The SNP rs10911021 is associated with oxidative stress in coronary heart disease patients from Pakistan

BACKGROUND: rs10911021 (a single nucleotide polymorphism present upstream of the GLUL gene) affects glutamic acid metabolism, and was shown to be associated with coronary heart disease (CHD) in patients with T2DM but a definite mechanism is unknown. It may affect glutathione cycle, an important effector in the antioxidant defense mechanism, in the cells. We checked the association of this SNP with CHD and oxidative stress biomarkers, malondialdeheyde (MDA), GSH and GSSG in Pakistani patients. METHODS: A total of 650 subjects (425 CHD cases and 225 controls) were genotyped by TaqMan allelic discrimination technique. The levels of MDA, GSH and GSSG were measured by standard protocols. RESULTS: The risk allele frequency was higher in cases than controls, but the difference was insignificant (p = 0.55). The SNP was not associated with CHD (p = 0.053) but when the analysis was limited to CHD patients having DM, a significant association (p = 0.03) was observed. The blood levels of MDA and GSSG were higher while that of GSH was significantly lower in the cases than the controls (p < 0.05). Each risk allele increased MDA and GSSG by 0.29 (0.036) mmol/l and 0.4 (0.04) mmol/l, respectively, while decreased GSH by -0.36 (0.03) mmol/l. The SNP was not associated with any of the tested blood lipids. CONCLUSION: The SNP rs10911021 was associated with CHD only in patients having diabetes, but the SNP was associated with total oxidative stress biomarkers MDA and GSH and GSSG levels. As the SNP rs10911021 showed significant association with oxidative stress parameters and these parameters should an increased oxidative stress in the CHD subjects, it can be concluded that the SNP may have contributed to increase the risk of heart diseases in the diabetic subjects by increasing the oxidative stress

Lack of Association of LPA Gene Polymorphisms with Coronary Artery Disease in Pakistani Subjects

Coronary artery disease (CAD) is the leading cause of death worldwide. Pakistan faces a high epidemic of CAD, and the disease burden is increasing with the passage of time. Several genetic markers have been reported to be significantly associated with CAD; one of them is the lipoprotein A gene. The aim of the current investigation was to genotype the LPA gene SNPs, rs3798220 and rs10455872, in Pakistani subjects with CAD in a case control study design. The genotyping was done by TaqMan allelic discrimination assay. The results showed that the cases had significantly higher prevalence of diabetes (64.6%), hypertension (62.1%), and smoking habits (29.5%). The level of cholesterol in cases was higher than in controls (208.25±54.11 vs. 175.34±43.51, p≤0.0001). The LDL-C was higher in cases than in controls (104.62±37.94 vs. 77.05±21.17, p≤0.0001). Similarly, triglycerides were also higher in cases than in controls (214.51±74.60 vs. 190.54±70.26, p≤0.0001), whereas HDL-C was lower in cases than in controls (45.13±11.63 vs. 67.9±17.57, p≤0.0001). For rs3798220, the risk allele (C) frequency was 0.005 in cases and 0.002 in controls. For rs10455872, the risk allele (G) frequency was 0.017 in cases and 0.014 in controls. The risk allele frequencies were not significantly different between cases and controls (p>0.05). In conclusion, these two LPA SNPs do not contribute significantly to CAD progression and cannot be used as independent risk factors for CAD in Pakistani population

Cost effectiveness of cascade testing for familial hypercholesterolaemia, based on data from familial hypercholesterolaemia services in the UK

Peer reviewedPublisher PD

Applying a typology of health worker migration to non-EU migrant doctors in Ireland

