Obesity-related CpG Methylation (cg07814318) of Kruppel-like Factor-13 (KLF13) Gene with Childhood Obesity and its cis-Methylation Quantitative Loci

Bioinformatic Evaluation of KLF13 Genetic Variant: Implications for Neurodevelopmental and Psychiatric Symptoms

The Krüppel-like factor (KLF) family represents a group of transcription factors (TFs) performing different biological processes that are crucial for proper neuronal function, including neuronal development, synaptic plasticity, and neuronal survival. As reported, genetic variants within the KLF family have been associated with a wide spectrum of neurodevelopmental and psychiatric symptoms. In a patient exhibiting attention deficit hyperactivity disorder (ADHD) combined with both neurodevelopmental and psychiatric symptoms, whole-exome sequencing (WES) analysis revealed a de novo heterozygous variant within the Krüppel-like factor 13 (KLF13) gene, which belongs to the KLF family and regulates axonal growth, development, and regeneration in mice. Moreover, in silico analyses pertaining to the likely pathogenic significance of the variant and the impact of the mutation on the KLF13 protein structure suggested a potential deleterious effect. In fact, the variant was localized in correspondence to the starting residue of the N-terminal domain of KLF13, essential for protein-protein interactions, DNA binding, and transcriptional activation or repression. This study aims to highlight the potential involvement of the KLF13 gene in neurodevelopmental and psychiatric disorders. Nevertheless, we cannot rule out that excluded variants, those undetectable by WES, or the polygenic risk may have contributed to the patient's phenotype given ADHD's high polygenic risk. However, further functional studies are required to validate its potential contribution to these disorders.

Novel insights into regulators and functional modulators of adipogenesis

Adipogenesis is a process that differentiates new adipocytes from precursor cells and is tightly regulated by several factors, including many transcription factors and various post-translational modifications. Recently, new roles of adipogenesis have been suggested in various diseases. However, the molecular mechanisms and functional modulation of these adipogenic genes remain poorly understood. This review summarizes the regulatory factors and modulators of adipogenesis and discusses future research directions to identify novel mechanisms regulating adipogenesis and the effects of adipogenic regulators in pathological conditions. The master adipogenic transcriptional factors PPARγ and C/EBPα were identified along with other crucial regulatory factors such as SREBP, Kroxs, STAT5, Wnt, FOXO1, SWI/SNF, KLFs, and PARPs. These transcriptional factors regulate adipogenesis through specific mechanisms, depending on the adipogenic stage. However, further studies related to the in vivo role of newly discovered adipogenic regulators and their function in various diseases are needed to develop new potent therapeutic strategies for metabolic diseases and cancer.

Krüppel-like Factor-9 and Krüppel-like Factor-13: Highly Related, Multi-Functional, Transcriptional Repressors and Activators of Oncogenesis

Specificity Proteins/Krüppel-like Factors (SP/KLF family) are a conserved family of transcriptional regulators. These proteins share three highly conserved, contiguous zinc fingers in their carboxy-terminus, requisite for binding to cis elements in DNA. Each SP/KLF protein has unique primary sequence within its amino-terminal and carboxy-terminal regions, and it is these regions which interact with co-activators, co-repressors, and chromatin-modifying proteins to support the transcriptional activation and repression of target genes. Krüppel-like Factor 9 (KLF9) and Krüppel-like Factor 13 (KLF13) are two of the smallest members of the SP/KLF family, are paralogous, emerged early in metazoan evolution, and are highly conserved. Paradoxically, while most similar in primary sequence, KLF9 and KLF13 display many distinct roles in target cells. In this article, we summarize the work that has identified the roles of KLF9 (and to a lesser degree KLF13) in tumor suppression or promotion via unique effects on differentiation, pro- and anti-inflammatory pathways, oxidative stress, and tumor immune cell infiltration. We also highlight the great diversity of miRNAs, lncRNAs, and circular RNAs which provide mechanisms for the ubiquitous tumor-specific suppression of KLF9 mRNA and protein. Elucidation of KLF9 and KLF13 in cancer biology is likely to provide new inroads to the understanding of oncogenesis and its prevention and treatments.

Bioinformatics Analysis of Next Generation Sequencing Data Identifies Molecular Biomarkers Associated With Type 2 Diabetes Mellitus

Background

Type 2 diabetes mellitus (T2DM) is the most common metabolic disorder. The aim of the present investigation was to identify gene signature specific to T2DM.

