Precision nutrition based on phenotypical traits and the (epi)genotype: nutrigenetic and nutrigenomic approaches for obesity care

PURPOSE OF REVIEW

The purpose of this article is to rationally review and critically appraise the current knowledge in the most relevant nongenetic and genetic factors influencing obesity predisposition. This information may be translated into the implementation of personalized nutrition approaches involving precision nutrigenetic and nutrigenomic strategies for obesity monitoring and weight management.

RECENT FINDINGS

The importance and influence of several nongenetic contributors to obesity onset and individual responses to weight-loss interventions have been highlighted including the role of age, sex or perinatal feeding and others related to an individual's lifestyle and modifiable. Nutrigenetic studies have analysed potential interactions between polymorphisms influencing energy homeostasis/body composition and dietary factors in relation to adiposity phenotypes and therapy responsiveness. A second approach comprises the Nutrigenomic analysis of gene expression modifications in response to the consumption of specific nutrients or dietary bioactive compounds, which may involve epigenetic mechanisms including deoxyribonucleic acid methylation and micro-ribonucleic acid expression profiles.

SUMMARY

Taken together, these findings encompass the importance of taking into account up-to-date advances in Nutrigenetic and Nutrigenomic hallmarks, globally analysing the risk of weight gain and related outcomes after following nutrition counselling, this contributing to improve obesity care considering phenotypical traits and the genetic make-up for precision obesity care.

[Evolution of patients infected with SARS-CoV-2 according to previous metabolic status]

INTRODUCTION

coronavirus disease 2019 (COVID-19) encompasses a wide spectrum of symptoms, including respiratory, gastrointestinal, hematological, and dermatological manifestations. The virus interaction with cells located in the respiratory tract causes the release of inflammatory mediators, whose involvement could be exacerbated by co-existing obesity, diabetes, and cardiovascular events.

OBJECTIVES

the objective of this research was to analyze the clinically metabolic status in patients who have suffered COVID-19 disease in order to predict the outcome.

METHODS

this research is a retrospective study based on a cohort of 165 consecutively admitted patients with criteria for COVID-19 pneumonia according to WHO guidelines at the Hospital Universitario Puerta de Hierro between March and April 2020. Recorded variables included demographic and epidemiological data plus diagnoses as well as morbid complications during hospitalization. The Biochemistry Unit Laboratory carried out laboratory analyses according to validated operational procedures. The statistical tests included univariate and multivariate models adjusted for baseline characteristics and clinically relevant features.

RESULTS

the most frequent comorbidity in our cohort was arterial hypertension (44.0 %), followed by dyslipidemia (32.1 %), obesity (30.9 %), and diabetes mellitus (20.0 %). The association between admission to the intensive care unit (ICU) with body mass index (BMI) in a multivariate model was statistically significant, evidencing that obese subjects (BMI ≥ 30 kg/m2) have a 19 % higher risk of requiring ICU care. The univariate model revealed a statistically significant association between obesity and ICU admission and length of hospital stay (p < 0.05). The relationship between baseline blood glucose and in-hospital mortality was also statistically significant (p = 0.03), as well as with total cholesterol and ICU admission (p = 0.007).

CONCLUSIONS

obesity is related to a longer time of hospitalization and a higher rate of admissions to the ICU. Low total cholesterol levels and abnormal baseline blood glucose were risk factors for ICU requirement and in-hospital mortality. Patient categorization based on obesity could be valuable in the development of a precision medicine model within the COVID-19 pandemic.

