BACKGROUND:Cholesterol is a main contributor to coronary artery disease (CAD). Although the genetic basis of blood cholesterol concentration is well studied, there is currently a lack of studies investigating the genetics of its precursors from de novo biosynthesis. METHODS:We conducted a genome-wide association meta-analysis, combining data from KORA, LIFE-Heart, LIFE-Adult, LURIC, the Sorbs study, and YFS, resulting in up to 10,519 individuals. We investigated 14 traits related to serum concentrations of lanosterol, desmosterol, and cholesterol. Direct and indirect effects of lanosterol on CAD were investigated with a Mendelian randomisation mediation analysis. FINDINGS:Our analysis revealed four genome-wide significant (p < 5 × 10-8) associations not previously reported in the GWAS catalogue. These include two loci without prior connection to cholesterol, associated with lanosterol (7q21.2, CYP51A1) and free cholesterol (11q14.1), and two associations with lanosterol at loci previously reported for cholesterol (5q13.3, HMGCR; 11q23.3, APO cluster). We also replicated eight loci previously reported for associations with cholesterol-related traits. Lanosterol exhibited significant total and indirect effects on CAD, but its direct effect was not significant. INTERPRETATION:We demonstrate that the investigation of intermediate phenotypes can help to functionally fine map previously reported associations for cholesterol, improving our understanding of genetic regulation of cholesterol concentrations. Further, the effect of lanosterol on CAD is probably fully mediated by total cholesterol. FUNDING:This investigation was primarily funded by the ministry for science and health of the Rhineland-Palatinate through the CoAGE graduate programme. A complete list of funding organisations is provided in the acknowledgements.

BackgroundAngiopoietin-like 3/4/8 (ANGPTL3/4/8) proteins play critical roles in modulating lipid metabolism through calorically sensitive and tissue-specific regulation of lipoprotein lipase (LPL) activity via formation of ANGPTL3/8 and ANGPTL4/8 complexes. ANGPTL3/4/8 proteins are also associated with cardiovascular risk. Circulating levels of ANGPTL3, ANGPTL4/8, and C-terminal domain-containing ANGPTL4 (CD-ANGPTL4) have been associated with overall cardiovascular mortality. In this study, we investigated the associations of ANGPTL3/4/8 proteins and complexes with heart failure (HF) and HF death.MethodsWe studied 2,394 participants of the LUdwigshafen RIsk and Cardiovascular Health (LURIC) study, a cohort of patients referred for coronary angiography. HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF) were diagnosed at baseline. There was a follow-up period with a median (interquartile range) duration of 9.80 (8.75-10.40) years. ANGPTL3/4/8 proteins and complexes were measured at baseline using dedicated immunoassays, and their serum concentrations were compared to HF data.ResultsThere was an inverse association of ANGPTL3/8 with the N-terminal prohormone of B-type natriuretic peptide (NT-proBNP). ANGPTL3 was positively associated with NT-proBNP, HFpEF, and the New York Heart Association (NYHA) functional class. ANGPTL4/8 was positively associated with HFrEF, HFpEF, and NT-proBNP and was inversely associated with the left ventricular ejection fraction (LVEF). CD-ANGPTL4 was positively associated with the NYHA functional class, HFrEF, HFpEF, and NT-proBNP and was inversely associated with LVEF. A total of 101 participants died from HF. ANGPTL3/8 and ANGPTL4/8 were not associated with HF mortality. In contrast, ANGPTL3 and especially CD-ANGPTL4 were positively associated with HF death.ConclusionsWe found positive associations of ANGPTL3 and CD-ANGPTL4 with HF and HF mortality. Of particular interest, serum levels of CD-ANGPTL4 demonstrated positive associations with HFrEF, HFpEF, NT-proBNP, and NYHA functional class and an inverse association with LVEF. CD-ANGPTL4 also demonstrated the strongest positive association with HF mortality. The explanation for these associations is not currently apparent. Further investigation will be required to understand more fully the possible biochemical mechanisms that may be responsible for these associations.

