Browsing by Subject "SUSCEPTIBILITY LOCI"

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  • Sung, Yun J.; Winkler, Thomas W.; de las Fuentes, Lisa; Bentley, Amy R.; Brown, Michael R.; Kraja, Aldi T.; Schwander, Karen; Ntalla, Ioanna; Guo, Xiuqing; Franceschini, Nora; Lu, Yingchang; Cheng, Ching-Yu; Sim, Xueling; Vojinovic, Dina; Marten, Jonathan; Musani, Solomon K.; Li, Changwei; Feitosa, Mary F.; Kilpelainen, Tuomas O.; Richard, Melissa A.; Noordam, Raymond; Aslibekyan, Stella; Aschard, Hugues; Bartz, Traci M.; Dorajoo, Rajkumar; Liu, Yongmei; Manning, Alisa K.; Rankinen, Tuomo; Smith, Albert Vernon; Tajuddin, Salman M.; Tayo, Bamidele O.; Warren, Helen R.; Zhao, Wei; Zhou, Yanhua; Matoba, Nana; Sofer, Tamar; Alver, Maris; Amini, Marzyeh; Boissel, Mathilde; Chai, Jin Fang; Chen, Xu; Divers, Jasmin; Gandin, Ilaria; Gao, Chuan; Giulianini, Franco; Goel, Anuj; Harris, Sarah E.; Heikkinen, Sami; Koistinen, Heikki A.; Weir, David R. (2018)
    Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined similar to 18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p <5 x 10(-8)) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p <5 x 10(-8)). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling MSRA, EBF2).
  • Hebbar, Prashantha; Abubaker, Jehad Ahmed; Abu-Farha, Mohamed; Tuomilehto, Jaakko; Al-Mulla, Fahd; Thanaraj, Thangavel Alphonse (2019)
    Despite dedicated nation-wide efforts to raise awareness against the harmful effects of fast-food consumption and sedentary lifestyle, the Arab population continues to struggle with an increased risk for metabolic disorders. Unlike the European population, the Arab population lacks well-established genetic risk determinants for metabolic disorders, and the transferability of established risk loci to this population has not been satisfactorily demonstrated. The most recent findings have identified over 240 genetic risk loci (with similar to 400 independent association signals) for type 2 diabetes, but thus far only 25 risk loci (ADAMTS9, ALX4, BCL11A, CDKAL1, CDKN2A/B, COL8A1, DUSP9, FTO, GCK, GNPDA2, HMG20A, HNF1A, HNF1B, HNF4A, IGF2BP2, JAZF1, KCNJ11 , KCNQ1, MC4R, PPAR gamma, SLC30A8, TCF7L2, TFAP2B, TP53INP1, and WFS1) have been replicated in Arab populations. To our knowledge, large-scale population- or family-based association studies are non-existent in this region. Recently, we conducted genome-wide association studies on Arab individuals from Kuwait to delineate the genetic determinants for quantitative traits associated with anthropometry, lipid profile, insulin resistance, and blood pressure levels. Although these studies led to the identification of novel recessive variants, they failed to reproduce the established loci. However, they provided insights into the genetic architecture of the population, the applicability of genetic models based on recessive mode of inheritance, the presence of genetic signatures of inbreeding due to the practice of consanguinity, and the pleiotropic effects of rare disorders on complex metabolic disorders. This perspective presents analysis strategies and study designs for identifying genetic risk variants associated with diabetes and related traits in Arab populations.
  • 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.
  • Early Growth Genetics Consortium; Bradfield, Jonathan P.; Vogelezang, Suzanne; Pitkänen, Niina; Leinonen, Jaakko T.; Lindi, Virpi; Atalay, Mustafa; Kähönen, Mika; Raitakari, Olli T.; Eriksson, Johan; Widen, Elisabeth (2019)
    Although hundreds of genome-wide association studies-implicated loci have been reported for adult obesity-related traits, less is known about the genetics specific for early-onset obesity and with only a few studies conducted in non-European populations to date. Searching for additional genetic variants associated with childhood obesity, we performed a trans-ancestral meta-analysis of 30 studies consisting of up to 13005 cases (>= 95th percentile of body mass index (BMI) achieved 2-18 years old) and 15599 controls (consistently
  • PanScan PanC4 consortia; Walsh, Naomi; Zhang, Han; Männistö, Satu; Weiderpass, Elisabete (2019)
    Background Genome-wide association studies (GWAS) identify associations of individual single-nucleotide polymorphisms (SNPs) with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants is a powerful tool to identify networks of susceptibility genes. Methods We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided. Results We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P Conclusion Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.
