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1. A saturated map of common genetic variants associated with human height.

Author

Yengo L, Vedantam S, Marouli E, Sidorenko J, Bartell E, Sakaue S, Graff M, Eliasen AU, Jiang Y, Raghavan S, Miao J, Arias JD, Graham SE, Mukamel RE, Spracklen CN, Yin X, Chen SH, Ferreira T, Highland HH, Ji Y, Karaderi T, Lin K, Lüll K, Malden DE, Medina-Gomez C, Machado M, Moore A, Rüeger S, Sim X, Vrieze S, Ahluwalia TS, Akiyama M, Allison MA, Alvarez M, Andersen MK, Ani A, Appadurai V, Arbeeva L, Bhaskar S, Bielak LF, Bollepalli S, Bonnycastle LL, Bork-Jensen J, Bradfield JP, Bradford Y, Braund PS, Brody JA, Burgdorf KS, Cade BE, Cai H, Cai Q, Campbell A, Cañadas-Garre M, Catamo E, Chai JF, Chai X, Chang LC, Chang YC, Chen CH, Chesi A, Choi SH, Chung RH, Cocca M, Concas MP, Couture C, Cuellar-Partida G, Danning R, Daw EW, Degenhard F, Delgado GE, Delitala A, Demirkan A, Deng X, Devineni P, Dietl A, Dimitriou M, Dimitrov L, Dorajoo R, Ekici AB, Engmann JE, Fairhurst-Hunter Z, Farmaki AE, Faul JD, Fernandez-Lopez JC, Forer L, Francescatto M, Freitag-Wolf S, Fuchsberger C, Galesloot TE, Gao Y, Gao Z, Geller F, Giannakopoulou O, Giulianini F, Gjesing AP, Goel A, Gordon SD, Gorski M, Grove J, Guo X, Gustafsson S, Haessler J, Hansen TF, Havulinna AS, Haworth SJ, He J, Heard-Costa N, Hebbar P, Hindy G, Ho YA, Hofer E, Holliday E, Horn K, Hornsby WE, Hottenga JJ, Huang H, Huang J, Huerta-Chagoya A, Huffman JE, Hung YJ, Huo S, Hwang MY, Iha H, Ikeda DD, Isono M, Jackson AU, Jäger S, Jansen IE, Johansson I, Jonas JB, Jonsson A, Jørgensen T, Kalafati IP, Kanai M, Kanoni S, Kårhus LL, Kasturiratne A, Katsuya T, Kawaguchi T, Kember RL, Kentistou KA, Kim HN, Kim YJ, Kleber ME, Knol MJ, Kurbasic A, Lauzon M, Le P, Lea R, Lee JY, Leonard HL, Li SA, Li X, Li X, Liang J, Lin H, Lin SY, Liu J, Liu X, Lo KS, Long J, Lores-Motta L, Luan J, Lyssenko V, Lyytikäinen LP, Mahajan A, Mamakou V, Mangino M, Manichaikul A, Marten J, Mattheisen M, Mavarani L, McDaid AF, Meidtner K, Melendez TL, Mercader JM, Milaneschi Y, Miller JE, Millwood IY, Mishra PP, Mitchell RE, Møllehave LT, Morgan A, Mucha S, Munz M, Nakatochi M, Nelson CP, Nethander M, Nho CW, Nielsen AA, Nolte IM, Nongmaithem SS, Noordam R, Ntalla I, Nutile T, Pandit A, Christofidou P, Pärna K, Pauper M, Petersen ERB, Petersen LV, Pitkänen N, Polašek O, Poveda A, Preuss MH, Pyarajan S, Raffield LM, Rakugi H, Ramirez J, Rasheed A, Raven D, Rayner NW, Riveros C, Rohde R, Ruggiero D, Ruotsalainen SE, Ryan KA, Sabater-Lleal M, Saxena R, Scholz M, Sendamarai A, Shen B, Shi J, Shin JH, Sidore C, Sitlani CM, Slieker RC, Smit RAJ, Smith AV, Smith JA, Smyth LJ, Southam L, Steinthorsdottir V, Sun L, Takeuchi F, Tallapragada DSP, Taylor KD, Tayo BO, Tcheandjieu C, Terzikhan N, Tesolin P, Teumer A, Theusch E, Thompson DJ, Thorleifsson G, Timmers PRHJ, Trompet S, Turman C, Vaccargiu S, van der Laan SW, van der Most PJ, van Klinken JB, van Setten J, Verma SS, Verweij N, Veturi Y, Wang CA, Wang C, Wang L, Wang Z, Warren HR, Bin Wei W, Wickremasinghe AR, Wielscher M, Wiggins KL, Winsvold BS, Wong A, Wu Y, Wuttke M, Xia R, Xie T, Yamamoto K, Yang J, Yao J, Young H, Yousri NA, Yu L, Zeng L, Zhang W, Zhang X, Zhao JH, Zhao W, Zhou W, Zimmermann ME, Zoledziewska M, Adair LS, Adams HHH, Aguilar-Salinas CA, Al-Mulla F, Arnett DK, Asselbergs FW, Åsvold BO, Attia J, Banas B, Bandinelli S, Bennett DA, Bergler T, Bharadwaj D, Biino G, Bisgaard H, Boerwinkle E, Böger CA, Bønnelykke K, Boomsma DI, Børglum AD, Borja JB, Bouchard C, Bowden