Impact of Spirulina maxima Intake and Exercise (SIE) on Metabolic and Fitness Parameters in Sedentary Older Adults with Excessive Body Mass: Study Protocol of a Randomized Controlled Trial

Life expectancy has increased unprecedentedly in recent decades, benefiting the longevity of the world's population. The most frequent pathological conditions presented in this age group include excessive body fat, frailty, and hypercholesterolemia. These pathological characteristics condition general health and autonomy in adults to carry out their usual activities. In this sense, the search for a healthy lifestyle is necessary, consisting in a healthy diet that includes supplementation with nutraceuticals and the daily practice of physical activity. This study protocol aims to evaluate the independent and synergistic effect of 12 weeks of Spirulina maxima intake (5 g/day), with or without an exercise program on metabolic and fitness parameters of 52 sedentary older adults with excessive body mass in a double-blind, randomized, crossover, controlled trial design. The main findings from this trial will provide novel evidence for future interventions designed for the elderly population and the result will be disseminated through peer-reviewed journals and international meetings. ClinicalTrials.gov identification number: NCT04658875 (Effect of Spirulina maxima and Exercise on General Fitness and Blood Lipids in Older Adults).

Impact of APOE Alleles-by-Diet Interactions on Glycemic and Lipid Features- A Cross-Sectional Study of a Cohort of Type 2 Diabetes Patients from Western Mexico: Implications for Personalized Medicine

Purpose

To analyze clinically relevant interactions between the apolipoprotein E (APOE) ε2, ε3 and ε4 alleles and nutritional factors on glycemic control and lipid levels in a cohort of type 2 diabetes (T2D) patients from western Mexico.

Patients and Methods

In this cross-sectional study of the cohort of T2D patients, a total of 224 individuals were selected for interaction studies. Clinical and anthropometric data were obtained from pre-designed medical records. Dietary intake was assessed by validated three-day food consumption records. Biochemical measurements were determined by automated methods. APOE genotyping was performed by a real-time allelic discrimination assay. Gene–diet interactions were tested by corrected multiple linear regression analyses, which were adjusted by potential confounding factors such as age, sex, energy intake, BMI and anti-hyperglycemic therapy (Metformin, Glibenclamide or Insulin), and years with T2D.

Results

Seventy-six percent of patients with T2D were on Metformin therapy. The frequencies of the APOE alleles were ε2 (5.8%), ε3 (74.1%) and ε4 (20.1%). After statistical settings, significant APOE alleles-by-diet interactions in relation to the metabolic profile were found. Interestingly, higher blood levels of total cholesterol (p int. = 0.016), non-HDL-c (p int. = 0.024), and LDL-c (p int. = 0.030) were found only in carriers of the APOE ε2 allele with a low consumption of MUFA. In contrast, carriers of the APOE ε4 allele with a high ω-6:ω-3 PUFA ratio in the diet had higher %HbA1c blood concentrations (p int. = 0.035).

Conclusion

This study suggests a differential metabolic impact of APOE alleles on lipid/glycemic phenotypes depending on the dietary intake, with important potential implications in the personalized medicine and nutritional management of patients with type 2 diabetes mellitus.

Epigenetic signatures underlying inflammation: an interplay of nutrition, physical activity, metabolic diseases, and environmental factors for personalized nutrition

Aim and objective

Emerging translational evidence suggests that epigenetic alterations (DNA methylation, miRNA expression, and histone modifications) occur after external stimuli and may contribute to exacerbated inflammation and the risk of suffering several diseases including diabetes, cardiovascular diseases, cancer, and neurological disorders. This review summarizes the current knowledge about the harmful effects of high-fat/high-sugar diets, micronutrient deficiencies (folate, manganese, and carotenoids), obesity and associated complications, bacterial/viral infections, smoking, excessive alcohol consumption, sleep deprivation, chronic stress, air pollution, and chemical exposure on inflammation through epigenetic mechanisms. Additionally, the epigenetic phenomena underlying the anti-inflammatory potential of caloric restriction, n-3 PUFA, Mediterranean diet, vitamin D, zinc, polyphenols (i.e., resveratrol, gallic acid, epicatechin, luteolin, curcumin), and the role of systematic exercise are discussed.

Methods

Original and review articles encompassing epigenetics and inflammation were screened from major databases (including PubMed, Medline, Science Direct, Scopus, etc.) and analyzed for the writing of the review paper.

