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This collection contains original research articles, review articles and case reports published in local and international peer reviewed journals by the staff members of the Faculty of Medicine

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The adaptation, implementation, and performance evaluation of intake24, a digital 24-h dietary recall tool for South asian populations: the South asia biobank
(Elsevier Inc, 2025-01) Bhagtani, D.; Amoutzopoulos, B.; Steer, T.; Collins, D.; Abraham, S.; Holmes, B.A.; Rai, B.K.; Pradeepa, R.; Mahmood, S.; Shamim, A.A.; Mathur, P.; Athauda, L.; De Silva, L.; Khawaja, K.I.; Jha, V.; Kasturiratne, A.; Katulanda, P.; Mridha, M.K.; Anjana, R.M.; Chambers, J.C.; Page, P.; Forouhi, N.G.
BACKGROUND South Asia's diverse food supply, food preparations, and eating behaviors require dietary instruments that reflect the consumption patterns of South Asians to enable context specific dietary assessment. Such instruments are not readily available for detailed dietary assessment at scale in South Asia.OBJECTIVES We describe the adaptation, implementation, and performance evaluation of Intake24, an open-source digital 24-h dietary recall tool, for dietary assessment in South Asia.METHODS We adapted Intake24 for dietary assessment in the South Asia Biobank (SAB), a large population-based study in Bangladesh, India, Pakistan, and Sri Lanka. Intake24 adaptation encompassed the development of a South Asian food database with commonly consumed foods, linked with corresponding portion sizes, food probes, and nutrient information. Trained interviewers conducted the 24-h recalls. Performance of Intake24 was evaluated in 29,113 South Asian adults.RESULTS The South Asia Intake24 food database included 2283 items and demonstrated good coverage of foods consumed across SAB regions. Median recall completion time was 13 min. Quality control metrics showed 99% of recalls included >8 items and 8% had missing foods. Median energy intake was higher in younger individuals compared to older, and in males compared to females. Underweight participants reported lower energy intake, with no discernible difference across other BMI categories.CONCLUSIONS Intake24 enables comprehensive dietary assessment in regions of South Asia and will facilitate the analysis of dietary patterns, food and nutrient intake, and their relationship with health outcomes among South Asians.
Smokeless and combustible tobacco use among 148,944 South Asian adults: a cross-sectional study of South Asia Biobank
(Springer, 2023) Xie, W.; Mridha, M.K.; Gupta, A.; Kusuma, D.; Butt, A.M.; Hasan, M.; Brage, S.; Loh, M.; Khawaja, K.I.; Pradeepa, R.; Jha, V.; Kasturiratne, A.; Katulanda, P.; Anjana, R.M.; Chambers, J.C.
INTRODUCTION Tobacco use, in both smoking and smokeless forms, is highly prevalent among South Asian adults. The aims of the study were twofold: (1) describe patterns of SLT and combustible tobacco product use in four South Asian countries stratified by country and sex, and (2) assess the relationships between SLT and smoking intensity, smoking quit attempts, and smoking cessation among South Asian men. METHODS Data were obtained from South Asia Biobank Study, collected between 2018 and 2022 from 148,944 men and women aged 18 years and above, living in Bangladesh, India, Pakistan, or Sri Lanka. Mixed effects multivariable logistic and linear regression were used to quantify the associations of SLT use with quit attempt, cessation, and intensity. RESULTS Among the four South Asian countries, Bangladesh has the highest rates of current smoking (39.9% for male, 0.4% for female) and current SLT use (24.7% for male and 23.4% for female). Among male adults, ever SLT use was associated with a higher odds of smoking cessation in Bangladesh (OR, 2.88; 95% CI, 2.65, 3.13), India (OR, 2.02; 95% CI, 1.63, 2.50), and Sri Lanka (OR, 1.36; 95% CI, 1.14, 1.62). Ever SLT use and current SLT use was associated with lower smoking intensity in all countries. CONCLUSIONS In this large population-based study of South Asian adults, rates of smoking and SLT use vary widely by country and gender. Men who use SLT products are more likely to abstain from smoking compared with those who do not.
Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis
(BioMed Central Ltd, 2022) Kanoni, S.; Graham, S.E.; Wang, Y.; Surakka, I.; Ramdas, S.; Zhu, X.; Clarke, S.L.; Bhatti, K.F.; Vedantam, S.; Winkler, T.W.; Locke, A.E.; Marouli, E.; Zajac, G.J.M.; Wu, K.H.; Ntalla, I.; Hui, Q.; Klarin, D.; Hilliard, A.T.; Wang, Z.; Xue, C.; Thorleifsson, G.; Helgadottir, A.; Gudbjartsson, D.F.; Holm, H.; Olafsson, I.; Hwang, M.Y.; Han, S.; Akiyama, M.; Sakaue, S.; Terao, C.; Kanai, M.; Zhou, W.; Brumpton, B.M.; Rasheed, H.; Havulinna, A.S.; Veturi, Y.; Pacheco, J.A.; Rosenthal, E.A.; Lingren, T.; Feng, Q.; Kullo, I.J.; Narita, A.; Takayama, J.; Martin, H.C.; Hunt, K.A.; Trivedi, B.; Haessler, J.; Giulianini, F.; Bradford, Y.; Miller, J.E.; Campbell, A.; Lin, K.; Lin, K.; Millwood, I.Y.; Rasheed, A.; Hindy, G.; Faul, J.D.; Zhao, W.; Weir, D.R.; Turman, C.; Huang, H.; Graff, M.; Choudhury, A.; Sengupta, D.; 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.; Wood, A.R.; Ji, Y.; Gao, Z.; Haworth, S.; Yousri, N.A.; Mitchell, R.E.; Chai, J.F.; Aadahl, M.; Bjerregaard, A.A.; Yao, J.; Manichaikul, A.; Hwu, C.M.; Hung, Y.J.; Warren, H.R.; Ramirez, J.; Bork-Jensen, J.; Kårhus, L.L.; Goel, A.; Sabater-Lleal, M.; Noordam, R.; Mauro, P.; Matteo, F.; McDaid, A.F.; Marques-Vidal, P.; Wielscher, M.; Trompet, S.; Sattar, N.; Møllehave, L.T.; Munz, M.; Zeng, L.; Huang, J.; Yang, B.; Poveda, A.; Kurbasic, A.; Lamina, C.; Forer, L.; Scholz, M.; Galesloot, T.E.; Bradfield, J.P.; Ruotsalainen, S.E.; Daw, E.; Zmuda, J.M.; Mitchell, J.S.; Fuchsberger, C.; Christensen, H.; Brody, J.A.; Vazquez-Moreno, M.; Feitosa, M.F.; Wojczynski, M.K.; Wang, Z.; Preuss, M.H.; Mangino, M.; Christofidou, P.; Verweij, N.; Benjamins, J.W.; Engmann, J.; Tsao, N.L.; Verma, A.; 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.; Demirkan, A.; Leonard, H.L.; Marten, J.; Frank, M.; Schmidt, B.; Smyth, L.J.; Cañadas-Garre, M.; Wang, C.; Nakatochi, M.; Wong, A.; Hutri-Kähönen, N.; Lyssenko, V.; Fernandez-Lopez, J.C.; Huerta-Chagoya, A.; Xia, R.; Sim, X.; Nongmaithem, S.S.; Bayyana, S.; Stringham, H.M.; Irvin, M.R.; Oldmeadow, C.; Kim, H.N.; Ryu, S.; Timmers, P,R,H,J,; Arbeeva, L.; Dorajoo, R.; Lange, L.A.; Prasad, G.; Lorés-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.; Chen, S.; Liu, F.; Yang, J.; Kentistou, K.A.; Banas, B.; Nardone, G.G.; Meidtner, K.; Bielak, L.F.; Smith, J.A.; Hebbar, P.; Farmaki, A.E.; Hofer, E.; Lin, M.; Concas, M.P.; Vaccargiu, S.; van der Most, P.J.; Pitkänen, N.; Cade, B.E.; van der Laan, S.W.; Chitrala, K.N.; Weiss, S.; Bentley, A.R.; Doumatey, A.P.; Adeyemo, A.A.; Lee, J.Y.; Petersen, E.R.B.; Nielsen, A.A.; Choi, H.S.; Nethander, M.; Freitag-Wolf, S.; Southam, L.; Rayner, N.W.; Wang, C.A.; Lin, S.Y.; Wang, J.S.; Couture, C.; Lyytikäinen, L.P.; Nikus, K.; Cuellar-Partida, G.; Vestergaard, H.; Hidalgo, B.; Giannakopoulou, O.; Cai, Q.; Obura, M.O.; van Setten, J.; Li, X.; Liang, J.; Tang, H.; Terzikhan, N.; Shin, J.H.; Jackson, R.D.; Reiner, A.P.; Martin, L.W.; Chen, Z.; Li, L.; Kawaguchi, T.; Thiery, J.; Bis, J.C.; Launer, L.J.; Li, H.; Nalls, M.A.; Raitakari, O.T.; Ichihara, S.; Wild, S.H.; Nelson, C.P.; Campbell, H.; Jäger, S.; Nabika, T.; Al-Mulla, F.; Niinikoski, H.; Braund, P.S.; Kolcic, I.; Kovacs, P.; Giardoglou, T.; Katsuya, T.; de Kleijn, D.; de Borst, G.J.; Kim, E.K.; Adams, H.H.H.; Ikram, M.A.; Zhu, X.; 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.; Kähönen, M.; Pérusse, L.; Bouchard, C.; Tönjes, A.; Chen, Y.I.; Pennell, C.E.; Mori, T.A.; Lieb, W.; Franke, A.; Ohlsson, C.; Mellström, D.; Cho, Y.S.; Lee, H.; Yuan, J.M.; Koh, W.P.; Rhee, S.Y.; Woo, J.T.; Heid, I.M.; Stark, K.J.; Zimmermann, M.E.; Völzke, 