Genetic Markers Enhance Coronary Risk Prediction in Men: The MORGAM Prospective Cohorts

Background: More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.

Methods: Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5-18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.

Results: Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50-59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.

Conclusions: Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.

HDAC1 and HDAC2 independently predict mortality in hepatocellular carcinoma by a competing risk regression model in a Southeast Asian population

Histone deacetylases (HDACs) are enzymes involved in transcriptional repression. We aimed to examine the significance of HDAC1 and HDAC2 gene expression in the prediction of recurrence and survival in 156 patients with hepatocellular carcinoma (HCC) among a South East Asian population who underwent curative surgical resection in Singapore. We found that HDAC1 and HDAC2 were upregulated in the majority of HCC tissues. The presence of HDAC1 in tumor tissues was correlated with poor tumor differentiation. Notably, HDAC1 expression in adjacent non-tumor hepatic tissues was correlated with the presence of satellite nodules and multiple lesions, suggesting that HDAC1 upregulation within the field of HCC may contribute to tumor spread. Using competing risk regression analysis, we found that increased cancer-specific mortality was significantly associated with HDAC2 expression. Mortality was also increased with high HDAC1 expression. In the liver cancer cell lines, HEP3B, HEPG2, PLC5, and a colorectal cancer cell line, HCT116, the combined knockdown of HDAC1 and HDAC2 increased cell death and reduced cell proliferation as well as colony formation. In contrast, knockdown of either HDAC1 or HDAC2 alone had minimal effects on cell death and proliferation. Taken together, our study suggests that both HDAC1 and HDAC2 exert pro-survival effects in HCC cells, and the combination of isoform-specific HDAC inhibitors against both HDACs may be effective in targeting HCC to reduce mortality.

Troponin I and cardiovascular risk prediction in the general population: the BiomarCaRE consortium

AIMS: Our aims were to evaluate the distribution of troponin I concentrations in population cohorts across Europe, to characterize the association with cardiovascular outcomes, to determine the predictive value beyond the variables used in the ESC SCORE, to test a potentially clinically relevant cut-off value, and to evaluate the improved eligibility for statin therapy based on elevated troponin I concentrations retrospectively.

METHODS AND RESULTS: Based on the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE) project, we analysed individual level data from 10 prospective population-based studies including 74 738 participants. We investigated the value of adding troponin I levels to conventional risk factors for prediction of cardiovascular disease by calculating measures of discrimination (C-index) and net reclassification improvement (NRI). We further tested the clinical implication of statin therapy based on troponin concentration in 12 956 individuals free of cardiovascular disease in the JUPITER study. Troponin I remained an independent predictor with a hazard ratio of 1.37 for cardiovascular mortality, 1.23 for cardiovascular disease, and 1.24 for total mortality. The addition of troponin I information to a prognostic model for cardiovascular death constructed of ESC SCORE variables increased the C-index discrimination measure by 0.007 and yielded an NRI of 0.048, whereas the addition to prognostic models for cardiovascular disease and total mortality led to lesser C-index discrimination and NRI increment. In individuals above 6 ng/L of troponin I, a concentration near the upper quintile in BiomarCaRE (5.9 ng/L) and JUPITER (5.8 ng/L), rosuvastatin therapy resulted in higher absolute risk reduction compared with individuals <6 ng/L of troponin I, whereas the relative risk reduction was similar.

CONCLUSION: In individuals free of cardiovascular disease, the addition of troponin I to variables of established risk score improves prediction of cardiovascular death and cardiovascular disease.

Common polygenic variation enhances risk prediction for Alzheimer's disease.

The identification of subjects at high risk for Alzheimer’s disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer’s disease and the accuracy of Alzheimer’s disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer’s Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer’s disease (P = 4.9 × 10−26). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10−19). The best prediction accuracy AUC = 78.2% (95% confidence interval 77–80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer’s disease has a significant polygenic component, which has predictive utility for Alzheimer’s disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes.

