Abstract: Background: Obesity results from complex interactions between genetic susceptibility to weight gain and poor eating and lifestyle behaviors. The approach that has been traditionally used in genetics to investigate gene-environment/lifestyle interaction in obesity is based on the concept of moderation, or effect modification. Another approach called mediation analysis can be used to investigate gene-environment interaction in obesity. The objective of this review article is to explain the differences between the concepts of moderation and mediation and summarize the studies that have used mediation analysis to support the role of eating or lifestyle behaviors as putative mediators of genetic susceptibility to obesity.Summary: Moderation is used to determine whether the effect of an exposure (genes associated with obesity) on an outcome (obesity phenotype) differs in magnitude and/or direction across the spectrum of environmental exposure. Mediation analysis is used to assess the extent to which the effect of the exposure on the outcome is explained by a given set of hypothesized mediators with the aim of understanding how the exposure could lead to the outcome. In comparison with moderation, relatively few studies used mediation analyses to investigate gene-environment in obesity. Most studies found evidence that traits related to appetite or eating behaviors partly mediated genetic susceptibility to obesity in either children or adults. Key messages: Moderation and mediation represent two complementary approaches to investigate gene-environment interaction in obesity and address different research questions pertaining to the cause-effect relationship between genetic susceptibility to obesity and various obesity outcomes. More studies relying on mediation are needed to better understand the role eating and lifestyle habits in mediating genetic susceptibility to obesity.
Abstract: Introduction: microRNA (miRNA) profiles have been shown to change after intake of dairy products. Dysregulation of miRNA is associated with the changes in the level of glycemic parameters. The objectives are 1- to investigate miRNAs expression after consumption of dairy products; and 2- to study the association between miRNAs and glycemic profile among individuals with hyperinsulinemia. Methods: In crossover design, 24 participants were randomized into 2 phases: high-dairy (HD) (≥4 servings / day according to the Canadian Food Guide (2007)) and adequate-dairy (AD) (≤2 servings / day) over 6-week. First, miRNAs were extracted from a pooled plasma sample of 10 subjects after HD and AD intervention which analyzed in duplicate by array hybridization (Affymetrix Gene Chip miRNA Array v. 4.0). Secondly, 6 miRNAs related to type 2 diabetes (T2D) were validated by qRT-PCR from plasma of 24 participants. Results: Microarray analysis indicated that 237 miRNAs expressed differentially (FC ≥ ±1.2; p value < 0.05)) between AD and HD. Among pooled miRNAs, the level of selected miRNAs, including miR-652-3p, miR-106b-5p, miR-93-5p, and miR-107 were down-regulated; conversely, miR-223-3p and miR-122-5p were up-regulated. After qRT-PCR validation, only the expression level of miR-106-5p increased after HD compared to AD (p = 0.02). After AD intervention, the level of fasting plasma glucose (FPG) and insulin, HOMA-IR were negatively correlated with miR-122-5p. Similarly, negative correlation was found between miR-106-5p and FPG. Conclusion: The miRNAs profile was modified after HD compared to AD and this may have role in modifying the risk of T2D (Registration number: NCT02961179)
Abstract: Introduction: The oral cavity is home to a diverse and distinct microbiome. While the role of oral bacteria in cariogenic and other dental diseases is irrefutable, their beneficial effects in the form of probiotics (PB) has been less studied, especially pertaining to oral diseases in children. This study compares the efficacy of a PB mouthrinse with 0.12% chlorhexidine (CHX) and 0.05% sodium fluoride (NaF) mouthrinse on the colony counts of mutans streptococci (MS) in children. Methods: A triple-blind crossover randomized trial between interventional groups was planned. Fifty-one children between 8 to 12 years of age were divided into three groups (I, II, and III) and were exposed to all three mouthrinses (A, B, and C) by randomized allocation for a period of two weeks with an inter-phase washout period of four weeks. Pre- and post-interventional MS counts (CFU/mL) were assessed, and the mean change was analysed using the t test (intragroup) and ANOVA (intergroup and crossover). Results: The mean changes in the colony counts obtained with the use of PB, CHX, and NaF mouthrinses were −1.0223 (−1.2201 to −0.8246), −0.9564 (−1.1503 to −0.7626), and −0.9511 (−1.1554 to −0.7467), respectively, which were statistically significant (p #x3c; 0.0001). However, the intergroup comparison for the mean change in colony counts revealed no statistically significant differences (p #x3e; 0.05). Conclusion: The study concluded that the PB mouthrinse was equally efficacious as compared to CHX and NaF mouthrinses against MS in 8- to 12-year-old children. However, further studies are recommended to strengthen the evidence. Lifestyle Genomics PubDate: Wed, 12 Jan 2022 07:56:21 +010
