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Background Disparities in COVID-19 outcomes exist on the basis of ethnicity and comorbidities. Minority ethnic groups in the UK are known to have poorer COVID-19 outcomes, but also an increased prevelance of certain comorbidities associated with severe outcomes. Additionally, despite the prevalence of certain psychiatric disorders there is a lack of research establishing their relationship with COVID-19 outcomes. Methods We used UK Biobank data, involving 472,182 participants, to test for an association between comorbidities and COVID-19 diagnosis ( n  = 30,901); and to test for an association between comorbidities and severe COVID-19 ( n  = 3182). This was done by performing univariable and multivariable logistic regression analysis, estimating odds ratios (ORs) and their 95% confidence intervals (95% CIs). The comorbidities studied were coronary heart disease (CHD), hypertension, type II diabetes mellitus (T2DM), obesity, chronic kidney disease (CKD), depression and anxiety. Multivariable models were adjusted for various socioeconomic, demographic and health-related confounders. We then performed sub-group analysis by common UK ethnic groups (White, South Asian, and Black). Results Increased prevalence of all studied comorbidities was seen in both outcomes, compared to the rest of the cohort. All studied comorbidities were associated with an increased risk of COVID-19 infection and severity across all models. For example, the adjusted ORs (95% CI) for depression were 1.112 (1.083 – 1.161) for COVID-19 diagnosis and 2.398 (2.163 – 2.658) for severe COVID-19. Sub-group analysis revealed stronger associations of COVID-19 diagnosis and severe COVID-19 for South-Asian participants for CHD (OR 1.585 [95% CI 1.194–2.105] for COVID-19 diagnosis and 3.021 [1.683–5.390] for severe COVID-19), hypertension (1.488 [1.231–1.799]; 3.399 [1.862–6.206]) and T2DM (1.671 [1.346–2.076]; 5.412 [3.130–9.357]) compared to White participants (1.264 [1.195–1.336] and 1.627 [1.441–1.837] for CHD; 1.131 [1.097–1.116] and 2.075 [1.885–2.284] for hypertension; 1.402 [1.331–1.476] and 2.890 [2.596–3.216] for T2DM). Similar results were seen for Black participants with CKD and hypertension. Conclusion Specific comorbidities are risk factors for poorer COVID-19 outcomes, supporting targeted interventions and policy aimed at individuals with these comorbidities. Although further research is required, there’s also a need for targeted policies for ethnic minorities assessing the unique reasons they are at greater risk of poor COVID-19 outcomes.

DNA methylation plays a fundamental role in the regulation of the genome, but the optimal strategy for analysis of genome-wide DNA methylation data remains to be determined. We developed a comprehensive analysis pipeline for epigenome-wide association studies (EWAS) using the Illumina Infinium HumanMethylation450 BeadChip, based on 2,687 individuals, with 36 samples measured in duplicate. We propose new approaches to quality control, data normalisation and batch correction through control-probe adjustment and establish a null hypothesis for EWAS using permutation testing. Our analysis pipeline outperforms existing approaches, enabling accurate identification of methylation quantitative trait loci for hypothesis driven follow-up experiments.

Background COVID-19 manifests with huge heterogeneity in susceptibility and severity outcomes. UK Black Asian and Minority Ethnic (BAME) groups have demonstrated disproportionate burdens. Some variability remains unexplained, suggesting potential genetic contribution. Polygenic Risk Scores (PRS) can determine genetic predisposition to disease based on Single Nucleotide Polymorphisms (SNPs) within the genome. COVID-19 PRS analyses within non-European samples are extremely limited. We applied a multi-ethnic PRS to a UK-based cohort to understand genetic contribution to COVID-19 variability. Methods We constructed two PRS for susceptibility and severity outcomes based on leading risk-variants from the COVID-19 Host Genetics Initiative. Scores were applied to 447,382 participants from the UK-Biobank. Associations with COVID-19 outcomes were assessed using binary logistic regression and discriminative power was validated using incremental area under receiver operating curve (ΔAUC). Variance explained was compared between ethnic groups via incremental pseudo-R 2 (ΔR 2 ). Results Compared to those at low genetic risk, those at high risk had a significantly greater risk of severe COVID-19 for White (odds ratio [OR] 1.57, 95% confidence interval [CI] 1.42–1.74), Asian (OR 2.88, 95% CI 1.63–5.09) and Black (OR 1.98, 95% CI 1.11–3.53) ethnic groups. Severity PRS performed best within Asian (ΔAUC 0.9%, ΔR 2 0.98%) and Black (ΔAUC 0.6%, ΔR 2 0.61%) cohorts. For susceptibility, higher genetic risk was significantly associated with COVID-19 infection risk for the White cohort (OR 1.31, 95% CI 1.26–1.36), but not for Black or Asian groups. Conclusions Significant associations between PRS and COVID-19 outcomes were elicited, establishing a genetic basis for variability in COVID-19. PRS showed utility in identifying high-risk individuals. The multi-ethnic approach allowed applicability of PRS to diverse populations, with the severity model performing well within Black and Asian cohorts. Further studies with larger sample sizes of non-White samples are required to increase statistical power and better assess impacts within BAME populations.