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.; Bandinelli, S.; Dedoussis, G.; Thanaraj, T.A.; Kardia, S.L.R.; Peyser, P.A.; Kato, N.; Schulze, M.B.; Girotto, G.; Böger, C.A.; Jung, B.; 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.; Tusié-Luna, T.; Aguilar-Salinas, C.A.; Adair, L.S.; Bechayda, S.A.; de Silva, H.J.; Wickremasinghe, A.R.; Krauss, R.M.; Wu, J.Y.; Zheng, W.; 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.; Hunt, S.C.; Walker, M.; Koistinen, H.A.; Chandak, G.R.; Mercader, J.M.; Costanzo, M.C.; Jang, D.; Burtt, N.P.; Villalpando, C.G.; Orozco, L.; Fornage, M.; Tai, E.; van Dam, R.M.; Lehtimäki, T.; Chaturvedi, N.; Yokota, M.; Liu, J.; Reilly, D.F.; McKnight, A.J.; Kee, F.; Jöckel, K.H.; McCarthy, M.I.; Palmer, C.N.A.; Vitart, V.; Hayward, C.; Simonsick, E.; van Duijn, C.M.; Jin, Z.B.; Qu, J.; Hishigaki, H.; Lin, X.; März, W.; Gudnason, V.; Tardif, J.C.; Lettre, G.; 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.; Parra, E.J.; Cruz, M.; Psaty, B.M.; Brandslund, I.; Pramstaller, P.P.; Rotimi, C.N.; Christensen, K.; Ripatti, S.; Widén, 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.; Männikkö, M.; Jarvelin, M.R.; Kutalik, Z.; Francesco, C.; Mook-Kanamori, D.O.; van Dijk, K.W.; Watkins, H.; Strachan, D.P.; Grarup, N.; Sever, P.; Poulter, N.; Chuang, L.M.; Rotter, J.I.; Dantoft, T.M.; Karpe, F.; Neville, M.J.; Timpson, N.J.; Cheng, C.Y.; Wong, T.Y.; Khor, C.C.; Li, H.; Sabanayagam, C.; Sabanayagam, C.; Peters, A.; Gieger, C.; Hattersley, A.T.; Pedersen, N.L.; Magnusson, P.K.E.; Boomsma, D.I.; Willemsen, A.H.M.; Cupples, L.; 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.; Hazelhurst, S.; Ramsay, M.; 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.; Baras, A.; Justice, A.E.; Buring, J.E.; Ridker, P.M.; Chasman, D.I.; Kooperberg, C.; Tamiya, G.; Yamamoto, M.; van Heel, D.A.; Trembath, R.C.; Wei, W.Q.; Jarvik, G.P.; Namjou, B.; Hayes, M.G.; Ritchie, M.D.; Jousilahti, P.; Salomaa, V.; Hveem, K.; Åsvold, B.O.; Kubo, M.; Kamatani, Y.; Okada, Y.; Murakami, Y.; Kim, B.J.; Thorsteinsdottir, U.; Stefansson, K.; Zhang, J.; Chen, Y.; 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.W.F.; Frayling, T.M.; Hirschhorn, J.N.; Kathiresan, S.; Mohlke, K.L.; Sun, Y.V.; Morris, A.P.; Boehnke, M.; Brown, C.D.; Natarajan, P.; Deloukas, P.; Willer, C.J.; Assimes, T.L.; Peloso, G.M.
BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
A saturated map of common genetic variants associated with human height
(Nature Publishing Group, 2022) 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, S.H.; 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.; Chen, C.H.; 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.; Gorski, M.; Grove, J.; Guo, X.; Gustafsson, S.; Haessler, J.; Hansen, T.F.; Havulinna, A.S.; Haworth, S.J.; He, J.; Heard-Costa, N.; Hebbar, P.; Hindy, G.; Ho, Y.A.; Hofer, E.; Holliday, E.; Horn, K.; Hornsby, W.E.; Hottenga, J.J.; Huang, H.; Huang, J.; Huerta-Chagoya, A.; Huffman, J.E.; Hung, Y.J.; Huo, S.; Hwang, M.Y.; Ha, H.; Ikeda, D.D.; Isono, M.; Jackson, A.U.; Jäger, S.; Jansen, I.E.; Johansson, I.; Jonas, J.B.; Jonsson, A.; Jørgensen, T.; Kalafati, I.P.; Kanai, M.; Kanoni, S.; Kårhus, L.L.; Kasturiratne, A.; Katsuya, T.; Kawaguchi, T.; Kember, R.L.; Kentistou, K.A.; Kim, H.N.; Kim, Y.J.; Kleber, M.E.; Knol, M.J.; Kurbasic, A.; Lauzon, M.; Le, P.; Lea, R.; Lee, J