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2. Meta-GWAS identifies FADS2 a novel locus for PCSK9 concentrations

Author

Kheirkhah, A., primary, Schachtl-Rieß, J., additional, Lamina, C., additional, Di Maio, S., additional, Koller, A., additional, Schönherr, S., additional, Coassin, S., additional, Forer, L., additional, Schultheiß, U.T., additional, Sekula, P., additional, Kotsis, F., additional, Gieger, C., additional, Peters, A., additional, Köttgen, A., additional, Eckardt, K.-U., additional, and Kronenberg, F., additional

Published
2023
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3. Improved mutation screening in the KIV-2 copy number variation of the lPA gene from short-read whole-exome-sequencing data

Author

Di Maio, S., primary, Zöscher, P., additional, Weissensteiner, H., additional, Forer, L., additional, Schachtl-Rieß, J., additional, Amstler, S., additional, Streiter, G., additional, Pfurtscheller, C., additional, Paulweber, B., additional, Kronenberg, F., additional, Coassin, S., additional, and Schönherr, S., additional

Published
2023
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5. Statin treatment and prevalent CVD influence the association between PCSK9 and incident CVD in patients with moderately decreased kidney function: Results from the GCKD study

Author

Kheirkhah, A., primary, Lamina, C., additional, Kollerits, B., additional, Schachtl-Riess, J.F., additional, Schultheiss, U.T., additional, Forer, L., additional, Sekula, P., additional, Kotsis, F., additional, Köttgen, A., additional, Eckardt, K.U., additional, and Kronenberg, F., additional

Published
2022
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8. A saturated map of common genetic variants associated with human height

Author

Yengo, L., Vedantam, S., Marouli, E., Sidorenko, J., Bartell, E., Sakaue, S., Graff, M, Eliasen, A.U., Jiang, Y., Raghavan, S., Miao, J., Arias, J.D., Graham, S.E., Mukamel, R.E., Spracklen, C.N., Yin, X., Chen, Shiou-Shiou, Ferreira, T., Highland, H.H., Ji, Y., Karaderi, T., Lin, K., Lüll, K., Malden, D.E., Medina-Gomez, C., Machado, M., Moore, A., Rüeger, S., Sim, X., Vrieze, S., Ahluwalia, T.S., Akiyama, M., Allison, M.A., Alvarez, M., Andersen, M.K., Ani, A., Appadurai, V., Arbeeva, L., Bhaskar, S., Bielak, L.F., Bollepalli, S., Bonnycastle, L.L., Bork-Jensen, J., Bradfield, J.P., Bradford, Y., Braund, P.S., Brody, J.A., Burgdorf, K.S., Cade, B.E., Cai, H., Cai, Q., Campbell, A., Cañadas-Garre, M., Catamo, E., Chai, J.F., Chai, X., Chang, L.C., Chang, Y.C., Chen, Chen, Chesi, A., Choi, S.H., Chung, R.H., Cocca, M., Concas, M.P., Couture, C., Cuellar-Partida, G., Danning, R., Daw, E.W., Degenhard, F., Delgado, G.E., Delitala, A., Demirkan, A., Deng, X., Devineni, P., Dietl, A., Dimitriou, M., Dimitrov, L., Dorajoo, R., Ekici, A.B., Engmann, J.E., Fairhurst-Hunter, Z., Farmaki, A.E., Faul, J.D., Fernandez-Lopez, J.C., Forer, L., Francescatto, M., Freitag-Wolf, S., Fuchsberger, C., Galesloot, T.E., Gao, Y., Gao, Z., Geller, F., Giannakopoulou, O., Giulianini, F., Gjesing, A.P., Goel, A., Gordon, S.D.S., Gorski, M., Grove, J, Lores-Motta, Laura, Pauper, M., Hollander, A.I. den, Hoyng, C.B., Kiemeney, L.A.L.M., Visscher, P.M., Hirschhorn, J.N., Yengo, L., Vedantam, S., Marouli, E., Sidorenko, J., Bartell, E., Sakaue, S., Graff, M, Eliasen, A.U., Jiang, Y., Raghavan, S., Miao, J., Arias, J.D., Graham, S.E., Mukamel, R.E., Spracklen, C.N., Yin, X., Chen, Shiou-Shiou, Ferreira, T., Highland, H.H., Ji, Y., Karaderi, T., Lin, K., Lüll, K., Malden, D.E., Medina-Gomez, C., Machado, M., Moore, A., Rüeger, S., Sim, X., Vrieze, S., Ahluwalia, T.S., Akiyama, M., Allison, M.A., Alvarez, M., Andersen, M.K., Ani, A., Appadurai, V., Arbeeva, L., Bhaskar, S., Bielak, L.F., Bollepalli, S., Bonnycastle, L.L., Bork-Jensen, J., Bradfield, J.P., Bradford, Y., Braund, P.S., Brody, J.A., Burgdorf, K.S., Cade, B.E., Cai, H., Cai, Q., Campbell, A., Cañadas-Garre, M., Catamo, E., Chai, J.F., Chai, X., Chang, L.C., Chang, Y.C., Chen, Chen, Chesi, A., Choi, S.H., Chung, R.H., Cocca, M., Concas, M.P., Couture, C., Cuellar-Partida, G., Danning, R., Daw, E.W., Degenhard, F., Delgado, G.E., Delitala, A., Demirkan, A., Deng, X., Devineni, P., Dietl, A., Dimitriou, M., Dimitrov, L., Dorajoo, R., Ekici, A.B., Engmann, J.E., Fairhurst-Hunter, Z., Farmaki, A.E., Faul, J.D., Fernandez-Lopez, J.C., Forer, L., Francescatto, M., Freitag-Wolf, S., Fuchsberger, C., Galesloot, T.E., Gao, Y., Gao, Z., Geller, F., Giannakopoulou, O., Giulianini, F., Gjesing, A.P., Goel, A., Gordon, S.D.S., Gorski, M., Grove, J, Lores-Motta, Laura, Pauper, M., Hollander, A.I. den, Hoyng, C.B., Kiemeney, L.A.L.M., Visscher, P.M., and Hirschhorn, J.N.

Abstract

Item does not contain fulltext, Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Published
2022

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

Author

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

Abstract

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Published
2022

10. Apolipoprotein A-IV concentrations and clinical outcomes in chronic kidney disease patients: Results from the German Chronic Kidney Disease (GCKD) study

Author

Schwaiger, J.P., primary, Kollerits, B., additional, Steinbrenner, I., additional, Weissensteiner, H., additional, Schönherr, S., additional, Forer, L., additional, Kotsis, F., additional, Schneider, M.P., additional, Schultheiss, U.T., additional, Wanner, C., additional, Köttgen, A., additional, Eckardt, K.-U., additional, and Kronenberg, F., additional

Published
2021
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12. The power of genetic diversity in genome-wide association studies of lipids

