Imperial College London

ProfessorJohnChambers

Faculty of MedicineSchool of Public Health

Professor of Cardiovascular Epidemiology
 
 
 
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Contact

 

+44 (0)7866 365 776john.chambers

 
 
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Location

 

172Medical SchoolSt Mary's Campus

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Summary

 

Publications

Publication Type
Year
to

335 results found

Mina T, Yew YW, Ng HK, Sadhu N, Wansaicheong G, Dalan R, Low DYW, Lam BCC, Riboli E, Lee ES, Ngeow J, Elliott P, Griva K, Loh M, Lee J, Chambers Jet al., 2023, Adiposity impacts cognitive function in Asian populations: an epidemiological and Mendelian Randomization study., Lancet Reg Health West Pac, Vol: 33

BACKGROUND: Obesity and related metabolic disturbances including diabetes, hypertension and hyperlipidemia predict future cognitive decline. Asia has a high prevalence of both obesity and metabolic disease, potentially amplifying the future burden of dementia in the region. We aimed to investigate the impact of adiposity and metabolic risk on cognitive function in Asian populations, using an epidemiological analysis and a two-sample Mendelian Randomization (MR) study. METHODS: The Health for Life in Singapore (HELIOS) Study is a population-based cohort of South-East-Asian men and women in Singapore, aged 30-84 years. We analyzed 8769 participants with metabolic and cognitive data collected between 2018 and 2021. Whole-body fat mass was quantified with Dual X-Ray Absorptiometry (DEXA). Cognition was assessed using a computerized cognitive battery. An index of general cognition ' g ' was derived through factor analysis. We tested the relationship of fat mass indices and metabolic measures with ' g ' using regression approaches. We then performed inverse-variance-weighted MR of adiposity and metabolic risk factors on ' g ', using summary statistics for genome-wide association studies of BMI, visceral adipose tissue (VAT), waist-hip-ratio (WHR), blood pressure, HDL cholesterol, triglycerides, fasting glucose, HbA1c, and general cognition. FINDINGS: Participants were 58.9% female, and aged 51.4 (11.3) years. In univariate analysis, all 29 adiposity and metabolic measures assessed were associated with ' g ' at P < 0.05. In multivariable analyses, reduced ' g ' was consistently associated with increased visceral fat mass index and lower HDL cholesterol (P < 0.001), but not with blood pressure, triglycerides, or glycemic indices. The reduction in ' g ' associated with 1SD higher visceral fat, or 1SD lower HDL cholesterol, was equivalent to a 0.7 and 0.9-year increase in chronological age respectively (P < 0.001). Inverse vari

Journal article

Wong E, Bertin N, Hebrard M, Tirado-Magallanes R, Bellis C, Lim WK, Chua CY, Tong PML, Chua R, Mak K, Lim TM, Cheong WY, Thien KE, Goh KT, Chai J-F, Lee J, Sung JJ-Y, Wong TY, Chin CWL, Gluckman PD, Goh LL, Ban KHK, Tan TW, SG10KHealth Consortium, Sim X, Cheng C-Y, Davila S, Karnani N, Leong KP, Liu J, Prabhakar S, Maurer-Stroh S, Verma CS, Krishnaswamy P, Goh RSM, Chia I, Ho C, Low D, Virabhak S, Yong J, Zheng W, Seow SW, Seck YK, Koh M, Chambers JC, Tai ES, Tan Pet al., 2023, The Singapore National Precision Medicine Strategy., Nat Genet, Vol: 55, Pages: 178-186

Precision medicine promises to transform healthcare for groups and individuals through early disease detection, refining diagnoses and tailoring treatments. Analysis of large-scale genomic-phenotypic databases is a critical enabler of precision medicine. Although Asia is home to 60% of the world's population, many Asian ancestries are under-represented in existing databases, leading to missed opportunities for new discoveries, particularly for diseases most relevant for these populations. The Singapore National Precision Medicine initiative is a whole-of-government 10-year initiative aiming to generate precision medicine data of up to one million individuals, integrating genomic, lifestyle, health, social and environmental data. Beyond technologies, routine adoption of precision medicine in clinical practice requires social, ethical, legal and regulatory barriers to be addressed. Identifying driver use cases in which precision medicine results in standardized changes to clinical workflows or improvements in population health, coupled with health economic analysis to demonstrate value-based healthcare, is a vital prerequisite for responsible health system adoption.

Journal article

Loh M, Chambers JC, 2023, Polygenic risk scores for complex diseases: Where are we now?, Singapore Med J, Vol: 64, Pages: 88-89

