Association of INSIG2 polymorphism with overweight and LDL in children

Polymorphic variants INSIG2 rs6726538, HLA-DRB1 rs9272143, and GCNT1P5 rs7780883 contribute to the susceptibility of cervical cancer in the Bangladeshi women

Objective

Cervical cancer is a gynecological health problem, affecting nearly 500,000 women each year worldwide. Genome‐wide association studies have revealed multiple susceptible genes and their polymorphisms for cervical carcinoma risk. We have carried out this case‐control study to investigate the association of INSIG2 rs6726538 (A; T), HLA‐DRB1 rs9272143 (T; C), and GCNT1P5 rs7780883 (G; A) with cervical cancer.

Methods

The present study recruited 234 cervical cancer patients as cases and 212 healthy females as controls. We have applied the tetra‐primer amplification refractory mutation system polymerase chain reaction (T‐ARMS‐PCR) method for genotyping.

Results

The SNP rs6726538 was significantly associated with increased risk of cervical cancer in all genetic models (AT vs. AA: OR = 3.30, 95% CI = 2.19–4.97, p < 0.0001; TT vs. AA: OR = 8.72, 95% CI = 3.87–19.7, p < 0.0001; AT+TT vs. AA: OR = 3.87, 95% CI = 2.61–5.73, p < 0.0001; T vs. A: OR = 2.97, 95% CI = 2.20–4.01, p < 0.0001) except the recessive model which showed a significantly reduced risk (TT vs. AA+AT: OR = 0.20, 95% CI = 0.09–0.44, p = 0.0001). rs9272143 showed significantly reduced risk for the additive model 1, dominant model, and allelic model (TC vs. TT: OR = 0.46, 95% CI = 0.31–0.70, p = 0.0004; TC+CC vs. TT: OR = 0.47 95% CI = 0.32–0.70, p = 0.0002; C vs. T: OR = 0.56, 95% CI = 0.40–0.78, p = 0.0006, respectively). The third variant, rs7780883, was significantly associated with increased risk in additive model 2, dominant, and allelic models (AA vs. GG: OR = 5.08, 95% CI = 2.45–10.5, p < 0.0001; GA+AA vs. GG: OR = 1.54, 95% CI = 1.06–2.24, p = 0.0237; A vs. G: OR = 1.88, 95% CI = 1.34–2.52, p < 0.0001, consecutively), whereas recessive model reduced the risk of cervical cancer (AA vs. GG+GA: OR = 0.20, 95% CI = 0.09–0.41, p < 0.0001). Other models of these SNPs were not associated with cervical cancer. All significant associations for three SNPs withstand after Bonferroni correction except the additive model 2 of rs7780883.

Conclusion

Our study concludes that INSIG2 rs6726538, HLA‐DRB1 rs9272143, and GCNT1P5 rs7780883 polymorphisms may contribute to the development of cervical cancer in the Bangladeshi population.

Personalized Nutrition and -Omics

With change in global concern toward food quality over food quantity, consumer concern and choice of healthy food has become a matter of prime importance. It gave rise to concept of “personalized or precision nutrition”. The theory behind personalization of nutrition is supported by multiple factors including advances in food analytics, nutrition based diseases and public health programs, increasing use of information technology in nutrition science, concept of gene-diet interaction and growing consumer capacity or concern by better and healthy foods. The advances in “omics” tools and related analytical techniques have resulted into tremendous scope of their application in nutrition science. As a consequence, a better understanding of underlying interaction between diet and individual is expected with addressing of key challenges for successful implementation of this science. In this chapter, the above aspects are discussed to get an insight into driving factors for increasing concern in personalized nutrition.

Adolescent obesity in the past decade: A systematic review of genetics and determinants of food choice

Background and purpose:

As the incidence of global obesity increases, concerns about adverse health outcomes in adolescents continues to rise. The complexity and expense of this problem require early recognition and specific preventive treatments. Knowledge of genetics and determinants of food choices contributing to adolescent obesity warrants further examination. The primary goal was to appraise the literature from the past decade (2007–2017) on the current state of food choice and genetic determinants of adolescent overweight/obesity in the United States. The secondary goal was to determine trends in the literature and areas for future research.