  • Pittman, Alan M.; Naranjo, Silvia; Jalava, Sanni E.; Twiss, Philip; Ma, Yussanne; Olver, Bianca; Lloyd, Amy; Vijayakrishnan, Jayaram; Qureshi, Mobshra; Broderick, Peter; van Wezel, Tom; Morreau, Hans; Tuupanen, Sari; Aaltonen, Lauri A.; Eva Alonso, M.; Manzanares, Miguel; Gavilan, Angela; Visakorpi, Tapio; Luis Gomez-Skarmeta, Jose; Houlston, Richard S. (2010)
  • Blanco, Ignacio; Kuchenbaecker, Karoline; Cuadras, Daniel; Wang, Xianshu; Barrowdale, Daniel; Ruiz de Garibay, Gorka; Librado, Pablo; Sanchez-Gracia, Alejandro; Rozas, Julio; Bonifaci, Nuria; McGuffog, Lesley; Pankratz, Vernon S.; Islam, Abul; Mateo, Francesca; Berenguer, Antoni; Petit, Anna; Catala, Isabel; Brunet, Joan; Feliubadalo, Lidia; Tornero, Eva; Benitez, Javier; Osorio, Ana; Cajal, Teresa Ramon Y.; Nevanlinna, Heli; Aittomaki, Kristiina; Arun, Banu K.; Toland, Amanda E.; Karlan, Beth Y.; Walsh, Christine; Lester, Jenny; Greene, Mark H.; Mai, Phuong L.; Nussbaum, Robert L.; Andrulis, Irene L.; Domchek, Susan M.; Nathanson, Katherine L.; Rebbeck, Timothy R.; Barkardottir, Rosa B.; Jakubowska, Anna; Lubinski, Jan; Durda, Katarzyna; Jaworska-Bieniek, Katarzyna; Claes, Kathleen; Van Maerken, Tom; Diez, Orland; Hansen, Thomas V.; Jonson, Lars; Gerdes, Anne-Marie; Ejlertsen, Bent; de la Hoya, Miguel; Caldes, Trinidad; Dunning, Alison M.; Oliver, Clare; Fineberg, Elena; Cook, Margaret; Peock, Susan; McCann, Emma; Murray, Alex; Jacobs, Chris; Pichert, Gabriella; Lalloo, Fiona; Chu, Carol; Dorkins, Huw; Paterson, Joan; Ong, Kai-Ren; Teixeira, Manuel R.; Teixeira,; Hogervorst, Frans B. L.; van der Hout, Annemarie H.; Seynaeve, Caroline; van der Luijt, Rob B.; Ligtenberg, Marjolijn J. L.; Devilee, Peter; Wijnen, Juul T.; Rookus, Matti A.; Meijers-Heijboer, Hanne E. J.; Blok, Marinus J.; van den Ouweland, Ans M. W.; Aalfs, Cora M.; Rodriguez, Gustavo C.; Phillips, Kelly-Anne A.; Piedmonte, Marion; Nerenstone, Stacy R.; Bae-Jump, Victoria L.; O'Malley, David M.; Ratner, Elena S.; Schmutzler, Rita K.; Wappenschmidt, Barbara; Rhiem, Kerstin; Engel, Christoph; Meindl, Alfons; Ditsch, Nina; Arnold, Norbert; Plendl, Hansjoerg J.; Niederacher, Dieter; Sutter, Christian; Wang-Gohrke, Shan; Steinemann, Doris; Preisler-Adams, Sabine; Kast, Karin; Varon-Mateeva, Raymonda; Gehrig, Andrea; Bojesen, Anders; Pedersen, Inge Sokilde; Sunde, Lone; Jensen, Uffe Birk; Thomassen, Mads; Kruse, Torben A.; Foretova, Lenka; Peterlongo, Paolo; Bernard, Loris; Peissel, Bernard; Scuvera, Giulietta; Manoukian, Siranoush; Radice, Paolo; Ottini, Laura; Montagna, Marco; Agata, Simona; Maugard, Christine; Simard, Jacques; Soucy, Penny; Berger, Andreas; Fink-Retter, Anneliese; Singer, Christian F.; Rappaport, Christine; Geschwantler-Kaulich, Daphne; Tea, Muy-Kheng; Pfeiler, Georg; John, Esther M.; Miron, Alex; Neuhausen, Susan L.; Terry, Mary Beth; Chung, Wendy K.; Daly, Mary B.; Goldgar, David E.; Janavicius, Ramunas; Dorfling, Cecilia M.; van Rensburg, Elisabeth J.; Fostira, Florentia; Konstantopoulou, Irene; Garber, Judy; Godwin, Andrew K.; Olah, Edith; Narod, Steven A.; Rennert, Gad; Paluch, Shani Shimon; Laitman, Yael; Friedman, Eitan; Liljegren, Annelie; Rantala, Johanna; Stenmark-Askmalm, Marie; Loman, Niklas; Imyanitov, Evgeny N.; Hamann, Ute; Spurdle, Amanda B.; Healey, Sue; Weitzel, Jeffrey N.; Herzog, Josef; Margileth, David; Gorrini, Chiara; Esteller, Manel; Gomez, Antonio; Sayols, Sergi; Vidal, Enrique; Heyn, Holger; Stoppa-Lyonnet, Dominique; Leone, Melanie; Barjhoux, Laure; Fassy-Colcombet, Marion; de Pauw, Antoine; Lasset, Christine; Ferrer, Sandra Fert; Castera, Laurent; Berthet, Pascaline; Cornelis, Francois; Bignon, Yves-Jean; Damiola, Francesca; Mazoyer, Sylvie; Sinilnikova, Olga M.; Maxwell, Christopher A.; Vijai, Joseph; Robson, Mark; Kauff, Noah; Corines, Marina J.; Villano, Danylko; Cunningham, Julie; Lee, Adam; Lindor, Noralane; Lazaro, Conxi; Easton, Douglas F.; Offit, Kenneth; Chenevix-Trench, Georgia; Couch, Fergus J.; Antoniou, Antonis C.; Angel Pujana, Miguel; BCFR; SWE-BRCA; KConFab Investigators; GEMO (2015)
    While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood approach. The association of HMMR rs299290 with breast cancer risk in BRCA1 mutation carriers was confirmed: per-allele hazard ratio (HR) = 1.10, 95% confidence interval (CI) 1.04 - 1.15, p = 1.9 x 10(-4) (false discovery rate (FDR)-adjusted p = 0.043). Variation in CSTF1, located next to AURKA, was also found to be associated with breast cancer risk in BRCA2 mutation carriers: rs2426618 per-allele HR = 1.10, 95% CI 1.03 - 1.16, p = 0.005 (FDR-adjusted p = 0.045). Assessment of pairwise interactions provided suggestions (FDR-adjusted p(interaction) values > 0.05) for deviations from the multiplicative model for rs299290 and CSTF1 rs6064391, and rs299290 and TUBG1 rs11649877 in both BRCA1 and BRCA2 mutation carriers. Following these suggestions, the expression of HMMR and AURKA or TUBG1 in sporadic breast tumors was found to potentially interact, influencing patients' survival. Together, the results of this study support the hypothesis of a causative link between altered function of AURKA-HMMR-TPX2-TUBG1 and breast carcinogenesis in BRCA1/2 mutation carriers.
