Cost-effectiveness of applying high-sensitivity troponin I to a score for cardiovascular risk prediction in asymptomatic population.

INTRODUCTION: Risk stratification scores such as the European Systematic COronary Risk Evaluation (SCORE) are used to guide individuals on cardiovascular disease (CVD) prevention. Adding high-sensitivity troponin I (hsTnI) to such risk scores has the potential to improve accuracy of CVD prediction. We investigated how applying hsTnI in addition to SCORE may impact management, outcome, and cost-effectiveness. METHODS: Characteristics of 72,190 apparently healthy individuals from the Biomarker for Cardiovascular Risk Assessment in Europe (BiomarCaRE) project were included into a discrete-event simulation comparing two strategies for assessing CVD risk. The standard strategy reflecting current practice employed SCORE (SCORE); the alternative strategy involved adding hsTnI information for further stratifying SCORE risk categories (S-SCORE). Individuals were followed over ten years from baseline examination to CVD event, death or end of follow-up. The model tracked the occurrence of events and calculated direct costs of screening, prevention, and treatment from a European health system perspective. Cost-effectiveness was expressed as incremental cost-effectiveness ratio (ICER) in € per quality-adjusted life year (QALYs) gained during 10 years of follow-up. Outputs were validated against observed rates, and results were tested in deterministic and probabilistic sensitivity analyses. RESULTS: S-SCORE yielded a change in management for 10.0% of individuals, and a reduction in CVD events (4.85% vs. 5.38%, p<0.001) and mortality (6.80% vs. 7.04%, p<0.001). S-SCORE led to 23 (95%CI: 20-26) additional event-free years and 7 (95%CI: 5-9) additional QALYs per 1,000 subjects screened, and resulted in a relative risk reduction for CVD of 9.9% (95%CI: 7.3-13.5%) with a number needed to screen to prevent one event of 183 (95%CI: 172 to 203). S-SCORE increased costs per subject by 187€ (95%CI: 177 € to 196 €), leading to an ICER of 27,440€/QALY gained. Sensitivity analysis was performed with eligibility for treatment being the most sensitive. CONCLUSION: Adding a person's hsTnI value to SCORE can impact clinical decision making and eventually improves QALYs and is cost-effective compared to CVD prevention strategies using SCORE alone. Stratifying SCORE risk classes for hsTnI would likely offer cost-effective alternatives, particularly when targeting higher risk groups.

Impact of Lipoprotein(a) Level on Low-Density Lipoprotein Cholesterol- or Apolipoprotein B-Related Risk of Coronary Heart Disease.

BACKGROUND: Conventional low-density lipoprotein cholesterol (LDL-C) quantification includes cholesterol attributable to lipoprotein(a) (Lp(a)-C) due to their overlapping densities. OBJECTIVES: The purposes of this study were to compare the association between LDL-C and LDL-C corrected for Lp(a)-C (LDLLp(a)corr) with incident coronary heart disease (CHD) in the general population and to investigate whether concomitant Lp(a) values influence the association of LDL-C or apolipoprotein B (apoB) with coronary events. METHODS: Among 68,748 CHD-free subjects at baseline LDLLp(a)corr was calculated as "LDL-C-Lp(a)-C," where Lp(a)-C was 30% or 17.3% of total Lp(a) mass. Fine and Gray competing risk-adjusted models were applied for the association between the outcome incident CHD and: 1) LDL-C and LDLLp(a)corr in the total sample; and 2) LDL-C and apoB after stratification by Lp(a) mass (≥/<90th percentile). RESULTS: Similar risk estimates for incident CHD were found for LDL-C and LDL-CLp(a)corr30 or LDL-CLp(a)corr17.3 (subdistribution HR with 95% CI) were 2.73 (95% CI: 2.34-3.20) vs 2.51 (95% CI: 2.15-2.93) vs 2.64 (95% CI: 2.26-3.10), respectively (top vs bottom fifth; fully adjusted models). Categorization by Lp(a) mass resulted in higher subdistribution HRs for uncorrected LDL-C and incident CHD at Lp(a) ≥90th percentile (4.38 [95% CI: 2.08-9.22]) vs 2.60 [95% CI: 2.21-3.07]) at Lp(a) <90th percentile (top vs bottom fifth; Pinteraction0.39). In contrast, apoB risk estimates were lower in subjects with higher Lp(a) mass (2.43 [95% CI: 1.34-4.40]) than in Lp(a) <90th percentile (3.34 [95% CI: 2.78-4.01]) (Pinteraction0.49). CONCLUSIONS: Correction of LDL-C for its Lp(a)-C content provided no meaningful information on CHD-risk estimation at the population level. Simple categorization of Lp(a) mass (≥/<90th percentile) influenced the association between LDL-C or apoB with future CHD mostly at higher Lp(a) levels.