Journal article

Kanoni S, Graham SE, Wang Y, Surakka I, Ramdas S, Zhu X, Clarke SL, Bhatti KF, Vedantam S, Winkler TW, Locke AE, Marouli E, Zajac GJM, Wu K-HH, Ntalla I, Hui Q, Klarin D, Hilliard AT, Wang Z, Xue C, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Hwang MY, Han S, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Havulinna AS, Veturi Y, Pacheco JA, Rosenthal EA, Lingren T, Feng Q, Kullo IJ, Narita A, Takayama J, Martin HC, Hunt KA, Trivedi B, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Rasheed A, Hindy G, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Choudhury A, Sengupta D, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao J-H, Matsuda F, Jang H-M, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Wood AR, Ji Y, Gao Z, Haworth S, Yousri NA, Mitchell RE, Chai JF, Aadahl M, Bjerregaard AA, Yao J, Manichaikul A, Hwu C-M, Hung Y-J, Warren HR, Ramirez J, Bork-Jensen J, Kårhus LL, Goel A, Sabater-Lleal M, Noordam R, Mauro P, Matteo F, McDaid AF, Marques-Vidal P, Wielscher M, Trompet S, Sattar N, Møllehave LT, Munz M, Zeng L, Huang J, Yang B, Poveda A, Kurbasic A, Lamina C, Forer L, Scholz M, Galesloot TE, Bradfield JP, Ruotsalainen SE, Daw E, Zmuda JM, Mitchell JS, Fuchsberger C, Christensen H, Brody JA, Vazquez-Moreno M, Feitosa MF, Wojczynski MK, Wang Z, Preuss MH, Mangino M, Christofidou P, Verweij N, Benjamins JW, Engmann J, Tsao NL, Verma A, Slieker RC, Lo KS, Zilhao NR, Le P, Kleber ME, Delgado GE, Huo S, Ikeda DD, Iha H, Yang J, Liu J, Demirkan A, Leonard HL, Marten J, Frank M, Schmidt B, Smyth LJ, Cañadas-Garre M, Wang C, Nakatochi M, Wong A, Hutri-Kähönen N, Sim X, Xia R, Huerta-Chagoya A, Fernandez-Lopez JC, Lyssenko V, Nongmaithem SS, Bayyana S, Stringham HM, Irvin MR, Oldmeadow C, Kim H-N, Ryu S, Timmers PRHJ, Arbeeva L, Dorajoo R, Lange LA, Prasad G, Lorés-Motta L, Pauper M, Long J, Li X, Theusch E, Takeuchi F, Spracklen CN, Loukolet al., 2022, Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis., Genome Biol, Vol: 23

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.

Journal article

Leong W-Y, Gupta A, Hasan M, Mahmood S, Siddiqui S, Ahmed S, Goon I, Loh M, Mina T, Lam B, Yew YW, Lee J, Lee ES, Riboli E, Elliott P, Tan GP, Chotirmall S, Wickremasinghe A, Kooner J, Irfan K, Chambers Jet al., 2022, Reference equations for evaluation of spirometry function tests in South Asia, and amongst South Asians living in other countries, European Respiratory Journal, Vol: 60, ISSN: 0903-1936

Background:There is little data to accurate interpretation of spirometry data in SouthAsia, a major global region with high reported burden for chronicrespiratory disease.Method:We measured lung function in 7,453 healthy men and women aged over18 years, from Bangladesh, North India, South India, Pakistan and SriLanka, as part of the South Asia Biobank study. We first assessed theaccuracy of existing equations for predicting normal forced vital capacity(FVC), forced expiratory volume in 1s (FEV1), and FEV1/FVC ratio. Wethen used our data to derive (N=5,589) and internally validate(N=1,864) new prediction equations amongst South Asians, with furtherexternal validation amongst 339 healthy South Asians living inSingapore.Results:GLI2012 and NHANESIII consistently overestimated expiratory volumes(best fit GLI-SEA, mean [sd] z-score: FEV1 -1.29 [1.04]; FVC -1.12[1.12]). Age, height and weight were strong predictors of lung functionin our participants (P<0.001), and sex specific reference equations usingthese three variables were highly accurate in both internal validation (z-scores: FEV1 0.03 [0.99]; FVC 0.04 [0.97]; FEV1/FVC -0.03 [0.99]) andexternal validation (z-scores: FEV1 0.31 [0.99]; FVC 0.24 [0.97];FEV1/FVC 0.16 [0.91]). Further adjustment for study regions improvesthe model fit, with highest accuracy for estimation of region specific lungfunction in South Asia.Conclusion:We present improved equations for predicting lung function in SouthAsians. These offer the opportunity to enhance diagnosis andmanagement of acute and chronic lung diseases in this major globalpopulation.

Journal article

Hawe JS, Saha A, Waldenberger M, Kunze S, Wahl S, Müller-Nurasyid M, Prokisch H, Grallert H, Herder C, Peters A, Strauch K, Theis FJ, Gieger C, Chambers J, Battle A, Heinig Met al., 2022, Network reconstruction for trans acting genetic loci using multi-omics data and prior information., Genome Med, Vol: 14

BACKGROUND: Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors used or have only been applied to model systems. In this study, we reconstruct the regulatory networks underlying trans-QTL hotspots using human cohort data and data-driven prior information. METHODS: We devised a new strategy to integrate QTL with human population scale multi-omics data. State-of-the art network inference methods including BDgraph and glasso were applied to these data. Comprehensive prior information to guide network inference was manually curated from large-scale biological databases. The inference approach was extensively benchmarked using simulated data and cross-cohort replication analyses. Best performing methods were subsequently applied to real-world human cohort data. RESULTS: Our benchmarks showed that prior-based strategies outperform methods without prior information in simulated data and show better replication across datasets. Application of our approach to human cohort data highlighted two novel regulatory networks related to schizophrenia and lean body mass for which we generated novel functional hypotheses. CONCLUSIONS: We demonstrate that existing biological knowledge can improve the integrative analysis of networks underlying trans associations and generate novel hypotheses about regulatory mechanisms.

