OBJECTIVE: This meta-analysis aimed to assess the updated pooled effects of these polymorphisms with DN among Asian populations with type 2 diabetes mellitus.
METHODS: The PubMed electronic database was searched without duration filter until August 2017 and the reference list of eligible studies was screened. The association of each polymorphism with DN was examined using odds ratio and its 95% confidence interval based on dominant, recessive and allele models. Subgroup analyses were conducted based on region, DN definition and DM duration.
RESULTS: In the main analysis, the ACE I/D (all models) and AGTR1 A1166C (dominant model) showed a significant association with DN. The main analysis of the AGT M235T polymorphism did not yield significant findings. There were significant subgroup differences and indication of significantly higher odds for DN in terms of DM duration (≥10 years) for ACE I/D (all models), AGT M235T (recessive and allele models) and AGTR1 A1166C (recessive model). Significant subgroup differences were also observed for DN definition (advanced DN group) and region (South Asia) for AGTR1 A1166C (recessive model).
CONCLUSION: In the Asian populations, ACE I/D and AGTR1 A1166C may contribute to DN susceptibility in patients with T2DM by different genetic models. However, the role of AGT M235T needs to be further evaluated.
INTRODUCTION: A study published in 2001 predicted a 30-50% increase in Singapore hip fracture incidence rates over the ensuing 30 years. To test that prediction, we examined the incidence of hip fracture in Singapore from 2000 to 2017.
METHODS: We carried out a population-based study of hip fractures among Singapore residents aged ≥ 50 years. National medical insurance claims data were used to identify admissions with a primary discharge diagnosis of hip fracture. Age-adjusted rates, based on the age distribution of the Singapore population of 2000, were analyzed separately by sex and ethnicity (Chinese, Malay, or Indian).
RESULTS: Over the 18-year study period, 36,082 first hip fractures were recorded. Total hip fracture admissions increased from 1487 to 2729 fractures/year in the years 2000 to 2017. Despite this absolute increase, age-adjusted fracture rates declined, with an average annual change of - 4.3 (95% CI - 5.0, - 3.5) and - 1.1 (95% CI - 1.7, - 0.5) fractures/100,000/year for women and men respectively. Chinese women had 1.4- and 1.9-fold higher age-adjusted rates than Malay and Indian women: 264 (95% CI 260, 267) versus 185 (95% CI 176, 193) and 141 (95% CI 132, 150) fractures/100,000/year, respectively. Despite their higher fracture rates, Chinese women were the only ethnic group exhibiting a decline, most evident in those ≥ 85 years, in age-adjusted fracture rate of - 5.3 (95% CI - 6.0, - 4.5) fractures/100,000/year.
CONCLUSION: Although the absolute number of fractures increased, steep drops in elderly Chinese women drove a reduction in overall age-adjusted hip fracture rates. Increases in the older population will lead to a rise in total number of hip fractures, requiring budgetary planning and new preventive strategies.
METHODS: To understand the contribution of the X chromosome in NPC susceptibility, we conducted an X chromosome-wide association analysis on 1615 NPC patients and 1025 healthy controls of Guangdong Chinese, followed by two validation analyses in Taiwan Chinese (n = 562) and Malaysian Chinese (n = 716).
RESULTS: Firstly, the proportion of variance of X-linked loci over phenotypic variance was estimated in the discovery samples, which revealed that the phenotypic variance explained by X chromosome polymorphisms was estimated to be 12.63% (non-dosage compensation model) in males, as compared with 0.0001% in females. This suggested that the contribution of X chromosome to the genetic variance of NPC should not be neglected. Secondly, association analysis revealed that rs5927056 in DMD gene achieved X chromosome-wide association significance in the discovery sample (OR = 0.81, 95% CI 0.73-0.89, P = 1.49 × 10-5). Combined analysis revealed rs5927056 for DMD gene with suggestive significance (P = 9.44 × 10-5). Moreover, the female-specific association of rs5933886 in ARHGAP6 gene (OR = 0.62, 95%CI: 0.47-0.81, P = 4.37 × 10-4) was successfully replicated in Taiwan Chinese (P = 1.64 × 10-2). rs5933886 also showed nominally significant gender × SNP interaction in both Guangdong (P = 6.25 × 10-4) and Taiwan datasets (P = 2.99 × 10-2).