Abstract Aims Blood concentrations of amino acids have been associated with depression, although findings have been inconsistent. We investigated associations between serum amino acid concentrations and genetic liability to depression, assessed by two genetic depression risk scores, in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. Methods The LURIC study enrolled 3,316 participants referred for coronary angiography; serum amino acid measurements were available for 2,143 individuals and were quantified by ion-exchange chromatography. Two weighted genetic depression risk scores, based on 101 and 220 genome-wide significant variants, were calculated. Associations between genetic depression risk scores and amino acid concentrations were assessed using multivariable linear regression models adjusted for age, sex, body mass index, renal function (eGFR), diabetes, hypertension, and coronary artery disease. Clinical depression data were not available; thus, analyses reflect genetic liability rather than manifest depression. Results In multivariable-adjusted analyses, higher genetic depression risk (per SD increase) was associated with lower concentrations of α-aminoadipic acid (GDRS₁₀₁: β = −0.097, 95% CI − 0.161 to − 0.033, p = 0.003; GDRS₂₂₀: β = −0.076, 95% CI − 0.141 to − 0.011, p = 0.021), which remained significant after false discovery rate (FDR) correction. α-aminobutyric acid showed inverse associations that did not remain significant after FDR correction. No statistically significant associations for other amino acids remained after multivariable adjustment and correction for multiple testing. Restricted cubic spline analyses suggested predominantly linear relationships, with evidence of non-linearity observed for selected amino acids, particularly homoarginine with respect to GDRS₂₂₀ (p for non-linearity = 0.005). Conclusion Genetic liability to depression was associated with differences in serum amino acid concentrations, particularly lower α-aminoadipic acid concentrations in this cardiovascular cohort, whereas associations with other amino acids were not robust after correction for multiple testing. These findings are associative and hypothesis-generating and should be confirmed in cohorts with detailed depression phenotyping and longitudinal follow-up.

Seasonal variation in cardiovascular disease (CVD) is well documented. Data on seasonal fluctuations in cardiovascular risk markers are relatively sparse but may be relevant for CVD risk classification and treatment. We aimed to quantify the presence, magnitude, and timing of seasonality across various cardiovascular risk markers in patients referred to coronary angiography. In this retrospective, cross-sectional study, we analysed cardiovascular risk markers in 3316 patients referred to coronary angiography between July 1997 and January 2000 from the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. Seasonal patterns were assessed using robust cosinor regressions, while correcting for age and sex. For each cardiovascular risk marker, we evaluated seasonality, peak date and magnitude (difference between peak and nadir) of seasonal fluctuations. Accordingly, we analysed 24 different cardiovascular risk markers and corrected for the false discovery rate (FDR). Overall, 16 cardiovascular risk markers showed significant seasonal dependency, of which the following had Cohen’s d higher than 0.2 (peak-nadir difference): 25-hydroxyvitamin D (10.28 ng/mL), LDL cholesterol (15.36 mg/dL), HbA1c (0.31

Aims The study investigated the association between self-reported physical fitness (SRPF) and mortality in 3248 participants of the Ludwigshafen Risk and Cardiovascular Health (LURIC) study with a mean follow-up of 9.9 years. Methods and results Self-reported physical fitness was inquired using an 11-point Likert scale on a paper-pencil questionnaire at enrolment, and we defined five distinct classes. Kaplan-Meier survival analysis and Cox regression models were used to investigate the association with mortality. Participants with higher baseline SRPF had a significantly lower risk of all-cause and cardiovascular mortality. Regarding cardiovascular mortality, participants in the highest SRPF class had the lowest risk with a hazard ratio of 0.14 (95% CI 0.08-0.24) compared with the lowest SRPF class. These associations remained statistically significant after adjustment for age, sex, hypertension, diabetes mellitus, low-density lipoprotein cholesterol, glycated haemoglobin A1c (HbA1c), smoking, and other confounders, including comorbidities. Similar results were seen in both participants with angiographically documented coronary artery disease (CAD, n = 2583, 78%) and those without CAD (n = 733; 22%). Higher SRPF was associated with significantly lower systolic blood pressure and resting heart rate as well as lower HbA1c, fasting glucose, serum uric acid, and lower inflammatory markers such as high-sensitive-C-reactive protein, interleukin-6, and serum amyloid A. Conversely, a higher SRPF was associated with higher apolipoprotein A-2 and high-density lipoprotein cholesterol concentrations (P < 0.001). Conclusion Our research shows that SRPF is a strong predictor of overall and cardiovascular mortality for individuals with and without CAD. This suggests that SRPF should be part of routine medical check-ups, highlighting the importance of promoting physical activity for cardiovascular health. Lay Summary This study shows that self-reported physical fitness (SRPF) is a strong predictor of mortality, with higher self-rated fitness linked to lower risks of both all-cause and cardiovascular mortality, independent of other risk factors.Low SRPF is significantly associated with increased risk of all-cause and cardiovascular mortality, suggesting it may be an important indicator for health outcomes.High SRPF shows a protective association, highlighting its potential as an accessible, low-cost tool for promoting cardiovascular health in routine medical assessments.

