Multiple genotype-phenotype association study reveals intronic variant pair on SIDT2 associated with metabolic syndrome in a Korean population

Metabolic Syndrome: An Overview on Its Genetic Associations and Gene-Diet Interactions

Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors that includes central obesity, hyperglycemia, hypertension, and dyslipidemias and whose inter-related occurrence may increase the odds of developing type 2 diabetes and cardiovascular diseases. MetS has become one of the most studied conditions, nevertheless, due to its complex etiology, this has not been fully elucidated. Recent evidence describes that both genetic and environmental factors play an important role on its development. With the advent of genomic-wide association studies, single nucleotide polymorphisms (SNPs) have gained special importance. In this review, we present an update of the genetics surrounding MetS as a single entity as well as its corresponding risk factors, considering SNPs and gene-diet interactions related to cardiometabolic markers. In this study, we focus on the conceptual aspects, diagnostic criteria, as well as the role of genetics, particularly on SNPs and polygenic risk scores (PRS) for interindividual analysis. In addition, this review highlights future perspectives of personalized nutrition with regard to the approach of MetS and how individualized multiomics approaches could improve the current outlook.

The functions of SID1 transmembrane family, member 2 (Sidt2)

The SID1 transmembrane family, member 2, namely, Sidt2, is a highly glycosylated multichannel lysosomal transmembrane protein, but its specific physiological function remains unknown. Lysosomal membrane proteins are very important for the executive functioning of lysosomes. As an important part of the lysosomal membrane, Sidt2 can maintain the normal morphology of lysosomes and help stabilize them from the acidic pH environment within. As a receptor/transporter, it binds and transports nucleic acids and mediates the uptake and degradation of RNA and DNA by the lysosome. During glucose metabolism, deletion of Sidt2 can cause an increase in fasting blood glucose and the impairment of grape tolerance, which is closely related to the secretion of insulin. During lipid metabolism, the loss of Sidt2 can cause hepatic steatosis and lipid metabolism disorders and can also play a role in signal regulation and transport. Here, we review the function of the lysosomal membrane protein Sidt2, and focus on its role in glucose and lipid metabolism, autophagy and nucleotide (DNA/RNA) transport.

Identifying genetic loci that are associated with changes in gene expression in PTSD in a South African cohort

The molecular mechanisms underlying posttraumatic stress disorder (PTSD) are yet to be fully elucidated, especially in underrepresented population groups. Expression quantitative trait loci (eQTLs) are DNA sequence variants that influence gene expression, in a local (cis-) or distal (trans-) manner, and subsequently impact cellular, tissue, and system physiology. This study aims to identify genetic loci associated with gene expression changes in a South African PTSD cohort. Genome-wide genotype and RNA-sequencing data were obtained from 32 trauma-exposed controls and 35 PTSD cases of mixed-ancestry, as part of the SHARED ROOTS project. The first approach utilised 108 937 single-nucleotide polymorphisms (SNPs) (MAF > 10%) and 11 312 genes with Matrix eQTL to map potential eQTLs, while controlling for covariates as appropriate. The second analysis was focused on 5638 SNPs related to a previously calculated PTSD polygenic risk score for this cohort. SNP-gene pairs were considered eQTLs if they surpassed Bonferroni correction and had a false discovery rate <0.05. We did not identify eQTLs that significantly influenced gene expression in a PTSD-dependent manner. However, several known cis-eQTLs, independent of PTSD diagnosis, were observed. rs8521 (C > T) was associated with TAGLN and SIDT2 expression, and rs11085906 (C > T) was associated with ZNF333 expression. This exploratory study provides insight into the molecular mechanisms associated with PTSD in a non-European, admixed sample population. This study was limited by the cross-sectional design and insufficient statistical power. Overall, this study should encourage further multi-omics approaches towards investigating PTSD in diverse populations.

Interaction between SIDT2 and ABCA1 Variants with Nutrients on HDL-c Levels in Mexican Adults

Previous studies have reported that the SIDT2 and ABCA1 genes are involved in lipid metabolism. We aimed to analyze the association-the gene x gene interaction between rs17120425 and rs1784042 on SIDT2 and rs9282541 on ABCA1 and their diet interaction on the HDL-c serum levels-in a cohort of 1982 Mexican adults from the Health Workers Cohort Study. Demographic and clinical data were collected through a structured questionnaire and standardized procedures. Genotyping was performed using a predesigned TaqMan assay. The associations and interactions of interest were estimated using linear and logistic regression. Carriers of the rs17120425-A and rs1784042-A alleles had slightly higher blood HDL-c levels compared to the non-carriers. In contrast, rs9282541-A was associated with low blood HDL-c levels (OR = 1.34, p = 0.013). The rs1784042 x rs9282541 interaction was associated with high blood HDL-c levels (p = 3.4 × 10^-4). Premenopausal women who carried at least one rs17120425-A allele and consumed high dietary fat, protein, monounsaturated, or polyunsaturated fatty acids levels had higher HDL-c levels than the non-carriers. These results support the association between the genetic variants on SIDT2 and ABCA1 with HDL-c levels and suggest gene-gene and gene-diet interactions over HDL-c concentrations in Mexican adults. Our findings could be a platform for developing clinical and dietary strategies for improving the health of the Mexican population.

