Yandiswa Y. Yako

Air pollution and risk of type 2 diabetes mellitus: A systematic review and meta-analysis

AIM Whether exposure to relatively high levels of air pollution is associated with diabetes occurrence remains unclear. We sought to assess and quantify the association between exposure to major air pollutants and risk of type 2 diabetes. METHODS PubMed and EMBASE databases (through September 2013) were searched using a combination of terms related to exposure to gaseous (NO2 and NOx) or particulate matter pollutants (PM2.5, PM10 and PM10-2.5) and type 2 diabetes. Descriptive and quantitative information were extracted from selected studies. We used random-effects models meta-analysis to derive overall risk estimates per type of pollutant. RESULTS We included ten studies (five cross-sectional and five prospective), assessing the effects of air pollutants on the occurrence of diabetes. In prospective investigations, the overall effect on diabetes occurrence was significant for both NO2 (adjusted hazard ratio [HR], 1.13; 95% confidence interval [95%CI], 1.01-1.22; p < 0.001; I(2) = 36.4%, pheterogeneity = 0.208) and PM2.5 (HR, 1.11; 95%CI, 1.03-1.20; p < 0.001; I(2) = 0.0%, pheterogeneity = 0.827). Odds ratios were reported by two cross-sectional studies which revealed similar associations between both NO2 and PM2.5 with type 2 diabetes. Across studies, risk estimates were generally adjusted for age, gender, body mass index and cigarette smoking. CONCLUSIONS Available evidence supports a prospective association of main air pollutants with an increased risk for type 2 diabetes. This finding may have implications for population-based strategies to reduce diabetes risk.

Molecular analysis of the parkin gene in South African patients diagnosed with Parkinson's disease

Parkinsons disease (PD) is a common movement disorder which may arise from mutations in the parkin gene. To date, more than 100 different parkin mutations have been reported. The aim of the present study was to determine the frequency of point mutations and homozygous exon deletions in the parkin gene in a group of 91 South African patients diagnosed with PD. Mutation screening of the 12 exons of parkin was performed using single strand conformation polymorphism analysis and the high-resolution melt technique. Six different mutations were identified: four putative disease-causing missense heterozygous changes (H200Q, D280N, E310D and R402C) and two homozygous exon deletions (exons 3 and 4, and exon 4). The D280N and R402C variants have both previously been described but their pathogenic status has been equivocal. In the present study, the D280N variant was observed in three early onset PD-affected siblings and was not present in a 63-year-old unaffected sibling. This data provide further support for the pathogenicity of this variant which is situated within the first RING finger of the RING-box. None of the four missense variants were detected in over 100 ethnic-matched control chromosomes. We conclude that point mutations and homozygous exon deletions in the parkin gene are not a major cause of PD in the South African population. Further studies on this group of patients are needed to determine the contribution of heterozygous exon deletions and insertions in parkin. The present study is the first report on the molecular etiology of PD in South African patients.

Chronic kidney diseases in mixed ancestry south African populations: prevalence, determinants and concordance between kidney function estimators

BackgroundPopulation-based data on the burden of chronic kidney disease (CKD) in sub-Saharan Africa is still very limited. We assessed the prevalence and determinants of CKD, and evaluated the concordance of commonly advocated estimators of glomerular filtration rate (eGFR) in a mixed ancestry population from South Africa.MethodsParticipants were a population-based sample of adults selected from the Bellville-South community in the metropolitan city of Cape Town. eGFR was based on the Cockroft-Gault (CG), Modification of Diet in Kidney Disease (MDRD) and CKD Epidemiology Collaboration (CKD-EPI) equations (with and without adjustment for ethnicity). Kidney function staging used the Kidney Disease Outcome Quality Initiative (KDOQI) classification. Logistic regressions and kappa statistic were used to investigate determinants of CKD and assess the agreement between different estimators.ResultsThe crude prevalence of CKD stage 3–5 was 14.8% for Cockcroft-Gault, 7.6% and 23.9% respectively for the MDRD with and without ethnicity correction, and 7.4% and 17.3% for the CKD-EPI equations with and without ethnicity correction. The highest agreement between GFR estimators was between MDRD and CKD-EPI equations, both with ethnicity correction, Kappa 0.91 (95% CI: 0.86-0.95), correlation coefficient 0.95 (95% CI: 0.94-0.96). In multivariable logistic regression models, sex, age and known hypertension were consistently associated with CKD stage 3–5 across the 5 estimators.ConclusionsThe prevalence of CKD stages greater than 3 is the highest reported in Africa. This study provides evidence for support of the CKD-EPI equation for eGFR reporting and CKD classification.

