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1. Genome-wide association study of circulating interleukin 6 levels identifies novel loci

Author

Ahluwalia, T.S., Prins, B.P., Abdollahi, M., Armstrong, N.J., Aslibekyan, S., Bain, L., Jefferis, B., Baumert, J., Beekman, M., Ben-Shlomo, Y., Bis, J.C., Mitchell, B.D., Geus, E. de, Delgado, G.E., Marek, D., Eriksson, J., Kajantie, E., Kanoni, S., Kemp, J.P., Lu, C., Marioni, R.E., McLachlan, S., Milaneschi, Y., Nolte, I.M., Petrelis, A.M., Porcu, E., Sabater-Lleal, M., Naderi, E., Seppala, I., Shah, T., Singhal, G., Standl, M., Teumer, A., Thalamuthu, A., Thiering, E., Trompet, S., Ballantyne, C.M., Benjamin, E.J., Casas, J.P., Toben, C., Dedoussis, G., Deelen, J., Durda, P., Engmann, J., Feitosa, M.F., Grallert, H., Hammarstedt, A., Harris, S.E., Homuth, G., Hottenga, J.J., Jalkanen, S., Jamshidi, Y., Jawahar, M.C., Jess, T., Kivimaki, M., Kleber, M.E., Lahti, J., Liu, Y., Marques-Vidal, P., Mellstrom, D., Mooijaart, S.P., Muller-Nurasyid, M., Penninx, B., Revez, J.A., Rossing, P., Raikkonen, K., Sattar, N., Scharnagl, H., Sennblad, B., Silveira, A., St Pourcain, B., Timpson, N.J., Trollor, J., Dongen, J. van, Heemst, D. van, Visvikis-Siest, S., Vollenweider, P., Volker, U., Waldenberger, M., Willemsen, G., Zabaneh, D., Morris, R.W., Arnett, D.K., Baune, B.T., Boomsma, D.I., Chang, Y.P.C., Deary, I.J., Deloukas, P., Eriksson, J.G., Evans, D.M., Ferreira, M.A., Gaunt, T., Gudnason, V., Hamsten, A., Heinrich, J., Hingorani, A., Humphries, S.E., Jukema, J.W., Koenig, W., Kumari, M., Kutalik, Z., Lawlor, D.A., Lehtimaki, T., Marz, W., Mather, K.A., Naitza, S., Nauck, M., Ohlsson, C., Price, J.F., Raitakari, O., Rice, K., Sachdev, P.S., Slagboom, E., Sorensen, T.I.A., Spector, T., Stacey, D., Stathopoulou, M.G., Tanaka, T., Wannamethee, S.G., Whincup, P., Rotter, J.I., Dehghan, A., Boerwinkle, E., Psaty, B.M., Snieder, H., Alizadeh, B.Z., and CHARGE Inflammation Working Grp

Abstract

Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67428 (n(discovery)=52654 and n(replication)=14774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (P-combined=1.8x10(-11)), HLA-DRB1/DRB5 rs660895 on Chr6p21 (P-combined=1.5x10(-10)) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (P-combined=1.2x10(-122)). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.

Published
2021

2. Genome-Wide Association Study of Circulating Interleukin 6 Levels Identifies Novel Loci

Author

Ahluwalia, TS, Prins, BP, Abdollahi, M, Armstrong, NJ, Aslibekyan, S, Bain, L, Jefferis, B, Baumert, J, Beekman, M, Ben-Shlomo, Y, Bis, JC, Mitchell, BD, de Geus, E, Delgado, GE, Marek, D, Eriksson, J, Kajantie, E, Kanoni, S, Kemp, JP, Lu, C, Marioni, RE, McLachlan, S, Milaneschi, Y, Nolte, IM, Petrelis, AM, Porcu, E, Sabater-Lleal, M, Naderi, E, Seppälä, I, Shah, T, Singhal, G, Standl, M, Teumer, A, Thalamuthu, A, Thiering, E, Trompet, S, Ballantyne, CM, Benjamin, EJ, Casas, JP, Toben, C, Dedoussis, G, Deelen, J, Durda, P, Engmann, J, Feitosa, MF, Grallert, H, Hammarstedt, A, Harris, SE, Homuth, G, Hottenga, J-J, Jalkanen, S, Jamshidi, Y, Jawahar, MC, Jess, T, Kivimaki, M, Kleber, ME, Lahti, J, Liu, Y, Marques-Vidal, P, Mellström, D, Mooijaart, SP, Müller-Nurasyid, M, Penninx, B, Revez, JA, Rossing, P, Räikkönen, K, Sattar, N, Scharnagl, H, Sennblad, B, Silveira, A, Pourcain, BS, Timpson, NJ, Trollor, J, CHARGE Inflammation Working Group, van Dongen, J, Van Heemst, D, Visvikis-Siest, S, Vollenweider, P, Völker, U, Waldenberger, M, Willemsen, G, Zabaneh, D, Morris, RW, Arnett, DK, Baune, BT, Boomsma, DI, Chang, Y-PC, Deary, IJ, Deloukas, P, Eriksson, JG, Evans, DM, Ferreira, MA, Gaunt, T, Gudnason, V, Hamsten, A, Heinrich, J, Hingorani, A, Humphries, SE, Jukema, JW, Koeing, W, Kumari, M, Kutalik, Z, Lawlor, DA, Lehtimäki, T, März, W, Mather, K, Naitza, S, Nauck, M, Ohlsson, C, Price, JF, Raitakari, O, Rice, K, Sachdev, PS, Slagboom, E, Sørensen, TIA, Spector, T, Stacey, D, Stathopoulou, MG, Tanaka, T, Wannamethee, SG, Whincup, P, Rotter, JI, Dehghan, A, Boerwinkle, E, Psaty, BM, Snieder, H, and Alizadeh, BZ

Abstract

Interleukin-6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery, and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67 428 (ndiscovery = 52 654 and nreplication = 14 774) individuals of European ancestry. The inverse variance fixed-effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on Chromosome (Chr) 2q14, (pcombined = 1.8 × 10-11), HLA-DRB1/DRB5 rs660895 on Chr6p21 (pcombined = 1.5 × 10-10) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (pcombined = 1.2 × 10-122). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.

Published
2021

5. Multi-polygenic score approach to trait prediction

Author

Krapohl, E., Patel, H., Newhouse, S., Curtis, C. J., Von Stumm, S., Dale, P. S., Zabaneh, D., Breen, G., O'Reilly, P. F., and Plomin, R.

Abstract

A primary goal of polygenic scores, which aggregate the effects of thousands of trait-associated DNA variants discovered in genome-wide association studies (GWAS), is to estimate individual-specific genetic propensities and predict outcomes. This is typically achieved using a single polygenic score, but here we use a multi-polygenic score (MPS) approach to increase predictive power by exploiting the joint power of multiple discovery GWAS, without assumptions about the relationships among predictors. We used summary statistics of 81 well-powered GWAS of cognitive, medical, and anthropometric traits to predict three core developmental outcomes in our independent target sample: educational achievement, body-mass index (BMI), and general cognitive ability. We used regularized regression with repeated cross-validation to select from and estimate contributions of 81 polygenic scores in a UK-representative sample of 6,710 unrelated adolescents. The MPS approach predicted 11% variance in educational achievement, 4.8% in general cognitive ability, and 5.4% in BMI in an independent test set, improving prediction by 1.1%, 1.1%, and 1.6% variance explained over the best single-score predictions. As other relevant GWA analyses are reported, they can be incorporated in MPS models to maximize phenotype prediction. The MPS approach should be useful in research with modest sample sizes to investigate developmental, multivariate and gene-environment interplay issues and, eventually, in clinical settings to predict and prevent problems using personalized interventions.

Published
2018
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6. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

Author

Savage, J.E. Jansen, P.R. Stringer, S. Watanabe, K. Bryois, J. De Leeuw, C.A. Nagel, M. Awasthi, S. Barr, P.B. Coleman, J.R.I. Grasby, K.L. Hammerschlag, A.R. Kaminski, J.A. Karlsson, R. Krapohl, E. Lam, M. Nygaard, M. Reynolds, C.A. Trampush, J.W. Young, H. Zabaneh, D. Hägg, S. Hansell, N.K. Karlsson, I.K. Linnarsson, S. Montgomery, G.W. Muñoz-Manchado, A.B. Quinlan, E.B. Schumann, G. Skene, N.G. Webb, B.T. White, T. Arking, D.E. Avramopoulos, D. Bilder, R.M. Bitsios, P. Burdick, K.E. Cannon, T.D. Chiba-Falek, O. Christoforou, A. Cirulli, E.T. Congdon, E. Corvin, A. Davies, G. Deary, I.J. Derosse, P. Dickinson, D. Djurovic, S. Donohoe, G. Conley, E.D. Eriksson, J.G. Espeseth, T. Freimer, N.A. Giakoumaki, S. Giegling, I. Gill, M. Glahn, D.C. Hariri, A.R. Hatzimanolis, A. Keller, M.C. Knowles, E. Koltai, D. Konte, B. Lahti, J. Le Hellard, S. Lencz, T. Liewald, D.C. London, E. Lundervold, A.J. Malhotra, A.K. Melle, I. Morris, D. Need, A.C. Ollier, W. Palotie, A. Payton, A. Pendleton, N. Poldrack, R.A. Räikkönen, K. Reinvang, I. Roussos, P. Rujescu, D. Sabb, F.W. Scult, M.A. Smeland, O.B. Smyrnis, N. Starr, J.M. Steen, V.M. Stefanis, N.C. Straub, R.E. Sundet, K. Tiemeier, H. Voineskos, A.N. Weinberger, D.R. Widen, E. Yu, J. Abecasis, G. Andreassen, O.A. Breen, G. Christiansen, L. Debrabant, B. Dick, D.M. Heinz, A. Hjerling-Leffler, J. Ikram, M.A. Kendler, K.S. Martin, N.G. Medland, S.E. Pedersen, N.L. Plomin, R. Polderman, T.J.C. Ripke, S. Van Der Sluis, S. Sullivan, P.F. Vrieze, S.I. Wright, M.J. Posthuma, D.

Abstract

Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence 3-7 , but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders. © 2018 The Author(s).

Published
2018

7. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

Author

Savage, J. E., Jansen, P. R., Stringer, S., Watanabe, K., Bryois, J., De Leeuw, C. A., Nagel, M., Awasthi, S., Barr, P. B., Coleman, J. R. I., Grasby, K. L., Hammerschlag, A. R., Kaminski, J. A., Karlsson, R., Krapohl, E., Lam, M., Nygaard, M., Reynolds, C. A., Trampush, J. W., Young, H., Zabaneh, D., Hägg, S., Hansell, N. K., Karlsson, Ida K., Linnarsson, S., Montgomery, G. W., Muñoz-Manchado, A. B., Quinlan, E. B., Schumann, G., Skene, N. G., Webb, B. T., White, T., Arking, D. E., Avramopoulos, D., Bilder, R. M., Bitsios, P., Burdick, K. E., Cannon, T. D., Chiba-Falek, O., Christoforou, A., Cirulli, E. T., Congdon, E., Corvin, A., Davies, G., Deary, I. J., Derosse, P., Dickinson, D., Djurovic, S., Donohoe, G., Conley, E. D., Eriksson, J. G., Espeseth, T., Freimer, N. A., Giakoumaki, S., Giegling, I., Gill, M., Glahn, D. C., Hariri, A. R., Hatzimanolis, A., Keller, M. C., Knowles, E., Koltai, D., Konte, B., Lahti, J., Le Hellard, S., Lencz, T., Liewald, D. C., London, E., Lundervold, A. J., Malhotra, A. K., Melle, I., Morris, D., Need, A. C., Ollier, W., Palotie, A., Payton, A., Pendleton, N., Poldrack, R. A., Räikkönen, K., Reinvang, I., Roussos, P., Rujescu, D., Sabb, F. W., Scult, M. A., Smeland, O. B., Smyrnis, N., Starr, J. M., Steen, V. M., Stefanis, N. C., Straub, R. E., Sundet, K., Tiemeier, H., Voineskos, A. N., Weinberger, D. R., Widen, E., Yu, J., Abecasis, G., Andreassen, O. A., Breen, G., Christiansen, L., Debrabant, B., Dick, D. M., Heinz, A., Hjerling-Leffler, J., Ikram, M. A., Kendler, K. S., Martin, N. G., Medland, S. E., Pedersen, N. L., Plomin, R., Polderman, T. J. C., Ripke, S., Van Der Sluis, S., Sullivan, P. F., Vrieze, S. I., Wright, M. J., Posthuma, D., Savage, J. E., Jansen, P. R., Stringer, S., Watanabe, K., Bryois, J., De Leeuw, C. A., Nagel, M., Awasthi, S., Barr, P. B., Coleman, J. R. I., Grasby, K. L., Hammerschlag, A. R., Kaminski, J. A., Karlsson, R., Krapohl, E., Lam, M., Nygaard, M., Reynolds, C. A., Trampush, J. W., Young, H., Zabaneh, D., Hägg, S., Hansell, N. K., Karlsson, Ida K., Linnarsson, S., Montgomery, G. W., Muñoz-Manchado, A. B., Quinlan, E. B., Schumann, G., Skene, N. G., Webb, B. T., White, T., Arking, D. E., Avramopoulos, D., Bilder, R. M., Bitsios, P., Burdick, K. E., Cannon, T. D., Chiba-Falek, O., Christoforou, A., Cirulli, E. T., Congdon, E., Corvin, A., Davies, G., Deary, I. J., Derosse, P., Dickinson, D., Djurovic, S., Donohoe, G., Conley, E. D., Eriksson, J. G., Espeseth, T., Freimer, N. A., Giakoumaki, S., Giegling, I., Gill, M., Glahn, D. C., Hariri, A. R., Hatzimanolis, A., Keller, M. C., Knowles, E., Koltai, D., Konte, B., Lahti, J., Le Hellard, S., Lencz, T., Liewald, D. C., London, E., Lundervold, A. J., Malhotra, A. K., Melle, I., Morris, D., Need, A. C., Ollier, W., Palotie, A., Payton, A., Pendleton, N., Poldrack, R. A., Räikkönen, K., Reinvang, I., Roussos, P., Rujescu, D., Sabb, F. W., Scult, M. A., Smeland, O. B., Smyrnis, N., Starr, J. M., Steen, V. M., Stefanis, N. C., Straub, R. E., Sundet, K., Tiemeier, H., Voineskos, A. N., Weinberger, D. R., Widen, E., Yu, J., Abecasis, G., Andreassen, O. A., Breen, G., Christiansen, L., Debrabant, B., Dick, D. M., Heinz, A., Hjerling-Leffler, J., Ikram, M. A., Kendler, K. S., Martin, N. G., Medland, S. E., Pedersen, N. L., Plomin, R., Polderman, T. J. C., Ripke, S., Van Der Sluis, S., Sullivan, P. F., Vrieze, S. I., Wright, M. J., and Posthuma, D.