BACKGROUND:Serum uromodulin (SUmod) and carbamylated albumin (C-Alb) are emerging biomarkers for chronic kidney disease (CKD) progression and mortality. SUmod reflects tubular health, while C-Alb is associated with excretory kidney function, CKD progression, and cardiovascular (CV) mortality. We hypothesized that the combined use of these markers would improve mortality risk assessments. METHODS:We analyzed the associations of C-Alb and SUmod levels with the estimated glomerular filtration rate (eGFR) along with their combined predictive value for assessing mortality in 3316 participants of the Ludwigshafen Risk and Cardiovascular Health study showing mid to high CV risk. RESULTS:SUmod correlated moderately with eGFR (ρ = 0.39, P < 0.001) and weakly and inversely with C-Alb (ρ = -0.19, P < 0.001); C-Alb negatively correlated with eGFR (ρ = -0.38, P < 0.001). Patients in the C-Alb high/SUmod low group had the highest mortality risk [hazard ratio (HR)= 3.30; 95% CI, 2.73-3.99], which remained significant after adjustment for confounders, including eGFR (HR = 1.89; 95% CI, 1.24-1.89). In risk-prediction models for all-cause mortality, adding SUmod increased the area under the curve (AUC) from 0.728 to 0.746 (P < 0.001), C-Alb to 0.738 (P = 0.026), and both combined to 0.751 (P < 0.001). For CV mortality, AUC rose from 0.698 to 0.721 with SUmod (P < 0.001), to 0.711 with C-Alb (P = 0.018), and to 0.727 (P = 0.004) in the combined model. CONCLUSIONS:SUmod and C-Alb levels yield complementary insights into kidney function, biology, and mortality risk beyond eGFR. Low SUmod/high C-Alb revealed the highest mortality risk, even after multivariate adjustment. GERMAN CLINICAL TRIALS REGISTER NUMBER:DRKS00032641.

MicroRNAs have been suggested as essential hypertension biomarkers, but evidence remains inconclusive due to limited high-throughput studies in population cohorts. We analyzed data from the Young Finns Study (YFS) from 2011 and 2018-2020 to assess cross-sectional and prospective associations between circulatory microRNAs, blood pressure (BP), and hypertension. Hypertension risk prediction potential was assessed using nested logistic and Weibull survival models; model performance was evaluated with likelihood ratio (LR) test and c-statistic. All models were adjusted with relevant risk factors. In 2011, whole blood microRNAs were profiled for 871 individuals (83 with hypertension); in 2018-2020, 760 were re-examined, with 67 newly diagnosed. Cross-sectionally, 16 miRNAs correlated with BP (Spearman, PFDR  < 0.05); miR-122-5p (fold change = 1.33) and miR-144-5p (fold change = -1.10) differentiated hypertensive individuals ( U test, PFDR  < 0.05). Associations persisted in adjusted regression models and some replicated in LURIC ( n  = 999) and YFS serum data ( n  = 126). Prospectively, miR-19a-3p [odds ratio (OR) = 1.51, 95% confidence interval (95% CI): 1.14-2.18], miR-19b-3p (OR = 1.50, 95% CI:1.11-2.04), and miR-329-3p (OR = 0.58, 95% CI: 0.39-0.74) levels prognosed hypertension incident. miR-329-3p improved model fit (LR test, P  = 2.85×10 -4 ) and discrimination (c-statistic = 0.849, Δ = 0.026). miR-19b-3p predicted time to onset (hazard ratio = 2.13, 95% CI: 1.38-4.45), improving model fit (LR test, P  = 0.0012) and time-dependent discrimination at 7 and 8-year horizons. Our findings highlight both novel and previously reported miRNAs associating with BP and hypertension and suggest that miR-329-3p, miR-19a-3p, and miR-19b-3p as promising candidates for further investigation in hypertension risk prediction.

