METHODS: The Singapore/Malaysia Cross-Sectional Genetics Epidemiology Study (SMCGES) is an ongoing study which uses established ISAAC guidelines to collect epidemiological data and information pertaining to allergic diseases such as asthma. Responses from young Chinese adults recruited in the National University of Singapore were analyzed.
RESULTS: Lifetime asthma prevalence rate was estimated at 19.1% (2049/10,736), while current asthma prevalence rate was estimated at 6.3% (679/10,736). For ever asthma, the most important risk factor was a parental history of asthma. Increased consumption of pulses (aOR: 0.822, 95% CI: 0.706-0.958) was associated with a lowered odds of ever asthma, but cereals (aOR: 1.256, 95% CI: 1.006-1.580), pasta (aOR: 1.265, 95% CI: 1.027-1.553), butter (aOR: 1.350, 95% CI: 1.113-1.632), and margarine (aOR: 1.343, 95% CI: 1.081-1.660) were associated with a higher risk of ever asthma. Increased television/computer usage was associated with a decreased risk of ever asthma (aOR: 0.448, 95% CI: 0.367-0.545). Conversely, genetic factors had a lower strength of effect on current asthma (parental history of asthma - OR: 1.465, 95% CI: 1.135-1.888) as compared to ever asthma. Only increased potato consumption was significantly associated with an increased risk of current asthma (most or all days per week vs never or only occasionally - aOR: 1.577, 95% CI: 1.145-2.180). Physical activity (aOR: 0.693, 95% CI: 0.542-0.885) was associated with a lower odds of asthma, while second-hand smoke exposure was associated with an increased risk for current asthma (aOR: 1.435, 95% CI: 1.001-2.047).
CONCLUSION: Overall, the prevalence of lifetime asthma and current asthma among young Chinese adults was 19.1% and 6.3%, higher than that of previous studies. Our results suggested a stronger association between genetic factors and ever asthma as compared to current asthma. Parental asthma was the most important intrinsic epidemiological factor for asthma manifestation, while various foods, physical activity levels, and television or computer usage were also significantly associated with asthma. Future studies should consider risk factors in conjunction with other accompanying variables given the potential interactions between them, to discern the effects of environment and lifestyle on asthma more distinctly.
METHODS: GWAS identified an association between genetic variants at 6p21.32 locus and AD. Genotypes of 6p21.32 locus variants were evaluated against LOC100294145 expression in peripheral blood mononuclear cells (PBMCs). Their influence on LOC100294145 promoter activity was measured in vitro via a dual-luciferase assay. The function of LOC100294145 was then elucidated through a combination of co-expression analyses and gene enrichment with g:Profiler. Mendelian randomization was further used to assess the causal regulatory effect of LOC100294145 on its co-expressed genes.
RESULTS: Minor alleles of rs116160149 and rs115388857 at 6p21.32 locus were associated with increased AD risk (p = 2.175 × 10-8, OR = 1.552; p = 2.805 × 10-9, OR = 1.55) and higher LOC100294145 expression in PBMCs (adjusted p = 0.182; 8.267 × 10-12). LOC100294145 expression was also found to be increased in those with AD (adjusted p = 3.653 × 10-2). The genotype effect of 6p21.32 locus on LOC100294145 promoter activity was further validated in vitro. Co-expression analyses predicted LOC100294145 protein's involvement in interleukin-27 and type 1 interferon signaling, which was further substantiated through mendelian randomization.
CONCLUSION: Genetic variants at 6p21.32 locus increase AD susceptibility through raising LOC100294145 expression. A multi-omics approach enabled the deduction of its pathogenesis model comprising dysregulation of hub genes involved in type 1 interferon and interleukin 27 signaling.
METHODS: Young Chinese adults recruited from Singapore in the Singapore/Malaysia Cross-Sectional Genetic Epidemiology Study (SMCGES) were analyzed. We used the International Study of Asthma and Allergies in Childhood (ISAAC) protocol and a skin prick test to determine atopic dermatitis (AD), allergic rhinitis (AR), and asthma status. Information regarding total sleep time (TST) and sleep quality (SQ) was also obtained.