CONCLUSION: Our finding reveals new susceptibility loci at the X chromosome conferring risk of NPC and supports the value of including the X chromosome in large-scale association studies.
METHODS: A case control study was conducted among 142 newly diagnosed IHD women patients registered in government hospitals in Terengganu, Malaysia and their 1:1 frequency matched population controls. Data on sociodemographic and socioeconomic profile, co-morbidities, lifestyle factors related to physical activities, dietary fat intake, stress, passive smoking history, anthropometric measurements and biochemical markers were obtained.
RESULTS: Middle aged women were recruited with women diagnosed with diabetes (aOR = 1.92, 95% CI: 1.11-3.31), having low HDL-C (aOR = 3.30, 95% CI: 1.28-8.27), those with positive family history of IHD (aOR = 1.92, 95% CI:1.13-3.26) and passive smokers (aOR = 2.99, 95% CI:1.81-4.94) were at higher odds of IHD.
CONCLUSIONS: The findings are useful for public health interventions and policy making focusing on specific women population.
METHODS: The distribution of polymorphic variants in the SLCO1B1 gene at eight loci that spanned approximately 48 kb was investigated in the three different Asian ethnic groups and in 32 non-cancerous liver tissues from Chinese patients.
RESULTS: Of the 26 polymorphisms screened, we found eight polymorphic variants that differed in genotypic and allelic frequencies between the Chinese, Malay and Indian populations. Significant interethnic differences were observed in the genotype frequency distributions across the promoter SNP [g.-11187G>A (P = 0.030)] as well as three coding region SNPs [c.388G>A (P < 0.001); c.571T>C (P < 0.001); c.597C>T (P < 0.001)] in the healthy subjects. Haplotype analysis revealed 12 different haplotypes in both the Chinese and Malay populations and 18 haplotypes in the Indian population. In both the Malay and Indian populations, the htSNPs were c.388A>G, c.571T>C and c.597C>T, whereas in the Chinese population they were g.-11187G>A, c.388A>G and c.597C>T. The c.388A>G and c.597C>T htSNPs accounted for more than 70% of the variations between the three major haplotypes in each Asian ethnic group. In terms of the c.388A>G htSNPs, genotypic-phenotypic association analyses revealed that there was no effect on SLCO1B1 expression in hepatic tissues; in addition, no genotypic-phenotypic associations were evident with regards to the c.597C>T htSNP.
CONCLUSION: Future studies should investigate the phenotypic effects of the c.388A>G htSNP on the disposition of OATP1B1 substrates in Asian populations.
MATERIALS AND METHODS: Five Malay patients receiving warfarin maintenance therapy were investigated for their CYP2C9*2, CYP2C9*3, and VKORC1-1639G>A genotypes and their vitamin K-dependent (VKD) clotting factor activities. The records of their daily warfarin doses and international normalized ratio (INR) 2 years prior to and after the measurement of VKD clotting factors activities were acquired. The mean warfarin doses were compared with predicted warfarin doses calculated from a genotypic-based dosing model developed for Asians.
RESULTS: A patient with the VKORC1-1639 GA genotype, who was supposed to have higher dose requirements, had a lower mean warfarin dose similar to those having the VKORC1-1639 AA genotype. This discrepancy may be due to the coadministration of celecoxib, which has the potential to decrease warfarins metabolism. Not all patients' predicted mean warfarin doses based on a previously developed dosing algorithm for Asians were similar to the actual mean warfarin dose, with the worst predicted dose being 54.34% higher than the required warfarin dose.