  • Gusev, Alexander; Shi, Huwenbo; Kichaev, Gleb; Pomerantz, Mark; Li, Fugen; Long, Henry W.; Ingles, Sue A.; Kittles, Rick A.; Strom, Sara S.; Rybicki, Benjamin A.; Nemesure, Barbara; Isaacs, William B.; Zheng, Wei; Pettaway, Curtis A.; Yeboah, Edward D.; Tettey, Yao; Biritwum, Richard B.; Adjei, Andrew A.; Tay, Evelyn; Truelove, Ann; Niwa, Shelley; Chokkalingam, Anand P.; John, Esther M.; Murphy, Adam B.; Signorello, Lisa B.; Carpten, John; Leske, M. Cristina; Wu, Suh-Yuh; Hennis, Anslem J. M.; Neslund-Dudas, Christine; Hsing, Ann W.; Chu, Lisa; Goodman, Phyllis J.; Klein, Eric A.; Witte, John S.; Casey, Graham; Kaggwa, Sam; Cook, Michael B.; Stram, Daniel O.; Blot, William J.; Eeles, Rosalind A.; Easton, Douglas; Kote-Jarai, ZSofia; Al Olama, Ali Amin; Benlloch, Sara; Muir, Kenneth; Giles, Graham G.; Southey, Melissa C.; Fitzgerald, Liesel M.; Taari, Kimmo; PRACTICAL Consortium (2016)
    Although genome-wide association studies have identified over 100 risk loci that explain similar to 33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.
  • Perazzio, Sandro F.; Allenspach, Eric J.; Eklund, Kari K.; Varjosalo, Markku; Shinohara, Michi M.; Torgerson, Troy R.; Seppänen, Mikko R. J. (2020)
    Behcet's disease (BD) is a heterogeneous multi-organ disorder in search of a unified pathophysiological theory and classification. The disease frequently has overlapping features resembling other disease clusters, such as vasculitides, spondyloarthritides and thrombophilias with similar genetic risk variants, namelyHLA-B*51,ERAP1,IL-10,IL-23R. Many of the BD manifestations, such as unprovoked recurrent episodes of inflammation and increased expression of IL-1, IL-6 and TNF alpha, overlap with those of the hereditary monogenic autoinflammatory syndromes, positioning BD at the crossroads between autoimmune and autoinflammatory syndromes. BD-like disease associates with various inborn errors of immunity, including familial Mediterranean fever, conditions related to dysregulated NF-kappa B activation (egTNFAIP3,NFKB1,OTULIN,RELA,IKBKG) and either constitutional trisomy 8 or acquired trisomy 8 in myelodysplastic syndromes. We review here the recent advances in the immunopathology of BD, BD-like diseases and the NF-kappa B pathway suggesting new elements in the elusive BD etiopathogenesis.
  • Kirchhoff, Tomas; Gaudet, Mia M.; Antoniou, Antonis C.; McGuffog, Lesley; Humphreys, Manjeet K.; Dunning, Alison M.; Bojesen, Stig E.; Nordestgaard, Borge G.; Flyger, Henrik; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Ahn, Sei-Hyun; Dork, Thilo; Schuermann, Peter; Karstens, Johann H.; Hillemanns, Peter; Couch, Fergus J.; Olson, Janet; Vachon, Celine; Wang, Xianshu; Cox, Angela; Brock, Ian; Elliott, Graeme; Reed, Malcolm W. R.; Burwinkel, Barbara; Meindl, Alfons; Brauch, Hiltrud; Hamann, Ute; Ko, Yon-Dschun; Broeks, Annegien; Schmidt, Marjanka K.; Van 't Veer, Laura J.; Braaf, Linde M.; Johnson, Nichola; Fletcher, Olivia; Gibson, Lorna; Peto, Julian; Turnbull, Clare; Seal, Sheila; Renwick, Anthony; Rahman, Nazneen; Wu, Pei-Ei; Yu, Jyh-Cherng; Hsiung, Chia-Ni; Shen, Chen-Yang; Southey, Melissa C.; Hopper, John L.; Nevanlinna, Heli; Heikkinen, Tuomas; EMBRACE, BCAC-CIMBA, HEBON, AOCS Study Grp, kConFab, GENICA Network, SWE-BRCA (2012)
  • Karinen, Sirkku; Heikkinen, Tuomas; Nevanlinna, Heli; Hautaniemi, Sampsa (2011)
  • Psychiat Genomics Consortium; Lönnqvist, Jouko; Paunio, Tiina (2018)
    Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on similar to 150,000 individuals give a higher accuracy than LDSC estimates based on similar to 400,000 individuals (from combinedmeta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.