Association of transketolase polymorphisms with diabetic polyneuropathy in the general population: The KORA F4 study.

AIMS: We recently reported that genetic variability in the TKT gene encoding transketolase, a key enzyme in the pentose phosphate pathway, is associated with measures of diabetic sensorimotor polyneuropathy (DSPN) in recent-onset diabetes. Here, we aimed to substantiate these findings in a population-based KORA F4 study. MATERIALS AND METHODS: In this cross-sectional study, we assessed seven single nucleotide polymorphisms (SNPs) in the transketolase gene in 952 participants from the KORA F4 study with normal glucose tolerance (NGT; n = 394), prediabetes (n = 411), and type 2 diabetes (n = 147). DSPN was defined by the examination part of the Michigan Neuropathy Screening Instrument (MNSI) using the original MNSI > 2 cut-off and two alternative versions extended by touch/pressure perception (TPP) (MNSI > 3) and by TPP plus cold perception (MNSI > 4). RESULTS: After adjustment for sex, age, BMI, and HbA1c, in type 2 diabetes participants, four out of seven transketolase SNPs were associated with DSPN for all three MNSI versions (all p ≤ 0.004). The odds ratios of these associations increased with extending the MNSI score, for example, OR (95% CI) for SNP rs62255988 with MNSI > 2: 1.99 (1.16-3.41), MNSI > 3: 2.27 (1.26-4.09), and MNSI > 4: 4.78 (2.22-10.26); SNP rs9284890 with MNSI > 2: 2.43 (1.42-4.16), MNSI > 3: 3.46 (1.82-6.59), and MNSI > 4: 4.75 (2.15-10.51). In contrast, no associations were found between transketolase SNPs and the three MNSI versions in the NGT and prediabetes groups. CONCLUSIONS: The link of genetic variation in transketolase enzyme to diabetic polyneuropathy corroborated at the population level strengthens the concept suggesting an important role of pathways metabolising glycolytic intermediates in the evolution of diabetic polyneuropathy.

Population-based reference values for kidney function and kidney function decline in 25- to 95-year-old Germans without and with diabetes.

Understanding normal aging of kidney function is pivotal to help distinguish individuals at particular risk for chronic kidney disease. Glomerular filtration rate (GFR) is typically estimated via serum creatinine (eGFRcrea) or cystatin C (eGFRcys). Since population-based age-group-specific reference values for eGFR and eGFR-decline are scarce, we aimed to provide such reference values from population-based data of a wide age range. In four German population-based cohorts (KORA-3, KORA-4, AugUR, DIACORE), participants underwent medical exams, interview, and blood draw up to five times within up to 25 years. We analyzed eGFRcrea and eGFRcys cross-sectionally and longitudinally (12,000 individuals, age 25-95 years). Cross-sectionally, we found age-group-specific eGFRcrea to decrease approximately linearly across the full age range, for eGFRcys up to the age of 60 years. Within age-groups, there was little difference by sex or diabetes status. Longitudinally, linear mixed models estimated an annual eGFRcrea decline of -0.80 [95% confidence interval -0.82, -0.77], -0.79 [-0.83, -0.76], and -1.20 mL/min/1.73m2 [-1.33, -1.08] for the general population, "healthy" individuals, or individuals with diabetes, respectively. Reference values for eGFR using cross-sectional data were shown as percentile curves for "healthy" individuals and for individuals with diabetes. Reference values for eGFR-decline using longitudinal data were presented as 95% prediction intervals for "healthy" individuals and for individuals with diabetes, obesity, and/or albuminuria. Thus, our results can help clinicians to judge eGFR values in individuals seen in clinical practice according to their age and to understand the expected range of annual eGFR-decline based on their risk profile.

Sex hormone-binding globulin may explain sex differences for glucose homeostasis and incidence of type 2 diabetes: the KORA study.

Research has indicated that sex hormone-binding globulin (SHBG) is associated with glucose homeostasis and may play a role in the etiology of type 2 diabetes (T2D). While it is unclear whether SHBG may mediate sex differences in glucose control and subsequently, incidence of T2D. We used observational data from the German population-based KORA F4 study (n = 1937, mean age: 54 years, 41% women) and its follow-up examination KORA FF4 (median follow-up 6.5 years, n = 1387). T2D was initially assessed by self-report and validated by contacting the physicians and/ or reviewing the medical charts. Mediation analyses were performed to assess the role of SHBG in mediating the association between sex (women vs. men) and glucose- and insulin-related traits (cross-sectional analysis) and incidence of T2D (longitudinal analysis). After adjustment for confounders, (model 1: adjusted for age; model 2: model 1 + smoking + alcohol consumption + physical activity), women had lower fasting glucose levels compared to men (ß = -4.94 (mg/dl), 95% CI: -5.77, -4.11). SHBG levels were significantly higher in women than in men (ß = 0.47 (nmol/l), 95% CI:0.42, 0.51). Serum SHBG may mediate the association between sex and fasting glucose levels with a proportion mediated (PM) of 30% (CI: 22-41%). Also, a potential mediatory role of SHBG was observed for sex differences in incidence of T2D (PM = 95% and 63% in models 1 and 2, respectively). Our novel findings suggest that SHBG may partially explain sex-differences in glucose control and T2D incidence.

