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Your search keyword '"Gådin, Jesper R."' showing total 6 results
Start Over Author "Gådin, Jesper R." Topic genome-wide association study
6 results on '"Gådin, Jesper R."'

1. Comparison of quantitative trait loci methods: Total expression and allelic imbalance method in brain RNA-seq.

Author

Gådin JR, Buil A, Colantuoni C, Jaffe AE, Nielsen J, Shin JH, Hyde TM, Kleinman JE, Plath N, Eriksson P, Brunak S, Didriksen M, Weinberger DR, and Folkersen L

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Alleles, Child, Child, Preschool, Female, Genetic Predisposition to Disease genetics, Genotype, Humans, Infant, Infant, Newborn, Male, Middle Aged, Polymorphism, Single Nucleotide genetics, Schizophrenia genetics, Exome Sequencing methods, Young Adult, Allelic Imbalance genetics, Brain pathology, Genome-Wide Association Study methods, Quantitative Trait Loci genetics, RNA-Seq methods
Abstract

Background: Of the 108 Schizophrenia (SZ) risk-loci discovered through genome-wide association studies (GWAS), 96 are not altering the sequence of any protein. Evidence linking non-coding risk-SNPs and genes may be established using expression quantitative trait loci (eQTL). However, other approaches such allelic expression quantitative trait loci (aeQTL) also may be of use., Methods: We applied both the eQTL and aeQTL analysis to a biobank of deeply sequenced RNA from 680 dorso-lateral pre-frontal cortex (DLPFC) samples. For each of 340 genes proximal to the SZ risk-SNPs, we asked how much SNP-genotype affected total expression (eQTL), as well as how much the expression ratio between the two alleles differed from 1:1 as a consequence of the risk-SNP genotype (aeQTL)., Results: We analyzed overlap with comparable eQTL-findings: 16 of the 30 risk-SNPs known to have gene-level eQTL also had gene-level aeQTL effects. 6 of 21 risk-SNPs with known splice-eQTL had exon-aeQTL effects. 12 novel potential risk genes were identified with the aeQTL approach, while 55 tested SNP-pairs were found as eQTL but not aeQTL. Of the tested 108 loci we could find at least one gene to be associated with 21 of the risk-SNPs using gene-level aeQTL, and with an additional 18 risk-SNPs using exon-level aeQTL., Conclusion: Our results suggest that the aeQTL strategy complements the eQTL approach to susceptibility gene identification., Competing Interests: A consortium comprising The Lieber Institute for Brain Development, Pfizer, Lilly, Roche, Astra Zeneca, Astellas and Lundbeck paid for the material in the study. However, these companies had no influence over the conclusions of the study. The funding from Lundbeck A/S does not alter our adherence to PLOS ONE policies on sharing data and materials.

Published
2019
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2. Effects of the coronary artery disease associated LPA and 9p21 loci on risk of aortic valve stenosis.

Author

Trenkwalder T, Nelson CP, Musameh MD, Mordi IR, Kessler T, Pellegrini C, Debiec R, Rheude T, Lazovic V, Zeng L, Martinsson A, Gustav Smith J, Gådin JR, Franco-Cereceda A, Eriksson P, Nielsen JB, Graham SE, Willer CJ, Hveem K, Kastrati A, Braund PS, Palmer CNA, Aracil A, Husser O, Koenig W, Schunkert H, Lang CC, Hengstenberg C, and Samani NJ

Subjects
Aged, Aortic Valve Stenosis diagnosis, Case-Control Studies, Coronary Artery Disease diagnosis, Female, Genetic Predisposition to Disease genetics, Genetic Variation genetics, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide genetics, Aortic Valve Stenosis genetics, Chromosomes, Human, Pair 9 genetics, Coronary Artery Disease genetics, Genetic Loci genetics, Genome-Wide Association Study methods, Lipoprotein(a) genetics
Abstract

