Background Myocardial infarction (MI) remains the leading cause of death and disability among cardiovascular diseases worldwide. Studies show that elevated low-density lipid protein cholesterol (LDL-C) levels confer the highest absolute risk of MI, and Apolipoprotein E (ApoE) is implicated in regulating levels of triglycerides (TGs), cholesterol, and LDL-C. Our study aimed to evaluate the association between APOE polymorphism and MI, and to provide evidence for the etiology of MI. Methods Case–control studies on the association between APOE polymorphisms and the risk of myocardial infarction were included by searching PubMed, Web of Science, and CNKI, and this meta-analysis was written in accordance with PRISMA guideline statement. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using either random-effects or fixed-effects models by R software. Results A total of 33 eligible articles involving 13,706 cases and 14,817 controls were finally selected. The pooled analysis based on the total eligible articles showed that the risk of MI was associated with ApoE epsilon 2 and epsilon 4 alleles. The results showed that patients with MI had a low frequency of the ε2 allele (OR 0.74, 95% CI 0.64–0.86) and a high frequency of the ε4 allele (OR 1.24, 95% CI 1.09–1.42). Conclusions APOE ε2-involved genotypes may be protective factors for MI; in contrast, ε4-involved genotypes (ε4/ε3 vs. ε3/ε3, and ε4/ε4 vs. ε3/ε3) may be risk factors for MI.

Background Multimorbidity is defined as two or more chronic health conditions existing in an individual simultaneously. Multimorbidity has been associated with poor conditions, such as higher health care costs and the poor quality of life. Thus, identifying the risk factors of the multimorbidity is required for multimorbidity prevention. Methods This study was based on the Comprehensive Demonstration Research Project of Major Chronic Noncommunicable Disease Prevention and Control Technology in Northeast China initiated by China Medical University. The investigation was a cross-sectional study under a multistage stratified cluster random sampling design. Associations between multimorbidity and sociodemographic and behavioral factors in adult residents were investigated using univariate analysis and multivariate logistic regression analysis. Results A total of 6706 participants were enrolled in this investigation, and the prevalence of multimorbidity was 21.2% among the adult residents of northeastern China. There existed differences of association between age and multimorbidity risks (65–69 years old: OR = 3.53, 95%CI: 2.04–6.12; 70–74 years old: OR = 5.26, 95%CI: 3.02–9.17). Participants who are overweight had significantly high multimorbidity risk (OR = 2.76, 95%CI: 1.50–5.24). Family history of hypertension and family history of diabetes were significantly associated with high multimorbidity risk (family history of hypertension: OR = 2.34, 95%CI: 1.96–2.79; family history of diabetes: OR = 1.77, 95%CI: 1.38–2.26). Compared with the frequency of fatigue (< 1 time/week or 1–2 times/week), that (≥3 times/week) was associated with high multimorbidity risk (OR = 1.39, 95%CI: 1.07–1.81). For fresh fruit consumption, compared with eating fruits regularly, eating rarely had a higher risk of multimorbidity (OR = 2.33, 95%CI: 1.90–2.85). Conclusions Sociodemographic indices (age, BMI, family history of hypertension, and family history of diabetes) and behavioral indices (fatigue status and fresh fruit consumption) increase the risks of multimorbidity. This study provides a necessary route to prevent and control multimorbidity in northeast China.

Skin cutaneous melanoma (SKCM) is the most lethal form of skin cancers owing to high invasiveness and high metastatic potential. Tumor microenvironment (TME) provides powerful evidences for discerning SKCM, raising the prospect to identify biomarkers of SKCM. Based on the transcriptome profiles of patients with SKCM and the corresponding clinical information from The Cancer Genome Atlas (TCGA), we used ESTIMATE algorithm to calculate ImmuneScore and StromalScore and identified the TME-Related differentially expressed genes (DEGs), than the intersected TME-Related DEGs were used for subsequent functional enrichment analysis. Protein–protein interaction (PPI) analysis was used to identify the functionality-related DEGs and univariate Cox regression analysis was used to identify the survival-related DEGs. Furthermore, SKCM-related DEGs were identified based on two Gene Expression Omnibus (GEO) datasets. Finally, we intersected functionality-related DEGs, survival-related DEGs, and SKCM-related DEGs, ascertaining that six DEGs (CCL4, CXCL10, CCL5, GZMB, C1QA, and C1QB) function as core TME-related genes (CTRGs). Significant differences of GZMB, C1QA, and C1QB expressions were found in gender and clinicopathologic staging of SKCM. High levels of GZMB, C1QA, and C1QB expressions were associated with favorable prognosis. Gene set enrichment analysis (GSEA) showed that cell–cell interaction, cell behavior, and intracellular signaling transduction may be mainly involved in both C1QA, C1QB and GZMB expressions and metabolism of phospholipid and amino acid, transcription, and translation may be implicated in low GZMB expressions. C1QA, C1QB, and GZMB are novel SKCM-relating CTRGs, providing promising immune-related prognostic biomarkers for SKCM.

Background Overweight and obesity lead to a range of noncommunicable diseases (NCDs), such as type 2 diabetes, cardiovascular disease, and stroke. Physical activity (PA) is an important lifestyle behavior for controlling body weight. Dietary inflammatory index (DII), which is associated with systemic inflammatory markers, is used to evaluate the potential of dietary inflammation. This is the first study to investigate the independent and joint associations of PA and DII with the risk of overweight/obesity among US adults. Methods Participants and data were obtained from the National Health and Nutrition Examination Survey (NHANES) from 2007–2018, which is designed to examine the health and nutritional status of the non-institutionalized US population by a complex, multi-stage, probability sampling design. Results A total of 10723 US adults were selected. Physically active participants had lower overweight/obesity risk (total-time PA: OR = 0.756, 95% CI: 0.669–0.855; leisure-time PA: OR = 0.723, 95% CI: 0.643–0.813; and walk/bicycle-time PA: OR = 0.748, 95% CI: 0.639–0.875); however, those with work-time PA showed no significant association between PA and overweight/obesity. Compared with participants in the lowest DII group (Q1), those in the other three groups had high risks of overweight/obesity (Q2: OR = 1.218, 95% CI: 1.054–1.409; Q3: OR = 1.452, 95% CI: 1.245–1.693; Q4: OR = 1.763, 95% CI: 1.495–2.079). In joint analyses, PA was not eligible for reducing risks of weight/obesity if far more pro-inflammatory diet (Q4 of DII = 2.949–5.502) was taken in (total-time PA: OR = 1.725, 95% CI: 1.420–2.097; leisure-time PA: OR = 1.627, 95% CI: 1.258–2.105; walk/bicycle-time PA: OR = 1.583, 95% CI: 1.074–2.332; and work-time PA: OR = 1.919, 95% CI: 1.493–2.467). Conclusions More leisure-time PA and walk/bicycle-time PA are associated with lower risk of overweight/obesity, and higher DII is associated with higher risk of overweight/obesity. In addition, higher DII impacts overweight/obesity substantially: once the DII score reached Q4, there is still risks of overweight/obesity even if PA is performed. Supplementary information The online version contains supplementary material available at https://doi.org/10.1265/ehpm.23-00016 .

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