Author

Graham, S. E. (Sarah E.), Clarke, S. L. (Shoa L.), Wu, K. H. (Kuan-Han H.), Kanoni, S. (Stavroula), Zajac, G. J. (Greg J. M.), Ramdas, S. (Shweta), Surakka, I. (Ida), Ntalla, I. (Ioanna), Vedantam, S. (Sailaja), Winkler, T. W. (Thomas W.), Locke, A. E. (Adam E.), Marouli, E. (Eirini), Hwang, M. Y. (Mi Yeong), Han, S. (Sohee), Narita, A. (Akira), Choudhury, A. (Ananyo), Bentley, A. R. (Amy R.), Ekoru, K. (Kenneth), Verma, A. (Anurag), Trivedi, B. (Bhavi), Martin, H. C. (Hilary C.), Hunt, K. A. (Karen A.), Hui, Q. (Qin), Klarin, D. (Derek), Zhu, X. (Xiang), Thorleifsson, G. (Gudmar), Helgadottir, A. (Anna), Gudbjartsson, D. F. (Daniel F.), Holm, H. (Hilma), Olafsson, I. (Isleifur), Akiyama, M. (Masato), Sakaue, S. (Saori), Terao, C. (Chikashi), Kanai, M. (Masahiro), Zhou, W. (Wei), Brumpton, B. M. (Ben M.), Rasheed, H. (Humaira), Ruotsalainen, S. E. (Sanni E.), Havulinna, A. S. (Aki S.), Veturi, Y. (Yogasudha), Feng, Q. (QiPing), Rosenthal, E. A. (Elisabeth A.), Lingren, T. (Todd), Pacheco, J. A. (Jennifer Allen), Pendergrass, S. A. (Sarah A.), Haessler, J. (Jeffrey), Giulianini, F. (Franco), Bradford, Y. (Yuki), Miller, J. E. (Jason E.), Campbell, A. (Archie), Lin, K. (Kuang), Millwood, I. Y. (Iona Y.), Hindy, G. (George), Rasheed, A. (Asif), Faul, J. D. (Jessica D.), Zhao, W. (Wei), Weir, D. R. (David R.), Turman, C. (Constance), Huang, H. (Hongyan), Graff, M. (Mariaelisa), Mahajan, A. (Anubha), Brown, M. R. (Michael R.), Zhang, W. (Weihua), Yu, K. (Ketian), Schmidt, E. M. (Ellen M.), Pandit, A. (Anita), Gustafsson, S. (Stefan), Yin, X. (Xianyong), Luan, J. (Jian'an), Zhao, J.-H. (Jing-Hua), Matsuda, F. (Fumihiko), Jang, H.-M. (Hye-Mi), Yoon, K. (Kyungheon), Medina-Gomez, C. (Carolina), Pitsillides, A. (Achilleas), Hottenga, J. J. (Jouke Jan), Willemsen, G. (Gonneke), Wood, A. R. (Andrew R.), Ji, Y. (Yingji), Gao, Z. (Zishan), Haworth, S. (Simon), Mitchell, R. E. (Ruth E.), Chai, J. F. (Jin Fang), Aadahl, M. (Mette), Yao, J. (Jie), Manichaikul, A. (Ani), Warren, H. R. (Helen R.), Ramirez, J. (Julia), Bork-Jensen, J. (Jette), Karhus, L. L. (Line L.), Goel, A. (Anuj), Sabater-Lleal, M. (Maria), Noordam, R. (Raymond), Sidore, C. (Carlo), Fiorillo, E. (Edoardo), McDaid, A. F. (Aaron F.), Marques-Vidal, P. (Pedro), Wielscher, M. (Matthias), Trompet, S. (Stella), Sattar, N. (Naveed), Mollehave, L. T. (Line T.), Thuesen, B. H. (Betina H.), Munz, M. (Matthias), Zeng, L. (Lingyao), Huang, J. (Jianfeng), Yang, B. (Bin), Poveda, A. (Alaitz), Kurbasic, A. (Azra), Lamina, C. (Claudia), Forer, L. (Lukas), Scholz, M. (Markus), Galesloot, T. E. (Tessel E.), Bradfield, J. P. (Jonathan P.), Daw, E. W. (E. Warwick), Zmuda, J. M. (Joseph M.), Mitchell, J. S. (Jonathan S.), Fuchsberger, C. (Christian), Christensen, H. (Henry), Brody, J. A. (Jennifer A.), Feitosa, M. F. (Mary F.), Wojczynski, M. K. (Mary K.), Preuss, M. (Michael), Mangino, M. (Massimo), Christofidou, P. (Paraskevi), Verweij, N. (Niek), Benjamins, J. W. (Jan W.), Engmann, J. (Jorgen), Kember, R. L. (Rachel L.), Slieker, R. C. (Roderick C.), Lo, K. S. (Ken Sin), Zilhao, N. R. (Nuno R.), Kleber, M. E. (Marcus E.), Delgado, G. E. (Graciela E.), Huo, S. (Shaofeng), Ikeda, D. D. (Daisuke D.), Iha, H. (Hiroyuki), Yang, J. (Jian), Liu, J. (Jun), Leonard, H. L. (Hampton L.), Marten, J. (Jonathan), Schmidt, B. (Borge), Arendt, M. (Marina), Smyth, L. J. (Laura J.), Canadas-Garre, M. (Marisa), Wang, C. (Chaolong), Nakatochi, M. (Masahiro), Wong, A. (Andrew), Hutri-Kahonen, N. (Nina), Sim, X. (Xueling), Xia, R. (Rui), Huerta-Chagoya, A. (Alicia), Fernandez-Lopez, J. C. (Juan Carlos), Lyssenko, V. (Valeriya), Ahmed, M. (Meraj), Jackson, A. U. (Anne U.), Irvin, M. R. (Marguerite R.), Oldmeadow, C. (Christopher), Kim, H.-N. (Han-Na), Ryu, S. (Seungho), Timmers, P. R. (Paul R. H. J.), Arbeeva, L. (Liubov), Dorajoo, R. (Rajkumar), Lange, L. A. (Leslie A.), Chai, X. (Xiaoran), Prasad, G. (Gauri), Lores-Motta, L. (Laura), Pauper, M. (Marc), Long, J. (Jirong), Li, X. (Xiaohui), Theusch, E. (Elizabeth), Takeuchi, F. (Fumihiko), Spracklen, C. N. (Cassandra N.), Loukola, A. (Anu), Bollepalli, S. (Sailalitha), Warner, S. C. (Sophie C.), Wang, Y. X. (Ya Xing), Wei, W. B. (Wen B.), Nutile, T. (Teresa), Ruggiero, D. (Daniela), Sung, Y. J. (Yun Ju), Hung, Y.-J. (Yi-Jen), Chen, S. (Shufeng), Liu, F. (Fangchao), Yang, J. (Jingyun), Kentistou, K. A. (Katherine A.), Gorski, M. (Mathias), Brumat, M. (Marco), Meidtner, K. (Karina), Bielak, L. F. (Lawrence F.), Smith, J. A. (Jennifer A.), Hebbar, P. (Prashantha), Farmaki, A.-E. (Aliki-Eleni), Hofer, E. (Edith), Lin, M. (Maoxuan), Xue, C. (Chao), Zhang, J. (Jifeng), Concas, M. P. (Maria Pina), Vaccargiu, S. (Simona), van der Most, P. J. (Peter J.), Pitkanen, N. (Niina), Cade, B. E. (Brian E.), Lee, J. (Jiwon), van Der Laan, S. W. (Sander W.), Chitrala, K. N. (Kumaraswamy Naidu), Weiss, S. (Stefan), Zimmermann, M. E. (Martina E.), Lee, J. Y. (Jong Young), Choi, H. S. (Hyeok Sun), Nethander, M. (Maria), Freitag-Wolf, S. (Sandra), Southam, L. (Lorraine), Rayner, N. W. (Nigel W.), Wang, C. A. (Carol A.), Lin, S.-Y. (Shih-Yi), Wang, J.-S. (Jun-Sing), Couture, C. (Christian), Lyytikainen, L.-P. (Leo-Pekka), Nikus, K. (Kjell), Cuellar-Partida, G. (Gabriel), Vestergaard, H. (Henrik), Hildalgo, B. (Bertha), Giannakopoulou, O. (Olga), Cai, Q. (Qiuyin), Obura, M. O. (Morgan O.), van Setten, J. (Jessica), Li, X. (Xiaoyin), Schwander, K. (Karen), Terzikhan, N. (Natalie), Shin, J. H. (Jae Hun), Jackson, R. D. (Rebecca D.), Reiner, A. P. (Alexander P.), Martin, L. W. (Lisa Warsinger), Chen, Z. (Zhengming), Li, L. (Liming), Highland, H. M. (Heather M.), Young, K. L. (Kristin L.), Kawaguchi, T. (Takahisa), Thiery, J. (Joachim), Bis, J. C. (Joshua C.), Nadkarni, G. N. (Girish N.), Launer, L. J. (Lenore J.), Li, H. (Huaixing), Nalls, M. A. (Mike A.), Raitakari, O. T. (Olli T.), Ichihara, S. (Sahoko), Wild, S. H. (Sarah H.), Nelson, C. P. (Christopher P.), Campbell, H. (Harry), Jager, S. (Susanne), Nabika, T. (Toru), Al-Mulla, F. (Fahd), Niinikoski, H. (Harri), Braund, P. S. (Peter S.), Kolcic, I. (Ivana), Kovacs, P. (Peter), Giardoglou, T. (Tota), Katsuya, T. (Tomohiro), Bhatti, F. (Fatima), de Kleijn, D. (Dominique), de Borst, G. J. (Gert J.), Kim, E. K. (Eung Kweon), Adams, H. H. (Hieab H. H.), Ikram, M. A. (M. Arfan), Zhu, X. (Xiaofeng), Asselbergs, F. W. (Folkert W.), Kraaijeveld, A. O. (Adriaan O.), Beulens, J. W. (Joline W. J.), Shu, X.-O. (Xiao-Ou), Rallidis, L. S. (Loukianos S.), Pedersen, O. (Oluf), Hansen, T. (Torben), Mitchell, P. (Paul), Hewitt, A. W. (Alex W.), Kahonen, M. (Mika), Perusse, L. (Louis), Bouchard, C. (Claude), Tonjes, A. (Anke), Chen, Y. I. (Yii-Der Ida), Pennell, C. E. (Craig E.), Mori, T. A. (Trevor A.), Lieb, W. (Wolfgang), Franke, A. (Andre), Ohlsson, C. (Claes), Mellstrom, D. (Dan), Cho, Y. S. (Yoon Shin), Lee, H. (Hyejin), Yuan, J.-M. (Jian-Min), Koh, W.-P. (Woon-Puay), Rhee, S. Y. (Sang Youl), Woo, J.-T. (Jeong-Taek), Heid, I. M. (Iris M.), Stark, K. J. (Klaus J.), Volzke, H. (Henry), Homuth, G. (Georg), Evans, M. K. (Michele K.), Zonderman, A. B. (Alan B.), Polasek, O. (Ozren), Pasterkamp, G. (Gerard), Hoefer, I. E. (Imo E.), Redline, S. (Susan), Pahkala, K. (Katja), Oldehinkel, A. J. (Albertine J.), Snieder, H. (Harold), Biino, G. (Ginevra), Schmidt, R. (Reinhold), Schmidt, H. (Helena), Chen, Y. E. (Y. Eugene), Bandinelli, S. (Stefania), Dedoussis, G. (George), Thanaraj, T. A. (Thangavel Alphonse), Kardia, S. L. (Sharon L. R.), Kato, N. (Norihiro), Schulze, M. B. (Matthias B.), Girotto, G. (Giorgia), Jung, B. (Bettina), Boger, C. A. (Carsten A.), Joshi, P. K. (Peter K.), Bennett, D. A. (David A.), De Jager, P. L. (Philip L.), Lu, X. (Xiangfeng), Mamakou, V. (Vasiliki), Brown, M. (Morris), Caulfield, M. J. (Mark J.), Munroe, P. B. (Patricia B.), Guo, X. (Xiuqing), Ciullo, M. (Marina), Jonas, J. B. (Jost B.), Samani, N. J. (Nilesh J.), Kaprio, J. (Jaakko), Pajukanta, P. (Paivi), Adair, L. S. (Linda S.), Bechayda, S. A. (Sonny Augustin), de Silva, H. J. (H. Janaka), Wickremasinghe, A. R. (Ananda R.), Krauss, R. M. (Ronald M.), Wu, J.-Y. (Jer-Yuarn), Zheng, W. (Wei), den Hollander, A. I. (Anneke, I), Bharadwaj, D. (Dwaipayan), Correa, A. (Adolfo), Wilson, J. G. (James G.), Lind, L. (Lars), Heng, C.-K. (Chew-Kiat), Nelson, A. E. (Amanda E.), Golightly, Y. M. (Yvonne M.), Wilson, J. F. (James F.), Penninx, B. (Brenda), Kim, H.-L. (Hyung-Lae), Attia, J. (John), Scott, R. J. (Rodney J.), Rao, D. C. (D. C.), Arnett, D. K. (Donna K.), Walker, M. (Mark), Koistinen, H. A. (Heikki A.), Chandak, G. R. (Giriraj R.), Yajnik, C. S. (Chittaranjan S.), Mercader, J. M. (Josep M.), Tusie-Luna, T. (Teresa), Aguilar-Salinas, C. A. (Carlos A.), Villalpando, C. G. (Clicerio Gonzalez), Orozco, L. (Lorena), Fornage, M. (Myriam), Tai, E. S. (E. Shyong), van Dam, R. M. (Rob M.), Lehtimaki, T. (Terho), Chaturvedi, N. (Nish), Yokota, M. (Mitsuhiro), Liu, J. (Jianjun), Reilly, D. F. (Dermot F.), McKnight, A. J. (Amy Jayne), Kee, F. (Frank), Jockel, K.-H. (Karl-Heinz), McCarthy, M. I. (Mark, I), Palmer, C. N. (Colin N. A.), Vitart, V. (Veronique), Hayward, C. (Caroline), Simonsick, E. (Eleanor), van Duijn, C. M. (Cornelia M.), Lu, F. (Fan), Qu, J. (Jia), Hishigaki, H. (Haretsugu), Lin, X. (Xu), Marz, W. (Winfried), Parra, E. J. (Esteban J.), Cruz, M. (Miguel), Gudnason, V. (Vilmundur), Tardif, J.-C. (Jean-Claude), Lettre, G. (Guillaume), Elders, P. J. (Petra J. M.), Damrauer, S. M. (Scott M.), Kumari, M. (Meena), Kivimaki, M. (Mika), van der Harst, P. (Pim), Spector, T. D. (Tim D.), Loos, R. J. (Ruth J. F.), Province, M. A. (Michael A.), Psaty, B. M. (Bruce M.), Brandslund, I. (Ivan), Pramstaller, P. P. (Peter P.), Christensen, K. (Kaare), Ripatti, S. (Samuli), Widen, E. (Elisabeth), Hakonarson, H. (Hakon), Grant, S. F. (Struan F. A.), Kiemeney, L. A. (Lambertus A. L. M.), de Graaf, J. (Jacqueline), Loeffler, M. (Markus), Kronenberg, F. (Florian), Gu, D. (Dongfeng), Erdmann, J. (Jeanette), Schunkert, H. (Heribert), Franks, P. W. (Paul W.), Linneberg, A. (Allan), Jukema, J. W. (J. Wouter), Khera, A. V. (Amit, V), Männikkö, M. (Minna), Järvelin, M.-R. (Marjo-Riitta), Kutalik, Z. (Zoltan), Cucca, F. (Francesco), Mook-Kanamori, D. O. (Dennis O.), van Dijk, K. W. (Ko Willems), Watkins, H. (Hugh), Strachan, D. P. (David P.), Grarup, N. (Niels), Sever, P. (Peter), Poulter, N. (Neil), Rotter, J. I. (Jerome, I), Dantoft, T. M. (Thomas M.), Karpe, F. (Fredrik), Neville, M. J. (Matt J.), Timpson, N. J. (Nicholas J.), Cheng, C.-Y. (Ching-Yu), Wong, T.-Y. (Tien-Yin), Khor, C. C. (Chiea Chuen), Sabanayagam, C. (Charumathi), Peters, A. (Annette), Gieger, C. (Christian), Hattersley, A. T. (Andrew T.), Pedersen, N. L. (Nancy L.), Magnusson, P. K. (Patrik K. E.), Boomsma, D. I. (Dorret, I), de Geus, E. J. (Eco J. C.), Cupples, L. A. (L. Adrienne), van Meurs, J. B. (Joyce B. J.), Ghanbari, M. (Mohsen), Rsen, P. G. (Penny Gordon-La), Huang, W. (Wei), Kim, Y. J. (Young Jin), Tabara, Y. (Yasuharu), Wareham, N. J. (Nicholas J.), Langenberg, C. (Claudia), Zeggini, E. (Eleftheria), Kuusisto, J. (Johanna), Laakso, M. (Markku), Ingelsson, E. (Erik), Abecasis, G. (Goncalo), Chambers, J. C. (John C.), Kooner, J. S. (Jaspal S.), de Vries, P. S. (Paul S.), Morrison, A. C. (Alanna C.), North, K. E. (Kari E.), Daviglus, M. (Martha), Kraft, P. (Peter), Martin, N. G. (Nicholas G.), Whitfield, J. B. (John B.), Abbas, S. (Shahid), Saleheen, D. (Danish), Walters, R. G. (Robin G.), Holmes, M. V. (Michael, V), Black, C. (Corri), Smith, B. H. (Blair H.), Justice, A. E. (Anne E.), Baras, A. (Aris), Buring, J. E. (Julie E.), Ridker, P. M. (Paul M.), Chasman, D. I. (Daniel, I), Kooperberg, C. (Charles), Wei, W.-Q. (Wei-Qi), Jarvik, G. P. (Gail P.), Namjou, B. (Bahram), Hayes, M. G. (M. Geoffrey), Ritchie, M. D. (Marylyn D.), Jousilahti, P. (Pekka), Salomaa, V. (Veikko), Hveem, K. (Kristian), Asvold, B. O. (Bjorn Olav), Kubo, M. (Michiaki), Kamatani, Y. (Yoichiro), Okada, Y. (Yukinori), Murakami, Y. (Yoshinori), Thorsteinsdottir, U. (Unnur), Stefansson, K. (Kari), Ho, Y.-L. (Yuk-Lam), Lynch, J. A. (Julie A.), Rader, D. J. (Daniel J.), Tsao, P. S. (Philip S.), Chang, K.-M. (Kyong-Mi), Cho, K. (Kelly), O'Donnell, C. J. (Christopher J.), Gaziano, J. M. (John M.), Wilson, P. (Peter), Rotimi, C. N. (Charles N.), Hazelhurst, S. (Scott), Ramsay, M. (Michele), Trembath, R. C. (Richard C.), van Heel, D. A. (David A.), Tamiya, G. (Gen), Yamamoto, M. (Masayuki), Kim, B.-J. (Bong-Jo), Mohlke, K. L. (Karen L.), Frayling, T. M. (Timothy M.), Hirschhorn, J. N. (Joel N.), Kathiresan, S. (Sekar), Boehnke, M. (Michael), Natarajan, P. (Pradeep), Peloso, G. M. (Gina M.), Brown, C. D. (Christopher D.), Morris, A. P. (Andrew P.), Assimes, T. L. (Themistocles L.), Deloukas, P. (Panos), Sun, Y. V. (Yan, V), Willer, C. J. (Cristen J.), Graham, S. E. (Sarah E.), Clarke, S. L. (Shoa L.), Wu, K. H. (Kuan-Han H.), Kanoni, S. (Stavroula), Zajac, G. J. (Greg J. M.), Ramdas, S. (Shweta), Surakka, I. (Ida), Ntalla, I. (Ioanna), Vedantam, S. (Sailaja), Winkler, T. W. (Thomas W.), Locke, A. E. (Adam E.), Marouli, E. (Eirini), Hwang, M. Y. (Mi Yeong), Han, S. (Sohee), Narita, A. (Akira), Choudhury, A. (Ananyo), Bentley, A. R. (Amy R.), Ekoru, K. (Kenneth), Verma, A. (Anurag), Trivedi, B. (Bhavi), Martin, H. C. (Hilary C.), Hunt, K. A. (Karen A.), Hui, Q. (Qin), Klarin, D. (Derek), Zhu, X. (Xiang), Thorleifsson, G. (Gudmar), Helgadottir, A. (Anna), Gudbjartsson, D. F. (Daniel F.), Holm, H. (Hilma), Olafsson, I. (Isleifur), Akiyama, M. (Masato), Sakaue, S. (Saori), Terao, C. (Chikashi), Kanai, M. (Masahiro), Zhou, W. (Wei), Brumpton, B. M. (Ben M.), Rasheed, H. (Humaira), Ruotsalainen, S. E. (Sanni E.), Havulinna, A. S. (Aki S.), Veturi, Y. (Yogasudha), Feng, Q. (QiPing), Rosenthal, E. A. (Elisabeth A.), Lingren, T. (Todd), Pacheco, J. A. (Jennifer Allen), Pendergrass, S. A. (Sarah A.), Haessler, J. (Jeffrey), Giulianini, F. (Franco), Bradford, Y. (Yuki), Miller, J. E. (Jason E.), Campbell, A. (Archie), Lin, K. (Kuang), Millwood, I. Y. (Iona Y.), Hindy, G. (George), Rasheed, A. (Asif), Faul, J. D. (Jessica D.), Zhao, W. (Wei), Weir, D. R. (David R.), Turman, C. (Constance), Huang, H. (Hongyan), Graff, M. (Mariaelisa), Mahajan, A. (Anubha), Brown, M. R. (Michael R.), Zhang, W. (Weihua), Yu, K. (Ketian), Schmidt, E. M. (Ellen M.), Pandit, A. (Anita), Gustafsson, S. (Stefan), Yin, X. (Xianyong), Luan, J. (Jian'an), Zhao, J.-H. (Jing-Hua), Matsuda, F. (Fumihiko), Jang, H.-M. (Hye-Mi), Yoon, K. (Kyungheon), Medina-Gomez, C. (Carolina), Pitsillides, A. (Achilleas), Hottenga, J. J. (Jouke Jan), Willemsen, G. (Gonneke), Wood, A. R. (Andrew R.), Ji, Y. (Yingji), Gao, Z. (Zishan), Haworth, S. (Simon), Mitchell, R. E. (Ruth E.), Chai, J. F. (Jin Fang), Aadahl, M. (Mette), Yao, J. (Jie), Manichaikul, A. (Ani), Warren, H. R. (Helen R.), Ramirez, J. (Julia), Bork-Jensen, J. (Jette), Karhus, L. L. (Line L.), Goel, A. (Anuj), Sabater-Lleal, M. (Maria), Noordam, R. (Raymond), Sidore, C. (Carlo), Fiorillo, E. (Edoardo), McDaid, A. F. (Aaron F.), Marques-Vidal, P. (Pedro), Wielscher, M. (Matthias), Trompet, S. (Stella), Sattar, N. (Naveed), Mollehave, L. T. (Line T.), Thuesen, B. H. (Betina H.), Munz, M. (Matthias), Zeng, L. (Lingyao), Huang, J. (Jianfeng), Yang, B. (Bin), Poveda, A. (Alaitz), Kurbasic, A. (Azra), Lamina, C. (Claudia), Forer, L. (Lukas), Scholz, M. (Markus), Galesloot, T. E. (Tessel E.), Bradfield, J. P. (Jonathan P.), Daw, E. W. (E. Warwick), Zmuda, J. M. (Joseph M.), Mitchell, J. S. (Jonathan S.), Fuchsberger, C. (Christian), Christensen, H. (Henry), Brody, J. A. (Jennifer A.), Feitosa, M. F. (Mary F.), Wojczynski, M. K. (Mary K.), Preuss, M. (Michael), Mangino, M. (Massimo), Christofidou, P. (Paraskevi), Verweij, N. (Niek), Benjamins, J. W. (Jan W.), Engmann, J. (Jorgen), Kember, R. L. (Rachel L.), Slieker, R. C. (Roderick C.), Lo, K. S. (Ken Sin), Zilhao, N. R. (Nuno R.), Kleber, M. E. (Marcus E.), Delgado, G. E. (Graciela E.), Huo, S. (Shaofeng), Ikeda, D. D. (Daisuke D.), Iha, H. (Hiroyuki), Yang, J. (Jian), Liu, J. (Jun), Leonard, H. L. (Hampton L.), Marten, J. (Jonathan), Schmidt, B. (Borge), Arendt, M. (Marina), Smyth, L. J. (Laura J.), Canadas-Garre, M. (Marisa), Wang, C. (Chaolong), Nakatochi, M. (Masahiro), Wong, A. (Andrew), Hutri-Kahonen, N. (Nina), Sim, X. (Xueling), Xia, R. (Rui), Huerta-Chagoya, A. (Alicia), Fernandez-Lopez, J. C. (Juan Carlos), Lyssenko, V. (Valeriya), Ahmed, M. (Meraj), Jackson, A. U. (Anne U.), Irvin, M. R. (Marguerite R.), Oldmeadow, C. (Christopher), Kim, H.-N. (Han-Na), Ryu, S. (Seungho), Timmers, P. R. (Paul R. H. J.), Arbeeva, L. (Liubov), Dorajoo, R. (Rajkumar), Lange, L. A. (Leslie A.), Chai, X. (Xiaoran), Prasad, G. (Gauri), Lores-Motta, L. (Laura), Pauper, M. (Marc), Long, J. (Jirong), Li, X. (Xiaohui), Theusch, E. (Elizabeth), Takeuchi, F. (Fumihiko), Spracklen, C. N. (Cassandra N.), Loukola, A. (Anu), Bollepalli, S. (Sailalitha), Warner, S. C. (Sophie C.), Wang, Y. X. (Ya Xing), Wei, W. B. (Wen B.), Nutile, T. (Teresa), Ruggiero, D. (Daniela), Sung, Y. J. (Yun Ju), Hung, Y.-J. (Yi-Jen), Chen, S. (Shufeng), Liu, F. (Fangchao), Yang, J. (Jingyun), Kentistou, K. A. (Katherine A.), Gorski, M. (Mathias), Brumat, M. (Marco), Meidtner, K. (Karina), Bielak, L. F. (Lawrence F.), Smith, J. A. (Jennifer A.), Hebbar, P. (Prashantha), Farmaki, A.-E. (Aliki-Eleni), Hofer, E. (Edith), Lin, M. (Maoxuan), Xue, C. (Chao), Zhang, J. (Jifeng), Concas, M. P. (Maria Pina), Vaccargiu, S. (Simona), van der Most, P. J. (Peter J.), Pitkanen, N. (Niina), Cade, B. E. (Brian E.), Lee, J. (Jiwon), van Der Laan, S. W. (Sander W.), Chitrala, K. N. (Kumaraswamy Naidu), Weiss, S. (Stefan), Zimmermann, M. E. (Martina E.), Lee, J. Y. (Jong Young), Choi, H. S. (Hyeok Sun), Nethander, M. (Maria), Freitag-Wolf, S. (Sandra), Southam, L. (Lorraine), Rayner, N. W. (Nigel W.), Wang, C. A. (Carol A.), Lin, S.-Y. (Shih-Yi), Wang, J.-S. (Jun-Sing), Couture, C. (Christian), Lyytikainen, L.-P. (Leo-Pekka), Nikus, K. (Kjell), Cuellar-Partida, G. (Gabriel), Vestergaard, H. (Henrik), Hildalgo, B. (Bertha), Giannakopoulou, O. (Olga), Cai, Q. (Qiuyin), Obura, M. O. (Morgan O.), van Setten, J. (Jessica), Li, X. (Xiaoyin), Schwander, K. (Karen), Terzikhan, N. (Natalie), Shin, J. H. (Jae Hun), Jackson, R. D. (Rebecca D.), Reiner, A. P. (Alexander P.), Martin, L. W. (Lisa Warsinger), Chen, Z. (Zhengming), Li, L. (Liming), Highland, H. M. (Heather M.), Young, K. L. (Kristin L.), Kawaguchi, T. (Takahisa), Thiery, J. (Joachim), Bis, J. C. (Joshua C.), Nadkarni, G. N. (Girish N.), Launer, L. J. (Lenore J.), Li, H. (Huaixing), Nalls, M. A. (Mike A.), Raitakari, O. T. (Olli T.), Ichihara, S. (Sahoko), Wild, S. H. (Sarah H.), Nelson, C. P. (Christopher P.), Campbell, H. (Harry), Jager, S. (Susanne), Nabika, T. (Toru), Al-Mulla, F. (Fahd), Niinikoski, H. (Harri), Braund, P. S. (Peter S.), Kolcic, I. (Ivana), Kovacs, P. (Peter), Giardoglou, T. (Tota), Katsuya, T. (Tomohiro), Bhatti, F. (Fatima), de Kleijn, D. (Dominique), de Borst, G. J. (Gert J.), Kim, E. K. (Eung Kweon), Adams, H. H. (Hieab H. H.), Ikram, M. A. (M. Arfan), Zhu, X. (Xiaofeng), Asselbergs, F. W. (Folkert W.), Kraaijeveld, A. O. (Adriaan O.), Beulens, J. W. (Joline W. J.), Shu, X.-O. (Xiao-Ou), Rallidis, L. S. (Loukianos S.), Pedersen, O. (Oluf), Hansen, T. (Torben), Mitchell, P. (Paul), Hewitt, A. W. (Alex W.), Kahonen, M. (Mika), Perusse, L. (Louis), Bouchard, C. (Claude), Tonjes, A. (Anke), Chen, Y. I. (Yii-Der Ida), Pennell, C. E. (Craig E.), Mori, T. A. (Trevor A.), Lieb, W. (Wolfgang), Franke, A. (Andre), Ohlsson, C. (Claes), Mellstrom, D. (Dan), Cho, Y. S. (Yoon Shin), Lee, H. (Hyejin), Yuan, J.-M. (Jian-Min), Koh, W.-P. (Woon-Puay), Rhee, S. Y. (Sang Youl), Woo, J.-T. (Jeong-Taek), Heid, I. M. (Iris M.), Stark, K. J. (Klaus J.), Volzke, H. (Henry), Homuth, G. (Georg), Evans, M. K. (Michele K.), Zonderman, A. B. (Alan B.), Polasek, O. (Ozren), Pasterkamp, G. (Gerard), Hoefer, I. E. (Imo E.), Redline, S. (Susan), Pahkala, K. (Katja), Oldehinkel, A. J. (Albertine J.), Snieder, H. (Harold), Biino, G. (Ginevra), Schmidt, R. (Reinhold), Schmidt, H. (Helena), Chen, Y. E. (Y. Eugene), Bandinelli, S. (Stefania), Dedoussis, G. (George), Thanaraj, T. A. (Thangavel Alphonse), Kardia, S. L. (Sharon L. R.), Kato, N. (Norihiro), Schulze, M. B. (Matthias B.), Girotto, G. (Giorgia), Jung, B. (Bettina), Boger, C. A. (Carsten A.), Joshi, P. K. (Peter K.), Bennett, D. A. (David A.), De Jager, P. L. (Philip L.), Lu, X. (Xiangfeng), Mamakou, V. (Vasiliki), Brown, M. (Morris), Caulfield, M. J. (Mark J.), Munroe, P. B. (Patricia B.), Guo, X. (Xiuqing), Ciullo, M. (Marina), Jonas, J. B. (Jost B.), Samani, N. J. (Nilesh J.), Kaprio, J. (Jaakko), Pajukanta, P. (Paivi), Adair, L. S. (Linda S.), Bechayda, S. A. (Sonny Augustin), de Silva, H. J. (H. Janaka), Wickremasinghe, A. R. (Ananda R.), Krauss, R. M. (Ronald M.), Wu, J.-Y. (Jer-Yuarn), Zheng, W. (Wei), den Hollander, A. I. (Anneke, I), Bharadwaj, D. (Dwaipayan), Correa, A. (Adolfo), Wilson, J. G. (James G.), Lind, L. (Lars), Heng, C.-K. (Chew-Kiat), Nelson, A. E. (Amanda E.), Golightly, Y. M. (Yvonne M.), Wilson, J. F. (James F.), Penninx, B. (Brenda), Kim, H.-L. (Hyung-Lae), Attia, J. (John), Scott, R. J. (Rodney J.), Rao, D. C. (D. C.), Arnett, D. K. (Donna K.), Walker, M. (Mark), Koistinen, H. A. (Heikki A.), Chandak, G. R. (Giriraj R.), Yajnik, C. S. (Chittaranjan S.), Mercader, J. M. (Josep M.), Tusie-Luna, T. (Teresa), Aguilar-Salinas, C. A. (Carlos A.), Villalpando, C. G. (Clicerio Gonzalez), Orozco, L. (Lorena), Fornage, M. (Myriam), Tai, E. S. (E. Shyong), van Dam, R. M. (Rob M.), Lehtimaki, T. (Terho), Chaturvedi, N. (Nish), Yokota, M. (Mitsuhiro), Liu, J. (Jianjun), Reilly, D. F. (Dermot F.), McKnight, A. J. (Amy Jayne), Kee, F. (Frank), Jockel, K.-H. (Karl-Heinz), McCarthy, M. I. (Mark, I), Palmer, C. N. (Colin N. A.), Vitart, V. (Veronique), Hayward, C. (Caroline), Simonsick, E. (Eleanor), van Duijn, C. M. (Cornelia M.), Lu, F. (Fan), Qu, J. (Jia), Hishigaki, H. (Haretsugu), Lin, X. (Xu), Marz, W. (Winfried), Parra, E. J. (Esteban J.), Cruz, M. (Miguel), Gudnason, V. (Vilmundur), Tardif, J.-C. (Jean-Claude), Lettre, G. (Guillaume), Elders, P. J. (Petra J. M.), Damrauer, S. M. (Scott M.), Kumari, M. (Meena), Kivimaki, M. (Mika), van der Harst, P. (Pim), Spector, T. D. (Tim D.), Loos, R. J. (Ruth J. F.), Province, M. A. (Michael A.), Psaty, B. M. (Bruce M.), Brandslund, I. (Ivan), Pramstaller, P. P. (Peter P.), Christensen, K. (Kaare), Ripatti, S. (Samuli), Widen, E. (Elisabeth), Hakonarson, H. (Hakon), Grant, S. F. (Struan F. A.), Kiemeney, L. A. (Lambertus A. L. M.), de Graaf, J. (Jacqueline), Loeffler, M. (Markus), Kronenberg, F. (Florian), Gu, D. (Dongfeng), Erdmann, J. (Jeanette), Schunkert, H. (Heribert), Franks, P. W. (Paul W.), Linneberg, A. (Allan), Jukema, J. W. (J. Wouter), Khera, A. V. (Amit, V), Männikkö, M. (Minna), Järvelin, M.-R. (Marjo-Riitta), Kutalik, Z. (Zoltan), Cucca, F. (Francesco), Mook-Kanamori, D. O. (Dennis O.), van Dijk, K. W. (Ko Willems), Watkins, H. (Hugh), Strachan, D. P. (David P.), Grarup, N. (Niels), Sever, P. (Peter), Poulter, N. (Neil), Rotter, J. I. (Jerome, I), Dantoft, T. M. (Thomas M.), Karpe, F. (Fredrik), Neville, M. J. (Matt J.), Timpson, N. J. (Nicholas J.), Cheng, C.-Y. (Ching-Yu), Wong, T.-Y. (Tien-Yin), Khor, C. C. (Chiea Chuen), Sabanayagam, C. (Charumathi), Peters, A. (Annette), Gieger, C. (Christian), Hattersley, A. T. (Andrew T.), Pedersen, N. L. (Nancy L.), Magnusson, P. K. (Patrik K. E.), Boomsma, D. I. (Dorret, I), de Geus, E. J. (Eco J. C.), Cupples, L. A. (L. Adrienne), van Meurs, J. B. (Joyce B. J.), Ghanbari, M. (Mohsen), Rsen, P. G. (Penny Gordon-La), Huang, W. (Wei), Kim, Y. J. (Young Jin), Tabara, Y. (Yasuharu), Wareham, N. J. (Nicholas J.), Langenberg, C. (Claudia), Zeggini, E. (Eleftheria), Kuusisto, J. (Johanna), Laakso, M. (Markku), Ingelsson, E. (Erik), Abecasis, G. (Goncalo), Chambers, J. C. (John C.), Kooner, J. S. (Jaspal S.), de Vries, P. S. (Paul S.), Morrison, A. C. (Alanna C.), North, K. E. (Kari E.), Daviglus, M. (Martha), Kraft, P. (Peter), Martin, N. G. (Nicholas G.), Whitfield, J. B. (John B.), Abbas, S. (Shahid), Saleheen, D. (Danish), Walters, R. G. (Robin G.), Holmes, M. V. (Michael, V), Black, C. (Corri), Smith, B. H. (Blair H.), Justice, A. E. (Anne E.), Baras, A. (Aris), Buring, J. E. (Julie E.), Ridker, P. M. (Paul M.), Chasman, D. I. (Daniel, I), Kooperberg, C. (Charles), Wei, W.-Q. (Wei-Qi), Jarvik, G. P. (Gail P.), Namjou, B. (Bahram), Hayes, M. G. (M. Geoffrey), Ritchie, M. D. (Marylyn D.), Jousilahti, P. (Pekka), Salomaa, V. (Veikko), Hveem, K. (Kristian), Asvold, B. O. (Bjorn Olav), Kubo, M. (Michiaki), Kamatani, Y. (Yoichiro), Okada, Y. (Yukinori), Murakami, Y. (Yoshinori), Thorsteinsdottir, U. (Unnur), Stefansson, K. (Kari), Ho, Y.-L. (Yuk-Lam), Lynch, J. A. (Julie A.), Rader, D. J. (Daniel J.), Tsao, P. S. (Philip S.), Chang, K.-M. (Kyong-Mi), Cho, K. (Kelly), O'Donnell, C. J. (Christopher J.), Gaziano, J. M. (John M.), Wilson, P. (Peter), Rotimi, C. N. (Charles N.), Hazelhurst, S. (Scott), Ramsay, M. (Michele), Trembath, R. C. (Richard C.), van Heel, D. A. (David A.), Tamiya, G. (Gen), Yamamoto, M. (Masayuki), Kim, B.-J. (Bong-Jo), Mohlke, K. L. (Karen L.), Frayling, T. M. (Timothy M.), Hirschhorn, J. N. (Joel N.), Kathiresan, S. (Sekar), Boehnke, M. (Michael), Natarajan, P. (Pradeep), Peloso, G. M. (Gina M.), Brown, C. D. (Christopher D.), Morris, A. P. (Andrew P.), Assimes, T. L. (Themistocles L.), Deloukas, P. (Panos), Sun, Y. V. (Yan, V), and Willer, C. J. (Cristen J.)