DW, Brandslund I, Brumpton B, Buring JE, Caulfield MJ, Chambers JC, Chandak GR, Chanock SJ, Chaturvedi N, Chen YI, Chen Z, Cheng CY, Christophersen IE, Ciullo M, Cole JW, Collins FS, Cooper RS, Cruz M, Cucca F, Cupples LA, Cutler MJ, Damrauer SM, Dantoft TM, de Borst GJ, de Groot LCPGM, De Jager PL, de Kleijn DPV, Janaka de Silva H, Dedoussis GV, den Hollander AI, Du S, Easton DF, Elders PJM, Eliassen AH, Ellinor PT, Elmståhl S, Erdmann J, Evans MK, Fatkin D, Feenstra B, Feitosa MF, Ferrucci L, Ford I, Fornage M, Franke A, Franks PW, Freedman BI, Gasparini P, Gieger C, Girotto G, Goddard ME, Golightly YM, Gonzalez-Villalpando C, Gordon-Larsen P, Grallert H, Grant SFA, Grarup N, Griffiths L, Gudnason V, Haiman C, Hakonarson H, Hansen T, Hartman CA, Hattersley AT, Hayward C, Heckbert SR, Heng CK, Hengstenberg C, Hewitt AW, Hishigaki H, Hoyng CB, Huang PL, Huang W, Hunt SC, Hveem K, Hyppönen E, Iacono WG, Ichihara S, Ikram MA, Isasi CR, Jackson RD, Jarvelin MR, Jin ZB, Jöckel KH, Joshi PK, Jousilahti P, Jukema JW, Kähönen M, Kamatani Y, Kang KD, Kaprio J, Kardia SLR, Karpe F, Kato N, Kee F, Kessler T, Khera AV, Khor CC, Kiemeney LALM, Kim BJ, Kim EK, Kim HL, Kirchhof P, Kivimaki M, Koh WP, Koistinen HA, Kolovou GD, Kooner JS, Kooperberg C, Köttgen A, Kovacs P, Kraaijeveld A, Kraft P, Krauss RM, Kumari M, Kutalik Z, Laakso M, Lange LA, Langenberg C, Launer LJ, Le Marchand L, Lee H, Lee NR, Lehtimäki T, Li H, Li L, Lieb W, Lin X, Lind L, Linneberg A, Liu CT, Liu J, Loeffler M, London B, Lubitz SA, Lye SJ, Mackey DA, Mägi R, Magnusson PKE, Marcus GM, Vidal PM, Martin NG, März W, Matsuda F, McGarrah RW, McGue M, McKnight AJ, Medland SE, Mellström D, Metspalu A, Mitchell BD, Mitchell P, Mook-Kanamori DO, Morris AD, Mucci LA, Munroe PB, Nalls MA, Nazarian S, Nelson AE, Neville MJ, Newton-Cheh C, Nielsen CS, Nöthen MM, Ohlsson C, Oldehinkel AJ, Orozco L, Pahkala K, Pajukanta P, Palmer CNA, Parra EJ, Pattaro C, Pedersen O, Pennell CE, Penninx BWJH, Perusse L, Peters A, Peyser PA, Porteous DJ, Posthuma D, Power C, Pramstaller PP, Province MA, Qi Q, Qu J, Rader DJ, Raitakari OT, Ralhan S, Rallidis LS, Rao DC, Redline S, Reilly DF, Reiner AP, Rhee SY, Ridker PM, Rienstra M, Ripatti S, Ritchie MD, Roden DM, Rosendaal FR, Rotter JI, Rudan I, Rutters F, Sabanayagam C, Saleheen D, Salomaa V, Samani NJ, Sanghera DK, Sattar N, Schmidt B, Schmidt H, Schmidt R, Schulze MB, Schunkert H, Scott LJ, Scott RJ, Sever P, Shiroma EJ, Shoemaker MB, Shu XO, Simonsick EM, Sims M, Singh JR, Singleton AB, Sinner MF, Smith JG, Snieder H, Spector TD, Stampfer MJ, Stark KJ, Strachan DP, 't Hart LM, Tabara Y, Tang H, Tardif JC, Thanaraj TA, Timpson NJ, Tönjes A, Tremblay A, Tuomi T, Tuomilehto J, Tusié-Luna MT, Uitterlinden AG, van Dam RM, van der Harst P, Van der Velde N, van Duijn CM, van Schoor NM, Vitart V, Völker U, Vollenweider P, Völzke H, Wacher-Rodarte NH, Walker M, Wang YX, Wareham NJ, Watanabe RM, Watkins H, Weir DR, Werge TM, Widen E, Wilkens LR, Willemsen G, Willett WC, Wilson JF, Wong TY, Woo JT, Wright AF, Wu JY, Xu H, Yajnik CS, Yokota M, Yuan JM, Zeggini E, Zemel BS, Zheng W, Zhu X, Zmuda JM, Zonderman AB, Zwart JA, Chasman DI, Cho YS, Heid IM, McCarthy MI, Ng MCY, O'Donnell CJ, Rivadeneira F, Thorsteinsdottir U, Sun YV, Tai ES, Boehnke M, Deloukas P, Justice AE, Lindgren CM, Loos RJF, Mohlke KL, North KE, Stefansson K, Walters RG, Winkler TW, Young KL, Loh PR, Yang J, Esko T, Assimes TL, Auton A, Abecasis GR, Willer CJ, Locke AE, Berndt SI, Lettre G, Frayling TM, Okada Y, Wood AR, Visscher PM, and Hirschhorn JN