A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

“Big Data” Approaches for Prevention of the Metabolic Syndrome

Metabolic syndrome (MetS) is characterized by the concurrence of multiple metabolic disorders resulting in the increased risk of a variety of diseases related to disrupted metabolism homeostasis. The prevalence of MetS has reached a pandemic level worldwide. In recent years, extensive amount of data have been generated throughout the research targeted or related to the condition with techniques including high-throughput screening and artificial intelligence, and with these “big data”, the prevention of MetS could be pushed to an earlier stage with different data source, data mining tools and analytic tools at different levels. In this review we briefly summarize the recent advances in the study of “big data” applications in the three-level disease prevention for MetS, and illustrate how these technologies could contribute tobetter preventive strategies.

Differential DNA Methylation and Cardiometabolic Risk in African American Mother-Adolescent Dyads

BACKGROUND

Cardiovascular disease disproportionately affects African Americans as the leading cause of morbidity and mortality. Among African Americans, compared to other racial groups, cardiovascular disease onset occurs at an earlier age due to a higher prevalence of cardiometabolic risk factors, particularly obesity, hypertension and type 2 diabetes. Emerging evidence suggests that heritable epigenetic processes are related to increased cardiovascular disease risk, but this is largely unexplored in adolescents or across generations.

MATERIALS AND METHODS

In a cross-sectional descriptive pilot study in low-income African American mother-adolescent dyads, we examined associations between DNA methylation and the cardiometabolic indicators of body mass index, waist circumference, and insulin resistance.

RESULTS

Four adjacent cytosine and guanine nucleotides (CpG) sites were significantly differentially methylated and associated with C-reactive protein (CRP), 62 with waist circumference, and none to insulin resistance in models for both mothers and adolescents.

CONCLUSION

Further study of the relations among psychological and environmental stressors, indicators of cardiovascular disease, risk, and epigenetic factors will improve understanding of cardiovascular disease risk so that preventive measures can be instituted earlier and more effectively. To our knowledge this work is the first to examine DNA methylation and cardiometabolic risk outcomes in mother-adolescent dyads.

A nine-hub-gene signature of metabolic syndrome identified using machine learning algorithms and integrated bioinformatics

Early risk assessments and interventions for metabolic syndrome (MetS) are limited because of a lack of effective biomarkers. In the present study, several candidate genes were selected as a blood-based transcriptomic signature for MetS. We collected so far the largest MetS-associated peripheral blood high-throughput transcriptomics data and put forward a novel feature selection strategy by combining weighted gene co-expression network analysis, protein-protein interaction network analysis, LASSO regression and random forest approaches. Two gene modules and 51 hub genes as well as a 9-hub-gene signature associated with metabolic syndrome were identified. Then, based on this 9-hub-gene signature, we performed logistic analysis and subsequently established a web nomogram calculator for metabolic syndrome risk (https://xjtulgz.shinyapps.io/DynNomapp/). This 9-hub-gene signature showed excellent classification and calibration performance (AUC = 0.968 in training set, AUC = 0.883 in internal validation set, AUC = 0.861 in external validation set) as well as ideal potential clinical benefit.

The role of lysosomal membrane proteins in glucose and lipid metabolism

Lysosomes have long been regarded as the "garbage dump" of the cell. More recently, however, researchers have revealed novel roles for lysosomal membranes in autophagy, ion transport, nutrition sensing, and membrane fusion and repair. With active research into lysosomal membrane proteins (LMP), increasing evidence has become available showing that LMPs are inextricably linked to glucose and lipid metabolism, and this relationship represents mutual influence and regulation. In this review, we summarize the roles of LMPs in relation to glucose and lipid metabolism, and describe their roles in glucose transport, glycolysis, cholesterol transport, and lipophagy. The role of transport proteins can be traced back to the original discoveries of GLUT8, NPC1, and NPC2, which were all found to have significant roles in the pathways involved in glucose and lipid metabolism. CLC-5 and SIDT2-knockout animals show serious phenotypic disorders of metabolism, and V-ATPase and LAMP-2 have been found to interact with proteins related to glucose and lipid metabolism. These findings all emphasize the critical role of LMPs in glycolipid metabolism and help to strengthen our understanding of the independent and close relationship between LMPs and glycolipid metabolism.

Genome-Wide Association Study Identifies a Functional SIDT2 Variant Associated With HDL-C (High-Density Lipoprotein Cholesterol) Levels and Premature Coronary Artery Disease

Objective

Low HDL-C (high-density lipoprotein cholesterol) is the most frequent dyslipidemia in Mexicans, but few studies have examined the underlying genetic basis. Our purpose was to identify genetic variants associated with HDL-C levels and cardiovascular risk in the Mexican population.

