Modeling biological rhythms in failure time data

BACKGROUND: The human body exhibits a variety of biological rhythms. There are patterns that correspond, among others, to the daily wake/sleep cycle, a yearly seasonal cycle and, in women, the menstrual cycle. Sine/cosine functions are often used to model biological patterns for continuous data, but this model is not appropriate for analysis of biological rhythms in failure time data. METHODS: We adapt the cosinor method to the proportional hazards model and present a method to provide an estimate and confidence interval of the time when the minimum hazard is achieved. We then apply this model to data taken from a clinical trial of adjuvant of pre-menopausal breast cancer patients. RESULTS: The application of this technique to the breast cancer data revealed that the optimal day for pre-resection incisional or excisional biopsy of 28-day cycle (i. e. the day associated with the lowest recurrence rate) is day 8 with 95% confidence interval of 4–12 days. We found that older age, fewer positive nodes, smaller tumor size, and experimental treatment were predictive of longer relapse-free survival. CONCLUSION: In this paper we have described a method for modeling failure time data with an underlying biological rhythm. The advantage of adapting a cosinor model to proportional hazards model is its ability to model right censored data. We have presented a method to provide an estimate and confidence interval of the day in the menstrual cycle where the minimum hazard is achieved. This method is not limited to breast cancer data, and may be applied to any biological rhythms linked to right censored data

The Complex Etiology of Childhood Obesity in Arabs Is Highlighted by a Combination of Biological and Socio-Economic Factors

Objectives: To identify predictors of childhood and adolescent obesity in Kuwaitis with Arab ethnicity.Methods: A cross-sectional sample of 6–18 year-old schoolchildren was randomly selected from 244 public schools across all six governorates in the State of Kuwait. Anthropometric data were measured from 6,574 Arab Kuwaiti schoolchildren, and a structured questionnaire was used to collect information on possible risk factors associated with obesity. Overweight and obesity were defined in accordance with the Center for Disease Control and Prevention criteria.Results: The prevalence of overweight and obesity in children (aged 6–18 years) were 17.7% and 33.7%, respectively. The likelihood of childhood obesity increased with birth weights >4.0 Kg [odds ratio (OR) = 2.3; p < 0.0001], maternal employment (OR = 1.26, p = 0.0006), maternal age at pregnancy >30 years (OR = 1.24; p = 0.0016) and family size of <6 members (OR = 1.16, p = 0.0106).Conclusions: Public health professionals should be aware that advanced maternal age, maternal employment, smaller family size, and high birthweight may predict the risk of obesity in Kuwaiti Arab children and adolescents

Gender Differences in Ghrelin Association with Cardiometabolic Risk Factors in Arab Population

Ghrelin is a stomach produced hormone that has been shown to have protective role against development of CVD which is a leading cause of death in the Arab world. The objective of this study is to examine the gender difference in association between traditional CVD risk factors and plasma ghrelin among Arabs. 359 Arab residents in Kuwait participated in a cross-sectional survey (≥20 years old): 191 were females and 168 were males. Plasma level of ghrelin was assessed using Luminex-based assay. Ghrelin levels were significantly higher in females (935 ± 78 pg/mL) than males (763 ± 65 pg/mL) (P=0.0007). Females showed inverse association with WC (r=-0.23, P=0.001) and HbA1C (r=-0.19, P=0.0102) as well as SBP (r=-0.15, P=0.0383) and DBP (r=-0.16, P=0.0230), respectively. Higher levels of ghrelin were shown to associate with increased insulin resistance, as measured by HOMAIR, in male Arab subjects (P-trend = 0.0202) but not in females. In this study we show that higher ghrelin level was negatively associated with measures of obesity, HbA1C, and blood pressure in females and positively associated with increased insulin resistance in Arab males

Higher plasma betatrophin/ANGPTL8 level in Type 2 Diabetes subjects does not correlate with blood glucose or insulin resistance

