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Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10 Show less

Apelin, a bioactive peptide that serves as an endogenous ligand for the apelin receptor (APJ), is overexpressed in various types of cancers and contributes to cancer cell proliferation, viability, migration, angiogenesis, and metastasis, as well as immune deviation. Noncoding RNAs (ncRNAs) regulate gene expression, and there is growing evidence suggesting a bidirectional crosstalk between ncRNAs (including long noncoding RNAs [lncRNAs], circular RNAs [circRNAs], and microRNAs [miRNAs]) and apelin in cancers. Certain miRNAs can directly target the apelin and inhibit its expression, thereby suppressing tumor growth. It has been indicated that miR-224, miR-195/miR-195-5p, miR-204-5p, miR-631, miR-4286, miR-637, miR-4493, and miR-214-3p target apelin mRNA and influence its expression in prostate cancer, lung cancer, esophageal cancer, chondrosarcoma, melanoma, gastric cancer, glioma, and hepatocellular carcinoma (HCC), respectively. Moreover, circ-NOTCH1, circ-ZNF264, and lncRNA BACE1-AS upregulate apelin expression in gastric cancer, glioma, and HCC, respectively. On the other hand, apelin has been shown to regulate the expression of certain ncRNAs to affect tumorigenesis. It was revealed that apelin affects the expression of circ₀₀₀₀₀₀₄/miR-1303, miR-15a-5p, and miR-106a-5p in osteosarcoma, lung cancer, and prostate cancer, respectively. This review explains a bidirectional interplay between ncRNAs and apelin in cancers to provide insights concerning the molecular mechanisms underlying this crosstalk and potential implications for cancer therapy. Show less

Identifying population-specific genetic variants associated with disease and disease-predisposing traits is important to provide insights into the genetic determinants of health and disease between populations, as well as furthering genomic justice. Various common pan-population polymorphisms at Show less

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals ( Show less

Immune checkpoint inhibitors have revolutionized the treatment of metastatic melanoma, but most tumors show resistance. Resistance is connected to a non-T cell inflamed phenotype partially caused by a lack of functional dendritic cells (DCs) that are crucial for T cell priming. Herein, we investigated whether the adenoviral gene vehicle mLOAd703 carrying both DC- and T cell-activating genes can lead to inflammation in a B16-CD46 model and thereby overcome resistance to checkpoint inhibition therapy. B16-CD46 cells were injected subcutaneously in one or both flanks of immunocompetent C57BL/6J mice. mLOAd703 treatments were given intratumorally alone or in combination with intraperitoneal checkpoint inhibition therapy (anti-PD-1, anti-PD-L1, or anti-TIM-3). Tumor, lymph node, spleen, and serum samples were analyzed for the presence of immune cells and cytokines/chemokines. B16-CD46 tumors were non-inflamed and resistant to checkpoint blockade. In contrast, mLOAd703 treatment led to infiltration of the tumor by CD8 Show less

The current understanding of the genetic architecture of lipids has largely come from genome-wide association studies (GWAS). To date, few GWAS have examined the genetic architecture of lipids in Polynesians, and none have in Samoans, whose unique population history, including many population bottlenecks, may provide insight into the biological foundations of variation in lipid levels. Here we performed a GWAS of four fasting serum lipid levels: total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglycerides (TG) in a sample of 2849 Samoans, with validation genotyping for associations in a replication cohort comprising 1798 Samoans and American Samoans. We identified multiple genome-wide significant associations (P < 5 × 10 Show less

Mechanisms of metabolic syndrome (MetS) causation are complex, genetic and environmental factors are important factors for the pathogenesis of MetS In this study, we aimed to evaluate familial and genetic influences on metabolic syndrome risk factor and also assess association between FTO (rs1558902 and rs7202116) and CETP(rs1864163) genes' single nucleotide polymorphisms (SNP) with low HDL_C in the Tehran Lipid and Glucose Study (TLGS). The design was a cross-sectional study of 1776 members of 227 randomly-ascertained families. Selected families contained at least one affected metabolic syndrome and at least two members of the family had suffered a loss of HDL_C according to ATP III criteria. In this study, after confirming the familial aggregation with intra-trait correlation coefficients (ICC) of Metabolic syndrome (MetS) and the quantitative lipid traits, the genetic linkage analysis of HDL_C was performed using conditional logistic method with adjusted sex and age. The results of the aggregation analysis revealed a higher correlation between siblings than between parent-offspring pairs representing the role of genetic factors in MetS. In addition, the conditional logistic model with covariates showed that the linkage results between HDL_C and three marker, rs1558902, rs7202116 and rs1864163 were significant. In summary, a high risk of MetS was found in siblings confirming the genetic influences of metabolic syndrome risk factor. Moreover, the power to detect linkage increases in the one parameter conditional logistic model regarding the use of age and sex as covariates. Show less