Conclusion

Although caution should be exercised, research on epigenetic mechanisms is contributing to understand pathological processes involving inflammatory responses, the prediction of disease risk based on the epigenotype, as well as the putative design of therapeutic interventions targeting the epigenome.

Antioxidant Lifestyle, Co-Morbidities and Quality of Life Empowerment Concerning Liver Fibrosis

The assessment of liver fibrosis has gained importance since the progression of non-alcoholic fatty liver disease (NAFLD). Indeed, the description of the association between undetected liver fibrosis and lifestyle in terms of antioxidant habits, comorbidity and quality of life (QoL) domains may help in the characterization of subjects with NAFLD. A cross-sectional evaluation of (n = 116) consecutive patients from an Internal Medicine ambulatory evaluation was performed. Demographic data, lifestyle, co-morbidity, QoL (according to the SF-36 index) and analytical values to calculate the oxidative related Fibrosis-4 (FIB-4) index were recorded. The association between FIB-4 and co-morbidity, antioxidant habits in QoL was assessed in univariate analysis (p < 0.05) and confirmed in multivariable analysis for 4 of the 8 SF-36 categories: Physical QoL, Physical role, Social QoL and General QoL, as well as in the Physical summary of SF-36 (p < 0.05). Finally, interactions were assessed between co-morbidity, FIB-4 and antioxidant habits showed in the prediction of mean SF-36 (p < 0.01). Liver fibrosis assessed by the oxidative surrogate index FIB-4 is associated with the interaction between antioxidant lifestyle, co-morbidity and physical, social and general aspects of QoL in apparent liver disease-free individuals, generating a proof of concept for health empowerment and personalized medicine.

Exploring Host Genetic Polymorphisms Involved in SARS-CoV Infection Outcomes: Implications for Personalized Medicine in COVID-19

Objective

To systematically explore genetic polymorphisms associated with the clinical outcomes in SARS-CoV infection in humans.

Methods

This comprehensive literature search comprised available English papers published in PubMed/Medline and SCOPUS databases following the PRISMA-P guidelines and PICO/AXIS criteria.

Results

Twenty-nine polymorphisms located in 21 genes were identified as associated with SARS-CoV susceptibility/resistance, disease severity, and clinical outcomes predominantly in Asian populations. Thus, genes implicated in key pathophysiological processes such as the mechanisms related to the entry of the virus into the cell and the antiviral immune/inflammatory responses were identified.

Conclusions

Although caution must be taken, the results of this systematic review suggest that multiple genetic polymorphisms are associated with SARS-CoV infection features by affecting virus pathogenesis and host immune response, which could have important applications for the study and understanding of genetics in SARS-CoV-2/COVID-19 and for personalized translational clinical practice depending on the population studied and associated environments.

DNA methylation in genes of longevity-regulating pathways: association with obesity and metabolic complications

Aging is the main risk factor for most chronic diseases. Epigenetic mechanisms, such as DNA methylation (DNAm) plays a pivotal role in the regulation of physiological responses that can vary along lifespan. The aim of this research was to analyze the association between leukocyte DNAm in genes involved in longevity and the occurrence of obesity and related metabolic alterations in an adult population. Subjects from the MENA cohort (n=474) were categorized according to age (<45 vs 45>) and the presence of metabolic alterations: increased waist circumference, hypercholesterolemia, insulin resistance, and metabolic syndrome. The methylation levels of 58 CpG sites located at genes involved in longevity-regulating pathways were strongly correlated (FDR-adjusted< 0.0001) with BMI. Fifteen of them were differentially methylated (p<0.05) between younger and older subjects that exhibited at least one metabolic alteration. Six of these CpG sites, located at MTOR (cg08862778), ULK1 (cg07199894), ADCY6 (cg11658986), IGF1R (cg01284192), CREB5 (cg11301281), and RELA (cg08128650), were common to the metabolic traits, and CREB5, RELA, and ULK1 were statistically associated with age. In summary, leukocyte DNAm levels of several CpG sites located at genes involved in longevity-regulating pathways were associated with obesity and metabolic syndrome traits, suggesting a role of DNAm in aging-related metabolic alterations.