Abstract

Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence 3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

Published
2018
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8. Genetic loci associated with heart rate variability and their effects on cardiac disease risk

Author

Nolte, IM, Munoz, ML, Tragante, V, Amare, AT, Jansen, R, Vaez, A, Von Der Heyde, B, Avery, CL, Bis, JC, Dierckx, B, Van Dongen, J, Gogarten, SM, Goyette, P, Hernesniemi, J, Huikari, V, Hwang, SJ, Jaju, D, Kerr, KF, Kluttig, A, Krijthe, BP, Kumar, J, Van Der Laan, SW, Lyytikäinen, LP, Maihofer, AX, Minassian, A, Van Der Most, PJ, Müller-Nurasyid, M, Nivard, M, Salvi, E, Stewart, JD, Thayer, JF, Verweij, N, Wong, A, Zabaneh, D, Zafarmand, MH, Abdellaoui, A, Albarwani, S, Albert, C, Alonso, A, Ashar, F, Auvinen, J, Axelsson, T, Baker, DG, De Bakker, PIW, Barcella, M, Bayoumi, R, Bieringa, RJ, Boomsma, D, Boucher, G, Britton, AR, Christophersen, IE, Dietrich, A, Ehret, GB, Ellinor, PT, Eskola, M, Felix, JF, Floras, JS, Franco, OH, Friberg, P, Gademan, MGJ, Geyer, MA, Giedraitis, V, Hartman, CA, Hemerich, D, Hofman, A, Hottenga, JJ, Huikuri, H, Hutri-Kähönen, N, and Jouven, X

Abstract

Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74

Published
2017
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9. Genome-wide association meta- Analysis of 78,308 individuals identifies new loci and genes influencing human intelligence

Author

Sniekers, S. (Suzanne), Stringer, S. (Sven), Watanabe, K. (Kyoko), Jansen, P.R. (Philip), Coleman, J.R.I. (Jonathan R I), Krapohl, E. (Eva), Taskesen, E. (Erdogan), Hammerschlag, A.R. (Anke R.), Okbay, A. (Aysu), Zabaneh, D. (Delilah), Amin, N. (Najaf), Breen, G. (Gerome), Cesarini, D. (David), Chabris, C.F. (Christopher F), Iacono, W.G. (William), Ikram, M.A. (Arfan), Johannesson, M. (Magnus), Koellinger, P. (Philipp), Lee, J.J. (James J.), Magnusson, P.K. (Patrik), McGue, M. (Matt), Miller, M. (Mike), Ollier, W.E.R. (William), Payton, A. (Antony), Pendleton, N. (Neil), Plomin, R. (Robert), Rietveld, C.A. (Niels), Tiemeier, H.W. (Henning), Duijn, C.M. (Cornelia) van, Posthuma, D. (Danielle), Sniekers, S. (Suzanne), Stringer, S. (Sven), Watanabe, K. (Kyoko), Jansen, P.R. (Philip), Coleman, J.R.I. (Jonathan R I), Krapohl, E. (Eva), Taskesen, E. (Erdogan), Hammerschlag, A.R. (Anke R.), Okbay, A. (Aysu), Zabaneh, D. (Delilah), Amin, N. (Najaf), Breen, G. (Gerome), Cesarini, D. (David), Chabris, C.F. (Christopher F), Iacono, W.G. (William), Ikram, M.A. (Arfan), Johannesson, M. (Magnus), Koellinger, P. (Philipp), Lee, J.J. (James J.), Magnusson, P.K. (Patrik), McGue, M. (Matt), Miller, M. (Mike), Ollier, W.E.R. (William), Payton, A. (Antony), Pendleton, N. (Neil), Plomin, R. (Robert), Rietveld, C.A. (Niels), Tiemeier, H.W. (Henning), Duijn, C.M. (Cornelia) van, and Posthuma, D. (Danielle)

Abstract

Intelligence is associated with important economic and health-related life outcomes. Despite intelligence having substantial heritability (0.54) and a confirmed polygenic nature, initial genetic studies were mostly underpowered. Here we report a meta- A nalysis for intelligence of 78,308 individuals. We identify 336 associated SNPs (METAL P < 5 × 10-8) in 18 genomic loci, of which 15 are new. Around half of the SNPs are located inside a gene, implicating 22 genes, of which 11 are new findings. Gene-based analyses identified an additional 30 genes (MAGMA P < 2.73 × 10-6), of which all but one had not been implicated previously. We show that the identified genes are predominantly expressed in brain tissue, and pathway analysis indicates the involvement of genes regulating cell development (MAGMA competitive P = 3.5 × 10-6). Despite the well-known difference in twin-based heritability for intelligence in childhood (0.45) and adulthood (0.80), we show substantial genetic correlation (rg = 0.89, LD score regression P = 5.4 × 10-29). These findings provide new insight into the genetic architecture of intelligence.

Published
2017
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10. Genetic loci associated with heart rate variability and their effects on cardiac disease risk

Author

Nolte, I. M. (Ilja M.), Munoz, M. L. (M. Loretto), Tragante, V. (Vinicius), Amare, A. T. (Azmeraw T.), Jansen, R. (Rick), Vaez, A. (Ahmad), von der Heyde, B. (Benedikt), Avery, C. L. (Christy L.), Bis, J. C. (Joshua C.), Dierckx, B. (Bram), van Dongen, J. (Jenny), Gogarten, S. M. (Stephanie M.), Goyette, P. (Philippe), Hernesniemi, J. (Jussi), Huikari, V. (Ville), Hwang, S.-J. (Shih-Jen), Jaju, D. (Deepali), Kerr, K. F. (Kathleen F.), Kluttig, A. (Alexander), Krijthe, B. P. (Bouwe P.), Kumar, J. (Jitender), van der Laan, S. W. (Sander W.), Lyytikäinen, L.-P. (Leo-Pekka), Maihofer, A. X. (Adam X.), Minassian, A. (Arpi), van der Most, P. J. (Peter J.), Mueller-Nurasyid, M. (Martina), Nivard, M. (Michel), Salvi, E. (Erika), Stewart, J. D. (James D.), Thayer, J. F. (Julian F.), Verweij, N. (Niek), Wong, A. (Andrew), Zabaneh, D. (Delilah), Zafarmand, M. H. (Mohammad H.), Abdellaoui, A. (Abdel), Albarwani, S. (Sulayma), Albert, C. (Christine), Alonso, A. (Alvaro), Ashar, F. (Foram), Auvinen, J. (Juha), Axelsson, T. (Tomas), Baker, D. G. (Dewleen G.), de Bakker, P. I. (Paul I. W.), Barcella, M. (Matteo), Bayoumi, R. (Riad), Bieringa, R. J. (Rob J.), Boomsma, D. (Dorret), Boucher, G. (Gabrielle), Britton, A. R. (Annie R.), Christophersen, I. E. (Ingrid E.), Dietrich, A. (Andrea), Ehret, G. B. (George B.), Ellinor, P. T. (Patrick T.), Eskola, M. (Markku), Felix, J. F. (Janine F.), Floras, J. S. (John S.), Franco, O. H. (Oscar H.), Friberg, P. (Peter), Gademan, M. G. (Maaike G. J.), Geyer, M. A. (Mark A.), Giedraitis, V. (Vilmantas), Hartman, C. A. (Catharina A.), Hemerich, D. (Daiane), Hofman, A. (Albert), Hottenga, J.-J. (Jouke-Jan), Huikuri, H. (Heikki), Hutri-Kähönen, N. (Nina), Jouven, X. (Xavier), Junttila, J. (Juhani), Juonala, M. (Markus), Kiviniemi, A. M. (Antti M.), Kors, J. A. (Jan A.), Kumari, M. (Meena), Kuznetsova, T. (Tatiana), Laurie, C. C. (Cathy C.), Lefrandt, J. D. (Joop D.), Li, Y. (Yong), Li, Y. (Yun), Liao, D. (Duanping), Limacher, M. C. (Marian C.), Lin, H. J. (Henry J.), Lindgren, C. M. (Cecilia M.), Lubitz, S. A. (Steven A.), Mahajan, A. (Anubha), McKnight, B. (Barbara), zu Schwabedissen, H. M. (Henriette Meyer), Milaneschi, Y. (Yuri), Mononen, N. (Nina), Morris, A. P. (Andrew P.), Nalls, M. A. (Mike A.), Navis, G. (Gerjan), Neijts, M. (Melanie), Nikus, K. (Kjell), North, K. E. (Kari E.), O'Connor, D. T. (Daniel T.), Ormel, J. (Johan), Perz, S. (Siegfried), Peters, A. (Annette), Psaty, B. M. (Bruce M.), Raitakari, O. T. (Olli T.), Risbrough, V. B. (Victoria B.), Sinner, M. F. (Moritz F.), Siscovick, D. (David), Smit, J. H. (Johannes H.), Smith, N. L. (Nicholas L.), Soliman, E. Z. (Elsayed Z.), Sotoodehnia, N. (Nona), Staessen, J. A. (Jan A.), Stein, P. K. (Phyllis K.), Stilp, A. M. (Adrienne M.), Stolarz-Skrzypek, K. (Katarzyna), Strauch, K. (Konstantin), Sundström, J. (Johan), Swenne, C. A. (Cees A.), Syvänen, A.-C. (Ann-Christine), Tardif, J.-C. (Jean-Claude), Taylor, K. D. (Kent D.), Teumer, A. (Alexander), Thornton, T. A. (Timothy A.), Tinker, L. E. (Lesley E.), Uitterlinden, A. G. (Andre G.), van Setten, J. (Jessica), Voss, A. (Andreas), Waldenberger, M. (Melanie), Wilhelmsen, K. C. (Kirk C.), Willemsen, G. (Gonneke), Wong, Q. (Quenna), Zhang, Z.-M. (Zhu-Ming), Zonderman, A. B. (Alan B.), Cusi, D. (Daniele), Evans, M. K. (Michele K.), Greiser, H. K. (Halina K.), van der Harst, P. (Pim), Hassan, M. (Mohammad), Ingelsson, E. (Erik), Järvelin, M.-R. (Marjo-Riitta), Kaab, S. (Stefan), Kähönen, M. (Mika), Kivimäki, M. (Mika), Kooperberg, C. (Charles), Kuh, D. (Diana), Lehtimäki, T. (Terho), Lind, L. (Lars), Nievergelt, C. M. (Caroline M.), O'Donnell, C. J. (Chris J.), Oldehinkel, A. J. (Albertine J.), Penninx, B. (Brenda), Reiner, A. P. (Alexander P.), Riese, H. (Harriette), van Roon, A. M. (Arie M.), Rioux, J. D. (John D.), Rotter, J. I. (Jerome I.), Sofer, T. (Tamar), Stricker, B. H. (Bruno H.), Tiemeier, H. (Henning), Vrijkotte, T. G. (Tanja G. M.), Asselbergs, F. W. (Folkert W.), Brundel, B. J. (Bianca J. J. M.), Heckbert, S. R. (Susan R.), Whitsel, E. A. (Eric A.), den Hoed, M. (Marcel), Snieder, H. (Harold), de Geus, E. J. (Eco J. C.), Nolte, I. M. (Ilja M.), Munoz, M. L. (M. Loretto), Tragante, V. (Vinicius), Amare, A. T. (Azmeraw T.), Jansen, R. (Rick), Vaez, A. (Ahmad), von der Heyde, B. (Benedikt), Avery, C. L. (Christy L.), Bis, J. C. (Joshua C.), Dierckx, B. (Bram), van Dongen, J. (Jenny), Gogarten, S. M. (Stephanie M.), Goyette, P. (Philippe), Hernesniemi, J. (Jussi), Huikari, V. (Ville), Hwang, S.-J. (Shih-Jen), Jaju, D. (Deepali), Kerr, K. F. (Kathleen F.), Kluttig, A. (Alexander), Krijthe, B. P. (Bouwe P.), Kumar, J. (Jitender), van der Laan, S. W. (Sander W.), Lyytikäinen, L.-P. (Leo-Pekka), Maihofer, A. X. (Adam X.), Minassian, A. (Arpi), van der Most, P. J. (Peter J.), Mueller-Nurasyid, M. (Martina), Nivard, M. (Michel), Salvi, E. (Erika), Stewart, J. D. (James D.), Thayer, J. F. (Julian F.), Verweij, N. (Niek), Wong, A. (Andrew), Zabaneh, D. (Delilah), Zafarmand, M. H. (Mohammad H.), Abdellaoui, A. (Abdel), Albarwani, S. (Sulayma), Albert, C. (Christine), Alonso, A. (Alvaro), Ashar, F. (Foram), Auvinen, J. (Juha), Axelsson, T. (Tomas), Baker, D. G. (Dewleen G.), de Bakker, P. I. (Paul I. W.), Barcella, M. (Matteo), Bayoumi, R. (Riad), Bieringa, R. J. (Rob J.), Boomsma, D. (Dorret), Boucher, G. (Gabrielle), Britton, A. R. (Annie R.), Christophersen, I. E. (Ingrid E.), Dietrich, A. (Andrea), Ehret, G. B. (George B.), Ellinor, P. T. (Patrick T.), Eskola, M. (Markku), Felix, J. F. (Janine F.), Floras, J. S. (John S.), Franco, O. H. (Oscar H.), Friberg, P. (Peter), Gademan, M. G. (Maaike G. J.), Geyer, M. A. (Mark A.), Giedraitis, V. (Vilmantas), Hartman, C. A. (Catharina A.), Hemerich, D. (Daiane), Hofman, A. (Albert), Hottenga, J.-J. (Jouke-Jan), Huikuri, H. (Heikki), Hutri-Kähönen, N. (Nina), Jouven, X. (Xavier), Junttila, J. (Juhani), Juonala, M. (Markus), Kiviniemi, A. M. (Antti M.), Kors, J. A. (Jan A.), Kumari, M. (Meena), Kuznetsova, T. (Tatiana), Laurie, C. C. (Cathy C.), Lefrandt, J. D. (Joop D.), Li, Y. (Yong), Li, Y. (Yun), Liao, D. (Duanping), Limacher, M. C. (Marian C.), Lin, H. J. (Henry J.), Lindgren, C. M. (Cecilia M.), Lubitz, S. A. (Steven A.), Mahajan, A. (Anubha), McKnight, B. (Barbara), zu Schwabedissen, H. M. (Henriette Meyer), Milaneschi, Y. (Yuri), Mononen, N. (Nina), Morris, A. P. (Andrew P.), Nalls, M. A. (Mike A.), Navis, G. (Gerjan), Neijts, M. (Melanie), Nikus, K. (Kjell), North, K. E. (Kari E.), O'Connor, D. T. (Daniel T.), Ormel, J. (Johan), Perz, S. (Siegfried), Peters, A. (Annette), Psaty, B. M. (Bruce M.), Raitakari, O. T. (Olli T.), Risbrough, V. B. (Victoria B.), Sinner, M. F. (Moritz F.), Siscovick, D. (David), Smit, J. H. (Johannes H.), Smith, N. L. (Nicholas L.), Soliman, E. Z. (Elsayed Z.), Sotoodehnia, N. (Nona), Staessen, J. A. (Jan A.), Stein, P. K. (Phyllis K.), Stilp, A. M. (Adrienne M.), Stolarz-Skrzypek, K. (Katarzyna), Strauch, K. (Konstantin), Sundström, J. (Johan), Swenne, C. A. (Cees A.), Syvänen, A.-C. (Ann-Christine), Tardif, J.-C. (Jean-Claude), Taylor, K. D. (Kent D.), Teumer, A. (Alexander), Thornton, T. A. (Timothy A.), Tinker, L. E. (Lesley E.), Uitterlinden, A. G. (Andre G.), van Setten, J. (Jessica), Voss, A. (Andreas), Waldenberger, M. (Melanie), Wilhelmsen, K. C. (Kirk C.), Willemsen, G. (Gonneke), Wong, Q. (Quenna), Zhang, Z.-M. (Zhu-Ming), Zonderman, A. B. (Alan B.), Cusi, D. (Daniele), Evans, M. K. (Michele K.), Greiser, H. K. (Halina K.), van der Harst, P. (Pim), Hassan, M. (Mohammad), Ingelsson, E. (Erik), Järvelin, M.-R. (Marjo-Riitta), Kaab, S. (Stefan), Kähönen, M. (Mika), Kivimäki, M. (Mika), Kooperberg, C. (Charles), Kuh, D. (Diana), Lehtimäki, T. (Terho), Lind, L. (Lars), Nievergelt, C. M. (Caroline M.), O'Donnell, C. J. (Chris J.), Oldehinkel, A. J. (Albertine J.), Penninx, B. (Brenda), Reiner, A. P. (Alexander P.), Riese, H. (Harriette), van Roon, A. M. (Arie M.), Rioux, J. D. (John D.), Rotter, J. I. (Jerome I.), Sofer, T. (Tamar), Stricker, B. H. (Bruno H.), Tiemeier, H. (Henning), Vrijkotte, T. G. (Tanja G. M.), Asselbergs, F. W. (Folkert W.), Brundel, B. J. (Bianca J. J. M.), Heckbert, S. R. (Susan R.), Whitsel, E. A. (Eric A.), den Hoed, M. (Marcel), Snieder, H. (Harold), and de Geus, E. J. (Eco J. C.)