Insulin resistance and related metabolic disturbances are major risk factors for the higher T2D risk and associated morbidity and mortality amongst South Asians. The contribution of physical activity to the increased prevalence of insulin resistance and related disturbances amongst South Asians is unknown. We recruited 902 South Asian and European men and women, aged 35-85 years from the ongoing LOLIPOP study. Clinical characterisation comprised standardised questionnaire and measurement of height, weight, waist and hip circumference and blood pressure. Fasting bloods were taken for assessment of glucose, insulin, lipids and HbA1c. Physical activity was quantified using a validated accelerometer, Actigraph GT3X+, worn for 7 days. Univariate and multivariate approaches were used to investigate the relationship between ethnicity, physical activity, insulin resistance and related metabolic disturbances. Total physical activity was ~31% (P = 0.01) lower amongst South Asians compared to Europeans (Mean MET.minutes [SD]: 1505.2 [52] vs. 2050.9 [86.6], P<0.001). After adjusting for age and sex, total physical activity had a negative association with HOMA-IR (B [SE]: -0.18 [0.08], P = 0.04) and fasting glucose levels (B[SE]: -0.11 [0.04], P = 0.02). There was no association between physical activity and other glycemic and lipid parameters. Total physical activity per week contributed towards the differences in insulin resistance and associated metabolic disturbances between South Asians and Europeans. Lower levels of physical activity may contribute to the increased insulin resistance in South Asians compared to Europeans. Our results suggest that lifestyle modification through increased physical activity may help to improve glucose metabolism and reduce the burden of excess T2D and related complications amongst South Asians.

DNA methylation variations are prevalent in human obesity but evidence of a causative role in disease pathogenesis is limited. Here, we combine epigenome-wide association and integrative genomics to investigate the impact of adipocyte DNA methylation variations in human obesity. We discover extensive DNA methylation changes that are robustly associated with obesity (N = 190 samples, 691 loci in subcutaneous and 173 loci in visceral adipocytes, P < 1 × 10-7). We connect obesity-associated methylation variations to transcriptomic changes at >500 target genes, and identify putative methylation-transcription factor interactions. Through Mendelian Randomisation, we infer causal effects of methylation on obesity and obesity-induced metabolic disturbances at 59 independent loci. Targeted methylation sequencing, CRISPR-activation and gene silencing in adipocytes, further identifies regional methylation variations, underlying regulatory elements and novel cellular metabolic effects. Our results indicate DNA methylation is an important determinant of human obesity and its metabolic complications, and reveal mechanisms through which altered methylation may impact adipocyte functions. DNA methylation variation is associated with human obesity but a whether it plays a causal role in disease pathogenesis is unclear. Here, the authors perfom an integrative genomic study in human adipocytes to show that DNA methylation variations contribute to obesity and type 2 diabetes susceptibility, revealing underlying genomic and molecular mechanisms.