Homozygous carriers of the CNDP1 (CTG)5 allele with diabetes mellitus are believed to have a lower risk of developing diabetic kidney disease compared to individuals carrying alleles with higher numbers of this CTG repeat. However, recent studies claimed that homozygosity for the (CTG)5 allele increases the risk of disease progression towards end-stage renal disease and even cardiovascular mortality, at least in women. Therefore, this study sought to confirm in a prospective manner in a cardiovascular high-risk cohort if individuals with two (CTG)5 alleles indeed have an increased cardiovascular mortality. 3,201 individuals from the LURIC study were included and followed for a median of 9.9 years. CNDP1 (CTG)n genotypes were assessed and related to all-cause and cardiovascular mortality. 1,157 (36.1%) patients carried the homozygous CNDP1 (CTG)5 genotype. No significant difference for all-cause and cardiovascular mortality was detected after multiple adjustments for cardiovascular risk factors, neither for the whole cohort nor for men or women, respectively. In this prospective cardiovascular high-risk cohort, homozygosity for the CNDP1 (CTG)5 allele was not associated with increased cardiovascular mortality compared to all other genotypes together. These findings do not confirm previous reports suggesting a sex-specific increase in cardiovascular mortality among women carrying two (CTG)5 alleles.

To identify blood DNA methylation profiles related to liver steatosis, we performed an EWAS on the presence of ultrasonically-identified liver steatosis in the Young Finns Study (YFS) participants (n = 1529, 33–50y.), and on liver enzyme levels and fatty liver index (FLI) across three discovery cohorts: YFS, LURIC (n = 2371, 17–92y.) and KORA FF4 (n = 1872, 39–88y.). We further investigated the discovered associations across the longitudinal subset of YFS (n = 255), encompassing three follow-ups over 32 years, and the three-generational YFS-3G follow-up in 2018–2020. Finally, we examined the associations of the discovered CpGs with nearby genetic variation and whole blood expression of nearby genes. In YFS, the methylation levels of cg06690548 (SLC7A11) were lower in individuals with liver steatosis (Δbeta = − 0.011, FDR = 0.004). Methylation of 9 CpGs associated with GGT and 23 CpGs with FLI in at least two of the discovery cohorts. Methylation at cg06690548 (SLC7A11) and the majority of the CpGs associating with GGT or FLI had the strongest association in the two oldest generations of YFS-3G follow-up (ages 43–59y. and 59–93y.), with minor or non-significant association in the youngest generation (ages 6–36y.). Discovered meQTLs for the CpGs did not modulate the association between the methylation levels and GGT or FLI. The expression of the nearby genes mediated only the association between cg06500161 (ABCG1) and cg20544516 (SREBF1) and FLI. Our findings highlight the association between the methylation levels of cg06690548 (SLC7A11) and liver steatosis, describe the dynamic relationship between whole blood DNA methylation and MASLD, and contribute to a deeper understanding of the pathophysiology of liver diseases.

