Association of cardiorenal biomarkers with mortality in metabolic syndrome patients: A prospective cohort study from NHANES

Objectives

Approximately 20%-25% of the global adult population is affected by metabolic syndrome (MetS), highlighting its status as a major public health concern. This study aims to investigate the predictive value of cardiorenal biomarkers on mortality among patients with MetS, thus optimizing treatment strategies.

Methods

Utilizing data from the National Health and Nutrition Examination Survey (NHANES) cycles between 1999 and 2004, we conducted a prospective cohort study involving 2369 participants diagnosed with MetS. We evaluated the association of cardiac and renal biomarkers with all-cause and cardiovascular disease (CVD) mortality, employing weighted Cox proportional hazards models. Furthermore, machine learning models were used to predict mortality outcomes based on these biomarkers.

Results

Among 2369 participants in the study cohort, over a median follow-up period of 17.1 years, 774 (32.67%) participants died, including 260 (10.98%) from CVD. The highest quartiles of cardiac biomarkers (N-terminal pro-B-type natriuretic peptide [NT-proBNP]) and renal biomarkers (beta-2 microglobulin, [β2M]) were significantly associated with increased risks of all-cause mortality (hazard ratios [HRs] ranging from 1.94 to 2.06) and CVD mortality (HRs up to 2.86), after adjusting for confounders. Additionally, a U-shaped association was observed between high-sensitivity cardiac troponin T (Hs-cTnT), creatinine (Cr), and all-cause mortality in patients with MetS. Machine learning analyses identified Hs-cTnT, NT-proBNP, and β2M as important predictors of mortality, with the CatBoost model showing superior performance (area under the curve [AUC] = 0.904).

Conclusion

Cardiac and renal biomarkers are significant predictors of mortality in MetS patients, with Hs-cTnT, NT-proBNP, and β2M emerging as crucial indicators. Further research is needed to explore intervention strategies targeting these biomarkers to improve clinical outcomes.

Investigating the shared genetic architecture between primary sclerosing cholangitis and inflammatory bowel diseases: a Mendelian randomization study

BACKGROUND

Several studies have found that primary sclerosing cholangitis (PSC) and inflammatory bowel disease (IBD) are closely associated. However, the direction and causality of their interactions remain unclear. Thus, this study employs Mendelian Randomization to explore whether there are causal associations of genetically predicted PSC with IBD.

METHODS

Genetic variants associated with the genome-wide association study (GWAS) of PSC were used as instrumental variables. The statistics for IBD, including ulcerative colitis (UC), and Crohn's disease (CD) were derived from GWAS. Then, five methods were used to estimate the effects of genetically predicted PSC on IBD, including MR Egger, Weighted median (WM), Inverse variance weighted (IVW), Simple mode, and Weighted mode. Last, we also evaluated the pleiotropic effects, heterogeneity, and a leave-one-out sensitivity analysis that drives causal associations to confirm the validity of the analysis.

RESULTS

Genetically predicted PSC was significantly associated with an increased risk of UC, according to the study (odds ratio [OR] IVW= 1.0014, P<0.05). However, none of the MR methods found significant causal evidence of genetically predicted PSC in CD (All P>0.05). The sensitivity analysis results showed that the causal effect estimations of genetically predicted PSC on IBD were robust, and there was no horizontal pleiotropy or statistical heterogeneity.

CONCLUSIONS

Our study corroborated a causal association between genetically predicted PSC and UC but did not between genetically predicted PSC and CD. Then, we identification of shared SNPs for PSC and UC, including rs3184504, rs9858213, rs725613, rs10909839, and rs4147359. More animal experiments and clinical observational studies are required to further clarify the underlying mechanisms of PSC and IBD.

A Mendelian randomization study on causal effects of leisure sedentary behaviour on the risk of rheumatoid arthritis

BACKGROUND

The causal inference between leisure sedentary behaviour (LSB) and rheumatoid arthritis (RA) is still controversial because of potential residual confounding and reverse causality.

METHODS

The present study used publicly available large-scale genome-wide association studies (GWAS) of LSB (television watching, computer use, and driving) and RA to perform a two-sample Mendelian randomization (MR) study to evaluate the causal effect of LSB on the risk of RA. We detected significant causal associations using the multiplicative random effects-inverse variance weighted (MRE-IVW) method, the maximum likelihood, robust adjusted profile scores, the weighted median, MR-Egger regression, and several complementary sensitivity analyses. Risk factor analysis was also conducted to further investigate potential mediators linking causal inference.

RESULTS

Increased genetic liability to leisure television watching was significantly associated with a higher risk of RA (MRE-IVW method; OR = 2.46, 95% CI 1.77-3.41; p = 8.35 × 10^-8 ). MR estimates indicated that prolonged leisure computer use was causally associated with a lower risk of RA (MRE-IVW method; OR = 0.23, 95% CI 0.12-0.46; p = 2.19 × 10^-5 ). However, we found no evidence for a causal effect of leisure driving on the risk of RA (MRE-IVW method; OR = 0.59, 95% CI 0.10-3.41; p = 0.557). No pleiotropy was detected by the sensitivity analysis.

CONCLUSIONS

This study supports a causal association between prolonged leisure television watching and an increased risk of RA. Additionally, prolonged computer use might be a protective factor for RA.