Background: Aortic valve stenosis (AVS) and coronary artery disease (CAD) have a significant genetic contribution and commonly co-exist. To compare and contrast genetic determinants of the two diseases, we investigated associations of the LPA and 9p21 loci, i.e. the two strongest CAD risk loci, with risk of AVS., Methods: We genotyped the CAD-associated variants at the LPA (rs10455872) and 9p21 loci (rs1333049) in the GeneCAST (Genetics of Calcific Aortic STenosis) Consortium and conducted a meta-analysis for their association with AVS. Cases and controls were stratified by CAD status. External validation of findings was undertaken in five cohorts including 7880 cases and 851,152 controls., Results: In the meta-analysis including 4651 cases and 8231 controls the CAD-associated allele at the LPA locus was associated with increased risk of AVS (OR 1.37; 95%CI 1.24-1.52, p = 6.9 × 10 -10 ) with a larger effect size in those without CAD (OR 1.53; 95%CI 1.31-1.79) compared to those with CAD (OR 1.27; 95%CI 1.12-1.45). The CAD-associated allele at 9p21 was associated with a trend towards lower risk of AVS (OR 0.93; 95%CI 0.88-0.99, p = 0.014). External validation confirmed the association of the LPA risk allele with risk of AVS (OR 1.37; 95%CI 1.27-1.47), again with a higher effect size in those without CAD. The small protective effect of the 9p21 CAD risk allele could not be replicated (OR 0.98; 95%CI 0.95-1.02)., Conclusions: Our study confirms the association of the LPA locus with risk of AVS, with a higher effect in those without concomitant CAD. Overall, 9p21 was not associated with AVS., (Copyright © 2018. Published by Elsevier B.V.)

Published
2019
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3. Genetic studies of body mass index yield new insights for obesity biology.