Subjects
Humans, Gene Frequency genetics, Genome, Human genetics, Genome-Wide Association Study, Haplotypes genetics, Linkage Disequilibrium genetics, Europe ethnology, Sample Size, Phenotype, Body Height genetics, Polymorphism, Single Nucleotide genetics, Chromosome Mapping
Abstract

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes 1 . Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel 2 ) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries., (© 2022. The Author(s).)

Published
2022
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2. Effect of Genetically Low 25-Hydroxyvitamin D on Mortality Risk: Mendelian Randomization Analysis in 3 Large European Cohorts.

Author

Aspelund T, Grübler MR, Smith AV, Gudmundsson EF, Keppel M, Cotch MF, Harris TB, Jorde R, Grimnes G, Joakimsen R, Schirmer H, Wilsgaard T, Mathiesen EB, Njølstad I, Løchen ML, März W, Kleber ME, Tomaschitz A, Grove-Laugesen D, Rejnmark L, Swart KMA, Brouwer IA, Lips P, van Schoor NM, Sempos CT, Durazo-Arvizu RA, Škrabáková Z, Dowling KG, Cashman KD, Kiely M, Pilz S, Gudnason V, and Eiriksdottir G

Subjects
Aged, Aged, 80 and over, Carbon-Nitrogen Ligases with Glutamine as Amide-N-Donor genetics, Carbon-Nitrogen Ligases with Glutamine as Amide-N-Donor metabolism, Cholestanetriol 26-Monooxygenase genetics, Cholestanetriol 26-Monooxygenase metabolism, Cohort Studies, Cytochrome P450 Family 2 genetics, Cytochrome P450 Family 2 metabolism, Europe, Female, Gene Expression Regulation, Humans, Male, Middle Aged, Mortality, Oxidoreductases Acting on CH-CH Group Donors genetics, Oxidoreductases Acting on CH-CH Group Donors metabolism, Polymorphism, Single Nucleotide, Vitamin D blood, Genetic Predisposition to Disease, Mendelian Randomization Analysis, Vitamin D analogs & derivatives
Abstract

The aim of this study was to determine if increased mortality associated with low levels of serum 25-hydroxyvitamin D (25(OH)D) reflects a causal relationship by using a Mendelian randomisation (MR) approach with genetic variants in the vitamin D synthesis pathway. Individual participant data from three European cohorts were harmonized with standardization of 25(OH)D according to the Vitamin D Standardization Program. Most relevant single nucleotide polymorphisms of the genes CYP2R1 (rs12794714, rs10741657) and DHCR7/NADSYN1 (rs12785878, rs11234027), were combined in two allelic scores. Cox proportional hazards regression models were used with the ratio estimator and the delta method for calculating the hazards ratio (HR) and standard error of genetically determined 25(OH)D effect on all-cause mortality. We included 10,501 participants (50.1% females, 67.1±10.1 years) of whom 4003 died during a median follow-up of 10.4 years. The observed adjusted HR for all-cause mortality per decrease in 25(OH)D by 20 nmol/L was 1.20 (95% CI: 1.15⁻1.25). The HR per 20 nmol/L decrease in genetically determined 25(OH)D was 1.32 (95% CI: 0.80⁻2.24) and 1.35 (95% CI of 0.81 to 2.37) based on the two scores. In conclusion, the results of this MR study in a combined sample from three European cohort studies provide further support for a causal relationship between vitamin D deficiency and increased all-cause mortality. However, as the current study, even with ~10,000 participants, was underpowered for the study of the effect of the allele score on mortality, larger studies on genetics and mortality are needed to improve the precision.

Published
2019
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3. Cardiovascular mortality attributable to dietary risk factors in 51 countries in the WHO European Region from 1990 to 2016: a systematic analysis of the Global Burden of Disease Study.