Abstract Background: Research on health worker migration in the Irish context has categorized migrant health workers by country or region of training (for example, non-EU nurses or doctors) or recruitment mechanism (for example, actively recruited nurses). This paper applies a new typology of health worker migrants – livelihood, career-oriented, backpacker, commuter, undocumented and returner migrants (European Observatory on Health Systems and Policies and WHO, vol. 2:129-152, 2014) – to the experiences of non-EU migrant doctors in Ireland and tests its utility for understanding health worker migration internationally. Methods: The paper draws on quantitative survey (N = 366) and qualitative interview (N = 37) data collected from non-EU migrant doctors in Ireland between 2011 and 2013. Results: Categorizing non-EU migrant doctors in Ireland according to the typology (European Observatory on Health Systems and Policies and WHO, vol. 2:129-152, 2014) offers insight into their differing motivations, particularly on arrival. Findings suggest that the career-oriented migrant is the most common type of doctor among non-EU migrant doctor respondents, accounting for 60 % (N = 220) of quantitative and 54 % (N = 20) of qualitative respondents. The authors propose a modification to the typology via the addition of two additional categories – the family migrant and the safety and security migrant. Conclusions: Employing a typology of health worker migration can facilitate a more comprehensive understanding of the migrant medical workforce, a necessary prerequisite for the development of useful policy tools (European Observatory on Health Systems and Policies and WHO, vol. 2:129-152, 2014). The findings indicate that there is some fluidity between categories, as health worker motivations change over time. This indicates the potential for policy levers to influence migrant health worker decision-making, if they are sufficiently “tuned in” to migrant health worker motivation. Keywords: Doctor migration, Migration typology, Medical workforce planning, Health workforce planning, Health human resources for healt

LDL-C Concentrations and the 12-SNP LDL-C Score for Polygenic Hypercholesterolaemia in Self-Reported South Asian, Black and Caribbean Participants of the UK Biobank

Background: Monogenic familial hypercholesterolaemia (FH) is an autosomal dominant disorder characterised by elevated low-density lipoprotein cholesterol (LDL-C) concentrations due to monogenic mutations in LDLR, APOB, PCSK9, and APOE. Some mutation-negative patients have a polygenic cause for elevated LDL-C due to a burden of common LDL-C-raising alleles, as demonstrated in people of White British (WB) ancestry using a 12-single nucleotide polymorphism (SNP) score. This score has yet to be evaluated in people of South Asian (SA), and Black and Caribbean (BC) ethnicities. Objectives: 1) Compare the LDL-C and 12-SNP score distributions across the three major ethnic groups in the United Kingdom: WB, SA, and BC individuals; 2) compare the association of the 12-SNP score with LDL-C in these groups; 3) evaluate ethnicity-specific and WB 12-SNP score decile cut-off values, applied to SA and BC ethnicities, in predicting LDL-C concentrations and hypercholesterolaemia (LDL-C>4.9 mmol/L). Methods: The United Kingdom Biobank cohort was used to analyse the LDL-C (adjusted for statin use) and 12-SNP score distributions in self-reported WB (n = 353,166), SA (n = 7,016), and BC (n = 7,082) participants. To evaluate WB and ethnicity-specific 12-SNP score deciles, the total dataset was split 50:50 into a training and testing dataset. Regression analyses (logistic and linear) were used to analyse hypercholesterolaemia (LDL-C>4.9 mmol/L) and LDL-C. Findings: The mean (±SD) measured LDL-C differed significantly between the ethnic groups and was highest in WB [3.73 (±0.85) mmol/L], followed by SA [3.57 (±0.86) mmol/L, p < 2.2 × 10−16], and BC [3.42 (±0.90) mmol/L] participants (p < 2.2 × 10−16). There were significant differences in the mean (±SD) 12-SNP score between WB [0.90 (±0.23)] and BC [0.72 (±0.25), p < 2.2 × 10−16], and WB and SA participants [0.86 (±0.19), p < 2.2 × 10−16]. In all three ethnic groups the 12-SNP score was associated with measured LDL-C [R2 (95% CI): WB = 0.067 (0.065–0.069), BC = 0.080 (0.063–0.097), SA = 0.027 (0.016–0.038)]. The odds ratio and the area under the curve for hypercholesterolaemia were not statistically different when applying ethnicity-specific or WB deciles in all ethnic groups. Interpretation: We provide information on the differences in LDL-C and the 12-SNP score distributions in self-reported WB, SA, and BC individuals of the United Kingdom Biobank. We report the association between the 12-SNP score and LDL-C in these ethnic groups. We evaluate the performance of ethnicity-specific and WB 12-SNP score deciles in predicting LDL-C and hypercholesterolaemia

