Objective Energy metabolism plays a crucial role in the improvement of heart dysfunction as well as the development of heart failure (HF). The current study is designed to identify energy metabolism-related diagnostic biomarkers for predicting the risk of HF due to myocardial infarction. Methods Transcriptome sequencing data of HF patients and non-heart failure (NF) people (GSE66360 and GSE59867) were obtained from gene expression omnibus (GEO) database. Energy metabolism-related differentially expressed genes (DEGs) were screened between HF and NF samples. The subtyping consistency analysis was performed to enable the samples to be grouped. The immune infiltration level among subtypes was assessed by single sample gene set enrichment analysis (ssGSEA). Random forest algorithm (RF) and support vector machine (SVM) were applied to identify diagnostic biomarkers, and the receiver operating characteristic curves (ROC) was plotted to validate the accuracy. Predictive nomogram was constructed and validated based on the result of the RF. Drug screening and gene-miRNA network were analyzed to predict the energy metabolism-related drugs and potential molecular mechanism. Results A total of 22 energy metabolism-related DEGs were identified between HF and NF patients. The clustering analysis showed that HF patients could be classified into two subtypes based on the energy metabolism-related genes, and functional analyses demonstrated that the identified DEGs among two clusters were mainly involved in immune response regulating signaling pathway and lipid and atherosclerosis. ssGSEA analysis revealed that there were significant differences in the infiltration levels of immune cells between two subtypes of HF patients. Random-forest and support vector machine algorithm eventually identified ten diagnostic markers (MEF2D, RXRA, PPARA, FOXO1, PPARD, PPP3CB, MAPK14, CREB1, MEF2A, PRMT1) for risk prediction of HF patients, and the proposed nomogram resulted in good predictive performance (GSE66360, AUC = 0.91; GSE59867, AUC = 0.84) and the clinical usefulness in HF patients. More importantly, 10 drugs and 15 miRNA were predicted as drug target and hub miRNA that associated with energy metabolism-related genes, providing further information on clinical HF treatment. Conclusion This study identified ten energy metabolism-related diagnostic markers using random forest algorithm, which may help optimize risk stratification and clinical treatment in HF patients.

https://www.frontiersin.org/articles/10.3389/fcvm.2022.993142/pdf

Identification of energy metabolism-related biomarkers for risk prediction of heart failure patients using random forest algorithm

Background: The role of aldehyde dehydrogenase 2 (ALDH2) in cardiovascular diseases has been gradually studied. However, it is unclear whether ALDH2 polymorphism is associated with the risk of early onset (onset age ≤ 55 years old in men and ≤ 65 years old in women) coronary artery stenosis (CAS). The association between ALDH2 single nucleotide polymorphism (SNP) rs671 and risk in patients with early onset CAS was investigated in this study. Methods: The study included 213 early onset CAS patients and 352 individuals without CAS were set as controls. The ALDH2 rs671 polymorphism was genotyped by polymerase chain reaction (PCR) - microarray. Differences in ALDH2 rs671 genotypes and alleles between patients and controls were compared. Multiple logistic regression analysis was performed after adjusting for gender, body mass index (BMI), smoking history, drinking history, and diabetes mellitus to assess the relationship between ALDH2 rs671 genotypes and early onset CAS risk. Results: The frequency of the ALDH2 rs671 G/G genotype was lower in the early onset CAS patients (43.7% vs 55.3%, p =0.007) than that in the controls. The frequency of the ALDH2 rs671 A allele was higher (32.9% vs 25.0%) than that in the controls ( p =0.005). After adjusting for other confounding factors, multivariate logistic regression showed that ALDH2 rs671 A/A genotype (A/A vs G/G: odds ratio (OR) 2.508, 95% confidence interval (CI): 1.130– 5.569, p =0.024), overweight (BMI≥ 24.0 vs 18.5– 23.9: OR 5.047, 95% CI: 3.275– 7.777, p < 0.001), history of smoking (yes vs no: OR 2.813, 95% CI: 1.595– 4.961, p < 0.001), and diabetes mellitus (yes vs no: OR 2.191, 95% CI: 1.397– 3.437, p =0.001) were the independent risk factors of early onset CAS. Conclusion: In men ≤ 55 years old and women ≤ 65 years old, individuals with ALDH2 rs671 A/A genotype, overweight (BMI ≥ 24.0 kg/m 2 ), smoking history, and diabetes mellitus increased risk of developing CAS. Keywords: aldehyde dehydrogenase 2, gene polymorphism, coronary artery stenosis, early onset 

Aldehyde dehydrogenase 2 rs671 a/A Genotype is Associated with an Increased Risk of Early Onset Coronary Artery Stenosis