RESULTS: Of 1558 participants with a mean age of 25.0 years (SD = 7.6), 61.4% were female, and the mean total sleep time (TST) was 6.8 h (SD = 1.1). The proportions of AD, AR, and asthma were 24.5% (393/1542), 36.4% (987/1551), and 14.7% (227/1547), respectively. 59.8% (235/393) of AD cases suffered from AD-related sleep disturbances, 37.1% (209/564) of AR cases suffered from AR-related sleep disturbances, and 25.1% (57/227) of asthma cases suffered from asthma-related sleep disturbances. Only asthma cases showed a significantly lower mean TST than those without asthma (p = 0.015). Longer TST was significantly associated with lower odds of AR (OR = 0.905, 95% CI = 0.820-0.999) and asthma (OR = 0.852, 95% CI = 0.746-0.972). Linear regression analyses showed that lower TST was significantly associated with asthma (β = - 0.18, SE = 0.076, p-value = 0.017), and AR when adjusted for AR-related sleep disturbances (β = - 0.157, SE = 0.065, p-value = 0.016). Only sleep disturbances due to AR were significantly associated with a poorer SQ (OR = 1.962, 95% CI = 1.245-3.089).
CONCLUSIONS: We found that sleep quality, but not sleep duration was significantly poorer among AD cases, although the exact direction of influence could not be determined. In consideration of the literature coupled with our findings, we posit that TST influences allergic rhinitis rather than vice versa. Finally, the association between TST and asthma is likely mediated by asthma-related sleep disturbances, since mean TST was significantly lower among those with nighttime asthma symptoms. Future studies could consider using objective sleep measurements coupled with differential expression analysis to investigate the pathophysiology of sleep and allergic diseases.
METHODS: There are 3 objectives in our study. We first aim to update the epidemiological status of AD amongst young adults in Singapore and Malaysia, in particular amongst the Chinese ethnic background. Next, we re-evaluated the possible associated risk factors, identified in our previous meta-analysis and review studies, on the current cohort. Finally, we described here a detailed disease presentation and symptoms profile of our Singapore and Malaysia Cross-Sectional Genetics Epidemiology Study (SMCGES) cohort, which forms the base population for the discovery of associated genetic factors in relation to asthma, allergic diseases and skin conditions. Based on a skin prick test (SPT) and investigator-administered medical history responses, we assessed the AD profiles of 11 494 participants and the significant modifiable and non-modifiable factors associated with disease presentation.
RESULTS: The prevalence of AD in the combined population was 13.5%. Chronic and moderate/severe AD were observed in 35.5% and 40.5% of the individuals with AD, respectively. Family history of atopic diseases, prior history of drug allergies, a history of acne, increased household family monthly income, higher number of individuals in the shared household, parental education, sedentary lifestyle, physical activities, alcoholic consumption, and even quality of diet was significantly associated with AD presentation, chronicity, and severity. Among all the factors evaluated, family and personal history of atopic diseases imposed the strongest associated risk.
CONCLUSIONS: These findings supported our previous review studies and affirmed that familial history or genetic factors critically influence the development of AD in our population and environment. Environmental and other modifiable factors can also trigger AD throughout the lifetime of individuals who have especially inherited the atopic disease disposition. A better understanding of how these risk factors affect AD individuals in our population can facilitate disease surveillance, monitor disease control, and serve as a description for our future genetic epidemiology studies.
METHODS: We evaluated the association between the dietary intake of 16 food types and AD manifestations using our Singapore/Malaysia Cross-sectional Genetics Epidemiology Study (SMCGES) population. Dietary habits profiles of 11,494 young Chinese adults (1,550 AD cases/2,978 non-atopic controls/6,386 atopic controls) were assessed by an investigator-administered questionnaire. AD cases were further evaluated for their chronicity (550 chronic) and severity (628 moderate-to-severe). Additionally, we derived a novel food index, Quality of Diet based on Glycaemic Index Score (QDGIS), to examine the association between dietary intake of glycaemic index (GI) and various AD phenotypes.
RESULTS: The majority of AD subjects are distributed in the good (37.1%) and moderate (36.2%) QDGIS classes. From the multivariable analyses for age and gender, a moderate QDGIS class was significantly associated with a lower odds of AD (adjusted odds ratio (AOR): 0.844; 95% confidence interval (CI): 0.719-0.991; p < 0.05) and moderate-to-severe AD (AOR: 0.839; 95% CI: 0.714-0.985; p < 0.05). A good QDGIS class was only significantly associated with a lower odds of chronic AD (AOR: 0.769; 95% CI: 0.606-0.976; p < 0.05). Among high GI foods, frequent consumption of burgers/fast food was strongly associated with an increased risk of chronic and moderate-to-severe AD. Among low GI foods, increased intake frequencies of fruits, vegetables, and pulses decreased the odds of AD. Finally, we identified significant associations between frequent seafood, margarine, butter, and pasta consumption with an increased odds of AD despite them having little GI values.
CONCLUSION: While genetic components are well-established in their risks associated with increased AD prevalence, there is still a lack of a focus epidemiology study associating dietary influence with AD. Based on the first allergic epidemiology study conducted here in Singapore and Malaysia, it laid the groundwork to guide potential dietary interventions from changing personal dietary habits.