Background The prevalence of obesity and its related chronic diseases have been increasing especially in Asian countries. Obesity-related genetic variants have been identified, but these explain little of the variation in BMI. Recent studies reported associations between DNA methylation and obesity, mostly in non-Asian populations. Methods We performed an epigenome-wide association study (EWAS) on general adiposity (body mass index, BMI) and abdominal adiposity (waist circumference, WC) in 409 multi-ethnic Asian individuals and replicated BMI and waist-associated DNA methylation CpGs identified in other populations. The cross-lagged panel model and Mendelian randomization were used to assess the temporal relationship between methylation and BMI. The temporal relationship between the identified CpGs and inflammation and metabolic markers was also examined. Results EWAS identified 116 DNA methylation CpGs independently associated with BMI and eight independently associated with WC at false discovery rate P FDR  < 0.05 in 409 Asian samples. We replicated 110 BMI-associated CpGs previously reported in Europeans and identified six novel BMI-associated CpGs and two novel WC-associated CpGs. We observed high consistency in association direction of effect compared to studies in other populations. Causal relationship analyses indicated that BMI was more likely to be the cause of DNA methylation alteration, rather than the consequence. The causal analyses using BMI-associated methylation risk score also suggested that higher levels of the inflammation marker IL-6 were likely the consequence of methylation change. Conclusion Our study provides evidence of an association between obesity and DNA methylation in multi-ethnic Asians and suggests that obesity can drive methylation change. The results also suggested possible causal influence that obesity-related methylation changes might have on inflammation and lipoprotein levels.

Recent genome-wide association scans (GWAS) and meta-analysis studies on European populations have identified many genes previously implicated in lipid regulation. Validation of these loci on different global populations is important in determining their clinical relevance, particularly for development of novel drug targets for treating and preventing diabetic dyslipidemia and coronary artery disease (CAD). In an attempt to replicate GWAS findings on a non-European sample, we examined the role of six of these loci (CELSR2-PSRC1-SORT1 rs599839; CDKN2A-2B rs1333049; BUD13-ZNF259 rs964184; ZNF259 rs12286037; CETP rs3764261; APOE-C1-C4-C2 rs4420638) in our Asian Indian cohort from the Sikh Diabetes Study (SDS) comprising 3,781 individuals (2,902 from Punjab and 879 from the US). Two of the six SNPs examined showed convincing replication in these populations of Asian Indian origin. Our study confirmed a strong association of CETP rs3764261 with high-density lipoprotein cholesterol (HDL-C) (p = 2.03×10(-26)). Our results also showed significant associations of two GWAS SNPs (rs964184 and rs12286037) from BUD13-ZNF259 near the APOA5-A4-C3-A1 genes with triglyceride (TG) levels in this Asian Indian cohort (rs964184: p = 1.74×10(-17); rs12286037: p = 1.58×10(-2)). We further explored 45 SNPs in a ∼195 kb region within the chromosomal region 11q23.3 (encompassing the BUD13-ZNF259, APOA5-A4-C3-A1, and SIK3 genes) in 8,530 Asian Indians from the London Life Sciences Population (LOLIPOP) (UK) and SDS cohorts. Five more SNPs revealed significant associations with TG in both cohorts individually as well as in a joint meta-analysis. However, the strongest signal for TG remained with BUD13-ZNF259 (rs964184: p = 1.06×10(-39)). Future targeted deep sequencing and functional studies should enhance our understanding of the clinical relevance of these genes in dyslipidemia and hypertriglyceridemia (HTG) and, consequently, diabetes and CAD.

South Asians are 1/4 of the world's population and have increased susceptibility to central obesity and related cardiometabolic disease. Knowledge of genetic variants affecting risk of central obesity is largely based on genome-wide association studies of common SNPs in Europeans. To evaluate the contribution of DNA sequence variation to the higher levels of central obesity (defined as waist hip ratio adjusted for body mass index, WHR) among South Asians compared to Europeans we carried out: i) a genome-wide association analysis of >6M genetic variants in 10,318 South Asians with focused analysis of population-specific SNPs; ii) an exome-wide association analysis of ~250K SNPs in protein-coding regions in 2,637 South Asians; iii) a comparison of risk allele frequencies and effect sizes of 48 known WHR SNPs in 12,240 South Asians compared to Europeans. In genome-wide analyses, we found no novel associations between common genetic variants and WHR in South Asians at P<5x10-8; variants showing equivocal association with WHR (P<1x10-5) did not replicate at P<0.05 in an independent cohort of South Asians (N = 1,922) or in published, predominantly European meta-analysis data. In the targeted analyses of 122,391 population-specific SNPs we also found no associations with WHR in South Asians at P<0.05 after multiple testing correction. Exome-wide analyses showed no new associations between genetic variants and WHR in South Asians, either individually at P<1.5x10-6 or grouped by gene locus at P<2.5x10-6. At known WHR loci, risk allele frequencies were not higher in South Asians compared to Europeans (P = 0.77), while effect sizes were unexpectedly smaller in South Asians than Europeans (P<5.0x10-8). Our findings argue against an important contribution for population-specific or cosmopolitan genetic variants underlying the increased risk of central obesity in South Asians compared to Europeans.