Author

Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, Powell C, Vedantam S, Buchkovich ML, Yang J, Croteau-Chonka DC, Esko T, Fall T, Ferreira T, Gustafsson S, Kutalik Z, Luan J, Mägi R, Randall JC, Winkler TW, Wood AR, Workalemahu T, Faul JD, Smith JA, Zhao JH, Zhao W, Chen J, Fehrmann R, Hedman ÅK, Karjalainen J, Schmidt EM, Absher D, Amin N, Anderson D, Beekman M, Bolton JL, Bragg-Gresham JL, Buyske S, Demirkan A, Deng G, Ehret GB, Feenstra B, Feitosa MF, Fischer K, Goel A, Gong J, Jackson AU, Kanoni S, Kleber ME, Kristiansson K, Lim U, Lotay V, Mangino M, Leach IM, Medina-Gomez C, Medland SE, Nalls MA, Palmer CD, Pasko D, Pechlivanis S, Peters MJ, Prokopenko I, Shungin D, Stančáková A, Strawbridge RJ, Sung YJ, Tanaka T, Teumer A, Trompet S, van der Laan SW, van Setten J, Van Vliet-Ostaptchouk JV, Wang Z, Yengo L, Zhang W, Isaacs A, Albrecht E, Ärnlöv J, Arscott GM, Attwood AP, Bandinelli S, Barrett A, Bas IN, Bellis C, Bennett AJ, Berne C, Blagieva R, Blüher M, Böhringer S, Bonnycastle LL, Böttcher Y, Boyd HA, Bruinenberg M, Caspersen IH, Chen YI, Clarke R, Daw EW, de Craen AJM, Delgado G, Dimitriou M, Doney ASF, Eklund N, Estrada K, Eury E, Folkersen L, Fraser RM, Garcia ME, Geller F, Giedraitis V, Gigante B, Go AS, Golay A, Goodall AH, Gordon SD, Gorski M, Grabe HJ, Grallert H, Grammer TB, Gräßler J, Grönberg H, Groves CJ, Gusto G, Haessler J, Hall P, Haller T, Hallmans G, Hartman CA, Hassinen M, Hayward C, Heard-Costa NL, Helmer Q, Hengstenberg C, Holmen O, Hottenga JJ, James AL, Jeff JM, Johansson Å, Jolley J, Juliusdottir T, Kinnunen L, Koenig W, Koskenvuo M, Kratzer W, Laitinen J, Lamina C, Leander K, Lee NR, Lichtner P, Lind L, Lindström J, Lo KS, Lobbens S, Lorbeer R, Lu Y, Mach F, Magnusson PKE, Mahajan A, McArdle WL, McLachlan S, Menni C, Merger S, Mihailov E, Milani L, Moayyeri A, Monda KL, Morken MA, Mulas A, Müller G, Müller-Nurasyid M, Musk AW, Nagaraja R, Nöthen MM, Nolte IM, Pilz S, Rayner NW, Renstrom F, Rettig R, Ried JS, Ripke S, Robertson NR, Rose LM, Sanna S, Scharnagl H, Scholtens S, Schumacher FR, Scott WR, Seufferlein T, Shi J, Smith AV, Smolonska J, Stanton AV, Steinthorsdottir V, Stirrups K, Stringham HM, Sundström J, Swertz MA, Swift AJ, Syvänen AC, Tan ST, Tayo BO, Thorand B, Thorleifsson G, Tyrer JP, Uh HW, Vandenput L, Verhulst FC, Vermeulen SH, Verweij N, Vonk JM, Waite LL, Warren HR, Waterworth D, Weedon MN, Wilkens LR, Willenborg C, Wilsgaard T, Wojczynski MK, Wong A, Wright AF, Zhang Q, Brennan EP, Choi M, Dastani Z, Drong AW, Eriksson P, Franco-Cereceda A, Gådin JR, Gharavi AG, Goddard ME, Handsaker RE, Huang J, Karpe F, Kathiresan S, Keildson S, Kiryluk K, Kubo M, Lee JY, Liang L, Lifton RP, Ma B, McCarroll SA, McKnight AJ, Min JL, Moffatt MF, Montgomery GW, Murabito