Journal article

Chan SH, Bylstra Y, Teo JX, Kuan JL, Bertin N, Gonzalez-Porta M, Hebrard M, Tirado-Magallanes R, Tan JHJ, Jeyakani J, Li Z, Chai JF, Chong YS, Davila S, Goh LL, Lee ES, Wong E, Wong TY, Prabhakar S, Liu J, Cheng C-Y, Eisenhaber B, Karnani N, Leong KP, Sim X, Yeo KK, Chambers JC, Tai E-S, Tan P, Jamuar SS, Ngeow J, Lim WKet al., 2022, Analysis of clinically relevant variants from ancestrally diverse Asian genomes, Nature Communications, Vol: 13, ISSN: 2041-1723

Asian populations are under-represented in human genomics research. Here, we characterize clinically significant genetic variation in 9051 genomes representing East Asian, South Asian, and severely under-represented Austronesian-speaking Southeast Asian ancestries. We observe disparate genetic risk burden attributable to ancestry-specific recurrent variants and identify individuals with variants specific to ancestries discordant to their self-reported ethnicity, mostly due to cryptic admixture. About 27% of severe recessive disorder genes with appreciable carrier frequencies in Asians are missed by carrier screening panels, and we estimate 0.5% Asian couples at-risk of having an affected child. Prevalence of medically-actionable variant carriers is 3.4% and a further 1.6% harbour variants with potential for pathogenic classification upon additional clinical/experimental evidence. We profile 23 pharmacogenes with high-confidence gene-drug associations and find 22.4% of Asians at-risk of Centers for Disease Control and Prevention Tier 1 genetic conditions concurrently harbour pharmacogenetic variants with actionable phenotypes, highlighting the benefits of pre-emptive pharmacogenomics. Our findings illuminate the diversity in genetic disease epidemiology and opportunities for precision medicine for a large, diverse Asian population.

Journal article

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, 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, Mollehavet al., 2022, A saturated map of common genetic variants associated with human height, NATURE, Vol: 610, Pages: 704-+, ISSN: 0028-0836

Journal article

Muilwijk M, Loh M, Mahmood S, Palaniswamy S, Siddiqui S, Silva W, Frost GS, Gage HM, Jarvelin M-R, Rannan-Eliya RP, Ahmad S, Jha S, Kasturiratne A, Katulanda P, Khawaja K, Kooner JS, Wickremasinghe AR, van Valkengoed IGM, Chambers JCet al., 2022, 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, TRIALS, Vol: 23

Journal article

Dixon PH, Levine AP, Cebola I, Chan MMY, Amin AS, Aich A, Mozere M, Maude H, Mitchell AL, Zhang J, NIHR BioResource, Genomics England Research Consortium Collaborators, Chambers J, Syngelaki A, Donnelly J, Cooley S, Geary M, Nicolaides K, Thorsell M, Hague WM, Estiu MC, Marschall H-U, Gale DP, Williamson Cet al., 2022, GWAS meta-analysis of intrahepatic cholestasis of pregnancy implicates multiple hepatic genes and regulatory elements, Nature Communications, Vol: 13, ISSN: 2041-1723

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disorder affecting 0.5–2% of pregnancies. The majority of cases present in the third trimester with pruritus, elevated serum bile acids and abnormal serum liver tests. ICP is associated with an increased risk of adverse outcomes, including spontaneous preterm birth and stillbirth. Whilst rare mutations affecting hepatobiliary transporters contribute to the aetiology of ICP, the role of common genetic variation in ICP has not been systematically characterised to date. Here, we perform genome-wide association studies (GWAS) and meta-analyses for ICP across three studies including 1,138 cases and 153,642 controls. Eleven loci achieve genome-wide significance and have been further investigated and fine-mapped using functional genomics approaches. Our results pinpoint common sequence variation in liver-enriched genes and liver-specific cis-regulatory elements as contributing mechanisms to ICP susceptibility.

Journal article

Ramdas S, Judd J, Graham SE, Kanoni S, Wang Y, Surakka I, Wenz B, Clarke SL, Chesi A, Wells A, Bhatti KF, Vedantam S, Winkler TW, Locke AE, Marouli E, Zajac GJM, Wu K-HH, Ntalla I, Hui Q, Klarin D, Hilliard AT, Wang Z, Xue C, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Hwang MY, Han S, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Havulinna AS, Veturi Y, Pacheco JA, Rosenthal EA, Lingren T, Feng Q, Kullo IJ, Narita A, Takayama J, Martin HC, Hunt KA, Trivedi B, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Rasheed A, Hindy G, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Choudhury A, Sengupta D, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao J-H, Matsuda F, Jang H-M, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Wood AR, Ji Y, Gao Z, Haworth S, Mitchell RE, Chai JF, Aadahl M, Bjerregaard AA, Yao J, Manichaikul A, Lee W-J, Hsiung CA, Warren HR, Ramirez J, Bork-Jensen J, Karhus LL, Goel A, Sabater-Lleal M, Noordam R, Mauro P, Matteo F, McDaid AF, Marques-Vidal P, Wielscher M, Trompet S, Sattar N, Mollehave LT, Munz M, Zeng L, Huang J, Yang B, Poveda A, Kurbasic A, Schonherr S, Forer L, Scholz M, Galesloot TE, Bradfield JP, Ruotsalainen SE, Daw EW, Zmuda JM, Mitchell JS, Fuchsberger C, Christensen H, Brody JA, Le P, Feitosa MF, Wojczynski MK, Hemerich D, Preuss M, Mangino M, Christofidou P, Verweij N, Benjamins JW, Engmann J, Noah TL, Verma A, Slieker RC, Lo KS, Zilhao NR, Kleber ME, Delgado GE, Huo S, Ikeda DD, Iha H, Yang J, Liu J, Demirkan A, Leonard HL, Marten J, Emmel C, Schmidt B, Smyth LJ, Canadas-Garre M, Wang C, Nakatochi M, Wong A, Hutri-Kahonen N, Sim X, Xia R, Huerta-Chagoya A, Fernandez-Lopez JC, Lyssenko V, Nongmaithem SS, Sankareswaran A, Irvin MR, Oldmeadow C, Kim H-N, Ryu S, Timmers PRHJ, Arbeeva L, Dorajoo R, Lange LA, Prasad G, Lores-Motta L, Pauper M, Long J, Li X, Theusch E, Takeuchi F, Spracklen CN, Loukolaet al., 2022, A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids, AMERICAN JOURNAL OF HUMAN GENETICS, Vol: 109, Pages: 1366-1387, ISSN: 0002-9297