.Y.; Leonard, H.L.; Li, S.A.; Li, X.; Li, X.; Liang, J.; Lin, H.; Lin, S.Y.; Liu, J.; Liu, X.; Lo, K.S.; Long, J.; Lores-Motta, L.; Luan, J.; Lyssenko, V.; Lyytikäinen, L.P.; Mahajan, A.; Mamakou, V.; Mangino, M.; Manichaikul, A.; Marten, J.,; Mattheisen, M.; Mavarani, L.; McDaid, A.F.; Meidtner, K.; Melendez, T.L.; Mercader, J.M.; Milaneschi, Y.; Miller, J.E.; Millwood, I.Y.; Mishra, P.P.; Mitchell, R.E.; Møllehave, L.T.; Morgan, A.; Mucha, S.; Munz, M.; Nakatochi, M.; Nelson, C.P.; Nethander, M.; Nho, C.W.; Nielsen, A.A.; Nolte, I.M.; Nongmaithem, S.S.; Noordam, R.; Ntalla, I.; Nutile, T.; Pandit, A.; Christofidou, P.; Pärna, K.; Pauper, M.; Petersen, E.R.B.; Petersen, L.V.; Pitkänen, N.; Polašek, O.; Poveda, A.; Preuss, M.H.; Pyarajan, S.; Raffield, L.M.; Rakugi, H.; Ramirez, J.; Rasheed, A.; Raven, D.; Rayner, N.W.; Riveros, C.; Rohde, R.; Ruggiero, D.; Ruotsalainen, S.E.; Ryan, K.A.; Sabater-Lleal, M.; Saxena, R.; Scholz, M.; Sendamarai, A.; Shen, B.; Shi, J.; Shin, J.H.; Sidore, C.; Sitlani, C.M.; Slieker, R.C.; Smit, R.A.J.; Smith, A.V.; Smith, J.A.; Smyth, L.J.; Southam, L.; Steinthorsdottir, V.; Sun, L.; Takeuchi, F.; Tallapragada, D.S.P.; Taylor, K.D.; Tayo, B.O.; Tcheandjieu, C.; Terzikhan, N.; Tesolin, P.; Teumer, A.; Theusch, E.; Thompson, D.J.; Thorleifsson, G.; Timmers, P.R.H.J.; Trompet, S.; Turman, C.; Vaccargiu, S.; van der Laan, S.W.; van der Most, P.J.; van Klinken, J.B.; van Setten, J.; Verma, S.S.; Verweij, N.; Veturi, Y.; Wang, C.A.; Wang, C.; Wang, L.; Wang, Z.; Warren, H.R.; Bin Wei, W.; Wickremasinghe, A.R.; Wielscher, M.; Wiggins, K.L.; Winsvold, B.S.; Wong, A.; Wu, Y.; Wuttke, M.; Xia, R.; Xie, T.; Yamamoto, K.; Yang, J.; Yao, J.; Young, H.; Yousri, N.A.; Yu, L.; Zeng, L.; Zhang, W.; Zhang, X.; Zhao, J.H.; Zhao. W.; Zhou, W.; Zimmermann, M.E.; Zoledziewska, M.; Adair, L.S.; Adams, H.H.H.; Aguilar-Salinas, C.A.; Al-Mulla, F.; Arnett, D.K.; Arnett, D.K.; Asselbergs, F.W.; Åsvold, B.O.; Attia, J.; Banas, B.; Bandinelli, S.; Bennett D.A.; Bergler, T.; Bharadwaj, D.; Biino, G.; Bisgaard, H.; Boerwinkle, E.; Böger, C.A.; Bønnelykke, K.; Boomsma, D.I.; Børglum, A.D.; Borja, J.B.; Bouchard, C.; Bowden, D.W.; Brandslund, I.; Brumpton, B.; Buring, J.E.; Caulfield, M.J.; Chambers, J.C.; Chandak, G.R.; Chanock, S.J.; Chaturvedi, N.; Chen, Y.I.; Chen, Z.; Cheng, C.Y.; Christophersen, I.E.; Ciullo, M.; Cole, J.W.; Collins, F.S.; Cooper, R.S.; Cruz, M.; Cucca, F.; Cupples, L.A.; Cutler, M.J.; Damrauer, S.M.; Dantoft, T.M.; de Borst, G.J.; de Groot, L.C.P.G.M.; de Jager, P.L.; de Kleijn, D.P.V.; de Silva, H.J.; Dedoussis, G.V.; den Hollander, A.I.; Du, S.; Easton, D.F.; Elders, P.J.M.; Eliassen, A.H.; Ellinor, P.T.; Elmståhl, S.; Erdmann, J.; Evans, M.K.; Fatkin, D.; Feenstra, B.; Feitosa, M.F.; Ferrucci, L.; Ford, I.; Fornage, M.; Franke, A.; Franks, P.W.; Freedman, B.I.; Gasparini, P.; Gieger, C.; Girotto, G.; Goddard, M.E.; Golightly, Y.M.; Gonzalez-Villalpando. C.; Gordon-Larsen, P.; Grallert, H.; Grant, S.F.A.; Grarup, N.; Griffiths, L.; Gudnason, V.; Haiman, C.; Hakonarson, H.; Hansen, T.; Hartman, C.A.; Hattersley, A.T.; Hayward, C.; Heckbert, S.R.; Heng, C.K.; Hengstenberg, C.; Hewitt, A.W.; Hishigaki, H.; Hoyng, C.B.; Huang, P.L.; Huang, W.; Hunt, S.C.; Hveem, K.; Hyppönen, E.; Iacono, W.G.; Ichihara, S.; Ikram, M.A.; Isasi, C.R.; Jackson, R.D.; Jarvelin, M.R.; Jin, Z.B.; Jöckel, K.H.; Joshi, P.K.; Jousilahti, P.; Jukema, J.W.; Kähönen, M.; Kamatani, Y.; Kang, K.D.; Kaprio, J.; Kardia, S.L.R.; Karpe, F.; Kato, N.; Kee, F.; Kessler, T.; Khera, A.V.; Khor, C.C.; Kiemeney, L.A.L.M.; Kim, B.J.; Kim, E.K.; Kim, H.L.; Kirchhof, P.; Kivimaki, M.; Koh, W.P.; Koistinen, H.A.; Kolovou, G.D.; Kooner, J.S.; Kooperberg, C.; Köttgen, A.; Kovacs, P.; Kraaijeveld, A.; Kraft, P.; Krauss, R.M.; Kumari, M.; Kutalik, Z.; Laakso, M.; Lange, L.A.; Langenberg, C.; Launer, L.J.; Le