Differential associations between selenoprotein P and distal sensorimotor polyneuropathy in people with and without diabetes: KORA F4/FF4 study.

BACKGROUND: Oxidative stress is a risk factor for distal sensorimotor polyneuropathy (DSPN). Selenoprotein P is a protein with antioxidant properties but has not been investigated in the context of DSPN. This study aimed to assess the associations between selenoprotein P and DSPN in people without and with type 2 diabetes (T2D). METHODS: Cross-sectional and prospective analyses were based on 1053 (including 217 with T2D) and 513 participants (including 79 with T2D), respectively, aged 61-82 years from the population-based KORA F4 survey. DSPN at baseline (KORA F4) and in the follow-up survey KORA FF4 was defined based on the Michigan Neuropathy Screening Instrument. Serum levels of full-length selenoprotein P were quantified by ELISA. Associations between selenoprotein P and prevalent or incident DSPN were estimated using logistic regression analysis adjusting for multiple confounders. RESULTS: Selenoprotein P levels were not associated with prevalent DSPN in the total sample. However, there was a significant interaction by diabetes status. Higher levels of selenoprotein P were associated with lower odds of prevalent DSPN in individuals without T2D (fully adjusted model: OR 0.825 [95 % CI 0.682, 0.998], p = 0.0476), but not in those with T2D (OR [95 % CI] 1.098 [0.829, 1.454], p = 0.5132; pinteraction = 0.0488). Selenoprotein P levels were not associated with incident DSPN over a follow-up of 6.5 years. CONCLUSION: In individuals without T2D from the older general population, lower selenoprotein P levels were associated with a higher prevalence of DSPN. Whether the antioxidant properties of selenoprotein P are responsible for the observed associations remains to be elucidated in future research.

Associations between multiple neurological biomarkers and distal sensorimotor polyneuropathy: KORA F4/FF4 study.

AIMS: The aim of this study was to assess associations between neurological biomarkers and distal sensorimotor polyneuropathy (DSPN). MATERIALS AND METHODS: Cross-sectional analyses were based on 1032 participants aged 61-82 years from the population-based KORA F4 survey, 177 of whom had DSPN at baseline. The prevalence of type 2 diabetes was 20%. Prospective analyses used data from 505 participants without DSPN at baseline, of whom 125 had developed DSPN until the KORA FF4 survey. DSPN was defined based on the examination part of the Michigan Neuropathy Screening Instrument. Serum levels of neurological biomarkers were measured using proximity extension assay technology. Associations between 88 biomarkers and prevalent or incident DSPN were estimated using Poisson regression with robust error variance and are expressed as risk ratios (RR) and 95% CI per 1-SD increase. Results were adjusted for multiple confounders and multiple testing using the Benjamini-Hochberg procedure. RESULTS: Higher serum levels of CTSC (cathepsin C; RR [95% CI] 1.23 (1.08; 1.39), pB-H = 0.044) and PDGFRα (platelet-derived growth factor receptor A; RR [95% CI] 1.21 (1.08; 1.35), pB-H = 0.044) were associated with prevalent DSPN in the total study sample. CDH3, JAM-B, LAYN, RGMA and SCARA5 were positively associated with DSPN in the diabetes subgroup, whereas GCP5 was positively associated with DSPN in people without diabetes (all pB-H for interaction <0.05). None of the biomarkers showed an association with incident DSPN (all pB-H>0.05). CONCLUSIONS: This study identified multiple novel associations between neurological biomarkers and prevalent DSPN, which may be attributable to functions of these proteins in neuroinflammation, neural development and myelination.

Prognostic Value of Cardiovascular Biomarkers in the Population.