Abstract

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4‐23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

Published
2021

13. A novel but frequent variant in LPA KIV-2 is associated with a pronounced Lp(a) and cardiovascular risk reduction

Author

Coassin, S., Erhart, G., Weissensteiner, H., de Araujo, M.E.G., Lamina, C., Schoenherr, S., Forer, L., Haun, M., Losso, J.L., Koettgen, A., Schmidt, K., Utermann, G., Peters, A., Gieger, C., Strauch, K., Finkenstedt, A., Bale, R., Zoller, H., Paulweber, B., Eckardt, K., Huettenhofer, A., Huber, L.A., and Kronenberg, F.

Subjects
Adult, Male, Kringle IV-type 2, DNA Copy Number Variations, Genotype, Lipoprotein(a), Lpa, Cvd Risk, Kringle Iv-type 2, Copy Number Variation, Copy number variation, Fast Track Clinical Research, Basic Science for the Clinician, Middle Aged, Polymorphism, Single Nucleotide, Linkage Disequilibrium, LPA, Editor's Choice, Phenotype, Kringles, Cardiovascular Diseases, Risk Factors, Humans, Protein Isoforms, Female, CVD risk, Aged
Abstract

Aims Lp(a) concentrations represent a major cardiovascular risk factor and are almost entirely controlled by one single locus (LPA). However, many genetic factors in LPA governing the enormous variance of Lp(a) levels are still unknown. Since up to 70% of the LPA coding sequence are located in a difficult to access hypervariable copy number variation named KIV-2, we hypothesized that it may contain novel functional variants with pronounced effects on Lp(a) concentrations. We performed a large scale mutation analysis in the KIV-2 using an extreme phenotype approach Methods and results We compiled an discovery set of 123 samples showing discordance between LPA isoform phenotype and Lp(a) concentrations and controls. Using ultra-deep sequencing, we identified a splice site variant (G4925A) in preferential association with the smaller LPA isoforms. Follow-up in a European general population (n = 2892) revealed an exceptionally high carrier frequency of 22.1% in the general population. The variant explains 20.6% of the Lp(a) variance in carriers of low molecular weight (LMW) apo(a) isoforms (P = 5.75e-38) and reduces Lp(a) concentrations by 31.3 mg/dL. Accordingly the odds ratio for cardiovascular disease was reduced from 1.39 [95% confidence interval (CI): 1.17-1.66, P = 1.89e-04] for wildtype LMW individuals to 1.19 [95% CI: 0.92; 1.56, P = 0.19] in LMW individuals who were additionally positive for G4925A. Functional studies point towards a reduction of splicing efficiency by this novel variant. Conclusion A highly frequent but until now undetected variant in the LPA KIV-2 region is strongly associated with reduced Lp(a) concentrations and reduced cardiovascular risk in LMW individuals.

Published
2017

14. Estimation of the Required Lipoprotein(a)-Lowering Therapeutic Effect Size for Reduction in Coronary Heart Disease Outcomes: A Mendelian Randomization Analysis

Author

Lamina, C., Kronenberg, F., Mack, S., Coassin, S., Rueedi, R., Yousri, N.A., Seppälä, I., Lp(a)-GWAS-Consortium (Gieger, C.), Schönherr, S., Forer, L., Erhart, G., Marques-Vidal, P., Lp(a)-GWAS-Consortium (Ried, J.S.), Waeber, G., Bergmann, S., Daehnhardt, D., Stoeckl, A., Raitakari, O.T., Kähönen, M., Lp(a)-GWAS-Consortium (Peters, A.), Lp(a)-GWAS-Consortium (Meitinger, T.), Lp(a)-GWAS-Consortium (Strauch, K.), Kedenko, L., Paulweber, B., Lehtimäki, T., Hunt, S.C., and Vollenweider, P.

Subjects
Adult, Male, medicine.medical_specialty, Statin, medicine.drug_class, Population, Genome-wide association study, Coronary Disease, 030204 cardiovascular system & hematology, Polymorphism, Single Nucleotide, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Medicine, Humans, 030212 general & internal medicine, education, education.field_of_study, biology, business.industry, Brief Report, Therapeutic effect, Mendelian Randomization Analysis, Lipoprotein(a), Odds ratio, Cholesterol, LDL, Middle Aged, Case-Control Studies, Cohort, biology.protein, Female, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Cardiology and Cardiovascular Medicine, business
Abstract

Importance Genetic and epidemiologic data suggest that lipoprotein(a) (Lp[a]) is one of the strongest genetically determined risk factors for coronary heart disease (CHD). Specific therapies to lower Lp(a) are on the horizon, but the required reduction of Lp(a) to translate into clinically relevant lowering of CHD outcomes is a matter of debate. Objective To estimate the required Lp(a)-lowering effect size that may be associated with a reduction of CHD outcomes compared with the effect size of low-density lipoprotein cholesterol (LDL-C)–lowering therapies. Design, Setting, and Participants Genetic epidemiologic study using a mendelian randomization analysis to estimate the required Lp(a)-lowering effect size for a clinically meaningful effect on outcomes. We used the effect estimates for Lp(a) from a genome-wide association study (GWAS) and meta-analysis on Lp(a) published in 2017 of 5 different primarily population-based studies of European ancestry. All Lp(a) measurements were performed in 1 laboratory. Genetic estimates for 27 single-nucleotide polymorphisms on Lp(a) concentrations were used. Odds ratios for these 27 single-nucleotide polymorphisms associated with CHD risk were retrieved from a subsample of the CHD Exome+ consortium. Exposures GeneticLPAscore, plasma Lp(a) concentrations, and observations of statin therapies on CHD outcomes. Main Outcomes and Measures Coronary heart disease. Results The study included 13 781 individuals from the Lp(a)-GWAS-Consortium from 5 primarily population-based studies and 20 793 CHD cases and 27 540 controls from a subsample of the CHD Exome+ consortium. Four of the studies were similar in age distribution (means between 51 and 59 years), and 1 cohort was younger; mean age, 32 years. The frequency of women was similar between 51% and 55%. We estimated that the required reduction in Lp(a) effect size would be 65.7 mg/dL (95% CI, 46.3-88.3) to reach the same potential effect on clinical outcomes that can be reached by lowering LDL-C by 38.67 mg/dL (to convert to millimoles per liter, multiply by 0.0259). Conclusions and Relevance This mendelian randomization analysis estimated a required Lp(a)-lowering effect size of 65.7 mg/dL to reach the same effect as a 38.67-mg/dL lowering of LDL-C. However, this estimate is determined by the observed effect estimates of single-nucleotide polymorphisms on Lp(a) concentrations and is therefore influenced by the standardization of the Lp(a) assay used. As a consequence, calculations of the required Lp(a)-lowering potential of a drug to be clinically effective might have been overestimated in the past.

Published
2019

15. Evaluating the causal relation of ApoA-IV with disease-related traits - A bidirectional two-sample mendelian randomization study

Author

Mack, S., Coassin, S., Vaucher, J., Kronenberg, F., Lamina, C., Rueedi, R., Yousri, N.A., Seppälä, I., ApoA-IV-GWAS Constortium (Gieger, C.), Schönherr, S., Forer, L., Erhart, G., Kollerits, B., Marques-Vidal, P., ApoA-IV-GWAS Constortium (Müller-Nurasyid, M.), Waeber, G., Bergmann, S., Dähnhardt, D., Stöckl, A., Kiechl, S., Raitakari, O.T., Kähönen, M., Willeit, J., Kedenko, L., Paulweber, B., ApoA-IV-GWAS Constortium (Peters, A.), ApoA-IV-GWAS Constortium (Meitinger, T.), ApoA-IV-GWAS Constortium (Strauch, K.), Lehtimäki, T., Hunt, S.C., Vollenweider, P., ApoA-IV-GWAS Consortium, Rueedi, R., Yousri, N.A., Seppälä, I., Gieger, C., Schönherr, S., Forer, L., Erhart, G., Kollerits, B., Marques-Vidal, P., Müller-Nurasyid, M., Waeber, G., Bergmann, S., Dähnhardt, D., Stöckl, A., Kiechl, S., Raitakari, O.T., Kähönen, M., Willeit, J., Kedenko, L., Paulweber, B., Peters, A., Meitinger, T., Strauch, K., Lehtimäki, T., Hunt, S.C., and Vollenweider, P.

Subjects
Blood Glucose, Fasting, Mendelian Randomization Analysis, Lipids, Polymorphism, Single Nucleotide, Article, Phenotype, Quantitative Trait, Heritable, Humans, Genetic Predisposition to Disease, lipids (amino acids, peptides, and proteins), Adiposity, Apolipoproteins A/genetics, Apolipoproteins A/metabolism, Biomarkers, Genetic Association Studies/methods, Glomerular Filtration Rate, Lipids/blood, Apolipoproteins A, Genetic Association Studies
Abstract

Apolipoprotein A-IV (apoA-IV) has been observed to be associated with lipids, kidney function, adiposity- and diabetes-related parameters. To assess the causal relationship of apoA-IV with these phenotypes, we conducted bidirectional Mendelian randomization (MR) analyses using publicly available summary-level datasets from GWAS consortia on apoA-IV concentrations (n = 13,813), kidney function (estimated glomerular filtration rate (eGFR), n = 133,413), lipid traits (HDL cholesterol, LDL cholesterol, triglycerides, n = 188,577), adiposity-related traits (body-mass-index (n = 322,206), waist-hip-ratio (n = 210,088)) and fasting glucose (n = 133,010). Main analyses consisted in inverse-variance weighted and multivariable MR, whereas MR-Egger regression and weighted median estimation were used as sensitivity analyses. We found that eGFR is likely to be causal on apoA-IV concentrations (53 SNPs; causal effect estimate per 1-SD increase in eGFR = -0.39; 95% CI = [-0.54, -0.24]; p-value = 2.4e-07). Triglyceride concentrations were also causally associated with apoA-IV concentrations (40 SNPs; causal effect estimate per 1-SD increase in triglycerides = -0.06; 95% CI = [-0.08, -0.04] ; p-value = 4.8e-07), independently of HDL-C and LDL-C concentrations (causal effect estimate from multivariable MR = -0.06; 95% CI = [-0.10, -0.02]; p-value = 0.0014). Evaluating the inverse direction of causality revealed a possible causal association of apoA-IV on HDL-cholesterol (2 SNPs; causal effect estimate per one percent increase in apoA-IV = -0.40; 95% CI = [-0.60, -0.21] ; p-value = 5.5e-05).

Published
2017

16. Somatic mitochondrial DNA mutations are associated with progression, metastasis and death in oral squamous cell carcinoma

Author

Kloss-Brandstatter, A., primary, Erhart, G., additional, Weissensteiner, H., additional, Schafer, G., additional, Forer, L., additional, Schonherr, S., additional, Pacher, D., additional, Seifarth, C., additional, Stockl, A., additional, Sottsas, I., additional, Klocker, H., additional, Huck, C. W., additional, Rasse, M., additional, Kronenberg, F., additional, and Kloss, F., additional

Published
2014
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17. A genome-wide association meta-analysis on apolipoprotein A-IV concentrations

Author

Lamina, C., Friedel, S., Coassin, S., Rueedi, R., Yousri, N.A., Seppälä, I., Gieger, C., Schönherr, S., Forer, L., Erhart, G., Kollerits, B., Marques-Vidal, P., Ried, J., Waeber, G., Bergmann, S., Dähnhardt, D., Stöckl, A., Kiechl, S., Raitakari, O.T., Kähönen, M., Willeit, J., Kedenko, L., Paulweber, B., Peters, A., Meitinger, T., Strauch, K., Study Group, K., Lehtimäki, T., Hunt, S.C., Vollenweider, P., and Kronenberg, F.

Subjects
Male, Association Studies Articles, Cholesterol, HDL, nutritional and metabolic diseases, Kidney, Lipids, Polymorphism, Single Nucleotide, Humans, lipids (amino acids, peptides, and proteins), Female, Alleles, Apolipoproteins A, Triglycerides, Genome-Wide Association Study
Abstract

Apolipoprotein A-IV (apoA-IV) is a major component of HDL and chylomicron particles and is involved in reverse cholesterol transport. It is an early marker of impaired renal function. We aimed to identify genetic loci associated with apoA-IV concentrations and to investigate relationships with known susceptibility loci for kidney function and lipids. A genome-wide association meta-analysis on apoA-IV concentrations was conducted in five population-based cohorts (n = 13,813) followed by two additional replication studies (n = 2,267) including approximately 10 M SNPs. Three independent SNPs from two genomic regions were significantly associated with apoA-IV concentrations: rs1729407 near APOA4 (P = 6.77 × 10 (-) (44)), rs5104 in APOA4 (P = 1.79 × 10(-)(24)) and rs4241819 in KLKB1 (P = 5.6 × 10(-)(14)). Additionally, a look-up of the replicated SNPs in downloadable GWAS meta-analysis results was performed on kidney function (defined by eGFR), HDL-cholesterol and triglycerides. From these three SNPs mentioned above, only rs1729407 showed an association with HDL-cholesterol (P = 7.1 × 10 (-) (07)). Moreover, weighted SNP-scores were built involving known susceptibility loci for the aforementioned traits (53, 70 and 38 SNPs, respectively) and were associated with apoA-IV concentrations. This analysis revealed a significant and an inverse association for kidney function with apoA-IV concentrations (P = 5.5 × 10(-)(05)). Furthermore, an increase of triglyceride-increasing alleles was found to decrease apoA-IV concentrations (P = 0.0078). In summary, we identified two independent SNPs located in or next the APOA4 gene and one SNP in KLKB1 The association of KLKB1 with apoA-IV suggests an involvement of apoA-IV in renal metabolism and/or an interaction within HDL particles. Analyses of SNP-scores indicate potential causal effects of kidney function and by lesser extent triglycerides on apoA-IV concentrations.

Published
2016

18. Association of mitochondrial DNA copy number with metabolic syndrome and type 2 diabetes in 14 176 individuals.

Author

Fazzini, F., Lamina, C., Raftopoulou, A., Koller, A., Fuchsberger, C., Pattaro, C., Del Greco, F. M., Döttelmayer, P., Fendt, L., Fritz, J., Meiselbach, H., Schönherr, S., Forer, L., Weissensteiner, H., Pramstaller, P. P., Eckardt, K.‐U., Hicks, A. A., and Kronenberg, F.