Abstract

Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74

Published
2017

11. Adult height, coronary heart disease and stroke : A multi-locus Mendelian randomization meta-analysis

Author

Nüesch, Eveline, Dale, Caroline, Palmer, Tom M., White, Jon, Keating, Brendan J., van Iperen, Erik P A, Goel, Anuj, Padmanabhan, Sandosh, Asselbergs, F. W., Verschuren, W. M., Wijmenga, C., Van der Schouw, Y. T., Onland-Moret, N. C., Lange, Leslie A., Hovingh, G. K., Sivapalaratnam, Suthesh, Morris, Richard W., Whincup, Peter H., Wannamethe, Goya S., Gaunt, Tom R., Ebrahim, Shah, Steel, Laura, Nair, Nikhil, Reiner, Alexander P., Kooperberg, Charles, Wilson, James F., Bolton, Jennifer L., McLachlan, Stela, Price, Jacqueline F., Strachan, Mark W J, Robertson, Christine M., Kleber, Marcus E., Delgado, Graciela, März, Winfried, Melander, Olle, Dominiczak, Anna F., Farrall, Martin, Watkins, Hugh, Leusink, Maarten, Maitland-van der Zee, Anke H., de Groot, Mark C H, Dudbridge, Frank, Hingorani, Aroon, Ben-Shlomo, Yoav, Lawlor, Debbie A., Amuzu, A., Caufield, M., Cavadino, A., Cooper, J., Davies, T. L., Day, I. N., Drenos, F., Engmann, J., Finan, C., Giambartolomei, C., Hardy, R., Humphries, S. E., Hypponen, E., Kivimaki, M., Kuh, D., Kumari, M., Ong, K., Plagnol, V., Power, C., Richards, M., Shah, S., Shah, T., Sofat, R., Talmud, P. J., Wareham, N., Warren, H., Whittaker, J. C., Wong, A., Zabaneh, D., Smith, George Davey, Wells, Jonathan C., Leon, David A., Holmes, Michael V., and Casas, Juan P.

Subjects
Medicine(all), procedure, Epidemiology, alleles, Journal Article, body mass index, cerebrovascular accident, triglycerides
Abstract

© The Author 2015; all rights reserved. Background: We investigated causal effect of completed growth, measured by adult height, on coronary heart disease (CHD), stroke and cardiovascular traits, using instrumental variable (IV) Mendelian randomization meta-analysis. Methods: We developed an allele score based on 69 single nucleotide polymorphisms (SNPs) associated with adult height, identified by the IBCCardioChip, and used it for IV analysis against cardiovascular risk factors and events in 21 studies and 60 028 participants. IV analysis on CHD was supplemented by summary data from 180 height-SNPs from the GIANT consortium and their corresponding CHD estimates derived from CARDIoGRAMplusC4D. Results: IV estimates from IBCCardioChip and GIANT-CARDIoGRAMplusC4D showed that a 6.5-cm increase in height reduced the odds of CHD by 10% [odds ratios 0.90; 95% confidence intervals (CIs): 0.78 to 1.03 and 0.85 to 0.95, respectively],which agrees with the estimate from the Emerging Risk Factors Collaboration (hazard ratio 0.93; 95% CI: 0.91 to 0.94). IV analysis revealed no association with stroke (odds ratio 0.97; 95% CI: 0.79 to 1.19). IV analysis showed that a 6.5-cm increase in height resulted in lower levels of body mass index (P < 0.001), triglycerides (P < 0.001), non high-density (non-HDL) cholesterol (P < 0.001), C-reactive protein (P = 0.042), and systolic blood pressure (P = 0.064) and higher levels of forced expiratory volume in 1 s and forced vital capacity (P < 0.001 for both). Conclusions: Taller individuals have a lower risk of CHD with potential explanations being that taller people have a better lung function and lower levels of body mass index, cholesterol and blood pressure.

Published
2016

13. Mendelian randomization of blood lipids for coronary heart disease

Author

Holmes, M, Asselbergs, F, Palmer, T, Drenos, F, Lanktree, M, Nelson, C, Dale, C, Padmanabhan, S, Finan, C, Swerdlow, D, Tragante, V, van Iperen, E, Sivapalaratnam, S, Shah, S, Elbers, C, Shah, T, Engmann, J, Giambartolomei, C, White, J, Zabaneh, D, Sofat, R, McLachlan, S, Doevendans, P, Balmforth, A, and Hall, A

Abstract

AIMS: To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. METHODS AND RESULTS: We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10(-6)); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75). CONCLUSION: The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.

Published
2016

14. Replication and characterization of association between ABO SNPs and red blood cell traits by meta-analysis in Europeans

Author

McLachlan, S, Giambartolomei, C, White, J, Charoen, P, Wong, A, Finan, C, Engmann, J, Shah, T, Hersch, M, Podmore, C, Cavadino, A, Jefferis, BJ, Dale, CE, Hypponen, E, Morris, RW, Casas, JP, Kumari, M, Ben-Shlomo, Y, Gaunt, TR, Drenos, F, Langenberg, C, Kuh, D, Kivimaki, M, Rueedi, R, Waeber, G, Hingorani, AD, Price, JF, Walker, AP, Cooper, J, Day, IN, De Silva, M, Dudbridge, F, Fatemifar, G, Garfield, V, Humphries, SE, Lawlor, DA, Davies, TL, Plagnol, V, Power, C, Shah, S, Sofat, R, Swerdlow, DI, Talmud, PJ, Whincup, P, Whittaker, JC, and Zabaneh, D

Subjects
General Science & Technology, hemic and lymphatic diseases, MD Multidisciplinary
Abstract

Red blood cell (RBC) traits are routinely measured in clinical practice as important markers of health. Deviations from the physiological ranges are usually a sign of disease, although variation between healthy individuals also occurs, at least partly due to genetic factors. Recent large scale genetic studies identified loci associated with one or more of these traits; further characterization of known loci and identification of new loci is necessary to better understand their role in health and disease and to identify potential molecular mechanisms. We performed meta-analysis of Metabochip association results for six RBC traits—hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV) and red blood cell count (RCC)—in 11 093 Europeans from seven studies of the UCL-LSHTM-Edinburgh-Bristol (UCLEB) Consortium. We identified 394 non-overlapping SNPs in five loci at genome-wide significance: 6p22.1-6p21.33 (with HFE among others), 6q23.2 (with HBS1L among others), 6q23.3 (contains no genes), 9q34.3 (only ABO gene) and 22q13.1 (with TMPRSS6 among others), replicating previous findings of association with RBC traits at these loci and extending them by imputation to 1000 Genomes. We further characterized associations between ABO SNPs and three traits: hemoglobin, hematocrit and red blood cell count, replicating them in an independent cohort. Conditional analyses indicated the independent association of each of these traits with ABO SNPs and a role for blood group O in mediating the association. The 15 most significant RBC-associated ABO SNPs were also associated with five cardiometabolic traits, with discordance in the direction of effect between groups of traits, suggesting that ABO may act through more than one mechanism to influence cardiometabolic risk. British Heart Foundation; UK Medical Research Council ; Wellcome Trust; European Commission Framework Programme 6; French Ministry of Research

Published
2016

15. Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis

Author

White, J, Sofat, R, Hemani, G, Shah, T, Engmann, J, Dale, C, Shah, S, Kruger, FA, Giambartolomei, C, Swerdlow, DI, Palmer, T, McLachlan, S, Langenberg, C, Zabaneh, D, Lovering, R, Cavadino, A, Jefferis, B, Finan, C, Wong, A, Amuzu, A, Ong, K, Gaunt, TR, Warren, H, Davies, TL, Drenos, F, Cooper, J, Ebrahim, S, Lawlor, DA, Talmud, PJ, Humphries, SE, Power, C, Hypponen, E, Richards, M, Hardy, R, Kuh, D, Wareham, N, Ben-Shlomo, Y, Day, IN, Whincup, P, Morris, R, Strachan, MW, Price, J, Kumari, M, Kivimaki, M, Plagnol, V, Whittaker, JC, International Consortium for Blood Pressure (ICBP), Smith, GD, Dudbridge, F, Casas, JP, Holmes, MV, Hingorani, AD, and UCLEB (University College London-London School of Hygiene & Trop

Abstract

BACKGROUND: Increased circulating plasma urate concentration is associated with an increased risk of coronary heart disease, but the extent of any causative effect of urate on risk of coronary heart disease is still unclear. In this study, we aimed to clarify any causal role of urate on coronary heart disease risk using Mendelian randomisation analysis. METHODS: We first did a fixed-effects meta-analysis of the observational association of plasma urate and risk of coronary heart disease. We then used a conventional Mendelian randomisation approach to investigate the causal relevance using a genetic instrument based on 31 urate-associated single nucleotide polymorphisms (SNPs). To account for potential pleiotropic associations of certain SNPs with risk factors other than urate, we additionally did both a multivariable Mendelian randomisation analysis, in which the genetic associations of SNPs with systolic and diastolic blood pressure, HDL cholesterol, and triglycerides were included as covariates, and an Egger Mendelian randomisation (MR-Egger) analysis to estimate a causal effect accounting for unmeasured pleiotropy. FINDINGS: In the meta-analysis of 17 prospective observational studies (166 486 individuals; 9784 coronary heart disease events) a 1 SD higher urate concentration was associated with an odds ratio (OR) for coronary heart disease of 1·07 (95% CI 1·04-1·10). The corresponding OR estimates from the conventional, multivariable adjusted, and Egger Mendelian randomisation analysis (58 studies; 198 598 individuals; 65 877 events) were 1·18 (95% CI 1·08-1·29), 1·10 (1·00-1·22), and 1·05 (0·92-1·20), respectively, per 1 SD increment in plasma urate. INTERPRETATION: Conventional and multivariate Mendelian randomisation analysis implicates a causal role for urate in the development of coronary heart disease, but these estimates might be inflated by hidden pleiotropy. Egger Mendelian randomisation analysis, which accounts for pleiotropy but has less statistical power, suggests there might be no causal effect. These results might help investigators to determine the priority of trials of urate lowering for the prevention of coronary heart disease compared with other potential interventions. FUNDING: UK National Institute for Health Research, British Heart Foundation, and UK Medical Research Council.

Published
2016

16. Cystatin C and cardiovascular disease : A mendelian randomization study

Author

van der Laan, S.W, Fall, T, Soumaré, A, Teumer, A, Sedaghat, S, Baumert, J, Zabaneh, D, van Setten, J, Ärnlöv, Johan, and Asselbergs, F. W

Subjects
Klinisk medicin, Clinical Medicine, urologic and male genital diseases, female genital diseases and pregnancy complications
Abstract

BACKGROUND: Epidemiological studies show that high circulating cystatin C is associated with risk of cardiovascular disease (CVD), independent of creatinine-based renal function measurements. It is unclear whether this relationship is causal, arises from residual confounding, and/or is a consequence of reverse causation. OBJECTIVES: The aim of this study was to use Mendelian randomization to investigate whether cystatin C is causally related to CVD in the general population. METHODS We incorporated participant data from 16 prospective cohorts (n ¼ 76,481) with 37,126 measures of cystatin C and added genetic data from 43 studies (n ¼ 252,216) with 63,292 CVD events. We used the common variant rs911119 in CST3 as an instrumental variable to investigate the causal role of cystatin C in CVD, including coronary heart disease, ischemic stroke, and heart failure. RESULTS: Cystatin C concentrations were associated with CVD risk after adjusting for age, sex, and traditional risk factors (relative risk: 1.82 per doubling of cystatin C; 95% confidence interval [CI]: 1.56 to 2.13; p ¼ 2.12 1014). The minor allele of rs911119 was associated with decreased serum cystatin C (6.13% per allele; 95% CI: 5.75 to 6.50; p ¼ 5.95 10211), explaining 2.8% of the observed variation in cystatin C. Mendelian randomization analysis did not provide evidence for a causal role of cystatin C, with a causal relative risk for CVD of 1.00 per doubling cystatin C (95% CI: 0.82 to 1.22; p ¼ 0.994), which was statistically different from the observational estimate (p ¼ 1.6 105 ). A causal effect of cystatin C was not detected for any individual component of CVD. CONCLUSIONS: Mendelian randomization analyses did not support a causal role of cystatin C in the etiology of CVD. As such, therapeutics targeted at lowering circulating cystatin C are unlikely to be effective in preventing CVD.