Importance: Identification of individuals at high risk for atherosclerotic cardiovascular disease within the population is important to inform primary prevention strategies. Objective: To evaluate the prognostic value of routinely available cardiovascular biomarkers when added to established risk factors. Design, Setting, and Participants: Individual-level analysis including data on cardiovascular biomarkers from 28 general population-based cohorts from 12 countries and 4 continents with assessments by participant age. The median follow-up was 11.8 years. Exposure: Measurement of high-sensitivity cardiac troponin I, high-sensitivity cardiac troponin T, N-terminal pro-B-type natriuretic peptide, B-type natriuretic peptide, or high-sensitivity C-reactive protein. Main Outcomes and Measures: The primary outcome was incident atherosclerotic cardiovascular disease, which included all fatal and nonfatal events. The secondary outcomes were all-cause mortality, heart failure, ischemic stroke, and myocardial infarction. Subdistribution hazard ratios (HRs) for the association of biomarkers and outcomes were calculated after adjustment for established risk factors. The additional predictive value of the biomarkers was assessed using the C statistic and reclassification analyses. Results: The analyses included 164 054 individuals (median age, 53.1 years [IQR, 42.7-62.9 years] and 52.4% were women). There were 17 211 incident atherosclerotic cardiovascular disease events. All biomarkers were significantly associated with incident atherosclerotic cardiovascular disease (subdistribution HR per 1-SD change, 1.13 [95% CI, 1.11-1.16] for high-sensitivity cardiac troponin I; 1.18 [95% CI, 1.12-1.23] for high-sensitivity cardiac troponin T; 1.21 [95% CI, 1.18-1.24] for N-terminal pro-B-type natriuretic peptide; 1.14 [95% CI, 1.08-1.22] for B-type natriuretic peptide; and 1.14 [95% CI, 1.12-1.16] for high-sensitivity C-reactive protein) and all secondary outcomes. The addition of each single biomarker to a model that included established risk factors improved the C statistic. For 10-year incident atherosclerotic cardiovascular disease in younger people (aged <65 years), the combination of high-sensitivity cardiac troponin I, N-terminal pro-B-type natriuretic peptide, and high-sensitivity C-reactive protein resulted in a C statistic improvement from 0.812 (95% CI, 0.8021-0.8208) to 0.8194 (95% CI, 0.8089-0.8277). The combination of these biomarkers also improved reclassification compared with the conventional model. Improvements in risk prediction were most pronounced for the secondary outcomes of heart failure and all-cause mortality. The incremental value of biomarkers was greater in people aged 65 years or older vs younger people. Conclusions and Relevance: Cardiovascular biomarkers were strongly associated with fatal and nonfatal cardiovascular events and mortality. The addition of biomarkers to established risk factors led to only a small improvement in risk prediction metrics for atherosclerotic cardiovascular disease, but was more favorable for heart failure and mortality.

Air pollution, traffic noise, greenness, and temperature and the risk of incident type 2 diabetes: Results from the KORA cohort study.

Introduction: Type 2 diabetes (T2D) is a major public health concern, and various environmental factors have been associated with the development of this disease. This study aimed to investigate the longitudinal effects of multiple environmental exposures on the risk of incident T2D in a German population-based cohort. Methods: We used data from the KORA cohort study (Augsburg, Germany) and assessed exposure to air pollutants, traffic noise, greenness, and temperature at the participants' residencies. Cox proportional hazard models were used to analyze the associations with incident T2D, adjusting for potential confounders. Results: Of 7736 participants included in the analyses, 10.5% developed T2D during follow-up (mean: 15.0 years). We found weak or no association between environmental factors and the risk of T2D, with sex and education level significantly modifying the effects of air pollutants. Conclusion: Our study contributes to the growing body of literature investigating the impact of environmental factors on T2D risks and suggests that the impact of environmental factors may be small.

Associations of Proteomics With Hypertension and Systolic Blood Pressure: KORA S4/F4/FF4 and KORA Age1/Age2 Cohort Studies.

BACKGROUND: Hypertension, a complex condition, is primarily defined based on blood pressure readings without involving its pathophysiological mechanisms. We aimed to identify biomarkers through a proteomic approach, thereby enhancing the future definition of hypertension with insights into its molecular mechanisms. METHODS: The discovery analysis included 1560 participants, aged 55 to 74 years at baseline, from the KORA (Cooperative Health Research in the Region of Augsburg) S4/F4/FF4 cohort study, with 3332 observations over a median of 13.4 years of follow-up. Generalized estimating equations were used to estimate the associations of 233 plasma proteins with hypertension and systolic blood pressure (SBP). For validation, proteins significantly associated with hypertension or SBP in the discovery analysis were validated in the KORA Age1/Age2 cohort study (1024 participants, 1810 observations). A 2-sample Mendelian randomization analysis was conducted to infer causalities of validated proteins with SBP. RESULTS: Discovery analysis identified 49 proteins associated with hypertension and 99 associated with SBP. Validation in the KORA Age1/Age2 study replicated 7 proteins associated with hypertension and 23 associated with SBP. Three proteins, NT-proBNP (N-terminal pro-B-type natriuretic peptide), KIM1 (kidney injury molecule 1), and OPG (osteoprotegerin), consistently showed positive associations with both outcomes. Five proteins demonstrated potential causal associations with SBP in Mendelian randomization analysis, including NT-proBNP and OPG. CONCLUSIONS: We identified and validated 7 hypertension-associated and 23 SBP-associated proteins across 2 cohort studies. KIM1, NT-proBNP, and OPG demonstrated robust associations, and OPG was identified for the first time as associated with blood pressure. For NT-proBNP (protective) and OPG, causal associations with SBP were suggested.

