang; Lannfelt, Lars; Lauritzen, Torsten; Narisu, Narisu; Linneberg, Allan; Melander, Olle; Milani, Lili; Neville, Matt; Orho-Melander, Marju; Qi, Lu; Qi, Qibin; Roden, Michael; Rolandsson, Olov; Swift, Amy; Rosengren, Anders H.; Stirrups, Kathleen; Wood, Andrew R.; Mihailov, Evelin; Blancher, Christine; Carneiro, Mauricio O.; Maguire, Jared; Poplin, Ryan; Shakir, Khalid; Fennell, Timothy; DePristo, Mark; De Angelis, Martin Hrabe; Deloukas, Panos; Gjesing, Anette P.; Jun, Goo; Nilsson, Peter M.; Murphy, Jacquelyn; Onofrio, Robert; Thorand, Barbara; Hansen, Torben; Meisinger, Christa; Hu, Frank B.; Isomaa, Bo; Karpe, Fredrik; Liang, Liming; Peters, Annette; Huth, Cornelia; O'Rahilly, Stephen P.; Palmer, Colin N. A.; Pedersen, Oluf; Rauramaa, Rainer; Tuomilehto, Jaakko; Salomaa, Veikko; Watanabe, Richard M.; Syvanen, Ann-Christine; Bergman, Richard N.; Bharadwaj, Dwaipayan; Bottinger, Erwin P.; Cho, Yoon Shin; Chandak, Giriraj R.; Chan, Juliana Cn; Chia, Kee Seng; Daly, Mark J.; Ebrahim, Shah B.; Langenberg, Claudia; Elliott, Paul; Jablonski, Kathleen A.; Lehman, Donna M.; Jia, Weiping; Ma, Ronald Cw; Pollin, Toni I.; Sandhu, Manjinder; Tandon, Nikhil; Froguel, Philippe; Barroso, Ines; Teo, Yik Ying; Zeggini, Eleftheria; Loos, Ruth J. F.; Small, Kerrin S.; Ried, Janina S.; DeFronzo, Ralph A.; Grallert, Harald; Glaser, Benjamin; Metspalu, Andres; Wareham, Nicholas J.; Walker, Mark; Banks, Eric; Gieger, Christian; Ingelsson, Erik; Im, Hae Kyung; Illig, Thomas; Franks, Paul W.; Buck, Gemma; Trakalo, Joseph; Buck, David; Prokopenko, Inga; Magi, Reedik; Lind, Lars; Farjoun, Yossi; Owen, Katharine R.; Gloyn, Anna L.; Strauch, Konstantin; Tuomi, Tiinamaija; Kooner, Jaspal Singh; Lee, Jong-Young; Park, Taesung; Donnelly, Peter; Morris, Andrew D.; Hattersley, Andrew T.; Bowden, Donald W.; Collins, Francis S.; Atzmon, Gil; Chambers, John C.; Spector, Timothy D.; Laakso, Markku; Strom, Tim M.; Bell, Graeme I.; Blangero, John; Duggirala, Ravindranath; Tai, EShyong; McVean, Gilean; Hanis, Craig L.; Wilson, James G.; Seielstad, Mark; Frayling, Timothy M.; Meigs, James B.; Cox, Nancy J.; Sladek, Rob; Lander, Eric S.; Gabriel, Stacey; Mohlke, Karen L.; Meitinger, Thomas; Groop, Leif; Abecasis, Goncalo; Scott, Laura J.; Morris, Andrew P.; Kang, Hyun Min; Altshuler, David; Burtt, Noel P.; Florez, Jose C.; Boehnke, Michael; McCarthy, Mark I. (2017)
    To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to 82 K Europeans via the exome chip, and similar to 90% of low-frequency non-coding variants in similar to 44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
  • NHLBI TOPMED Lipids Working Grp (2018)
    Lipoprotein(a), Lp(a), is a modified low- density lipoprotein particle that contains apolipoprotein( a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans.
  • Leppaaho, Eemeli; Renvall, Hanna; Salmela, Elina; Kere, Juha; Salmelin, Riitta; Kaski, Samuel (2019)
    Brain structure and many brain functions are known to be genetically controlled, but direct links between neuroimaging measures and their underlying cellular-level determinants remain largely undiscovered. Here, we adopt a novel computational method for examining potential similarities in high-dimensional brain imaging data between siblings. We examine oscillatory brain activity measured with magnetoencephalography (MEG) in 201 healthy siblings and apply Bayesian reduced-rank regression to extract a low-dimensional representation of familial features in the participants' spectral power structure. Our results show that the structure of the overall spectral power at 1-90Hz is a highly conspicuous feature that not only relates siblings to each other but also has very high consistency within participants' own data, irrespective of the exact experimental state of the participant. The analysis is extended by seeking genetic associations for low-dimensional descriptions of the oscillatory brain activity. The observed variability in the MEG spectral power structure was associated with SDK1 (sidekick cell adhesion molecule 1) and suggestively with several other genes that function, for example, in brain development. The current results highlight the potential of sophisticated computational methods in combining molecular and neuroimaging levels for exploring brain functions, even for high-dimensional data limited to a few hundred participants.