Marchand, L.; Lee, H.; Lee, N.R.; Lehtimäki, T.; Li, H.; Li, L.; Lieb, W.; Lin, X.; Lind, L.; Linneberg, A.; Liu, C.T.; Liu, J.; Loeffler, M.; London, B.; Lubitz, S.A.; Lye, S.J.; Mackey, D.A.; Mägi, R.; Magnusson, P.K.E.; Marcus, G.M.; Vidal, P.M.; Martin, N.G.; Martin, N.G.; Lieb, W.; Lin, X.; Lind, L.; Linneberg, A.; Liu, C.T.; Liu, J.; Loeffler, M.; London, B.; Lubitz, S.A.; Lye, S.J.; Mackey, D.A.; Mägi, R.; Mägi, R.; Magnusson, P.K.E.; Marcus, G.M.; Vidal, P.M.; Martin, N.G.; März, W.; Matsuda, F.; McGarrah, R.W.; McGue, M.; McKnight, A.J.; Medland, S.E.; Mellström, D.; Metspalu, A.; Mitchell, B.D.; Mitchell, P.; Mook-Kanamori, D.O.; Morris, A.D.; Mucci, L.A.; Munroe, P.B.; Nalls, M.A.; Nazarian, S.; Nelson, A.E.; Neville, M.J.; Newton-Cheh, C.; Nielsen, C.S.; Nöthen, M.M.; Ohlsson, C.; Oldehinkel, A.J.; Oldehinkel, A.J.; Orozco, L.; Pahkala, K.; Pajukanta, P.; Palmer, C.N.A.; Parra, E.J.; Pattaro, C.; Pedersen, O.; Pennell, C.E.; Penninx, B.W.J.H.; Perusse, L.; Peters, A.; Peyser, P.A.; Porteous, D.J.; Posthuma, D.; Power, C.; Pramstaller, P.P.; Province, M.A.; Qi, Q.; Qu, J.; Rader, D.J.; Raitakari, O.T.; Ralhan, S.; Rallidis, L.S.; Rao, D.C.; Redline, S.; Reilly, D.F.; Reiner, A.P.; Rhee, S.Y.; Ridker, P.M.; Rienstra, M.; Ripatti, S.; Ritchie, M.D.; Roden, D.M.; Rosendaal, F.R.; Rotter, J.I.; Rudan, I.; Rutters, F.; Sabanayagam, C.; Saleheen, D.; Salomaa, V.; Samani, N.J.; Sanghera, D.K.; Sattar, N.; Schmidt, B.; Schmidt, H.; Schmidt, R.; Schulze, M.B.; Schunkert, H.; Scott, L.J.; Scott, R.J.; Sever, P.; Shiroma, E.J.; Shoemaker, M.B.; Shu, X.O.; Simonsick, E.M.; Sims, M.; Singh, J.R.; Singleton, A.B.; Sinner, M.F.; Smith, J.G.; Snieder, H.; Spector, T.D.; Stampfer, M.J.; Stark, K.J.; Strachan, D.P.; 't Hart, L.M.; Tabara, Y.; Tang, H.; Tardif, J.C.; Thanaraj, T.A.; Timpson, N.J.; Tönjes, A.; Tremblay, A.; Tuomi, T.; Tuomilehto, J.; Tusié-Luna, M.T.; Uitterlinden, A.G.; van Dam, R.M.; van der Harst, P.; Van der Velde, N.; van Duijn, C.M.; van Schoor, N.M.; Vitart, V.; Völker, U.; Vollenweider, P.; Völzke, H.; Wacher-Rodarte, N.H.; Walker, M.; Wang, Y.X.; Wareham, N.J.; Watanabe, R.M.; Watkins, H.; Weir, D.R.; Werge, T.M.; Widen, E.; Wilkens, L.R.; Willemsen, G.; Willett, W.C.; Wilson, J.F.; Wong, T.Y.; Woo, J.T.; Wright, A.F.; Wu, J.Y.; Xu, H.; Yajnik, C.S.; Yokota, M.; Yuan, J.M.; Zeggini, E.; Zemel, B.S.; Zheng, W.; Zhu, X.; Zmuda, J.M.; Zonderman, A.B.; Zwart, J.A.; 23andMe Research Team; VA Million Veteran Program.; DiscovEHR (DiscovEHR and MyCode Community Health Initiative).; eMERGE (Electronic Medical Records and Genomics Network).; Lifelines Cohort Study.; PRACTICAL Consortium.; Understanding Society Scientific Group.; Chasman, D.I.; Cho, Y.S.; Heid, I.M.; McCarthy, M.I.; Ng, M.C.Y.; O'Donnell, C.J.; Rivadeneira, F.; Thorsteinsdottir, U.; Sun, Y.V.; Tai, E.S.; Boehnke, M.; Deloukas, P.; Justice, A.E.; Lindgren, C.M.; Loos, R.J.F.; Mohlke, K.L.; North, K.E.; Stefansson, K.; Walters R.G.v.; Winkler, T.W.; Young, K.L.; Loh, P.R.; Yang, J.; Esko, T.; Assimes, T.L.; Auton, A.; Abecasis, G.R.; Willer, C.J.; Locke, A.E.; Berndt, S.I.; Lettre, G.; Frayling, T.M.; Frayling, T.M.; Okada, Y.; Wood, A.R.; Visscher, P.M.; Hirschhorn, J.N.