  • Prasad, Rashmi B.; Lessmark, Anna; Almgren, Peter; Kovacs, Gyorgyi; Hansson, Ola; Oskolkov, Nikolay; Vitai, Marta; Ladenvall, Claes; Kovacs, Peter; Fadista, Joao; Lachmann, Michael; Zhou, Yuedan; Sonestedt, Emily; Poon, Wenny; Wollheim, Claes B.; Orho-Melander, Marju; Stumvoll, Michael; Tuomi, Tiinamaija; Paeaebo, Svante; Koranyi, Laszlo; Groop, Leif (2016)
    Aims/hypothesis Genome-wide association studies (GWAS) have identified more than 65 genetic loci associated with risk of type 2 diabetes. However, the contribution of distorted parental transmission of alleles to risk of type 2 diabetes has been mostly unexplored. Our goal was therefore to search for parent-of-origin effects (POE) among type 2 diabetes loci in families. Methods Families from the Botnia study (n = 4,211, 1,083 families) were genotyped for 72 single-nucleotide polymorphisms (SNPs) associated with type 2 diabetes and assessed for POE on type 2 diabetes. The family-based Hungarian Transdanubian Biobank (HTB) (n = 1,463, > 135 families) was used to replicate SNPs showing POE. Association of type 2 diabetes loci within families was also tested. Results Three loci showed nominal POE, including the previously reported variants in KCNQ1, for type 2 diabetes in families from Botnia (rs2237895: p(POE) = 0.037), which can be considered positive controls. The strongest POE was seen for rs7578597 SNP in the THADA gene, showing excess transmission of the maternal risk allele T to diabetic offspring (Botnia: p(POE) = 0.01; HTB p(POE) = 0.045). These data are consistent with previous evidence of allelic imbalance for expression in islets, suggesting that the THADA gene can be imprinted in a POE-specific fashion. Five CpG sites, including those flanking rs7578597, showed differential methylation between diabetic and non-diabetic donor islets. Conclusions/interpretation Taken together, the data emphasise the need for genetic studies to consider from which parent an offspring has inherited a susceptibility allele.
  • Darabi, Hatef; Beesley, Jonathan; Droit, Arnaud; Kar, Siddhartha; Nord, Silje; Marjaneh, Mahdi Moradi; Soucy, Penny; Michailidou, Kyriaki; Ghoussaini, Maya; Wahl, Hanna Fues; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Alonso, M. Rosario; Andrulis, Irene L.; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W.; Benitez, Javier; Bogdanova, Natalia V.; Bojesen, Stig E.; Brauch, Hiltrud; Brenner, Hermann; Broeks, Annegien; Bruening, Thomas; Burwinkel, Barbara; Chang-Claude, Jenny; Choi, Ji-Yeob; Conroy, Don M.; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Czene, Kamila; Devilee, Peter; Doerk, Thilo; Easton, Douglas F.; Fasching, Peter A.; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Galle, Eva; Garcia-Closas, Montserrat; Giles, Graham G.; Goldberg, Mark S.; Gonzalez-Neira, Anna; Guenel, Pascal; Haiman, Christopher A.; Hallberg, Emily; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L.; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kang, Daehee; Khan, Sofia; Kosma, Veli-Matti; Kriege, Mieke; Kristensen, Vessela; Lambrechts, Diether; Le Marchand, Loic; Lee, Soo Chin; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Matsuo, Keitaro; Mayes, Rebecca; Mckay, James; Meindl, Alfons; Milne, Roger L.; Muir, Kenneth; Neuhausen, Susan L.; Nevanlinna, Heli; Olswold, Curtis; Orr, Nick; Peterlongo, Paolo; Pita, Guillermo; Pylkaes, Katri; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Marjanka K.; Schmutzler, Rita K.; Seynaeve, Caroline; Shah, Mitul; Shen, Chen-Yang; Shu, Xiao-Ou; Southey, Melissa C.; Stram, Daniel O.; Surowy, Harald; Swerdlow, Anthony; Teo, Soo H.; Tessier, Daniel C.; Tomlinson, Ian; Torres, Diana; Truong, Therese; Vachon, Celine M.; Vincent, Daniel; Winqvist, Robert; Wu, Anna H.; Wu, Pei-Ei; Yip, Cheng Har; Zheng, Wei; Pharoah, Paul D. P.; Hall, Per; Edwards, Stacey L.; Simard, Jacques; French, Juliet D.; Chenevix-Trench, Georgia; Dunning, Alison M. (2016)
    Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90-0.94; P = 8.96 x 10(-15))) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 x 10-09, r(2) = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 x 10(-11), r(2) = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus.