Methods

The next generation sequencing (NGS) dataset GSE81608 was retrieved from the gene expression omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) between T2DM and normal controls. Then, Gene Ontology (GO) and pathway enrichment analysis, protein-protein interaction (PPI) network, modules, miRNA (micro RNA)-hub gene regulatory network construction and TF (transcription factor)-hub gene regulatory network construction, and topological analysis were performed. Receiver operating characteristic curve (ROC) analysis was also performed to verify the prognostic value of hub genes.

Results

A total of 927 DEGs (461 were up regulated and 466 down regulated genes) were identified in T2DM. GO and REACTOME results showed that DEGs mainly enriched in protein metabolic process, establishment of localization, metabolism of proteins, and metabolism. The top centrality hub genes APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1 were screened out as the critical genes. ROC analysis provides prognostic value of hub genes.

Conclusion

The potential crucial genes, especially APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1, might be linked with risk of T2DM. Our study provided novel insights of T2DM into genetics, molecular pathogenesis, and novel therapeutic targets.

Krüppel-like factors family regulation of adipogenic markers genes in bovine cattle adipogenesis

Intramuscular fat (IMF) content is a crucial determinant of meat quality traits in livestock. A network of transcription factors act in concert to regulate adipocyte formation and differentiation, which in turn influences intramuscular fat. Several genes and associated transcription factors have been reported to influence lipogenesis and adipogenesis during fetal and subsequent growth stage. Specifically in cattle, Krüppel-like factors (KLFs), which represents a family of transcription factors, have been reported to be involved in adipogenic differentiation and development. KLFs are a relatively large group of zinc-finger transcription factors that have a variety of functions in addition to adipogenesis. In mammals, the participation of KLFs in cell development and differentiation is well known. Specifically in the context of adipogenesis, KLFs function either as positive (KLF4, KLF5, KLF6, KLF8, KLF9, KLF10, KLF11, KLF12, KLF13, KLF14 and KLF15) or negative organizers (KLF2, KLF3 and KLF7), by a variety of different mechanisms such as crosstalk with C/EBP and PPARγ. In this review, we aim to summarize the potential functions of KLFs in regulating adipogenesis and associated pathways in cattle. Furthermore, the function of known bovine adipogenic marker genes, and associated transcription factors that regulate the expression of these marker genes is also summarized. Overall, this review will provide an overview of marker genes known to influence bovine adipogenesis and regulation of expression of these genes, to provide insights into leveraging these genes and transcription factors to enhance breeding programs, especially in the context of IMF deposition and meat quality.

Perspectives and challenges of epigenetic determinants of childhood obesity: A systematic review

The tremendous increase in childhood obesity prevalence over the last few decades cannot merely be explained by genetics and evolutionary changes in the genome, implying that gene-environment interactions, such as epigenetic modifications, likely play a major role. This systematic review aims to summarize the evidence of the association between epigenetics and childhood obesity. A literature search was performed via PubMed and Scopus engines using a combination of terms related to epigenetics and pediatric obesity. Articles studying the association between epigenetic mechanisms (including DNA methylation and hydroxymethylation, non-coding RNAs, and chromatin and histones modification) and obesity and/or overweight (or any related anthropometric parameters) in children (0-18 years) were included. The risk of bias was assessed with a modified Newcastle-Ottawa scale for non-randomized studies. One hundred twenty-one studies explored epigenetic changes related to childhood obesity. DNA methylation was the most widely investigated mechanism (N = 101 studies), followed by non-coding RNAs (N = 19 studies) with evidence suggestive of an association with childhood obesity for DNA methylation of specific genes and microRNAs (miRNAs). One study, focusing on histones modification, was identified. Heterogeneity of findings may have hindered more insights into the epigenetic changes related to childhood obesity. Gaps and challenges that future research should face are herein described.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

Insights into the multifactorial causation of obesity by integrated genetic and epigenetic analysis

Obesity is a highly heritable multifactorial disease that places an enormous burden on human health. Its increasing prevalence and the concomitant-reduced life expectancy has intensified the search for new analytical methods that can reduce the knowledge gap between genetic susceptibility and functional consequences of the disease pathology. Although the influence of genetics and epigenetics has been studied independently in the past, there is increasing evidence that genetic variants interact with environmental factors through epigenetic regulation. This suggests that a combined analysis of genetic and epigenetic variation may be more effective in characterizing the obesity phenotype. To date, limited genome-wide integrative analyses have been performed. In this review, we provide an overview of the latest findings, advantages, and challenges and discuss future perspectives.