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.
The iHealth-T2D study: a cluster randomised trial for the prevention of type 2 diabetes amongst South Asians with central obesity and prediabetes-a statistical analysis plan
(BioMed Central, London, 2022) Muilwijk, M.; Loh, M.; Mahmood, S.; Palaniswamy, S.; Siddiqui, S.; Silva, W.; Frost, G.S.; Gage, H.M.; Jarvelin, M.R.; Rannan-Eliya, R.P.; Ahmad, S.; Jha, S.; Kasturiratne, A.; Katulanda, P.; Khawaja, K.I.; Kooner, J.S.; Wickremasinghe, A.R.; van Valkengoed, I.G.M.; Chambers, J.C.
Background: South Asians are at high risk of type 2 diabetes (T2D). Lifestyle modification is effective at preventing T2D amongst South Asians, but the approaches to screening and intervention are limited by high costs, poor scalability and thus low impact on T2D burden. An intensive family-based lifestyle modification programme for the prevention of T2D was developed. The aim of the iHealth-T2D trial is to compare the effectiveness of this programme with usual care. Methods: The iHealth-T2D trial is designed as a cluster randomised controlled trial (RCT) conducted at 120 sites across India, Pakistan, Sri Lanka and the UK. A total of 3682 South Asian men and women with age between 40 and 70 years without T2D but at elevated risk for T2D [defined by central obesity (waist circumference ≥ 95 cm in Sri Lanka or ≥ 100 cm in India, Pakistan and the UK) and/or prediabetes (HbA1c ≥ 6.0%)] were included in the trial. Here, we describe in detail the statistical analysis plan (SAP), which was finalised before outcomes were available to the investigators. The primary outcome will be evaluated after 3 years of follow-up after enrolment to the study and is defined as T2D incidence in the intervention arm compared to usual care. Secondary outcomes are evaluated both after 1 and 3 years of follow-up and include biochemical measurements, anthropometric measurements, behavioural components and treatment compliance. Discussion: The iHealth-T2D trial will provide evidence of whether an intensive family-based lifestyle modification programme for South Asians who are at high risk for T2D is effective in the prevention of T2D. The data from the trial will be analysed according to this pre-specified SAP. Ethics and dissemination: The trial was approved by the international review board of each participating study site. Study findings will be disseminated through peer-reviewed publications and in conference presentations.
Food environment and diabetes mellitus in South Asia: A geospatial analysis of health outcome data
(Public Library of Science,San Francisco, 2022) Kusuma, D.; Atanasova, P.; Pineda, E.; Anjana, R.M.; de Silva, L.; Hanif, A.A.; Hasan, M.; Hossain, M.M.; Indrawansa, S.; Jayamanne, D.; Jha, S.; Kasturiratne, A.; Katulanda, P.; Khawaja, K.I.; Kumarendran, B.; Mridha, M.K.; Rajakaruna, V.; Chambers, J.C.; Frost, G.; Sassi, F.; Miraldo, M.
Background: The global epidemic of type 2 diabetes mellitus (T2DM) renders its prevention a major public health priority. A key risk factor of diabetes is obesity and poor diets. Food environments have been found to influence people's diets and obesity, positing they may play a role in the prevalence of diabetes. Yet, there is scant evidence on the role they may play in the context of low- and middle-income countries (LMICs). We examined the associations of food environments on T2DM among adults and its heterogeneity by income and sex. Methods and findings: We linked individual health outcome data of 12,167 individuals from a network of health surveillance sites (the South Asia Biobank) to the density and proximity of food outlets geolocated around their homes from environment mapping survey data collected between 2018 and 2020 in Bangladesh and Sri Lanka. Density was defined as share of food outlets within 300 m from study participant's home, and proximity was defined as having at least 1 outlet within 100 m from home. The outcome variables include fasting blood glucose level, high blood glucose, and self-reported diagnosed diabetes. Control variables included demographics, socioeconomic status (SES), health status, healthcare utilization, and physical activities. Data were analyzed in ArcMap 10.3 and STATA 15.1. A higher share of fast-food restaurants (FFR) was associated with a 9.21 mg/dl blood glucose increase (95% CI: 0.17, 18.24; p < 0.05). Having at least 1 FFR in the proximity was associated with 2.14 mg/dl blood glucose increase (CI: 0.55, 3.72; p < 0.01). A 1% increase in the share of FFR near an individual's home was associated with 8% increase in the probability of being clinically diagnosed as a diabetic (average marginal effects (AMEs): 0.08; CI: 0.02, 0.14; p < 0.05). Having at least 1 FFR near home was associated with 16% (odds ratio [OR]: 1.16; CI: 1.01, 1.33; p < 0.05) and 19% (OR: 1.19; CI: 1.03, 1.38; p < 0.05) increases in the odds of higher blood glucose levels and diagnosed diabetes, respectively. The positive association between FFR density and blood glucose level was stronger among women than men, but the association between FFR proximity and blood glucose level was stronger among men as well as among those with higher incomes. One of the study's key limitations is that we measured exposure to food environments around residency geolocation; however, participants may source their meals elsewhere. Conclusions: Our results suggest that the exposure to fast-food outlets may have a detrimental impact on the risk of T2DM, especially among females and higher-income earners. Policies should target changes in the food environments to promote better diets and prevent T2DM.
