Polyunsaturated Fatty Acids Modulate the Association between PIK3CA-KCNMB3 Genetic Variants and Insulin Resistance

Genotype-based precision nutrition strategies for the prediction and clinical management of type 2 diabetes mellitus

Globally, type 2 diabetes mellitus (T2DM) is one of the most common metabolic disorders. T2DM physiopathology is influenced by complex interrelationships between genetic, metabolic and lifestyle factors (including diet), which differ between populations and geographic regions. In fact, excessive consumptions of high fat/high sugar foods generally increase the risk of developing T2DM, whereas habitual intakes of plant-based healthy diets usually exert a protective effect. Moreover, genomic studies have allowed the characterization of sequence DNA variants across the human genome, some of which may affect gene expression and protein functions relevant for glucose homeostasis. This comprehensive literature review covers the impact of gene-diet interactions on T2DM susceptibility and disease progression, some of which have demonstrated a value as biomarkers of personal responses to certain nutritional interventions. Also, novel genotype-based dietary strategies have been developed for improving T2DM control in comparison to general lifestyle recommendations. Furthermore, progresses in other omics areas (epigenomics, metagenomics, proteomics, and metabolomics) are improving current understanding of genetic insights in T2DM clinical outcomes. Although more investigation is still needed, the analysis of the genetic make-up may help to decipher new paradigms in the pathophysiology of T2DM as well as offer further opportunities to personalize the screening, prevention, diagnosis, management, and prognosis of T2DM through precision nutrition.

PUFA, genotypes and risk for cardiovascular disease

Polyunsaturated fatty acids (PUFAs) are long chain fatty acids that are characterized by the presence of more than one double bond. These include fatty acids such as ꞷ-3-α-linolenic acid (ALA) and ꞷ-6 -linoleic acid (LA) which can only be obtained from dietary sources and are therefore termed essential fatty acids. They contain the building blocks for dihomo-γ-linolenic acid and arachidonic acid in the ꞷ-6 family as well as eicosapentaenoic acid and docosahexaenoic acid in the ꞷ-3 family. Both ALA and LA are important constituents of animal and plant cell membranes and are important components of anti-inflammatory and pro-inflammatory hormones and therefore, often modulate cellular immunity under chronic inflammatory states. The variation in physiological PUFA levels is under significant genetic influence, the fatty acid desaturase (FADS) genes being key regulators of PUFA metabolism. These genetic variants have been shown to alter fatty acid metabolism and influence the onset and progression of various metabolic conditions. This detailed review discusses the role of PUFAs, diet and genotypes in risk for cardiovascular diseases.

Genome-wide interaction study reveals epistatic interactions for beef lipid-related traits in Nellore cattle

Gene-gene interactions cause hidden genetic variation in natural populations and could be responsible for the lack of replication that is typically observed in complex traits studies. This study aimed to identify gene-gene interactions using the empirical Hilbert-Schmidt Independence Criterion method to test for epistasis in beef fatty acid profile traits of Nellore cattle. The dataset contained records from 963 bulls, genotyped using a 777 962k SNP chip. Meat samples of Longissimus muscle, were taken to measure fatty acid composition, which was quantified by gas chromatography. We chose to work with the sums of saturated (SFA), monounsaturated (MUFA), polyunsaturated (PUFA), omega-3 (OM3), omega-6 (OM6), SFA:PUFA and OM3:OM6 fatty acid ratios. The SNPs in the interactions where P < 10 - 8 were mapped individually and used to search for candidate genes. Totals of 602, 3, 13, 23, 13, 215 and 169 candidate genes for SFAs, MUFAs, PUFAs, OM3s, OM6s and SFA:PUFA and OM3:OM6 ratios were identified respectively. The candidate genes found were associated with cholesterol, lipid regulation, low-density lipoprotein receptors, feed efficiency and inflammatory response. Enrichment analysis revealed 57 significant GO and 18 KEGG terms ( P < 0.05), most of them related to meat quality and complementary terms. Our results showed substantial genetic interactions associated with lipid profile, meat quality, carcass and feed efficiency traits for the first time in Nellore cattle. The knowledge of these SNP-SNP interactions could improve understanding of the genetic and physiological mechanisms that contribute to lipid-related traits and improve human health by the selection of healthier meat products.