Published
2016

17. Multi-polygenic score approach to trait prediction

Author

Krapohl, E, primary, Patel, H, additional, Newhouse, S, additional, Curtis, C J, additional, von Stumm, S, additional, Dale, P S, additional, Zabaneh, D, additional, Breen, G, additional, O'Reilly, P F, additional, and Plomin, R, additional

Published
2017
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18. A genome-wide association study for extremely high intelligence

Author

Zabaneh, D, primary, Krapohl, E, additional, Gaspar, H A, additional, Curtis, C, additional, Lee, S H, additional, Patel, H, additional, Newhouse, S, additional, Wu, H M, additional, Simpson, M A, additional, Putallaz, M, additional, Lubinski, D, additional, Plomin, R, additional, and Breen, G, additional

Published
2017
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19. Cystatin C and Cardiovascular Disease: A Mendelian Randomization Study

Author

Laan, S.W. van der, Fall, T., Soumare, A., Teumer, A., Sedaghat, S., Baumert, J., Zabaneh, D., Setten, J. van, Isgum, I., Galesloot, T.E., Arpegard, J., Amouyel, P., Trompet, S., Waldenberger, M., Dorr, M., Magnusson, P.K., Giedraitis, V., Larsson, A., Morris, A.P., Felix, J.F., Morrison, A.C., Franceschini, N., Bis, J.C., Kavousi, M., O'Donnell, C., Drenos, F., Tragante, V., Munroe, P.B., Malik, R., Dichgans, M., Worrall, B.B., Erdmann, J., Nelson, C.P., Samani, N.J., Schunkert, H., Marchini, J., Patel, R.S., Hingorani, A.D., Lind, L., Pedersen, N.L., Graaf, J. de, Kiemeney, L.A.L.M., Baumeister, S.E., Franco, O.H., Hofman, A., Uitterlinden, A.G., Koenig, W., Meisinger, C., Peters, A., Thorand, B., Jukema, J.W., Eriksen, B.O., Toft, I., Wilsgaard, T., Onland-Moret, N.C., Schouw, Y.T. van der, Debette, S., Kumari, M., Svensson, P., Harst, P. van der, Kivimäki, M., Keating, B.J., Sattar, N., Dehghan, A., Reiner, A.P., Ingelsson, E., Ruijter, H.M. Den, Bakker, P.I. de, Pasterkamp, G., Arnlov, J., Holmes, M.V., Asselbergs, F.W., Laan, S.W. van der, Fall, T., Soumare, A., Teumer, A., Sedaghat, S., Baumert, J., Zabaneh, D., Setten, J. van, Isgum, I., Galesloot, T.E., Arpegard, J., Amouyel, P., Trompet, S., Waldenberger, M., Dorr, M., Magnusson, P.K., Giedraitis, V., Larsson, A., Morris, A.P., Felix, J.F., Morrison, A.C., Franceschini, N., Bis, J.C., Kavousi, M., O'Donnell, C., Drenos, F., Tragante, V., Munroe, P.B., Malik, R., Dichgans, M., Worrall, B.B., Erdmann, J., Nelson, C.P., Samani, N.J., Schunkert, H., Marchini, J., Patel, R.S., Hingorani, A.D., Lind, L., Pedersen, N.L., Graaf, J. de, Kiemeney, L.A.L.M., Baumeister, S.E., Franco, O.H., Hofman, A., Uitterlinden, A.G., Koenig, W., Meisinger, C., Peters, A., Thorand, B., Jukema, J.W., Eriksen, B.O., Toft, I., Wilsgaard, T., Onland-Moret, N.C., Schouw, Y.T. van der, Debette, S., Kumari, M., Svensson, P., Harst, P. van der, Kivimäki, M., Keating, B.J., Sattar, N., Dehghan, A., Reiner, A.P., Ingelsson, E., Ruijter, H.M. Den, Bakker, P.I. de, Pasterkamp, G., Arnlov, J., Holmes, M.V., and Asselbergs, F.W.

Abstract

Contains fulltext : 172252.pdf (Publisher’s version ) (Open Access), BACKGROUND: Epidemiological studies show that high circulating cystatin C is associated with risk of cardiovascular disease (CVD), independent of creatinine-based renal function measurements. It is unclear whether this relationship is causal, arises from residual confounding, and/or is a consequence of reverse causation. OBJECTIVES: The aim of this study was to use Mendelian randomization to investigate whether cystatin C is causally related to CVD in the general population. METHODS: We incorporated participant data from 16 prospective cohorts (n = 76,481) with 37,126 measures of cystatin C and added genetic data from 43 studies (n = 252,216) with 63,292 CVD events. We used the common variant rs911119 in CST3 as an instrumental variable to investigate the causal role of cystatin C in CVD, including coronary heart disease, ischemic stroke, and heart failure. RESULTS: Cystatin C concentrations were associated with CVD risk after adjusting for age, sex, and traditional risk factors (relative risk: 1.82 per doubling of cystatin C; 95% confidence interval [CI]: 1.56 to 2.13; p = 2.12 x 10(-14)). The minor allele of rs911119 was associated with decreased serum cystatin C (6.13% per allele; 95% CI: 5.75 to 6.50; p = 5.95 x 10(-211)), explaining 2.8% of the observed variation in cystatin C. Mendelian randomization analysis did not provide evidence for a causal role of cystatin C, with a causal relative risk for CVD of 1.00 per doubling cystatin C (95% CI: 0.82 to 1.22; p = 0.994), which was statistically different from the observational estimate (p = 1.6 x 10(-5)). A causal effect of cystatin C was not detected for any individual component of CVD. CONCLUSIONS: Mendelian randomization analyses did not support a causal role of cystatin C in the etiology of CVD. As such, therapeutics targeted at lowering circulating cystatin C are unlikely to be effective in preventing CVD.

Published
2016

20. Cystatin C and Cardiovascular Disease: A Mendelian Randomization Study

Author

Van Der Laan, S.W. (Sander W.), Fall, M. (Magnus), Soumaré, A. (Aicha), Teumer, A. (Alexander), Sedaghat, S. (Sanaz), Baumert, J. (Jens), Zabaneh, D. (Delilah), Setten, J. (Jessica) van, Isgum, I. (Ivana), Galesloot, T.E. (Tessel), Arpegård, J. (Johannes), Amouyel, P. (Philippe), Trompet, S. (Stella), Waldenberger, M. (Melanie), Dörr, M. (Marcus), Magnusson, P.K. (Patrik), Giedraitis, V. (Vilmantas), Larsson, A. (Anders), Morris, A.P. (Andrew), Felix, J.F. (Janine), Morrison, A.C. (Alanna C.), Franceschini, N. (Nora), Bis, J.C. (Joshua), Kavousi, M. (Maryam), O'Donnell, C.J. (Christopher), Drenos, F. (Fotios), Tragante, V. (Vinicius), Munroe, P. (Patricia), Malik, R. (Rainer), Kubisch, C. (Christian), Worrall, B.B. (Bradford B.), Erdmann, J. (Jeanette), Nelson, C.P. (Christopher P.), Samani, N.J. (Nilesh), Schunkert, H. (Heribert), Marchini, J. (Jonathan), Patel, R.S. (Riyaz), Hingorani, A. (Aroon), Kao, W.H.L. (Wen), Pedersen, N.L. (Nancy), Graaf, J. (Jacqueline) de, Kiemeney, L.A.L.M. (Bart), Baumeister, S.E. (Sebastian), Franco, O.H. (Oscar), Hofman, A. (Albert), Uitterlinden, A.G. (André), Koenig, W. (Wolfgang), Meisinger, C. (Christa), Peters, A. (Annette), Thorand, B. (Barbara), Jukema, J.W. (Jan Wouter), Eriksen, B.O. (Bjørn Odvar), Toft, I. (Ingrid), Wilsgaard, T. (Tom), Onland-Moret, N.C. (N. Charlotte), Schouw, Y.T. (Yvonne) van der, Debette, S. (Stéphanie), Kumari, M. (Meena), Svensson, P. (Per), van der Harst, P. (Pim), Kivimaki, M. (Mika), Keating, J. (John), Sattar, N. (Naveed), Dehghan, A. (Abbas), Reiner, A. (Alexander), Ingelsson, E. (Erik), Ruijter, H.M. (Hester ) den, Bakker, P.I.W. (Paul) de, Pasterkamp, G. (Gerard), Ärnlöv, J. (Johan), Holmes, M.V. (Michael), Asselbergs, F.W. (Folkert), Van Der Laan, S.W. (Sander W.), Fall, M. (Magnus), Soumaré, A. (Aicha), Teumer, A. (Alexander), Sedaghat, S. (Sanaz), Baumert, J. (Jens), Zabaneh, D. (Delilah), Setten, J. (Jessica) van, Isgum, I. (Ivana), Galesloot, T.E. (Tessel), Arpegård, J. (Johannes), Amouyel, P. (Philippe), Trompet, S. (Stella), Waldenberger, M. (Melanie), Dörr, M. (Marcus), Magnusson, P.K. (Patrik), Giedraitis, V. (Vilmantas), Larsson, A. (Anders), Morris, A.P. (Andrew), Felix, J.F. (Janine), Morrison, A.C. (Alanna C.), Franceschini, N. (Nora), Bis, J.C. (Joshua), Kavousi, M. (Maryam), O'Donnell, C.J. (Christopher), Drenos, F. (Fotios), Tragante, V. (Vinicius), Munroe, P. (Patricia), Malik, R. (Rainer), Kubisch, C. (Christian), Worrall, B.B. (Bradford B.), Erdmann, J. (Jeanette), Nelson, C.P. (Christopher P.), Samani, N.J. (Nilesh), Schunkert, H. (Heribert), Marchini, J. (Jonathan), Patel, R.S. (Riyaz), Hingorani, A. (Aroon), Kao, W.H.L. (Wen), Pedersen, N.L. (Nancy), Graaf, J. (Jacqueline) de, Kiemeney, L.A.L.M. (Bart), Baumeister, S.E. (Sebastian), Franco, O.H. (Oscar), Hofman, A. (Albert), Uitterlinden, A.G. (André), Koenig, W. (Wolfgang), Meisinger, C. (Christa), Peters, A. (Annette), Thorand, B. (Barbara), Jukema, J.W. (Jan Wouter), Eriksen, B.O. (Bjørn Odvar), Toft, I. (Ingrid), Wilsgaard, T. (Tom), Onland-Moret, N.C. (N. Charlotte), Schouw, Y.T. (Yvonne) van der, Debette, S. (Stéphanie), Kumari, M. (Meena), Svensson, P. (Per), van der Harst, P. (Pim), Kivimaki, M. (Mika), Keating, J. (John), Sattar, N. (Naveed), Dehghan, A. (Abbas), Reiner, A. (Alexander), Ingelsson, E. (Erik), Ruijter, H.M. (Hester ) den, Bakker, P.I.W. (Paul) de, Pasterkamp, G. (Gerard), Ärnlöv, J. (Johan), Holmes, M.V. (Michael), and Asselbergs, F.W. (Folkert)

Abstract

__Background__ Epidemiological studies show that high circulating cystatin C is associated with risk of cardiovascular disease (CVD), independent of creatinine-based renal function measurements. It is unclear whether this relationship is causal, arises from residual confounding, and/or is a consequence of reverse causation. __Objectives__ The aim of this study was to use Mendelian randomization to investigate whether cystatin C is causally related to CVD in the general population. __Methods__ We incorporated participant data from 16 prospective cohorts (n = 76,481) with 37,126 measures of cystatin C and added genetic data from 43 studies (n = 252,216) with 63,292 CVD events. We used the common variant rs911119 in CST3 as an instrumental variable to investigate the causal role of cystatin C in CVD, including coronary heart disease, ischemic stroke, and heart failure. __Results__ Cystatin C concentrations were associated with CVD risk after adjusting for age, sex, and traditional risk factors (relative risk: 1.82 per doubling of cystatin C; 95% confidence interval [CI]: 1.56 to 2.13; p = 2.12 × 10−14). The minor allele of rs911119 was associated with decreased serum cystatin C (6.13% per allele; 95% CI: 5.75 to 6.50; p = 5.95 × 10−211), explaining 2.8% of the observed variation in cystatin C. Mendelian randomization analysis did not provide evidence for a causal role of cystatin C, with a causal relative risk for CVD of 1.00 per doubling cystatin C (95% CI: 0.82 to 1.22; p = 0.994), which was statistically different from the observational estimate (p = 1.6 × 10−5). A causal effect of cystatin C was not detected for any individual component of CVD. __Conclusions__ Mendelian randomization analyses did not support a causal role of cystatin C in the etiology of CVD. As such, therapeutics targeted at lowering circulating cystatin C are unlikely to be effective in preventing CVD.