Modeling of an integrative prototype based on genetic, phenotypic, and environmental information for personalized prescription of energy-restricted diets in overweight/obese subjects

BACKGROUND

Interindividual variability in weight loss and metabolic responses depends upon interactions between genetic, phenotypic, and environmental factors.

OBJECTIVE

We aimed to model an integrative (nutri) prototype based on genetic, phenotypic, and environmental information for the personalized prescription of energy-restricted diets with different macronutrient distribution.

METHODS

A 4-mo nutritional intervention was conducted in 305 overweight/obese volunteers involving 2 energy-restricted diets (30% restriction) with different macronutrient distribution: a moderately high-protein (MHP) diet (30% proteins, 30% lipids, and 40% carbohydrates) and a low-fat (LF) diet (22% lipids, 18% proteins, and 60% carbohydrates). A total of 201 subjects with good dietary adherence were genotyped for 95 single nucleotide polymorphisms (SNPs) related to energy homeostasis. Genotyping was performed by targeted next-generation sequencing. Two weighted genetic risk scores for the MHP (wGRS1) and LF (wGRS2) diets were computed using statistically relevant SNPs. Multiple linear regression models were performed to estimate percentage BMI decrease depending on the dietary macronutrient composition.

RESULTS

After energy restriction, both the MHP and LF diets induced similar significant decreases in adiposity, body composition, and blood pressure, and improved the lipid profile. Furthermore, statistically relevant differences in anthropometric and biochemical markers depending on sex and age were found. BMI decrease in the MHP diet was best predicted at ∼28% (optimism-corrected adjusted R2 = 0.279) by wGRS1 and age, whereas wGRS2 and baseline energy intake explained ∼29% (optimism-corrected adjusted R2 = 0.287) of BMI decrease variability in the LF diet. The incorporation of these predictive models into a decision algorithm allowed the personalized prescription of the MHP and LF diets.

CONCLUSIONS

Different genetic, phenotypic, and exogenous factors predict BMI decreases depending on the administration of a hypocaloric MHP diet or an LF diet. This holistic approach may help to personalize dietary advice for the management of excessive body weight using precision nutrition variables.This trial was registered at clinicaltrials.gov as NCT02737267.

Interplay of an Obesity-Based Genetic Risk Score with Dietary and Endocrine Factors on Insulin Resistance

This study aimed to nutrigenetically screen gene-diet and gene-metabolic interactions influencing insulin resistance (IR) phenotypes. A total of 232 obese or overweight adults were categorized by IR status: non-IR (HOMA-IR (homeostatic model assessment - insulin resistance) index ≤ 2.5) and IR (HOMA-IR index > 2.5). A weighted genetic risk score (wGRS) was constructed using 95 single nucleotide polymorphisms related to energy homeostasis, which were genotyped by a next generation sequencing system. Body composition, the metabolic profile and lifestyle variables were evaluated, where individuals with IR showed worse metabolic outcomes. Overall, 16 obesity-predisposing genetic variants were associated with IR (p < 0.10 in the multivariate model). The wGRS strongly associated with the HOMA-IR index (adj. R squared = 0.2705, p < 0.0001). Moreover, the wGRS positively interacted with dietary intake of cholesterol (P int. = 0.002), and with serum concentrations of C-reactive protein (P int. = 0.008) regarding IR status, whereas a negative interaction was found regarding adiponectin blood levels (P int. = 0.006). In conclusion, this study suggests that interactions between an adiposity-based wGRS with nutritional and metabolic/endocrine features influence IR phenotypes, which could facilitate the prescription of personalized nutrition recommendations for precision prevention and management of IR and diabetes.