Clusters of longitudinal risk profile trajectories are associated with cardiometabolic diseases: Results from the population-based KORA cohort.

BACKGROUND: Multiple risk factors contribute jointly to the development and progression of cardiometabolic diseases. Therefore, joint longitudinal trajectories of multiple risk factors might represent different degrees of cardiometabolic risk. METHODS: We analyzed population-based data comprising three examinations (Exam 1: 1999-2001, Exam 2: 2006-2008, Exam 3: 2013-2014) of 976 male and 1004 female participants of the KORA cohort (Southern Germany). Participants were followed up for cardiometabolic diseases, including cardiovascular mortality, myocardial infarction and stroke, or a diagnosis of type 2 diabetes, until 2016. Longitudinal multivariate k-means clustering identified sex-specific trajectory clusters based on nine cardiometabolic risk factors (age, systolic and diastolic blood pressure, body-mass-index, waist circumference, Hemoglobin-A1c, total cholesterol, high- and low-density lipoprotein cholesterol). Associations between clusters and cardiometabolic events were assessed by logistic regression models. RESULTS: We identified three trajectory clusters for men and women, respectively. Trajectory clusters reflected a distinct distribution of cardiometabolic risk burden and were associated with prevalent cardiometabolic disease at Exam 3 (men: odds ratio (OR)ClusterII = 2.0, 95% confidence interval: (0.9-4.5); ORClusterIII = 10.5 (4.8-22.9); women: ORClusterII = 1.7 (0.6-4.7); ORClusterIII = 5.8 (2.6-12.9)). Trajectory clusters were furthermore associated with incident cardiometabolic cases after Exam 3 (men: ORClusterII = 3.5 (1.1-15.6); ORClusterIII = 7.5 (2.4-32.7); women: ORClusterII = 5.0 (1.1-34.1); ORClusterIII = 8.0 (2.2-51.7)). Associations remained significant after adjusting for a single time point cardiovascular risk score (Framingham). CONCLUSIONS: On a population-based level, distinct longitudinal risk profiles over a 14-year time period are differentially associated with cardiometabolic events. Our results suggest that longitudinal data may provide additional information beyond single time-point measures. Their inclusion in cardiometabolic risk assessment might improve early identification of individuals at risk.

Omentin associates with serum metabolite profiles indicating lower diabetes risk: KORA F4 Study.

INTRODUCTION: Circulating omentin levels have been positively associated with insulin sensitivity. Although a role for adiponectin in this relationship has been suggested, underlying mechanisms remain elusive. In order to reveal the relationship between omentin and systemic metabolism, this study aimed to investigate associations of serum concentrations of omentin and metabolites. RESEARCH DESIGN AND METHODS: This study is based on 1124 participants aged 61-82 years from the population-based KORA (Cooperative Health Research in the Region of Augsburg) F4 Study, for whom both serum omentin levels and metabolite concentration profiles were available. Associations were assessed with five multivariable regression models, which were stepwise adjusted for multiple potential confounders, including age, sex, body mass index, waist-to-hip ratio, lifestyle markers (physical activity, smoking behavior and alcohol consumption), serum adiponectin levels, high-density lipoprotein cholesterol, use of lipid-lowering or anti-inflammatory medication, history of myocardial infarction and stroke, homeostasis model assessment 2 of insulin resistance, diabetes status, and use of oral glucose-lowering medication and insulin. RESULTS: Omentin levels significantly associated with multiple metabolites including amino acids, acylcarnitines, and lipids (eg, sphingomyelins and phosphatidylcholines (PCs)). Positive associations for several PCs, such as diacyl (PC aa C32:1) and alkyl-alkyl (PC ae C32:2), were significant in models 1-4, whereas those with hydroxytetradecenoylcarnitine (C14:1-OH) were significant in all five models. Omentin concentrations were negatively associated with several metabolite ratios, such as the valine-to-PC ae C32:2 and the serine-to-PC ae C32:2 ratios in most models. CONCLUSIONS: Our results suggest that omentin may influence insulin sensitivity and diabetes risk by changing systemic lipid metabolism, but further mechanistic studies investigating effects of omentin on metabolism of insulin-sensitive tissues are needed.

Association of plasma proteomics with incident coronary heart disease in individuals with and without type 2 diabetes: results from the population-based KORA study.