  • Fachal, L.; Aschard, H.; Beesley, J.; Barnes, D.R.; Allen, J.; Kar, S.; Pooley, K.A.; Dennis, J.; Michailidou, K.; Turman, C.; Soucy, P.; Lemaçon, A.; Lush, M.; Tyrer, J.P.; Ghoussaini, M.; Marjaneh, M.M.; Jiang, X.; Agata, S.; Aittomäki, K.; Alonso, M.R.; Andrulis, I.L.; Anton-Culver, H.; Antonenkova, N.N.; Arason, A.; Arndt, V.; Aronson, K.J.; Arun, B.K.; Auber, B.; Auer, P.L.; Azzollini, J.; Balmaña, J.; Barkardottir, R.B.; Barrowdale, D.; Beeghly-Fadiel, A.; Benitez, J.; Bermisheva, M.; Białkowska, K.; Blanco, A.M.; Blomqvist, C.; Blot, W.; Bogdanova, N.V.; Bojesen, S.E.; Bolla, M.K.; Bonanni, B.; Borg, A.; Bosse, K.; Brauch, H.; Brenner, H.; Briceno, I.; Brock, I.W.; Brooks-Wilson, A.; Brüning, T.; Burwinkel, B.; Buys, S.S.; Cai, Q.; Caldés, T.; Caligo, M.A.; Camp, N.J.; Campbell, I.; Canzian, F.; Carroll, J.S.; Carter, B.D.; Castelao, J.E.; Chiquette, J.; Christiansen, H.; Chung, W.K.; Claes, K.B.M.; Clarke, C.L.; Mari, V.; Berthet, P.; Castera, L.; Vaur, D.; Lallaoui, H.; Bignon, Y.-J.; Uhrhammer, N.; Bonadona, V.; Lasset, C.; Révillion, F.; Vennin, P.; Muller, D.; Gomes, D.M.; Ingster, O.; Coupier, I.; Pujol, P.; Collonge-Rame, M.-A.; Mortemousque, I.; Bera, O.; Rose, M.; Baurand, A.; Bertolone, G.; Faivre, L.; Dreyfus, H.; Leroux, D.; Venat-Bouvet, L.; Bézieau, S.; Delnatte, C.; Chiesa, J.; Gilbert-Dussardier, B.; Gesta, P.; Prieur, F.P.; Bronner, M.; Sokolowska, J.; Coulet, F.; Boutry-Kryza, N.; Calender, A.; Giraud, S.; Leone, M.; Fert-Ferrer, S.; Stoppa-Lyonnet, D.; Jiao, Y.; Lesueur, F.L.; Mebirouk, N.; Barouk-Simonet, E.; Bubien, V.; Longy, M.; Sevenet, N.; Gladieff, L.; Toulas, C.; Reimineras, A.; Sobol, H.; Paillerets, B.B.-D.; Cabaret, O.; Caron, O.; Guillaud-Bataille, M.; Rouleau, E.; Belotti, M.; Buecher, B.; Caputo, S.; Colas, C.; Pauw, A.D.; Fourme, E.; Gauthier-Villars, M.; Golmard, L.; Moncoutier, V.; Saule, C.; Donaldson, A.; Murray, A.; Brady, A.; Brewer, C.; Pottinger, C.; Miller, C.; Gallagher, D.; Gregory, H.; Cook, J.; Eason, J.; Adlard, J.; Barwell, J.; Ong, K.-R.; Snape, K.; Walker, L.; Izatt, L.; Side, L.; Tischkowitz, M.; Rogers, M.T.; Porteous, M.E.; Ahmed, M.; Morrison, P.J.; Brennan, P.; Eeles, R.; Davidson, R.; Collée, M.; Cornelissen, S.; Couch, F.J.; Cox, A.; Cross, S.S.; Cybulski, C.; Czene, K.; Daly, M.B.; de la Hoya, M.; Devilee, P.; Diez, O.; Ding, Y.C.; Dite, G.S.; Domchek, S.M.; Dörk, T.; dos-Santos-Silva, I.; Droit, A.; Dubois, S.; Dumont, M.; Duran, M.; Durcan, L.; Dwek, M.; Eccles, D.M.; Engel, C.; Eriksson, M.; Evans, D.G.; Fasching, P.A.; Fletcher, O.; Floris, G.; Flyger, H.; Foretova, L.; Foulkes, W.D.; Friedman, E.; Fritschi, L.; Frost, D.; Gabrielson, M.; Gago-Dominguez, M.; Gambino, G.; Ganz, P.A.; Gapstur, S.M.; Garber, J.; García-Sáenz, J.A.; Gaudet, M.M.; Georgoulias, V.; Giles, G.; Glendon, G.; Godwin, A.K.; Goldberg, M.S.; Goldgar, D.E.; González-Neira, A.; Tibiletti, M.G.; Greene, M.H.; Grip, M.; Gronwald, J.; Grundy, A.; Guénel, P.; Hahnen, E.; Haiman, C.A.; Håkansson, N.; Hall, P.; Hamann, U.; Harrington, P.A.; Hartikainen, J.M.; Hartman, M.; He, W.; Healey, C.S.; Heemskerk-Gerritsen, B.A.M.; Heyworth, J.; Hillemanns, P.; Hogervorst, F.B.L.; Hollestelle, A.; Hooning, M.; Hopper, J.; Howell, A.; Huang, G.; Hulick, P.J.; Imyanitov, E.N.; Sexton, A.; Christian, A.; Trainer, A.; Spigelman, A.; Fellows, A.; Shelling, A.; Fazio, A.D.; Blackburn, A.; Crook, A.; Meiser, B.; Patterson, B.; Clarke, C.; Saunders, C.; Hunt, C.; Scott, C.; Amor, D.; Marsh, D.; Edkins, E.; Salisbury