Methods:

A systematic review of research studies in the United States from 2007 to 2017 was completed. Database searches were conducted using CINAHL, Embase, PsycINFO, PsycArticles, PubMed, Scopus, Academic Search Complete, Web of Science, BIOSIS, and the Cochrane Library. A total of 535 studies were selected. Of these, 283 studies focused on determinants of food choices and 165 studies focused on genetic factors.

Conclusions:

A total of 41 full-text articles included in this literature review contained studies limited exclusively to adolescents. Stress factors related to food choices demonstrated a new trend being explored. The need for precision health, the application of genetic information, could uncover ways food choices affect adolescent obesity.

Implications for practice:

The etiology of adolescent obesity requires that nurses gain knowledge of genetics and food choice determinants to inform personalized treatments for adolescents, which may establish effective interventions that promote healthy weight achievement.

Antipsychotics Promote Metabolic Disorders Disrupting Cellular Lipid Metabolism and Trafficking

Antipsychotics frequently cause obesity and related metabolic disorders that current psychopharmacological/endocrinological theories do not explain consistently. An integrative/alternative theory implies metabolic alterations happening at the cellular level. Many observations in vitro and in vivo, and pivotal observations in humans, point towards chemical properties of antipsychotics, independent of receptor binding characteristics. Being amphiphilic weak bases, antipsychotics can disrupt lysosomal function, affecting cholesterol trafficking; moreover, by chemical mimicry, antipsychotics can inhibit cholesterol biosynthesis. These two molecular adverse effects may trigger a cascade of transcriptional and biochemical events, ultimately reducing available cholesterol while increasing cholesterol precursors and fatty acids. The macroscopic manifestation of these molecular alterations includes decreased high-density lipoprotein and increased very low-density lipoprotein and triglycerides that may translate into obesity and related metabolic disorders.

INSIG2 rs7566605 single nucleotide variant and global DNA methylation index levels are associated with weight loss in a personalized weight reduction program

Single nucleotide polymorphisms associated with lipid metabolism and energy balance are implicated in the weight loss response caused by nutritional interventions. Diet-induced weight loss is also associated with differential global DNA methylation. DNA methylation has been proposed as a predictive biomarker for weight loss response. Personalized biomarkers for successful weight loss may inform clinical decisions when deciding between behavioral and surgical weight loss interventions. The aim of the present study was to investigate the association between global DNA methylation, genetic variants associated with energy balance and lipid metabolism, and weight loss following a non-surgical weight loss regimen. The present study included 105 obese participants that were enrolled in a personalized weight loss program based on their allelic composition of the following five energy balance and lipid metabolism-associated loci: Near insulin-induced gene 2 (INSIG2); melanocortin 4 receptor; adrenoceptor β2; apolipoprotein A5; and G-protein subunit β3. The present study investigated the association between a global DNA methylation index (GDMI), the allelic composition of the five energy balance and lipid metabolism-associated loci, and weight loss during a 12 month program, after controlling for age, sex and body mass index (BMI). The results demonstrated a significant association between the GDMI and near INSIG2 locus, after adjusting for BMI and weight loss, and significant trends were observed when stratifying by gender. In conclusion, a combination of genetic and epigenetic biomarkers may be used to design personalized weight loss interventions, enabling adherence and ensuring improved outcomes for obesity treatment programs. Precision weight loss programs designed based on molecular information may enable the creation of personalized interventions for patients, that use genomic biomarkers for treatment design and for treatment adherence monitoring, thus improving response to treatment.

The future of nutrition: Nutrigenomics and nutrigenetics in obesity and cardiovascular diseases

Over time, the relationship between diet and health has aroused great interest, since nutrition can prevent and treat several diseases. It has been demonstrated that general recommendations on macronutrients and micronutrients do not affect to every individual in the same way because diet is an important environmental factor that interacts with genes. Thus, there is a growing necessity of improving a personalized nutrition to treat obesity and associated medical conditions, taking into account the interactions between diet, genes and health. Therefore, the knowledge of the interactions between the genome and nutrients at the molecular level, has led to the advent of nutritional genomics, which involves the sciences of nutrigenomics and nutrigenetics. In this review, we will comprehensively analyze the role of the most important genes associated with two interrelated chronic medical conditions, such as obesity and cardiovascular diseases.