Published
2016
Full Text
View/download PDF

21. Adult height, coronary heart disease and stroke: A multi-locus Mendelian randomization meta-analysis

Author

Cardiologie, Circulatory Health, Team Medisch, Public Health Epidemiologie, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Cardiovasculaire Epidemiologie, Cardiovasculaire Epi Team 3, Brain, Cancer, JC onderzoeksprogramma Kanker, CDL Upod, Other research (not in main researchprogram), Nüesch, Eveline, Dale, Caroline, Palmer, Tom M., White, Jon, Keating, Brendan J., van Iperen, Erik P A, Goel, Anuj, Padmanabhan, Sandosh, Asselbergs, F. W., Verschuren, W. M., Wijmenga, C., Van der Schouw, Y. T., Onland-Moret, N. C., Lange, Leslie A., Hovingh, G. K., Sivapalaratnam, Suthesh, Morris, Richard W., Whincup, Peter H., Wannamethe, Goya S., Gaunt, Tom R., Ebrahim, Shah, Steel, Laura, Nair, Nikhil, Reiner, Alexander P., Kooperberg, Charles, Wilson, James F., Bolton, Jennifer L., McLachlan, Stela, Price, Jacqueline F., Strachan, Mark W J, Robertson, Christine M., Kleber, Marcus E., Delgado, Graciela, März, Winfried, Melander, Olle, Dominiczak, Anna F., Farrall, Martin, Watkins, Hugh, Leusink, Maarten, Maitland-van der Zee, Anke H., de Groot, Mark C H, Dudbridge, Frank, Hingorani, Aroon, Ben-Shlomo, Yoav, Lawlor, Debbie A., Amuzu, A., Caufield, M., Cavadino, A., Cooper, J., Davies, T. L., Day, I. N., Drenos, F., Engmann, J., Finan, C., Giambartolomei, C., Hardy, R., Humphries, S. E., Hypponen, E., Kivimaki, M., Kuh, D., Kumari, M., Ong, K., Plagnol, V., Power, C., Richards, M., Shah, S., Shah, T., Sofat, R., Talmud, P. J., Wareham, N., Warren, H., Whittaker, J. C., Wong, A., Zabaneh, D., Smith, George Davey, Wells, Jonathan C., Leon, David A., Holmes, Michael V., Casas, Juan P., Cardiologie, Circulatory Health, Team Medisch, Public Health Epidemiologie, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Cardiovasculaire Epidemiologie, Cardiovasculaire Epi Team 3, Brain, Cancer, JC onderzoeksprogramma Kanker, CDL Upod, Other research (not in main researchprogram), Nüesch, Eveline, Dale, Caroline, Palmer, Tom M., White, Jon, Keating, Brendan J., van Iperen, Erik P A, Goel, Anuj, Padmanabhan, Sandosh, Asselbergs, F. W., Verschuren, W. M., Wijmenga, C., Van der Schouw, Y. T., Onland-Moret, N. C., Lange, Leslie A., Hovingh, G. K., Sivapalaratnam, Suthesh, Morris, Richard W., Whincup, Peter H., Wannamethe, Goya S., Gaunt, Tom R., Ebrahim, Shah, Steel, Laura, Nair, Nikhil, Reiner, Alexander P., Kooperberg, Charles, Wilson, James F., Bolton, Jennifer L., McLachlan, Stela, Price, Jacqueline F., Strachan, Mark W J, Robertson, Christine M., Kleber, Marcus E., Delgado, Graciela, März, Winfried, Melander, Olle, Dominiczak, Anna F., Farrall, Martin, Watkins, Hugh, Leusink, Maarten, Maitland-van der Zee, Anke H., de Groot, Mark C H, Dudbridge, Frank, Hingorani, Aroon, Ben-Shlomo, Yoav, Lawlor, Debbie A., Amuzu, A., Caufield, M., Cavadino, A., Cooper, J., Davies, T. L., Day, I. N., Drenos, F., Engmann, J., Finan, C., Giambartolomei, C., Hardy, R., Humphries, S. E., Hypponen, E., Kivimaki, M., Kuh, D., Kumari, M., Ong, K., Plagnol, V., Power, C., Richards, M., Shah, S., Shah, T., Sofat, R., Talmud, P. J., Wareham, N., Warren, H., Whittaker, J. C., Wong, A., Zabaneh, D., Smith, George Davey, Wells, Jonathan C., Leon, David A., Holmes, Michael V., and Casas, Juan P.

Published
2016

22. Cystatin C and Cardiovascular Disease A Mendelian Randomization Study

Author

van der Laan, SW, Fall, T, Soumare, A, Teumer, A, Sedaghat, Sanaz, Baumert, J, Zabaneh, D, van Setten, J, Isgum, I, Galesloot, TE, Arpegard, J, Amouyel, P, Trompet, S, Waldenberger, M, Dorr, M, Magnusson, PK, Giedraitis, V, Larsson, A, Morris, AP, Felix, Janine, Morrison, AC, Franceschini, N, Bis, JC, Kavousi, Maryam, O'Donnell, C, Drenos, F, Tragante, V, Munroe, PB, Malik, R, Dichgans, M, Worrall, BB, Erdmann, J, Nelson, CP, Samani, NJ, Schunkert, H, Marchini, J, Patel, RS, Hingorani, AD, Lind, L, Pedersen, NL, van der Graaf, J, Kiemeney, LALM, Baumeister, SE, Franco Duran, OH, Hofman, Bert, Uitterlinden, André, Koenig, W, Meisinger, C, Peters, A, Thorand, B, Jukema, JW, Eriksen, B O, Toft, I, Wilsgaard, T, Onland-Moret, NC, van der Schouw, YT, Debette, S, Kumari, M, Svensson, P, van der Harst, P, Kivimaki, M, Keating, BJ, Sattar, N, Dehghan, Abbas, Reiner, AP, Ingelsson, E, den Ruijter, HM, de Bakker, PIW, Pasterkamp, G, Arnlov, J, Holmes, MV, Asselbergs, FW, van der Laan, SW, Fall, T, Soumare, A, Teumer, A, Sedaghat, Sanaz, Baumert, J, Zabaneh, D, van Setten, J, Isgum, I, Galesloot, TE, Arpegard, J, Amouyel, P, Trompet, S, Waldenberger, M, Dorr, M, Magnusson, PK, Giedraitis, V, Larsson, A, Morris, AP, Felix, Janine, Morrison, AC, Franceschini, N, Bis, JC, Kavousi, Maryam, O'Donnell, C, Drenos, F, Tragante, V, Munroe, PB, Malik, R, Dichgans, M, Worrall, BB, Erdmann, J, Nelson, CP, Samani, NJ, Schunkert, H, Marchini, J, Patel, RS, Hingorani, AD, Lind, L, Pedersen, NL, van der Graaf, J, Kiemeney, LALM, Baumeister, SE, Franco Duran, OH, Hofman, Bert, Uitterlinden, André, Koenig, W, Meisinger, C, Peters, A, Thorand, B, Jukema, JW, Eriksen, B O, Toft, I, Wilsgaard, T, Onland-Moret, NC, van der Schouw, YT, Debette, S, Kumari, M, Svensson, P, van der Harst, P, Kivimaki, M, Keating, BJ, Sattar, N, Dehghan, Abbas, Reiner, AP, Ingelsson, E, den Ruijter, HM, de Bakker, PIW, Pasterkamp, G, Arnlov, J, Holmes, MV, and Asselbergs, FW

Published
2016

23. Phenome-wide analysis of genome-wide polygenic scores

Author

Krapohl, E, primary, Euesden, J, additional, Zabaneh, D, additional, Pingault, J-B, additional, Rimfeld, K, additional, von Stumm, S, additional, Dale, P S, additional, Breen, G, additional, O'Reilly, P F, additional, and Plomin, R, additional

Published
2015
Full Text
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24. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

Author

Mahajan, A, Go, MJ, Zhang, W, Below, JE, Gaulton, KJ, Ferreira, T, Horikoshi, M, Johnson, AD, Ng, MCY, Prokopenko, I, Saleheen, D, Wang, X, Zeggini, E, Abecasis, GR, Adair, LS, Almgren, P, Atalay, M, Aung, T, Baldassarre, D, Balkau, B, Bao, Y, Barnett, AH, Barroso, I, Basit, A, Been, LF, Beilby, J, Bell, GI, Benediktsson, R, Bergman, RN, Boehm, BO, Boerwinkle, E, Bonnycastle, LL, Burtt, N, Cai, Q, Campbell, H, Carey, J, Cauchi, S, Caulfield, M, Chan, JCN, Chang, L-C, Chang, T-J, Chang, Y-C, Charpentier, G, Chen, C-H, Chen, H, Chen, Y-T, Chia, K-S, Chidambaram, M, Chines, PS, Cho, NH, Cho, YM, Chuang, L-M, Collins, FS, Cornelis, MC, Couper, DJ, Crenshaw, AT, van Dam, RM, Danesh, J, Das, D, de Faire, U, Dedoussis, G, Deloukas, P, Dimas, AS, Dina, C, Doney, ASF, Donnelly, PJ, Dorkhan, M, van Duijn, C, Dupuis, J, Edkins, S, Elliott, P, Emilsson, V, Erbel, R, Eriksson, JG, Escobedo, J, Esko, T, Eury, E, Florez, JC, Fontanillas, P, Forouhi, NG, Forsen, T, Fox, C, Fraser, RM, Frayling, TM, Froguel, P, Frossard, P, Gao, Y, Gertow, K, Gieger, C, Gigante, B, Grallert, H, Grant, GB, Groop, LC, Groves, CJ, Grundberg, E, Guiducci, C, Hamsten, A, Han, B-G, Hara, K, Hassanali, N, Hattersley, AT, Hayward, C, Hedman, AK, Herder, C, Hofman, A, Holmen, OL, Hovingh, K, Hreidarsson, AB, Hu, C, Hu, FB, Hui, J, Humphries, SE, Hunt, SE, Hunter, DJ, Hveem, K, Hydrie, ZI, Ikegami, H, Illig, T, Ingelsson, E, Islam, M, Isomaa, B, Jackson, AU, Jafar, T, James, A, Jia, W, Joeckel, K-H, Jonsson, A, Jowett, JBM, Kadowaki, T, Kang, HM, Kanoni, S, Kao, WHL, Kathiresan, S, Kato, N, Katulanda, P, Keinanen-Kiukaanniemi, SM, Kelly, AM, Khan, H, Khaw, K-T, Khor, C-C, Kim, H-L, Kim, S, Kim, YJ, Kinnunen, L, Klopp, N, Kong, A, Korpi-Hyovalti, E, Kowlessur, S, Kraft, P, Kravic, J, Kristensen, MM, Krithika, S, Kumar, A, Kumate, J, Kuusisto, J, Kwak, SH, Laakso, M, Lagou, V, Lakka, TA, Langenberg, C, Langford, C, Lawrence, R, Leander, K, Lee, J-M, Lee, NR, Li, M, Li, X, Li, Y, Liang, J, Liju, S, Lim, W-Y, Lind, L, Lindgren, CM, Lindholm, E, Liu, C-T, Liu, JJ, Lobbens, S, Long, J, Loos, RJF, Lu, W, Luan, J, Lyssenko, V, Ma, RCW, Maeda, S, Maegi, R, Mannisto, S, Matthews, DR, Meigs, JB, Melander, O, Metspalu, A, Meyer, J, Mirza, G, Mihailov, E, Moebus, S, Mohan, V, Mohlke, KL, Morris, AD, Muehleisen, TW, Mueller-Nurasyid, M, Musk, B, Nakamura, J, Nakashima, E, Navarro, P, Peng-Keat, N, Nica, AC, Nilsson, PM, Njolstad, I, Noethen, MM, Ohnaka, K, Ong, TH, Owen, KR, Palmer, CNA, Pankow, JS, Park, KS, Parkin, M, Pechlivanis, S, Pedersen, NL, Peltonen, L, Perry, JRB, Peters, A, Pinidiyapathirage, JM, Platou, CGP, Potter, S, Price, JF, Qi, L, Radha, V, Rallidis, L, Rasheed, A, Rathmann, W, Rauramaa, R, Raychaudhuri, S, Rayner, NW, Rees, SD, Rehnberg, E, Ripatti, S, Robertson, N, Roden, M, Rossin, EJ, Rudan, I, Rybin, D, Saaristo, TE, Salomaa, V, Saltevo, J, Samuel, M, Sanghera, DK, Saramies, J, Scott, J, Scott, LJ, Scott, RA, Segre, AV, Sehmi, J, Sennblad, B, Shah, N, Shah, S, Shera, AS, Shu, XO, Shuldiner, AR, Sigurdsson, G, Sijbrands, E, Silveira, A, Sim, X, Sivapalaratnam, S, Small, KS, So, WY, Stancakova, A, Stefansson, K, Steinbach, G, Steinthorsdottir, V, Stirrups, K, Strawbridge, RJ, Stringham, HM, Sun, Q, Suo, C, Syvanen, A-C, Takayanagi, R, Takeuchi, F, Tay, WT, Teslovich, TM, Thorand, B, Thorleifsson, G, Thorsteinsdottir, U, Tikkanen, E, Trakalo, J, Tremoli, E, Trip, MD, Tsai, FJ, Tuomi, T, Tuomilehto, J, Uitterlinden, AG, Valladares-Salgado, A, Vedantam, S, Veglia, F, Voight, BF, Wang, C, Wareham, NJ, Wennauer, R, Wickremasinghe, AR, Wilsgaard, T, Wilson, JF, Wiltshire, S, Winckler, W, Wong, TY, Wood, AR, Wu, J-Y, Wu, Y, Yamamoto, K, Yamauchi, T, Yang, M, Yengo, L, Yokota, M, Young, R, Zabaneh, D, Zhang, F, Zhang, R, Zheng, W, Zimmet, PZ, Altshuler, D, Bowden, DW, Cho, YS, Cox, NJ, Cruz, M, Hanis, CL, Kooner, J, Lee, J-Y, Seielstad, M, Teo, YY, Boehnke, M, Parra, EJ, Chambers, JC, Tai, ES, McCarthy, MI, Morris, AP, Mahajan, A, Go, MJ, Zhang, W, Below, JE, Gaulton, KJ, Ferreira, T, Horikoshi, M, Johnson, AD, Ng, MCY, Prokopenko, I, Saleheen, D, Wang, X, Zeggini, E, Abecasis, GR, Adair, LS, Almgren, P, Atalay, M, Aung, T, Baldassarre, D, Balkau, B, Bao, Y, Barnett, AH, Barroso, I, Basit, A, Been, LF, Beilby, J, Bell, GI, Benediktsson, R, Bergman, RN, Boehm, BO, Boerwinkle, E, Bonnycastle, LL, Burtt, N, Cai, Q, Campbell, H, Carey, J, Cauchi, S, Caulfield, M, Chan, JCN, Chang, L-C, Chang, T-J, Chang, Y-C, Charpentier, G, Chen, C-H, Chen, H, Chen, Y-T, Chia, K-S, Chidambaram, M, Chines, PS, Cho, NH, Cho, YM, Chuang, L-M, Collins, FS, Cornelis, MC, Couper, DJ, Crenshaw, AT, van Dam, RM, Danesh, J, Das, D, de Faire, U, Dedoussis, G, Deloukas, P, Dimas, AS, Dina, C, Doney, ASF, Donnelly, PJ, Dorkhan, M, van Duijn, C, Dupuis, J, Edkins, S, Elliott, P, Emilsson, V, Erbel, R, Eriksson, JG, Escobedo, J, Esko, T, Eury, E, Florez, JC, Fontanillas, P, Forouhi, NG, Forsen, T, Fox, C, Fraser, RM, Frayling, TM, Froguel, P, Frossard, P, Gao, Y, Gertow, K, Gieger, C, Gigante, B, Grallert, H, Grant, GB, Groop, LC, Groves, CJ, Grundberg, E, Guiducci, C, Hamsten, A, Han, B-G, Hara, K, Hassanali, N, Hattersley, AT, Hayward, C, Hedman, AK, Herder, C, Hofman, A, Holmen, OL, Hovingh, K, Hreidarsson, AB, Hu, C, Hu, FB, Hui, J, Humphries, SE, Hunt, SE, Hunter, DJ, Hveem, K, Hydrie, ZI, Ikegami, H, Illig, T, Ingelsson, E, Islam, M, Isomaa, B, Jackson, AU, Jafar, T, James, A, Jia, W, Joeckel, K-H, Jonsson, A, Jowett, JBM, Kadowaki, T, Kang, HM, Kanoni, S, Kao, WHL, Kathiresan, S, Kato, N, Katulanda, P, Keinanen-Kiukaanniemi, SM, Kelly, AM, Khan, H, Khaw, K-T, Khor, C-C, Kim, H-L, Kim, S, Kim, YJ, Kinnunen, L, Klopp, N, Kong, A, Korpi-Hyovalti, E, Kowlessur, S, Kraft, P, Kravic, J, Kristensen, MM, Krithika, S, Kumar, A, Kumate, J, Kuusisto, J, Kwak, SH, Laakso, M, Lagou, V, Lakka, TA, Langenberg, C, Langford, C, Lawrence, R, Leander, K, Lee, J-M, Lee, NR, Li, M, Li, X, Li, Y, Liang, J, Liju, S, Lim, W-Y, Lind, L, Lindgren, CM, Lindholm, E, Liu, C-T, Liu, JJ, Lobbens, S, Long, J, Loos, RJF, Lu, W, Luan, J, Lyssenko, V, Ma, RCW, Maeda, S, Maegi, R, Mannisto, S, Matthews, DR, Meigs, JB, Melander, O, Metspalu, A, Meyer, J, Mirza, G, Mihailov, E, Moebus, S, Mohan, V, Mohlke, KL, Morris, AD, Muehleisen, TW, Mueller-Nurasyid, M, Musk, B, Nakamura, J, Nakashima, E, Navarro, P, Peng-Keat, N, Nica, AC, Nilsson, PM, Njolstad, I, Noethen, MM, Ohnaka, K, Ong, TH, Owen, KR, Palmer, CNA, Pankow, JS, Park, KS, Parkin, M, Pechlivanis, S, Pedersen, NL, Peltonen, L, Perry, JRB, Peters, A, Pinidiyapathirage, JM, Platou, CGP, Potter, S, Price, JF, Qi, L, Radha, V, Rallidis, L, Rasheed, A, Rathmann, W, Rauramaa, R, Raychaudhuri, S, Rayner, NW, Rees, SD, Rehnberg, E, Ripatti, S, Robertson, N, Roden, M, Rossin, EJ, Rudan, I, Rybin, D, Saaristo, TE, Salomaa, V, Saltevo, J, Samuel, M, Sanghera, DK, Saramies, J, Scott, J, Scott, LJ, Scott, RA, Segre, AV, Sehmi, J, Sennblad, B, Shah, N, Shah, S, Shera, AS, Shu, XO, Shuldiner, AR, Sigurdsson, G, Sijbrands, E, Silveira, A, Sim, X, Sivapalaratnam, S, Small, KS, So, WY, Stancakova, A, Stefansson, K, Steinbach, G, Steinthorsdottir, V, Stirrups, K, Strawbridge, RJ, Stringham, HM, Sun, Q, Suo, C, Syvanen, A-C, Takayanagi, R, Takeuchi, F, Tay, WT, Teslovich, TM, Thorand, B, Thorleifsson, G, Thorsteinsdottir, U, Tikkanen, E, Trakalo, J, Tremoli, E, Trip, MD, Tsai, FJ, Tuomi, T, Tuomilehto, J, Uitterlinden, AG, Valladares-Salgado, A, Vedantam, S, Veglia, F, Voight, BF, Wang, C, Wareham, NJ, Wennauer, R, Wickremasinghe, AR, Wilsgaard, T, Wilson, JF, Wiltshire, S, Winckler, W, Wong, TY, Wood, AR, Wu, J-Y, Wu, Y, Yamamoto, K, Yamauchi, T, Yang, M, Yengo, L, Yokota, M, Young, R, Zabaneh, D, Zhang, F, Zhang, R, Zheng, W, Zimmet, PZ, Altshuler, D, Bowden, DW, Cho, YS, Cox, NJ, Cruz, M, Hanis, CL, Kooner, J, Lee, J-Y, Seielstad, M, Teo, YY, Boehnke, M, Parra, EJ, Chambers, JC, Tai, ES, McCarthy, MI, and Morris, AP