Subjects
MITOCHONDRIAL DNA, TYPE 2 diabetes, METABOLIC syndrome, CHRONIC kidney failure, KIDNEY physiology, OBESITY
Abstract

Background: Mitochondria play an important role in cellular metabolism, and their dysfunction is postulated to be involved in metabolic disturbances. Mitochondrial DNA is present in multiple copies per cell. The quantification of mitochondrial DNA copy number (mtDNA‐CN) might be used to assess mitochondrial dysfunction. Objectives: We aimed to investigate the cross‐sectional association of mtDNA‐CN with type 2 diabetes and the potential mediating role of metabolic syndrome. Methods: We examined 4812 patients from the German Chronic Kidney Disease (GCKD) study and 9364 individuals from the Cooperative Health Research in South Tyrol (CHRIS) study. MtDNA‐CN was measured in whole blood using a plasmid‐normalized qPCR‐based assay. Results: In both studies, mtDNA‐CN showed a significant correlation with most metabolic syndrome parameters: mtDNA‐CN decreased with increasing number of metabolic syndrome components. Furthermore, individuals with low mtDNA‐CN had significantly higher odds of metabolic syndrome (OR = 1.025; 95% CI = 1.011–1.039, P = 3.19 × 10−4, for each decrease of 10 mtDNA copies) and type 2 diabetes (OR = 1.027; 95% CI = 1.012–1.041; P = 2.84 × 10−4) in a model adjusted for age, sex, smoking and kidney function in the meta‐analysis of both studies. Mediation analysis revealed that the association of mtDNA‐CN with type 2 diabetes was mainly mediated by waist circumference in the GCKD study (66%) and by several metabolic syndrome parameters, especially body mass index and triglycerides, in the CHRIS study (41%). Conclusions: Our data show an inverse association of mtDNA‐CN with higher risk of metabolic syndrome and type 2 diabetes. A major part of the total effect of mtDNA‐CN on type 2 diabetes is mediated by obesity parameters. [ABSTRACT FROM AUTHOR]

Published
2021
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19. A Comprehensive Map Of The Variability In The Lipoprotein(A) Kiv 2 Repeat Region And Follow-Up Of The Kiv-2 Arg20ter Mutation In 11,000 Individuals

Author

Coassin, S., primary, Schönherr, S., additional, Weissensteiner, H., additional, Erhart, G., additional, Di Maio, S., additional, Forer, L., additional, Lamina, C., additional, Peters, A., additional, Thorand, B., additional, Eckardt, K.U., additional, Köttgen, A., additional, Utermann, G., additional, Specht, G., additional, and Kronenberg, F., additional

Published
2019
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20. The Natural History of Ferroportin Disease – First Results of the International, Multicenter non-HFE Registry

Author

Schaefer, B, additional, Viveiros, A, additional, Corradini, E, additional, Massimo, F, additional, Scarlini, S, additional, Rametta, R, additional, Pelucchi, S, additional, Busti, F, additional, Weissensteiner, H, additional, Schönherr, S, additional, Forer, L, additional, Bardou-Jaquet, E, additional, Ryan, J, additional, Loreal, O, additional, Drakesmith, H, additional, Weiss, G, additional, Theurl, I, additional, Kronenberg, F, additional, Girelli, D, additional, Piperno, A, additional, Pietrangelo, A, additional, Valenti, L, additional, Porto, G, additional, Tilg, H, additional, and Zoller, H, additional

Published
2019
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21. A genome-wide association meta-analysis on lipoprotein (a) concentrations adjusted for apolipoprotein (a) isoforms

Author

Mack, S., Coassin, S., Rueedi, R., Yousri, N.A., Seppälä, I., Gieger, C., Schönherr, S., Forer, L., Erhart, G., Marques-Vidal, P., Ried, J.S., Waeber, G., Bergmann, S., Dähnhardt, D., Stöckl, A., Raitakari, O.T., Kähönen, M., Peters, A., Meitinger, T., Strauch, K., Kedenko, L., Paulweber, B., Lehtimäki, T., Hunt, S.C., Vollenweider, P., Lamina, C., Kronenberg, F., and KORA-Study Group

Subjects
Sex Characteristics, Animals, Apolipoproteins A/genetics, Apolipoproteins A/metabolism, Genome-Wide Association Study/methods, Humans, Lipoprotein(a)/genetics, Lipoprotein(a)/metabolism, Polymorphism, Single Nucleotide, Protein Isoforms/metabolism, coronary artery disease, epidemiology, genetics, Commentary, Genetics, Epidemiology, Coronary Artery Disease, Protein Isoforms, Apolipoproteins A, Genome-Wide Association Study, Lipoprotein(a)
Abstract

High lipoprotein (a) [Lp(a)] concentrations are an independent risk factor for cardiovascular outcomes. Concentrations are strongly influenced by apo(a) kringle IV repeat isoforms. We aimed to identify genetic loci associated with Lp(a) concentrations using data from five genome-wide association studies (n = 13,781). We identified 48 independent SNPs in the LPA and 1 SNP in the APOE gene region to be significantly associated with Lp(a) concentrations. We also adjusted for apo(a) isoforms to identify loci affecting Lp(a) levels independently from them, which resulted in 31 SNPs (30 in the LPA , 1 in the APOE gene region). Seven SNPs showed a genome-wide significant association with coronary artery disease (CAD) risk. A rare SNP (rs186696265; MAF ∼1%) showed the highest effect on Lp(a) and was also associated with increased risk of CAD (odds ratio = 1.73, P = 3.35 × 10 -30 ). Median Lp(a) values increased from 2.1 to 91.1 mg/dl with increasing number of Lp(a)-increasing alleles. We found the APOE2 -determining allele of rs7412 to be significantly associated with Lp(a) concentrations ( P = 3.47 × 10 -10 ). Each APOE2 allele decreased Lp(a) by 3.34 mg/dl corresponding to ∼15% of the population's mean values. Performing a gene-based test of association, including suspected Lp(a) receptors and regulators, resulted in one significant association of the TLR2 gene with Lp(a) ( P = 3.4 × 10 -4 ). In summary, we identified a large number of independent SNPs in the LPA gene region, as well as the APOE2 allele, to be significantly associated with Lp(a) concentrations.

Published
2017

23. Circulating dendritic cell precursors in chronic kidney disease: a cross-sectional study

Author

Paul, Katharina, Kretzschmar, Daniel, Yilmaz, Atilla, Bärthlein, Barbara, Titze, Stephanie, Wolf, Gunter, Busch, Martin, GCKD-Study Investigators, Eitner, Frank, Schlieper, Georg Rainer, Findeisen, K., Arweiler, E., Ernst, S., Unger, M., Flöge, Jürgen, Schaeffner, E., Baid-Agrawal, S., Petzold, K., Schindler, R., Hilgers, K. F., Hübner, S., Avendano, S., Becker-Grosspietsch, D., Köttgen, A., Schultheiss, U., Meder, S., Mitsch, E., Walz, G., Lorenzen, J., Kielstein, J. T., Otto, P., Haller, H., Sommerer, C., Föllinger, C., Löschner, T., Zeier, M., Busch, M., Paul, K., Dittrich, L., Wolf, G., Sitter, T., Hilge, R., Blank, C., Krane, V., Schmiedeke, D., Toncar, S., Cavitt, D., Wanner, C., Franz, S., Eckardt, K. U., Titze, S., Hauck, N., Seuchter, S. A., Hausknecht, B., Rittmeier, M., Weigel, A., Prokosch, H. U., Bärthlein, B., Haberländer, K., Beck, A., Ganslandt, T., Stefan, S., Knispel, S., Dressel, T., Gefeller, O., Schmid, M., Malzer, M., Reis, A., Ekici, A. B., Kronenberg, F., Kollerits, B., Weißensteiner, H., Forer, L., Schönherr, S., Oefner, P., and Gronwald, W.

Subjects
Nephrology, Male, Myeloid, 610 Medizin, Disease, Comorbidity, Coronary Artery Disease, Gastroenterology, Coronary artery disease, Medizinische Fakultät, Risk Factors, Germany, Dendritic Cells/pathology, Prevalence, 570 Biowissenschaften, Biologie, Hematopoietic Stem Cells/pathology, Aged, 80 and over, ddc:610, Middle Aged, Coronary Artery Disease/pathology, Renal Insufficiency, Chronic/pathology, Causality, medicine.anatomical_structure, Female, ddc:570, medicine.symptom, Research Article, Adult, medicine.medical_specialty, ddc:500, Germany/epidemiology, Inflammation, Young Adult, Immune system, Internal medicine, medicine, Humans, Renal Insufficiency, Chronic, Aged, business.industry, Dendritic Cells, medicine.disease, Hematopoietic Stem Cells, Blood Cell Count, Blood Cell Count/statistics & numerical data, Cross-Sectional Studies, Immunology, 500 Naturwissenschaften, business, Kidney disease
Abstract

BACKGROUND: Dendritic cells (DC) are professional antigen-presenting cells in the immune system. They patrol the blood as circulating dendritic cell precursors (DCP). Decreased blood DCP count has been shown to be related to atherosclerotic plaque burden. Since chronic kidney disease (CKD) is associated with chronic inflammation and increased cardiovascular risk, the aim of our study was to investigate a potential effect of CKD on circulating DCP numbers especially in patients with a history of cardiovascular disease. METHODS: The number of circulating myeloid (mDCP), plasmacytoid (pDCP), and total DCP (tDCP) was analysed by flow cytometry in 245 patients with CKD stage 3 (with and without known cardiovascular events) and 85 coronary healthy controls. In addition, data were compared with a historical group of 130 patients with known coronary artery disease (CAD). RESULTS: Compared to controls, patients with CKD 3 revealed a significant decrease in circulating mDCP (-29%), pDCP (-43%), and tDCP (-38%) (P < 0.001, respectively). Compared with CAD-patients, the decrease in circulating DCP in CKD was comparable or even more pronounced indicating a potential role for DCP in cardiovascular risk potentiation due to CKD. CONCLUSIONS: Based on previous findings in CAD, the marked decrease of DCP in CKD implicates a potential role for DCP as a mediator of cardiovascular disease. Whether DCP in CKD may act as new cardiovascular biomarkers needs to be established in future prospective trials., authors on behalf of the GCKD-Study Investigators

Published
2013

24. Mirror extreme BMI phenotypes associated with gene dosage at the chromosome 16p11.2 locus

Author

Jacquemont, S., Reymond, A., Zufferey, F., Harewood, L., Walters, R.G., Kutalik, Z., Martinet, D., Shen, Y., Valsesia, A., Beckmann, N.D., Thorleifsson, G., Belfiore, M., Bouquillon, S., Campion, D., Leeuw, N. de, Vries, L.B.A. de, Esko, T., Fernandez, B.A., Fernandez-Aranda, F., Fernandez-Real, J.M., Gratacos, M., Guilmatre, A., Hoyer, J., Jarvelin, M.R., Kooy, R.F., Kurg, A., Caignec, C. Le, Mannik, K., Platt, O.S., Sanlaville, D., Haelst, M.M. van, Villatoro Gomez, S., Walha, F., Wu, B.L., Yu, Y., Aboura, A., Addor, M.C., Alembik, Y., Antonarakis, S.E., Arveiler, B., Barth, M., Bednarek, N., Bena, F., Bergmann, S., Beri, M., Bernardini, L., Blaumeiser, B., Bonneau, D., Bottani, A., Boute, O., Brunner, H.G., Cailley, D., Callier, P., Chiesa, J., Chrast, J., Coin, L., Coutton, C., Cuisset, J.M., Cuvellier, J.C., David, A., Freminville, B. de, Delobel, B., Delrue, M.A., Demeer, B., Descamps, D., Didelot, G., Dieterich, K., Disciglio, V., Doco-Fenzy, M., Drunat, S., Duban-Bedu, B., Dubourg, C., El-Sayed Moustafa, J.S., Elliott, P., Faas, B.H.W., Faivre, L., Faudet, A., Fellmann, F., Ferrarini, A., Fisher, R., Flori, E., Forer, L., Gaillard, D., Gerard, M., Gieger, C., Gimelli, S., Gimelli, G., Grabe, H.J., Guichet, A., Guillin, O., Hartikainen, A.L., Heron, D., Hippolyte, L., Holder, M., Homuth, G., Isidor, B., Jaillard, S., Jaros, Z., Jimenez-Murcia, S., Helas, G.J., et al., Jacquemont, S., Reymond, A., Zufferey, F., Harewood, L., Walters, R.G., Kutalik, Z., Martinet, D., Shen, Y., Valsesia, A., Beckmann, N.D., Thorleifsson, G., Belfiore, M., Bouquillon, S., Campion, D., Leeuw, N. de, Vries, L.B.A. de, Esko, T., Fernandez, B.A., Fernandez-Aranda, F., Fernandez-Real, J.M., Gratacos, M., Guilmatre, A., Hoyer, J., Jarvelin, M.R., Kooy, R.F., Kurg, A., Caignec, C. Le, Mannik, K., Platt, O.S., Sanlaville, D., Haelst, M.M. van, Villatoro Gomez, S., Walha, F., Wu, B.L., Yu, Y., Aboura, A., Addor, M.C., Alembik, Y., Antonarakis, S.E., Arveiler, B., Barth, M., Bednarek, N., Bena, F., Bergmann, S., Beri, M., Bernardini, L., Blaumeiser, B., Bonneau, D., Bottani, A., Boute, O., Brunner, H.G., Cailley, D., Callier, P., Chiesa, J., Chrast, J., Coin, L., Coutton, C., Cuisset, J.M., Cuvellier, J.C., David, A., Freminville, B. de, Delobel, B., Delrue, M.A., Demeer, B., Descamps, D., Didelot, G., Dieterich, K., Disciglio, V., Doco-Fenzy, M., Drunat, S., Duban-Bedu, B., Dubourg, C., El-Sayed Moustafa, J.S., Elliott, P., Faas, B.H.W., Faivre, L., Faudet, A., Fellmann, F., Ferrarini, A., Fisher, R., Flori, E., Forer, L., Gaillard, D., Gerard, M., Gieger, C., Gimelli, S., Gimelli, G., Grabe, H.J., Guichet, A., Guillin, O., Hartikainen, A.L., Heron, D., Hippolyte, L., Holder, M., Homuth, G., Isidor, B., Jaillard, S., Jaros, Z., Jimenez-Murcia, S., Helas, G.J., and et al.

Abstract

Contains fulltext : 96105.pdf (publisher's version ) (Closed access), Both obesity and being underweight have been associated with increased mortality. Underweight, defined as a body mass index (BMI)

Published
2011

30. Patron saints.

Author

Forer, L.

Subjects
*POLITICAL patronage, UNITED States politics & government
Abstract

Advances the idea that the United States government would be more humanized by a return to the patronage system. How it would benefit ordinary citizens; Elected officials would be more answerable; More voters would go to the polls; Party committees as community advocates; Suggested reform of the civil service rules to create more patronage jobs.

Published
1991

31. Morphological Comparisons Between Xiphinema rivesi Daimasso and X. americanum Cobb Populations from the Eastern United States

Author

Wojtowlcz, Marek R., Golden, A. Morgan, Forer, L. B., and Stouffer, R. F.

Subjects
food and beverages, Article
Abstract

Though in the past Xiphinema americanum has been the most commonly reported dagger nematode in the eastern United States, our studies revealed the presence in Pennsvlvania of a previously unrecognized and unreported species related to X. americanum, Morphometric data and photomicrographs establish the identity of this form as X. rivesi and show expected variations in populations of this species from various locations. Similar data and illustrations are given for X. americanum populations from Pennsylvania and other areas, showing variations and relationships. Xiphinema rivesi is widely distributed in the fruit producing area of south-central Pennsylvania and is also reported herein from raspberry in Vermont and apple in Maryland and New York. This species is frequently found in fruit growing areas of Pennsylvania associated with tomato ringspot virus-induced diseases and is also found associated with corn, bluegrass sod, and alfalfa.

Published
1982

32. Cloudgene: A graphical execution platform for MapReduce programs on private and public clouds

Author

Schönherr Sebastian, Forer Lukas, Weißensteiner Hansi, Kronenberg Florian, Specht Günther, and Kloss-Brandstätter Anita

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background The MapReduce framework enables a scalable processing and analyzing of large datasets by distributing the computational load on connected computer nodes, referred to as a cluster. In Bioinformatics, MapReduce has already been adopted to various case scenarios such as mapping next generation sequencing data to a reference genome, finding SNPs from short read data or matching strings in genotype files. Nevertheless, tasks like installing and maintaining MapReduce on a cluster system, importing data into its distributed file system or executing MapReduce programs require advanced knowledge in computer science and could thus prevent scientists from usage of currently available and useful software solutions. Results Here we present Cloudgene, a freely available platform to improve the usability of MapReduce programs in Bioinformatics by providing a graphical user interface for the execution, the import and export of data and the reproducibility of workflows on in-house (private clouds) and rented clusters (public clouds). The aim of Cloudgene is to build a standardized graphical execution environment for currently available and future MapReduce programs, which can all be integrated by using its plug-in interface. Since Cloudgene can be executed on private clusters, sensitive datasets can be kept in house at all time and data transfer times are therefore minimized. Conclusions Our results show that MapReduce programs can be integrated into Cloudgene with little effort and without adding any computational overhead to existing programs. This platform gives developers the opportunity to focus on the actual implementation task and provides scientists a platform with the aim to hide the complexity of MapReduce. In addition to MapReduce programs, Cloudgene can also be used to launch predefined systems (e.g. Cloud BioLinux, RStudio) in public clouds. Currently, five different bioinformatic programs using MapReduce and two systems are integrated and have been successfully deployed. Cloudgene is freely available at http://cloudgene.uibk.ac.at.

Published
2012
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33. CONAN: copy number variation analysis software for genome-wide association studies

Author

Wichmann Heinz-Erich, Gieger Christian, Kluckner Thomas, Haider Florian, Weissensteiner Hansi, Schönherr Sebastian, Forer Lukas, Specht Günther, Kronenberg Florian, and Kloss-Brandstätter Anita

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Genome-wide association studies (GWAS) based on single nucleotide polymorphisms (SNPs) revolutionized our perception of the genetic regulation of complex traits and diseases. Copy number variations (CNVs) promise to shed additional light on the genetic basis of monogenic as well as complex diseases and phenotypes. Indeed, the number of detected associations between CNVs and certain phenotypes are constantly increasing. However, while several software packages support the determination of CNVs from SNP chip data, the downstream statistical inference of CNV-phenotype associations is still subject to complicated and inefficient in-house solutions, thus strongly limiting the performance of GWAS based on CNVs. Results CONAN is a freely available client-server software solution which provides an intuitive graphical user interface for categorizing, analyzing and associating CNVs with phenotypes. Moreover, CONAN assists the evaluation process by visualizing detected associations via Manhattan plots in order to enable a rapid identification of genome-wide significant CNV regions. Various file formats including the information on CNVs in population samples are supported as input data. Conclusions CONAN facilitates the performance of GWAS based on CNVs and the visual analysis of calculated results. CONAN provides a rapid, valid and straightforward software solution to identify genetic variation underlying the 'missing' heritability for complex traits that remains unexplained by recent GWAS. The freely available software can be downloaded at http://genepi-conan.i-med.ac.at.