Author

Meier T, Gräfe K, Senn F, Sur P, Stangl GI, Dawczynski C, März W, Kleber ME, and Lorkowski S

Subjects
Adult, Aged, Aged, 80 and over, Cardiovascular Diseases prevention & control, Diet, Healthy, Europe epidemiology, Female, Global Burden of Disease, Humans, Male, Middle Aged, Mortality, Premature, Risk Factors, Cardiovascular Diseases mortality, Diet adverse effects
Abstract

This study was performed to highlight the relationship between single dietary risk factors and cardiovascular diseases (CVDs) in the WHO European Region. We used the comparative risk assessment framework of the Global Burden of Disease Study to estimate CVD mortality attributable to diet; comprising eleven forms of CVDs, twelve food and nutrient groups and 27 risk-outcome pairs in four GBD regions including 51 countries by age and sex between 1990 and 2016. In 2016, dietary risks were associated with 2.1 million cardiovascular deaths (95% uncertainty interval (UI), 1.7-2.5 million) in the WHO European Region, accounting for 22.4% of all deaths and 49.2% of CVD deaths. In terms of single dietary risks, a diet low in whole grains accounted for approximately 429,000 deaths, followed by a diet low in nuts and seeds (341,000 deaths), a diet low in fruits (262,000 deaths), a diet high in sodium (251,000 deaths), and a diet low in omega-3 fatty acids (227,000 deaths). Thus, with an optimized, i.e. balanced diet, roughly one in every five premature deaths could be prevented. Although age-standardized death rates decreased over the last 26 years, the absolute number of diet-related cardiovascular deaths increased between 2010 and 2016 by 25,600 deaths in Western Europe and by 4300 deaths in Central Asia. In 2016, approximately 601,000 deaths (28.6% of all diet-related CVD deaths) occurred among adults younger than 70 years. Compared to other behavioural risk factors, a balanced diet is a potential key lever to avoid premature deaths.

Published
2019
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4. 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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5. New genetic loci link adipose and insulin biology to body fat distribution.