Cytoplasmic lipid droplets (LDs), which are remarkably dynamic, neutral lipid storage organelles, play fundamental roles in lipid metabolism and energy homeostasis. Both the dynamic remodeling of LDs and LD-mitochondrion interactions in adipocytes are effective mechanisms to ameliorate obesity and related comorbidities. Zeaxanthin (ZEA) is a natural carotenoid and has beneficial effects on anti-obesity. However, the underlying mechanisms of ZEA on LD modulation are still unclear. In the present study, ZEA efficiently inhibited LD accumulation and attenuated adipocyte proliferation by arresting the cell cycle. ZEA drove transcriptional alterations to reprogram a lipid oxidative metabolism phenotype in mature 3T3-L1 adipocytes. ZEA significantly decreased the TAG and FA content and modulated the dynamic alterations of LDs by upregulating the expression of lipases and the LD-mitochondrion contact site protein, perilipin 5 (PLIN5), and downregulating the LD fusion protein, fat-specific protein 27 (FSP27). Mechanistically, ZEA stimulated LD remodeling and ameliorated mitochondrial defects caused by large and unilocular LD accumulation by activating β3-adrenergic receptor (β3-AR) signaling. Furthermore, the knockdown of PLIN5 impaired the LD-mitochondrion interactions, thereby disrupting the role of ZEA in promoting mitochondrial fatty acid oxidation and respiratory chain operation. Collectively, the present study demonstrates that ZEA induces LD structural and metabolic remodeling by activating β3-AR signaling and enhances PLIN5-mediated LD-mitochondrion interactions in hypertrophic white adipocytes, thereby enhancing oxidative capacity, and has the potential as a nutritional intervention for the prevention and treatment of obesity and associated metabolic syndrome.

Zeaxanthin remodels cytoplasmic lipid droplets via β3-adrenergic receptor signaling and enhances perilipin 5-mediated lipid droplet-mitochondrion interactions in adipocytes.

Maternal obesity (MO) causes maternal and fetal oxidative stress (OS) and metabolic dysfunction. We investigated whether supplementing obese mothers with resveratrol improves maternal metabolic alterations and reduces OS in the placenta and maternal and fetal liver. From weaning through pregnancy female Wistar rats ate chow (C) or a high-fat diet (MO). One month before mating until 19 days’ gestation (dG), half the rats received 20 mg resveratrol/kg/d orally (Cres and MOres). At 19dG, maternal body weight, retroperitoneal fat adipocyte size, metabolic parameters, and OS biomarkers in the placenta and liver were determined. MO mothers showed higher body weight, triglycerides and leptin serum concentrations, insulin resistance (IR), decreased small and increased large adipocytes, liver fat accumulation, and hepatic upregulation of genes related to IR and inflammatory processes. Placenta, maternal and fetal liver OS biomarkers were augmented in MO. MOres mothers showed more small and fewer large adipocytes, lower triglycerides serum concentrations, IR and liver fat accumulation, downregulation of genes related to IR and inflammatory processes, and lowered OS in mothers, placentas, and female fetal liver. Maternal resveratrol supplementation in obese rats improves maternal metabolism and reduces placental and liver OS of mothers and fetuses in a sex-dependent manner.

/pdf/resveratrol-supplementation-in-obese-pregnant-rats-improves-15uklyx2.pdf

Resveratrol Supplementation in Obese Pregnant Rats Improves Maternal Metabolism and Prevents Increased Placental Oxidative Stress

Objective Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) are collectively known as Lewy body dementia (LBD). Considering the heterogeneous nature of LBD and the different constellations of symptoms with which patients can present, the exact molecular mechanism underlying the differences between these two isoforms is still unknown. Therefore, this study aimed to explore the biomarkers and potential mechanisms that distinguish between PDD and DLB. Methods The mRNA expression profile dataset of GSE150696 was acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between 12 DLB and 12 PDD were identified from Brodmann area 9 of human postmortem brains using GEO2R. A series of bioinformatics methods were applied to identify the potential signaling pathways involved, and a protein–protein interaction (PPI) network was constructed. Weighted gene co-expression network analysis (WGCNA) was used to further investigate the relationship between gene co-expression and different LBD subtypes. Hub genes that are strongly associated with PDD and DLB were obtained from the intersection of DEGs and selected modules by WGCNA. Results A total of 1,864 DEGs between PDD and DLB were filtered by the online analysis tool GEO2R. We found that the most significant GO- and KEGG-enriched terms are involved in the establishment of the vesicle localization and pathways of neurodegeneration-multiple diseases. Glycerolipid metabolism and viral myocarditis were enriched in the PDD group. A B-cell receptor signaling pathway and one carbon pool by folate correlated with DLB in the results obtained from the GSEA. We found several clusters of co-expressed genes which we designated by colors in our WGCNA analysis. Furthermore, we identified seven upregulated genes, namely, SNAP25, GRIN2A, GABRG2, GABRA1, GRIA1, SLC17A6, and SYN1, which are significantly correlated with PDD. Conclusion The seven hub genes and the signaling pathways we identified may be involved in the heterogeneous pathogenesis of PDD and DLB.