Common Genetic Variation Near Melatonin Receptor MTNR1B Contributes to Raised Plasma Glucose and Increased Risk of Type 2 Diabetes Among Indian Asians and European Caucasians John C. Chambers 1 , Weihua Zhang 1 , Delilah Zabaneh 1 , Joban Sehmi 2 , Piyush Jain 2 , Mark I. McCarthy 3 , Philippe Froguel 4 , 5 , Aimo Ruokonen 6 , David Balding 1 , Marjo-Riitta Jarvelin 1 , 7 , James Scott 2 , Paul Elliott 1 and Jaspal S. Kooner 2 1 Department of Epidemiology and Public Health, Imperial College London, London, U.K.; 2 National Heart and Lung Institute, Imperial College London, London, U.K.; 3 Oxford Centre for Diabetes, Endocrinology and Metabolism and Oxford National Institute for Health Research, Biomedical Research Centre, Oxford, U.K.; 4 Section of Genomic Medicine, Imperial College London, London, U.K., and the Centre National de la Recherche Scientifique, 8090-Institute of Biology, Pasteur Institute, Lille, France; 5 UMR 8090-Institute of Biology, Pasteur Institute, Lille, France; 6 Department of Clinical Sciences/Clinical Chemistry, University Hospital Oulu, Oulu, Finland; 7 Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland, and Department of Child and Adolescent Health, National Institute of Health and Welfare, Helsinki, Finland. Corresponding author: Jaspal S. Kooner, j.kooner{at}imperial.ac.uk . Abstract OBJECTIVE Fasting plasma glucose and risk of type 2 diabetes are higher among Indian Asians than among European and North American Caucasians. Few studies have investigated genetic factors influencing glucose metabolism among Indian Asians. RESEARCH DESIGN AND METHODS We carried out genome-wide association studies for fasting glucose in 5,089 nondiabetic Indian Asians genotyped with the Illumina Hap610 BeadChip and 2,385 Indian Asians (698 with type 2 diabetes) genotyped with the Illumina 300 BeadChip. Results were compared with findings in 4,462 European Caucasians. RESULTS We identified three single nucleotide polymorphisms (SNPs) associated with glucose among Indian Asians at P < 5 × 10 −8 , all near melatonin receptor MTNR1B . The most closely associated was rs2166706 (combined P = 2.1 × 10 −9 ), which is in moderate linkage disequilibrium with rs1387153 ( r 2 = 0.60) and rs10830963 ( r 2 = 0.45), both previously associated with glucose in European Caucasians. Risk allele frequency and effect sizes for rs2166706 were similar among Indian Asians and European Caucasians: frequency 46.2 versus 45.0%, respectively ( P = 0.44); effect 0.05 (95% CI 0.01–0.08) versus 0.05 (0.03–0.07 mmol/l), respectively, higher glucose per allele copy ( P = 0.84). SNP rs2166706 was associated with type 2 diabetes in Indian Asians (odds ratio 1.21 [95% CI 1.06–1.38] per copy of risk allele; P = 0.006). SNPs at the GCK , GCKR , and G6PC2 loci were also associated with glucose among Indian Asians. Risk allele frequencies of rs1260326 ( GCKR ) and rs560887 ( G6PC2 ) were higher among Indian Asians compared with European Caucasians. CONCLUSIONS Common genetic variation near MTNR1B influences blood glucose and risk of type 2 diabetes in Indian Asians. Genetic variation at the MTNR1B , GCK , GCKR , and G6PC2 loci may contribute to abnormal glucose metabolism and related metabolic disturbances among Indian Asians. Footnotes The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Received December 29, 2008. Accepted July 13, 2009. © 2009 American Diabetes Association

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. Trial registration EudraCT 2016–001,350-18 . Registered on 14 April 2016. ClinicalTrials.gov NCT02949739 . Registered on 31 October 2016.