Author

Shungin D, Winkler TW, Croteau-Chonka DC, Ferreira T, Locke AE, Mägi R, Strawbridge RJ, Pers TH, Fischer K, Justice AE, Workalemahu T, Wu JMW, Buchkovich ML, Heard-Costa NL, Roman TS, Drong AW, Song C, Gustafsson S, Day FR, Esko T, Fall T, Kutalik Z, Luan J, Randall JC, Scherag A, Vedantam S, Wood AR, Chen J, Fehrmann R, Karjalainen J, Kahali B, Liu CT, Schmidt EM, Absher D, Amin N, Anderson D, Beekman M, Bragg-Gresham JL, Buyske S, Demirkan A, Ehret GB, Feitosa MF, Goel A, Jackson AU, Johnson T, Kleber ME, Kristiansson K, Mangino M, Leach IM, Medina-Gomez C, Palmer CD, Pasko D, Pechlivanis S, Peters MJ, Prokopenko I, Stančáková A, Sung YJ, Tanaka T, Teumer A, Van Vliet-Ostaptchouk JV, Yengo L, Zhang W, Albrecht E, Ärnlöv J, Arscott GM, Bandinelli S, Barrett A, Bellis C, Bennett AJ, Berne C, Blüher M, Böhringer S, Bonnet F, Böttcher Y, Bruinenberg M, Carba DB, Caspersen IH, Clarke R, Daw EW, Deelen J, Deelman E, Delgado G, Doney AS, Eklund N, Erdos MR, Estrada K, Eury E, Friedrich N, Garcia ME, Giedraitis V, Gigante B, Go AS, Golay A, Grallert H, Grammer TB, Gräßler J, Grewal J, Groves CJ, Haller T, Hallmans G, Hartman CA, Hassinen M, Hayward C, Heikkilä K, Herzig KH, Helmer Q, Hillege HL, Holmen O, Hunt SC, Isaacs A, Ittermann T, James AL, Johansson I, Juliusdottir T, Kalafati IP, Kinnunen L, Koenig W, Kooner IK, Kratzer W, Lamina C, Leander K, Lee NR, Lichtner P, Lind L, Lindström J, Lobbens S, Lorentzon M, Mach F, Magnusson PK, Mahajan A, McArdle WL, Menni C, Merger S, Mihailov E, Milani L, Mills R, Moayyeri A, Monda KL, Mooijaart SP, Mühleisen TW, Mulas A, Müller G, Müller-Nurasyid M, Nagaraja R, Nalls MA, Narisu N, Glorioso N, Nolte IM, Olden M, Rayner NW, Renstrom F, Ried JS, Robertson NR, Rose LM, Sanna S, Scharnagl H, Scholtens S, Sennblad B, Seufferlein T, Sitlani CM, Smith AV, Stirrups K, Stringham HM, Sundström J, Swertz MA, Swift AJ, Syvänen AC, Tayo BO, Thorand B, Thorleifsson G, Tomaschitz A, Troffa C, van Oort FV, Verweij N, Vonk JM, Waite LL, Wennauer R, Wilsgaard T, Wojczynski MK, Wong A, Zhang Q, Zhao JH, Brennan EP, Choi M, Eriksson P, Folkersen L, Franco-Cereceda A, Gharavi AG, Hedman ÅK, Hivert MF, Huang J, Kanoni S, Karpe F, Keildson S, Kiryluk K, Liang L, Lifton RP, Ma B, McKnight AJ, McPherson R, Metspalu A, Min JL, Moffatt MF, Montgomery GW, Murabito JM, Nicholson G, Nyholt DR, Olsson C, Perry JR, Reinmaa E, Salem RM, Sandholm N, Schadt EE, Scott RA, Stolk L, Vallejo EE, Westra HJ, Zondervan KT, Amouyel P, Arveiler D, Bakker SJ, Beilby J, Bergman RN, Blangero J, Brown MJ, Burnier M, Campbell H, Chakravarti A, Chines PS, Claudi-Boehm S, Collins FS, Crawford DC, Danesh J, de Faire U, de Geus EJ, Dörr M, Erbel R, Eriksson JG, Farrall M, Ferrannini E, Ferrières J, Forouhi NG, Forrester T, Franco OH, Gansevoort RT, Gieger C, Gudnason V, Haiman CA, Harris TB, Hattersley AT, Heliövaara M, Hicks AA, Hingorani AD, Hoffmann W, Hofman A, Homuth G, Humphries SE, Hyppönen E, Illig T, Jarvelin MR, Johansen B, Jousilahti P, Jula AM, Kaprio J, Kee F, Keinanen-Kiukaanniemi SM, Kooner JS, Kooperberg C, Kovacs P, Kraja AT, Kumari M, Kuulasmaa K, Kuusisto J, Lakka TA, Langenberg C, Le Marchand L, Lehtimäki T, Lyssenko V, Männistö S, Marette A, Matise TC, McKenzie CA, McKnight B, Musk AW, Möhlenkamp S, Morris AD, Nelis M, Ohlsson C, Oldehinkel AJ, Ong KK, Palmer LJ, Penninx BW, Peters A, Pramstaller PP, Raitakari OT, Rankinen T, Rao DC, Rice TK, Ridker PM, Ritchie MD, Rudan I, Salomaa V, Samani NJ, Saramies J, Sarzynski MA, Schwarz PE, Shuldiner AR, Staessen JA, Steinthorsdottir V, Stolk RP, Strauch K, Tönjes A, Tremblay A, Tremoli E, Vohl MC, Völker U, Vollenweider P, Wilson JF, Witteman JC, Adair LS, Bochud M, Boehm BO, Bornstein SR, Bouchard C, Cauchi S, Caulfield MJ, Chambers JC, Chasman DI, Cooper RS, Dedoussis G, Ferrucci L, Froguel P, Grabe HJ, Hamsten A, Hui J, Hveem K, Jöckel KH, Kivimaki M, Kuh D, Laakso M, Liu Y, März W, Munroe PB, Njølstad I, Oostra BA, Palmer CN, Pedersen NL, Perola M, Pérusse L, Peters U, Power C, Quertermous T, Rauramaa R, Rivadeneira F, Saaristo TE, Saleheen D, Sinisalo J, Slagboom PE, Snieder H, Spector TD, Stefansson K, Stumvoll M, Tuomilehto J, Uitterlinden AG, Uusitupa M, van der Harst P, Veronesi G, Walker M, Wareham NJ, Watkins H, Wichmann HE, Abecasis GR, Assimes TL, Berndt SI, Boehnke M, Borecki IB, Deloukas P, Franke L, Frayling TM, Groop LC, Hunter DJ, Kaplan RC, O'Connell JR, Qi L, Schlessinger D, Strachan DP, Thorsteinsdottir U, van Duijn CM, Willer CJ, Visscher PM, Yang J, Hirschhorn JN, Zillikens MC, McCarthy MI, Speliotes EK, North KE, Fox CS, Barroso I, Franks PW, Ingelsson E, Heid IM, Loos RJ, Cupples LA, Morris AP, Lindgren CM, and Mohlke KL

Subjects
Adipocytes metabolism, Adipogenesis genetics, Age Factors, Body Mass Index, Epigenesis, Genetic, Europe ethnology, Female, Genome, Human genetics, Humans, Insulin Resistance genetics, Male, Models, Biological, Neovascularization, Physiologic genetics, Obesity genetics, Polymorphism, Single Nucleotide genetics, Racial Groups genetics, Sex Characteristics, Transcription, Genetic genetics, Waist-Hip Ratio, Adipose Tissue metabolism, Body Fat Distribution, Genome-Wide Association Study, Insulin metabolism, Quantitative Trait Loci genetics
Abstract

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

Published
2015
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6. Genome-wide association study for circulating tissue plasminogen activator levels and functional follow-up implicates endothelial STXBP5 and STX2.