Common Breast Cancer Susceptibility Alleles and the Risk of Breast Cancer for BRCA1 and BRCA2 Mutation Carriers: Implications for Risk Prediction

The known breast cancer susceptibility polymorphisms in FGFR2, TNRC9/TOX3, MAP3K1, LSP1, and 2q35 confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. We evaluated the associations of 3 additional single nucleotide polymorphisms (SNPs), rs4973768 in SLC4A7/NEK10, rs6504950 in STXBP4/COX11, and rs10941679 at 5p12, and reanalyzed the previous associations using additional carriers in a sample of 12,525 BRCA1 and 7,409 BRCA2 carriers. Additionally, we investigated potential interactions between SNPs and assessed the implications for risk prediction. The minor alleles of rs4973768 and rs10941679 were associated with increased breast cancer risk for BRCA2 carriers (per-allele HR - 1.10, 95% CI: 1.03-1.18, P - 0.006 and HR - 1.09, 95% CI: 1.01-1.19, P = 0.03, respectively). Neither SNP was associated with breast cancer risk for BRCA1 carriers, and rs6504950 was not associated with breast cancer for either BRCA1 or BRCA2 carriers. Of the 9 polymorphisms investigated, 7 were associated with breast cancer for BRCA2 carriers (FGFR2, TOX3, MAP3K1, LSP1, 2q35, SLC4A7, 5p12, P 7 = 10 x (11) - 0.03), but only TOX3 and 2q35 were associated with the risk for BRCA1 carriers (P = 0.0049, 0.03, respectively). All risk-associated polymorphisms appear to interact multiplicatively on breast cancer risk for mutation carriers. Based on the joint genotype distribution of the 7 risk-associated SNPs in BRCA2 mutation carriers, the 5% of BRCA2 carriers at highest risk (i.e., between 95th and 100th percentiles) were predicted to have a probability between 80% and 96% of developing breast cancer by age 80, compared with 42%

Complement Component 3: an assessment of association with AMD and analysis of gene-gene and gene-environment interactions in a Northern Irish cohort

Purpose: A non-synonymous single nucleotide polymorphism ( SNP) in complement component 3 has been shown to increase the risk of age-related macular degeneration (AMD). We assess its effect on AMD risk in a Northern Irish sample, test for gene-gene and gene-environment interaction, and review a risk prediction model.

Surveillance for ocular hypertension: An evidence synthesis and economic evaluation

OBJECTIVES: To determine effective and efficient monitoring criteria for ocular hypertension [raised intraocular pressure (IOP)] through (i) identification and validation of glaucoma risk prediction models; and (ii) development of models to determine optimal surveillance pathways.

DESIGN: A discrete event simulation economic modelling evaluation. Data from systematic reviews of risk prediction models and agreement between tonometers, secondary analyses of existing datasets (to validate identified risk models and determine optimal monitoring criteria) and public preferences were used to structure and populate the economic model.

SETTING: Primary and secondary care.

PARTICIPANTS: Adults with ocular hypertension (IOP > 21 mmHg) and the public (surveillance preferences).

INTERVENTIONS: We compared five pathways: two based on National Institute for Health and Clinical Excellence (NICE) guidelines with monitoring interval and treatment depending on initial risk stratification, 'NICE intensive' (4-monthly to annual monitoring) and 'NICE conservative' (6-monthly to biennial monitoring); two pathways, differing in location (hospital and community), with monitoring biennially and treatment initiated for a ≥ 6% 5-year glaucoma risk; and a 'treat all' pathway involving treatment with a prostaglandin analogue if IOP > 21 mmHg and IOP measured annually in the community.

MAIN OUTCOME MEASURES: Glaucoma cases detected; tonometer agreement; public preferences; costs; willingness to pay and quality-adjusted life-years (QALYs).

RESULTS: The best available glaucoma risk prediction model estimated the 5-year risk based on age and ocular predictors (IOP, central corneal thickness, optic nerve damage and index of visual field status). Taking the average of two IOP readings, by tonometry, true change was detected at two years. Sizeable measurement variability was noted between tonometers. There was a general public preference for monitoring; good communication and understanding of the process predicted service value. 'Treat all' was the least costly and 'NICE intensive' the most costly pathway. Biennial monitoring reduced the number of cases of glaucoma conversion compared with a 'treat all' pathway and provided more QALYs, but the incremental cost-effectiveness ratio (ICER) was considerably more than £30,000. The 'NICE intensive' pathway also avoided glaucoma conversion, but NICE-based pathways were either dominated (more costly and less effective) by biennial hospital monitoring or had a ICERs > £30,000. Results were not sensitive to the risk threshold for initiating surveillance but were sensitive to the risk threshold for initiating treatment, NHS costs and treatment adherence.

