BMP1 5'UTR + 104 T/C gene variation: can be a predictive marker for serum HDL and apoprotein A1 levels in male patients with coronary heart disease

Can Bone Morphogenetic Protein 1 (BMP1) Be a Potential Biomarker of Obesity?

Background Obesity has long been a severe threat to public health as an epidemic, and studies on its pathogenesis and treatment have been ongoing. Our study aims to compare the serum levels of bone morphogenetic protein 1 (BMP1), neuregulin 4 (NRG4), and apolipoprotein A5 (ApoA5) in obese and non-obese individuals and investigate their association with obesity. Methodology Our study included a total of 111 participants, of whom 46 were obese (body mass index (BMI) ≥30 kg/m2), aged 18-65 years, and had no comorbidities, and 65 were non-obese (BMI = 18.5-29.9 kg/m2) without any additional disease. For all participants, BMP1, NRG4, and ApoA5 levels were determined and compared with clinical and biochemical parameters. Results Overall, 60.4% (n = 67) of the participants were female and 39.6% (n = 44) were male. In terms of the BMI scores, 58.6% (n = 65) had a BMI <30 kg/m2 and 41.4% (n = 46) had a BMI ≥30 kg/m2. Both, the BMI and the gender groups did not differ significantly in terms of age (p = 0.093 and p = 0.795, respectively). The weight, fat-free mass, mineral quantity, protein quantity, fluid weight, and fluid ratio values of the male participants were significantly higher than females (p = 0.011, p = 0.001, p = 0.001, p = 0.001, p = 0.001, and p = 0.001, respectively). The aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratios and the triglyceride/glucose (TG/Glu) ratios were found to be significantly higher in males than in females (p = 0.001 and p = 0.001, respectively). The respective BMP1 (15.88 vs. 13.35), AST/ALT (1.36 vs. 1.04) and TG/Glu ratios (1.47 vs. 1.29) were significantly higher, while the quantitative insulin sensitivity check index (QUICKI) was lower in obese individuals than in non-obese individuals (0.32 vs. 0.34). NRG4 and ApoA5 values were similar between the two groups. BMP1, QUICKI values, and AST/ALT ratios proved to be statistically significant in obesity through the univariable logistic regression analysis (β = 1.066, p = 0.048; β = 0.0001, p = 0.001, and β = 3.707, p = 0.003, respectively). On multiple logistic regression analysis, QUICKI values (β = 0.001, p = 0.001) had a negative and significant effect on obesity, and the AST/ALT ratios (β = 2.803, p = 0.033) had a positive and significant effect on obesity. Conclusions Our study indicates that detecting an important link between BMP1 in obese patients will help elucidate the pathogenesis of obesity and come up with a potential therapeutic candidate. BMP1 levels, along with AST/ALT and TG/Glu ratios, were significantly higher in obese patients. BMP1 levels were also an independent significant predictor of obesity together with AST/ALT ratio and QUICKI in this study, suggesting that it may exhibit a metabolic deterioration in obese individuals. However, the results cannot absolutely tell whether it supported deterioration or was a component of the repair mechanism. Althoughit is generally known from recent studies that BMP1 plays a role in osteogenesis, some encouraging results were obtained in our study indicating that BMP1 may play a role in the pathogenesis of obesity. It is expected that our results will not only promote the elucidation of the pathogenesis of obesity, but also provide a therapeutic agent.

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is the metabolic disorder that appears during pregnancy. The current investigation aimed to identify central differentially expressed genes (DEGs) in GDM. The transcription profiling by array data (E-MTAB-6418) was obtained from the ArrayExpress database. The DEGs between GDM samples and non-GDM samples were analyzed. Functional enrichment analysis were performed using ToppGene. Then we constructed the protein–protein interaction (PPI) network of DEGs by the Search Tool for the Retrieval of Interacting Genes database (STRING) and module analysis was performed. Subsequently, we constructed the miRNA–hub gene network and TF–hub gene regulatory network. The validation of hub genes was performed through receiver operating characteristic curve (ROC). Finally, the candidate small molecules as potential drugs to treat GDM were predicted by using molecular docking. Through transcription profiling by array data, a total of 869 DEGs were detected including 439 up-regulated and 430 down-regulated genes. Functional enrichment analysis showed these DEGs were mainly enriched in reproduction, cell adhesion, cell surface interactions at the vascular wall and extracellular matrix organization. Ten genes, HSP90AA1, EGFR, RPS13, RBX1, PAK1, FYN, ABL1, SMAD3, STAT3 and PRKCA were associated with GDM, according to ROC analysis. Finally, the most significant small molecules were predicted based on molecular docking. This investigation identified hub genes, signal pathways and therapeutic agents, which might help us, enhance our understanding of the mechanisms of GDM and find some novel therapeutic agents for GDM.

[Influence of rs670 variant of APOA1 gene on serum HDL response to an enriched-polyunsaturated vs. an enriched-monounsaturated fat hypocaloric diet]

Introduction

Background and objectives: genetic variants of the APOA1 gene have been related to lipid profile in obese subjects. Our aim was to analyze the effects of the rs670 APOA1 gene polymorphism on metabolic changes secondary to an enriched-polyunsaturated fat vs. an enriched-monounsaturated fat hypocaloric diet. Methods: 360 Caucasian obese subjects were randomly allocated to two groups. One group received an enriched-polyunsaturated fat (diet P) and the other an enriched-monounsaturated fat hypocaloric diet (diet M) during 12 weeks. The effects on serum biomarkers related to lipid and carbohydrate metabolism were evaluated before and after the dietary intervention. Results: after both diets, body mass index, weight, fat mass, waist circumference, systolic blood pressure, plasma leptin concentration, and waist circumference decreased in all patients. After 12 weeks of intervention with diet P, plasma insulin levels and HOMA-IR decreased in A-allele carriers: delta: -7.3 ± 2.2 IU/L (p = 0.01), and delta: -2.8 ± 0.5 units (p = 0.02), respectively. The same changes in delta were observed after diet M in A-allele carriers: insulin delta: -5.9 ± 1.2 IU/L (p = 0.01), and HOMA-IR delta: -2.1 ± 0.8 units (p = 0.02). In A-allele carriers, LDL-cholesterol decreased and HDL-cholesterol increased after the dietary intervention with diet P: delta: -12.1 ± 4.3 mg/dL (p = 0.01), and delta: 2.6 ± 0.7 mg/dL (p = 0.01), respectively. No differences in lipid profile were observed after diet M. These improvements were not observed in non-A-allele carriers after both interventions. Conclusions: our study showed the association of the rs670 ApoA1 polymorphism with insulin resistance changes as induced by both diets. An enriched-polyunsaturated fat diet produced an additional improvement of HDL-cholesterol and LDL-cholesterol in A-allele carriers.