BACKGROUND: Coronary heart disease (CHD) is a major global health concern, especially among individuals with type 2 diabetes (T2D). Given the crucial role of proteins in various biological processes, this study aimed to elucidate the aetiological role and predictive performance of protein biomarkers on incident CHD in individuals with and without T2D. METHODS: The discovery cohort included 1492 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 study with 147 incident CHD cases (45 vs. 102 cases in the group with T2D and without T2D, respectively) during 15.6 years of follow-up. The validation cohort included 888 participants from the KORA-Age1 study with 70 incident CHD cases (19 vs. 51 cases in the group with T2D and without T2D, respectively) during 6.9 years of follow-up. We measured 233 plasma proteins related to cardiovascular disease and inflammation using proximity extension assay technology. Associations of proteins with incident CHD were assessed using Cox regression and Mendelian randomization (MR) analysis. Predictive models were developed using priority-Lasso and were evaluated on top of Framingham risk score variables using the C-index, category-free net reclassification index (cfNRI), and relative integrated discrimination improvement (IDI). RESULTS: We identified two proteins associated with incident CHD in individuals with and 29 in those without baseline T2D, respectively. Six of these proteins are novel candidates for incident CHD. MR suggested a potential causal role for hepatocyte growth factor in CHD development. The developed four-protein-enriched model for individuals with baseline T2D (ΔC-index: 0.017; cfNRI: 0.253; IDI: 0.051) and the 12-protein-enriched model for individuals without baseline T2D (ΔC-index: 0.054; cfNRI: 0.462; IDI: 0.024) consistently improved CHD prediction in the discovery cohort, while in the validation cohort, significant improvements were only observed for selected performance measures (with T2D: cfNRI: 0.633; without T2D: ΔC-index: 0.038; cfNRI: 0.465). CONCLUSIONS: This study identified novel protein biomarkers associated with incident CHD in individuals with and without T2D and reaffirmed previously reported protein candidates. These findings enhance our understanding of CHD pathophysiology and provide potential targets for prevention and treatment.

Epigenome-wide association study of dietary fatty acid intake.

BACKGROUND: Dietary intake of n-3 polyunsaturated fatty acids (PUFA) may have a protective effect on the development of cardiovascular diseases, diabetes, depression and cancer, while a high intake of n-6 PUFA was often reported to be associated with inflammation-related traits. The effect of PUFAs on health outcomes might be mediated by DNA methylation (DNAm). The aim of our study is to identify the impact of PUFA intake on DNAm in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 cohort and the Leiden Longevity Study (LLS). RESULTS: DNA methylation levels were measured in whole blood from the population-based KORA FF4 study (N = 1354) and LLS (N = 448), using the Illumina MethylationEPIC BeadChip and Illumina HumanMethylation450 array, respectively. We assessed associations between DNAm and intake of eight and four PUFAs in KORA and LLS, respectively. Where possible, results were meta-analyzed. Below the Bonferroni correction threshold (p < 7.17 × 10-8), we identified two differentially methylated positions (DMPs) associated with PUFA intake in the KORA study. The DMP cg19937480, annotated to gene PRDX1, was positively associated with docosahexaenoic acid (DHA) in model 1 (beta: 2.00 × 10-5, 95%CI: 1.28 × 10-5-2.73 × 10-5, P value: 6.98 × 10-8), while cg05041783, annotated to gene MARK2, was positively associated with docosapentaenoic acid (DPA) in our fully adjusted model (beta: 9.80 × 10-5, 95%CI: 6.25 × 10-5-1.33 × 10-4, P value: 6.75 × 10-8). In the meta-analysis, we identified the CpG site (cg15951061), annotated to gene CDCA7L below Bonferroni correction (1.23 × 10-7) associated with eicosapentaenoic acid (EPA) intake in model 1 (beta: 2.00 × 10-5, 95% CI: 1.27 × 10-5-2.73 × 10-5, P value = 5.99 × 10-8) and we confirmed the association of cg19937480 with DHA in both models 1 and 2 (beta: 2.07 × 10-5, 95% CI: 1.31 × 10-5-2.83 × 10-5, P value = 1.00 × 10-7 and beta: 2.19 × 10-5, 95% CI: 1.41 × 10-5-2.97 × 10-5, P value = 5.91 × 10-8 respectively). CONCLUSIONS: Our study identified three CpG sites associated with PUFA intake. The mechanisms of these sites remain largely unexplored, highlighting the novelty of our findings. Further research is essential to understand the links between CpG site methylation and PUFA outcomes.

Association of serum magnesium with metabolic syndrome and the role of chronic kidney disease: A population-based cohort study with Mendelian randomization.