Optimal Waist-to-Height Ratio Values for Cardiometabolic Risk Screening in an Ethnically Diverse Sample of South African Urban and Rural School Boys and Girls

Background The proposed waist-to-height ratio (WHtR) cut-off of 0.5 is less optimal for cardiometabolic risk screening in children in many settings. The purpose of this study was to determine the optimal WHtR for children from South Africa, and investigate variations by gender, ethnicity and residence in the achieved value. Methods Metabolic syndrome (MetS) components were measured in 1272 randomly selected learners, aged 10–16 years, comprising of 446 black Africans, 696 mixed-ancestry and 130 Caucasians. The Youden’s index and the closest-top-left (CTL) point approaches were used to derive WHtR cut-offs for diagnosing any two MetS components, excluding the waist circumference. Results The two approaches yielded similar cut-off in girls, 0.465 (sensitivity 50.0, specificity 69.5), but two different values in boys, 0.455 (42.9, 88.4) and 0.425 (60.3, 67.7) based on the Youden’s index and the CTL point, respectively. Furthermore, WHtR cut-off values derived differed substantially amongst the regions and ethnic groups investigated, whereby the highest cut-off was observed in semi-rural and white children, respectively, Youden’s index0.505 (31.6, 87.1) and CTL point 0.475 (44.4, 75.9). Conclusion The WHtR cut-off of 0.5 is less accurate for screening cardiovascular risk in South African children. The optimal value in this setting is likely gender and ethnicity-specific and sensitive to urbanization.

Genomic medicine and risk prediction across the disease spectrum

Abstract Genomic medicine is based on the knowledge that virtually every medical condition, disease susceptibility or response to treatment is caused, regulated or influenced by genes. Genetic testing may therefore add value across the disease spectrum, ranging from single-gene disorders with a Mendelian inheritance pattern to complex multi-factorial diseases. The critical factors for genomic risk prediction are to determine: (1) where the genomic footprint of a particular susceptibility or dysfunction resides within this continuum, and (2) to what extent the genetic determinants are modified by environmental exposures. Regarding the small subset of highly penetrant monogenic disorders, a positive family history and early disease onset are mostly sufficient to determine the appropriateness of genetic testing in the index case and to inform pre-symptomatic diagnosis in at-risk family members. In more prevalent polygenic non-communicable diseases (NCDs), the use of appropriate eligibility criteria is required to ensure a balance between benefit and risk. An additional screening step may therefore be necessary to identify individuals most likely to benefit from genetic testing. This need provided the stimulus for the development of a pathology-supported genetic testing (PSGT) service as a new model for the translational implementation of genomic medicine in clinical practice. PSGT is linked to the establishment of a research database proven to be an invaluable resource for the validation of novel and previously described gene-disease associations replicated in the South African population for a broad range of NCDs associated with increased cardio-metabolic risk. The clinical importance of inquiry concerning family history in determining eligibility for personalized genotyping was supported beyond its current limited role in diagnosing or screening for monogenic subtypes of NCDs. With the recent introduction of advanced microarray-based breast cancer subtyping, genetic testing has extended beyond the genome of the host to also include tumor gene expression profiling for chemotherapy selection. The decreasing cost of next generation sequencing over recent years, together with improvement of both laboratory and computational protocols, enables the mapping of rare genetic disorders and discovery of shared genetic risk factors as novel therapeutic targets across diagnostic boundaries. This article reviews the challenges, successes, increasing inter-disciplinary integration and evolving strategies for extending PSGT towards exome and whole genome sequencing (WGS) within a dynamic framework. Specific points of overlap are highlighted between the application of PSGT and exome or WGS, as the next logical step in genetically uncharacterized patients for whom a particular disease pattern and/or therapeutic failure are not adequately accounted for during the PSGT pre-screen. Discrepancies between different next generation sequencing platforms and low concordance among variant-calling pipelines caution against offering exome or WGS as a stand-alone diagnostic approach. The public reference human genome sequence (hg19) contains minor alleles at more than 1 million loci and variant calling using an advanced major allele reference genome sequence is crucial to ensure data integrity. Understanding that genomic risk prediction is not deterministic but rather probabilistic provides the opportunity for disease prevention and targeted treatment in a way that is unique to each individual patient.