Genetic determinants of inherited susceptibility to hypercholesterolemia - a comprehensive literature review

Hypercholesterolemia is a strong determinant of mortality and morbidity associated with cardiovascular diseases and a major contributor to the global disease burden. Mutations in four genes (LDLR, APOB, PCSK9 and LDLRAP1) account for the majority of cases with familial hypercholesterolemia. However, a substantial proportion of adults with hypercholesterolemia do not have a mutation in any of these four genes. This indicates the probability of having other genes with a causative or contributory role in the pathogenesis of hypercholesterolemia and suggests a polygenic inheritance of this condition. Here in, we review the recent evidence of association of the genetic variants with hypercholesterolemia and the three lipid traits; total cholesterol (TC), HDL-cholesterol (HDL-C) and LDL-cholesterol (LDL-C), their biological pathways and the associated pathogenetic mechanisms. Nearly 80 genes involved in lipid metabolism (encoding structural components of lipoproteins, lipoprotein receptors and related proteins, enzymes, lipid transporters, lipid transfer proteins, and activators or inhibitors of protein function and gene transcription) with single nucleotide variants (SNVs) that are recognized to be associated with hypercholesterolemia and serum lipid traits in genome-wide association studies and candidate gene studies were identified. In addition, genome-wide association studies in different populations have identified SNVs associated with TC, HDL-C and LDL-C in nearly 120 genes within or in the vicinity of the genes that are not known to be involved in lipid metabolism. Over 90% of the SNVs in both these groups are located outside the coding regions of the genes. These findings indicates that there might be a considerable number of unrecognized processes and mechanisms of lipid homeostasis, which when disrupted, would lead to hypercholesterolemia. Knowledge of these molecular pathways will enable the discovery of novel treatment and preventive methods as well as identify the biochemical and molecular markers for the risk prediction and early detection of this common, yet potentially debilitating condition.

Four novel polymorphisms of buffalo INSIG2 gene are associated with milk production traits in Chinese buffaloes

Insulin-induced genes (INSIGs), including INSIG1 and INSIG2, are important mediators that play a pivotal role in the lipid metabolism and could cause the retention of the SCAP/SREBP complex. Therefore, the objective of this study is to detect the single nucleotide polymorphisms (SNPs) of buffalo INSIG2 gene and evaluate their associations with milk production traits in Chinese buffaloes. A total of four SNPs (g.621272A > G, g.621364A > C, g.632543G > A, and g.632684C > T) were identified using DNA pooled sequencing, and the SNP genotyping for the identified SNPs was performed by using Matrix-assisted laser desorption/ionization time of flight mass spectrometry method from 264 individuals. The results showed that four SNPs were significantly associated with 305-day milk yield or protein percentage in Murrah and crossbred breeds (P < 0.05), but they had no significant effect on milk production traits in Nili-Ravi buffaloes (P > 0.05). Linkage disequilibrium (LD) analysis revealed that one haplotype block was successfully constructed, of which the diplotype H1H1 showed significant association with 305-day milk yield in Murrah buffaloes (P < 0.05). Our findings provide evidence that polymorphisms in buffalo INSIG2 gene are associated with milk production traits, and could be used as a candidate gene for marker-assisted selection in buffalo breeding program.

SETDB2 Links Glucocorticoid to Lipid Metabolism through Insig2a Regulation

Transcriptional and chromatin regulations mediate the liver response to nutrient availability. The role of chromatin factors involved in hormonal regulation in response to fasting is not fully understood. We have identified SETDB2, a glucocorticoid-induced putative epigenetic modifier, as a positive regulator of GR-mediated gene activation in liver. Insig2a increases during fasting to limit lipid synthesis, but the mechanism of induction is unknown. We show Insig2a induction is GR-SETDB2 dependent. SETDB2 facilitates GR chromatin enrichment and is key to glucocorticoid-dependent enhancer-promoter interactions. INSIG2 is a negative regulator of SREBP, and acute glucocorticoid treatment decreased active SREBP during refeeding or in livers of Ob/Ob mice, both systems of elevated SREBP-1c-driven lipogenesis. Knockdown of SETDB2 or INSIG2 reversed the inhibition of SREBP processing. Overall, these studies identify a GR-SETDB2 regulatory axis of hepatic transcriptional reprogramming and identify SETDB2 as a potential target for metabolic disorders with aberrant glucocorticoid actions.