Interactions between DRD2/ANKK1 TaqIA Polymorphism and Dietary Factors Influence Plasma Triglyceride Concentrations in Diabetic Patients from Western Mexico: A Cross-sectional Study

This study aimed to screen relevant interactions between DRD2/ANKK1 TaqIA polymorphism and dietary intakes with reference to phenotypical features in patients with T2D from western Mexico. In this cross-sectional study, a total of 175 T2D patients were enrolled. Dietary intake was evaluated using 3-day food records and appropriate software. Glycemic and blood lipid profiles were measured by standardized methods. Genotyping of the DRD2/ANKK1 TaqIA polymorphism was performed by the RFLP method. Gene-diet interactions regarding anthropometric and metabolic phenotypes were screened by adjusted multiple linear regression analyses. Genotype frequencies of the DRD2/ANKK1 TaqIA polymorphism were A1A1 (16.0%), A1A2 (52.6%), and A2A2 (31.4%). Statistically significant interactions between the DRD2/ANKK1 TaqIA genotypes and dietary factors in relation to blood triglyceride (TG) levels were found. Carriers of the A1 allele (A1A1 homozygotes plus A1A2 heterozygotes) were protected from TG increases by maltose intake (P int. = 0.023). Instead, A2A2 homozygotes were susceptible to TG rises through consumptions of total fat (P int. = 0.041), monounsaturated fatty acids (P int. = 0.001), and dietary cholesterol (P int. = 0.019). This study suggests that the interactions between DRD2/ANKK1 TaqIA polymorphism and dietary factors (sugar and fats) influence TG levels in diabetic patients.

Fatty acids, epigenetic mechanisms and chronic diseases: a systematic review

Background

Chronic illnesses like obesity, type 2 diabetes (T2D) and cardiovascular diseases, are worldwide major causes of morbidity and mortality. These pathological conditions involve interactions between environmental, genetic, and epigenetic factors. Recent advances in nutriepigenomics are contributing to clarify the role of some nutritional factors, including dietary fatty acids in gene expression regulation. This systematic review assesses currently available information concerning the role of the different fatty acids on epigenetic mechanisms that affect the development of chronic diseases or induce protective effects on metabolic alterations.

Methods

A targeted search was conducted in the PubMed/Medline databases using the keywords “fatty acids and epigenetic”. The data were analyzed according to the PRISMA-P guidelines.

Results

Consumption fatty acids like n-3 PUFA: EPA and DHA, and MUFA: oleic and palmitoleic acid was associated with an improvement of metabolic alterations. On the other hand, fatty acids that have been associated with the presence or development of obesity, T2D, pro-inflammatory profile, atherosclerosis and IR were n-6 PUFA, saturated fatty acids (stearic and palmitic), and trans fatty acids (elaidic), have been also linked with epigenetic changes.

Conclusions

Fatty acids can regulate gene expression by modifying epigenetic mechanisms and consequently result in positive or negative impacts on metabolic outcomes.

DRD2/ANKK1 TaqI A1 polymorphism associates with overconsumption of unhealthy foods and biochemical abnormalities in a Mexican population

PURPOSE

The dopamine receptor 2/ankyrin repeat domain and content kinase 1 (DRD2/ANKK1) TaqIA polymorphism (rs1800497) has been associated with rewarding behaviors. This study aimed to investigate the association of DRD2/ANKK1 TaqIA polymorphism with the dietary intake, the intake frequency of food groups and biochemical profile in Mexican mestizo subjects.

METHODS

A cross-sectional/analytical study with 276 Mexican subjects was performed. Dietary intake was assessed with a 24-h recall and a food frequency questionnaire (FFQ). An allelic discrimination assay evaluated DRD2/ANKK1 TaqIA genotypes. Anthropometric and biochemical data were evaluated.