CONCLUSION: Multiple clinical factors can significantly change the actual required dose from the predicted dose from time to time. The additions of other dynamic variables, especially INR, VKD clotting factors, and concomitant drug use, into the dosing model are important in order to improve its accuracy.
OBJECTIVE: Apply machine learning for the prediction and identification of factors associated with short and long-term mortality in Asian STEMI patients and compare with a conventional risk score.
METHODS: The National Cardiovascular Disease Database for Malaysia registry, of a multi-ethnic, heterogeneous Asian population was used for in-hospital (6299 patients), 30-days (3130 patients), and 1-year (2939 patients) model development. 50 variables were considered. Mortality prediction was analysed using feature selection methods with machine learning algorithms and compared to Thrombolysis in Myocardial Infarction (TIMI) score. Invasive management of varying degrees was selected as important variables that improved mortality prediction.
RESULTS: Model performance using a complete and reduced variable produced an area under the receiver operating characteristic curve (AUC) from 0.73 to 0.90. The best machine learning model for in-hospital, 30 days, and 1-year outperformed TIMI risk score (AUC = 0.88, 95% CI: 0.846-0.910; vs AUC = 0.81, 95% CI:0.772-0.845, AUC = 0.90, 95% CI: 0.870-0.935; vs AUC = 0.80, 95% CI: 0.746-0.838, AUC = 0.84, 95% CI: 0.798-0.872; vs AUC = 0.76, 95% CI: 0.715-0.802, p < 0.0001 for all). TIMI score underestimates patients' risk of mortality. 90% of non-survival patients are classified as high risk (>50%) by machine learning algorithm compared to 10-30% non-survival patients by TIMI. Common predictors identified for short- and long-term mortality were age, heart rate, Killip class, fasting blood glucose, prior primary PCI or pharmaco-invasive therapy and diuretics. The final algorithm was converted into an online tool with a database for continuous data archiving for algorithm validation.
CONCLUSIONS: In a multi-ethnic population, patients with STEMI were better classified using the machine learning method compared to TIMI scoring. Machine learning allows for the identification of distinct factors in individual Asian populations for better mortality prediction. Ongoing continuous testing and validation will allow for better risk stratification and potentially alter management and outcomes in the future.
Objectives: To identify novel genome-wide significant loci for PD in Asian individuals and to compare genetic risk between Asian and European cohorts.
Design Setting, and Participants: Genome-wide association data generated from PD cases and controls in an Asian population (ie, Singapore/Malaysia, Hong Kong, Taiwan, mainland China, and South Korea) were collected from January 1, 2016, to December 31, 2018, as part of an ongoing study. Results were combined with inverse variance meta-analysis, and replication of top loci in European and Japanese samples was performed. Discovery samples of 31 575 individuals passing quality control of 35 994 recruited were used, with a greater than 90% participation rate. A replication cohort of 1 926 361 European-ancestry and 3509 Japanese samples was analyzed. Parkinson disease was diagnosed using UK Parkinson's Disease Society Brain Bank Criteria.
Main Outcomes and Measures: Genotypes of common variants, association with disease status, and polygenic risk scores.
Results: Of 31 575 samples identified, 6724 PD cases (mean [SD] age, 64.3 [10] years; age at onset, 58.8 [10.6] years; 3472 [53.2%] men) and 24 851 controls (age, 59.4 [11.4] years; 11 030 [45.0%] men) were analyzed in the discovery study. Eleven genome-wide significant loci were identified; 2 of these loci were novel (SV2C and WBSCR17) and 9 were previously found in Europeans. Replication in European-ancestry and Japanese samples showed robust association for SV2C (rs246814; odds ratio, 1.16; 95% CI, 1.11-1.21; P = 1.17 × 10-10 in meta-analysis of discovery and replication samples) but showed potential genetic heterogeneity at WBSCR17 (rs9638616; I2=67.1%; P = 3.40 × 10-3 for hetereogeneity). Polygenic risk score models including variants at these 11 loci were associated with a significant improvement in area under the curve over the model based on 78 European loci alone (63.1% vs 60.2%; P = 6.81 × 10-12).