Proliferator-activated receptor gamma Pro12Ala interacts with the insulin receptor substrate 1 Gly972Arg and increase the risk of insulin resistance and diabetes in the mixed ancestry population from South Africa.

BackgroundThe peroxisome proliferator-activated receptor gamma (PPARG), Pro12Ala and the insulin receptor substrate (IRS1), Gly972Arg confer opposite effects on insulin resistance and type 2 diabetes mellitus (T2DM). We investigated the independent and joint effects of PPARG Pro12Ala and IRS1 Gly972Arg on markers of insulin resistance and T2DM in an African population with elevated risk of T2DM. In all 787 (176 men) mixed-ancestry adults from the Bellville-South community in Cape Town were genotyped for PPARG Pro12Ala and IRS1 Gly972Arg by two independent laboratories. Glucose tolerance status and insulin resistance/sensitivity were assessed.ResultsGenotype frequencies were 10.4% (PPARG Pro12Ala) and 7.7% (IRS1 Gly972Arg). Alone, none of the polymorphisms predicted prevalent T2DM, but in regression models containing both alleles and their interaction term, PPARG Pro12 conferred a 64% higher risk of T2DM. Furthermore PPARG Pro12 was positively associated in adjusted linear regressions with increased 2-hour post-load insulin in non-diabetic but not in diabetic participants.ConclusionThe PPARG Pro12 is associated with insulin resistance and this polymorphism interacts with IRS1 Gly972Arg, to increase the risk of T2DM in the mixed-ancestry population of South Africa. Our findings require replication in a larger study before any generalisation and possible application for risk stratification.

Three-year's changes in glucose tolerance status in the Bellville South cohort: rates and phenotypes associated with progression.

AIMS To determine the phenotypes associated with progression to type 2 diabetes or worsening in glucose tolerance during a 3-year follow-up of a community-based cohort in Cape Town, South Africa. METHODS A total of 198 eligible subjects (72.3% women) aged 55.2 years, from the Bellville-South community were followed-up between 2008 and 2011. Baseline and follow-up data collections included glucose tolerance status, anthropometric, blood pressure, lipids, insulin, γ-glutamyltransferase, cotinine, creatinine and HbA1c. Progression in glucose tolerance status at 3-year was the composite of new-onset diabetes and any worsening in glucose tolerance status. RESULTS The cumulative incidence of progression in glucose tolerance status was: 16.2% (32 participants including 11 with new-onset diabetes), and increased in a stepwise fashion with the number of components of metabolic syndrome (MetS). In age and sex-adjusted logistic regression analyses, MetS [odd ratio: 3.08 (95% CI: 1.34-7.10)], HbA1c [5.26 (1.94-14.24)], HDL-cholesterol [0.05 (0.01-0.33)], γ-glutamyltransferase [1.99 (1.07-3.67)], triglycerides [1.71 (1.13-2.58)] and total/HDL-cholesterol [1.45 (1.08-1.93)] were significant predictors of progression, while borderline effects were observed for baseline glucose and diastolic blood pressure. Markers of adiposity were mostly stable or improved among non-progressors during follow-up, but deteriorated significantly among progressors, resulting in significant statistical interactions. CONCLUSIONS High rates of deterioration of glucose status over time were found in our population, with nearly one-fifth of them acquiring a glucose tolerance worse status within a very short follow-up. Our study extends to this setting the well-known utility of phenotypes of MetS single or in combination, in predicting worsening in glucose tolerance status.

Gamma‐glutamyltransferase, insulin resistance and cardiometabolic risk profile in a middle‐aged African population