The association of telomere length with paternal history of premature myocardial infarction in the European Atherosclerosis Research Study II

Inter-individual variability in telomere length is highly heritable and has been correlated with risk of coronary heart disease (CHD). Our aim was to determine the association of mean leukocyte telomere length with paternal history of premature myocardial infarction (MI). Mean leukocyte telomere length was measured with real-time polymerase chain reactions in 369 male students (18–28 years) with a paternal history of MI before the age of 55, recruited from 14 European universities, serving as cases and 396 age-matched controls with no paternal history of CHD. Overall, cases had borderline significantly shorter mean length (~550 bp), adjusted for age and geographical region, than controls (p = 0.05). A significant difference in telomere length across the geographical regions of Europe was observed (p < 0.0001), with shorter mean length in the Baltic and South and the longest in the Middle. The case–control difference (∼2.24 kb) in mean length was highly significant only in the Baltic region (p < 0.0001). There is suggestive evidence that, in young men, the biological expression of a paternal history of premature MI is at least in part mediated through inherited short telomeres. The association with paternal history of MI is strongly seen only in the Baltic compared to the rest of Europe, but this is not explained by shorter telomere length in this region

Genomic Research to Identify Novel Pathways in the Development of Abdominal Aortic Aneurysm

Abdominal aortic aneurysm (AAA) is a common disease with a large heritable component. There is a need to improve our understanding of AAA pathogenesis in order to develop novel treatment paradigms. Genomewide association studies have revolutionized research into the genetic variants that underpin the development of many complex diseases including AAA. This article reviews the progress that has been made to date in this regard, including mechanisms by which loci identified by GWAS may contribute to the development of AAA. It also highlights potential post-GWAS analytical strategies to improve our understanding of the disease further

Human paraoxonase gene cluster polymorphisms as predictors of coronary heart disease risk in the prospective Northwick Park Heart Study II

AbstractThe anti-atherogenic effect of HDL has been suggested to be partly due to the action of HDL-associated paraoxonase (PON). Three distinct enzymes have been identified, encoded by PON1, PON2 and PON3, clustered on chromosome 7q21–q22. Two cSNPs in PON1 (L55M and Q192R) and one in PON2 (S311C) have been implicated as independent risk factors for coronary heart disease (CHD) in some, but not all, studies. A PON3 SNP (A99A) was identified and the effect of these four PON SNPs on HDL levels and CHD risk was examined in the prospective Northwick Park Heart Study II (NPHSII). Genotype frequencies did not differ between cases and controls but the CHD risk associated with smoking was significantly modified by PON1 L55M genotype. Compared to LL non-smokers, LL smokers had a hazard ratio (HR) of 1.30 (95% CI 0.81–2.06) while M-allele carriers had a HR of 1.76 (1.17–2.67). When genotypes were analysed in combination, men with the genotype PON1 55 LM/MM+PON2 311 CC, had HR of 3.54 (1.81–6.93) compared to PON1 LL+PON2 SS/SC men (interaction P=0.004). These effects were independent of classical risk factors. These data demonstrate the importance of stratifying by environmental factors and the use of multiple SNPs for genetic analysis