Published
2010
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34. The power of genetic diversity in genome-wide association studies of lipids

Author

Graham, Sarah E, Clarke, Shoa L, Wu, Kuan-Han H, Kanoni, Stavroula, Zajac, Greg JM, Ramdas, Shweta, Surakka, Ida, Ntalla, Ioanna, Vedantam, Sailaja, Winkler, Thomas W, Locke, Adam E, Marouli, Eirini, Hwang, Mi Yeong, Han, Sohee, Narita, Akira, Choudhury, Ananyo, Bentley, Amy R, Ekoru, Kenneth, Verma, Anurag, Trivedi, Bhavi, Martin, Hilary C, Hunt, Karen A, Hui, Qin, Klarin, Derek, Zhu, Xiang, Thorleifsson, Gudmar, Helgadottir, Anna, Gudbjartsson, Daniel F, Holm, Hilma, Olafsson, Isleifur, Akiyama, Masato, Sakaue, Saori, Terao, Chikashi, Kanai, Masahiro, Zhou, Wei, Brumpton, Ben M, Rasheed, Humaira, Ruotsalainen, Sanni E, Havulinna, Aki S, Veturi, Yogasudha, Feng, QiPing, Rosenthal, Elisabeth A, Lingren, Todd, Pacheco, Jennifer Allen, Pendergrass, Sarah A, Haessler, Jeffrey, Giulianini, Franco, Bradford, Yuki, Miller, Jason E, Campbell, Archie, Lin, Kuang, Millwood, Iona Y, Hindy, George, Rasheed, Asif, Faul, Jessica D, Zhao, Wei, Weir, David R, Turman, Constance, Huang, Hongyan, Graff, Mariaelisa, Mahajan, Anubha, Brown, Michael R, Zhang, Weihua, Yu, Ketian, Schmidt, Ellen M, Pandit, Anita, Gustafsson, Stefan, Yin, Xianyong, Luan, Jian’an, Zhao, Jing-Hua, Matsuda, Fumihiko, Jang, Hye-Mi, Yoon, Kyungheon, Medina-Gomez, Carolina, Pitsillides, Achilleas, Hottenga, Jouke Jan, Willemsen, Gonneke, Wood, Andrew R, Ji, Yingji, Gao, Zishan, Haworth, Simon, Mitchell, Ruth E, Chai, Jin Fang, Aadahl, Mette, Yao, Jie, Manichaikul, Ani, Warren, Helen R, Ramirez, Julia, Bork-Jensen, Jette, Kårhus, Line L, Goel, Anuj, Sabater-Lleal, Maria, Noordam, Raymond, Sidore, Carlo, Fiorillo, Edoardo, McDaid, Aaron F, Marques-Vidal, Pedro, Wielscher, Matthias, Trompet, Stella, Sattar, Naveed, Møllehave, Line T, Thuesen, Betina H, Munz, Matthias, Zeng, Lingyao, Huang, Jianfeng, Yang, Bin, Poveda, Alaitz, Kurbasic, Azra, Lamina, Claudia, Forer, Lukas, Scholz, Markus, Galesloot, Tessel E., Bradfield, Jonathan P., Daw, E Warwick, Zmuda, Joseph M, Mitchell, Jonathan S, Fuchsberger, Christian, Christensen, Henry, Brody, Jennifer A, Feitosa, Mary F, Wojczynski, Mary K, Preuss, Michael, Mangino, Massimo, Christofidou, Paraskevi, Verweij, Niek, Benjamins, Jan W, Engmann, Jorgen, Kember, Rachel L, Slieker, Roderick C, Lo, Ken Sin, Zilhao, Nuno R, Le, Phuong, Kleber, Marcus E, Delgado, Graciela E, Huo, Shaofeng, Ikeda, Daisuke D, Iha, Hiroyuki, Yang, Jian, Liu, Jun, Leonard, Hampton L, Marten, Jonathan, Schmidt, Börge, Arendt, Marina, Smyth, Laura J, Cañadas-Garre, Marisa, Wang, Chaolong, Nakatochi, Masahiro, Wong, Andrew, Hutri-Kähönen, Nina, Sim, Xueling, Xia, Rui, Huerta-Chagoya, Alicia, Fernandez-Lopez, Juan Carlos, Lyssenko, Valeriya, Ahmed, Meraj, Jackson, Anne U, Irvin, Marguerite R, Oldmeadow, Christopher, Kim, Han-Na, Ryu, Seungho, Timmers, Paul RHJ, Arbeeva, Liubov, Dorajoo, Rajkumar, Lange, Leslie A, Chai, Xiaoran, Prasad, Gauri, Lorés-Motta, Laura, Pauper, Marc, Long, Jirong, Li, Xiaohui, Theusch, Elizabeth, Takeuchi, Fumihiko, Spracklen, Cassandra N, Loukola, Anu, Bollepalli, Sailalitha, Warner, Sophie C, Wang, Ya Xing, Wei, Wen B., Nutile, Teresa, Ruggiero, Daniela, Sung, Yun Ju, Hung, Yi-Jen, Chen, Shufeng, Liu, Fangchao, Yang, Jingyun, Kentistou, Katherine A, Gorski, Mathias, Brumat, Marco, Meidtner, Karina, Bielak, Lawrence F, Smith, Jennifer A, Hebbar, Prashantha, Farmaki, Aliki-Eleni, Hofer, Edith, Lin, Maoxuan, Xue, Chao, Zhang, Jifeng, Concas, Maria Pina, Vaccargiu, Simona, van der Most, Peter J, Pitkänen, Niina, Cade, Brian E, Lee, Jiwon, van der Laan, Sander W., Chitrala, Kumaraswamy Naidu, Weiss, Stefan, Zimmermann, Martina E, Lee, Jong Young, Choi, Hyeok Sun, Nethander, Maria, Freitag-Wolf, Sandra, Southam, Lorraine, Rayner, Nigel W, Wang, Carol A, Lin, Shih-Yi, Wang, Jun-Sing, Couture, Christian, Lyytikäinen, Leo-Pekka, Nikus, Kjell, Cuellar-Partida, Gabriel, Vestergaard, Henrik, Hildalgo, Bertha, Giannakopoulou, Olga, Cai, Qiuyin, Obura, Morgan O, van Setten, Jessica, Li, Xiaoyin, Schwander, Karen, Terzikhan, Natalie, Shin, Jae Hun, Jackson, Rebecca D, Reiner, Alexander P, Martin, Lisa Warsinger, Chen, Zhengming, Li, Liming, Highland, Heather M, Young, Kristin L, Kawaguchi, Takahisa, Thiery, Joachim, Bis, Joshua C, Nadkarni, Girish N., Launer, Lenore J, Li, Huaixing, Nalls, Mike A, Raitakari, Olli T, Ichihara, Sahoko, Wild, Sarah H, Nelson, Christopher P, Campbell, Harry, Jäger, Susanne, Nabika, Toru, Al-Mulla, Fahd, Niinikoski, Harri, Braund, Peter S, Kolcic, Ivana, Kovacs, Peter, Giardoglou, Tota, Katsuya, Tomohiro, Bhatti, Konain Fatima, de Kleijn, Dominique, de Borst, Gert J., Kim, Eung Kweon, Adams, Hieab H.H., Ikram, M. Arfan, Zhu, Xiaofeng, Asselbergs, Folkert W, Kraaijeveld, Adriaan O, Beulens, Joline WJ, Shu, Xiao-Ou, Rallidis, Loukianos S, Pedersen, Oluf, Hansen, Torben, Mitchell, Paul, Hewitt, Alex W, Kähönen, Mika, Pérusse, Louis, Bouchard, Claude, Tönjes, Anke, Chen, Yii-Der Ida, Pennell, Craig E, Mori, Trevor A, Lieb, Wolfgang, Franke, Andre, Ohlsson, Claes, Mellström, Dan, Cho, Yoon Shin, Lee, Hyejin, Yuan, Jian-Min, Koh, Woon-Puay, Rhee, Sang Youl, Woo, Jeong-Taek, Heid, Iris M, Stark, Klaus J, Völzke, Henry, Homuth, Georg, Evans, Michele K, Zonderman, Alan B, Polasek, Ozren, Pasterkamp, Gerard, Hoefer, Imo E, Redline, Susan, Pahkala, Katja, Oldehinkel, Albertine J, Snieder, Harold, Biino, Ginevra, Schmidt, Reinhold, Schmidt, Helena, Chen, Y Eugene, Bandinelli, Stefania, Dedoussis, George, Thanaraj, Thangavel Alphonse, Kardia, Sharon LR, Kato, Norihiro, Schulze, Matthias B, Girotto, Giorgia, Jung, Bettina, Böger, Carsten A, Joshi, Peter K, Bennett, David A, De Jager, Philip L, Lu, Xiangfeng, Mamakou, Vasiliki, Brown, Morris, Caulfield, Mark J, Munroe, Patricia B, Guo, Xiuqing, Ciullo, Marina, Jonas, Jost B., Samani, Nilesh J, Chasman, Daniel I., Kaprio, Jaakko, Pajukanta, Päivi, Tusié-Luna, Teresa, Aguilar-Salinas, Carlos A, Adair, Linda S, Bechayda, Sonny Augustin, de Silva, H. Janaka, Wickremasinghe, Ananda R, Krauss, Ronald M, Wu, Jer-Yuarn, Zheng, Wei, den Hollander, Anneke I, Bharadwaj, Dwaipayan, Correa, Adolfo, Wilson, James G, Lind, Lars, Heng, Chew-Kiat, Nelson, Amanda E, Golightly, Yvonne M, Wilson, James F, Penninx, Brenda, Kim, Hyung-Lae, Attia, John, Scott, Rodney J, Rao, D C, Arnett, Donna K, Walker, Mark, Koistinen, Heikki A, Chandak, Giriraj R, Yajnik, Chittaranjan S, Mercader, Josep M, Tusie-Luna, Teresa, Aguilar-Salinas, Carlos, Villalpando, Clicerio Gonzalez, Orozco, Lorena, Fornage, Myriam, Tai, E Shyong, van Dam, Rob M, Lehtimäki, Terho, Chaturvedi, Nish, Yokota, Mitsuhiro, Liu, Jianjun, Reilly, Dermot F, McKnight, Amy Jayne, Kee, Frank, Jöckel, Karl-Heinz, McCarthy, Mark I, Palmer, Colin NA, Vitart, Veronique, Hayward, Caroline, Simonsick, Eleanor, van Duijn, Cornelia M, Lu, Fan, Qu, Jia, Hishigaki, Haretsugu, Lin, Xu, März, Winfried, Parra, Esteban J, Cruz, Miguel, Gudnason, Vilmundur, Tardif, Jean-Claude, Lettre, Guillaume, Hart, Leen M t, Elders, Petra JM, Rader, Daniel J, Damrauer, Scott M, Kumari, Meena, Kivimaki, Mika, van der Harst, Pim, Spector, Tim D, Loos, Ruth J.F., Province, Michael A, Psaty, Bruce M, Brandslund, Ivan, Pramstaller, Peter P, Christensen, Kaare, Ripatti, Samuli, Widén, Elisabeth, Hakonarson, Hakon, Grant, Struan F.A., Kiemeney, Lambertus ALM, de Graaf, Jacqueline, Loeffler, Markus, Kronenberg, Florian, Gu, Dongfeng, Erdmann, Jeanette, Schunkert, Heribert, Franks, Paul W, Linneberg, Allan, Jukema, J. Wouter, Khera, Amit V, Männikkö, Minna, Jarvelin, Marjo-Riitta, Kutalik, Zoltan, Cucca, Francesco, Mook-Kanamori, Dennis O, van Dijk, Ko Willems, Watkins, Hugh, Strachan, David P, Grarup, Niels, Sever, Peter, Poulter, Neil, Rotter, Jerome I, Dantoft, Thomas M, Karpe, Fredrik, Neville, Matt J, Timpson, Nicholas J, Cheng, Ching-Yu, Wong, Tien-Yin, Khor, Chiea Chuen, Sabanayagam, Charumathi, Peters, Annette, Gieger, Christian, Hattersley, Andrew T, Pedersen, Nancy L, Magnusson, Patrik KE, Boomsma, Dorret I, de Geus, Eco JC, Cupples, L Adrienne, van Meurs, Joyce B.J., Ghanbari, Mohsen, Gordon-Larsen, Penny, Huang, Wei, Kim, Young Jin, Tabara, Yasuharu, Wareham, Nicholas J, Langenberg, Claudia, Zeggini, Eleftheria, Kuusisto, Johanna, Laakso, Markku, Ingelsson, Erik, Abecasis, Goncalo, Chambers, John C, Kooner, Jaspal S, de Vries, Paul S, Morrison, Alanna C, North, Kari E., Daviglus, Martha, Kraft, Peter, Martin, Nicholas G, Whitfield, John B, Abbas, Shahid, Saleheen, Danish, Walters, Robin G, Holmes, Michael V, Black, Corri, Smith, Blair H, Justice, Anne E, Baras, Aris, Buring, Julie E, Ridker, Paul M, Chasman, Daniel I, Kooperberg, Charles, Wei, Wei-Qi, Jarvik, Gail P, Namjou, Bahram, Hayes, M. Geoffrey, Ritchie, Marylyn D, Jousilahti, Pekka, Salomaa, Veikko, Hveem, Kristian, Åsvold, Bjørn Olav, Kubo, Michiaki, Kamatani, Yoichiro, Okada, Yukinori, Murakami, Yoshinori, Thorsteinsdottir, Unnur, Stefansson, Kari, Ho, Yuk-Lam, Lynch, Julie A, Rader, Daniel, Tsao, Phil S, Chang, Kyong-Mi, Cho, Kelly, O’Donnell, Christopher J, Gaziano, John M, Wilson, Peter, Rotimi, Charles N, Hazelhurst, Scott, Ramsay, Michèle, Trembath, Richard C, van Heel, David A, Tamiya, Gen, Yamamoto, Masayuki, Kim, Bong-Jo, Mohlke, Karen L, Frayling, Timothy M, Hirschhorn, Joel N, Kathiresan, Sekar, Boehnke, Michael, Natarajan, Pradeep, Peloso, Gina M, Brown, Christopher D, Morris, Andrew P, Assimes, Themistocles L, Deloukas, Panos, Sun, Yan V, Willer, Cristen J, VA Million Veteran Program, Global Lipids Genetics Consortium, Internal Medicine, Epidemiology, Radiology & Nuclear Medicine, Graham, S. E., Clarke, S. L., Wu, K. -H. H., Kanoni, S., Zajac, G. J. M., Ramdas, S., Surakka, I., Ntalla, I., Vedantam, S., Winkler, T. W., Locke, A. E., Marouli, E., Hwang, M. Y., Han, S., Narita, A., Choudhury, A., Bentley, A. R., Ekoru, K., Verma, A., Trivedi, B., Martin, H. C., Hunt, K. A., Hui, Q., Klarin, D., Zhu, X., Thorleifsson, G., Helgadottir, A., Gudbjartsson, D. F., Holm, H., Olafsson, I., Akiyama, M., Sakaue, S., Terao, C., Kanai, M., Zhou, W., Brumpton, B. M., Rasheed, H., Ruotsalainen, S. E., Havulinna, A. S., Veturi, Y., Feng, Q. P., Rosenthal, E. A., Lingren, T., Pacheco, J. A., Pendergrass, S. A., Haessler, J., Giulianini, F., Bradford, Y., Miller, J. E., Campbell, A., Lin, K., Millwood, I. Y., Hindy, G., Rasheed, A., Faul, J. D., Zhao, W., Weir, D. R., Turman, C., Huang, H., Graff, M., Mahajan, A., Brown, M. R., Zhang, W., Yu, K., Schmidt, E. M., Pandit, A., Gustafsson, S., Yin, X., Luan, J., Zhao, J. -H., Matsuda, F., Jang, H. -M., Yoon, K., Medina-Gomez, C., Pitsillides, A., Hottenga, J. J., Willemsen, G., Wood, A. R., Ji, Y., Gao, Z., Haworth, S., Mitchell, R. E., Chai, J. F., Aadahl, M., Yao, J., Manichaikul, A., Warren, H. R., Ramirez, J., Bork-Jensen, J., Karhus, L. L., Goel, A., Sabater-Lleal, M., Noordam, R., Sidore, C., Fiorillo, E., Mcdaid, A. F., Marques-Vidal, P., Wielscher, M., Trompet, S., Sattar, N., Mollehave, L. T., Thuesen, B. H., Munz, M., Zeng, L., Huang, J., Yang, B., Poveda, A., Kurbasic, A., Lamina, C., Forer, L., Scholz, M., Galesloot, T. E., Bradfield, J. P., Daw, E. W., Zmuda, J. M., Mitchell, J. S., Fuchsberger, C., Christensen, H., Brody, J. A., Feitosa, M. F., Wojczynski, M. K., Preuss, M., Mangino, M., Christofidou, P., Verweij, N., Benjamins, J. W., Engmann, J., Kember, R. L., Slieker, R. C., Lo, K. S., Zilhao, N. R., Le, P., Kleber, M. E., Delgado, G. E., Huo, S., Ikeda, D. D., Iha, H., Yang, J., Liu, J., Leonard, H. L., Marten, J., Schmidt, B., Arendt, M., Smyth, L. J., Canadas-Garre, M., Wang, C., Nakatochi, M., Wong, A., Hutri-Kahonen, N., Sim, X., Xia, R., Huerta-Chagoya, A., Fernandez-Lopez, J. C., Lyssenko, V., Ahmed, M., Jackson, A. U., Irvin, M. R., Oldmeadow, C., Kim, H. -N., Ryu, S., Timmers, P. R. H. J., Arbeeva, L., Dorajoo, R., Lange, L. A., Chai, X., Prasad, G., Lores-Motta, L., Pauper, M., Long, J., Li, X., Theusch, E., Takeuchi, F., Spracklen, C. N., Loukola, A., Bollepalli, S., Warner, S. C., Wang, Y. X., Wei, W. B., Nutile, T., Ruggiero, D., Sung, Y. J., Hung, Y. -J., Chen, S., Liu, F., Kentistou, K. A., Gorski, M., Brumat, M., Meidtner, K., Bielak, L. F., Smith, J. A., Hebbar, P., Farmaki, A. -E., Hofer, E., Lin, M., Xue, C., Zhang, J., Concas, M. P., Vaccargiu, S., van der Most, P. J., Pitkanen, N., Cade, B. E., Lee, J., van der Laan, S. W., Chitrala, K. N., Weiss, S., Zimmermann, M. E., Lee, J. Y., Choi, H. S., Nethander, M., Freitag-Wolf, S., Southam, L., Rayner, N. W., Wang, C. A., Lin, S. -Y., Wang, J. -S., Couture, C., Lyytikainen, L. -P., Nikus, K., Cuellar-Partida, G., Vestergaard, H., Hildalgo, B., Giannakopoulou, O., Cai, Q., Obura, M. O., van Setten, J., Schwander, K., Terzikhan, N., Shin, J. H., Jackson, R. D., Reiner, A. P., Martin, L. W., Chen, Z., Li, L., Highland, H. M., Young, K. L., Kawaguchi, T., Thiery, J., Bis, J. C., Nadkarni, G. N., Launer, L. J., Li, H., Nalls, M. A., Raitakari, O. T., Ichihara, S., Wild, S. H., Nelson, C. P., Campbell, H., Jager, S., Nabika, T., Al-Mulla, F., Niinikoski, H., Braund, P. S., Kolcic, I., Kovacs, P., Giardoglou, T., Katsuya, T., Bhatti, K. F., de Kleijn, D., de Borst, G. J., Kim, E. K., Adams, H. H. H., Ikram, M. A., Asselbergs, F. W., Kraaijeveld, A. O., Beulens, J. W. J., Shu, X. -O., Rallidis, L. S., Pedersen, O., Hansen, T., Mitchell, P., Hewitt, A. W., Kahonen, M., Perusse, L., Bouchard, C., Tonjes, A., Chen, Y. -D. I., Pennell, C. E., Mori, T. A., Lieb, W., Franke, A., Ohlsson, C., Mellstrom, D., Cho, Y. S., Lee, H., Yuan, J. -M., Koh, W. -P., Rhee, S. Y., Woo, J. -T., Heid, I. M., Stark, K. J., Volzke, H., Homuth, G., Evans, M. K., Zonderman, A. B., Polasek, O., Pasterkamp, G., Hoefer, I. E., Redline, S., Pahkala, K., Oldehinkel, A. J., Snieder, H., Biino, G., Schmidt, R., Schmidt, H., Chen, Y. E., Bandinelli, S., Dedoussis, G., Thanaraj, T. A., Kardia, S. L. R., Kato, N., Schulze, M. B., Girotto, G., Jung, B., Boger, C. A., Joshi, P. K., Bennett, D. A., De Jager, P. L., Lu, X., Mamakou, V., Brown, M., Caulfield, M. J., Munroe, P. B., Guo, X., Ciullo, M., Jonas, J. B., Samani, N. J., Kaprio, J., Pajukanta, P., Adair, L. S., Bechayda, S. A., de Silva, H. J., Wickremasinghe, A. R., Krauss, R. M., Wu, J. -Y., Zheng, W., den Hollander, A. I., Bharadwaj, D., Correa, A., Wilson, J. G., Lind, L., Heng, C. -K., Nelson, A. E., Golightly, Y. M., Wilson, J. F., Penninx, B., Kim, H. -L., Attia, J., Scott, R. J., Rao, D. C., Arnett, D. K., Walker, M., Koistinen, H. A., Chandak, G. R., Yajnik, C. S., Mercader, J. M., Tusie-Luna, T., Aguilar-Salinas, C. A., Villalpando, C. G., Orozco, L., Fornage, M., Tai, E. S., van Dam, R. M., Lehtimaki, T., Chaturvedi, N., Yokota, M., Reilly, D. F., Mcknight, A. J., Kee, F., Jockel, K. -H., Mccarthy, M. I., Palmer, C. N. A., Vitart, V., Hayward, C., Simonsick, E., van Duijn, C. M., Lu, F., Qu, J., Hishigaki, H., Lin, X., Marz, W., Parra, E. J., Cruz, M., Gudnason, V., Tardif, J. -C., Lettre, G., 't Hart, L. M., Elders, P. J. M., Damrauer, S. M., Kumari, M., Kivimaki, M., van der Harst, P., Spector, T. D., Loos, R. J. F., Province, M. A., Psaty, B. M., Brandslund, I., Pramstaller, P. P., Christensen, K., Ripatti, S., Widen, E., Hakonarson, H., Grant, S. F. A., Kiemeney, L. A. L. M., de Graaf, J., Loeffler, M., Kronenberg, F., Gu, D., Erdmann, J., Schunkert, H., Franks, P. W., Linneberg, A., Jukema, J. W., Khera, A. V., Mannikko, M., Jarvelin, M. -R., Kutalik, Z., Cucca, F., Mook-Kanamori, D. O., van Dijk, K. W., Watkins, H., Strachan, D. P., Grarup, N., Sever, P., Poulter, N., Rotter, J. I., Dantoft, T. M., Karpe, F., Neville, M. J., Timpson, N. J., Cheng, C. -Y., Wong, T. -Y., Khor, C. C., Sabanayagam, C., Peters, A., Gieger, C., Hattersley, A. T., Pedersen, N. L., Magnusson, P. K. E., Boomsma, D. I., de Geus, E. J. C., Cupples, L. A., van Meurs, J. B. J., Ghanbari, M., Gordon-Larsen, P., Huang, W., Kim, Y. J., Tabara, Y., Wareham, N. J., Langenberg, C., Zeggini, E., Kuusisto, J., Laakso, M., Ingelsson, E., Abecasis, G., Chambers, J. C., Kooner, J. S., de Vries, P. S., Morrison, A. C., North, K. E., Daviglus, M., Kraft, P., Martin, N. G., Whitfield, J. B., Abbas, S., Saleheen, D., Walters, R. G., Holmes, M. V., Black, C., Smith, B. H., Justice, A. E., Baras, A., Buring, J. E., Ridker, P. M., Chasman, D. I., Kooperberg, C., Wei, W. -Q., Jarvik, G. P., Namjou, B., Hayes, M. G., Ritchie, M. D., Jousilahti, P., Salomaa, V., Hveem, K., Asvold, B. O., Kubo, M., Kamatani, Y., Okada, Y., Murakami, Y., Thorsteinsdottir, U., Stefansson, K., Ho, Y. -L., Lynch, J. A., Rader, D. J., Tsao, P. S., Chang, K. -M., Cho, K., O'Donnell, C. J., Gaziano, J. M., Wilson, P., Rotimi, C. N., Hazelhurst, S., Ramsay, M., Trembath, R. C., van Heel, D. A., Tamiya, G., Yamamoto, M., Kim, B. -J., Mohlke, K. L., Frayling, T. M., Hirschhorn, J. N., Kathiresan, S., Boehnke, M., Natarajan, P., Peloso, G. M., Brown, C. D., Morris, A. P., Assimes, T. L., Deloukas, P., Sun, Y. V., Willer, C. J., Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Life Course Epidemiology (LCE), Cardiovascular Centre (CVC), Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, APH - Mental Health, APH - Methodology, AMS - Ageing & Vitality, and AMS - Sports