The association of genetically controlled CpG methylation (cg158269415) of protein tyrosine phosphatase, receptor type N2 (PTPRN2) with childhood obesity

Protein tyrosine phosphatase, receptor type N2 (PTPRN2) encodes a major islet autoantigen in type-1 diabetes. Previous genetic studies have shown its significant association with obesity. PTPRN2 plays an important role in epigenetic regulation of metabolic diseases and cancers. We investigated CpG methylations (cg17429772 and cg158269415) in PTPRN2 by pyrosequencing from blood samples of childhood obesity (n = 638). cg158269415 had significant positive correlations with body mass index (BMI) and waist-hip ratio (WHR). Case-control analysis showed that cg158269415 methylation in blood sample was significantly more hypermethylated in obese cases (n = 252), an average of 2.93% more than that that in controls (n = 386). The cg158269415 methylation has a trimodal distribution pattern with strong dependency on nearby located rs1670344 G > A genotype. Correlations of cg158269415 with BMI and WHR were significant and strong in major G allele carriers (GG + GA). Our study showed that an epigenetic association of PTPRN2 gene with childhood obesity was under certain genetic background. The genetic and epigenetic interplay of PTPRN2 gene may implicate a mechanism of childhood obesity. Whether these small changes in DNA methylation from whole blood are causally or consequently related to childhood obesity outcome and their clinical relevance remains to be determined. However, this study presents a promising obesity risk marker that warrants further investigation.

Making Sense of the Epigenome Using Data Integration Approaches

Epigenetic research involves examining the mitotically heritable processes that regulate gene expression, independent of changes in the DNA sequence. Recent technical advances such as whole-genome bisulfite sequencing and affordable epigenomic array-based technologies, allow researchers to measure epigenetic profiles of large cohorts at a genome-wide level, generating comprehensive high-dimensional datasets that may contain important information for disease development and treatment opportunities. The epigenomic profile for a certain disease is often a result of the complex interplay between multiple genetic and environmental factors, which poses an enormous challenge to visualize and interpret these data. Furthermore, due to the dynamic nature of the epigenome, it is critical to determine causal relationships from the many correlated associations. In this review we provide an overview of recent data analysis approaches to integrate various omics layers to understand epigenetic mechanisms of complex diseases, such as obesity and cancer. We discuss the following topics: (i) advantages and limitations of major epigenetic profiling techniques, (ii) resources for standardization, annotation and harmonization of epigenetic data, and (iii) statistical methods and machine learning methods for establishing data-driven hypotheses of key regulatory mechanisms. Finally, we discuss the future directions for data integration that shall facilitate the discovery of epigenetic-based biomarkers and therapies.

The genetic and epigenetic association of LDL Receptor Related Protein 1B (LRP1B) gene with childhood obesity

Low-density lipoprotein Receptor Related Protein 1B (LRP1B) is homologous to the gigantic lipoprotein receptor-related protein 1 that belongs to the family of Low-density lipoprotein receptors. Previous genetic association studies of the LRP1B gene have shown its genetic association with obesity. Through exome sequencing of the LRP1B gene from a childhood severe obesity cohort (n = 692), we found novel single nucleotide polymorphism (rs431809) in intron 4, which has been significantly correlated with both body mass index (BMI) and waist-hip-ratio (WHR). Three methylations of CpG sites (cg141441481, cg01852095 and cg141441470) in the same intron were also significantly correlated with BMI and WHR. All CpG methylations had bimodal patterns, and were dependent on rs431809 genotypes. The genetic influences of obesity on the LRP1B gene may be linked to the interplay of CpG methylations in the same intron. Heritability of SNP interacts with epigenetic crosstalk in LRP1B. Genetic and epigenetic crosstalk of LRP1B gene may be implicated in the prevention and therapeutic approach to childhood obesity.