JM, Nicholson G, Nyholt DR, Okada Y, Perry JRB, Dorajoo R, Reinmaa E, Salem RM, Sandholm N, Scott RA, Stolk L, Takahashi A, Tanaka T, van 't Hooft FM, Vinkhuyzen AAE, Westra HJ, Zheng W, Zondervan KT, Heath AC, Arveiler D, Bakker SJL, Beilby J, Bergman RN, Blangero J, Bovet P, Campbell H, Caulfield MJ, Cesana G, Chakravarti A, Chasman DI, Chines PS, Collins FS, Crawford DC, Cupples LA, Cusi D, Danesh J, de Faire U, den Ruijter HM, Dominiczak AF, Erbel R, Erdmann J, Eriksson JG, Farrall M, Felix SB, Ferrannini E, Ferrières J, Ford I, Forouhi NG, Forrester T, Franco OH, Gansevoort RT, Gejman PV, Gieger C, Gottesman O, Gudnason V, Gyllensten U, Hall AS, Harris TB, Hattersley AT, Hicks AA, Hindorff LA, Hingorani AD, Hofman A, Homuth G, Hovingh GK, Humphries SE, Hunt SC, Hyppönen E, Illig T, Jacobs KB, Jarvelin MR, Jöckel KH, Johansen B, Jousilahti P, Jukema JW, Jula AM, Kaprio J, Kastelein JJP, Keinanen-Kiukaanniemi SM, Kiemeney LA, Knekt P, Kooner JS, Kooperberg C, Kovacs P, Kraja AT, Kumari M, Kuusisto J, Lakka TA, Langenberg C, Marchand LL, Lehtimäki T, Lyssenko V, Männistö S, Marette A, Matise TC, McKenzie CA, McKnight B, Moll FL, Morris AD, Morris AP, Murray JC, Nelis M, Ohlsson C, Oldehinkel AJ, Ong KK, Madden PAF, Pasterkamp G, Peden JF, Peters A, Postma DS, Pramstaller PP, Price JF, Qi L, Raitakari OT, Rankinen T, Rao DC, Rice TK, Ridker PM, Rioux JD, Ritchie MD, Rudan I, Salomaa V, Samani NJ, Saramies J, Sarzynski MA, Schunkert H, Schwarz PEH, Sever P, Shuldiner AR, Sinisalo J, Stolk RP, Strauch K, Tönjes A, Trégouët DA, Tremblay A, Tremoli E, Virtamo J, Vohl MC, Völker U, Waeber G, Willemsen G, Witteman JC, Zillikens MC, Adair LS, Amouyel P, Asselbergs FW, Assimes TL, Bochud M, Boehm BO, Boerwinkle E, Bornstein SR, Bottinger EP, Bouchard C, Cauchi S, Chambers JC, Chanock SJ, Cooper RS, de Bakker PIW, Dedoussis G, Ferrucci L, Franks PW, Froguel P, Groop LC, Haiman CA, Hamsten A, Hui J, Hunter DJ, Hveem K, Kaplan RC, Kivimaki M, Kuh D, Laakso M, Liu Y, Martin NG, März W, Melbye M, Metspalu A, Moebus S, Munroe PB, Njølstad I, Oostra BA, Palmer CNA, Pedersen NL, Perola M, Pérusse L, Peters U, Power C, Quertermous T, Rauramaa R, Rivadeneira F, Saaristo TE, Saleheen D, Sattar N, Schadt EE, Schlessinger D, Slagboom PE, Snieder H, Spector TD, Thorsteinsdottir U, Stumvoll M, Tuomilehto J, Uitterlinden AG, Uusitupa M, van der Harst P, Walker M, Wallaschofski H, Wareham NJ, Watkins H, Weir DR, Wichmann HE, Wilson JF, Zanen P, Borecki IB, Deloukas P, Fox CS, Heid IM, O'Connell JR, Strachan DP, Stefansson K, van Duijn CM, Abecasis GR, Franke L, Frayling TM, McCarthy MI, Visscher PM, Scherag A, Willer CJ, Boehnke M, Mohlke KL, Lindgren CM, Beckmann JS, Barroso I, North KE, Ingelsson E, Hirschhorn JN, Loos RJF, and Speliotes EK