Background Mechanisms linking liver functions with cardiometabolic risk may involve insulin resistance (IR) and non‐alcoholic fatty liver disease. We assessed the associations of gamma‐glutamyltransferase (GGT) levels with IR and metabolic syndrome (MetS) in an adult South African urban cohort. Methods 1198 participants aged >15 years (297 men) were drawn from the Bellville‐South suburb (Cape Town). The homeostatic model assessment of insulin (HOMA‐IR), β‐cells function (HOMA‐B%), fasting insulin resistance index (FIRI) and the quantitative insulin‐sensitivity check index (QUICKI) were calculated, and MetS defined according to the Join Interim Statement 2009 criteria. Associations of GGT levels with covariates were assessed on a continuous scale and across sex‐specific quarters of GGT, with adjustment for confounders via generalized linear and logistic regressions. Results Indicators of IR (HOMA‐IR, FIRI and fasting insulin) increased, whereas those for insulin sensitivity (Sib and QUICKI) diminished significantly linearly and across increasing GGT quarters. In multivariable‐adjusted models, adjustment for sex, age, BMI, cigarette smoking and alcohol intake yielded the strongest, significant associations between GGT and all markers of IR/IS and glycemia excluding glucose insulin ratio. In a similar level of adjustments, with/without further adjustment for markers of IR/insulin sensitivity, the prevalence of MetS significantly increased across quarters of GGT. Conclusions GGT levels were independently associated with insulin sensitivity and MetS in this population. Unaccounted, chronic elevation of GGT may therefore be a cue to screen and monitor individuals for MetS and diabetes, and may warrant consideration as an indicator of high risk for the development of these metabolic disorders.

Polymorphisms in the Non-Muscle Myosin Heavy Chain Gene (MYH9) Are Associated with Lower Glomerular Filtration Rate in Mixed Ancestry Diabetic Subjects from South Africa

Objective Though single nucleotide polymorphisms (SNPs) in the non-muscle myosin gene (MYH9) have been reported to explain most of the excess risk of nondiabetic chronic kidney disease (CKD), in African-Americans, some studies have also shown associations with diabetic end-stage renal disease. We investigated the association of MYH9 SNPs with renal traits in a mixed-ancestry South African population prone to diabetes. Research Design and Methods Three SNPs known to be associated with CKD (rs4821480, rs5756152 and rs12107) were genotyped using Taqman assay in 716 adults (198 with diabetes) from the Bellville-South community, Cape Town. Glomerular filtration rate was estimated (eGFR) and urinary albumin/creatinine ratio (ACR) assessed. Multivariable regressions were used to relate the SNPs with renal traits. Results Mean age was 53.6 years, with the expected differences observed in characteristics by diabetic status. Significant associations were found between rs575152 and serum creatinine, and eGFR in the total population, and in diabetic participants (all p≤0.003), but not in non-diabetics (all p≥0.16), with significant interactions by diabetes status (interaction-p≤0.009). The association with ACR was borderline in diabetic participants (p = 0.05) and non-significant in non-diabetics (p = 0.85), with significant interaction (interaction p = 0.02). rs12107 was associated with fasting-, 2-hour glucose and HbA1c in diabetic participants only (interaction-p≤0.003), but not with renal traits. Conclusion MYH9 SNPs were associated with renal traits only in diabetic participants in this population. Our findings and other studies suggest that MYH9 may have a broader genetic risk effect on kidney diseases.

Genetic risk of type 2 diabetes in populations of the African continent: A systematic review and meta-analyses

BACKGROUND Type 2 diabetes (T2D) is growing faster in Africa than anywhere else, driven by the dual effects of genetic and environmental factors. We conducted a systematic review and meta-analyses of published studies on genetic markers of T2D in populations within Africa. METHODS Multiple databases were searched for studies of genetic variants associated with T2D in populations living in Africa. Studies reporting on the association of a genetic marker with T2D or indicators of glycaemia were included. Data were extracted on study design and characteristics, genetic determinants, effect estimates of associations with T2D. FINDINGS Overall, 100 polymorphisms in 57 genes have been investigated in relation with T2D in populations within Africa, in 60 studies. Almost all studies used the candidate gene approach, with >88% published during 2006-2014 and 70% (42/60) originating from Tunisia and Egypt. Polymorphisms in ACE, AGRP, eNOS, GSTP1, HSP70-2, MC4R, MTHFR, PHLPP, POL1, TCF7L2, and TNF-α gene were found to be associated with T2D, with overlapping effect on various cardiometabolic traits. The polymorphisms investigated in multiple studies mostly had consistent effects across studies, with only modest or no statistical heterogeneity. Effect sizes were modestly significant [e.g., odd ratio 1.49 (95%CI 1.33-1.66) for TCF7L2 (rs7903146)]. Underpowered genome-wide studies revealed no diabetes risk loci specific to African populations. INTERPRETATION Current evidence on the genetic markers of T2D in African populations mostly originate from North African countries, is overall scanty and largely insufficient to reliably inform the genetic architecture of T2D across Africa.