OBJECTIVES: To assess the association of serum magnesium with prevalent and incident metabolic syndrome (MetS) and its individual components in the general population and to examine any effect modification by chronic kidney disease (CKD) status. METHODS: We analysed longitudinal data from the population-based KORA F4/FF4 study, including 2996 participants (387 with CKD) for cross-sectional analysis and 1446 participants (88 with CKD) for longitudinal analysis. Associations with MetS, as well as single components of MetS, were assessed by adjusted regression models. Nonlinearity was tested by restricted cubic splines and analyses were stratified by CKD. Causality was evaluated by two-sample Mendelian randomization (MR). RESULTS: Serum magnesium (1 SD) was inversely associated with prevalent MetS (odds ratio [OR] 0.90, 95% confidence interval [CI] 0.83, 0.98). The association was more pronounced in individuals with CKD (OR 0.75, 95% CI 0.59, 0.94). Among MetS components, serum magnesium was negatively associated with elevated fasting glucose (OR 0.78, 95% CI 0.71, 0.88) and, again, this association was more pronounced in individuals with CKD (OR 0.67, 95% CI 0.53, 0.84). Serum magnesium was not associated with incident MetS or its components. Restricted cubic spline analysis revealed a significant nonlinear inverse relationship of serum magnesium with MetS and elevated fasting glucose. MR analysis suggested an inverse causal effect of serum magnesium on MetS (OR 0.91, 95% CI 0.85, 0.97). CONCLUSION: Serum magnesium is associated with prevalent, but not incident MetS, and this effect is stronger in individuals with CKD. MR analysis implies a potential, albeit weak, causal role of magnesium in MetS.

C-reactive protein modifies lipoprotein(a)-related risk for coronary heart disease: the BiomarCaRE project.

BACKGROUND AND AIMS: Recent investigations have suggested an interdependence of lipoprotein(a) [Lp(a)]-related risk for cardiovascular disease with background inflammatory burden. The aim the present analysis was to investigate whether high-sensitive C-reactive protein (hsCRP) modulates the association between Lp(a) and coronary heart disease (CHD) in the general population. METHODS: Data from 71 678 participants from 8 European prospective population-based cohort studies were used (65 661 without/6017 with established CHD at baseline; median follow-up 9.8/13.8 years, respectively). Fine and Gray competing risk-adjusted models were calculated according to accompanying hsCRP concentration (<2 and ≥2 mg/L). RESULTS: Among CHD-free individuals, increased Lp(a) levels were associated with incident CHD irrespective of hsCRP concentration: fully adjusted sub-distribution hazard ratios [sHRs (95% confidence interval)] for the highest vs. lowest fifth of Lp(a) distribution were 1.45 (1.23-1.72) and 1.48 (1.23-1.78) for a hsCRP group of <2 and ≥2 mg/L, respectively, with no interaction found between these two biomarkers on CHD risk (Pinteraction = 0.82). In those with established CHD, similar associations were seen only among individuals with hsCRP ≥ 2 mg/L [1.34 (1.03-1.76)], whereas among participants with a hsCRP concentration <2 mg/L, there was no clear association between Lp(a) and future CHD events [1.29 (0.98-1.71)] (highest vs. lowest fifth, fully adjusted models; Pinteraction = 0.024). CONCLUSIONS: While among CHD-free individuals Lp(a) was significantly associated with incident CHD regardless of hsCRP, in participants with CHD at baseline, Lp(a) was related to recurrent CHD events only in those with residual inflammatory risk. These findings might guide adequate selection of high-risk patients for forthcoming Lp(a)-targeting compounds.

Proteogenomic Data Integration Reveals CXCL10 as a Potentially Downstream Causal Mediator for IL-6 Signaling on Atherosclerosis.

BACKGROUND: Genetic and experimental studies support a causal involvement of IL-6 (interleukin-6) signaling in atheroprogression. Although trials targeting IL-6 signaling are underway, any benefits must be balanced against an impaired host immune response. Dissecting the mechanisms that mediate the effects of IL-6 signaling on atherosclerosis could offer insights about novel drug targets with more specific effects. METHODS: Leveraging data from 522 681 individuals, we constructed a genetic instrument of 26 variants in the gene encoding the IL-6R (IL-6 receptor) that proxied for pharmacological IL-6R inhibition. Using Mendelian randomization, we assessed its effects on 3281 plasma proteins quantified with an aptamer-based assay in the INTERVAL cohort (n=3301). Using mediation Mendelian randomization, we explored proteomic mediators of the effects of genetically proxied IL-6 signaling on coronary artery disease, large artery atherosclerotic stroke, and peripheral artery disease. For significant mediators, we tested associations of their circulating levels with incident cardiovascular events in a population-based study (n=1704) and explored the histological, transcriptomic, and cellular phenotypes correlated with their expression levels in samples from human atherosclerotic lesions. RESULTS: We found significant effects of genetically proxied IL-6 signaling on 70 circulating proteins involved in cytokine production/regulation and immune cell recruitment/differentiation, which correlated with the proteomic effects of pharmacological IL-6R inhibition in a clinical trial. Among the 70 significant proteins, genetically proxied circulating levels of CXCL10 (C-X-C motif chemokine ligand 10) were associated with risk of coronary artery disease, large artery atherosclerotic stroke, and peripheral artery disease, with up to 67% of the effects of genetically downregulated IL-6 signaling on these end points mediated by decreases in CXCL10. Higher midlife circulating CXCL10 levels were associated with a larger number of cardiovascular events over 20 years, whereas higher CXCL10 expression in human atherosclerotic lesions correlated with a larger lipid core and a transcriptomic profile reflecting immune cell infiltration, adaptive immune system activation, and cytokine signaling. CONCLUSIONS: Integrating multiomics data, we found a proteomic signature of IL-6 signaling activation and mediators of its effects on cardiovascular disease. Our analyses suggest the interferon-γ-inducible chemokine CXCL10 to be a potentially causal mediator for atherosclerosis in 3 vascular compartments and, as such, could serve as a promising drug target for atheroprotection.