Subjects
Adipogenesis genetics, Adiposity genetics, Age Factors, Energy Metabolism genetics, Europe ethnology, Female, Genetic Predisposition to Disease genetics, Glutamic Acid metabolism, Humans, Insulin metabolism, Insulin Secretion, Male, Polymorphism, Single Nucleotide genetics, Quantitative Trait Loci genetics, Racial Groups genetics, Synapses metabolism, Body Mass Index, Genome-Wide Association Study, Obesity genetics, Obesity metabolism
Abstract

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Published
2015
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4. Genetic loci on chromosome 5 are associated with circulating levels of interleukin-5 and eosinophil count in a European population with high risk for cardiovascular disease

Author

McLeod, Olga, Silveira, Angela, Valdes-Marquez, Elsa, Björkbacka, Harry, Almgren, Peter, Gertow, Karl, Gådin, Jesper R., Bäcklund, Alexandra, Sennblad, Bengt, Baldassarre, Damiano, Veglia, Fabrizio, Humphries, Steve E., Tremoli, Elena, de Faire, Ulf, Nilsson, Jan, Melander, Olle, Hopewell, Jemma C., Clarke, Robert, Björck, Hanna M., Hamsten, Anders, Öhrvik, John, and Strawbridge, Rona J.

Subjects
Male, Intima-media thickness, Immunology, Gene Expression, IMT-Bifmax, max of IMT measures in the carotid bifurcation, Coronary Artery Disease, Carotid Intima-Media Thickness, Polymorphism, Single Nucleotide, Biochemistry, Article, IMT-CCmax, max of IMT measures in the common carotid, Leukocyte Count, Risk Factors, Genetics, Humans, Immunology and Allergy, Genetic Predisposition to Disease, cardiovascular diseases, Subclinical atherosclerosis, Molecular Biology, Aged, Chromosomes, Human, Pair 14, IL-5, Eosinophil count, Hematology, Middle Aged, Plaque, Atherosclerotic, IMT-Bifmean, mean of IMT measures in the carotid bifurcation, Acid Anhydride Hydrolases, DNA-Binding Proteins, Eosinophils, Europe, DNA Repair Enzymes, Genetics, Population, Genetic Loci, IMT-CCmean, mean of IMT measures in the common carotid, cardiovascular system, Linear Models, RAD50, IMTmean-max, mean of the maximum IMT measures along the entire carotid tree, Chromosomes, Human, Pair 5, Female, Interleukin-5, Genome-Wide Association Study
Abstract

Highlights • Two loci identified for IL-5 levels on chromosomes and 14. • One locus on chromosome 5 was identified for eosinophil count. • The chromosome 5 loci are in close proximity, but independent and non-overlapping. • IL-5-associated SNPs were not associated with carotid intima-media thickness. • Eosinophil-associated SNPs were not associated with carotid intima-media thickness., IL-5 is a Th2 cytokine which activates eosinophils and is suggested to have an atheroprotective role. Genetic variants in the IL5 locus have been associated with increased risk of CAD and ischemic stroke. In this study we aimed to identify genetic variants associated with IL-5 concentrations and apply a Mendelian randomisation approach to assess IL-5 levels for causal effect on intima-media thickness in a European population at high risk of coronary artery disease. We analysed SNPs within robustly associated candidate loci for immune, inflammatory, metabolic and cardiovascular traits. We identified 2 genetic loci for IL-5 levels (chromosome 5, rs56183820, BETA = 0.11, P = 6.73E−5 and chromosome 14, rs4902762, BETA = 0.12, P = 5.76E−6) and one for eosinophil count (rs72797327, BETA = −0.10, P = 1.41E−6). Both chromosome 5 loci were in the vicinity of the IL5 gene, however the association with IL-5 levels failed to replicate in a meta-analysis of 2 independent cohorts (rs56183820, BETA = 0.04, P = 0.2763, I2 = 24, I2 − P = 0.2516). No significant associations were observed between SNPs associated with IL-5 levels or eosinophil count and IMT measures. Expression quantitative trait analyses indicate effects of the IL-5 and eosinophil-associated SNPs on RAD50 mRNA expression levels (rs12652920 (r2 = 0.93 with rs56183820) BETA = −0.10, P = 8.64E−6 and rs11739623 (r2 = 0.96 with rs72797327) BETA = −0.23, P = 1.74E−29, respectively). Our data do not support a role for IL-5 levels and eosinophil count in intima-media thickness, however SNPs associated with IL-5 and eosinophils might influence stability of the atherosclerotic plaque via modulation of RAD50 levels.