Abstract

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

Published
2014

25. Genome-wide association study identifies variants in TMPRSS6 associated with hemoglobin levels

Author

Sehmi, J., Sternberg, M.J.E., Wass, M.N., Li, Y., Ruokonen, A., Kooner, J.S., Maxwell, P.H., Hoggart, C., Peltonen, L., Elliott, P., Srai, S.K., McCarthy, M.I., Scott, J., Chambers, J.C., Jarvelin, M.-R., Zabaneh, D., Zhang, W., Abecasis, G., Bayele, H., and Freimer, N.B.

Abstract

We carried out a genome-wide association study of hemoglobin levels in 16,001 individuals of European and Indian Asian ancestry. The most closely associated SNP (rs855791) results in nonsynonymous (V736A) change in the serine protease domain of TMPRSS6 and a blood hemoglobin concentration 0.13 (95% CI 0.09-0.17) g/dl lower per copy of allele A (P = 1.6 �� 10 13). Our findings suggest that TMPRSS6, a regulator of hepcidin synthesis and iron handling, is crucial in hemoglobin level maintenance.

Published
2009
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29. A gene-centric study of common carotid artery remodelling

Author

Harrison, S.C., Zabaneh, D., Asselbergs, F.W., Drenos, F., Jones, G.T., Shah, S., Gertow, K., Sennblad, B., Strawbridge, R.J., Gigante, B., Holewijn, S., Graaf, J. de, Vermeulen, S., Folkersen, L., Rij, A.M. van, Baldassarre, D., Veglia, F., Talmud, P.J., Deanfield, J.E., Agu, O., Kivimäki, M., Kumari, M., Bown, M.J., Nyyssonen, K., Rauramaa, R., Smit, A.J., Franco-Cereceda, A., Giral, P., Mannarino, E., Silveira, A., Syvanen, A.C., Borst, G.J. de, Graaf, Y. van der, Faire, U. de, Baas, A.F., Blankensteijn, J.D., Wareham, N.J., Fowkes, G., Tzoulaki, I., Price, J.F., Tremoli, E., Hingorani, A.D., Eriksson, P., Hamsten, A., Humphries, S.E., Harrison, S.C., Zabaneh, D., Asselbergs, F.W., Drenos, F., Jones, G.T., Shah, S., Gertow, K., Sennblad, B., Strawbridge, R.J., Gigante, B., Holewijn, S., Graaf, J. de, Vermeulen, S., Folkersen, L., Rij, A.M. van, Baldassarre, D., Veglia, F., Talmud, P.J., Deanfield, J.E., Agu, O., Kivimäki, M., Kumari, M., Bown, M.J., Nyyssonen, K., Rauramaa, R., Smit, A.J., Franco-Cereceda, A., Giral, P., Mannarino, E., Silveira, A., Syvanen, A.C., Borst, G.J. de, Graaf, Y. van der, Faire, U. de, Baas, A.F., Blankensteijn, J.D., Wareham, N.J., Fowkes, G., Tzoulaki, I., Price, J.F., Tremoli, E., Hingorani, A.D., Eriksson, P., Hamsten, A., and Humphries, S.E.

Abstract

Item does not contain fulltext, BACKGROUND: Expansive remodelling is the process of compensatory arterial enlargement in response to atherosclerotic stimuli. The genetic determinants of this process are poorly characterized. METHODS: Genetic association analyses of inter-adventitial common carotid artery diameter (ICCAD) in the IMPROVE study (n = 3427) using the Illumina 200k Metabochip was performed. Single nucleotide polymorphisms (SNPs) that met array-wide significance were taken forward for analysis in three further studies (n = 5704), and tested for association with Abdominal Aortic Aneurysm (AAA). RESULTS: rs3768445 on Chromosome 1q24.3, in a cluster of protein coding genes (DNM3, PIGC, C1orf105) was associated with larger ICCAD in the IMPROVE study. For each copy of the rare allele carried, ICCAD was on average 0.13 mm greater (95% CI 0.08-0.18 mm, P = 8.2 x 10(-8)). A proxy SNP (rs4916251, R(2) = 0.99) did not, however, show association with ICCAD in three follow-up studies (P for replication = 0.29). There was evidence of interaction between carotid intima-media thickness (CIMT) and rs4916251 on ICCAD in two of the cohorts studies suggesting that it plays a role in the remodelling response to atherosclerosis. In meta-analysis of 5 case-control studies pooling data from 5007 cases and 43,630 controls, rs4916251 was associated with presence of AAA 1.10, 95% CI 1.03-1.17, p = 2.8 x 10(-3), I(2) = 18.8, Q = 0.30). A proxy SNP, rs4916251 was also associated with increased expression of PIGC in aortic tissue, suggesting that this may the mechanism by which this locus affects vascular remodelling. CONCLUSIONS: Common variation at 1q24.3 is associated with expansive vascular remodelling and risk of AAA. These findings support a hypothesis that pathways involved in systemic vascular remodelling play a role in AAA development.

Published
2013

30. A genome-wide association study for extremely high intelligence

Author

Zabaneh, D, Krapohl, E, Gaspar, H A, Curtis, C, Lee, S H, Patel, H, Newhouse, S, Wu, H M, Simpson, M A, Putallaz, M, Lubinski, D, Plomin, R, and Breen, G

Abstract

We used a case–control genome-wide association (GWA) design with cases consisting of 1238 individuals from the top 0.0003 (~170 mean IQ) of the population distribution of intelligence and 8172 unselected population-based controls. The single-nucleotide polymorphism heritability for the extreme IQ trait was 0.33 (0.02), which is the highest so far for a cognitive phenotype, and significant genome-wide genetic correlations of 0.78 were observed with educational attainment and 0.86 with population IQ. Three variants in locus ADAM12 achieved genome-wide significance, although they did not replicate with published GWA analyses of normal-range IQ or educational attainment. A genome-wide polygenic score constructed from the GWA results accounted for 1.6% of the variance of intelligence in the normal range in an unselected sample of 3414 individuals, which is comparable to the variance explained by GWA studies of intelligence with substantially larger sample sizes. The gene family plexins, members of which are mutated in several monogenic neurodevelopmental disorders, was significantly enriched for associations with high IQ. This study shows the utility of extreme trait selection for genetic study of intelligence and suggests that extremely high intelligence is continuous genetically with normal-range intelligence in the population.

Published
2018
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32. A Genome-Wide Association Study of the Metabolic Syndrome in Indian Asian Men

Author

Ruiz, JR, Zabaneh, D, Balding, DJ, Ruiz, JR, Zabaneh, D, and Balding, DJ

Abstract

We conducted a two-stage genome-wide association study to identify common genetic variation altering risk of the metabolic syndrome and related phenotypes in Indian Asian men, who have a high prevalence of these conditions. In Stage 1, approximately 317,000 single nucleotide polymorphisms were genotyped in 2700 individuals, from which 1500 SNPs were selected to be genotyped in a further 2300 individuals. Selection for inclusion in Stage 1 was based on four metabolic syndrome component traits: HDL-cholesterol, plasma glucose and Type 2 diabetes, abdominal obesity measured by waist to hip ratio, and diastolic blood pressure. Association was tested with these four traits and a composite metabolic syndrome phenotype. Four SNPs reaching significance level p<5x10(-7) and with posterior probability of association >0.8 were found in genes CETP and LPL, associated with HDL-cholesterol. These associations have already been reported in Indian Asians and in Europeans. Five additional loci harboured SNPs significant at p<10(-6) and posterior probability >0.5 for HDL-cholesterol, type 2 diabetes or diastolic blood pressure. Our results suggest that the primary genetic determinants of metabolic syndrome are the same in Indian Asians as in other populations, despite the higher prevalence. Further, we found little evidence of a common genetic basis for metabolic syndrome traits in our sample of Indian Asian men.

Published
2010

33. Common Genetic Variation Near Melatonin Receptor MTNR1B Contributes to Raised Plasma Glucose and Increased Risk of Type 2 Diabetes Among Indian Asians and European Caucasians

Author

Chambers, JC, Zhang, W, Zabaneh, D, Sehmi, J, Jain, P, McCarthy, MI, Froguel, P, Ruokonen, A, Balding, D, Jarvelin, M-R, Scott, J, Elliott, P, Kooner, JS, Chambers, JC, Zhang, W, Zabaneh, D, Sehmi, J, Jain, P, McCarthy, MI, Froguel, P, Ruokonen, A, Balding, D, Jarvelin, M-R, Scott, J, Elliott, P, and Kooner, JS

Abstract

OBJECTIVE: Fasting plasma glucose and risk of type 2 diabetes are higher among Indian Asians than among European and North American Caucasians. Few studies have investigated genetic factors influencing glucose metabolism among Indian Asians. RESEARCH DESIGN AND METHODS: We carried out genome-wide association studies for fasting glucose in 5,089 nondiabetic Indian Asians genotyped with the Illumina Hap610 BeadChip and 2,385 Indian Asians (698 with type 2 diabetes) genotyped with the Illumina 300 BeadChip. Results were compared with findings in 4,462 European Caucasians. RESULTS: We identified three single nucleotide polymorphisms (SNPs) associated with glucose among Indian Asians at P < 5 x 10(-8), all near melatonin receptor MTNR1B. The most closely associated was rs2166706 (combined P = 2.1 x 10(-9)), which is in moderate linkage disequilibrium with rs1387153 (r(2) = 0.60) and rs10830963 (r(2) = 0.45), both previously associated with glucose in European Caucasians. Risk allele frequency and effect sizes for rs2166706 were similar among Indian Asians and European Caucasians: frequency 46.2 versus 45.0%, respectively (P = 0.44); effect 0.05 (95% CI 0.01-0.08) versus 0.05 (0.03-0.07 mmol/l), respectively, higher glucose per allele copy (P = 0.84). SNP rs2166706 was associated with type 2 diabetes in Indian Asians (odds ratio 1.21 [95% CI 1.06-1.38] per copy of risk allele; P = 0.006). SNPs at the GCK, GCKR, and G6PC2 loci were also associated with glucose among Indian Asians. Risk allele frequencies of rs1260326 (GCKR) and rs560887 (G6PC2) were higher among Indian Asians compared with European Caucasians. CONCLUSIONS: Common genetic variation near MTNR1B influences blood glucose and risk of type 2 diabetes in Indian Asians. Genetic variation at the MTNR1B, GCK, GCKR, and G6PC2 loci may contribute to abnormal glucose metabolism and related metabolic disturbances among Indian Asians.