Subjects
blood lipid level, Multifactorial Inheritance, GWAS, blood lipid levels, cardiovascular disease, Vascular damage Radboud Institute for Health Sciences [Radboudumc 16], Medizin, LOCI, ANCESTRY, VARIANTS, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Sensory disorders Donders Center for Medical Neuroscience [Radboudumc 12], Article, Population Groups, SDG 3 - Good Health and Well-being, Humans, Genetic Predisposition to Disease, METAANALYSIS, POLYMORPHISMS, RISK, Multidisciplinary, Cardiovascular Diseases, Genome-Wide Association Study, Cardiovascular Diseases/genetics, Genetic Predisposition to Disease/genetics, Genome-Wide Association Study/methods, Polymorphism, Single Nucleotide/genetics, CHOLESTEROL, Human Genetics, INDIVIDUALS, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], DISCOVERY, LOW-FREQUENCY, Delivery of Health Care
Abstract

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use 1 . Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels 2 , heart disease remains the leading cause of death worldwide 3 . Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS 4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns 24 . Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine 25 , we anticipate that increased diversity of participants will lead to more accurate and equitable 26 application of polygenic scores in clinical practice.

Published
2021

35. Mirror extreme BMI phenotypes associated with gene dosage at the chromosome 16p11.2 locus

Author

Stephen W. Scherer, Mònica Gratacòs, Kari Stefansson, Muriel Holder, Unnur Thorsteinsdottir, Lukas Forer, Katharina M. Roetzer, Josette Lucas, Claudia Schurmann, Satu Kaksonen, Armand Valsesia, Carina Wallgren-Pettersson, Barbara Leube, Alexandra I. F. Blakemore, Alexandre Moerman, Marco Belfiore, Anne Faudet, Dominique Gaillard, Roberto Ravazzolo, Dominique Bonneau, Marjo-Riitta Järvelin, Yongguo Yu, Louis Vallée, Bénédicte Demeer, Sophie Visvikis-Siest, Frédérique Béna, Brigitte H. W. Faas, Benoit Arveiler, Georg Homuth, Charles Coutton, Bénédicte de Fréminville, Giorgio Gimelli, Xavier Estivill, Richard I. Fisher, Stefania Gimelli, Wendy Roberts, Jacques S. Beckmann, Emilie Landais, Orah S. Platt, Robin G. Walters, Gudmar Thorleifsson, Alexandre Reymond, Anna-Liisa Hartikainen, Solenn Legallic, James F. Gusella, Peter Vollenweider, Gian Paolo Ramelli, Tõnu Esko, Boris Keren, Nine V A M Knoers, Fanny Morice-Picard, Dominique Campion, Odile Boute, Evica Rajcan-Separovic, Rolph Pfundt, Nathalie Bednarek, Martine Doco-Fenzy, Suzanne M E Lewis, Gérard Didelot, Mylène Beri, Engilbert Sigurdsson, Véronique Satre, Audrey Labalme, Carola Tengstrom, Florian Kronenberg, Florence Petit, Simon Zwolinksi, Philippe Froguel, Paul Elliott, Dorothée Cailley, Christian R. Marshall, Bruno Leheup, Klaus Dieterich, Janina S. Ried, Sylvie Jaillard, Armand Bottani, Stylianos E. Antonarakis, Elisabetta Lapi, Jean-Christophe Cuvellier, Robert M. Witwicki, Gérard Waeber, Christèle Dubourg, Marion Gérard, Lachlan J. M. Coin, Magalie Barth, Anita Kloss-Brandstätter, Vincent Mooser, Cristóbal Richart, Giuseppe Merla, Bénédicte Duban-Bedu, Yiping Shen, Ants Kurg, Audrey Guilmatre, Juliane Hoyer, Susana Jiménez-Murcia, Mafalda Mucciolo, Bai-Lin Wu, Alessandra Ferrarini, Séverine Drunat, Yves Alembik, Páll Magnússon, Han G. Brunner, Maria Antonietta Mencarelli, Dominique Descamps, R. Frank Kooy, Azzedine Aboura, Valérie Layet, Sven Bergmann, Thomas Meitinger, Peter M. Kroisel, Nathalie Van der Aa, Olivier Guillin, Michèle Mathieu-Dramard, Zoltán Kutalik, Elisabeth Flori, Laurent Pasquier, André Reis, Noam D. Beckmann, Bertrand Isidor, Delphine Héron, Philippe Jonveaux, Sergi Villatoro Gomez, Ann Nordgren, José Manuel Fernández-Real, Florence Fellmann, Fernando Fernández-Aranda, Laurence Faivre, Dimitri J. Stavropoulos, Katrin Männik, Christian Gieger, Evald Saemundsen, Agnès Guichet, Jean-Marie Cuisset, R. Touraine, Laura Bernardini, Marie-Ange Delrue, Alessandra Renieri, Omar Gustafsson, Flore Zufferey, David A. Koolen, Massimiliano Rossi, Jacqueline Chrast, Ghislaine Plessis, Faida Walha, Joris Andrieux, Ellen van Binsbergen, Albert David, Catherine Vincent-Delorme, Cédric Le Caignec, Jean Chiesa, Ndeye Coumba Ndiaye, Geraldine Joly Helas, Damien Sanlaville, Anita Rauch, Louise Harewood, Mark I. McCarthy, Bridget A. Fernandez, Sébastien Jacquemont, Hreinn Stefansson, Anneke T. Vulto-van Silfhout, Zdenek Jaros, Matthias Nauck, Hans J. Grabe, Sonia Bouquillon, Mieke M. van Haelst, Andres Metspalu, Loyse Hippolyte, Patrick Callier, Bert B.A. de Vries, Francisco J. Tinahones, Nicole de Leeuw, Julia S. El-Sayed Moustafa, Claudine Rieubland, Kay D. MacDermot, Vittoria Disciglio, Henry Völzke, Caroline Rooryck, Bettina Blaumeiser, Danielle Martinet, Marie-Claude Addor, Bruno Delobel, Jacquemont, S, Reymond, A, Zufferey, F, Harewood, L, Walters, Rg, Kutalik, Z, Martinet, D, Shen, Y, Valsesia, A, Beckmann, Nd, Thorleifsson, G, Belfiore, M, Bouquillon, S, Campion, D, de Leeuw, N, de Vries, Bb, Esko, T, Fernandez, Ba, Fernández-Aranda, F, Fernández-Real, Jm, Gratacòs, M, Guilmatre, A, Hoyer, J, Jarvelin, Mr, Kooy, Rf, Kurg, A, Le Caignec, C, Männik, K, Platt, O, Sanlaville, D, Van Haelst, Mm, Villatoro Gomez, S, Walha, F, Wu, Bl, Yu, Y, Aboura, A, Addor, Mc, Alembik, Y, Antonarakis, Se, Arveiler, B, Barth, M, Bednarek, N, Béna, F, Bergmann, S, Beri, M, Bernardini, L, Blaumeiser, B, Bonneau, D, Bottani, A, Boute, O, Brunner, Hg, Cailley, D, Callier, P, Chiesa, J, Chrast, J, Coin, L, Coutton, C, Cuisset, Jm, Cuvellier, Jc, David, A, de Freminville, B, Delobel, B, Delrue, Ma, Demeer, B, Descamps, D, Didelot, G, Dieterich, K, Disciglio, V, Doco-Fenzy, M, Drunat, S, Duban-Bedu, B, Dubourg, C, El-Sayed Moustafa, J, Elliott, P, Faas, Bh, Faivre, L, Faudet, A, Fellmann, F, Ferrarini, A, Fisher, R, Flori, E, Forer, L, Gaillard, D, Gerard, M, Gieger, C, Gimelli, S, Gimelli, G, Grabe, Hj, Guichet, A, Guillin, O, Hartikainen, Al, Heron, D, Hippolyte, L, Holder, M, Homuth, G, Isidor, B, Jaillard, S, Jaros, Z, Jiménez-Murcia, S, Helas, Gj, Jonveaux, P, Kaksonen, S, Keren, B, Kloss-Brandstätter, A, Knoers, Nv, Koolen, Da, Kroisel, Pm, Kronenberg, F, Labalme, A, Landais, E, Lapi, E, Layet, V, Legallic, S, Leheup, B, Leube, B, Lewis, S, Lucas, J, Macdermot, Kd, Magnusson, P, Marshall, C, Mathieu-Dramard, M, Mccarthy, Mi, Meitinger, T, Mencarelli, Ma, Merla, G, Moerman, A, Mooser, V, Morice-Picard, F, Mucciolo, M, Nauck, M, Ndiaye, Nc, Nordgren, A, Pasquier, L, Petit, F, Pfundt, R, Plessis, G, Rajcan-Separovic, E, Ramelli, Gp, Rauch, A, Ravazzolo, R, Reis, A, Renieri, A, Richart, C, Ried, J, Rieubland, C, Roberts, W, Roetzer, Km, Rooryck, C, Rossi, M, Saemundsen, E, Satre, V, Schurmann, C, Sigurdsson, E, Stavropoulos, Dj, Stefansson, H, Tengström, C, Thorsteinsdóttir, U, Tinahones, Fj, Touraine, R, Vallée, L, van Binsbergen, E, Van der Aa, N, Vincent-Delorme, C, Visvikis-Siest, S, Vollenweider, P, Völzke, H, Vulto-van Silfhout, At, Waeber, G, Wallgren-Pettersson, C, Witwicki, Rm, Zwolinksi, S, Andrieux, J, Estivill, X, Gusella, Jf, Gustafsson, O, Metspalu, A, Scherer, Sw, Stefansson, K, Blakemore, Ai, Beckmann, J, Froguel, P, Faculteit Medische Wetenschappen/UMCG, Service de génétique médicale, Centre Hospitalier Universitaire Vaudois [Lausanne] (CHUV), Center for Integrative Genomics - Institute of Bioinformatics, Génopode (CIG), Swiss Institute of Bioinformatics [Lausanne] (SIB), Université de Lausanne = University of Lausanne (UNIL)-Université de Lausanne = University of Lausanne (UNIL), Department of Genomics of Common Disease, Imperial College London, Department of Medical Genetics, Université de Lausanne = University of Lausanne (UNIL), Laboratory Medicine, Boston Children's Hospital, Center for Human Genetic Research, Massachusetts General Hospital [Boston], Ludwig Institute for Cancer Research, deCODE Genetics, deCODE genetics [Reykjavik], Laboratoire de Génétique Médicale, Hôpital Jeanne de Flandre [Lille]-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Génétique médicale et fonctionnelle du cancer et des maladies neuropsychiatriques, Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Estonian Genome and Medicine, University of Tartu, Department of human genetics, Radboud University Medical Center [Nijmegen]-Nijmegen Centre for Molecular Life Sciences-Institute for Genetic and Metabolic Disorders, Institute of Molecular and Cell Biology, Disciplines of Genetics and Medicine, Memorial University of Newfoundland = Université Memorial de Terre-Neuve [St. John's, Canada] (MUN), Department of Psychiatry (IDIBELL), CIBERobn Fisiopatología de la Obesidad y Nutrición-University Hospital of Bellvitge, Section of Diabetes, Endocrinology and Nutrition, University Hospital of Girona-Biomedical Research Institute 'Dr Josep Trueta'-CIBERobn Fisiopatología de la Obesidad y Nutrición, Center for Genomic Regulation (CRG-UPF), CIBER de Epidemiología y Salud Pública (CIBERESP), Institute of Human Genetics [Erlangen, Allemagne], Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Department of child and adolescent health, University of Oulu-Institute of Health Sciences and Biocenter Oulu-National Institute for Health and Welfare [Helsinki], Antwerp University Hospital [Edegem] (UZA), CHU Trousseau [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Service de cytogénétique constitutionnelle, Hospices Civils de Lyon (HCL)-CHU de Lyon-Centre Neuroscience et Recherche, University Medical Center [Utrecht], Institutes of Biomedical Science, Fudan University [Shanghai]-Children's Hospital, Shanghai Children's Medical Center, Département de génétique, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Robert Debré-Université Paris Diderot - Paris 7 (UPD7), Service de cytogénétique, CHU Strasbourg-Hôpital de Hautepierre [Strasbourg], Génétique médicale, Hôpitaux Universitaires de Genève (HUG), Maladies Rares - Génétique et Métabolisme (MRGM), Université Bordeaux Segalen - Bordeaux 2-Hôpital Pellegrin-Service de Génétique Médicale du CHU de Bordeaux, Université de Bordeaux (UB)-CHU Bordeaux [Bordeaux]-Groupe hospitalier Pellegrin, Service de génétique [Angers], Université d'Angers (UA)-Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM)-PRES Université Nantes Angers Le Mans (UNAM), Université de Reims Champagne-Ardenne (URCA), Department of Molecular Genetics, Weizmann Institute of Science [Rehovot, Israël], Service de Génétique [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Mendel Laboratory, Istituto di Ricovero e Cura a Carattere Scientifico, Ospedale Casa Sollievo della Sofferenza [San Giovanni Rotondo] (IRCCS), Service de Génétique clinique, Laboratoire de cytogénétique (CHU de Dijon), Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Laboratoire de Cytogénétique, Centre Hospitalier Universitaire de Nîmes (CHU Nîmes), Département de génétique et procréation, Université Joseph Fourier - Grenoble 1 (UJF)-CHU Grenoble-faculté de médecine-pharmacie, AGeing and IMagery (AGIM), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de biochimie et génétique moléculaire, CHU Grenoble, Service de Neuropédiatrie, Hôpital Roger Salengro [Lille]-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Service de génétique, Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E), Centre de Génétique Chromosomique, Hôpital Saint Vincent de Paul-Groupement des Hôpitaux de l'Institut Catholique de Lille (GHICL), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), CHU Amiens-Picardie, Centre Hospitalier de Béthune (CH Béthune), GHT de l'Artois, Service de Génétique Clinique, Department of Biotechnology, Università degli Studi di Siena = University of Siena (UNISI)-Medical Genetics, Service de Génétique, Centre Hospitalier Universitaire de Reims (CHU Reims)-Hôpital Maison Blanche-IFR 53, Université de Reims Champagne-Ardenne (URCA)-Université de Reims Champagne-Ardenne (URCA), Institut de Génétique et Développement de Rennes (IGDR), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS), Department of Epidemiology and Public Health, Department of Human Genetics [Nijmegen], Radboud University Medical Center [Nijmegen], Department of Experimental Cardiology, Academic Medical Center - Academisch Medisch Centrum [Amsterdam] (AMC), University of Amsterdam [Amsterdam] (UvA)-University of Amsterdam [Amsterdam] (UvA)-Heart Failure Research Center (HFRC), CHU Pitié-Salpêtrière [AP-HP], Institute of human genetics, International Centre for Life, Division of genetic epidemiology, HMNC Brain Health-Molecular and Clinical Pharmacology-Innsbruck Medical University = Medizinische Universität Innsbruck (IMU), Institute of Experimental Medicine, Czech Academy of Sciences [Prague] (CAS), Department of Obstetrics and Gynecology, University of Oulu-Institute of Clinical Medicine, Laboratorio di citogenetica, G. Gaslini Institute, Department of Psychiatry and Psychotherapy, Universität Greifswald - University of Greifswald, Interfaculty Institute for Genetics and Functional Genomics, Abteilung für Kinder und Jugendheilkunde, Landesklinikum Waldviertel Zwettl, Service de génétique [Rouen], CHU Rouen, Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU), The Habilitation Unit of Folkhalsan, Medical University Graz, Medical Genetics Unit, Children's Hospital Anna Meyer, Unité de Cytogénétique et Génétique Médicale, Groupe Hospitalier du Havre-Hôpital Gustave Flaubert, Service de Médecine Infantile III et Génétique Clinique [CHRU Nancy], Institute of Human Genetics and Anthropology, Heinrich-Heine University Hospital Duesseldorf, Child and Family Research Institute-University of British Columbia (UBC), North West Thames Regional Genetics Service, Northwick Park & St Marks Hospital, Child and Adolescent Psychiatry, Landspitali University Hospital, Program in Genetics and Genomic Biology, Hospital for Sick Children-University of Toronto McLaughlin Centre, Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), University of Oxford, The Wellcome Trust Centre for Human Genetics [Oxford], Institute of Human Genetics, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM)-Helmholtz Zentrum München = German Research Center for Environmental Health, Genetics, GlaxoSmithKline R&D, GlaxoSmithKline, Institute of Clinical Chemistry and Laboratory Medicine, Génétique cardiovasculaire (GC), Université Henri Poincaré - Nancy 1 (UHP), Molecular Medicine and Surgery department, Karolinska Institutet [Stockholm], Service de Génétique [CHU Caen], Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Tumorothèque de Caen Basse-Normandie (TCBN), Department of Pathology, Division of pediatrics, Ospedale San Giovanni, Institute of Medical Genetics, Universität Zürich [Zürich] = University of Zurich (UZH), Department of pediatrics and CEBR, Università degli studi di Genova = University of Genoa (UniGe)-G. Gaslini Institute, Department of Internal Medicine, Universitat Rovira i Virgili-University Hospital Juan XXIII-Instituto Salud Carlos III-Ciber Fisiopatologia Obesidad y Nutricion (CIBEROBN), Division of Human Genetics, Department of Paediatrics, Inselspital-University of Bern, Autism Research Unit, The Hospital for sick children [Toronto] (SickKids)-University of Toronto, State Diagnostic, Counseling Center, University of Iceland [Reykjavik], Department of Pediatric Laboratory Medicine, Hospital for Sick Children, Genetic Services, Rinnekoti Research Foundation, Department of Endocrinology and Nutrition, Instituto Salud Carlos III-Clinic Hospital of Virgen de la Victoria-Ciber Fisiopatologia y Nutricion (CIBEROBN), Centre de Maladies Rares, Anomalies du Développement Nord de France-CH Arras - CHRU Lille, Institute for Community Medicine, Department of Medical and Clinical Genetics [Helsinki], Haartman Institute [Helsinki], Faculty of Medecine [Helsinki], Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Faculty of Medecine [Helsinki], Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, The Centre for Applied Genomics, Toronto, The Hospital for sick children [Toronto] (SickKids)-University of Toronto-Department of Molecular Genetics-McLaughlin Centre, Institut de biologie de Lille - UMS 3702 (IBL), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), This work was supported by the Leenaards Foundation Prize (SJ, DM and AR), the Jérôme Lejeune Foundation (AR), the Telethon Action Suisse Foundation (AR), the Swiss National Science Foundation (AR, JSB, SB and SEA), a SNSF Sinergia grant (SJ, DM, SB, JSB and AR), the European Commission anEUploidy Integrated Project grant 037627 (AR, SB, XE, HGB and SEA), the Ludwig Institute for Cancer Research (AV), the Swiss Institute of Bioinformatics (SB, ZK), an Imperial College Dept of Medicine PhD studentship (JSe-SM), the Comprehensive Biomedical Research Centre, Imperial College Healthcare NHS Trust, and the National Institute for Health Research (PE), the Wellcome Trust and the Medical Research Council (AIFB and PF), the Instituto de Salud Carlos III (ISCIII)-FIS, the German Mental Retardation Network funded through a grant of the German Federal Ministry of Education and Research (NGFNplus 01GS08160) to A Reis and European Union-FEDER (PI081714, PS09/01778), SAF2008-02278 (XE, MG, FFA), the Belgian National Fund for Scientific Research - Flanders (NVA, RFK), the Dutch Organisation for Health Research and Development (ZONMW grant 917-86-319) and Hersenstichting Nederland (BBAdV), grant 81000346 from the Chinese National Natural Science Foundation (YGY), the Simons Foundation Autism Research Initiative, Autism Speaks and NIH grant GM061354 (JFG), and the OENB grant 13059 (AK-B). YS holds a Young Investigator Award from the Children's Tumor Foundation and Catalyst Award from Harvard Medical School, and BLW, a Fudan Scholar Research Award from Fudan University, a grant from Chinese National '973' project on Population and Health (2010CB529601) and a grant from Science and Technology Council of Shanghai (09JC1402400). ERS and SL, recipients of the Michael Smith Foundation for Health Research Scholar award, acknowledge the CIHR MOP 74502 operational grant. EGCUT received support from the EU Centre of Excellence in Genomics and FP7 grants #201413 and #245536, from Estonian Government SF0180142s08, SF0180026s09 and SF0180027s10 (AM, KM, AK). The Helmholtz Zentrum Munich and the State of Bavaria financed KORA, also supported by the German National Genome Research Network (NGFN-2 and NGFNPlus: 01GS0823), the German Federal Ministry of Education and Research (BMBF), and the Munich Center of Health Sciences (MC Health, LMUinnovativ). CIBEROBN and CIBERESP are initiatives of ISCIII (Spain). SWS holds the GlaxoSmithKline-Canadian Institutes of Health (CIHR) Chair in Genetics, Genomics at the University of Toronto and the Hospital for Sick Children and is supported by Genome Canada and the McLaughlin Centre. deCODE was funded in part by NIH grant MH071425 (KS), EU grant HEALTH-2007-2.2.1-10-223423 (Project PsychCNV) and EU grant IMI-JU-NewMeds., Centre de génomique intégrative, Université de Lausanne (UNIL), Swiss Institute of Bioinformatics (SIB), Swiss Institute of Bioinformatics, Memorial University of Newfoundland [St. John's], Friedrich Alexander University [Erlangen-Nürnberg], Service d'ORL et de Chirurgie Cervicofaciale, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Trousseau [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpital Robert Debré-Université Paris Diderot - Paris 7 (UPD7), Weizmann Institute of Science, IRCCS Casa Sollievo della Sofferenza Hospital, Centre Hospitalier Régional Universitaire de Nîmes (CHRU Nîmes), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-École pratique des hautes études (EPHE)-Centre National de la Recherche Scientifique (CNRS), Hôpital Roger Salengro-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), CHU Saint-Etienne-Hôpital nord, Hôpital Saint Vincent de Paul-GHICL, Centre hospitalier de Béthune, Università degli Studi di Siena (UNISI)-Medical Genetics, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-IFR140-Centre National de la Recherche Scientifique (CNRS), Department of Human Genetics, Radboud University Medical Centre, PO Box 9101, 6500 HB Nijmegen, Service de Génétique Cytogénétique et Embryologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Pitié-Salpêtrière [APHP], Innsbruck Medical University [Austria] (IMU)-HMNC Brain Health-Molecular and Clinical Pharmacology, Czech Academy of Sciences [Prague] (ASCR), University of Oxford [Oxford], Technische Universität München [München] (TUM)-Helmholtz-Zentrum München (HZM)-German Research Center for Environmental Health, University of Zürich [Zürich] (UZH), Universita degli studi di Genova -G. Gaslini Institute, University of Toronto-The Hospital for Sick Children, University of Helsinki-University of Helsinki-Faculty of Medecine [Helsinki], University of Helsinki-University of Helsinki, University of Toronto-The Hospital for Sick Children-Department of Molecular Genetics-McLaughlin Centre, Institut de biologie de Lille - IBL (IBLI), Université de Lille, Sciences et Technologies-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Reproduction & Development (AR&D), De Villemeur, Hervé, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-École pratique des hautes études (EPHE), Service of Medical Genetics, Centre Hospitalier Universitaire Vaudois, 1011 Lausanne, Switzerland., Other departments, Reymond, Alexandre, Antonarakis, Stylianos, Sloan Bena, Frédérique, Bottani, Armand, Callier, Patrick, Gimelli, Stefania, Merla, Giuseppe, Vollenweider, Peter, Université de Lausanne (UNIL)-Université de Lausanne (UNIL), Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Joseph Fourier - Grenoble 1 (UJF)-Université Pierre Mendès France - Grenoble 2 (UPMF), Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM)-Helmholtz-Zentrum München (HZM)-German Research Center for Environmental Health, CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Université de Caen Normandie (UNICAEN), University of Toronto-The Hospital for sick children [Toronto] (SickKids)-Department of Molecular Genetics-McLaughlin Centre, Université de Lille-Institut Pasteur de Lille, and Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Male, Aging, Transcription, Genetic, Adolescent, Adult, Aged, Body Height, Body Mass Index, Case-Control Studies, Child, Child, Preschool, Chromosomes, Human, Pair 16, Cohort Studies, Comparative Genomic Hybridization, Developmental Disabilities, Energy Metabolism, Europe, Female, Gene Dosage, Gene Duplication, Gene Expression Profiling, Genetic Predisposition to Disease, Genome-Wide Association Study, Head, Heterozygote, Humans, Infant, Infant, Newborn, Mental Disorders, Middle Aged, Mutation, North America, Obesity, Phenotype, RNA, Messenger, Sequence Deletion, Thinness, Young Adult, Physiology, RNA, Messenger/analysis/genetics, Genome-wide association study, HIDDEN-MARKOV MODEL, 0302 clinical medicine, Sequence Deletion/genetics, ddc:576.5, 0303 health sciences, education.field_of_study, Body Height/genetics, Genetic Predisposition to Disease/genetics, [SDV.MHEP.EM]Life Sciences [q-bio]/Human health and pathology/Endocrinology and metabolism, 3. Good health, population characteristics, Chromosomes, Human, Pair 16/genetics, Human, Locus (genetics), Gene Duplication/genetics, Article, 03 medical and health sciences, Genetic, education, SNP GENOTYPING DATA, Thinness/genetics, [SDV.GEN]Life Sciences [q-bio]/Genetics, Pair 16, Case-control study, nutritional and metabolic diseases, social sciences, medicine.disease, DEPENDENT PROBE AMPLIFICATION, Human medicine, Body mass index, 030217 neurology & neurosurgery, Messenger, Obesity/genetics, FAILURE-TO-THRIVE, [SDV.GEN] Life Sciences [q-bio]/Genetics, Head/anatomy & histology, METABOLIC SYNDROME, [SDV.MHEP.EM] Life Sciences [q-bio]/Human health and pathology/Endocrinology and metabolism, 2. Zero hunger, Genetics, Multidisciplinary, TIME QUANTITATIVE PCR, Failure to thrive, medicine.symptom, Underweight, Transcription, geographic locations, Mutation/genetics, Population, Biology, Chromosomes, 150 000 MR Techniques in Brain Function, medicine, Preschool, 030304 developmental biology, COPY NUMBER VARIATION, Mental Disorders/genetics, Energy Metabolism/genetics, RELATIVE QUANTIFICATION, Gene Dosage/genetics, Newborn, BODY-MASS INDEX, CIRCULAR BINARY SEGMENTATION, RNA, Genetics and epigenetic pathways of disease Genomic disorders and inherited multi-system disorders [NCMLS 6], human activities, Developmental Disabilities/genetics
Abstract