Conclusions and Relevance: This study identified 2 apparently novel gene loci and found 9 previously identified European loci to be associated with PD in this large, meta-genome-wide association study in a worldwide population of Asian individuals and reports similarities and differences in genetic risk factors between Asian and European individuals in the risk for PD. These findings may lead to improved stratification of Asian patients and controls based on polygenic risk scores. Our findings have potential academic and clinical importance for risk stratification and precision medicine in Asia.
METHODS: We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants were selected using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB) and include polymorphisms of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 genes. The CYP2D6 gene allele quantification was determined simultaneously with TaqMan copy number assays targeting intron 2 and exon 9 regions. The genotyping results showed high call rate accuracy according to concordance with genotypes identified by independent analyses on Sequenome massarray and droplet digital PCR. Furthermore, 506 genomic samples across three major ethnic groups of Singapore (Malay, Indian and Chinese) were analysed on our workflow.
RESULTS: We found that 98% of our study subjects carry one or more CPIC actionable variants. The major alleles detected include CYP2C9*3, CYP2C19*2, CYP2D6*10, CYP2D6*36, CYP2D6*41, CYP3A5*3 and VKORC1*2. These translate into a high percentage of intermediate (IM) and poor metabolizer (PM) phenotypes for these genes in our population.
CONCLUSION: Genotyping may be useful to identify patients who are prone to drug toxicity with standard doses of drug therapy in our population. The simplicity and robustness of this PGx panel is highly suitable for use in a clinical laboratory.
OBJECTIVE: We aimed to identify a posteriori dietary patterns for Chinese, Malay, and Indian ethnic groups in an urban Asian setting, compare these with a priori dietary patterns, and ascertain associations with cardiovascular disease risk factors including hypertension, obesity, and abnormal blood lipid concentrations.
METHODS: We used cross-sectional data from 8433 Singapore residents (aged 21-94 y) from the Multi-Ethnic Cohort study of Chinese, Malay, and Indian ethnicity. Food consumption was assessed using a validated 169-item food-frequency questionnaire. With the use of 28 food groups, dietary patterns were derived by principal component analysis, and their association with cardiovascular disease risk factors was assessed using multiple linear regression. Associations between derived patterns and a priori patterns (aHEI-2010-Alternative Healthy Eating Index-2010, aMED-alternate Mediterranean Diet, and DASH-Dietary Approaches to Stop Hypertension) were assessed, and the magnitude of associations with risk factors compared.
RESULTS: We identified a "healthy" dietary pattern, similar across ethnic groups, and characterized by high intakes of whole grains, fruit, dairy, vegetables, and unsaturated cooking oil and low intakes of Western fast foods, sugar-sweetened beverages, poultry, processed meat, and flavored rice. This "healthy" pattern was inversely associated with body mass index (BMI; in kg/m2) (-0.26 per 1 SD of the pattern score; 95% CI: -0.36, -0.16), waist circumference (-0.57 cm; 95% CI: -0.82, -0.32), total cholesterol (-0.070 mmol/L; 95% CI: -0.091, -0.048), LDL cholesterol (-0.054 mmol/L; 95% CI: -0.074, -0.035), and fasting triglycerides (-0.22 mmol/L; 95% CI: -0.04, -0.004) and directly associated with HDL cholesterol (0.013 mmol/L; 95% CI: 0.006, 0.021). Generally, "healthy" pattern associations were at least as strong as a priori pattern associations with cardiovascular disease risk factors.
CONCLUSION: A healthful dietary pattern that correlated well with a priori patterns and was associated with lower BMI, serum LDL cholesterol, total cholesterol, and fasting triglyceride concentrations was identified across 3 major Asian ethnic groups.