LIMITATIONS: Optimal monitoring intervals were based on IOP data. There were insufficient data to determine the optimal frequency of measurement of the visual field or optic nerve head for identification of glaucoma. The economic modelling took a 20-year time horizon which may be insufficient to capture long-term benefits. Sensitivity analyses may not fully capture the uncertainty surrounding parameter estimates.

CONCLUSIONS: For confirmed ocular hypertension, findings suggest that there is no clear benefit from intensive monitoring. Consideration of the patient experience is important. A cohort study is recommended to provide data to refine the glaucoma risk prediction model, determine the optimum type and frequency of serial glaucoma tests and estimate costs and patient preferences for monitoring and treatment.

FUNDING: The National Institute for Health Research Health Technology Assessment Programme.

Investigating clinical predictors of arteriovenous fistula functional patency in a European cohort

Background: Arteriovenous fistula (AVF) failure to mature (FTM) rates contribute to excessive dependence on central venous catheters for haemodialysis. Choosing the most appropriate vascular access site for an individual patient is guided largely by their age, co-morbidities and clinical examination. We investigated the clinical predictors of AVF FTM in a European cohort of patients and applied an existing clinical risk prediction model for AVF FTM to this population.
Methods: A prospective cohort study was designed that included all patients undergoing AVF creation between January 2009 and December 2014 in a single centre (Belfast City Hospital) who had a functional AVF outcome observed by March 2015.
Results: A total of 525 patients had a functional AVF outcome recorded and were included in the FTM analysis. In this cohort, 309 (59%) patients achieved functional AVF patency and 216 (41%) patients had FTM. Female gender [P < 0.001, odds ratio (OR) 2.03 (CI 1.37–3.02)] and lower-arm AVF [P < 0.001, OR 4.07 (CI 2.77–5.92)] were associated with AVF FTM. The Lok model did not predict FTM outcomes based on the associated risk stratification in our population.
Conclusions: In this European study, female gender was associated with twice the risk of AVF FTM and a lower-arm AVF with four times the risk of FTM. The FTM risk prediction model was not found to be discriminative in this population. Clinical risk factors for AVF FTM vary between populations;we would recommend that units investigate their own clinical predictors of FTM to maximize AVF functional patency and ultimately survival in dialysis patients. Clinical predictors of AVF FTM may not be sufficient on their own to improve vascular access functional patency rates.

The role of angiogenic and antiangiogenic factors in the second trimester in the prediction of preeclampsia in pregnant women with type 1 diabetes

OBJECTIVE To assess the association between circulating angiogenic and antiangiogenic factors in the second trimester and risk of preeclampsia in women with type 1 diabetes.

RESEARCH DESIGN AND METHODS Maternal plasma concentrations of placental growth factor (PlGF), soluble fms-like tyrosine kinase 1 (sFlt-1), and soluble endoglin (sEng) were available at 26 weeks of gestation in 540 women with type 1 diabetes enrolled in the Diabetes and Preeclampsia Intervention Trial.

RESULTS Preeclampsia developed in 17% of pregnancies (n = 94). At 26 weeks of gestation, women in whom preeclampsia developed later had significantly lower PlGF (median [interquartile range]: 231 pg/mL [120–423] vs. 365 pg/mL [237–582]; P < 0.001), higher sFlt-1 (1,522 pg/mL [1,108–3,393] vs. 1,193 pg/mL [844–1,630] P < 0.001), and higher sEng (6.2 ng/mL [4.9–7.9] vs. 5.1 ng/mL[(4.3–6.2]; P < 0.001) compared with women who did not have preeclampsia. In addition, the ratio of PlGF to sEng was significantly lower (40 [17–71] vs. 71 [44–114]; P < 0.001) and the ratio of sFlt-1 to PlGF was significantly higher (6.3 [3.4–15.7] vs. 3.1 [1.8–5.8]; P < 0.001) in women who later developed preeclampsia. The addition of the ratio of PlGF to sEng or the ratio of sFlt-1 to PlGF to a logistic model containing established risk factors (area under the curve [AUC], 0.813) significantly improved the predictive value (AUC, 0.850 and 0.846, respectively; P < 0.01) and significantly improved reclassification according to the integrated discrimination improvement index (IDI) (IDI scores 0.086 and 0.065, respectively; P < 0.001).