Identification of genetic effects underlying type 2 diabetes in South Asian and European populations
(Nature Publishing Group UK, 2022) Loh, M.; Zhang, W.; Ng, H.K.; Schmid, K.; Lamri, A.; Tong, L.; Ahmad, M.; Lee, J.J.; Ng, M.C.Y.; Petty, L.E.; Spracklen, C.N.; Takeuchi, F.; Islam, M.T.; Jasmine, F.; Kasturiratne, A.; Kibriya, M.; Mohlke, K.L.; Paré, G.; Prasad, G.; Shahriar, M.; Chee, M.L.; de Silva, H.J.; Engert, J.C.; Gerstein, H.C.; Mani, K.R.; Sabanayagam, C.; Vujkovic, M.; Wickremasinghe, A.R.; Wong, T.Y.; Yajnik, C.S.; Yusuf, S.; Ahsan, H.; Bharadwaj, D.; Anand, S.S.; Below, J.E.; Boehnke, M.; Bowden, D.W.; Chandak, G.R.; Cheng, C.Y.; Kato, N.; Mahajan, A.; Sim, X.; McCarthy, M.I.; Morris, A.P.; Kooner, J.S.; Saleheen, D.; Chambers, J.C.
South Asians are at high risk of developing type 2 diabetes (T2D). We carried out a genome-wide association meta-analysis with South Asian T2D cases (n = 16,677) and controls (n = 33,856), followed by combined analyses with Europeans (neff = 231,420). We identify 21 novel genetic loci for significant association with T2D (P = 4.7 × 10-8 to 5.2 × 10-12), to the best of our knowledge at the point of analysis. The loci are enriched for regulatory features, including DNA methylation and gene expression in relevant tissues, and highlight CHMP4B, PDHB, LRIG1 and other genes linked to adiposity and glucose metabolism. A polygenic risk score based on South Asian-derived summary statistics shows ~4-fold higher risk for T2D between the top and bottom quartile. Our results provide further insights into the genetic mechanisms underlying T2D, and highlight the opportunities for discovery from joint analysis of data from across ancestral populations.
Food environments and obesity: A geospatial analysis of the South Asia Biobank, income and sex inequalities
(Elsevier Ltd, 2022) Atanasova, P.; Kusuma, D.; Pineda, E.; Anjana, R.M.; de Silva, L.; Hanif, A.A.M.; Hasan, M.; Hossain, M.M.; Indrawansa, S.; Jayamanne, D.; Jha, S.; Kasturiratne, A.; Katulanda, P.; Khawaja, K.I.; Kumarendran, B.; Mrida, M.K.; Rajakaruna, V.; Chambers, J.C.; Frost, G.; Sassi, F.; Miraldo, M.
Introduction: In low-middle income countries (LMICs) the role of food environments on obesity has been understudied. We address this gap by 1) examining the effect of food environments on adults' body size (BMI, waist circumference) and obesity; 2) measuring the heterogeneity of such effects by income and sex.Methods: This cross-sectional study analysed South Asia Biobank surveillance and environment mapping data for 12,167 adults collected between 2018 and 2020 from 33 surveillance sites in Bangladesh and Sri Lanka. Individual-level data (demographic, socio-economic, and health characteristics) were combined with exposure to healthy and unhealthy food environments measured with geolocations of food outlets (obtained through ground-truth surveys) within 300 m buffer zones around participants' homes. Multivariate regression models were used to assess association of exposure to healthy and unhealthy food environments on waist circumference, BMI, and probability of obesity for the total sample and stratified by sex and income.Findings: The presence of a higher share of supermarkets in the neighbourhood was associated with a reduction in body size (BMI, β = - 3∙23; p < 0∙0001, and waist circumference, β = -5∙99; p = 0∙0212) and obesity (Average Marginal Effect (AME): -0∙18; p = 0∙0009). High share of fast-food restaurants in the neighbourhood was not significantly associated with body size, but it significantly increased the probability of obesity measured by BMI (AME: 0∙09; p = 0∙0234) and waist circumference (AME: 0∙21; p = 0∙0021). These effects were stronger among females and low-income individuals.Interpretation: The results suggest the availability of fast-food outlets influences obesity, especially among female and lower-income groups. The availability of supermarkets is associated with reduced body size and obesity, but their effects do not outweigh the role of fast-food outlets. Policies should target food environments to promote better diets and reduce obesity.