Betatrophin/ANGPTL8 is a newly identified hormone produced in liver and adipose tissue that has been shown to be induced as a result of insulin resistance and regulates lipid metabolism. Little is known about betatrophin level in humans and its association with T2D and metabolic risk factors. Plasma level of betatrophin was measured by ELISA in 1603 subjects: 1047 non-diabetic and 556 T2D subjects and its associations with metabolic risk factors in both non-diabetic and T2D were also studied. Our data show a significant difference in betatrophin levels between non-diabetic (731.3 (59.5–10625.0) pg/ml) and T2D (1710.5 (197.4–12361.1) p < 0.001. Betatrophin was positively correlated with age, BMI, waist/hip ratio, FBG, HbA1C, HOMA-IR and TG in the non-diabetic subjects. However, no association was observed with BMI, FBG, HbA1C or HOMA-IR in T2D subjects. TC and LDL showed negative association with betatrophin in T2D subjects. Multivariate analysis showed that subjects in the highest tertile of betatrophin had higher odds of having T2D (odd ratio [OR] = 6.15, 95% confidence interval [CI] = (3.15 – 12.01). Our data show strong positive associations between betatrophin and FBG and insulin resistance in non-diabetic subjects. However, correlations with FBG and insulin resistance were diminished in T2D subjects

Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population

While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/resources, and drug targets generated by global studies to a broad range of ethnic populations. Further, consideration of populations such as Arabs, that are characterized by consanguinity and a high level of inbreeding, can lead to identification of novel risk loci. We imputed published GWAS data from two Kuwaiti Arab cohorts (n = 1434 and 1298) to the 1000 Genomes Project haplotypes and performed meta-analysis for associations with 13 metabolic traits. We compared the observed association signals with those established for metabolic traits. Our study highlighted 70 variants from 9 different genes, some of which have established links to metabolic disorders. By relaxing the genome-wide significance threshold, we identified ‘novel’ risk variants from 11 genes for metabolic traits. Many novel risk variant association signals were observed at or borderline to genome-wide significance. Furthermore, 349 previously established variants from 187 genes were validated in our study. Pleiotropic effect of risk variants on multiple metabolic traits were observed. Fine-mapping illuminated rs7838666/CSMD1 rs1864163/CETP and rs112861901/[INTS10,LPL] as candidate causal variants influencing fasting plasma glucose and high-density lipoprotein levels. Computational functional analysis identified a variety of gene regulatory signals around several variants. This study enlarges the population ancestry diversity of available GWAS and elucidates new variants in an ethnic group burdened with metabolic disorders.Peer reviewe

Genome-wide association study identifies novel risk variants from RPS6KA1, CADPS, VARS, and DHX58 for fasting plasma glucose in Arab population

Consanguineous populations of the Arabian Peninsula, which has seen an uncontrolled rise in type 2 diabetes incidence, are underrepresented in global studies on diabetes genetics. We performed a genome-wide association study on the quantitative trait of fasting plasma glucose (FPG) in unrelated Arab individuals from Kuwait (discovery-cohort:n = 1,353; replication-cohort:n = 1,196). Genome-wide genotyping in discovery phase was performed for 632,375 markers from Illumina HumanOmniExpress Beadchip; and top-associating markers were replicated using candidate genotyping. Genetic models based on additive and recessive transmission modes were used in statistical tests for associations in discovery phase, replication phase, and meta-analysis that combines data from both the phases. A genome-wide significant association with high FPG was found at rs1002487 (RPS6KA1) (p-discovery = 1.64E-08, p-replication = 3.71E-04, p-combined = 5.72E-11; beta-discovery = 8.315; beta-replication = 3.442; beta-combined = 6.551). Further, three suggestive associations (p-values <8.2E-06) with high FPG were observed at rs487321 (CADPS), rs707927 (VARS and 2Kb upstream of VWA7), and rs12600570 (DHX58); the first two markers reached genome-wide significance in the combined analysis (p-combined = 1.83E-12 and 3.07E-09, respectively). Significant interactions of diabetes traits (serum triglycerides, FPG, and glycated hemoglobin) with homeostatic model assessment of insulin resistance were identified for genotypes heterozygous or homozygous for the risk allele. Literature reports support the involvement of these gene loci in type 2 diabetes etiology.Peer reviewe