Highlights d Discovery of 52 million novel variants by 13.73 WGS of 4,810 Singaporeans d Insights into population structure and evolutionary history of Asians d Identification of 20 loci under selection that are enriched for GWAS signals d Substantial improvement of imputation in diverse Asian and Oceanian populations

Asian populations are currently underrepresented in human genetics research. Here we present whole-genome sequencing data of 4,810 Singaporeans from three diverse ethnic groups: 2,780 Chinese, 903 Malays, and 1,127 Indians. Despite a medium depth of 13.7×, we achieved essentially perfect (>99.8%) sensitivity and accuracy for detecting common variants and good sensitivity (>89%) for detecting extremely rare variants with <0.1% allele frequency. We found 89.2 million single-nucleotide polymorphisms (SNPs) and 9.1 million small insertions and deletions (INDELs), more than half of which have not been cataloged in dbSNP. In particular, we found 126 common deleterious mutations (MAF>0.01) that were absent in the existing public databases, highlighting the importance of local population reference for genetic diagnosis. We describe fine-scale genetic structure of Singapore populations and their relationship to worldwide populations from the 1000 Genomes Project. In addition to revealing noticeable amounts of admixture among three Singapore populations and a Malay-related novel ancestry component that has not been captured by the 1000 Genomes Project, our analysis also identified some fine-scale features of genetic structure consistent with two waves of prehistoric migration from south China to Southeast Asia. Finally, we demonstrate that our data can substantially improve genotype imputation not only for Singapore populations, but also for populations across Asia and Oceania. These results highlight the genetic diversity in Singapore and the potential impacts of our data as a resource to empower human genetics discovery in a broad geographic region.

The findings suggest that visceral adiposity is associated with DR in individuals with longstanding T2D. This relationship may be attributable to generalized vascular injury as reflected by coexisting renal burden. Therefore, effective management of visceral adiposity and ameliorating renal burden may ameliorate susceptibility to DR.

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Diabetes is a risk factor for developing severe COVID-19, but the pathogenesis remains unclear. We investigated if the association of diabetes and COVID-19 severity may be mediated by inflammation. We also hypothesized that this increased risk may extend to prediabetes. Hospitalized patients in Singapore with COVID-19 were subdivided into three groups in a retrospective cohort: normoglycemia (HbA1c: ≤5.6%), prediabetes (HbA1c: 5.7%-6.4%) and diabetes (HbA1c: ≥6.5%). The primary outcome of severe COVID-19 was defined by respiratory rate ≥30, SpO2 ≤93% or intensive care unit admission. The association between clinical factors on severe COVID-19 outcome was analyzed by cox regression. Adjusted mediation analysis of C-reactive protein (CRP) on the relationship between diabetes and severe COVID-19 was performed. Of 1042 hospitalized patients, mean age 39 ± 11 years, 13% had diabetes, 9% prediabetes and 78% normoglycemia. Severe COVID-19 occurred in 4.9% of subjects. Compared to normoglycemia, diabetes was significantly associated with severe COVID-19 on both univariate (hazard ratio [HR]: 9.94; 95% confidence interval [CI]: 5.54-17.84; p < .001) and multivariate analysis (HR: 3.99; 95% CI: 1.92-8.31; p < .001), while prediabetes was not a risk factor (HR: 0.94; 95% CI: 0.22-4.03; p = .929). CRP, a biomarker of inflammation, mediated 32.7% of the total association between diabetes and severe COVID-19 outcome. In conclusion, CRP is a partial mediator of the association between diabetes and severe COVID-19 infection, confirming that inflammation is important in the pathogenesis of severe COVID-19 in diabetes.