Approach and Results

A genome-wide association studies for HDL-C levels in 2335 Mexicans, identified four loci associated with genome-wide significance: CETP, ABCA1, LIPC, and SIDT2. The SIDT2 missense Val636Ile variant was associated with HDL-C levels and was replicated in 3 independent cohorts (P=5.9×10−18 in the conjoint analysis). The SIDT2/Val636Ile variant is more frequent in Native American and derived populations than in other ethnic groups. This variant was also associated with increased ApoA1 and glycerophospholipid serum levels, decreased LDL-C (low-density lipoprotein cholesterol) and ApoB levels, and a lower risk of premature CAD. Because SIDT2 was previously identified as a protein involved in sterol transport, we tested whether the SIDT2/Ile636 protein affected this function using an in vitro site-directed mutagenesis approach. The SIDT2/Ile636 protein showed increased uptake of the cholesterol analog dehydroergosterol, suggesting this variant affects function. Finally, liver transcriptome data from humans and the Hybrid Mouse Diversity Panel are consistent with the involvement of SIDT2 in lipid and lipoprotein metabolism.

Conclusions

This is the first genome-wide association study for HDL-C levels seeking associations with coronary artery disease in the Mexican population. Our findings provide new insight into the genetic architecture of HDL-C and highlight SIDT2 as a new player in cholesterol and lipoprotein metabolism in humans.

Association of BTLA Polymorphisms with Susceptibility to Non-Small-Cell Lung Cancer in the Chinese Population

Studies have reported that B- and T-lymphocyte attenuator (BTLA) polymorphisms may be associated with the risk to different cancers. However, the correlation between those variations and non-small-cell lung cancer (NSCLC) is still unclear. A total of 1,003 NSCLC patients and 901 noncancer controls were recruited in the study, to confirm the association of variations in BTLA gene with the risk of NSCLC. The SNPscan™ genotyping assay was used to obtain the genotypes of the four BTLA polymorphisms (BTLA rs1982809 G>A, rs16859629 T>C, rs2171513 G>A, and rs3112270 A>G). It was found that BTLA rs1982809 polymorphism reduced the risk of NSCLC (GA vs. GG: adjusted odds ratio (OR) = 0.81, 95%confidence interval (CI) = 0.66‐0.99, and P = 0.043). However, the BTLA rs16859629, rs2171513, and rs3112270 polymorphisms showed no significant association between NSCLC patients and controls in overall comparison. In subgroup analyses, we found that BTLA rs1982809 polymorphism reduced the risk of NSCLC (nonsquamous cell carcinoma: GA vs. GG: adjusted OR = 0.79, 95%CI = 0.64‐0.97, and P = 0.026; AA/GA vs. GG: adjusted OR = 0.81, 95%CI = 0.66‐0.99, and P = 0.037; ≥59 years: GA vs. GG: P = 0.036; never alcohol consumption: GA vs. GG: P = 0.013; GA/AA vs. GG: P = 0.016; body mass index (BMI) ≥ 24 kg/m²: GA vs. GG: P = 0.030; GA/AA vs. GG: P = 0.041). The BTLA rs16859629 polymorphism increased the risk of the development of squamous cell carcinoma (CC vs. TT: adjusted OR = 9.85, 95%CI = 1.37‐71.03, and P = 0.023; CC vs. TT/TC: adjusted OR = 9.55, 95%CI = 1.32‐68.66, and P = 0.025). Taken together, the findings of the present suggest that BTLA rs1982809 and rs16859629 polymorphisms may influence the susceptibility to NSCLC in the Chinese population.

The Variant rs1784042 of the SIDT2 Gene is Associated with Metabolic Syndrome through Low HDL-c Levels in a Mexican Population

The Mexican population has one of the highest prevalences of metabolic syndrome (MetS) worldwide. The aim of this study was to investigate the association of single-nucleotide polymorphisms (SNPs) with MetS and its components. First, we performed a pilot Genome-wide association study (GWAS) scan on a sub-sample derived from the Health Workers Cohort Study (HWCS) (n = 411). Based on GWAS results, we selected the rs1784042 and rs17120425 SNPs in the SIDT1 transmembrane family member 2 (SIDT2) gene for replication in the entire cohort (n = 1963), using predesigned TaqMan assays. We observed a prevalence of MetS in the HWCS of 52.6%. The minor allele frequency for the variant rs17120425 was 10% and 29% for the rs1784042. The SNP rs1784042 showed an overall association with MetS (OR = 0.82, p = 0.01) and with low levels of high-density lipoprotein (HDL-c) (odds ratio (OR) = 0.77, p = 0.001). The SNP rs17120425 had a significant association with type 2 diabetes (T2D) risk in the overall population (OR = 1.39, p = 0.033). Our results suggest an association of the rs1784042 and rs17120425 variants with MetS, through different mechanisms in the Mexican population. Further studies in larger samples and other populations are required to validate these findings and the relevance of these SNPs in MetS.