  • Broad Genomics Platform; DiscovEHR Collaboration; CHARGE; LuCamp; ProDiGY; GoT2D; ESP; SIGMA-T2D; T2D-GENES; AMP-T2D-GENES; Flannick, Jason; Mercader, Josep M.; Koistinen, Heikki A.; Kuusisto, Johanna; Groop, Leif; Tuomi, Tiinamaija; Tuomilehto, Jaakko; Boehnke, Michael (2019)
    Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 x 10(-3)) and candidate genes from knockout mice (P = 5.2 x 10(-3)). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.
  • Sanna, Serena; Li, Bingshan; Mulas, Antonella; Sidore, Carlo; Kang, Hyun M.; Jackson, Anne U.; Piras, Maria Grazia; Usala, Gianluca; Maninchedda, Giuseppe; Sassu, Alessandro; Serra, Fabrizio; Palmas, Maria Antonietta; Wood, William H.; Njolstad, Inger; Laakso, Markku; Hveem, Kristian; Tuomilehto, Jaakko; Lakka, Timo A.; Rauramaa, Rainer; Boehnke, Michael; Cucca, Francesco; Uda, Manuela; Schlessinger, David; Nagaraja, Ramaiah; Abecasis, Goncalo R. (2011)
  • Jia, Qiong; Han, Yi; Huang, Pin; Woodward, Nicholas C.; Gukasyan, Janet; Kettunen, Johannes; Ala-Korpela, Mika; Anufrieva, Olga; Wang, Qin; Perola, Markus; Raitakari, Olli; Lehtimaki, Terho; Viikari, Jorma; Jarvelin, Marjo-Riitta; Boehnke, Michael; Laakso, Markku; Mohlke, Karen L.; Fiehn, Oliver; Wang, Zeneng; Tang, W. H. Wilson; Hazen, Stanley L.; Hartiala, Jaana A.; Allayee, Hooman (2019)
    Background-Recent studies have revealed sexually dimorphic associations between the carbamoyl-phosphate synthase 1 locus, intermediates of the metabolic pathway leading from choline to urea, and risk of coronary artery disease (CAD) in women. Based on evidence from the literature, the atheroprotective association with carbamoyl-phosphate synthase 1 could be mediated by the strong genetic effect of this locus on increased circulating glycine levels. Methods and Results-We sought to identify additional genetic determinants of circulating glycine levels by carrying out a metaanalysis of genome-wide association study data in up to 30 118 subjects of European ancestry. Mendelian randomization and other analytical approaches were used to determine whether glycine-associated variants were associated with CAD and traditional risk factors. Twelve loci were significantly associated with circulating glycine levels, 7 of which were not previously known to be involved in glycine metabolism (ACADM, PHGDH, COX1 8-ADAMTS3, PSPH, TRIB 1 , PTPRD, and ABO). Glycine-raising alleles at several loci individually exhibited directionally consistent associations with decreased risk of CAD. However, these effects could not be attributed directly to glycine because of associations with other CAD-related traits. By comparison, genetic models that only included the 2 variants directly involved in glycine degradation and for which there were no other pleiotropic associations were not associated with risk of CAD or blood pressure, lipid levels, and obesity-related traits. Conclusions-These results provide additional insight into the genetic architecture of glycine metabolism, but do not yield conclusive evidence for a causal relationship between circulating levels of this amino acid and risk of CAD in humans.
  • Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J.; Soininen, Pasi; Lehtimaki, Terho; Raitakari, Olli T.; Jarvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti (2016)
    Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. Results: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies.
  • Tachmazidou, Ioanna; Suveges, Daniel; Min, Josine L.; Ritchie, Graham R. S.; Steinberg, Julia; Walter, Klaudia; Iotchkova, Valentina; Schwartzentruber, Jeremy; Huang, Jie; Memari, Yasin; McCarthy, Shane; Crawford, Andrew A.; Bombieri, Cristina; Cocca, Massimiliano; Farmaki, Aliki-Eleni; Gaunt, Tom R.; Jousilahti, Pekka; Kooijman, Marjolein N.; Lehne, Benjamin; Malerba, Giovanni; Mannisto, Satu; Matchan, Angela; Medina-Gomez, Carolina; Metrustry, Sarah J.; Nag, Abhishek; Ntalla, Ioanna; Paternoster, Lavinia; Rayner, Nigel W.; Sala, Cinzia; Scott, William R.; Shihab, Hashem A.; Southam, Lorraine; St Pourcain, Beate; Traglia, Michela; Trajanoska, Katerina; Zaza, Gialuigi; Zhang, Weihua; Artigas, Maria S.; Bansal, Narinder; Benn, Marianne; Chen, Zhongsheng; Danecek, Petr; Lin, Wei-Yu; Locke, Adam; Luan, Jian'an; Manning, Alisa K.; Mulas, Antonella; Sidore, Carlo; Tybjaerg-Hansen, Anne; Perola, Markus; SpiroMeta Consortium; GoT2D Consortium; ArcOGEN Consortium; Understanding Soc Sci Grp; UK10KConsortium (2017)
    Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common-and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.