Journal article

Winkler TW, Rasheed H, Teumer A, Gorski M, Rowan BX, Stanzick KJ, Thomas LF, Tin A, Hoppmann A, Chu AY, Tayo B, Thio CHL, Cusi D, Chai J-F, Sieber KB, Horn K, Li M, Scholz M, Cocca M, Wuttke M, van der Most PJ, Yang Q, Ghasemi S, Nutile T, Li Y, Pontali G, Guenther F, Dehghan A, Correa A, Parsa A, Feresin A, de Vries APJ, Zonderman AB, Smith A, Oldehinkel AJ, De Grandi A, Rosenkranz AR, Franke A, Teren A, Metspalu A, Hicks AA, Morris AP, Toenjes A, Morgan A, Podgornaia A, Peters A, Koerner A, Mahajan A, Campbell A, Freedman B, Spedicati B, Ponte B, Schoettker B, Brumpton B, Banas B, Kraemer BK, Jung B, Asvold BO, Smith BH, Ning B, Penninx BWJH, Vanderwerff BR, Psaty BM, Kammerer CM, Langefeld CD, Hayward C, Spracklen CN, Robinson-Cohen C, Hartman CA, Lindgren CM, Wang C, Sabanayagam C, Heng C-K, Lanzani C, Khor C-C, Cheng C-Y, Fuchsberger C, Gieger C, Shaffer CM, Schulz C-A, Willer CJ, Chasman D, Gudbjartsson DF, Ruggiero D, Toniolo D, Czamara D, Porteous DJ, Waterworth DM, Mascalzoni D, Mook-Kanamori DO, Reilly DF, Daw EW, Hofer E, Boerwinkle E, Salvi E, Bottinger EP, Tai E-S, Catamo E, Rizzi F, Guo F, Rivadeneira F, Guilianini F, Sveinbjornsson G, Ehret G, Waeber G, Biino G, Girotto G, Pistis G, Nadkarni GN, Delgado GE, Montgomery GW, Snieder H, Campbell H, White HD, Gao H, Stringham HM, Schmidt H, Li H, Brenner H, Holm H, Kirsten H, Kramer H, Rudan I, Nolte IM, Tzoulaki I, Olafsson I, Martins J, Cook JP, Wilson JF, Halbritter J, Felix JF, Divers J, Kooner JS, Lee JJ-M, O'Connell J, Rotter J, Liu J, Xu J, Thiery J, Arnlov J, Kuusisto J, Jakobsdottir J, Tremblay J, Chambers JC, Whitfield JB, Gaziano JM, Marten J, Coresh J, Jonas JB, Mychaleckyj JC, Christensen K, Eckardt K-U, Mohlke KL, Endlich K, Dittrich K, Ryan KA, Rice KM, Taylor KD, Ho K, Nikus K, Matsuda K, Strauch K, Miliku K, Hveem K, Lind L, Wallentin L, Yerges-Armstrong LM, Raffield LM, Phillips LS, Launer LJ, Lyytikainen L-P, Lange LA, Citterio L, Klaric L, Ikram MA, Ising M, Kleber ME, Francescatto M Cet al., 2022, Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals, Communications Biology, Vol: 5, ISSN: 2399-3642

Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM.