Background:Decreased hepatic removal of low density lipoproteins (LDL) and increased apolipoprotein B (apoB) production cause hypercholesterolemia, a major causal risk factor of atherosclerotic cardiovascular disease (ASCVD). By a genome-wide siRNA screen, we previously identified subunits of the Coat protein I (COPI) complex to limit LDL uptake into Huh-7 hepatocarcinoma cells. Methods:These findings were validated by targeted in vitro experiments as well as genetic association studies in humans and three mouse models with mutated or disrupted COPI genes. Results:Silencing of COPA, COPB1, COPB2, ARCN1, COPG1, and COPZ1 in Huh-7 cells resulted in decreased uptake of LDL and aberrant glycosylation and altered cell surface abundance of the LDL receptor (LDLR) as well as increased apoB secretion and cellular lipid storage. Single nucleotide polymorphisms of ARCN1 were associated with lower ARCN1 expression and higher levels of LDL-cholesterol (LDL-C). Rare variants of COPA and COPG1 were enriched among patients with LDL-C > 5 mmol/L. Patients and mice carrying other rare immunopathogenic missense variants of COPA and COPG1 did not present with elevated plasma levels of LDL-C, while hepatic knockdown of murine Copg1 increased the concentrations of non-HDL-cholesterol in plasma and triglycerides in the liver. Conclusions:The COPI coatomer regulates LDLR activity and apoB secretion as well as lipid content of liver cells. Loss of function of some variants of COPI genes are associated with higher LDL-C levels.

Background: Interindividual variability in intestinal cholesterol absorption contributes to differences in serum lipid concentrations and cardiovascular risk. Total cholesterol (TC)-standardized campesterol and sitosterol levels are established markers of cholesterol absorption. However, genetic variants in Europeans associated with these markers remain incompletely characterized. Methods: A genome-wide association study (GWAS) was performed in 398 healthy individuals of European ancestry. Samples were genotyped using the Precision Medicine Research Array (PMRA). After quality control, 166,037 common genetic variants with a minor allele frequency (MAF) > 20% were analyzed. Associations between genetic variants and intestinal cholesterol absorption markers (campesterol/TC and sitosterol/TC) were evaluated using additive and recessive genetic models. Results: A total of 16 SNPs were identified. Eight SNPs overlapped with both campesterol/TC and sitosterol/TC, of which 2 reached genome-wide significance. Six overlapping SNPs were associated with higher concentrations of both markers: 3 SNPs in ABCG8 (rs4299376, rs6544713, and rs4245791), 1 SNP in ADAM12 (rs4962526), and 2 SNPs in non-coding regions (rs260769 and rs5011112). Additionally, two SNPs (rs2033254 and rs12708980) in CETP were associated with lower concentrations of these markers. Five of the identified SNPs have not previously been linked to markers of intestinal cholesterol absorption. Conclusions: This GWAS confirmed previously reported associations within ABCG8 and identified candidate loci in CETP and ADAM12 that may be involved in intestinal cholesterol absorption. These findings contribute to our understanding of genetic factors underlying intestinal cholesterol absorption and highlight candidate loci for future replication and functional studies.

BACKGROUND AND AIMS:Decreased removal and increased production of apolipoprotein B (apoB) containing lipoproteins cause hypercholesterolemia, a major causal risk factor of atherosclerotic cardiovascular disease. By a genome-wide siRNA screen, we previously identified subunits of the Coat protein I (COPI) complex to limit low density lipoprotein (LDL) uptake into Huh-7 hepatocarcinoma cells. This study investigated the underlying mechanism and the role of impaired COPI function for hypercholesterolemia. METHODS:Targeted loss of function experiments in vitro as well as genetic association studies in humans and three mouse models with mutated or disrupted COPI genes were performed. RESULTS:Silencing of COPA, COPB1, COPB2, ARCN1, COPG1, and COPZ1 in Huh-7 cells resulted in decreased uptake of LDL and aberrant glycosylation and reduced cell surface abundance of the LDL receptor (LDLR) as well as increased apoB secretion and cellular lipid storage. Single nucleotide polymorphisms of ARCN1 were associated with lower ARCN1 expression and higher levels of LDL-cholesterol. While patients and mice carrying rare immunopathogenic missense variants of the WD40- or appendage domains of COPA and COPG1, respectively, had normal LDL-cholesterol levels, rare variants altering other domains of these proteins were enriched among patients with hypercholesterolemia. The hepatic knockdown of Copg1 increased the concentrations of nonHDL-cholesterol in plasma and triglycerides in the liver of mice. CONCLUSIONS:The COPI coatomer regulates LDLR activity and apoB secretion as well as hepatic lipid content. Deficiency of Copg1 in mice and some but not all rare damaging COPI gene variants in humans are associated with higher LDL-cholesterol levels.