The Krüppel-Like Factors and Control of Energy Homeostasis

Nutrient handling by higher organisms is a complex process that is regulated at the transcriptional level. Studies over the past 15 years have highlighted the critical importance of a family of transcriptional regulators termed the Krüppel-like factors (KLFs) in metabolism. Within an organ, distinct KLFs direct networks of metabolic gene targets to achieve specialized functions. This regulation is often orchestrated in concert with recruitment of tissue-specific transcriptional regulators, particularly members of the nuclear receptor family. Upon nutrient entry into the intestine, gut, and liver, KLFs control a range of functions from bile synthesis to intestinal stem cell maintenance to effect nutrient acquisition. Subsequently, coordinated KLF activity across multiple organs distributes nutrients to sites of storage or liberates them for use in response to changes in nutrient status. Finally, in energy-consuming organs like cardiac and skeletal muscle, KLFs tune local metabolic programs to precisely match substrate uptake, flux, and use, particularly via mitochondrial function, with energetic demand; this is achieved in part via circulating mediators, including glucocorticoids and insulin. Here, we summarize current understanding of KLFs in regulation of nutrient absorption, interorgan circulation, and tissue-specific use.

Using Integrative Analysis of DNA Methylation and Gene Expression Data in Multiple Tissue Types to Prioritize Candidate Genes for Drug Development in Obesity

Obesity has become a major public health issue which is caused by a combination of genetic and environmental factors. Genome-wide DNA methylation studies have identified that DNA methylation at Cytosine-phosphate-Guanine (CpG) sites are associated with obesity. However, subsequent functional validation of the results from these studies has been challenging given the high number of reported associations. In this study, we applied an integrative analysis approach, aiming to prioritize the drug development candidate genes from many associated CpGs. Association data was collected from previous genome-wide DNA methylation studies and combined using a sample-size-weighted strategy. Gene expression data in adipose tissues and enriched pathways of the affiliated genes were overlapped, to shortlist the associated CpGs. The CpGs with the most overlapping evidence were indicated as the most appropriate CpGs for future studies. Our results revealed that 119 CpGs were associated with obesity (p ≤ 1.03 × 10⁻⁷). Of the affiliated genes, SOCS3 was the only gene involved in all enriched pathways and was differentially expressed in both visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). In conclusion, our integrative analysis is an effective approach in highlighting the DNA methylation with the highest drug development relevance. SOCS3 may serve as a target for drug development of obesity and its complications.

Role of genetic and environmental factors in DNA methylation of lipid metabolism

A number of recent studies revealed that DNA methylation plays a central role in the regulation of lipid metabolism. DNA methylation modifications are important regulators of transcriptional networks that do not affect the DNA sequence and can translate genetic variants and environmental factors into phenotypic traits. Therefore, elucidating the factors that underlie inter-individual DNA methylation variations gives us an opportunity to predict diseases and interfere with the establishment of aberrant DNA methylation early. In this review, we summarize the findings of DNA methylation-related studies focused on unravelling the potential role of genetic and environmental factors in DNA methylation and the regulatory effect of DNA methylation on gene expression in lipid metabolism.

Positive correlation of cg16672562 methylation with obesity-related traits in childhood obesity, and its independence with underlying HIF3A (hypoxia-inducible factor 3a) genetic background

Differential methylations of the HIF3A (hypoxia-inducible factor 3a) gene have been linked to body mass index (BMI). To explore the association of these methylations to childhood obesity, we measured 5 CpG methylation sites (cg27146050, cg46801562, cg22891070, cg16672562 and cg46801675) in intron 1 of the HIF3A gene by pyrosequencing, in the Korean population (mean age: 13.9 yrs, 305 obese cases and 387 controls). Two CpG methylations, cg46801562 and cg16672562, had statistically significant association with childhood obesity (P = 2.09E-9 and 1.66E-7, respectively). Notably, in the case of cg16672562, all correlations were significantly positive with BMI (beta = 0.285, P = 1.652E-13), waist-hip ratio (beta = 0.0028, P = 1.42E-15) and fasting plasma glucose level (beta = 0.0645, P = 2.61E-4), when analyzed by linear regression, with age and sex as covariates. We investigated any genetic effect of cg16672562 methylation by using 14 single nucleotide polymorphisms (SNP) identified by exome sequencing of the HIF3A locus cg16672562 methylation showed no statistically significant changes due to the 14 polymorphisms. In this study, we show that cg16672562 is the most significant blood DNA methylation marker for childhood obesity in the Korean population, and might be independent of any underlying HIF3A genetic background.