Journal article

Mahajan A, Spracklen CN, Zhang W, Ng MCY, Petty LE, Kitajima H, Yu GZ, Rueger S, Speidel L, Kim YJ, Horikoshi M, Mercader JM, Taliun D, Moon S, Kwak S-H, Robertson NR, Rayner NW, Loh M, Kim B-J, Chiou J, Miguel-Escalada I, Parolo PDB, Lin K, Bragg F, Preuss MH, Takeuchi F, Nano J, Guo X, Lamri A, Nakatochi M, Scott RA, Lee J-J, Huerta-Chagoya A, Graff M, Chai J-F, Parra EJ, Yao J, Bielak LF, Tabara Y, Hai Y, Steinthorsdottir V, Cook JP, Kals M, Grarup N, Schmidt EM, Pan I, Sofer T, Wuttke M, Sarnowski C, Gieger C, Nousome D, Trompet S, Long J, Sun M, Tong L, Chen W-M, Ahmad M, Noordam R, Lim VJY, Tam CHT, Joo YY, Chen C-H, Raffield LM, Lecoeur C, Prins BP, Nicolas A, Yanek LR, Chen G, Jensen RA, Tajuddin S, Kabagambe EK, An P, Xiang AH, Choi HS, Cade BE, Tan J, Flanagan J, Abaitua F, Adair LS, Adeyemo A, Aguilar-Salinas CA, Akiyama M, Anand SS, Bertoni A, Bian Z, Bork-Jensen J, Brandslund I, Brody JA, Brummett CM, Buchanan TA, Canouil M, Chan JCN, Chang L-C, Chee M-L, Chen J, Chen S-H, Chen Y-T, Chen Z, Chuang L-M, Cushman M, Das SK, de Silva HJ, Dedoussis G, Dimitrov L, Doumatey AP, Du S, Duan Q, Eckardt K-U, Emery LS, Evans DS, Evans MK, Fischer K, Floyd JS, Ford I, Fornage M, Franco OH, Frayling TM, Freedman B, Fuchsberger C, Genter P, Gerstein HC, Giedraitis V, Gonzalez-Villalpando C, Gonzalez-Villalpando ME, Goodarzi MO, Gordon-Larsen P, Gorkin D, Gross M, Guo Y, Hackinger S, Han S, Hattersley AT, Herder C, Howard A-G, Hsueh W, Huang M, Huang W, Hung Y-J, Hwang MY, Hwu C-M, Ichihara S, Ikram MA, Ingelsson M, Islam MT, Isono M, Jang H-M, Jasmine F, Jiang G, Jonas JB, Jorgensen ME, Jorgensen T, Kamatani Y, Kandeel FR, Kasturiratne A, Katsuya T, Kaur V, Kawaguchi T, Keaton JM, Kho AN, Khor C-C, Kibriya MG, Kim D-H, Kohara K, Kriebel J, Kronenberg F, Kuusisto J, Lall K, Lange LA, Lee M-S, Lee NR, Leong A, Li L, Li Y, Li-Gao R, Ligthart S, Lindgren CM, Linneberg A, Liu C-T, Liu J, Locke AE, Louie T, Luan J, Luk AO, Luo X, Lv J, Lyssenko V, Mamakou V, Mani KR, Meitinet al., 2022, Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation, NATURE GENETICS, Vol: 54, Pages: 560-+, ISSN: 1061-4036

Journal article

Loh M, Zhang W, Ng HK, Schmid K, Lamri A, Tong L, Ahmad M, Lee J-J, Ng MCY, Petty LE, Spracklen CN, Takeuchi F, Islam MT, Jasmine F, Kasturiratne A, Kibriya M, Mohlke KL, Pare G, Prasad G, Shahriar M, Chee ML, de Silva HJ, Engert JC, Gerstein HC, Mani KR, Sabanayagam C, Vujkovic M, Wickremasinghe AR, Wong TY, Yajnik CS, Yusuf S, Ahsan H, Bharadwaj D, Anand SS, Below JE, Boehnke M, Bowden DW, Chandak GR, Cheng C-Y, Kato N, Mahajan A, Sim X, McCarthy MI, Morris AP, Kooner JS, Saleheen D, Chambers JCet al., 2022, Identification of genetic effects underlying type 2 diabetes in South Asian and European populations (vol 5, 329, 2022), COMMUNICATIONS BIOLOGY, Vol: 5

Journal article

Jarvelin M-R, 2022, DNA methylation signature of chronic low-gradeinflammation and its role in cardio-respiratorydiseases, Nature Communications, Vol: 13, ISSN: 2041-1723

We performed a multi-ethnic Epigenome Wide Association study on 22,774 individuals to describe the DNA methylation signature of chronic low-grade inflammation as measured by C-Reactive protein (CRP). We find 1,511 independent differentially methylated loci associated with CRP. These CpG sites show correlation structures across chromosomes, and are primarily situated in euchromatin, depleted in CpG islands. These genomic loci are predominantly situated in transcription factor binding sites and genomic enhancer regions. Mendelian randomization analysis suggests altered CpG methylation is a consequence of increased blood CRP levels. Mediation analysis reveals obesity and smoking as important underlying driving factors for changed CpG methylation. Finally, we find that an activated CpG signature significantly increases the risk for cardiometabolic diseases and COPD.

Journal article

Loh M, Zhang W, Ng HK, Schmid K, Lamri A, Tong L, Ahmad M, Lee J-J, Ng MCY, Petty LE, Spracklen CN, Takeuchi F, Islam MT, Jasmine F, Kasturiratne A, Kibriya M, Mohlke KL, Pare G, Prasad G, Shahriar M, Chee ML, de Silva HJ, Engert JC, Gerstein HC, Mani KR, Sabanayagam C, Vujkovic M, Wickremasinghe AR, Wong TY, Yajnik CS, Yusuf S, Ahsan H, Bharadwaj D, Anand SS, Below JE, Boehnke M, Bowden DW, Chandak GR, Cheng C-Y, Kato N, Mahajan A, Sim X, McCarthy MI, Morris AP, Kooner JS, Saleheen D, Chambers Jet al., 2022, Identification of genetic effects underlying Type 2 Diabetes in South Asian and European populations, Communications Biology, Vol: 5, ISSN: 2399-3642

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=4.7x10-8 to 5.2x10-12), 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.