Abstract Background Tobacco smoking remains a major global health burden and is a leading risk factor for cardiovascular disease and cancer. Accumulating evidence suggests that tobacco smoke induces widespread alterations in DNA methylation, which may contribute to smoking-related morbidity and mortality. Methods The Ludwigshafen Risk and Cardiovascular Health (LURIC) study is a monocentric prospective cohort including 3316 patients referred for coronary angiography. Genome-wide DNA methylation was assessed in 2423 participants using the Illumina HumanMethylationEPIC BeadChip. A discovery–replication design was applied (discovery n = 1262; replication n = 1161). Associations between smoking status (never/former vs. current) and CpG-specific methylation levels were evaluated using multivariable linear regression models. Cox proportional hazards models were used to assess associations with all-cause and cardiovascular mortality. Mediation was examined within a counterfactual framework using natural effect models. Results In the discovery sample, 14,403 CpG sites were significantly associated with smoking after false-discovery-rate correction (differentially methylated probes, DMPs). Of these, 3,000 were replicated in the independent sample at an FDR-adjusted p value < 0.05. In random-effect meta-analysis of both samples, 24,930 DMPs remained significant after multiple testing correction, of which 11,907 had not been reported in the largest published smoking EWAS to date. Among former smokers, a subset of DMPs remained differentially methylated more than 10 years after smoking cessation, indicating long-term persistence of smoking-associated epigenetic alterations. A CpG score constructed from mortality-associated DMPs was strongly associated with all-cause mortality. Inclusion of this score in Cox regression models attenuated the association between smoking status and mortality. Mediation analysis demonstrated a statistically significant natural indirect effect of smoking on all-cause mortality via the CpG score. Conclusions Tobacco smoking is associated with widespread, exposure-dependent alterations in DNA methylation, many of which persist for years after cessation. These epigenetic changes are strongly linked to mortality risk and may represent an important biological pathway underlying the association between smoking and adverse health outcomes.

Background and aims:Cardiac rehabilitation (CR) is integral to secondary prevention in coronary artery disease (CAD), incorporating exercise, medical optimization, and dietary interventions. While low-carbohydrate (low-carb) and low-fat diets may improve metabolic health, their comparative impact on cardiovascular risk in CR remains unclear. This study assessed the effects of low-carb and low-fat diets on cardiovascular risk, body composition, and major adverse cardiovascular and cerebrovascular events (MACCE) in CAD patients undergoing inpatient CR. Methods:In this quasi-experimental study, 313 CAD patients (56 ± 7 years, 20% women) participated in CR, adopting a low-carb (n = 58), low-fat (n = 136), or regular diet (n = 119, control). Dietary assignment was non-randomized and based on assisted patient self-selection. A biomarker-based score to estimate the 10-year cardiovascular mortality risk, bioelectrical impedance analysis, and laboratory parameters (HbA1c, lipids, inflammation markers) were assessed at baseline, discharge, and 6-month follow-up. Kaplan-Meier analysis was used to compare MACCE recorded for a mean of 470 ± 293 days. Results:During 3-4 weeks of CR, the 10-year cardiovascular mortality risk decreased by a mean of 3.7 ± 9.6%, with no difference between dietary groups (p = 0.8651). HbA1c improved in the low-carb group during CR compared to the low-fat and regular diet (-4.0 ± 6.6%), but the effect was not significant after adjustments for baseline HbA1c, diabetes prevalence, and medication (p = 0.168). Reductions in BMI, body fat, and visceral fat were recorded in the low-carb and low-fat group, compared to the control group (p ≤ 0.0001). Total cholesterol, LDL, and triglyceride levels also decreased in all groups during CR without significant differences (p ≥ 0.3957). MACCE incidence did not differ between the groups (p = 0.2). Conclusion:No additional immediate benefit in risk reduction during CR for low-carb or low-fat dietary interventions was detected. However, the low-fat and low-carb diet resulted in significantly greater reductions in BMI, body fat and visceral fat, with a tendency towards more stable effects over 6 months in the low-fat group. While glycemic control was improved in the low-carb group during inpatient CR, long-term adherence appeared challenging, particularly for diabetic patients as HbA1c levels re-increased during 6 months follow-up. Since no difference in MACCE was seen, the dietary interventions may be considered equally safe for CAD patients.