, E.; Haan, E.; Neidermayr, E.; Macrea, F.; Farshid, G.; Lindeman, G.; Chenevix-Trench, G.; Mann, G.; Giles, G.; Gill, G.; Thorne, H.; Campbell, I.; Hickie, I.; Winship, I.; Flanagan, J.; Kollias, J.; Visvader, J.; Stone, J.; Taylor, J.; Burke, J.; Saunus, J.; Forbes, J.; Hopper, J.; Beesley, J.; Kirk, J.; French, J.; Tucker, K.; Wu, K.; Phillips, K.; Lipton, L.; Andrews, L.; Lobb, L.; Walker, L.; Kentwell, M.; Spurdle, M.; Cummings, M.; Gleeson, M.; Harris, M.; Jenkins, M.; Young, M.A.; Delatycki, M.; Wallis, M.; Burgess, M.; Price, M.; Brown, M.; Southey, M.; Bogwitz, M.; Field, M.; Friedlander, M.; Gattas, M.; Saleh, M.; Hayward, N.; Pachter, N.; Cohen, P.; Duijf, P.; James, P.; Simpson, P.; Fong, P.; Butow, P.; Williams, R.; Kefford, R.; Scott, R.; Milne, R.L.; Balleine, R.; Dawson, S.–J.; Lok, S.; O’Connell, S.; Greening, S.; Nightingale, S.; Edwards, S.; Fox, S.; McLachlan, S.-A.; Lakhani, S.; Antill, Y.; Aalfs, C.; Meijers-Heijboer, H.; van Engelen, K.; Gille, H.; Boere, I.; Collée, M.; van Deurzen, C.; Hooning, M.; Obdeijn, I.-M.; van den Ouweland, A.; Seynaeve, C.; Siesling, S.; Verloop, J.; van Asperen, C.J.; Devilee, P.; van Cronenburg, T.; Blok, R.; de Boer, M.; Garcia, E.G.; Adank, M.; Hogervorst, F.; Jenner, D.; van Leeuwen, F.; Rookus, M.; Russell, N.; Schmidt, M.; van den Belt-Dusebout, S.; Kets, C.; Mensenkamp, A.; de Bock, T.; van der Hout, A.; Mourits, M.; Oosterwijk, J.; Ausems, M.; Koudijs, M.; Clarke, C.; Marsh, D.; Scott, R.; Baxter, R.; Yip, D.; Carpenter, J.; Davis, A.; Pathmanathan, N.; Simpson, P.; Graham, D.; Sachchithananthan, M.; Isaacs, C.; Iwasaki, M.; Jager, A.; Jakimovska, M.; Jakubowska, A.; James, P.A.; Janavicius, R.; Jankowitz, R.C.; John, E.M.; Johnson, N.; Jones, M.E.; Jukkola-Vuorinen, A.; Jung, A.; Kaaks, R.; Kang, D.; Kapoor, P.M.; Karlan, B.Y.; Keeman, R.; Kerin, M.J.; Khusnutdinova, E.; Kiiski, J.I.; Kirk, J.; Kitahara, C.M.; Ko, Y.-D.; Konstantopoulou, I.; Kosma, V.-M.; Koutros, S.; Kubelka-Sabit, K.; Kwong, A.; Kyriacou, K.; Laitman, Y.; Lambrechts, D.; Lee, E.; Leslie, G.; Lester, J.; Lesueur, F.; Lindblom, A.; Lo, W.-Y.; Long, J.; Lophatananon, A.; Loud, J.T.; Lubiński, J.; MacInnis, R.J.; Maishman, T.; Makalic, E.; Mannermaa, A.; Manoochehri, M.; Manoukian, S.; Margolin, S.; Martinez, M.E.; Matsuo, K.; Maurer, T.; Mavroudis, D.; Mayes, R.; McGuffog, L.; McLean, C.; Mebirouk, N.; Meindl, A.; Miller, A.; Miller, N.; Montagna, M.; Moreno, F.; Muir, K.; Mulligan, A.M.; Muñoz-Garzon, V.M.; Muranen, T.A.; Narod, S.A.; Nassir, R.; Nathanson, K.L.; Neuhausen, S.L.; Nevanlinna, H.; Neven, P.; Nielsen, F.C.; Nikitina-Zake, L.; Norman, A.; Offit, K.; Olah, E.; Olopade, O.I.; Olsson, H.; Orr, N.; Osorio, A.; Pankratz, V.S.; Papp, J.; Park, S.K.; Park-Simon, T.-W.; Parsons, M.T.; Paul, J.; Pedersen, I.S.; Peissel, B.; Peshkin, B.; Peterlongo, P.; Peto, J.; Plaseska-Karanfilska, D.; Prajzendanc, K.; Prentice, R.; Presneau, N.; Prokofyeva, D.; Pujana, M.A.; Pylkäs, K.; Radice, P.; Ramus, S.J.; Rantala, J.; Rau-Murthy, R.; Rennert, G.; Risch, H.A.; Robson, M.; Romero, A.; Rossing, M.; Saloustros, E.; Sánchez-Herrero, E.; Sandler, D.P.; Santamariña, M.; Saunders, C.; Sawyer, E.J.; Scheuner, M.T.; Schmidt, D.F.; Schmutzler, R.K.; Schneeweiss, A.; Schoemaker, M.J.; Schöttker, B.; Schürmann, P.; Scott, C.; Scott, R.J.; Senter, L.; Seynaeve, C.M.; Shah, M.; Sharma, P.; Shen, C.-Y.; Shu, X.