/pdf/identification-of-key-genes-and-signaling-pathways-1veoxw4v.pdf

Identification of key genes and signaling pathways associated with dementia with Lewy bodies and Parkinson's disease dementia using bioinformatics

ABSTRACT Obesity is emerging as an epidemiological issue, being associated with the onset and progress of various metabolism-related disorders. Obesity is characterized by the white adipose expansion, which encounters white adipocyte hypertrophy and hyperplasia. White adipocyte hyperplasia is defined as adipogenesis with the increase in the number of the white adipocytes from the preadipocytes. Adipogenesis contributes to distributing excess triglycerides among the smaller newly formed adipocytes, reducing the number of hypertrophic adipocytes and secreting anti-inflammatory factor. Therefore, adipogenesis is emerging as a new therapeutic target for the treatment of obesity. In the present study, for a better understanding of the contribution of the alteration of the omental differentiated white adipocytes to the systemic metabolic disorders, we downloaded the mRNA expression profiles from GEO database GSE1657, 328 differentially expressed genes (DEGs) were screened between the undifferentiated preadipocytes (UNDIF) and omental differentiated white adipocytes (DIF). The contributions of the upregulated and downregulated DEGs to the system were performed via the Gene Ontology (GO) analysis, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Protein–Protein Interaction (PPI) network, respectively. The potential contribution of the whole altered genes in the differentiated white adipocytes was explored with the performance of Gene Set Enrichment Analysis (GSEA), especially on the GO analysis, KEGG analysis, hallmark analysis, oncogenic analysis and related miRNA analysis. The output of the current study will shed light on the new targets for the treatment of obesity and obesity-related disorders.

Analysis of the different characteristics between omental preadipocytes and differentiated white adipocytes using bioinformatics methods

Aldehyde dehydrogenase 2 (ALDH2), an acetaldehyde dehydrogenase in mitochondria, is primarily responsible for metabolizing alcohol-derived acetaldehyde and other endogenous aldehydes. Inactivating ALDH2 rs671 polymorphism is found in up to 8 % of the global population and 40 % of the East Asian population. Recent studies have shown that rs671 SNP mutation in the human ALDH2 gene is associated with an increased risk of metabolic dysfunction-associated steatotic liver diseases (MASLD), but the mechanism remains unclear. Here, we identify the role of ALDH2 in MASLD. Firstly, ALDH2 activity was lower in MASLD patients and the methionine-choline deficiency (MCD) diet induced MASLD model. Secondly, activation of ALDH2 activity with Alda-1 (ALDH2 agonist) attenuated MCD-diet induced hepatic triglyceride (TG) accumulation and steatosis, whereas the opposite result was observed with cyanamide (CYA, ALDH2 inhibitor). Furthermore, ALDH2 deficiency exacerbated hepatic steatosis, inflammation, and fibrosis in the MCD-diet induced mice. RNA sequencing (RNA-seq) revealed that oxysterol 7-α hydroxylase (Cyp7b1) and the related metabolic pathway significantly changed in the MCD-diet challenged ALDH2−/− mice. In ALDH2−/− mice, the expression of Cyp7b1 was downregulated and FXR/SHP signaling was inhibited, reducing the alternative bile acid (BA) synthetic pathway. In our in vitro experiments, knockdown of ALDH2 exacerbated TG accumulation in hepatocytes, whereas the opposite result was observed with overexpression of ALDH2. Moreover, chenodeoxycholic acid (CDCA) rescued ALDH2 downregulation induced TG accumulation in hepatocytes. Our study reveals that ALDH2 attenuates hepatocyte steatosis by regulating the alternative BA synthesis pathway, and ALDH2 may serve as a potential target for the treatment of MASLD. 

ALDH2 deficiency exacerbates MCD-diet induced MASLD by modulating bile acid metabolism.

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Analysis of the different characteristics between omental preadipocytes and differentiated white adipocytes using bioinformatics methods

ALDH2 deficiency exacerbates MCD-diet induced MASLD by modulating bile acid metabolism.