Abstract: Introduction: Cataracts are associated with the accumulation of galactose and galactitol in the lens. We determined the polygenetic risk scores for the best model(PRSBM) associated with age-related cataract(ARC) risk and their interaction with diets and lifestyles in 40,262 Korean adults aged over 50 years belonged to a hospital-based city cohort. Methods: The genetic variants for ARC risk were selected in lactose and galactose metabolism-related genes with multivariate logistic regression using the PLINK 1.9 version. PRSBM from the selected genetic variants was estimated by generalized multifactor dimensionality reduction (GMDR) after adjusting covariates. The interactions between the PRSBM and each lifestyle factor were determined to modulate ARC risk. Results: The genetic variants for ARC risk related to lactose- and galactose metabolism were SLC2A1_rs3729548, ST3GAL3_rs3791047, LCT_rs2304371, GALNT5_rs6728956, ST6GAL1_rs2268536, GALNT17_rs17058752, CSGALNACT1_rs1994788, GALNTL4_rs10831608, B4GALT6_rs1667288, and A4GALT_ rs9623659. In GMDR, the best model included all ten genetic variants. The highest odds ratio (OR) for a single SNP in the PRSBM was 1.26. However, subjects with a high-PRSBM had a higher ARC risk by 2.1-fold than a low-PRSBM after adjusting for covariates. Carbohydrate, dairy products, kimchi, and alcohol intake interacted with PRSBM for ARC risk: the participants with high-PRSBM had a much higher ARC risk than those with low-PRSBM when consuming diets with high carbohydrate and low dairy product and kimchi intake. However, only with low alcohol intake, the participants with high-PRSBM had a higher ARC risk than those with low-PRSBM. Conclusion: Adults aged >50 years having high-PRSBM may modulate dietary habits to reduce ARC risk.
Abstract: Introduction:APOE ɛ4 allele predisposes to high cholesterol and increases the risk for lifestyle-related diseases such as Alzheimer’s disease (AD) and cardiovascular diseases (CVD). The aim of this study was to analyse interrelationships of APOE genotypes with lipid metabolism and lifestyle factors in middle-aged Finns among whom the CVD risk factors are common.Methods:Participants (n=211) were analysed for APOE ε genotypes, physiological parameters and health- and diet-related plasma markers. Lifestyle choices were determined by a questionnaire.Results:APOE genotypes ε3/ε4 and ε4/ε4 (ε4 group) represented 34.1% of the participants. Genotype ε3/ε3 (ε3 group) frequency was 54.5%. Carriers of ε2 (ε2 group; ε2/ε2, ε2/ε3 and ε2/ε4) represented 11.4%; 1.9 % were of the genotype ε2/ε4. The LDL and total cholesterol levels were lower (P PubDate: Thu, 23 Dec 2021 14:29:35 +010
Abstract: Background: “Quantile-dependent expressivity” is a dependence of genetic effects on whether the phenotype (e.g., insulin resistance) is high or low relative to its distribution. Methods: Quantile-specific offspring-parent regression slopes (βOP) were estimated by quantile regression for fasting glucose concentrations in 6,453 offspring-parent pairs from the Framingham Heart Study. Results: Quantile-specific heritability (h2), estimated by 2βOP/(1 + rspouse), increased 0.0045 ± 0.0007 (p = 8.8 × 10−14) for each 1% increment in the fasting glucose distribution, that is, h2 ± SE were 0.057 ± 0.021, 0.095 ± 0.024, 0.146 ± 0.019, 0.293 ± 0.038, and 0.456 ± 0.061 at the 10th, 25th, 50th, 75th, and 90th percentiles of the fasting glucose distribution, respectively. Significant increases in quantile-specific heritability were also suggested for fasting insulin (p = 1.2 × 10−6), homeostatic model assessment of insulin resistance (HOMA-IR, p = 5.3 × 10−5), insulin/glucose ratio (p = 3.9 × 10−5), proinsulin (p = 1.4 × 10−6), proinsulin/insulin ratio (p = 2.7 × 10−5), and glucose concentrations during a glucose tolerance test (p = 0.001), and their logarithmically transformed values. Discussion/Conclusion: These findings suggest alternative interpretations to precision medicine and gene-environment interactions, including alternative interpretation of reported synergisms between ACE, ADRB3, PPAR-γ2, and TNF-α polymorphisms and being born small for gestational age on adult insulin resistance (fetal origin theory), and gene-adiposity (APOE, ENPP1, GCKR, IGF2BP2, IL-6, IRS-1, KIAA0280, LEPR, MFHAS1, RETN, TCF7L2), gene-exercise (INS), gene-diet (ACSL1, ELOVL6, IRS-1, PLIN, S100A9), and gene-socioeconomic interactions. Lifestyle Genomics PubDate: Mon, 06 Dec 2021 14:31:20 +010