-O.; Singer, C.F.; Slavin, T.P.; Smichkoska, S.; Southey, M.C.; Spinelli, J.J.; Spurdle, A.B.; Stone, J.; Stoppa-Lyonnet, D.; Sutter, C.; Swerdlow, A.J.; Tamimi, R.M.; Tan, Y.Y.; Tapper, W.J.; Taylor, J.A.; Teixeira, M.R.; Tengström, M.; Teo, S.H.; Terry, M.B.; Teulé, A.; Thomassen, M.; Thull, D.L.; Tischkowitz, M.; Toland, A.E.; Tollenaar, R.A.E.M.; Tomlinson, I.; Torres, D.; Torres-Mejía, G.; Troester, M.A.; Truong, T.; Tung, N.; Tzardi, M.; Ulmer, H.-U.; Vachon, C.M.; van Asperen, C.J.; van der Kolk, L.E.; van Rensburg, E.J.; Vega, A.; Viel, A.; Vijai, J.; Vogel, M.J.; Wang, Q.; Wappenschmidt, B.; Weinberg, C.R.; Weitzel, J.N.; Wendt, C.; Wildiers, H.; Winqvist, R.; Wolk, A.; Wu, A.H.; Yannoukakos, D.; Zhang, Y.; Zheng, W.; Hunter, D.; Pharoah, P.D.P.; Chang-Claude, J.; García-Closas, M.; Schmidt, M.K.; Milne, R.L.; Kristensen, V.N.; French, J.D.; Edwards, S.L.; Antoniou, A.C.; Chenevix-Trench, G.; Simard, J.; Easton, D.F.; Kraft, P.; Dunning, A.M.; Collaborators, GEMO Study; Collaborators, EMBRACE; Investigators, KConFab; Investigators, HEBON; Investigators, ABCTB (2020)
    Fine-mapping of causal variants and integration of epigenetic and chromatin conformation data identify likely target genes for 150 breast cancer risk regions. Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
  • Mahajan, Anubha; Taliun, Daniel; Thurner, Matthias; Robertson, Neil R.; Torres, Jason M.; Rayner, N. William; Payne, Anthony J.; Steinthorsdottir, Valgerdur; Scott, Robert A.; Grarup, Niels; Cook, James P.; Schmidt, Ellen M.; Wuttke, Matthias; Sarnowski, Chloe; Magill, Reedik; Nano, Jana; Gieger, Christian; Trompet, Stella; Lecoeur, Cecile; Preuss, Michael H.; Prins, Bram Peter; Guo, Xiuqing; Bielak, Lawrence F.; Below, Jennifer E.; Bowden, Donald W.; Chambers, John Campbell; Kim, Young Jin; Ng, Maggie C. Y.; Petty, Lauren E.; Sim, Xueling; Zhang, Weihua; Bennett, Amanda J.; Bork-Jensen, Jette; Brummett, Chad M.; Canouil, Mickael; Kardt, Kai-Uwe Ec; Fischer, Krista; Kardia, Sharon L. R.; Kronenberg, Florian; Lall, Kristi; Liu, Ching-Ti; Locke, Adam E.; Luan, Jian'an; Ntalla, Loanna; Nylander, Vibe; Schoenherr, Sebastian; Schurmann, Claudia; Yengo, Loic; Bottinger, Erwin P.; Brandslund, Ivan; Christensen, Cramer; Dedoussis, George; Florez, Jose C.; Ford, Ian; France, Oscar H.; Frayling, Timothy M.; Giedraitis, Vilmantas; Hackinger, Sophie; Hattersley, Andrew T.; Herder, Christian; Ikram, M. Arfan; Ingelsson, Martin; Jorgensen, Marit E.; Jorgensen, Torben; Kriebel, Jennifer; Kuusisto, Johanna; Ligthart, Symen; Lindgren, Cecilia M.; Linneberg, Allan; Lyssenko, Valeriya; Mamakou, Vasiliki; Meitinger, Thomas; Mohlke, Karen L.; Morris, Andrew D.; Nadkarni, Girish; Pankow, James S.; Peters, Annette; Sattar, Naveed; Stancakova, Alena; Strauch, Konstantin; Taylor, Kent D.; Thorand, Barbara; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Tuomilehto, Jaakko; Witte, Daniel R.; Dupuis, Josee; Peyser, Patricia A.; Zeggini, Eleftheria; Loos, Ruth J. F.; Froguel, Philippe; Ingelsson, Erik; Lind, Lars; Groop, Leif; Laakso, Markku; Collins, Francis S.; Jukema, J. Wouter; Palmer, Colin N. A.; Grallert, Harald; Metspalu, Andres; Dehghan, Abbas; Koettgen, Anna; Abecasis, Goncalo R.; Meigs, James B.; Rotter, Jerome; Marchini, Jonathan; Pedersen, Oluf; Hansen, Torben; Langenberg, Claudia; Wareham, Nicholas J.; Stefansson, Kari; Gloyn, Anna L.; Morris, Andrew P.; Boehnke, Michael; McCarthy, Mark (2018)
    We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci,135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency 2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).