Machine Learning Analysis of Longevity-Associated Gene Expression Landscapes in Mammals

One of the important questions in aging research is how differences in transcriptomics are associated with the longevity of various species. Unfortunately, at the level of individual genes, the links between expression in different organs and maximum lifespan (MLS) are yet to be fully understood. Analyses are complicated further by the fact that MLS is highly associated with other confounding factors (metabolic rate, gestation period, body mass, etc.) and that linear models may be limiting. Using gene expression from 41 mammalian species, across five organs, we constructed gene-centric regression models associating gene expression with MLS and other species traits. Additionally, we used SHapley Additive exPlanations and Bayesian networks to investigate the non-linear nature of the interrelations between the genes predicted to be determinants of species MLS. Our results revealed that expression patterns correlate with MLS, some across organs, and others in an organ-specific manner. The combination of methods employed revealed gene signatures formed by only a few genes that are highly predictive towards MLS, which could be used to identify novel longevity regulator candidates in mammals.

Regulation of BK Channels by Beta and Gamma Subunits

Ca²⁺- and voltage-gated K⁺ channels of large conductance (BK channels) are expressed in a diverse variety of both excitable and inexcitable cells, with functional properties presumably uniquely calibrated for the cells in which they are found. Although some diversity in BK channel function, localization, and regulation apparently arises from cell-specific alternative splice variants of the single pore-forming α subunit ( KCa1.1, Kcnma1, Slo1) gene, two families of regulatory subunits, β and γ, define BK channels that span a diverse range of functional properties. We are just beginning to unravel the cell-specific, physiological roles served by BK channels of different subunit composition.

Regulation of BK Channels by Beta and Gamma Subunits

Ca²⁺- and voltage-gated K⁺ channels of large conductance (BK channels) are expressed in a diverse variety of both excitable and inexcitable cells, with functional properties presumably uniquely calibrated for the cells in which they are found. Although some diversity in BK channel function, localization, and regulation apparently arises from cell-specific alternative splice variants of the single pore-forming α subunit ( KCa1.1, Kcnma1, Slo1) gene, two families of regulatory subunits, β and γ, define BK channels that span a diverse range of functional properties. We are just beginning to unravel the cell-specific, physiological roles served by BK channels of different subunit composition.

Dietary Fatty Acids and the Metabolic Syndrome: A Personalized Nutrition Approach

Dietary fatty acids are present in a wide variety of foods and appear in different forms and lengths. The different fatty acids are known to have various effects on metabolic health. The metabolic syndrome (MetS) is a constellation of risk factors of chronic diseases. The etiology of the MetS is represented by a complex interplay of genetic and environmental factors. Dietary fatty acids can be important contributors of the evolution or in prevention of the MetS; however, great interindividual variability exists in the response to fatty acids. The identification of genetic variants interacting with fatty acids might explain this heterogeneity in metabolic responses. This chapter reviews the mechanisms underlying the interactions between the different components of the MetS, dietary fatty acids and genes. Challenges surrounding the implementation of personalized nutrition are also covered.

FOXO transcription factors at the interface of metabolism and cancer

Diabetes refers to a group of metabolic diseases characterized by impaired insulin signalling and high blood glucose. A growing body of epidemiological evidence links diabetes to several types of cancer but the underlying molecular mechanisms are poorly understood. The signalling cascade connecting insulin and FOXO proteins provides a compelling example for a conserved pathway at the interface between insulin signalling and cancer. FOXOs are transcription factors that orchestrate programs of gene expression known to control a variety of processes in response to cellular stress. Genes regulated by this family of proteins are involved in the regulation of cellular energy production, oxidative stress resistance and cell viability and proliferation. Accordingly, FOXO factors have been shown to play an important role in the suppression of tumour growth and in the regulation of metabolic homeostasis. There is emerging evidence that deregulation of FOXO factors might account for the association between insulin resistance-related metabolic disorders and cancer.