The MoKaRi study aims to evaluate the impact of two nutritional concepts on cardiometabolic risk factors. For our 20-week intervention study, 65 participants with moderate elevated low-density lipoprotein cholesterol (LDL-C; ≥ 3 mmol/l) and without lipid-lowering therapy were recruited. The intervention to improve nutritional behavior was based on individualized menu plans which were characterized by defined energy and nutrient intake. To improve compliance, individual nutritional counselling sessions were held every two weeks. In addition to motivation, cooking skills were strengthened and nutritional knowledge was imparted. Follow-up visits were carried out after 10 and 20 weeks. The MoKaRi diet lowered the concentrations of total cholesterol (menu plan group (MP): -15

Despite extensive research on DNA methylation (DNAm) signatures associated with alcohol use disorder (AUD), findings are often inconsistent and not replicated. We conducted a large-scale meta-analysis of epigenome-wide association studies (EWAS) to identify reliable, reproducible epigenetic markers of AUD. Seven cohorts, comprising 3,775 individuals (1,325 with AUD), contributed to this meta-analysis within the framework of the Psychiatric Genomics Consortium Substance Use Disorders Epigenetics Working Group. Downstream analyses included the identification of differentially methylated regions, overrepresentation analyses, and the construction of a methylation risk score (MRS). We identified 118 significant CpG sites associated with AUD, with the strongest association found at cg24889777 ( p =5.12×10 -17 ) in the long non-coding RNA LOC100505942. CpG sites were enriched for pathways related to GTPase signaling and transmembrane transporter activity, as well as EWAS signals of alcohol consumption. The MRS explained 10.44% of variance in heavy drinking in an independent cohort (N=2,534, AUC=0.657). This large-scale meta-analysis offers key insights into the epigenetic mechanisms of AUD and lays the groundwork for future research on methylation risk scores for the diagnosis, prognosis, and treatment in AUD.

Introduction: The processes of atherosclerosis, inflammation, and carbamylation are closely linked in cardiovascular (CV) disease, but the potential of carbamylation burden as a CV mortality predictor is unclear, especially in patients with no or mild chronic kidney disease (CKD). This study aimed to investigate whether elevated carbamylated albumin (C-Alb), as a surrogate marker for carbamylation burden, is associated with mortality and arterial stiffness/atherosclerotic burden in patients with no or mild CKD, using pulse pressure (PP) as a marker for arterial stiffness. Methods: We measured C-Alb in 3,193 participants of the Ludwigshafen Risk and Cardiovascular Health study who had been referred for coronary angiography and followed up for 10 years. Results: The mean age was 62.7 years, and 30.4% were female. Mean blood pressure was 141/81 mm Hg, and mean C-Alb was 5.54 mmol/mol. Increase in C-Alb levels was associated with older age; female sex; increased PP, high-sensitivity C-reactive protein, and interleukin-6 levels; and increased incidence of coronary artery disease (CAD), peripheral artery disease (PAD), and carotid stenosis. In contrast, BMI, diastolic blood pressure (DBP), albumin, and the proportion of active smokers decreased with increasing C-Alb levels. In particular, C-Alb showed a highly significant correlation with CAD severity: Friesinger (Pearson correlation coefficient [r] = 0.082, p < 0.001) and Gensini score (r = 0.066, p < 0.001). The area under the curve (AUC) for all-cause mortality prediction by the European Society of Cardiology Heart Score (ESC-HS) significantly improved from 0.719 to 0.735, and the AUC for CV mortality prediction based on C-Alb increased from 0.726 to 0.750 in patients without previously known CV disease. C-Alb correlated directly and significantly with PP (r = 0.062, p < 0.001), which was consistently the strongest predictor of mortality across all C-Alb tertiles. The hazard ratios (HRs) for all-cause mortality per 10 mm Hg increase (or 1,000 mm Hg/min increase for double product [DP]) in the 1st tertile of C-Alb were 1.18, 1.13, 1.11, and 1.11 for PP, mean arterial pressure (MAP), systolic blood pressure (SBP), and DP, respectively, but the HR for DBP did not reach significance. In the 3rd tertile of C-Alb, the HRs were 1.13, 1.05, and 1.09, for PP, SBP, and DP, respectively, but the HR for MAP did not reach significance. Conclusion: C-Alb may be a valuable biomarker for assessing CV risk and improving mortality prediction even in patients with no or mild CKD. The findings support the notion of a crosslink between carbamylation, inflammation, atherosclerosis, and mortality. While these results are promising, further research is needed to fully elucidate the role of C-Alb in CV disease progression and risk stratification.