Age- and sex-adjusted reference intervals for steroid hormones measured by liquid chromatography-tandem mass spectrometry using a widely available kit.

Objective: Measurements utilizing commercially available sets of reagents for determination of steroid hormone profiles by liquid chromatography-tandem mass spectrometry (LC-MS/MS) have become increasingly important for routine laboratories. However, method-specific publications of reference intervals obtained from sufficiently large studies are often missing. Methods: After validation of performance characteristics, a widely available kit for steroid analysis by LC-MS/MS was used to measure concentrations of 15 endogenous steroids (aldosterone, cortisol, cortisone, corticosterone, 11-deoxycortisol, 21-deoxycortisol, dehydroepiandrosterone sulfate, estradiol, testosterone, androstenedione, dihydrotestosterone, dehydroepiandrosterone, 17-hydroxyprogesterone, 11-deoxycorticosterone, progesterone) in more than 500 blood samples from a population-based study. While randomly selected from a larger cohort, the samples equally represented both sexes and covered a wide range of adult age groups. Age- and sex-specific reference intervals were calculated, and correlation with BMI was assessed. Results: Performance characteristics of the assay matched expectations for 9 of 15 steroids. For most of them, reference intervals obtained from our study population were comparable to those reported by others, with age and sex being the major determinants. A sex-specific correlation with BMI was found for seven steroids. We identified limitations regarding sensitivity of the method for quantification of progesterone in males and postmenopausal females. Concentrations of aldosterone, 21-deoxycortisol, estradiol, 11-deoxycorticosterone, and dihydrotestosterone could not be quantified in a large percentage of samples. Conclusions: The reference intervals for nine steroids will support meaningful interpretation for steroid profiles as measured by a widely used kit for LC-MS/MS-based quantification. Laboratories using such kits must be aware of potential limitations in sensitivity for some steroids included in the profile. Significance Statement: Quantification of steroid hormones is a cornerstone for diagnosis of several diseases. Commonly used immunoassays have limitations in specificity. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a promising alternative, particularly if methods are harmonized across laboratories. The use of kits from commercial suppliers might support this. Clinical interpretation of steroid concentrations requires availability of appropriate reference intervals (RIs), but studies on RIs reported in the literature differ in preanalytical and analytical procedures. Here, we provide RIs for steroids measured by a widely available kit under preanalytical conditions mirroring common clinical practice. Such RIs might facilitate interpretation for those using the same method and comparable conditions in clinical routine.

Long-term exposure to ambient air pollution and inflammatory response in the KORA study.

Previous studies consistently showed an association between fine atmospheric particulate matter (PM2.5) and cardiovascular diseases. Concerns about adverse health effects of ultrafine particles (UFP) are growing but long-term studies are still scarce. In this study, we examined the association between long-term exposure to ambient air pollutants and blood biomarkers of inflammation and coagulation, including fibrinogen, high-sensitivity C-reactive protein (hs-CRP), serum amyloid A (SAA) adiponectin and interleukin-6 (IL-6), measured in the German KORA-S4 cohort study (1999-2001). IL-6 was available for older participants only, who were therefore considered as a subsample. Annual mean concentrations of UFP (as particle number concentration), particulate matter in different particles sizes (PM10, PMcoarse, PM2.5, PM2.5 absorbance), ozone (O3), and nitrogen oxides (NO2, NOX) were estimated by land-use regression models and assigned to participants' home addresses. We performed a multiple linear regression between each pollutant and each biomarker with adjustment for confounders. Per 1 interquartile range (IQR, 1945 particles/cm3) increase of UFP, fibrinogen increased by 0.70 % (0.04; 1.37) and hs-CRP increased by 3.16 % (-0.52; 6.98). Adiponectin decreased by -2.53 % (-4.78; -0.24) per 1 IQR (1.4 µg/m3) increase of PM2.5. Besides, PM2.5 was associated with increased IL-6 in the subsample. In conclusion, we observed that long-term exposure to air pollutants, including both fine and ultrafine particles, was associated with higher concentrations of pro-inflammatory and lower concentrations of an anti-inflammatory blood biomarkers, which is consistent with an increased risk for cardiovascular disease observed for long-term exposure to air pollutants.