Abstract: Background: For thousands of years, disabilities due to nutrient deficiencies have plagued humanity. Rickets, scurvy, anemia, stunted growth, blindness, and mental handicaps due to nutrient deficiencies affected up to 1/10 of the world’s population prior to 1900. The discovery of essential amino acids, vitamins, and minerals, in the early 1900s, led to a fundamental change in our understanding of food and a revolution in human health. Widespread vitamin and mineral supplementation, the development of recommended dietary allowances, and the implementation of food labeling and testing along with significant improvements in food production and food quality have meant that nutrient-related disorders have almost vanished in the developed world. The success of nutritional science in preventing disease at a population-wide level is one of the great scientific triumphs of the 20th century. The challenge for nutritional science in the 21st century is to understand how to use nutrients and other food constituents to enhance human health or prevent disease at a more personal level. This is the primary goal of precision nutrition. Summary: Precision nutrition is an emerging branch of nutrition science that aims to use modern omics technologies (genomics, proteomics, and metabolomics) to assess an individual’s response to specific foods or dietary patterns and thereby determine the most effective diet or lifestyle interventions to prevent or treat specific diseases in that individual. Metabolomics is vital to nearly every aspect of precision nutrition. It can be used to comprehensively characterize the thousands of chemicals in foods, to identify food byproducts in human biofluids or tissues, to characterize nutrient deficiencies or excesses, to monitor biochemical responses to dietary interventions, to track long-term or short-term dietary habits, and to guide the development of nutritional therapies. In this review, we will describe how metabolomics has been used to advance the field of precision nutrition by providing some notable examples or use cases. First, we will describe how metabolomics helped launch the field of precision nutrition through the diagnosis and dietary therapy of individuals with inborn errors of metabolism. Next, we will describe how metabolomics is being used to comprehensively characterize the full chemical complexity of many key foods, and how this is revealing much more about nutrients than ever imagined. Third, we will describe how metabolomics is being used to identify food consumption biomarkers and how this opens the door to a more objective and quantitative assessments of an individual’s diet and their response to certain foods. Finally, we will describe how metabolomics is being coupled with other omics technologies to develop custom diets and lifestyle interventions that are leading to positive health benefits. Key Message: Metabolomics is vital to the advancement of nutritional science and in making the dream of precision nutrition a reality. Lifestyle Genomics PubDate: Wed, 08 Sep 2021 14:13:54 +020
Abstract: Introduction: Type 2 diabetes (T2D) is a leading cause of global mortality with diet and genetics being considered amongst the most significant risk factors. Recently, studies have identified a single polymorphism of the TCF7L2 gene (rs7903146) as the most important genetic contributor. However, no studies have explored this factor in a healthy population and using glycated haemoglobin (HbA1c), which is a reliable long-term indicator of glucose management. This study investigates the association of the genetic polymorphism rs7903146 and dietary intake with T2D risk in a population free of metabolic disease. Methods: T2D risk was assessed using HbA1c plasma concentrations and dietary intake via a validated Food Frequency Questionnaire in 70 healthy participants. Results: T allele carriers had higher HbA1c levels than the CC group (32.4 ± 7.2 mmol/mol vs. 30.3 ± 7.6 mmol/mol, p = 0.005). Multiple regression reported associations between diet, genotype and HbA1c levels accounting for 37.1% of the variance in HbA1c (adj. R2 = 0.371, p #x3c; 0.001). The following macronutrients, expressed as a median percentage of total energy intake (TEI) in the risk group, were positively associated with HbA1c concentration: carbohydrate (≥39% TEI, p #x3c; 0.005; 95% CI 0.030/0.130) protein (≥21% TEI, p #x3c; 0.005, 95% CI 0.034/0.141), monounsaturated (≥15% TEI p #x3c; 0.05, 95% CI 0.006/0.163) and saturated fatty acids (≥13% TEI; p #x3c; 0.05, 95% CI 0.036/0.188). Conclusion: Carriers of the T allele showed significantly higher levels of HbA1c compared to non-carriers. Dietary intake affected T2D risk to a greater extent than genetic effects of TCF7L2rs7903146 genotype in a healthy population. The study focus on healthy individuals is beneficial due to the applicability of findings for T2D screening. Lifestyle Genomics PubDate: Thu, 12 Aug 2021 11:31:25 +020
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