To access publisher full text version of this article. Please click on the hyperlink in Additional Links field. Both obesity and being underweight have been associated with increased mortality. Underweight, defined as a body mass index (BMI) ≤ 18.5 kg per m(2) in adults and ≤ -2 standard deviations from the mean in children, is the main sign of a series of heterogeneous clinical conditions including failure to thrive, feeding and eating disorder and/or anorexia nervosa. In contrast to obesity, few genetic variants underlying these clinical conditions have been reported. We previously showed that hemizygosity of a ∼600-kilobase (kb) region on the short arm of chromosome 16 causes a highly penetrant form of obesity that is often associated with hyperphagia and intellectual disabilities. Here we show that the corresponding reciprocal duplication is associated with being underweight. We identified 138 duplication carriers (including 132 novel cases and 108 unrelated carriers) from individuals clinically referred for developmental or intellectual disabilities (DD/ID) or psychiatric disorders, or recruited from population-based cohorts. These carriers show significantly reduced postnatal weight and BMI. Half of the boys younger than five years are underweight with a probable diagnosis of failure to thrive, whereas adult duplication carriers have an 8.3-fold increased risk of being clinically underweight. We observe a trend towards increased severity in males, as well as a depletion of male carriers among non-medically ascertained cases. These features are associated with an unusually high frequency of selective and restrictive eating behaviours and a significant reduction in head circumference. Each of the observed phenotypes is the converse of one reported in carriers of deletions at this locus. The phenotypes correlate with changes in transcript levels for genes mapping within the duplication but not in flanking regions. The reciprocal impact of these 16p11.2 copy-number variants indicates that severe obesity and being underweight could have mirror aetiologies, possibly through contrasting effects on energy balance. Leenaards Foundation Jerome Lejeune Foundation Telethon Action Suisse Foundation Swiss National Science Foundation European Commission 037627 QLG1-CT-2000-01643 Ludwig Institute for Cancer Research Swiss Institute of Bioinformatics Imperial College Department of Medicine Comprehensive Biomedical Research Centre Imperial College Healthcare NHS Trust National Institute for Health Research Wellcome Trust Medical Research Council Instituto de Salud Carlos III (ISCIII)-FIS German Mental Retardation Network German Federal Ministry of Education and Research NGFNplus 01GS08160 European Union PI081714 PS09/01778 201413 245536 info:eu-repo/grantAgreement/EC/FP7/223423 Belgian National Fund for Scientific Research, Flanders Dutch Organisation for Health Research and Development (ZON-MW) 917-86-319 Hersenstichting Nederland (B.B.A.d.V.) Chinese National Natural Science Foundation 81000346 Simons Foundation Autism Research Initiative Autism Speaks NIH GM061354 MH071425 Oesterreichische Nationalbank (OENB) 13059 Children's Tumor Foundation Harvard Medical School Fudan University Chinese National '973' project on Population and Health 2010CB529601 Science and Technology Council of Shanghai 09JC1402400 Michael Smith Foundation for Health CIHR MOP 74502 Estonian Government SF0180142s08 SF0180026s09 SF0180027s10 Helmholtz Zentrum Munich State of Bavaria German National Genome Research Network 01GS0823 German Federal Ministry of Education and Research (BMBF) Munich Center of Health Sciences (MC Health, LMUinnovativ) Genome Canada McLaughlin Centre Academy of Finland 104781 120315 129269 1114194 University Hospital Oulu Biocenter University of Oulu, Finland 75617 NHLBI 5R01HL087679-02 1RL1MH083268-01 NIH/NIMH 5R01MH63706:02 ENGAGE project Medical Research Council, UK G0500539 G0600705 Academy of Finland Biocentrum Helsinki SAF2008-02278 HEALTH-F4-2007-201413

Published
2011

36. Validation of fat mass metrics in pediatric obesity.

Author

Lischka J, Pixner T, Mörwald K, Lauth W, Furthner D, Weghuber D, Gomahr J, Thivel D, Brandtner H, Bergauer M, Forer L, Torbahn G, Forslund A, Ciba I, Manell H, Kullberg J, Anderwald CH, and Bergsten P

Abstract

Introduction Hudda-Index is a prediction model for fat mass (FM) based on simple anthropometric measures., FM is a crucial factor in the development of comorbidities, i.e., type 2 diabetes. Hence, Hudda-Index is a promising tool to facilitate identification of children at risk for metabolic comorbidities. It has been validated against deuterium dilution assessments, however, independent validation against the gold-standard for body composition analysis, magnetic resonance imaging (MRI), is lacking. The aim of this study is to validate FM calculated by Hudda-Index against FM measured by MRI. The secondary aim is to compare Hudda-Index to other anthropometric measures including body mass index (BMI), BMI-standard deviation score (BMI-SDS), waist/hip-ratio, waist circumference (WC) and skinfold thickness. Methods The study cohort consists of 115 individuals between the age of 9 and 15 years, recruited at Paracelsus Medical University Hospital in Salzburg (Austria) and Uppsala University Children's Hospital (Sweden). Anthropometry, blood samples, and oral glucose tolerance tests followed standard procedures. MRI examinations were performed to determine visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Results BMI and WC showed slightly stronger associations with the reference standard VAT (r=0.72 and 0.70, p&lt;0.01, respectively) than Hudda-Index (r= 0.67, p&lt;0.01). There is an almost perfect linear association between BMI and Hudda-Index. Accordingly, BMI and Hudda-Index both showed an acceptable association with cardiometabolic parameters. VAT was strongly associated with markers of liver status (LFF r=0.59, p&lt;0.01) and insulin resistance (HOMA-IR r=0.71, p&lt;0.01) and predicted metabolic dysfunction-associated steatotic liver disease (MASLD). Conclusion BMI, although an imperfect measure, remains the most reliable tool and estimates cardiometabolic risk more reliably than other anthropometry-based measures., (S. Karger AG, Basel.)

Published
2024
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37. Nanopore sequencing with unique molecular identifiers enables accurate mutation analysis and haplotyping in the complex lipoprotein(a) KIV-2 VNTR.

Author

Amstler S, Streiter G, Pfurtscheller C, Forer L, Di Maio S, Weissensteiner H, Paulweber B, Schönherr S, Kronenberg F, and Coassin S

Subjects
Humans, DNA Mutational Analysis methods, Polymorphism, Single Nucleotide, Haplotypes, Minisatellite Repeats, Lipoprotein(a) genetics, Nanopore Sequencing methods
Abstract

Background: Repetitive genome regions, such as variable number of tandem repeats (VNTR) or short tandem repeats (STR), are major constituents of the uncharted dark genome and evade conventional sequencing approaches. The protein-coding LPA kringle IV type-2 (KIV-2) VNTR (5.6 kb per unit, 1-40 units per allele) is a medically highly relevant example with a particularly intricate structure, multiple haplotypes, intragenic homologies, and an intra-VNTR STR. It is the primary regulator of plasma lipoprotein(a) [Lp(a)] concentrations, an important cardiovascular risk factor. Lp(a) concentrations vary widely between individuals and ancestries. Multiple variants and functional haplotypes in the LPA gene and especially in the KIV-2 VNTR strongly contribute to this variance., Methods: We evaluated the performance of amplicon-based nanopore sequencing with unique molecular identifiers (UMI-ONT-Seq) for SNP detection, haplotype mapping, VNTR unit consensus sequence generation, and copy number estimation via coverage-corrected haplotypes quantification in the KIV-2 VNTR. We used 15 human samples and low-level mixtures (0.5 to 5%) of KIV-2 plasmids as a validation set. We then applied UMI-ONT-Seq to extract KIV-2 VNTR haplotypes in 48 multi-ancestry 1000 Genome samples and analyzed at scale a poorly characterized STR within the KIV-2 VNTR., Results: UMI-ONT-Seq detected KIV-2 SNPs down to 1% variant level with high sensitivity, specificity, and precision (0.977 ± 0.018; 1.000 ± 0.0005; 0.993 ± 0.02) and accurately retrieved the full-length haplotype of each VNTR unit. Human variant levels were highly correlated with next-generation sequencing (R 2  = 0.983) without bias across the whole variant level range. Six reads per UMI produced sequences of each KIV-2 unit with Q40 quality. The KIV-2 repeat number determined by coverage-corrected unique haplotype counting was in close agreement with droplet digital PCR (ddPCR), with 70% of the samples falling even within the narrow confidence interval of ddPCR. We then analyzed 62,679 intra-KIV-2 STR sequences and explored KIV-2 SNP haplotype patterns across five ancestries., Conclusions: UMI-ONT-Seq accurately retrieves the SNP haplotype and precisely quantifies the VNTR copy number of each repeat unit of the complex KIV-2 VNTR region across multiple ancestries. This study utilizes the KIV-2 VNTR, presenting a novel and potent tool for comprehensive characterization of medically relevant complex genome regions at scale., (© 2024. The Author(s).)

Published
2024
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38. Incidence of Medication-Related Osteonecrosis of the Jaw in Patients With Breast Cancer During a 20-Year Follow-Up: A Population-Based Multicenter Retrospective Study.

Author

Brunner C, Arvandi M, Marth C, Egle D, Baumgart F, Emmelheinz M, Walch B, Lercher J, Iannetti C, Wöll E, Pechlaner A, Zabernigg A, Volgger B, Castellan M, Andraschofsky OT, Markl A, Hubalek M, Schnallinger M, Puntscher S, Siebert U, Schönherr S, Forer L, Bruckmoser E, and Laimer J

Abstract

Purpose: Medication-related osteonecrosis of the jaw (MRONJ) is one of the most important toxicities of antiresorptive therapy, which is standard practice for patients with breast cancer and bone metastases. However, the population-based incidence of MRONJ is not well established. We therefore performed a retrospective multicenter study to assess the incidence for a whole Austrian federal state (Tyrol)., Materials and Methods: This retrospective multicenter study was conducted between 2000 and 2020 at all nine breast centers across Tyrol, Austria. Using the cancer registry, the total Tyrolean population was screened for all patients with breast cancer. All patients with breast cancer and bone metastases receiving antiresorptive therapy were finally included in the study., Results: From 8,860 patients initially screened, 639 individuals were eligible and included in our study. Patients received antiresorptive therapy once per month without de-escalation of therapy. MRONJ was diagnosed in 56 (8.8%, 95% CI, 6.6 to 11.0) patients. The incidence of MRONJ was 11.6% (95% CI, 8.0 to 15.3) in individuals treated with denosumab only, 2.8% (95% CI, 0.7 to 4.8) in those treated with bisphosphonates only, and 16.3% (95% CI, 8.8 to 23.9) in the group receiving bisphosphonates followed by denosumab. Individuals developed MRONJ significantly earlier when treated with denosumab. Time to MRONJ after treatment initiation was 4.6 years for individuals treated with denosumab only, 5.1 years for individuals treated with bisphosphonates only, and 8.4 years for individuals treated with both consecutively., Conclusion: MRONJ incidence in breast cancer patients with bone metastases was found to be considerably higher, especially for patients receiving denosumab, when compared with available data in the literature. Additionally, patients treated with denosumab developed MRONJ significantly earlier.

Published
2024
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39. Imputation Server PGS: an automated approach to calculate polygenic risk scores on imputation servers.

Author

Forer L, Taliun D, LeFaive J, Smith AV, Boughton AP, Coassin S, Lamina C, Kronenberg F, Fuchsberger C, and Schönherr S

Subjects
Humans, Internet, Genome-Wide Association Study methods, Polymorphism, Single Nucleotide, Genotype, Alleles, Genetic Risk Score, Multifactorial Inheritance genetics, Software, Genetic Predisposition to Disease
Abstract

Polygenic scores (PGS) enable the prediction of genetic predisposition for a wide range of traits and diseases by calculating the weighted sum of allele dosages for genetic variants associated with the trait or disease in question. Present approaches for calculating PGS from genotypes are often inefficient and labor-intensive, limiting transferability into clinical applications. Here, we present 'Imputation Server PGS', an extension of the Michigan Imputation Server designed to automate a standardized calculation of polygenic scores based on imputed genotypes. This extends the widely used Michigan Imputation Server with new functionality, bringing the simplicity and efficiency of modern imputation to the PGS field. The service currently supports over 4489 published polygenic scores from publicly available repositories and provides extensive quality control, including ancestry estimation to report population stratification. An interactive report empowers users to screen and compare thousands of scores in a fast and intuitive way. Imputation Server PGS provides a user-friendly web service, facilitating the application of polygenic scores to a wide range of genetic studies and is freely available at https://imputationserver.sph.umich.edu., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Published
2024
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40. mtDNA-Server 2: advancing mitochondrial DNA analysis through highly parallelized data processing and interactive analytics.

