👤 Fatemeh Zarei

Statins are a class of cholesterol-lowering agents widely used in clinical practice to reduce plasma levels of low-density lipoprotein cholesterol in hyperlipidemic patients. Beyond their lipidlowering roles, statins exhibit several additional effects. In the current review, we searched PubMed, ScienceDirect, and Google Scholar databases using the keywords "Statins," "HMG-CoA reductase inhibitors," "Anti-inflammatory," "Antioxidant," and "Anticancer" to provide an overview of the effects of statins. Articles published on these topics between 1990 and 2025 were included. The retrieved records were imported into EndNote, and duplicates were removed. Multiple potential therapeutic benefits of statins have been described, including suppression of apoptosis, antioxidant, anti-inflammatory and anticancer effects, immunomodulation and neuroprotection. NADPH oxidases (NOX) play a crucial role in the development of various diseases through excessive production of reactive oxygen species (ROS) and the creation of oxidative stress conditions. Stimulation of BDNF/Nrf2, inhibition of NOX pathways, and reduction of intracellular ROS via enhanced antioxidant activity represent possible mechanisms through which statins exert their effects. Interestingly, ROS and inflammatory cytokines activate nuclear factor kappa B (NF-κB), a critical factor in the development of malignant tumors, which induces the expression of genes involved in cell proliferation and carcinogenesis. Furthermore, statins inhibit NF-κB activity, a key transcriptional regulator in inflammatory responses. Clinical evidence suggests that statins may reduce the risk of various cancers and disease recurrence due to their anti-inflammatory and antioxidant properties. These findings form the basis for new therapeutic avenues in cancer treatment, potentially offering a more promising strategy than statin monotherapy. Show less

Previous studies have shown that the C allele of melanocortin 4 receptor (MC4R) rs17782313 and the Alternative Healthy Eating Index (AHEI) are separately associated with obesity. However, the present study aimed to investigate the interaction between MC4R rs17782313 variants and the AHEI and their association with central and general obesity indices, which has not been assessed previously. In total, 291 women with body mass index (BMI) ≥ 25 kg m After adjustment for age, energy intake, physical activity, marital status, and economic status, the interaction between MC4R rs17782313 and the AHEI was associated with hip circumference [β = -0.41, 95% confidence interval (CI) = -0.77 to -0.05, p = 0.02], BMI (β = -0.15, 95% CI = -0.29 to -0.02, p = 0.02), fat mass (kg) (β = -0.28, 95% CI = -0.56 to -0.01, p = 0.03), visceral fat area (β = -5.68, 95% CI = -9.55 to -1.80, p = 0.004). The other measures that appear to be suggestively related to this interaction (0.05 < p < 0.07) are waist circumference, waist-to-height ratio, trunk fat (%), trunk fat (kg), fat mass (%) and fat mass index. The interaction between MC4R rs17782313 and the AHEI can be related to central and general obesity indices in overweight/obese women. Show less

Everolimus monotherapy use for metastatic renal cell carcinoma (mRCC) has diminished due to recent approvals of immune checkpoint and VEGF inhibitors. We hypothesized that gene expression associated with everolimus benefit may provide rationale to select appropriate patients. To address this hypothesis, tumors from a phase I/II trial that compared everolimus alone or with BNC105P, a vascular disrupting agent, were profiled using Nanostring as a discovery cohort. A phase III trial (CheckMate 025) was used for validation. Clinical benefit (CB) was defined as response or stable disease for ≥6 months. A propensity score covariate adjustment was used, and model discrimination performance was assessed using the area under the ROC curve (AUC). In a discovery cohort of 82 patients, 35 (43%) were treated with everolimus alone and 47 (57%) received everolimus + BNC105P. Median PFS (mPFS) was 4.9 (95% CI, 2.8-6.2) months. A four-gene signature (ASXL1, DUSP6, ERCC2, and HSPA6) correlated with CB with everolimus ± BNC105P [AUC, 86.9% (95% CI, 79.2-94.7)]. This was validated in 130 patients from CheckMate 025 treated with everolimus [AUC, 60.2% (95% CI, 49.7-70.7)]. Among 43 patients (52.4%) with low expression of an 18-gene signature, everolimus + BNC105P was associated with significantly longer mPFS compared with everolimus alone (10.4 vs. 6.9 months; HR, 0.49; 95% CI, 0.24-1.002; Show less

The mechanisms by which genetic variants, such as single nucleotide polymorphisms (SNPs), identified in genome-wide association studies act to influence body mass remain unknown for most of these SNPs, which continue to puzzle the scientific community. Recent evidence points to the epigenetic and chromatin states of the genome as having important roles. We genotyped 355 healthy young individuals for 52 known obesity-associated SNPs and obtained DNA methylation levels in their blood using the Illumina 450 K BeadChip. Associations between alleles and methylation at proximal cytosine residues were tested using a linear model adjusted for age, sex, weight category, and a proxy for blood cell type counts. For replication in other tissues, we used two open-access datasets (skin fibroblasts, n = 62; four brain regions, n = 121-133) and an additional dataset in subcutaneous and visceral fat (n = 149). We found that alleles at 28 of these obesity-associated SNPs associate with methylation levels at 107 proximal CpG sites. Out of 107 CpG sites, 38 are located in gene promoters, including genes strongly implicated in obesity (MIR148A, BDNF, PTPMT1, NR1H3, MGAT1, SCGB3A1, HOXC12, PMAIP1, PSIP1, RPS10-NUDT3, RPS10, SKOR1, MAP2K5, SIX5, AGRN, IMMP1L, ELP4, ITIH4, SEMA3G, POMC, ADCY3, SSPN, LGR4, TUFM, MIR4721, SULT1A1, SULT1A2, APOBR, CLN3, SPNS1, SH2B1, ATXN2L, and IL27). Interestingly, the associated SNPs are in known eQTLs for some of these genes. We also found that the 107 CpGs are enriched in enhancers in peripheral blood mononuclear cells. Finally, our results indicate that some of these associations are not blood-specific as we successfully replicated four associations in skin fibroblasts. Our results strongly suggest that many obesity-associated SNPs are associated with proximal gene regulation, which was reflected by association of obesity risk allele genotypes with differential DNA methylation. This study highlights the importance of DNA methylation and other chromatin marks as a way to understand the molecular basis of genetic variants associated with human diseases and traits. Show less