Causal risk and protective factors in rheumatoid arthritis: A genetic update

The characterization of risk and protective factors in complex diseases such as rheumatoid arthritis (RA) has evolved from epidemiological studies, which test association, to the use of Mendelian randomization approaches, which test direct relationships. Indeed, direct associations with the mucosal origin of RA are retrieved with periodontal disease (Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans predominantly), interstitial lung involvement, tobacco smoking and air pollutants. Next, factors directly associated with an acquired immune response include genetic factors (HLA DRB1, PTPN22), capacity to produce anti-modified protein antibodies (AMPA), and relatives with a history of autoimmune diseases. Finally, factors can be also classified according to their direct capacity to interfere with the IL-6/CRP/sIL-IL6R proinflammatory pathway as risk factor (body fat, cardiometabolic factors, type 2 diabetes, depressive syndrome) or either as protective factors by controlling of sIL-6R levels (higher education level, and intelligence). Although some co-founders have been characterized (e.g. vitamin D, physical activity, cancer) the direct association with sex-discrepancy, pregnancy, and infections among other factors remains to be better explored.

Statin therapy is associated with epigenetic modifications in individuals with Type 2 diabetes

Aim: Statins lower cholesterol and reduce the risk of cardiovascular disease. However, the exact mechanisms of statins remain unknown. We investigated whether statin therapy associates with epigenetics in Type 2 diabetes (T2D) patients. Materials & methods: DNA methylation was analyzed in blood from newly diagnosed T2D patients in All New Diabetics in Scania (ANDIS) and a replication cohort All New Diabetics in Uppsala County (ANDiU). Results: Seventy-nine sites were differentially methylated between cases on statins and controls (false discovery rate <5%) in ANDIS. These include previously statin-associated methylation sites annotated to DHCR24 (cg17901584), ABCG1 (cg27243685) and SC4MOL (cg05119988). Differential methylation of two sites related to cholesterol biosynthesis and immune response, cg17901584 (DHCR24) and cg23011663 (ARIH2), were replicated in ANDiU. Conclusion: Statin therapy associates with epigenetic modifications in T2D patients.

Etiologies of Rheumatoid Arthritis: Update on Mucosal, Genetic, and Cellular Pathogenesis

Purpose of Review

Over the last few years, the scientific community has made significant progress in understanding the etiology of rheumatoid arthritis (RA). In this review, we summarize those key findings and trends.

Recent Findings

New data strongly implicates respiratory exposures, obesity, diet and microbiome, genetics, and their interactions in the etiology of RA. Furthermore, anti-posttranslationally modified protein antibodies (AMPAs) and abnormal glycosylation may be additional biomarkers for RA. Finally, functional genomics techniques implicate loss of certain macrophage populations and proliferation of synovial fibroblasts in RA.

Summary

These findings support the notion that RA originates at mucosal sites, augmented by genetic predisposition, and mediated by certain cell types including macrophages and fibroblasts. Weight loss, physical activity, and diet are additional modifiable factors beyond smoking cessation that can reduce risk of RA. Future epidemiologic and translational studies leveraging multi-omics approaches will help map the precise sequence of events in RA pathogenesis.

Hematopoietic stem-cell senescence and myocardial repair - Coronary artery disease genotype/phenotype analysis of post-MI myocardial regeneration response induced by CABG/CD133+ bone marrow hematopoietic stem cell treatment in RCT PERFECT Phase 3

Background

Bone marrow stem cell clonal dysfunction by somatic mutation is suspected to affect post-infarction myocardial regeneration after coronary bypass surgery (CABG).

Methods

Transcriptome and variant expression analysis was studied in the phase 3 PERFECT trial post myocardial infarction CABG and CD133⁺ bone marrow derived hematopoetic stem cells showing difference in left ventricular ejection fraction (∆LVEF) myocardial regeneration Responders (n=14; ∆LVEF +16% day 180/0) and Non-responders (n=9; ∆LVEF -1.1% day 180/0). Subsequently, the findings have been validated in an independent patient cohort (n=14) as well as in two preclinical mouse models investigating SH2B3/LNK antisense or knockout deficient conditions.

Findings

1. Clinical: R differed from NR in a total of 161 genes in differential expression (n=23, q<0•05) and 872 genes in coexpression analysis (n=23, q<0•05). Machine Learning clustering analysis revealed distinct RvsNR preoperative gene-expression signatures in peripheral blood acorrelated to SH2B3 (p<0.05). Mutation analysis revealed increased specific variants in RvsNR. (R: 48 genes; NR: 224 genes). 2. Preclinical:SH2B3/LNK-silenced hematopoietic stem cell (HSC) clones displayed significant overgrowth of myeloid and immune cells in bone marrow, peripheral blood, and tissue at day 160 after competitive bone-marrow transplantation into mice. SH2B3/LNK^−/− mice demonstrated enhanced cardiac repair through augmenting the kinetics of bone marrow-derived endothelial progenitor cells, increased capillary density in ischemic myocardium, and reduced left ventricular fibrosis with preserved cardiac function. 3. Validation: Evaluation analysis in 14 additional patients revealed 85% RvsNR (12/14 patients) prediction accuracy for the identified biomarker signature.

Interpretation

Myocardial repair is affected by HSC gene response and somatic mutation. Machine Learning can be utilized to identify and predict pathological HSC response.

Funding

German Ministry of Research and Education (BMBF): Reference and Translation Center for Cardiac Stem Cell Therapy - FKZ0312138A and FKZ031L0106C, German Ministry of Research and Education (BMBF): Collaborative research center - DFG:SFB738 and Center of Excellence - DFG:EC-REBIRTH), European Social Fonds: ESF/IV-WM-B34-0011/08, ESF/IV-WM-B34-0030/10, and Miltenyi Biotec GmbH, Bergisch-Gladbach, Germany. Japanese Ministry of Health : Health and Labour Sciences Research Grant (H14-trans-001, H17-trans-002)

Trial registration

ClinicalTrials.gov NCT00950274