Journal article

Ruamviboonsuk P, Tiwari R, Sayres R, Nganthavee V, Hemarat K, Kongprayoon A, Raman R, Levinstein B, Liu Y, Schaekermann M, Lee R, Virmani S, Widner K, Chambers J, Hersch F, Peng L, Webster DRet al., 2022, Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study, LANCET DIGITAL HEALTH, Vol: 4

Journal article

Warren H, Edwards T, Vaez A, Keaton J, Kamali Z, Xie T, Ani A, Evangelou E, Hellwege J, Yengo L, Young W, Traylor M, Giri A, Visscher P, Chasman D, Morris A, Caulfield M, Hwang S-J, Kooner J, Conen D, Attia J, Morrison A, Loos R, Kristiansson K, Schmidt R, Hicks A, Pramstaller P, Nelson C, Samani N, Risch L, Gyllensten U, Melander O, Riese H, Wilson J, Campbell H, Psaty B, Lu Y, Rotter J, Guo X, Rice K, Vollenweider P, Sundstrom J, Langenberg C, Tobin M, Giedraitis V, Luan J, Tuomilehto J, Kutalik Z, Ripatti S, Salomaa V, Girotto G, Trompet S, Jukema JW, Harst PVD, Ridker P, Giulianini F, Vitart V, Goel A, Watkins H, Harris S, Deary I, Most PVD, Oldehinkel A, Keavney B, Hayward C, Campbell A, Boehnke M, Scott L, Boutin T, Mamasoula C, Jarvelin M-R, Peters A, Gieger C, Lakatta E, Cucca F, Hui J, Knekt P, Enroth S, de Borst M, Polasek O, Concas MP, Catamo E, Cocca M, Li-Gao R, Hofer E, Schmidt H, Spedicati B, Waldenberger M, Strachan D, Laan M, Teumer A, Dörr M, Gudnason V, Cook J, Ruggiero D, Kolcic I, Boerwinkle E, Traglia M, Lehtimäki T, Raitakari O, Johnson A, Newton-Cheh C, Brown M, Dominiczak A, Sever P, Poulter N, Chambers J, Elosua R, Siscovick D, Esko T, Metspalu A, Strawbridge R, Laakso M, Hamsten A, Hottenga J-J, de Geus E, Morris A, Palmer C, Nolte I, Milaneschi Y, Marten J, Wright A, Zeggini E, Howson J, O'Donnell C, Spector T, Nalls M, Simonsick E, Liu Y, Duijn CV, Butterworth A, Danesh J, Menni C, Wareham N, Khaw K, Denny J, Levy D, Munroe P, Snieder Het al., 2022, Genome-wide analysis in over 1 million individuals reveals over 2,000 independent genetic signals for blood pressure

<jats:title>Abstract</jats:title> <jats:p>Hypertension is a leading cause of premature death affecting more than a billion individuals worldwide. Here we report on the genetic determinants of blood pressure (BP) traits (systolic, diastolic, and pulse pressure) in the largest single-stage genome-wide analysis to date (N = 1,028,980 European-descent individuals). We identified 2,103 independent genetic signals (P &lt; 5x10<jats:sup>− 8</jats:sup>) for BP traits, including 113 novel loci. These associations explain ~ 40% of common SNP heritability of systolic and diastolic BP. Comparison of top versus bottom deciles of polygenic risk scores (PRS) based on these results reveal clinically meaningful differences in BP (12.9 mm Hg for systolic BP, 95% CI 11.5–14.2 mm Hg, p = 9.08×10<jats:sup>− 73</jats:sup>) and hypertension risk (OR 5.41; 95% CI 4.12 to 7.10; P = 9.71×10<jats:sup>− 33</jats:sup>) in an independent dataset. Compared with the area under the curve (AUC) for hypertension discrimination for a model with sex, age, BMI, and genetic ancestry, adding systolic and diastolic BP PRS increased discrimination from 0.791 (95% CI = 0.781–0.801) to 0.814 (95% CI = 0.805–0.824, ∆AUC = 0.023, P = 2.27x10<jats:sup>− 22</jats:sup>). Our transcriptome-wide association study detected 2,793 BP colocalized associations with genetically-predicted expression of 1,070 genes in five cardiovascular tissues, of which 500 are previously unreported for BP traits. These findings represent an advance in our understanding of hypertension and highlight the role of increasingly large genomic studies for development of more accurate PRS, which may inform precision health research.</jats:p>

Journal article

Fraszczyk E, Spijkerman AMW, Zhang Y, Brandmaier S, Day FR, Zhou L, Wackers P, Dolle MET, Bloks VW, Gao X, Gieger C, Kooner J, Kriebel J, Picavet HSJ, Rathmann W, Schottker B, Loh M, Verschuren WMM, Van Vliet-Ostaptchouk JV, Wareham NJ, Chambers JC, Ong KK, Grallert H, Brenner H, Luijten M, Snieder Het al., 2022, Epigenome-wide association study of incident type 2 diabetes: a meta-analysis of five prospective European cohorts, DIABETOLOGIA, Vol: 65, Pages: 763-776, ISSN: 0012-186X

Journal article

Hawe JS, Wilson R, Schmid KT, Zhou L, Lakshmanan LN, Lehne BC, Kuehnel B, Scott WR, Wielscher M, Yew YW, Baumbach C, Lee DP, Marouli E, Bernard M, Pfeiffer L, Matias-Garcia PR, Autio M, Bourgeois S, Herder C, Karhunen V, Meitinger T, Prokisch H, Rathmann W, Roden M, Sebert S, Shin J, Strauch K, Zhang W, Tan WLW, Hauck SM, Merl-Pham J, Grallert H, Barbosa EG, Illig T, Peters A, Paus T, Pausova Z, Deloukas P, Foo RSY, Jarvelin M-R, Kooner JS, Loh M, Heinig M, Gieger C, Waldenberger M, Chambers JCet al., 2022, Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function, NATURE GENETICS, Vol: 54, Pages: 18-+, ISSN: 1061-4036

Journal article

Seneviratne S, Desloge A, Haregu T, Kwasnicka D, Kasturiratne A, Mandla A, Chambers J, Oldenburg Bet al., 2022, Characteristics and Outcomes of Community Health Worker Training to Improve the Prevention and Control of Cardiometabolic Diseases in Low and Middle-Income Countries: A Systematic Review., Inquiry, Vol: 59