Author

Huang J, Huffman JE, Yamakuchi M, Trompet S, Asselbergs FW, Sabater-Lleal M, Trégouët DA, Chen WM, Smith NL, Kleber ME, Shin SY, Becker DM, Tang W, Dehghan A, Johnson AD, Truong V, Folkersen L, Yang Q, Oudot-Mellkah T, Buckley BM, Moore JH, Williams FM, Campbell H, Silbernagel G, Vitart V, Rudan I, Tofler GH, Navis GJ, Destefano A, Wright AF, Chen MH, de Craen AJ, Worrall BB, Rudnicka AR, Rumley A, Bookman EB, Psaty BM, Chen F, Keene KL, Franco OH, Böhm BO, Uitterlinden AG, Carter AM, Jukema JW, Sattar N, Bis JC, Ikram MA, Sale MM, McKnight B, Fornage M, Ford I, Taylor K, Slagboom PE, McArdle WL, Hsu FC, Franco-Cereceda A, Goodall AH, Yanek LR, Furie KL, Cushman M, Hofman A, Witteman JC, Folsom AR, Basu S, Matijevic N, van Gilst WH, Wilson JF, Westendorp RG, Kathiresan S, Reilly MP, Tracy RP, Polasek O, Winkelmann BR, Grant PJ, Hillege HL, Cambien F, Stott DJ, Lowe GD, Spector TD, Meigs JB, Marz W, Eriksson P, Becker LC, Morange PE, Soranzo N, Williams SM, Hayward C, van der Harst P, Hamsten A, Lowenstein CJ, Strachan DP, and O'Donnell CJ

Subjects
Aged, Cells, Cultured, Coronary Artery Disease blood, Coronary Artery Disease enzymology, Coronary Artery Disease genetics, Europe, Female, Gene Expression Regulation, Gene Silencing, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Nerve Tissue Proteins genetics, Phenotype, Polymorphism, Single Nucleotide, R-SNARE Proteins genetics, Risk Factors, Stroke blood, Stroke enzymology, Stroke genetics, Syntaxin 1 genetics, Tissue Plasminogen Activator genetics, Transfection, United States, Up-Regulation, Endothelial Cells enzymology, Nerve Tissue Proteins metabolism, R-SNARE Proteins metabolism, Syntaxin 1 metabolism, Tissue Plasminogen Activator blood
Abstract

Objective: Tissue plasminogen activator (tPA), a serine protease, catalyzes the conversion of plasminogen to plasmin, the major enzyme responsible for endogenous fibrinolysis. In some populations, elevated plasma levels of tPA have been associated with myocardial infarction and other cardiovascular diseases. We conducted a meta-analysis of genome-wide association studies to identify novel correlates of circulating levels of tPA., Approach and Results: Fourteen cohort studies with tPA measures (N=26 929) contributed to the meta-analysis. Three loci were significantly associated with circulating tPA levels (P<5.0×10(-8)). The first locus is on 6q24.3, with the lead single nucleotide polymorphism (SNP; rs9399599; P=2.9×10(-14)) within STXBP5. The second locus is on 8p11.21. The lead SNP (rs3136739; P=1.3×10(-9)) is intronic to POLB and <200 kb away from the tPA encoding the gene PLAT. We identified a nonsynonymous SNP (rs2020921) in modest linkage disequilibrium with rs3136739 (r(2)=0.50) within exon 5 of PLAT (P=2.0×10(-8)). The third locus is on 12q24.33, with the lead SNP (rs7301826; P=1.0×10(-9)) within intron 7 of STX2. We further found evidence for the association of lead SNPs in STXBP5 and STX2 with expression levels of the respective transcripts. In in vitro cell studies, silencing STXBP5 decreased the release of tPA from vascular endothelial cells, whereas silencing STX2 increased the tPA release. Through an in silico lookup, we found no associations of the 3 lead SNPs with coronary artery disease or stroke., Conclusions: We identified 3 loci associated with circulating tPA levels, the PLAT region, STXBP5, and STX2. Our functional studies implicate a novel role for STXBP5 and STX2 in regulating tPA release.

Published
2014
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7. Novel genetic markers associate with atrial fibrillation risk in Europeans and Japanese.

Author

Lubitz SA, Lunetta KL, Lin H, Arking DE, Trompet S, Li G, Krijthe BP, Chasman DI, Barnard J, Kleber ME, Dörr M, Ozaki K, Smith AV, Müller-Nurasyid M, Walter S, Agarwal SK, Bis JC, Brody JA, Chen LY, Everett BM, Ford I, Franco OH, Harris TB, Hofman A, Kääb S, Mahida S, Kathiresan S, Kubo M, Launer LJ, MacFarlane PW, Magnani JW, McKnight B, McManus DD, Peters A, Psaty BM, Rose LM, Rotter JI, Silbernagel G, Smith JD, Sotoodehnia N, Stott DJ, Taylor KD, Tomaschitz A, Tsunoda T, Uitterlinden AG, Van Wagoner DR, Völker U, Völzke H, Murabito JM, Sinner MF, Gudnason V, Felix SB, März W, Chung M, Albert CM, Stricker BH, Tanaka T, Heckbert SR, Jukema JW, Alonso A, Benjamin EJ, and Ellinor PT

Subjects
Adult, Aged, Aged, 80 and over, Asian People genetics, Chromosome Mapping, Europe, Female, Genetic Markers, Homeodomain Proteins genetics, Humans, Japan, Male, Middle Aged, Polymorphism, Single Nucleotide, Transcription Factors genetics, White People genetics, Homeobox Protein PITX2, Atrial Fibrillation genetics, Chromosomes, Human, Pair 4, Genetic Predisposition to Disease ethnology
Abstract