Author

Weissensteiner H, Forer L, Kronenberg F, and Schönherr S

Subjects
Humans, Sequence Analysis, DNA methods, Genome, Mitochondrial, Workflow, High-Throughput Nucleotide Sequencing methods, Internet, Reproducibility of Results, INDEL Mutation, DNA, Mitochondrial genetics, Software
Abstract

Over the past decade, mtDNA-Server established itself as one of the most widely used variant calling web-services for human mitochondrial genomes. The service accepts sequencing data in BAM format and returns an annotated variant analysis report for both homoplasmic and heteroplasmic variants. In this work we present mtDNA-Server 2, which includes several new features highly requested by the community. Most importantly, it includes (a) the integration of a novel variant calling mode that accurately call insertions, deletions and single nucleotide variants at once, (b) the integration of additional quality control and input validation modules, (c) a method to estimate the required coverage to minimize false positives and (d) an interactive analytics dashboard. Furthermore, we migrated the complete analysis workflow to the Nextflow workflow manager for improved parallelization, reproducibility and local execution. Recognizing the importance of insertions and deletions as well as offering novel quality control, validation and reporting features, mtDNA-Server 2 provides researchers and clinicians a new state-of-the-art analysis platform for interpreting mitochondrial genomes. mtDNA-Server 2 is available via mitoverse, our analysis platform that offers a centralized place for mtDNA analysis in the cloud. The web-service, source code and its documentation are freely accessible at https://mitoverse.i-med.ac.at., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Published
2024
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41. Resolving intra-repeat variation in medically relevant VNTRs from short-read sequencing data using the cardiovascular risk gene LPA as a model.

Author

Di Maio S, Zöscher P, Weissensteiner H, Forer L, Schachtl-Riess JF, Amstler S, Streiter G, Pfurtscheller C, Paulweber B, Kronenberg F, Coassin S, and Schönherr S

Subjects
Humans, Genetic Variation, Sequence Analysis, DNA methods, Lipoprotein(a) genetics, Genetic Predisposition to Disease, Minisatellite Repeats, Cardiovascular Diseases genetics
Abstract

Background: Variable number tandem repeats (VNTRs) are highly polymorphic DNA regions harboring many potentially disease-causing variants. However, VNTRs often appear unresolved ("dark") in variation databases due to their repetitive nature. One particularly complex and medically relevant VNTR is the KIV-2 VNTR located in the cardiovascular disease gene LPA which encompasses up to 70% of the coding sequence., Results: Using the highly complex LPA gene as a model, we develop a computational approach to resolve intra-repeat variation in VNTRs from largely available short-read sequencing data. We apply the approach to six protein-coding VNTRs in 2504 samples from the 1000 Genomes Project and developed an optimized method for the LPA KIV-2 VNTR that discriminates the confounding KIV-2 subtypes upfront. This results in an F1-score improvement of up to 2.1-fold compared to previously published strategies. Finally, we analyze the LPA VNTR in > 199,000 UK Biobank samples, detecting > 700 KIV-2 mutations. This approach successfully reveals new strong Lp(a)-lowering effects for KIV-2 variants, with protective effect against coronary artery disease, and also validated previous findings based on tagging SNPs., Conclusions: Our approach paves the way for reliable variant detection in VNTRs at scale and we show that it is transferable to other dark regions, which will help unlock medical information hidden in VNTRs., (© 2024. The Author(s).)

Published
2024
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42. Interactive exploration of adverse events and multimorbidity in CKD.

Author

Steinbrenner I, Kotsis F, Kosch R, Meiselbach H, Bärthlein B, Stockmann H, Lipovsek J, Zacharias HU, Altenbuchinger M, Dienemann T, Wytopil M, Bächle H, Sommerer C, Titze S, Weigel A, Weissensteiner H, Schönherr S, Forer L, Kurz NS, Menne J, Schlieper G, Schneider MP, Schäffner E, Kielstein JT, Sitter T, Floege J, Wanner C, Kronenberg F, Köttgen A, Busch M, Krane V, Schmid M, Eckardt KU, and Schultheiss UT

Abstract

Background and Hypothesis: Persons with chronic kidney disease (CKD) are at increased risk of adverse events, early mortality, and multimorbidity. A detailed overview of adverse event types and rates from a large CKD cohort under regular nephrological care is missing. We generated an interactive tool to enable exploration of adverse events and their combinations in the prospective, observational German CKD (GCKD) study., Methods: The GCKD study enrolled 5217 participants under regular nephrological care with an estimated glomerular filtration rate of 30-60 or >60 mL/min/1.73m2 and an overt proteinuria. Cardio-, cerebro- and peripheral vascular, kidney, infection, and cancer events, as well as deaths were adjudicated following a standard operation procedure. We summarized these time-to-event data points for exploration in interactive graphs within an R shiny app. Multivariable adjusted Cox models for time to first event were fitted. Cumulative incidence functions, Kaplan-Meier curves and intersection plots were used to display main adverse events and their combinations by sex and CKD etiology., Results: Over a median of 6.5 years, 10 271 events occurred in total and 680 participants (13.0%) died while 2947 participants (56.5%) experienced any event. The new publicly available interactive platform enables readers to scrutinize adverse events and their combinations as well as mortality trends as a gateway to better understand multimorbidity in CKD: incident rates per 1000 patient-years varied by event type, CKD etiology, and baseline characteristics. Incidence rates for the most frequent events and their recurrence were 113.6 (cardiovascular), 75.0 (kidney), and 66.0 (infection). Participants with diabetic kidney disease and men were more prone to experiencing events., Conclusion: This comprehensive explorative tool to visualize adverse events (https://gckd.diz.uk-erlangen.de/), their combination, mortality, and multimorbidity among persons with CKD may manifest as a valuable resource for patient care, identification of high-risk groups, health services, and public health policy planning., (© The Author(s) 2024. Published by Oxford University Press on behalf of the ERA.)

Published
2024
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43. Corrigendum to "An Artificial Intelligence Generated Automated Algorithm to Measure Total Kidney Volume in ADPKD" [ Kidney International Reports Volume 9, Issue 2, February 2024, Pages 249-256].

Author

Taylor J, Thomas R, Metherall P, van Gastel M, Cornec-Le Gall E, Caroli A, Furlano M, Demoulin N, Devuyst O, Winterbottom J, Torra R, Perico N, Le Meur Y, Schoenherr S, Forer L, Gansevoort RT, Simms RJ, and Ong ACM

Abstract

[This corrects the article DOI: 10.1016/j.ekir.2023.10.029.]., (Crown Copyright © 2024 Published by Elsevier Inc. on behalf of the International Society of Nephrology.)

Published
2024
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44. Sex and statin-related genetic associations at the PCSK9 gene locus: results of genome-wide association meta-analysis.

Author

Pott J, Kheirkhah A, Gadin JR, Kleber ME, Delgado GE, Kirsten H, Forer L, Hauck SM, Burkhardt R, Scharnagl H, Loeffler M, März W, Thiery J, Gieger C, Peters A, Silveira A, Hooft FV, Kronenberg F, and Scholz M

Subjects
Male, Humans, Female, Proprotein Convertase 9 genetics, Proprotein Convertase 9 metabolism, Genome-Wide Association Study, Cholesterol, LDL genetics, Oxidoreductases, N-Demethylating, Jumonji Domain-Containing Histone Demethylases, Hydroxymethylglutaryl-CoA Reductase Inhibitors
Abstract

Background: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key player of lipid metabolism with higher plasma levels in women throughout their life. Statin treatment affects PCSK9 levels also showing evidence of sex-differential effects. It remains unclear whether these differences can be explained by genetics., Methods: We performed genome-wide association meta-analyses (GWAS) of PCSK9 levels stratified for sex and statin treatment in six independent studies of Europeans (8936 women/11,080 men respectively 14,825 statin-free/5191 statin-treated individuals). Loci associated in one of the strata were tested for statin- and sex-interactions considering all independent signals per locus. Independent variants at the PCSK9 gene locus were then used in a stratified Mendelian Randomization analysis (cis-MR) of PCSK9 effects on low-density lipoprotein cholesterol (LDL-C) levels to detect differences of causal effects between the subgroups., Results: We identified 11 loci associated with PCSK9 in at least one stratified subgroup (p < 1.0 × 10 -6 ), including the PCSK9 gene locus and five other lipid loci: APOB, TM6SF2, FADS1/FADS2, JMJD1C, and HP/HPR. The interaction analysis revealed eight loci with sex- and/or statin-interactions. At the PCSK9 gene locus, there were four independent signals, one with a significant sex-interaction showing stronger effects in men (rs693668). Regarding statin treatment, there were two significant interactions in PCSK9 missense mutations: rs11591147 had stronger effects in statin-free individuals, and rs11583680 had stronger effects in statin-treated individuals. Besides replicating known loci, we detected two novel genome-wide significant associations: one for statin-treated individuals at 6q11.1 (within KHDRBS2) and one for males at 12q24.22 (near KSR2/NOS1), both with significant interactions. In the MR of PCSK9 on LDL-C, we observed significant causal estimates within all subgroups, but significantly stronger causal effects in statin-free subjects compared to statin-treated individuals., Conclusions: We performed the first double-stratified GWAS of PCSK9 levels and identified multiple biologically plausible loci with genetic interaction effects. Our results indicate that the observed sexual dimorphism of PCSK9 and its statin-related interactions have a genetic basis. Significant differences in the causal relationship between PCSK9 and LDL-C suggest sex-specific dosages of PCSK9 inhibitors., (© 2024. The Author(s).)

Published
2024
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46. Apolipoprotein A-IV concentrations and cancer in a large cohort of chronic kidney disease patients: results from the GCKD study.

Author

Kollerits B, Gruber S, Steinbrenner I, Schwaiger JP, Weissensteiner H, Schönherr S, Forer L, Kotsis F, Schultheiss UT, Meiselbach H, Wanner C, Eckardt KU, and Kronenberg F

Subjects
Humans, Prospective Studies, Cohort Studies, Proteomics, Apolipoproteins A, Glomerular Filtration Rate, Risk Factors, Renal Insufficiency, Chronic complications, Renal Insufficiency, Chronic epidemiology, Neoplasms complications, Neoplasms epidemiology
Abstract

Background: Chronic kidney disease (CKD) is highly connected to inflammation and oxidative stress. Both favour the development of cancer in CKD patients. Serum apolipoprotein A-IV (apoA-IV) concentrations are influenced by kidney function and are an early marker of kidney impairment. Besides others, it has antioxidant and anti-inflammatory properties. Proteomic studies and small case-control studies identified low apoA-IV as a biomarker for various forms of cancer; however, prospective studies are lacking. We therefore investigated whether serum apoA-IV is associated with cancer in the German Chronic Kidney Disease (GCKD) study., Methods: These analyses include 5039 Caucasian patients from the prospective GCKD cohort study followed for 6.5 years. Main inclusion criteria were an eGFR of 30-60 mL/min/1.73m 2 or an eGFR > 60 mL/min/1.73m 2 in the presence of overt proteinuria., Results: Mean apoA-IV concentrations of the entire cohort were 28.9 ± 9.8 mg/dL (median 27.6 mg/dL). 615 patients had a history of cancer before the enrolment into the study. ApoA-IV concentrations above the median were associated with a lower odds for a history of cancer (OR = 0.79, p = 0.02 when adjusted age, sex, smoking, diabetes, BMI, albuminuria, statin intake, and eGFR creatinine ). During follow-up 368 patients developed an incident cancer event and those with apoA-IV above the median had a lower risk (HR = 0.72, 95%CI 0.57-0.90, P = 0.004). Finally, 62 patients died from such an incident cancer event and each 10 mg/dL higher apoA-IV concentrations were associated with a lower risk for fatal cancer (HR = 0.62, 95%CI 0.44-0.88, P = 0.007)., Conclusions: Our data indicate an association of high apoA-IV concentrations with reduced frequencies of a history of cancer as well as incident fatal and non-fatal cancer events in a large cohort of patients with CKD., (© 2024. The Author(s).)

Published
2024
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47. Performing highly parallelized and reproducible GWAS analysis on biobank-scale data.

Author

Schönherr S, Schachtl-Riess JF, Di Maio S, Filosi M, Mark M, Lamina C, Fuchsberger C, Kronenberg F, and Forer L

Abstract

Genome-wide association studies (GWAS) are transforming genetic research and enable the detection of novel genotype-phenotype relationships. In the last two decades, over 60 000 genetic associations across thousands of traits have been discovered using a GWAS approach. Due to increasing sample sizes, researchers are increasingly faced with computational challenges. A reproducible, modular and extensible pipeline with a focus on parallelization is essential to simplify data analysis and to allow researchers to devote their time to other essential tasks. Here we present nf-gwas, a Nextflow pipeline to run biobank-scale GWAS analysis. The pipeline automatically performs numerous pre- and post-processing steps, integrates regression modeling from the REGENIE package and supports single-variant, gene-based and interaction testing. It includes an extensive reporting functionality that allows to inspect thousands of phenotypes and navigate interactive Manhattan plots directly in the web browser. The pipeline is tested using the unit-style testing framework nf-test, a crucial requirement in clinical and pharmaceutical settings. Furthermore, we validated the pipeline against published GWAS datasets and benchmarked the pipeline on high-performance computing and cloud infrastructures to provide cost estimations to end users. nf-gwas is a highly parallelized, scalable and well-tested Nextflow pipeline to perform GWAS analysis in a reproducible manner., (© The Author(s) 2024. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

Published
2024
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48. Nuclear and mitochondrial genetic variants associated with mitochondrial DNA copy number.

Author

Koller A, Filosi M, Weissensteiner H, Fazzini F, Gorski M, Pattaro C, Schönherr S, Forer L, Herold JM, Stark KJ, Döttelmayer P, Hicks AA, Pramstaller PP, Würzner R, Eckardt KU, Heid IM, Fuchsberger C, Lamina C, and Kronenberg F

Subjects
Humans, Genome-Wide Association Study, Mitochondria genetics, Genetic Loci, Gasdermins, DNA, Mitochondrial genetics, DNA Copy Number Variations genetics
Abstract

Mitochondrial DNA copy number (mtDNA-CN) is a biomarker for mitochondrial dysfunction associated with several diseases. Previous genome-wide association studies (GWAS) have been performed to unravel underlying mechanisms of mtDNA-CN regulation. However, the identified gene regions explain only a small fraction of mtDNA-CN variability. Most of this data has been estimated from microarrays based on various pipelines. In the present study we aimed to (1) identify genetic loci for qPCR-measured mtDNA-CN from three studies (16,130 participants) using GWAS, (2) identify potential systematic differences between our qPCR derived mtDNA-CN measurements compared to the published microarray intensity-based estimates, and (3) disentangle the nuclear from mitochondrial regulation of the mtDNA-CN phenotype. We identified two genome-wide significant autosomal loci associated with qPCR-measured mtDNA-CN: at HBS1L (rs4895440, p = 3.39 × 10 -13 ) and GSDMA (rs56030650, p = 4.85 × 10 -08 ) genes. Moreover, 113/115 of the previously published SNPs identified by microarray-based analyses were significantly equivalent with our findings. In our study, the mitochondrial genome itself contributed only marginally to mtDNA-CN regulation as we only detected a single rare mitochondrial variant associated with mtDNA-CN. Furthermore, we incorporated mitochondrial haplogroups into our analyses to explore their potential impact on mtDNA-CN. However, our findings indicate that they do not exert any significant influence on our results., (© 2024. The Author(s).)

Published
2024
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49. Meta-GWAS on PCSK9 concentrations reveals associations of novel loci outside the PCSK9 locus in White populations.

Author

Kheirkhah A, Schachtl-Riess JF, Lamina C, Di Maio S, Koller A, Schönherr S, Coassin S, Forer L, Sekula P, Gieger C, Peters A, Köttgen A, Eckardt KU, and Kronenberg F

Subjects
Humans, Proprotein Convertase 9 genetics, Genome-Wide Association Study, White People, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Coronary Artery Disease genetics
Abstract

Background and Aims: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of lipid homeostasis. A few earlier genome-wide association studies (GWAS) investigated genetic variants associated with circulating PCSK9 concentrations. However, uncertainty remains about some of the genetic loci discovered beyond the PCSK9 locus. By conducting the largest PCSK9 meta-analysis of GWAS (meta-GWAS) so far, we aimed to identify novel loci and validate the previously reported loci that regulate PCSK9 concentrations., Methods: We performed GWAS for PCSK9 concentrations in two large cohorts (GCKD (n = 4,963) and KORA F3 (n = 2,895)). These were meta-analyzed with previously published data encompassing together 20,579 individuals. We further conducted a second meta-analysis in statin-naïve individuals (n = 15,390). A genetic risk score (GRS) was constructed on PCSK9-increasing SNPs and assessed its impact on the risk for coronary artery disease (CAD) in 394,943 statin-naïve participants (17,077 with events) of the UK Biobank by performing CAD-free survival analysis., Results: Nine loci were genome-wide significantly associated with PCSK9 concentrations. These included the previously described PCSK9, APOB, KCNA1/KCNA5, and TM6SF2/SUGP1 loci. All imputed SNPs in the PCSK9 locus account for ∼15% of variance of PCSK9 concentrations. We further identified FADS2 as a novel locus that was also found in statin-naïve participants. All imputed SNPs within the FADS2 locus explain ∼1.2% of variance of PCSK9 concentrations. Additionally, four further loci (a region on chromosome 5, SDK1, SPATA16 and HPR) were genome-wide significant in either the main model or the statin-naïve subset. The linear increase in a PCSK9 genetic risk score was associated with 1.41-fold (95%CI 1.16-1.72, p < 0.001) higher risk for incident CAD., Conclusions: We identified five novel loci (FADS2, SPATA16, SDK1, HPR and a region on chromosome 5) for PCSK9 concentrations that would require further research. Additionally, we confirm the genome-wide significant loci that were previously detected., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2023
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50. An Artificial Intelligence Generated Automated Algorithm to Measure Total Kidney Volume in ADPKD.

Author

Taylor J, Thomas R, Metherall P, van Gastel M, Cornec-Le Gall E, Caroli A, Furlano M, Demoulin N, Devuyst O, Winterbottom J, Torra R, Perico N, Le Meur Y, Schoenherr S, Forer L, Gansevoort RT, Simms RJ, and Ong ACM

Abstract

Introduction: Accurate tools to inform individual prognosis in patients with autosomal dominant polycystic kidney disease (ADPKD) are lacking. Here, we report an artificial intelligence (AI)-generated method for routinely measuring total kidney volume (TKV)., Methods: An ensemble U-net algorithm was created using the nnUNet approach. The training and internal cross-validation cohort consisted of all 1.5T magnetic resonance imaging (MRI) data acquired using 5 different MRI scanners (454 kidneys, 227 scans) in the CYSTic consortium, which was first manually segmented by a single human operator. As an independent validation cohort, we utilized 48 sequential clinical MRI scans with reference results of manual segmentation acquired by 6 individual analysts at a single center. The tool was then implemented for clinical use and its performance analyzed., Results: The training or internal validation cohort was younger (mean age 44.0 vs. 51.5 years) and the female-to-male ratio higher (1.2 vs. 0.94) compared to the clinical validation cohort. The majority of CYSTic patients had PKD1 mutations (79%) and typical disease (Mayo Imaging class 1, 86%). The median DICE score on the clinical validation data set between the algorithm and human analysts was 0.96 for left and right kidneys with a median TKV error of -1.8%. The time taken to manually segment kidneys in the CYSTic data set was 56 (±28) minutes, whereas manual corrections of the algorithm output took 8.5 (±9.2) minutes per scan., Conclusion: Our AI-based algorithm demonstrates performance comparable to manual segmentation. Its rapidity and precision in real-world clinical cases demonstrate its suitability for clinical application., (Crown Copyright © 2023 Published by Elsevier Inc. on behalf of the International Society of Nephrology.)

Published
2023
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