Published
2009

34. Phenome-wide analysis of genome-wide polygenic scores

Author

Krapohl, E, Euesden, J, Zabaneh, D, Pingault, J-B, Rimfeld, K, von Stumm, S, Dale, P S, Breen, G, O'Reilly, P F, and Plomin, R

Abstract

Genome-wide polygenic scores (GPS), which aggregate the effects of thousands of DNA variants from genome-wide association studies (GWAS), have the potential to make genetic predictions for individuals. We conducted a systematic investigation of associations between GPS and many behavioral traits, the behavioral phenome. For 3152 unrelated 16-year-old individuals representative of the United Kingdom, we created 13 GPS from the largest GWAS for psychiatric disorders (for example, schizophrenia, depression and dementia) and cognitive traits (for example, intelligence, educational attainment and intracranial volume). The behavioral phenome included 50 traits from the domains of psychopathology, personality, cognitive abilities and educational achievement. We examined phenome-wide profiles of associations for the entire distribution of each GPS and for the extremes of the GPS distributions. The cognitive GPS yielded stronger predictive power than the psychiatric GPS in our UK-representative sample of adolescents. For example, education GPS explained variation in adolescents’ behavior problems (~0.6%) and in educational achievement (~2%) but psychiatric GPS were associated with neither. Despite the modest effect sizes of current GPS, quantile analyses illustrate the ability to stratify individuals by GPS and opportunities for research. For example, the highest and lowest septiles for the education GPS yielded a 0.5 s.d. difference in mean math grade and a 0.25 s.d. difference in mean behavior problems. We discuss the usefulness and limitations of GPS based on adult GWAS to predict genetic propensities earlier in development.

Published
2016
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36. Mendelian randomization of blood lipids for coronary heart disease

Author

Mv, Holmes, Fw, Asselbergs, Tm, Palmer, Drenos F, Matthew Lanktree, Cp, Nelson, Ce, Dale, Padmanabhan S, Finan C, Di, Swerdlow, Tragante V, Ep, Iperen, Sivapalaratnam S, Shah S, Cc, Elbers, Shah T, Engmann J, Giambartolomei C, White J, Zabaneh D, Sofat R, McLachlan S, Ucleb, On Behalf Of The Consortium, Pa, Doevendans, Aj, Balmforth, As, Hall, Ke, North, Almoguera B, Rc, Hoogeveen, Cushman M, Fornage M, Sr, Patel, Redline S, Ds, Siscovick, My, Tsai, Kj, Karczewski, Mh, Hofker, Wm, Verschuren, Ml, Bots, Yt, Schouw, Melander O, Af, Dominiczak, Morris R, Ben-Shlomo Y, Price J, Kumari M, Baumert J, Peters A, Thorand B, Koenig W, Tr, Gaunt, Se, Humphries, Clarke R, Watkins H, Farrall M, Jg, Wilson, Ss, Rich, Pi, Bakker, La, Lange, Davey Smith G, Ap, Reiner, Pj, Talmud, Kivimäki M, Da, Lawlor, Dudbridge F, Nj, Samani, Bj, Keating, Ad, Hingorani, and Jp, Casas

Subjects
lipids (amino acids, peptides, and proteins)
Abstract

AIMS: To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. METHODS AND RESULTS: We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10(-6)); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75). CONCLUSION: The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.

37. Cystatin c and cardiovascular disease: a Mendelian randomization study

Author

van der Laan, SW, Fall, T, Soumaré, A, Teumer, A, Sedaghat, S, Baumert, J, Zabaneh, D, van Setten, J, Isgum, I, Galesloot, TE, Arpegård, J, Amouyel, P, Trompet, S, Waldenberger, M, Dörr, M, Magnusson, PK, Giedraitis, V, Larsson, A, Morris, A, Felix, JF, Morrison, AC, Franceschini, N, Bis, JC, Kavousi, M, O'Donnell, C, Drenos, F, Tragante, V, Munroe, PB, Malik, R, Dichgans, M, Worrall, BB, Erdmann, J, Nelson, CP, Samani, NJ, Schunkert, H, Marchini, J, Patel, RS, Hingorani, AD, Lind, L, Pedersen, NL, de Graaf, J, Kiemeney, LA, Baumeister, SE, Franco, OH, Hofman, A, Uitterlinden, AG, Koenig, W, Meisinger, C, Peters, A, Thorand, B, Jukema, JW, Eriksen, BO, Toft, I, Wilsgaard, T, Onland-Moret, NC, van der Schouw, YT, Debette, S, Kumari, M, Svensson, P, van der Harst, P, Kivimaki, M, Keating, BJ, Sattar, N, Dehghan, A, Reiner, AP, Ingelsson, E, den Ruijter, HM, de Bakker, PI, Pasterkamp, G, Ärnlöv, J, Holmes, M, and Asselbergs, FW

Subjects
urologic and male genital diseases, reproductive and urinary physiology, female genital diseases and pregnancy complications
Abstract

Epidemiological studies show that high circulating cystatin C is associated with risk of cardiovascular disease (CVD), independent of creatinine-based renal function measurements. It is unclear whether this relationship is causal, arises from residual confounding, and/or is a consequence of reverse causation.The aim of this study was to use Mendelian randomization to investigate whether cystatin C is causally related to CVD in the general population.We incorporated participant data from 16 prospective cohorts (n = 76,481) with 37,126 measures of cystatin C and added genetic data from 43 studies (n = 252,216) with 63,292 CVD events. We used the common variant rs911119 in CST3 as an instrumental variable to investigate the causal role of cystatin C in CVD, including coronary heart disease, ischemic stroke, and heart failure.Cystatin C concentrations were associated with CVD risk after adjusting for age, sex, and traditional risk factors (relative risk: 1.82 per doubling of cystatin C; 95% confidence interval [CI]: 1.56 to 2.13; p = 2.12 × 10(-14)). The minor allele of rs911119 was associated with decreased serum cystatin C (6.13% per allele; 95% CI: 5.75 to 6.50; p = 5.95 × 10(-211)), explaining 2.8% of the observed variation in cystatin C. Mendelian randomization analysis did not provide evidence for a causal role of cystatin C, with a causal relative risk for CVD of 1.00 per doubling cystatin C (95% CI: 0.82 to 1.22; p = 0.994), which was statistically different from the observational estimate (p = 1.6 × 10(-5)). A causal effect of cystatin C was not detected for any individual component of CVD.Mendelian randomization analyses did not support a causal role of cystatin C in the etiology of CVD. As such, therapeutics targeted at lowering circulating cystatin C are unlikely to be effective in preventing CVD.

41. Phenome-wide analysis of genome-wide polygenic scores

Author

Krapohl, E., Euesden, J., Zabaneh, D., Pingault, J.-B., Rimfeld, K., von Stumm, S., Dale, P. S., Breen, G., O'Reilly, P. F., Plomin, R., Krapohl, E., Euesden, J., Zabaneh, D., Pingault, J.-B., Rimfeld, K., von Stumm, S., Dale, P. S., Breen, G., O'Reilly, P. F., and Plomin, R.

Abstract

Genome-wide polygenic scores (GPS), which aggregate the effects of thousands of DNA variants from genome-wide association studies (GWAS), have the potential to make genetic predictions for individuals. We conducted a systematic investigation of associations between GPS and many behavioral traits, the behavioral phenome. For 3152 unrelated 16-year-old individuals representative of the United Kingdom, we created 13 GPS from the largest GWAS for psychiatric disorders (for example, schizophrenia, depression and dementia) and cognitive traits (for example, intelligence, educational attainment and intracranial volume). The behavioral phenome included 50 traits from the domains of psychopathology, personality, cognitive abilities and educational achievement. We examined phenome-wide profiles of associations for the entire distribution of each GPS and for the extremes of the GPS distributions. The cognitive GPS yielded stronger predictive power than the psychiatric GPS in our UK-representative sample of adolescents. For example, education GPS explained variation in adolescents’ behavior problems (~0.6%) and in educational achievement (~2%) but psychiatric GPS were associated with neither. Despite the modest effect sizes of current GPS, quantile analyses illustrate the ability to stratify individuals by GPS and opportunities for research. For example, the highest and lowest septiles for the education GPS yielded a 0.5 s.d. difference in mean math grade and a 0.25 s.d. difference in mean behavior problems. We discuss the usefulness and limitations of GPS based on adult GWAS to predict genetic propensities earlier in development.

42. A genome-wide association study for extremely high intelligence

Author

Gerome Breen, Robert Plomin, H M Wu, Eva Krapohl, Delilah Zabaneh, Helena Gaspar, Martha Putallaz, Charles Curtis, Hamel Patel, Sang Hyuck Lee, Stephen Newhouse, David Lubinski, Michael A. Simpson, Zabaneh, D, Krapohl, E, Gaspar, HA, Curtis, C, Lee, Sang Hong, Patel, H, Newhouse, S, Wu, HM, Simpson, MA, Putallaz, M, Lubinski, D, Plomin, R, and Breen, G

Subjects
Adult, Male, 0301 basic medicine, Multifactorial Inheritance, Adolescent, Intelligence, Population, ADAM12 Protein, Locus (genetics), Genome-wide association study, Quantitative trait locus, high intelligence, Polymorphism, Single Nucleotide, genetic study, 03 medical and health sciences, Cellular and Molecular Neuroscience, Quantitative Trait, Heritable, genome-wide association (GWA), Humans, Longitudinal Studies, education, Molecular Biology, Genetics, education.field_of_study, Heritability, Explained variation, Psychiatry and Mental health, Phenotype, 030104 developmental biology, Sample size determination, Case-Control Studies, educational attainment, Trait, Original Article, Female, Psychology, Genome-Wide Association Study, Clinical psychology
Abstract

We used a case-control genome-wide association (GWA) design with cases consisting of 1238 individuals from the top 0.0003 (∼170 mean IQ) of the population distribution of intelligence and 8172 unselected population-based controls. The single-nucleotide polymorphism heritability for the extreme IQ trait was 0.33 (0.02), which is the highest so far for a cognitive phenotype, and significant genome-wide genetic correlations of 0.78 were observed with educational attainment and 0.86 with population IQ. Three variants in locus ADAM12 achieved genome-wide significance, although they did not replicate with published GWA analyses of normal-range IQ or educational attainment. A genome-wide polygenic score constructed from the GWA results accounted for 1.6% of the variance of intelligence in the normal range in an unselected sample of 3414 individuals, which is comparable to the variance explained by GWA studies of intelligence with substantially larger sample sizes. The gene family plexins, members of which are mutated in several monogenic neurodevelopmental disorders, was significantly enriched for associations with high IQ. This study shows the utility of extreme trait selection for genetic study of intelligence and suggests that extremely high intelligence is continuous genetically with normal-range intelligence in the population. usc Refereed/Peer-reviewed

Published
2018
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43. Genome-wide association study of circulating interleukin 6 levels identifies novel loci.

Author

Ahluwalia TS, Prins BP, Abdollahi M, Armstrong NJ, Aslibekyan S, Bain L, Jefferis B, Baumert J, Beekman M, Ben-Shlomo Y, Bis JC, Mitchell BD, de Geus E, Delgado GE, Marek D, Eriksson J, Kajantie E, Kanoni S, Kemp JP, Lu C, Marioni RE, McLachlan S, Milaneschi Y, Nolte IM, Petrelis AM, Porcu E, Sabater-Lleal M, Naderi E, Seppälä I, Shah T, Singhal G, Standl M, Teumer A, Thalamuthu A, Thiering E, Trompet S, Ballantyne CM, Benjamin EJ, Casas JP, Toben C, Dedoussis G, Deelen J, Durda P, Engmann J, Feitosa MF, Grallert H, Hammarstedt A, Harris SE, Homuth G, Hottenga JJ, Jalkanen S, Jamshidi Y, Jawahar MC, Jess T, Kivimaki M, Kleber ME, Lahti J, Liu Y, Marques-Vidal P, Mellström D, Mooijaart SP, Müller-Nurasyid M, Penninx B, Revez JA, Rossing P, Räikkönen K, Sattar N, Scharnagl H, Sennblad B, Silveira A, Pourcain BS, Timpson NJ, Trollor J, van Dongen J, Van Heemst D, Visvikis-Siest S, Vollenweider P, Völker U, Waldenberger M, Willemsen G, Zabaneh D, Morris RW, Arnett DK, Baune BT, Boomsma DI, Chang YC, Deary IJ, Deloukas P, Eriksson JG, Evans DM, Ferreira MA, Gaunt T, Gudnason V, Hamsten A, Heinrich J, Hingorani A, Humphries SE, Jukema JW, Koenig W, Kumari M, Kutalik Z, Lawlor DA, Lehtimäki T, März W, Mather KA, Naitza S, Nauck M, Ohlsson C, Price JF, Raitakari O, Rice K, Sachdev PS, Slagboom E, Sørensen TIA, Spector T, Stacey D, Stathopoulou MG, Tanaka T, Wannamethee SG, Whincup P, Rotter JI, Dehghan A, Boerwinkle E, Psaty BM, Snieder H, and Alizadeh BZ

Subjects
Cohort Studies, Gene Expression Regulation, Genetic Loci, Genetic Predisposition to Disease, Humans, Interleukin-6 blood, Polymorphism, Single Nucleotide, White People genetics, Genome-Wide Association Study, HLA-DRB1 Chains genetics, Interleukin 1 Receptor Antagonist Protein genetics, Interleukin-1 genetics, Interleukin-6 genetics, Receptors, Interleukin-6 genetics
Abstract

Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67 428 (ndiscovery = 52 654 and nreplication = 14 774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (Pcombined = 1.8 × 10-11), HLA-DRB1/DRB5 rs660895 on Chr6p21 (Pcombined = 1.5 × 10-10) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (Pcombined = 1.2 × 10-122). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology., (© The Author(s) 2021. Published by Oxford University Press.)

Published
2021
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44. Assessing potential shared genetic aetiology between body mass index and sleep duration in 142,209 individuals.