  • Glubb, Dylan M.; Maranian, Mel J.; Michailidou, Kyriaki; Pooley, Karen A.; Meyer, Kerstin B.; Kar, Siddhartha; Carlebur, Saskia; O'Reilly, Martin; Betts, Joshua A.; Hillman, Kristine M.; Kaufmann, Susanne; Beesley, Jonathan; Canisius, Sander; Hopper, John L.; Southey, Melissa C.; Tsimiklis, Helen; Apicella, Carmel; Schmidt, Marjanka K.; Broeks, Annegien; Hogervorst, Frans B.; van der Schoot, C. Ellen; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Fasching, Peter A.; Ruebner, Matthias; Ekici, Arif B.; Beckmann, Matthias W.; Peto, Julian; Dos-Santos-Silva, Isabel; Fletcher, Olivia; Johnson, Nichola; Pharoah, Paul D. P.; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Sawyer, Elinor J.; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Burwinkel, Barbara; Marme, Frederik; Yang, Rongxi; Surowy, Harald; Guenel, Pascal; Nevanlinna, Heli; Muranen, Taru A.; Aittomäki, Kristiina; Blomqvist, Carl; GENICA Network; KConFab Investigators; Norwegian Breast Canc Study (2015)
  • Eising, Else; Huisman, Sjoerd M. H.; Mahfouz, Ahmed; Vijfhuizen, Lisanne S.; Anttila, Verneri; Winsvold, Bendik S.; Kurth, Tobias; Ikram, M. Arfan; Freilinger, Tobias; Kaprio, Jaakko; Boomsma, Dorret I.; van Duijn, Cornelia M.; Jarvelin, Marjo-Riitta R.; Zwart, John-Anker; Quaye, Lydia; Strachan, David P.; Kubisch, Christian; Dichgans, Martin; Smith, George Davey; Stefansson, Kari; Palotie, Aarno; Chasman, Daniel I.; Ferrari, Michel D.; Terwindt, Gisela M.; de Vries, Boukje; Nyholt, Dale R.; Lelieveldt, Boudewijn P. F.; van den Maagdenberg, Arn M. J. M.; Reinders, Marcel J. T. (2016)
    Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology.
  • Zhao, Huiying; Eising, Else; de Vries, Boukje; Vijfhuizen, Lisanne S.; Anttila, Verneri; Winsvold, Bendik S.; Kurth, Tobias; Stefansson, Hreinn; Kallela, Kaarlo Mikko; Malik, Rainer; Stam, Anine H.; Ikram, M. Arfan; Ligthart, Lannie; Freilinger, Tobias; Alexander, Michael; Mueller-Myhsok, Bertram; Schreiber, Stefan; Meitinger, Thomas; Aromas, Arpo; Eriksson, Johan G.; Boomsma, Dorret I.; van Duijn, Cornelia M.; Zwart, John-Anker; Quaye, Lydia; Kubisch, Christian; Dichgans, Martin; Wessman, Maija; Stefansson, Kari; Chasman, Daniel I.; Palotie, Aarno; Martin, Nicholas G.; Montgomery, Grant W.; Ferrari, Michel D.; Terwindt, Gisela M.; van den Maagdenberg, Arn M. J. M.; Nyholt, Dale R.; Int Headache Genetics Consortium (2016)
    Introduction It is unclear whether patients diagnosed according to International Classification of Headache Disorders criteria for migraine with aura (MA) and migraine without aura (MO) experience distinct disorders or whether their migraine subtypes are genetically related. Aim Using a novel gene-based (statistical) approach, we aimed to identify individual genes and pathways associated both with MA and MO. Methods Gene-based tests were performed using genome-wide association summary statistic results from the most recent International Headache Genetics Consortium study comparing 4505 MA cases with 34,813 controls and 4038 MO cases with 40,294 controls. After accounting for non-independence of gene-based test results, we examined the significance of the proportion of shared genes associated with MA and MO. Results We found a significant overlap in genes associated with MA and MO. Of the total 1514 genes with a nominally significant gene-based p value (p(gene-based)0.05) in the MA subgroup, 107 also produced p(gene-based)0.05 in the MO subgroup. The proportion of overlapping genes is almost double the empirically derived null expectation, producing significant evidence of gene-based overlap (pleiotropy) (p(binomial-test) = 1.5x10(-4)). Combining results across MA and MO, six genes produced genome-wide significant gene-based p values. Four of these genes (TRPM8, UFL1, FHL5 and LRP1) were located in close proximity to previously reported genome-wide significant SNPs for migraine, while two genes, TARBP2 and NPFF separated by just 259bp on chromosome 12q13.13, represent a novel risk locus. The genes overlapping in both migraine types were enriched for functions related to inflammation, the cardiovascular system and connective tissue. Conclusions Our results provide novel insight into the likely genes and biological mechanisms that underlie both MA and MO, and when combined with previous data, highlight the neuropeptide FF-amide peptide encoding gene (NPFF) as a novel candidate risk gene for both types of migraine.
  • kConFab Investigators; NBCS Collaborators; Park, JooYong; Choi, Ji-Yeob; Choi, Jaesung; Blomqvist, Carl; Nevanlinna, Heli (2021)
    Simple Summary Breast cancer is the most common cancer in females worldwide. To date, many gene-environment interaction (GxE) studies have been conducted to better understand how genetic factors combine with environmental factors to influence risk. However, previous studies have not found or found only a few interactions by using SNPs which were discovered from genome-wide association studies and have been conducted, for the most part, within European populations. In this study, we focused on estrogen-related lifestyle factors that have been identified for breast cancer, including several well-established reproductive factors that are mediated by hormonal mechanisms. We aimed to examine whether there are any gene and environmental factor interactions related to estrogen exposure or metabolism using a candidate approach in Korean women. We found two interactions in this study, although they were not replicated in the independent large consortium data. These findings suggest specificity in Koreans for breast cancer risk. In this study we aim to examine gene-environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2 x 10(-3)). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (p-2df = 1.1 x 10(-4)). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.