Published
2016

5. Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author

Lagou, Vasiliki, Mägi, Reedik, Hottenga, Jouke-Jan, Grallert, Harald, Perry, John RB, Bouatia-Naji, Nabila, Marullo, Letizia, Rybin, Denis, Jansen, Rick, Min, Josine L, Dimas, Antigone S, Ulrich, Anna, Zudina, Liudmila, Gådin, Jesper R, Jiang, Longda, Faggian, Alessia, Bonnefond, Amélie, Fadista, Joao, Stathopoulou, Maria G, Isaacs, Aaron, Willems, Sara M, Navarro, Pau, Tanaka, Toshiko, Jackson, Anne U, Montasser, May E, O'Connell, Jeff R, Bielak, Lawrence F, Webster, Rebecca J, Saxena, Richa, Stafford, Jeanette M, Pourcain, Beate St, Timpson, Nicholas J, Salo, Perttu, Shin, So-Youn, Amin, Najaf, Smith, Albert V, Li, Guo, Verweij, Niek, Goel, Anuj, Ford, Ian, Johnson, Paul CD, Johnson, Toby, Kapur, Karen, Thorleifsson, Gudmar, Strawbridge, Rona J, Rasmussen-Torvik, Laura J, Esko, Tõnu, Mihailov, Evelin, Fall, Tove, Fraser, Ross M, Mahajan, Anubha, Kanoni, Stavroula, Giedraitis, Vilmantas, Kleber, Marcus E, Silbernagel, Günther, Meyer, Julia, Müller-Nurasyid, Martina, Ganna, Andrea, Sarin, Antti-Pekka, Yengo, Loic, Shungin, Dmitry, Luan, Jian'an, Horikoshi, Momoko, An, Ping, Sanna, Serena, Boettcher, Yvonne, Rayner, N William, Nolte, Ilja M, Zemunik, Tatijana, Iperen, Erik Van, Kovacs, Peter, Hastie, Nicholas D, Wild, Sarah H, McLachlan, Stela, Campbell, Susan, Polasek, Ozren, Carlson, Olga, Egan, Josephine, Kiess, Wieland, Willemsen, Gonneke, Kuusisto, Johanna, Laakso, Markku, Dimitriou, Maria, Hicks, Andrew A, Rauramaa, Rainer, Bandinelli, Stefania, Thorand, Barbara, Liu, Yongmei, Miljkovic, Iva, Lind, Lars, Doney, Alex, Perola, Markus, Hingorani, Aroon, Kivimaki, Mika, Kumari, Meena, Bennett, Amanda J, Groves, Christopher J, Herder, Christian, Koistinen, Heikki A, Kinnunen, Leena, Faire, Ulf De, Bakker, Stephan JL, Uusitupa, Matti, Palmer, Colin NA, Jukema, J Wouter, Sattar, Naveed, Pouta, Anneli, Snieder, Harold, Boerwinkle, Eric, Pankow, James S, Magnusson, Patrik K, Krus, Ulrika, Scapoli, Chiara, De Geus, Eco JCN, Blüher, Matthias, Wolffenbuttel, Bruce HR, Province, Michael A, Abecasis, Goncalo R, Meigs, James B, Hovingh, G Kees, Lindström, Jaana, Wilson, James F, Wright, Alan F, Dedoussis, George V, Bornstein, Stefan R, Schwarz, Peter EH, Tönjes, Anke, Winkelmann, Bernhard R, Boehm, Bernhard O, März, Winfried, Metspalu, Andres, Price, Jackie F, Deloukas, Panos, Körner, Antje, Lakka, Timo A, Keinanen-Kiukaanniemi, Sirkka M, Saaristo, Timo E, Bergman, Richard N, Tuomilehto, Jaakko, Wareham, Nicholas J, Langenberg, Claudia, Männistö, Satu, Franks, Paul W, Hayward, Caroline, Vitart, Veronique, Kaprio, Jaakko, Visvikis-Siest, Sophie, Balkau, Beverley, Altshuler, David, Rudan, Igor, Stumvoll, Michael, Campbell, Harry, Van Duijn, Cornelia M, Gieger, Christian, Illig, Thomas, Ferrucci, Luigi, Pedersen, Nancy L, Pramstaller, Peter P, Boehnke, Michael, Frayling, Timothy M, Shuldiner, Alan R, Peyser, Patricia A, Kardia, Sharon LR, Palmer, Lyle J, Penninx, Brenda W, Meneton, Pierre, Harris, Tamara B, Navis, Gerjan, Harst, Pim Van Der, Smith, George Davey, Forouhi, Nita G, Loos, Ruth JF, Salomaa, Veikko, Soranzo, Nicole, Boomsma, Dorret I, Groop, Leif, Tuomi, Tiinamaija, Hofman, Albert, Munroe, Patricia B, Gudnason, Vilmundur, Siscovick, David S, Watkins, Hugh, Lecoeur, Cecile, Vollenweider, Peter, Franco-Cereceda, Anders, Eriksson, Per, Jarvelin, Marjo-Riitta, Stefansson, Kari, Hamsten, Anders, Nicholson, George, Karpe, Fredrik, Dermitzakis, Emmanouil T, Lindgren, Cecilia M, McCarthy, Mark I, Froguel, Philippe, Kaakinen, Marika A, Lyssenko, Valeriya, Watanabe, Richard M, Ingelsson, Erik, Florez, Jose C, Dupuis, Josée, Barroso, Inês, Morris, Andrew P, Prokopenko, Inga, and Meta-Analyses Of Glucose And Insulin-Related Traits Consortium (MAGIC)