Objectives: This study sought to identify nonredundant atrial fibrillation (AF) genetic susceptibility signals and examine their cumulative relations with AF risk., Background: AF-associated loci span broad genomic regions that may contain multiple susceptibility signals. Whether multiple signals exist at AF loci has not been systematically explored., Methods: We performed association testing conditioned on the most significant, independently associated genetic markers at 9 established AF loci using 2 complementary techniques in 64,683 individuals of European ancestry (3,869 incident and 3,302 prevalent AF cases). Genetic risk scores were created and tested for association with AF in Europeans and an independent sample of 11,309 individuals of Japanese ancestry (7,916 prevalent AF cases)., Results: We observed at least 4 distinct AF susceptibility signals on chromosome 4q25 upstream of PITX2, but not at the remaining 8 AF loci. A multilocus score comprised 12 genetic markers demonstrated an estimated 5-fold gradient in AF risk. We observed a similar spectrum of risk associated with these markers in Japanese. Regions containing AF signals on chromosome 4q25 displayed a greater degree of evolutionary conservation than the remainder of the locus, suggesting that they may tag regulatory elements., Conclusions: The chromosome 4q25 AF locus is architecturally complex and harbors at least 4 AF susceptibility signals in individuals of European ancestry. Similar polygenic AF susceptibility exists between Europeans and Japanese. Future work is necessary to identify causal variants, determine mechanisms by which associated loci predispose to AF, and explore whether AF susceptibility signals classify individuals at risk for AF and related morbidity., (Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Published
2014
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8. Gene-centric meta-analysis in 87,736 individuals of European ancestry identifies multiple blood-pressure-related loci.

Author

Tragante V, Barnes MR, Ganesh SK, Lanktree MB, Guo W, Franceschini N, Smith EN, Johnson T, Holmes MV, Padmanabhan S, Karczewski KJ, Almoguera B, Barnard J, Baumert J, Chang YP, Elbers CC, Farrall M, Fischer ME, Gaunt TR, Gho JM, Gieger C, Goel A, Gong Y, Isaacs A, Kleber ME, Mateo Leach I, McDonough CW, Meijs MF, Melander O, Nelson CP, Nolte IM, Pankratz N, Price TS, Shaffer J, Shah S, Tomaszewski M, van der Most PJ, Van Iperen EP, Vonk JM, Witkowska K, Wong CO, Zhang L, Beitelshees AL, Berenson GS, Bhatt DL, Brown M, Burt A, Cooper-DeHoff RM, Connell JM, Cruickshanks KJ, Curtis SP, Davey-Smith G, Delles C, Gansevoort RT, Guo X, Haiqing S, Hastie CE, Hofker MH, Hovingh GK, Kim DS, Kirkland SA, Klein BE, Klein R, Li YR, Maiwald S, Newton-Cheh C, O'Brien ET, Onland-Moret NC, Palmas W, Parsa A, Penninx BW, Pettinger M, Vasan RS, Ranchalis JE, M Ridker P, Rose LM, Sever P, Shimbo D, Steele L, Stolk RP, Thorand B, Trip MD, van Duijn CM, Verschuren WM, Wijmenga C, Wyatt S, Young JH, Zwinderman AH, Bezzina CR, Boerwinkle E, Casas JP, Caulfield MJ, Chakravarti A, Chasman DI, Davidson KW, Doevendans PA, Dominiczak AF, FitzGerald GA, Gums JG, Fornage M, Hakonarson H, Halder I, Hillege HL, Illig T, Jarvik GP, Johnson JA, Kastelein JJ, Koenig W, Kumari M, März W, Murray SS, O'Connell JR, Oldehinkel AJ, Pankow JS, Rader DJ, Redline S, Reilly MP, Schadt EE, Kottke-Marchant K, Snieder H, Snyder M, Stanton AV, Tobin MD, Uitterlinden AG, van der Harst P, van der Schouw YT, Samani NJ, Watkins H, Johnson AD, Reiner AP, Zhu X, de Bakker PI, Levy D, Asselbergs FW, Munroe PB, and Keating BJ

Subjects
Arterial Pressure, Computational Biology methods, Europe, Genetic Loci, Genome-Wide Association Study, Genotype, Humans, Phenotype, Polymorphism, Single Nucleotide, Quality Control, Quantitative Trait Loci, Risk Factors, Blood Pressure, Diastole, Genetics, Population, Systole, White People genetics
Abstract

Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ~50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10(-7)) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification., (Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2014
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9. Causal relationship between obesity and vitamin D status: bi-directional Mendelian randomization analysis of multiple cohorts.