Community health workers (CHWs) play an important role in controlling non-communicable diseases in low- and middle-income countries. The aim of this review was to describe the characteristics and outcomes of CHW training programs that focused on the prevention and control of cardiometabolic diseases in low- and middle-income countries (LMICs). Medline, CINAHL Complete, Academic Search Complete, Directory of Open Access Journal, ScienceDirect, ERIC, Gale Academic, and OneFile). Studies that described the training programs used to train CHWs for prevention and control of cardiovascular diseases and type2 diabetes mellitus in LMICs. Only studies that evaluated the outcomes of training programs in at least one of the 4 levels of Kirkpatrick's training evaluation model were included in the review. CHWs who underwent training focused on the prevention and control of cardiovascular disease and type 2 diabetes mellitus. We summarized the resulting evidence using qualitative synthesis through a narrative review. Training outcomes were assessed in relation to (1) CHW reactions to training, their degree of learning, and their behaviors following training, and (2) changes in biochemical and anthropometric indicators in target populations following the CHW program implementation. PROSPERO (CRD42020162116). Thirty-two studies were included. Methods used to train CHWs included: face-to-face lectures, interactive group activities, and blended teaching with online support. Training focused on identifying people with elevated risk of cardiometabolic diseases and their risk factors as well as supporting people to adopt healthy lifestyles. Many studies that utilized trained CHWs did not publish CHW training methods and evaluations, and therefore could not be included in this study. Training programs resulted in an increase in knowledge and skills among CHWs demonstrating that there are certain activities that can be shifted to CHWs following training.

Journal article

Kasturiratne A, Khawaja KI, Ahmad S, Siddiqui S, Shahzad K, Athauda LK, 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 RP, Gage HM, van Valkengoed IGM, Valabhji J, Frost GS, Loh M, Wickremasinghe AR, Kooner JS, Katulanda P, Jha S, Chambers JCet al., 2021, The iHealth-T2D study, prevention of type 2 diabetes amongst South Asians with central obesity and prediabetes: study protocol for a randomised controlled trial, TRIALS, Vol: 22

Journal article

Schlosser P, Tin A, Matias-Garcia PR, Thio CHL, Joehanes R, Liu H, Weihs A, Yu Z, Hoppmann A, Grundner-Culemann F, Min JL, Adeyemo AA, Agyemang C, Arnlov J, Aziz NA, Baccarelli A, Bochud M, Brenner H, Breteler MMB, Carmeli C, Chaker L, Chambers JC, Cole SA, Coresh J, Corre T, Correa A, Cox SR, de Klein N, Delgado GE, Domingo-Relloso A, Eckardt K-U, Ekici AB, Endlich K, Evans KL, Floyd JS, Fornage M, Franke L, Fraszczyk E, Gao X, Gao X, Ghanbari M, Ghasemi S, Gieger C, Greenland P, Grove ML, Harris SE, Hemani G, Henneman P, Herder C, Horvath S, Hou L, Hurme MA, Hwang S-J, Jarvelin M-R, Kardia SLR, Kasela S, Kleber ME, Koenig W, Kooner JS, Kramer H, Kronenberg F, Kuhnel B, Lehtimaki T, Lind L, Liu D, Liu Y, Lloyd-Jones DM, Lohman K, Lorkowski S, Lu AT, Marioni RE, Marz W, McCartney DL, Meeks KAC, Milani L, Mishra PP, Nauck M, Navas-Acien A, Nowak C, Peters A, Prokisch H, Psaty BM, Raitakari OT, Ratliff SM, Reiner AP, Rosas SE, Schottker B, Schwartz J, Sedaghat S, Smith JA, Sotoodehnia N, Stocker HR, Stringhini S, Sundstrom J, Swenson BR, Tellez-Plaza M, van Meurs JBJ, van Vliet-Ostaptchouk JV, Venema A, Verweij N, Walker RM, Wielscher M, Winkelmann J, Wolffenbuttel BHR, Zhao W, Zheng Y, Loh M, Snieder H, Levy D, Waldenberger M, Susztak K, Kottgen A, Teumer Aet al., 2021, Meta-analyses identify DNA methylation associated with kidney function and damage, NATURE COMMUNICATIONS, Vol: 12