Author

Garfield V, Fatemifar G, Dale C, Smart M, Bao Y, Llewellyn CH, Steptoe A, Zabaneh D, and Kumari M

Subjects
Adult, Aged, Female, Humans, Male, Middle Aged, Multifactorial Inheritance genetics, Obesity genetics, Phenotype, Self Report, Time Factors, Body Mass Index, Genetic Association Studies, Sleep genetics
Abstract

Observational studies find an association between increased body mass index (BMI) and short self-reported sleep duration in adults. However, the underlying biological mechanisms that underpin these associations are unclear. Recent findings from the UK Biobank suggest a weak genetic correlation between BMI and self-reported sleep duration. However, the potential shared genetic aetiology between these traits has not been examined using a comprehensive approach. To investigate this, we created a polygenic risk score (PRS) of BMI and examined its association with self-reported sleep duration in a combination of individual participant data and summary-level data, with a total sample size of 142,209 individuals. Although we observed a nonsignificant genetic correlation between BMI and sleep duration, using LD score regression (r g  = -0.067 [SE = 0.039], P = 0.092) we found that a PRS of BMI is associated with a decrease in sleep duration (unstandardized coefficient = -1.75 min [SE = 0.67], P = 6.13 × 10 -7 ), but explained only 0.02% of the variance in sleep duration. Our findings suggest that BMI and self-reported sleep duration possess a small amount of shared genetic aetiology and other mechanisms must underpin these associations., (© 2018 The Authors. Genetic Epidemiology Published by Wiley Periodicals, Inc.)

Published
2019
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45. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence.

Author

Savage JE, Jansen PR, Stringer S, Watanabe K, Bryois J, de Leeuw CA, Nagel M, Awasthi S, Barr PB, Coleman JRI, Grasby KL, Hammerschlag AR, Kaminski JA, Karlsson R, Krapohl E, Lam M, Nygaard M, Reynolds CA, Trampush JW, Young H, Zabaneh D, Hägg S, Hansell NK, Karlsson IK, Linnarsson S, Montgomery GW, Muñoz-Manchado AB, Quinlan EB, Schumann G, Skene NG, Webb BT, White T, Arking DE, Avramopoulos D, Bilder RM, Bitsios P, Burdick KE, Cannon TD, Chiba-Falek O, Christoforou A, Cirulli ET, Congdon E, Corvin A, Davies G, Deary IJ, DeRosse P, Dickinson D, Djurovic S, Donohoe G, Conley ED, Eriksson JG, Espeseth T, Freimer NA, Giakoumaki S, Giegling I, Gill M, Glahn DC, Hariri AR, Hatzimanolis A, Keller MC, Knowles E, Koltai D, Konte B, Lahti J, Le Hellard S, Lencz T, Liewald DC, London E, Lundervold AJ, Malhotra AK, Melle I, Morris D, Need AC, Ollier W, Palotie A, Payton A, Pendleton N, Poldrack RA, Räikkönen K, Reinvang I, Roussos P, Rujescu D, Sabb FW, Scult MA, Smeland OB, Smyrnis N, Starr JM, Steen VM, Stefanis NC, Straub RE, Sundet K, Tiemeier H, Voineskos AN, Weinberger DR, Widen E, Yu J, Abecasis G, Andreassen OA, Breen G, Christiansen L, Debrabant B, Dick DM, Heinz A, Hjerling-Leffler J, Ikram MA, Kendler KS, Martin NG, Medland SE, Pedersen NL, Plomin R, Polderman TJC, Ripke S, van der Sluis S, Sullivan PF, Vrieze SI, Wright MJ, and Posthuma D

Subjects
Adolescent, Brain physiology, Female, Genetic Predisposition to Disease, Genome-Wide Association Study methods, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Intelligence genetics
Abstract

Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence 3-7 , but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

Published
2018
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46. Erratum: Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence.

Author

Sniekers S, Stringer S, Watanabe K, Jansen PR, Coleman JRI, Krapohl E, Taskesen E, Hammerschlag AR, Okbay A, Zabaneh D, Amin N, Breen G, Cesarini D, Chabris CF, Iacono WG, Ikram MA, Johannesson M, Koellinger P, Lee JJ, Magnusson PKE, McGue M, Miller MB, Ollier WER, Payton A, Pendleton N, Plomin R, Rietveld CA, Tiemeier H, van Duijn CM, and Posthuma D

Published
2017
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47. Genome-wide analysis of health-related biomarkers in the UK Household Longitudinal Study reveals novel associations.

Author

Prins BP, Kuchenbaecker KB, Bao Y, Smart M, Zabaneh D, Fatemifar G, Luan J, Wareham NJ, Scott RA, Perry JRB, Langenberg C, Benzeval M, Kumari M, and Zeggini E

Subjects
Genome-Wide Association Study, Health Status, Longitudinal Studies, Reproductive Health, United Kingdom, Biomarkers blood, Family Characteristics, Family Health, Genetic Markers
Abstract

Serum biomarker levels are associated with the risk of complex diseases. Here, we aimed to gain insights into the genetic architecture of biomarker traits which can reflect health status. We performed genome-wide association analyses for twenty serum biomarkers involved in organ function and reproductive health. 9,961 individuals from the UK Household Longitudinal Study were genotyped using the Illumina HumanCoreExome array and variants imputed to the 1000 Genomes Project and UK10K haplotypes. We establish a polygenic heritability for all biomarkers, confirm associations of fifty-four established loci, and identify five novel, replicating associations at genome-wide significance. A low-frequency variant, rs28929474, (beta = 0.04, P = 2 × 10 -10 ) was associated with levels of alanine transaminase, an indicator of liver damage. The variant is located in the gene encoding serine protease inhibitor, low levels of which are associated with alpha-1 antitrypsin deficiency which leads to liver disease. We identified novel associations (rs78900934, beta = 0.05, P = 6 × 10 -12 ; rs2911280, beta = 0.09, P = 6 × 10 -10 ) for dihydroepiandrosterone sulphate, a precursor to major sex-hormones, and for glycated haemoglobin (rs12819124, beta = -0.03, P = 4 × 10 -9 ; rs761772, beta = 0.05, P = 5 × 10 -9 ). rs12819124 is nominally associated with risk of type 2 diabetes. Our study offers insights into the genetic architecture of well-known and less well-studied biomarkers.

Published
2017
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48. Erratum: Genetic loci associated with heart rate variability and their effects on cardiac disease risk.

Author

Nolte IM, Munoz ML, Tragante V, Amare AT, Jansen R, Vaez A, von der Heyde B, Avery CL, Bis JC, Dierckx B, van Dongen J, Gogarten SM, Goyette P, Hernesniemi J, Huikari V, Hwang SJ, Jaju D, Kerr KF, Kluttig A, Krijthe BP, Kumar J, van der Laan SW, Lyytikäinen LP, Maihofer AX, Minassian A, van der Most PJ, Müller-Nurasyid M, Nivard M, Salvi E, Stewart JD, Thayer JF, Verweij N, Wong A, Zabaneh D, Zafarmand MH, Abdellaoui A, Albarwani S, Albert C, Alonso A, Ashar F, Auvinen J, Axelsson T, Baker DG, de Bakker PIW, Barcella M, Bayoumi R, Bieringa RJ, Boomsma D, Boucher G, Britton AR, Christophersen I, Dietrich A, Ehret GB, Ellinor PT, Eskola M, Felix JF, Floras JS, Franco OH, Friberg P, Gademan MGJ, Geyer MA, Giedraitis V, Hartman CA, Hemerich D, Hofman A, Hottenga JJ, Huikuri H, Hutri-Kähönen N, Jouven X, Junttila J, Juonala M, Kiviniemi AM, Kors JA, Kumari M, Kuznetsova T, Laurie CC, Lefrandt JD, Li Y, Li Y, Liao D, Limacher MC, Lin HJ, Lindgren CM, Lubitz SA, Mahajan A, McKnight B, Zu Schwabedissen HM, Milaneschi Y, Mononen N, Morris AP, Nalls MA, Navis G, Neijts M, Nikus K, North KE, O'Connor DT, Ormel J, Perz S, Peters A, Psaty BM, Raitakari OT, Risbrough VB, Sinner MF, Siscovick D, Smit JH, Smith NL, Soliman EZ, Sotoodehnia N, Staessen JA, Stein PK, Stilp AM, Stolarz-Skrzypek K, Strauch K, Sundström J, Swenne CA, Syvänen AC, Tardif JC, Taylor KD, Teumer A, Thornton TA, Tinker LE, Uitterlinden AG, van Setten J, Voss A, Waldenberger M, Wilhelmsen KC, Willemsen G, Wong Q, Zhang ZM, Zonderman AB, Cusi D, Evans MK, Greiser HK, van der Harst P, Hassan M, Ingelsson E, Järvelin MR, Kääb S, Kähönen M, Kivimaki M, Kooperberg C, Kuh D, Lehtimäki T, Lind L, Nievergelt CM, O'Donnell CJ, Oldehinkel AJ, Penninx B, Reiner AP, Riese H, van Roon AM, Rioux JD, Rotter JI, Sofer T, Stricker BH, Tiemeier H, Vrijkotte TGM, Asselbergs FW, Brundel BJJM, Heckbert SR, Whitsel EA, den Hoed M, Snieder H, and de Geus EJC

Abstract

This corrects the article DOI: 10.1038/ncomms15805.

Published
2017
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49. Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence.

Author

Sniekers S, Stringer S, Watanabe K, Jansen PR, Coleman JRI, Krapohl E, Taskesen E, Hammerschlag AR, Okbay A, Zabaneh D, Amin N, Breen G, Cesarini D, Chabris CF, Iacono WG, Ikram MA, Johannesson M, Koellinger P, Lee JJ, Magnusson PKE, McGue M, Miller MB, Ollier WER, Payton A, Pendleton N, Plomin R, Rietveld CA, Tiemeier H, van Duijn CM, and Posthuma D

Subjects
Adolescent, Adult, Aged, Brain metabolism, Child, Child, Preschool, Female, Humans, Infant, Linkage Disequilibrium, Male, Middle Aged, Nerve Tissue Proteins genetics, Polymorphism, Single Nucleotide, White People genetics, Young Adult, Genome-Wide Association Study, Intelligence genetics
Abstract

Intelligence is associated with important economic and health-related life outcomes. Despite intelligence having substantial heritability (0.54) and a confirmed polygenic nature, initial genetic studies were mostly underpowered. Here we report a meta-analysis for intelligence of 78,308 individuals. We identify 336 associated SNPs (METAL P < 5 × 10 -8 ) in 18 genomic loci, of which 15 are new. Around half of the SNPs are located inside a gene, implicating 22 genes, of which 11 are new findings. Gene-based analyses identified an additional 30 genes (MAGMA P < 2.73 × 10 -6 ), of which all but one had not been implicated previously. We show that the identified genes are predominantly expressed in brain tissue, and pathway analysis indicates the involvement of genes regulating cell development (MAGMA competitive P = 3.5 × 10 -6 ). Despite the well-known difference in twin-based heritability for intelligence in childhood (0.45) and adulthood (0.80), we show substantial genetic correlation (r g = 0.89, LD score regression P = 5.4 × 10 -29 ). These findings provide new insight into the genetic architecture of intelligence.

Published
2017
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50. Genetic loci associated with heart rate variability and their effects on cardiac disease risk.

Author

Nolte IM, Munoz ML, Tragante V, Amare AT, Jansen R, Vaez A, von der Heyde B, Avery CL, Bis JC, Dierckx B, van Dongen J, Gogarten SM, Goyette P, Hernesniemi J, Huikari V, Hwang SJ, Jaju D, Kerr KF, Kluttig A, Krijthe BP, Kumar J, van der Laan SW, Lyytikäinen LP, Maihofer AX, Minassian A, van der Most PJ, Müller-Nurasyid M, Nivard M, Salvi E, Stewart JD, Thayer JF, Verweij N, Wong A, Zabaneh D, Zafarmand MH, Abdellaoui A, Albarwani S, Albert C, Alonso A, Ashar F, Auvinen J, Axelsson T, Baker DG, de Bakker PIW, Barcella M, Bayoumi R, Bieringa RJ, Boomsma D, Boucher G, Britton AR, Christophersen I, Dietrich A, Ehret GB, Ellinor PT, Eskola M, Felix JF, Floras JS, Franco OH, Friberg P, Gademan MGJ, Geyer MA, Giedraitis V, Hartman CA, Hemerich D, Hofman A, Hottenga JJ, Huikuri H, Hutri-Kähönen N, Jouven X, Junttila J, Juonala M, Kiviniemi AM, Kors JA, Kumari M, Kuznetsova T, Laurie CC, Lefrandt JD, Li Y, Li Y, Liao D, Limacher MC, Lin HJ, Lindgren CM, Lubitz SA, Mahajan A, McKnight B, Zu Schwabedissen HM, Milaneschi Y, Mononen N, Morris AP, Nalls MA, Navis G, Neijts M, Nikus K, North KE, O'Connor DT, Ormel J, Perz S, Peters A, Psaty BM, Raitakari OT, Risbrough VB, Sinner MF, Siscovick D, Smit JH, Smith NL, Soliman EZ, Sotoodehnia N, Staessen JA, Stein PK, Stilp AM, Stolarz-Skrzypek K, Strauch K, Sundström J, Swenne CA, Syvänen AC, Tardif JC, Taylor KD, Teumer A, Thornton TA, Tinker LE, Uitterlinden AG, van Setten J, Voss A, Waldenberger M, Wilhelmsen KC, Willemsen G, Wong Q, Zhang ZM, Zonderman AB, Cusi D, Evans MK, Greiser HK, van der Harst P, Hassan M, Ingelsson E, Järvelin MR, Kääb S, Kähönen M, Kivimaki M, Kooperberg C, Kuh D, Lehtimäki T, Lind L, Nievergelt CM, O'Donnell CJ, Oldehinkel AJ, Penninx B, Reiner AP, Riese H, van Roon AM, Rioux JD, Rotter JI, Sofer T, Stricker BH, Tiemeier H, Vrijkotte TGM, Asselbergs FW, Brundel BJJM, Heckbert SR, Whitsel EA, den Hoed M, Snieder H, and de Geus EJC

Subjects
Blood Pressure, Cohort Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Heart Diseases physiopathology, Humans, Hyperpolarization-Activated Cyclic Nucleotide-Gated Channels genetics, Muscle Proteins genetics, Polymorphism, Single Nucleotide, Potassium Channels genetics, Quantitative Trait Loci, RGS Proteins genetics, Risk Factors, White People genetics, Heart Diseases genetics, Heart Rate
Abstract

Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74g <-0.55) and blood pressure (-0.35g <-0.20). These findings provide clinically relevant biological insight into heritable variation in vagal heart rhythm regulation, with a key role for genetic variants (GNG11, RGS6) that influence G-protein heterotrimer action in GIRK-channel induced pacemaker membrane hyperpolarization.

Published
2017
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