Subjects
Adult, Blood Glucose, Male, Sex Characteristics, Anorexia Nervosa, Waist-Hip Ratio, Kruppel-Like Transcription Factors, Gene Expression, Fasting, Middle Aged, White People, 3. Good health, Phenotype, Sex Factors, Genetic Loci, Glucose Intolerance, Insulin Receptor Substrate Proteins, Humans, Insulin, Female, Insulin Resistance, Genome-Wide Association Study
Abstract

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.

6. Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

Author

Folkersen, Lasse, Gustafsson, Stefan, Wang, Qin, Hansen, Daniel Hvidberg, Hedman, Åsa K, Schork, Andrew, Page, Karen, Zhernakova, Daria V, Wu, Yang, Peters, James, Eriksson, Niclas, Bergen, Sarah E, Boutin, Thibaud S, Bretherick, Andrew D, Enroth, Stefan, Kalnapenkis, Anette, Gådin, Jesper R, Suur, Bianca E, Chen, Yan, Matic, Ljubica, Gale, Jeremy D, Lee, Julie, Zhang, Weidong, Quazi, Amira, Ala-Korpela, Mika, Choi, Seung Hoan, Claringbould, Annique, Danesh, John, Davey Smith, George, De Masi, Federico, Elmståhl, Sölve, Engström, Gunnar, Fauman, Eric, Fernandez, Celine, Franke, Lude, Franks, Paul W, Giedraitis, Vilmantas, Haley, Chris, Hamsten, Anders, Ingason, Andres, Johansson, Åsa, Joshi, Peter K, Lind, Lars, Lindgren, Cecilia M, Lubitz, Steven, Palmer, Tom, Macdonald-Dunlop, Erin, Magnusson, Martin, Melander, Olle, Michaelsson, Karl, Morris, Andrew P, Mägi, Reedik, Nagle, Michael W, Nilsson, Peter M, Nilsson, Jan, Orho-Melander, Marju, Polasek, Ozren, Prins, Bram, Pålsson, Erik, Qi, Ting, Sjögren, Marketa, Sundström, Johan, Surendran, Praveen, Võsa, Urmo, Werge, Thomas, Wernersson, Rasmus, Westra, Harm-Jan, Yang, Jian, Zhernakova, Alexandra, Ärnlöv, Johan, Fu, Jingyuan, Smith, J Gustav, Esko, Tõnu, Hayward, Caroline, Gyllensten, Ulf, Landen, Mikael, Siegbahn, Agneta, Wilson, James F, Wallentin, Lars, Butterworth, Adam S, Holmes, Michael V, Ingelsson, Erik, and Mälarstig, Anders

Subjects
Proteome, Receptors, CCR5, Receptors, CCR2, Quantitative Trait Loci, Intracellular Signaling Peptides and Proteins, Chromosome Mapping, Genomics, Mendelian Randomization Analysis, Protein Serine-Threonine Kinases, Inflammatory Bowel Diseases, Cardiovascular System, Interleukin-1 Receptor-Like 1 Protein, Asthma, Linkage Disequilibrium, 3. Good health, Drug Delivery Systems, Gene Knockdown Techniques, Humans, ATP Binding Cassette Transporter 1, Genome-Wide Association Study
Abstract

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.

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