Journal article

Graham SE, Clarke SL, Wu K-HH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, Locke AE, Marouli E, Hwang MY, Han S, Narita A, Choudhury A, Bentley AR, Ekoru K, Verma A, Trivedi B, Martin HC, Hunt KA, Hui Q, Klarin D, Zhu X, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Ruotsalainen SE, Havulinna AS, Veturi Y, Feng Q, Rosenthal EA, Lingren T, Pacheco JA, Pendergrass SA, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Hindy G, Rasheed A, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao J-H, Matsuda F, Jang H-M, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Willemsen G, Wood AR, Ji Y, Gao Z, Haworth S, Mitchell RE, Chai JF, Aadahl M, Yao J, Manichaikul A, Warren HR, Ramirez J, Bork-Jensen J, Karhus LL, Goel A, Sabater-Lleal M, Noordam R, Sidore C, Fiorillo E, McDaid AF, Marques-Vidal P, Wielscher M, Trompet S, Sattar N, Mollehave LT, Thuesen BH, Munz M, Zeng L, Huang J, Yang B, Poveda A, Kurbasic A, Lamina C, Forer L, Scholz M, Galesloot TE, Bradfield JP, Daw EW, Zmuda JM, Mitchell JS, Fuchsberger C, Christensen H, Brody JA, Feitosa MF, Wojczynski MK, Preuss M, Mangino M, Christofidou P, Verweij N, Benjamins JW, Engmann J, Kember RL, Slieker RC, Lo KS, Zilhao NR, Phuong L, Kleber ME, Delgado GE, Huo S, Ikeda DD, Iha H, Yang J, Liu J, Leonard HL, Marten J, Schmidt B, Arendt M, Smyth LJ, Canadas-Garre M, Wang C, Nakatochi M, Wong A, Hutri-Kahonen N, Sim X, Xia R, Huerta-Chagoya A, Fernandez-Lopez JC, Lyssenko V, Ahmed M, Jackson AU, Irvin MR, Oldmeadow C, Kim H-N, Ryu S, Timmers PRHJ, Arbeeva L, Dorajoo R, Lange LA, Chai X, Prasad G, Lores-Motta L, Pauper M, Long J, Li X, Theusch E, Takeuchi F, Spracklen CN, Loukola A, Bollepalli S, Warner SC, Wang YX, Wei WB, Nutile T, Ruggiero D, Sung YJ, Hung Y-J, Chen S, Liu F, Yaet al., 2021, The power of genetic diversity in genome-wide association studies of lipids, NATURE, Vol: 600, Pages: 675-+, ISSN: 0028-0836

Journal article

Chen Y, Kassam I, Lau SH, Kooner JS, Wilson R, Peters A, Winkelmann J, Chambers JC, Chow VT, Khor CC, van Dam RM, Teo Y-Y, Loh M, Sim Xet al., 2021, Impact of BMI and waist circumference on epigenome-wide DNA methylation and identification of epigenetic biomarkers in blood: an EWAS in multi-ethnic Asian individuals, CLINICAL EPIGENETICS, Vol: 13, ISSN: 1868-7075

Journal article

Muilwijk M, Loh M, Siddiqui S, Mahmood S, Palaniswamy S, Shahzad K, Athauda LK, Jayawardena R, Batool T, Burney S, Glover M, Bamunuarachchi V, Panda M, Madawanarachchi M, Rai B, Sattar I, Silva W, Waghdhare S, Jarvelin M-R, Rannan-Eliya RP, Wijemunige N, Gage HM, Valabhji J, Frost GS, Wickremasinghe R, Kasturiratne A, Khawaja K, Ahmad S, van Valkengoed IGM, Katulanda P, Jha S, Kooner JS, Chambers JCet al., 2021, Effects of a lifestyle intervention programme after 1 year of follow-up among South Asians at high risk of type 2 diabetes: a cluster randomised controlled trial, BMJ GLOBAL HEALTH, Vol: 6, ISSN: 2059-7908

Journal article

Goyal S, Tanigawa Y, Zhang W, Chai J-F, Almeida M, Sim X, Lerner M, Chainakul J, Ramiu JG, Seraphin C, Apple B, Vaughan A, Muniu J, Peralta J, Lehman DM, Ralhan S, Wander GS, Singh JR, Mehra NK, Sidorov E, Peyton MD, Blackett PR, Curran JE, Tai ES, van Dam R, Cheng C-Y, Duggirala R, Blangero J, Chambers JC, Sabanayagam C, Kooner JS, Rivas MA, Aston CE, Sanghera DKet al., 2021, APOC3 genetic variation, serum triglycerides, and risk of coronary artery disease in Asian Indians, Europeans, and other ethnic groups, LIPIDS IN HEALTH AND DISEASE, Vol: 20

Journal article

Goyal S, Tanigawa Y, Zhang W, Jin-Fang C, Almeida M, Sim X, Lerner M, Chainakul J, Ramiu JG, Seraphin C, Apple B, Vaughan A, Muniu J, Peralta J, Lehman DM, Ralhan S, Wander GS, Singh JR, Mehra NK, Sidorov E, Peyton M, Blackett PR, Curran JE, Tai ES, Van Dam RM, Cheng C-Y, Duggirala R, Blangero J, Chambers JC, Sabanayagam C, Kooner JS, Rivas MA, Sanghera Det al., 2021, ASSOCIATION OF APOCIII COMMON VARIANTS WITH RISK OF CORONARY ARTERY DISEASE: A MENDELIAN RANDOMIZATION STUDY, Publisher: ELSEVIER IRELAND LTD, Pages: E10-E11, ISSN: 0021-9150

Conference paper

Ranjani H, Nitika S, Hariharan R, Charumeena H, Oliver N, Pradeepa R, Chambers JC, Unnikrishnan R, Mohan V, Avari PE, Anjana RMet al., 2021, Systematic review and scientific rating of commercial apps available in India for diabetes prevention, JOURNAL OF DIABETOLOGY, Vol: 12, Pages: 285-+, ISSN: 2543-3288

Journal article

Song P, Gupta A, Goon IY, Hasan M, Mahmood S, Pradeepa R, Siddiqui S, Frost GS, Kusuma D, Miraldo M, Sassi F, Wareham NJ, Ahmed S, Anjana RM, Brage S, Forouhi NG, Jha S, Kasturiratne A, Katulanda P, Khawaja KI, Loh M, Mridha MK, Wickremasinghe AR, Kooner JS, Chambers JCet al., 2021, Data resource profile: Understanding the patterns and determinants of health in South Asians—the South Asia Biobank, International Journal of Epidemiology, Vol: 50, Pages: 717-718e, ISSN: 0300-5771

Journal article

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