CONCLUSIONS These data suggest that angiogenic and antiangiogenic factors measured during the second trimester are predictive of preeclampsia in women with type 1 diabetes. The addition of the ratio of PlGF to sEng or the ratio of sFlt-1 to PlGF to established clinical risk factors significantly improves the prediction of preeclampsia in women with type 1 diabetes.

Preeclampsia is characterized by the development of hypertension and new-onset proteinuria during the second half of pregnancy (1,2), leading to increased maternal morbidity and mortality (3). Women with type 1 diabetes are at increased risk for development of preeclampsia during pregnancy, with rates being two-times to four-times higher than that of the background maternity population (4,5). Small advances have come from preventive measures, such as low-dose aspirin in women at high risk (6); however, delivery remains the only effective intervention, and preeclampsia is responsible for up to 15% of preterm births and a consequent increase in infant mortality and morbidity (7).

Although the etiology of preeclampsia remains unclear, abnormal placental vascular remodeling and placental ischemia, together with maternal endothelial dysfunction, hemodynamic changes, and renal pathology, contribute to its pathogenesis (8). In addition, over the past decade accumulating evidence has suggested that an imbalance between angiogenic factors, such as placental growth factor (PlGF), and antiangiogenic factors, such as soluble fms-like tyrosine kinase 1 (sFlt-1) and soluble endoglin (sEng), plays a key role in the pathogenesis of preeclampsia (8,9). In women at low risk (10–13) and women at high risk (14,15), concentrations of angiogenic and antiangiogenic factors are significantly different between women who later develop preeclampsia (lower PlGF, higher sFlt-1, and higher sEng levels) compared with women who do not.

Few studies have specifically focused on circulating angiogenic factors and risk of preeclampsia in women with diabetes, and the results have been conflicting. In a small study, higher sFlt-1 and lower PlGF were reported at the time of delivery in women with diabetes who developed preeclampsia (16). In a longitudinal prospective cohort of pregnant women with diabetes, Yu et al. (17) reported increased sFlt-1 and reduced PlGF in the early third trimester as potential predictors of preeclampsia in women with type 1 diabetes, but they did not show any difference in sEng levels in women with preeclampsia compared with women without preeclampsia. By contrast, Powers et al. (18) reported only increased sEng in the second trimester in women with pregestational diabetes who developed preeclampsia.

The aim of this study, which was significantly larger than the previous studies highlighted, was to assess the association between circulating angiogenic (PlGF) and antiangiogenic (sFlt-1 and sEng) factors and the risk of preeclampsia in women with type 1 diabetes. A further aim was to evaluate the added predictive ability and clinical usefulness of angiogenic factors and established risk factors for preeclampsia risk prediction in women with type 1 diabetes.

Religion and the risk of suicide: longitudinal study of over 1 million people

Background: Durkheim’s seminal historical study demonstrated that religious affiliation reduces suicide risk, but it is unclear whether this protective effect persists in modern, more secular societies.

Aims: To examine suicide risk according to Christian religious affiliation and by inference to examine underlying mechanisms for suicide risk. If church attendance is important, risk should be lowest for Roman Catholics and highest for those with no religion; if religiosity is important, then ‘conservative’ Christians should fare best.

Method: A 9-year study followed 1 106 104 people aged 16–74 years at the 2001 UK census, using Cox proportional hazards models adjusted for census-based cohort attributes.

Results: In fully adjusted models analysing 1119 cases of suicide, Roman Catholics, Protestants and those professing no religion recorded similar risks. The risk associated with conservative Christians was lower than that for Catholics (HR = 0.71, 95% CI 0.52–0.97).

Conclusions: The relationship between religious affiliation and suicide established by Durkheim may not pertain in societies where suicide rates are highest at younger ages. Risks are similar for those with and without a religious affiliation, and Catholics (who traditionally are characterised by higher levels of church attendance) do not demonstrate lower risk of suicide. However, religious affiliation is a poor measure of religiosity, except for a small group of conservative Christians, although their lower risk of suicide may be attributable to factors such as lower risk behaviour and alcohol consumption.