Publications
214 results found
Leong W-Y, Gupta A, Hasan M, et 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.
Yengo L, Vedantam S, Marouli E, et al., 2022, A saturated map of common genetic variants associated with human height, NATURE, Vol: 610, Pages: 704-+, ISSN: 0028-0836
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- Citations: 6
Muilwijk M, Loh M, Mahmood S, et 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
Ramdas S, Judd J, Graham SE, et 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
Winkler TW, Rasheed H, Teumer A, et 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.
Mahajan A, Spracklen CN, Zhang W, et 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
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- Citations: 18
Loh M, Zhang W, Ng HK, et al., 2022, Identification of genetic effects underlying type 2 diabetes in South Asian and European populations (vol 5, 329, 2022), COMMUNICATIONS BIOLOGY, Vol: 5
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.
Loh M, Zhang W, Ng HK, et 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.
Fraszczyk E, Spijkerman AMW, Zhang Y, et 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
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- Citations: 7
Hawe JS, Wilson R, Schmid KT, et al., 2022, Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function, NATURE GENETICS, Vol: 54, Pages: 18-+, ISSN: 1061-4036
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- Citations: 18
Kasturiratne A, Khawaja KI, Ahmad S, et 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
Tin A, Schlosser P, Matias-Garcia PR, et al., 2021, Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus, NATURE COMMUNICATIONS, Vol: 12
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- Citations: 3
Schlosser P, Tin A, Matias-Garcia PR, et al., 2021, Meta-analyses identify DNA methylation associated with kidney function and damage, NATURE COMMUNICATIONS, Vol: 12
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- Citations: 6
Graham SE, Clarke SL, Wu K-HH, et al., 2021, The power of genetic diversity in genome-wide association studies of lipids, NATURE, Vol: 600, Pages: 675-+, ISSN: 0028-0836
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- Citations: 60
Chen Y, Kassam I, Lau SH, et 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
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- Citations: 5
Muilwijk M, Loh M, Siddiqui S, et 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
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- Citations: 1
Goyal S, Tanigawa Y, Zhang W, et 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
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- Citations: 5
Goyal S, Tanigawa Y, Zhang W, et 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
Song P, Gupta A, Goon IY, et 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
Goodrich JK, Singer-Berk M, Son R, et al., 2021, Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes, NATURE COMMUNICATIONS, Vol: 12, ISSN: 2041-1723
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- Citations: 19
Chen J, Spracklen CN, Marenne G, et al., 2021, The trans-ancestral genomic architecture of glycemic traits, Nature Genetics, Vol: 53, Pages: 840-860, ISSN: 1061-4036
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10−8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
Surendran P, Feofanova EV, Lahrouchi N, et al., 2021, Publisher Correction: Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals, Nature Genetics, Vol: 53, Pages: 1-2, ISSN: 1061-4036
Cummings BB, Karczewski KJ, Kosmicki JA, et al., 2021, Author Correction: Transcript expression-aware annotation improves rare variant interpretation.
Gerber RT, ASP S, Sachdev B, et al., 2015, Reproducibilty of the syntax score in a real world setting: implications for the choice of contemporary revascularisation strategy, BCS, Pages: A20-A21
Yaghootkar H, Scott RA, White CC, et al., 2014, Genetic evidence for a normal-weight "metabolically obese" phenotype linking insulin resistance, hypertension, coronary artery disease, and type 2 diabetes, Diabetes, Vol: 63, Pages: 4369-4377, ISSN: 0012-1797
The mechanisms that predispose to hypertension, coronary artery disease (CAD), and type 2 diabetes (T2D) in individuals of normal weight are poorly understood. In contrast, in monogenic primary lipodystrophy—a reduction in subcutaneous adipose tissue—it is clear that it is adipose dysfunction that causes severe insulin resistance (IR), hypertension, CAD, and T2D. We aimed to test the hypothesis that common alleles associated with IR also influence the wider clinical and biochemical profile of monogenic IR. We selected 19 common genetic variants associated with fasting insulin–based measures of IR. We used hierarchical clustering and results from genome-wide association studies of eight nondisease outcomes of monogenic IR to group these variants. We analyzed genetic risk scores against disease outcomes, including 12,171 T2D cases, 40,365 CAD cases, and 69,828 individuals with blood pressure measurements. Hierarchical clustering identified 11 variants associated with a metabolic profile consistent with a common, subtle form of lipodystrophy. A genetic risk score consisting of these 11 IR risk alleles was associated with higher triglycerides (β = 0.018; P = 4 × 10−29), lower HDL cholesterol (β = −0.020; P = 7 × 10−37), greater hepatic steatosis (β = 0.021; P = 3 × 10−4), higher alanine transaminase (β = 0.002; P = 3 × 10−5), lower sex-hormone-binding globulin (β = −0.010; P = 9 × 10−13), and lower adiponectin (β = −0.015; P = 2 × 10−26). The same risk alleles were associated with lower BMI (per-allele β = −0.008; P = 7 × 10−8) and increased visceral-to-subcutaneous adipose tissue ratio (β = −0.015; P = 6 × 10−7). Individuals carrying ≥17 fasting insulin–raising alleles (5.5% population) were slimmer (0.30 kg/m2) but at increased risk of T2D (odds ratio [OR] 1.46; per-allele P = 5
Wood AR, Esko T, Yang J, et al., 2014, Defining the role of common variation in the genomic and biological architecture of adult human height, Nature Genetics, Vol: 46, Pages: 1173-1186, ISSN: 1546-1718
Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ~2,000, ~3,700 and ~9,500 SNPs explained ~21%, ~24% and ~29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate–related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
Xi B, Takeuchi F, Meirhaeghe A, et al., 2014, Associations of genetic variants in/near body mass index-associated genes with type 2 diabetes: a systematic meta-analysis, CLINICAL ENDOCRINOLOGY, Vol: 81, Pages: 702-710, ISSN: 0300-0664
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- Citations: 29
Chen L, Kostadima M, Martens JHA, et al., 2014, Transcriptional diversity during lineage commitment of human blood progenitors, SCIENCE, Vol: 345, Pages: 1580-+, ISSN: 0036-8075
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- Citations: 175
Chambers JC, Abbott J, Zhang W, et al., 2014, The South Asian Genome, PLOS One, Vol: 9, ISSN: 1932-6203
The genetic sequence variation of people from the Indian subcontinent who comprise one-quarter of the world's population, is not well described. We carried out whole genome sequencing of 168 South Asians, along with whole-exome sequencing of 147 South Asians to provide deeper characterisation of coding regions. We identify 12,962,155 autosomal sequence variants, including 2,946,861 new SNPs and 312,738 novel indels. This catalogue of SNPs and indels amongst South Asians provides the first comprehensive map of genetic variation in this major human population, and reveals evidence for selective pressures on genes involved in skin biology, metabolism, infection and immunity. Our results will accelerate the search for the genetic variants underlying susceptibility to disorders such as type-2 diabetes and cardiovascular disease which are highly prevalent amongst South Asians.
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