Novel Risk Factors for Type II Diabetes Mellitus and Coronary Heart Disease

Despite the huge advances made in the understanding of type II diabetes and coronary heart disease (CHD), these diseases still constitute a major health problem. Since the 1950s, epidemiologists focused on chronic disorders, including type II diabetes and CHD. Major aims of their research were to find predisposing factors and to reveal their pathophysiology. In the following decades, multiple traits and life-style behavioral factors were introduced and referred to as “risk factors”. The so called traditional risk factors could explain part of the diseased cases, but a proportion of cases remained unexplained. For instance, obesity was identified as a major risk factor for type II diabetes, but not all patients were overweight. Similarly, it was estimated that at least 50% of CHD events were not caused by the traditional CHD risk factors1. These observations together with the needs for widening our knowledge on the pathogenesis of type II diabetes and CHD and better accuracy of disease prediction, called for moving beyond the known risk factors. In this thesis, we made an attempt to further study two novel risk factors

Variance heterogeneity analysis for detection of potentially interacting genetic loci: Method and its limitations

Background: Presence of interaction between a genotype and certain factor in determination of a trait's value, it is expected that the trait's variance is increased in the group of subjects having this genotype. Thus, test of heterogeneity of variances can be used as a test to screen for potentially interacting single-nucleotide polymorphisms (SNPs). In this work, we evaluated statistical properties of variance heterogeneity analysis in respect to the detection of potentially interacting SNPs in a case when an interaction variable is unknown.Results: Through simulations, we investigated type I error for Bartlett's test, Bartlett's test with prior rank transformation of a tr

Serum uric acid and chronic kidney disease: The role of hypertension

Background: There are inconsistent findings on the role of hyperuricemia as an independent risk factor for chronic kidney disease (CKD). Hypertension has been implicated as a factor influencing the association between serum uric acid and CKD. In this population-based study we investigated the association between serum uric acid and decline in renal function and tested whether hypertension moderates this association. Methods: We included 2601 subjects aged 55 years and over from the Rotterdam Study. Serum uric acid and estimated glomerular filtration rate (eGFR) were assessed at baseline. After average 6.5 years of follow-up, second eGFR was assessed. CKD was defined as eGFR<60 ml/min/1.73 m2. All associations were corrected for socio-demographic and cardiovascular factors. Results: Each unit (mg/dL) increase in serum uric acid was associated with 0.19 ml/min per 1.73 m2 faster annual decline in eGFR. While the association between serum uric acid and incidence of CKD was not significant in our study population (Hazard Ratio: 1.12, 95% confidence interval [CI]: 0.98-1.28), incorporating our results in a meta-analysis with eleven published studies revealed a significant association (Relative Risk: 1.18, 95%CI: 1.15-1.22). In the stratified analyses, we observed that the associations of serum uric acid with eGFR decline and incident CKD were stronger in hypertensive subjects (P for interaction = 0.046 and 0.024, respectively). Conclusions: Our findings suggest that hyperuricemia is independently associated with a decline in renal function. Stronger association in hypertensive individuals may indicate that hypertension mediates the association between serum uric acid and CKD

Novel inflammatory markers for incident pre-diabetes and type 2 diabetes: the Rotterdam Study

The immune response involved in each phase of type 2 diabetes (T2D) development might be different. We aimed to identify novel inflammatory markers that predict progression from normoglycemia to pre-diabetes, incident T2D and insulin therapy. We used plasma levels of 26 inflammatory markers in 971 subjects from the Rotterdam Study. Among them 17 are novel and 9 previously studied. Cox regression models were built to perform survival analysis. Main Outcome Measures: During a follow-up of up to 14.7 years (between April 1, 1997, and Jan 1, 2012) 139 cases of pre-diabetes, 110 cases of T2D and 26 cases of insulin initiation were identified. In age and sex adjusted Cox models, IL13 (HR = 0.78), EN-RAGE (1.30), CFH (1.24), IL18 (1.22) and CRP (1.32) were associated with incident pre-diabetes. IL13 (0.62), IL17 (0.75), EN-RAGE (1.25), complement 3 (1.44), IL18 (1.35), TNFRII (1.27), IL1ra (1.24) and CRP (1.64) were associated with incident T2D. In multivariate models, IL13 (0.77), EN-RAGE (1.23) and CRP (1.26) remained associated with pre-diabetes. IL13 (0.67), IL17 (0.76) and CRP (1.32) remained associated with T2D. IL13 (0.55) was the only marker associated with initiation of insulin therapy in diabetics. Various inflammatory markers are associated with progression from normoglycemia to pre-diabetes (IL13, EN-RAGE, CRP), T2D (IL13, IL17, CRP) or insulin therapy start (IL13). Among them, EN-RAGE is a novel inflammatory marker for pre-diabetes, IL17 for incident T2D and IL13 for pre-diabetes, incident T2D and insulin therapy start

The clinical value of metabolic syndrome and risks of cardiometabolic events and mortality in the elderly: The Rotterdam study

Background: To evaluate the clinical value of metabolic syndrome based on different definitions [American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI), International Diabetes Federation (IDF) and European Group for the Study of Insulin Resistance (EGIR)] in middle-aged and elderly populations. Methods: We studied 8643 participants from the Rotterdam study (1990-2012; mean age 62.7; 57.6% female), a large prospective population-based study with predominantly elderly participants. We performed cox-proportional hazards models for different definitions, triads within definitions and each separate component for the risk of incident type 2 diabetes mellitus, coronary heart disease, stroke, cardiovascular- and all-cause mortality. Results: In our population of 8643 subjects, metabolic syndrome was highly prevalent (prevalence between 19.4 and 42.4%). Metabolic syndrome in general was associated with incident type 2 diabetes mellitus (median follow-up of 6.8years, hazard ratios 3.13-3.78). The associations with coronary heart disease (median follow-up of 7.2years, hazard ratios 1.08-1.32), stroke (median follow-up of 7.7years, hazard ratios 0.98-1.32), cardiovascular mortality (median follow-up of 8.2years, ratios 0.95-1.29) and all-cause mortality (median follow-up of 8.7years, hazard ratios 1.05-1.10) were weaker. AHA/NHLBI- and IDF-definitions showed similar associations with clinical endpoints compared to the EGIR, which was only significantly associated with incident type 2 diabetes mellitus. All significant associations disappeared after correcting metabolic syndrome for its individual components. Conclusions: Large variability exists between and within definitions of the metabolic syndrome with respect to risk of clinical events and mortality. In a relatively old population the metabolic syndrome did not show an additional predictive value on top of its individual components. So, besides as a manner of easy identification of high risk patients, the metabolic syndrome does not seem to add any predictive value for clinical practice