Author

Vimaleswaran KS, Berry DJ, Lu C, Tikkanen E, Pilz S, Hiraki LT, Cooper JD, Dastani Z, Li R, Houston DK, Wood AR, Michaëlsson K, Vandenput L, Zgaga L, Yerges-Armstrong LM, McCarthy MI, Dupuis J, Kaakinen M, Kleber ME, Jameson K, Arden N, Raitakari O, Viikari J, Lohman KK, Ferrucci L, Melhus H, Ingelsson E, Byberg L, Lind L, Lorentzon M, Salomaa V, Campbell H, Dunlop M, Mitchell BD, Herzig KH, Pouta A, Hartikainen AL, Streeten EA, Theodoratou E, Jula A, Wareham NJ, Ohlsson C, Frayling TM, Kritchevsky SB, Spector TD, Richards JB, Lehtimäki T, Ouwehand WH, Kraft P, Cooper C, März W, Power C, Loos RJ, Wang TJ, Järvelin MR, Whittaker JC, Hingorani AD, and Hyppönen E

Subjects
Adult, Aged, Aged, 80 and over, Biomarkers blood, Body Mass Index, Europe, Evidence-Based Medicine, Female, Genetic Predisposition to Disease, Humans, Linear Models, Male, Middle Aged, Multivariate Analysis, North America, Obesity diagnosis, Obesity ethnology, Obesity therapy, Phenotype, Risk Assessment, Risk Factors, Vitamin D analogs & derivatives, Vitamin D blood, Vitamin D Deficiency diagnosis, Vitamin D Deficiency ethnology, Vitamin D Deficiency prevention & control, White People genetics, Mendelian Randomization Analysis, Obesity genetics, Polymorphism, Single Nucleotide, Vitamin D Deficiency genetics
Abstract

Background: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis., Methods and Findings: We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m(2) higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10⁻²⁷). The BMI allele score was associated both with BMI (p = 6.30×10⁻⁶²) and 25(OH)D (-0.06% [95% CI -0.10 to -0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10⁻⁵⁷ for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: -4.2 [95% CI -7.1 to -1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores)., Conclusions: On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.

Published
2013
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10. Genetic determinants of major blood lipids in Pakistanis compared with Europeans.

Author

Saleheen D, Soranzo N, Rasheed A, Scharnagl H, Gwilliam R, Alexander M, Inouye M, Zaidi M, Potter S, Haycock P, Bumpstead S, Kaptoge S, Di Angelantonio E, Sarwar N, Hunt SE, Sheikh N, Shah N, Samuel M, Haider SR, Murtaza M, Thompson A, Gobin R, Butterworth A, Ahmad U, Hakeem A, Zaman KS, Kundi A, Yaqoob Z, Cheema LA, Qamar N, Faruqui A, Mallick NH, Azhar M, Samad A, Ishaq M, Rasheed SZ, Jooma R, Niazi JH, Gardezi AR, Memon NA, Ghaffar A, Rehman FU, Hoffmann MM, Renner W, Kleber ME, Grammer TB, Stephens J, Attwood A, Koch K, Hussain M, Kumar K, Saleem A, Kumar K, Daood MS, Gul AA, Abbas S, Zafar J, Shahid F, Bhatti SM, Ali SS, Muhammad F, Sagoo G, Bray S, McGinnis R, Dudbridge F, Winkelmann BR, Böehm B, Thompson S, Ouwehand W, März W, Frossard P, Danesh J, and Deloukas P

Subjects
Adult, Aged, Case-Control Studies, Europe, Female, Genetic Loci, Genome-Wide Association Study, Humans, Lipid Metabolism Disorders blood, Lipid Metabolism Disorders ethnology, Lipid Metabolism Disorders genetics, Lipids genetics, Male, Meta-Analysis as Topic, Middle Aged, Pakistan, Polymorphism, Single Nucleotide, Lipid Metabolism genetics, Lipids blood
Abstract

Background: Evidence is sparse about the genetic determinants of major lipids in Pakistanis., Methods and Results: Variants (n=45 000) across 2000 genes were assessed in 3200 Pakistanis and compared with 2450 Germans using the same gene array and similar lipid assays. We also did a meta-analysis of selected lipid-related variants in Europeans. Pakistani genetic architecture was distinct from that of several ethnic groups represented in international reference samples. Forty-one variants at 14 loci were significantly associated with levels of HDL-C, triglyceride, or LDL-C. The most significant lipid-related variants identified among Pakistanis corresponded to genes previously shown to be relevant to Europeans, such as CETP associated with HDL-C levels (rs711752; P<10(-13)), APOA5/ZNF259 (rs651821; P<10(-13)) and GCKR (rs1260326; P<10(-13)) with triglyceride levels; and CELSR2 variants with LDL-C levels (rs646776; P<10(-9)). For Pakistanis, these 41 variants explained 6.2%, 7.1%, and 0.9% of the variation in HDL-C, triglyceride, and LDL-C, respectively. Compared with Europeans, the allele frequency of rs662799 in APOA5 among Pakistanis was higher and its impact on triglyceride concentration was greater (P-value for difference <10(-4))., Conclusions: Several lipid-related genetic variants are common to Pakistanis and Europeans, though they explain only a modest proportion of population variation in lipid concentration. Allelic frequencies and effect sizes of lipid-related variants can differ between Pakistanis and Europeans.

Published
2010
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