The power of genetic diversity in genome-wide association studies of lipids
(Macmillan Journals Ltd, 2021) Graham, S.E.; Clarke, S.L.; Wu, K.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.; 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.; Kårhus, 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.; Møllehave, 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.; Cañadas-Garre, M.; Wang, C.; Nakatochi, M.; Wong, A.; Hutri-Kähönen, 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.; Lorés-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.; Yang, J.; 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.; Pitkänen, 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.; Lyytikäinen, L.P.; Nikus, K.; Cuellar-Partida, G.; Vestergaard, H.; Hildalgo, B.; Giannakopoulou, O.; Cai, Q.; Obura, M.O.; van Setten, J.; Li, X.; 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.; Jäger, 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.; Zhu, X.; 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.; Kähönen, M.; Pérusse, L.; Bouchard, C.; Tönjes, A.; Chen, Y.I.; Pennell, C.E.; Mori, T.A.; Lieb, W.; Franke, A.; Ohlsson, C.; Mellström, D.; Cho, Y.S.; Lee, H.; Yuan, J.M.; Koh, W.P.; Rhee, S.Y.; Woo, J.T.; Heid, I.M.; Stark, K.J.; Völzke, 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.; Böger, 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.; Tusié-Luna, T.; Aguilar-Salinas, C.A.; Villalpando, C.G.; Orozco, L.; Fornage, M.; Tai, E.S.; van Dam, R.M.; Lehtimäki, T.; Chaturvedi, N.; Yokota, M.; Liu, J.; Reilly, D.F.; McKnight, A.J.; Kee, F.; Jöckel, 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.; März, 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.; Widén, 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.; Männikkö, 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.BJ.; Ghanbari, M.; Gordon-Larsen, P.; Huang, W.; Kim, Y.T.; 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.; Åsvold, 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.; VA Million Veteran Program; Global Lipids Genetics Consortium
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.
The iHealth-T2D study, prevention of type 2 diabetes amongst South Asians with central obesity and prediabetes: study protocol for a randomised controlled trial
(BioMed Central, London, 2021) Kasturiratne, A.; Khawaja, K.I.; Ahmad, S.; Siddiqui, S.; Shahzad, K.; Athauda, L.K.; Jayawardena, R.; Mahmood, S.; Muilwijk, M.; Batool, T.; Burney, S.; Glover, M.; Palaniswamy, S.; Bamunuarachchi, V.; Panda, M.; Madawanarachchi, S.; Rai, B.; Sattar, I.; Silva, W.; Waghdhare, S.; Jarvelin, M.R.; Rannan-Eliya, R.P.; Gage, H.M.; van Valkengoed, I.G.M.; Valabhji, J.; Frost, G.S.; Loh, M.; Wickremasinghe, A.R.; Kooner, J.S.; Katulanda, P.; Jha, S.; Chambers, J.C.
Background: People from South Asia are at increased risk of type 2 diabetes (T2D). There is an urgent need to develop approaches for the prevention of T2D in South Asians that are cost-effective, generalisable and scalable across settings.Hypothesis: Compared to usual care, the risk of T2D can be reduced amongst South Asians with central obesity or raised HbA1c, through a 12-month lifestyle modification programme delivered by community health workers.Design: Cluster randomised clinical trial (1:1 allocation to intervention or usual care), carried out in India, Pakistan, Sri Lanka and the UK, with 30 sites per country (120 sites total). Target recruitment 3600 (30 participants per site) with annual follow-up for 3 years.Entry criteria: South Asian, men or women, age 40-70 years with (i) central obesity (waist circumference ≥ 100 cm in India and Pakistan; ≥90 cm in Sri Lanka) and/or (ii) prediabetes (HbA1c 6.0-6.4% inclusive).Exclusion criteria: known type 1 or 2 diabetes, normal or underweight (body mass index < 22 kg/m2); pregnant or planning pregnancy; unstable residence or planning to leave the area; and serious illness.Endpoints: The primary endpoint is new-onset T2D at 3 years, defined as (i) HbA1c ≥ 6.5% or (ii) physician diagnosis and on treatment for T2D. Secondary endpoints at 1 and 3 years are the following: (i) physical measures: waist circumference, weight and blood pressure; (ii) lifestyle measures: smoking status, alcohol intake, physical activity and dietary intake; (iii) biochemical measures: fasting glucose, insulin and lipids (total and HDL cholesterol, triglycerides); and (iv) treatment compliance. Intervention: Lifestyle intervention (60 sites) or usual care (60 sites). Lifestyle intervention was delivered by a trained community health worker over 12 months (5 one-one sessions, 4 group sessions, 13 telephone sessions) with the goal of the participants achieving a 7% reduction in body mass index and a 10-cm reduction in waist circumference through (i) improved diet and (ii) increased physical activity. Usual care comprised a single 30-min session of lifestyle modification advice from the community health worker. Results: We screened 33,212 people for inclusion into the study. We identified 10,930 people who met study entry criteria, amongst whom 3682 agreed to take part in the intervention. Study participants are 49.2% female and aged 52.8 (SD 8.2) years. Clinical characteristics are well balanced between intervention and usual care sites. More than 90% of follow-up visits are scheduled to be complete in December 2020. Based on the follow-up to end 2019, the observed incidence of T2D in the study population is in line with expectations (6.1% per annum). Conclusion: The iHealth-T2D study will advance understanding of strategies for the prevention of diabetes amongst South Asians, use approaches for screening and intervention that are adapted for low-resource settings. Our study will thus inform the implementation of strategies for improving the health and well-being of this major global ethnic group.

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