BACKGROUND:Urea is elevated in chronic kidney disease (CKD) and end-stage renal disease (ESRD), and promotes the carbamylation of proteins, including human albumin, on multiple lysine side chains. Higher proportions of carbamylated albumin (C-Alb) have been associated with increased mortality risk in patients with ESRD. Whether C-Alb predicts mortality in patients with no or mild impairment of kidney function is unknown. METHODS:We measured C-Alb in 3197 participants of the Ludwigshafen Risk and Cardiovascular Health (LURIC) study who had been referred to coronary angiography and followed-up for 10 years. Association of baseline C-Alb with all-cause and cause-specific mortality was investigated using Cox proportional hazards regression. RESULTS:Higher quartiles of C-Alb were associated with a significantly increased risk of death from any cause, with hazard ratios (HRs, 95%CI) of 1.53 (1.26-1.85) and 2.52 (2.11-3.01) in the third and fourth quartiles, respectively. After adjustment for cardiovascular (CV) risk factors, including estimate glomerular filtration rate (eGFR), the association with mortality was attenuated with a HR of 1.25 (1.02-1.53) for the fourth quartile as compared to the first quartile. We observed the strongest association with death due to congestive heart failure (HF) with a HR of 7.19 (4.57-11.3) and 3.99 (2.40-6.63) per 1-unit increase of log-transformed C-Alb in unadjusted and multivariate adjusted analyses, respectively. CONCLUSIONS:We observed a strong association of C-Alb with CV risk in patients with no or mild CKD. This association was independent of traditional CV risk factors including eGFR and particularly strong regarding death due to congestive HF.

OBJECTIVE:Accurate prediction of type 2 diabetes mellitus (T2DM) onset is critical to enable timely interventions and preventive strategies. Although machine learning (ML) approaches have shown promise in risk prediction, their complexity often limits clinical implementation. There is a need for interpretable, user-friendly models that retain predictive strength. METHODS:We studied 904 cardiovascular risk patients without T2DM at baseline, assessing 71 anthropometric, clinical, and laboratory variables. Over a four-year follow-up, 10 % developed T2DM. We applied AutoScore, an interpretable ML framework that generates parsimonious, point-based risk scores, and compared its performance with an optimized Support Vector Machine (SVM) with a linear kernel. The SVM was refined using feature selection, Tomek link removal, and up-sampling to address class imbalance. RESULTS:Both approaches consistently identified fasting glucose, OGTT glucose, and the Matsuda index (reflecting glucose-insulin dynamics) as key predictors. The optimized SVM model achieved a higher balanced accuracy (75 % vs. 67 %), specificity (80 % vs. 77 %), and AUC (0.72 vs. 0.69) compared to AutoScore. However, AutoScore, other than the SVM model, relied exclusively on a small set of routinely available accessible parameters and thereby offered superior interpretability and ease of integration into clinical workflows. External validation in an independent cohort further confirmed the robustness of the AutoScore model. CONCLUSION:Although black-box models such as SVM deliver slightly higher predictive accuracy, interpretable frameworks like AutoScore provide clinically actionable risk stratification based on standard data. Their transparency and simplicity make them particularly valuable for real-world decision support.