A Machine Learning Model to Aid Detection of Familial Hypercholesterolemia

Background: People with monogenic familial hypercholesterolemia (FH) are at an increased risk of premature coronary heart disease and death. With a prevalence of 1:250, FH is relatively common; but currently there is no population screening strategy in place and most carriers are identified late in life, delaying timely and cost-effective interventions. // Objectives: The purpose of this study was to derive an algorithm to identify people with suspected monogenic FH for subsequent confirmatory genomic testing and cascade screening. // Methods: A least absolute shrinkage and selection operator logistic regression model was used to identify predictors that accurately identified people with FH in 139,779 unrelated participants of the UK Biobank. Candidate predictors included information on medical and family history, anthropometric measures, blood biomarkers, and a low-density lipoprotein cholesterol (LDL-C) polygenic score (PGS). Model derivation and evaluation were performed in independent training and testing data. // Results: A total of 488 FH variant carriers were identified using whole-exome sequencing of the low-density lipoprotein receptor, apolipoprotein B, apolipoprotein E, proprotein convertase subtilisin/kexin type 9 genes. A 14-variable algorithm for FH was derived, with an area under the curve of 0.77 (95% CI: 0.71-0.83), where the top 5 most important variables included triglyceride, LDL-C, apolipoprotein A1 concentrations, self-reported statin use, and LDL-C PGS. Excluding the PGS as a candidate feature resulted in a 9-variable model with a comparable area under the curve: 0.76 (95% CI: 0.71-0.82). Both multivariable models (w/wo the PGS) outperformed screening-prioritization based on LDL-C adjusted for statin use. // Conclusions: Detecting individuals with FH can be improved by considering additional predictors. This would reduce the sequencing burden in a 2-stage population screening strategy for FH

Critical appraisal of CRP measurement for the prediction of coronary heart disease events: new data and systematic review of 31 prospective cohorts.

BACKGROUND: Non-uniform reporting of relevant relationships and metrics hampers critical appraisal of the clinical utility of C-reactive protein (CRP) measurement for prediction of later coronary events. METHODS: We evaluated the predictive performance of CRP in the Northwick Park Heart Study (NPHS-II) and the Edinburgh Artery Study (EAS) comparing discrimination by area under the ROC curve (AUC), calibration and reclassification. We set the findings in the context of a systematic review of published studies comparing different available and imputed measures of prediction. Risk estimates per-quantile of CRP were pooled using a random effects model to infer the shape of the CRP-coronary event relationship. RESULTS: NPHS-II and EAS (3441 individuals, 309 coronary events): CRP alone provided modest discrimination for coronary heart disease (AUC 0.61 and 0.62 in NPHS-II and EAS, respectively) and only modest improvement in the discrimination of a Framingham-based risk score (FRS) (increment in AUC 0.04 and -0.01, respectively). Risk models based on FRS alone and FRS + CRP were both well calibrated and the net reclassification improvement (NRI) was 8.5% in NPHS-II and 8.8% in EAS with four risk categories, falling to 4.9% and 3.0% for 10-year coronary disease risk threshold of 15%. Systematic review (31 prospective studies 84 063 individuals, 11 252 coronary events): pooled inferred values for the AUC for CRP alone were 0.59 (0.57, 0.61), 0.59 (0.57, 0.61) and 0.57 (0.54, 0.61) for studies of 10 years follow up, respectively. Evidence from 13 studies (7201 cases) indicated that CRP did not consistently improve performance of the Framingham risk score when assessed by discrimination, with AUC increments in the range 0-0.15. Evidence from six studies (2430 cases) showed that CRP provided statistically significant but quantitatively small improvement in calibration of models based on established risk factors in some but not all studies. The wide overlap of CRP values among people who later suffered events and those who did not appeared to be explained by the consistently log-normal distribution of CRP and a graded continuous increment in coronary risk across the whole range of values without a threshold, such that a large proportion of events occurred among the many individuals with near average levels of CRP. CONCLUSIONS: CRP does not perform better than the Framingham risk equation for discrimination. The improvement in risk stratification or reclassification from addition of CRP to models based on established risk factors is small and inconsistent. Guidance on the clinical use of CRP measurement in the prediction of coronary events may require updating in light of this large comparative analysis