RESULTS

Genotype frequencies were A1A1 (18.48%), A1A2 (45.29%) and A2A2 (36.23%). TaqI A1 allele carriers had a higher intake of carbohydrates (p = 0.038), meats (p = 0.005), fried dishes (p = 0.039), and sugars (p = 0.009). Male TaqI A1 carriers consumed more carbohydrates (p = 0.009) and meats (p = 0.018) while females consumed fewer legumes (p = 0.005). TaqI A1 carriers had glucose (p = 0.037) and triglycerides (p = 0.011) abnormalities. TaqI A1 was associated with higher risk of consumption of unhealthy foods such as fried dishes (OR 3.79, 95% CI 1.53-9.35, p = 0.002) and meats (OR 2.31, 95% CI 1.32-4.05, p = 0.003), and lower healthy foods (OR 1.89, 95% CI 1.04-3.29, p = 0.038). TaqI A1 allele was associated with risk of abnormal glucose, triglycerides, and VLDL levels (OR 2.148, 95% CI 1.068-4.322, p = 0.036; OR 1.999, 95% CI 1.194-3.348, p = 0.011; OR 2.021, 95% CI 1.203-3.392, p = 0.007), respectively.

CONCLUSIONS

The presence of the TaqI A1 allele in Mexicans is a genetic risk factor for detrimental dietary quality that may predispose to metabolic disturbances.

LEVEL OF EVIDENCE

Level III, case-control analytic study.

Epigenetic Modifications as Outcomes of Exercise Interventions Related to Specific Metabolic Alterations: A Systematic Review

BACKGROUND

Chronic diseases arise as a consequence of an unhealthy lifestyle primarily characterized by physical inactivity and unbalanced diets. Regular physical activity can improve health, and there is consistent evidence that these improvements may be the result of epigenetic modifications.

OBJECTIVE

To identify epigenetic modificationsas outcomes of exercise interventions related to specific metabolic alterations.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) methodology for manuscript research and preparation was followed using PubMed and EBSCO databases for literature review. Out of 2,638 articles identified, only 34 articles met the inclusion criteria.

RESULTS

The sections of the review were organized by metabolic alterations in which studies were grouped according to healthy, diseased, and trained individuals. Resistance exercise in humans induced epigenetic changes in pathways associated with energy metabolism and insulin sensitivity, contributing to healthy skeletal muscle. Endurance exercise also caused modifications in biomarkers associated to metabolic alterations through changes in DNA methylation and the expression of specific miRNAs. However, both resistance and endurance exercise are necessary to obtain a better physiological adaptation and a combination of both seems to be needed to properly tackle the increasing prevalence of non-communicable pathologies.

CONCLUSION

Given the heterogeneity and complexity of the existing literature, it is currently not possible to propose a specific recommendation about the type, intensity, or duration of exercise that could be beneficial for different subsets of the population (healthy, diseased, and/or trained). Nevertheless, this review highlights the importance of exercise for health and shows the need to perform more research in this emerging area to identify epigenetic biomarkers that could serve as indicators of exercise adaptations.

Models Integrating Genetic and Lifestyle Interactions on Two Adiposity Phenotypes for Personalized Prescription of Energy-Restricted Diets With Different Macronutrient Distribution

Aim: To analyze the influence of genetics and interactions with environmental factors on adiposity outcomes [waist circumference reduction (WCR) and total body fat loss (TFATL)] in response to energy-restricted diets in subjects with excessive body weight.

Materials and Methods: Two hypocaloric diets (30% energy restriction) were prescribed to overweight/obese subjects during 16 weeks, which had different targeted macronutrient distribution: a low-fat (LF) diet (22% energy from lipids) and a moderately high-protein (MHP) diet (30% energy from proteins). At the end of the trial, a total of 201 participants (LF diet = 105; MHP diet = 96) who presented good/regular dietary adherence were genotyped for 95 single nucleotide polymorphisms (SNPs) previously associated with weight loss through next-generation sequencing from oral samples. Four unweighted (uGRS) and four weighted (wGRS) genetic risk scores were computed using statistically relevant SNPs for each outcome by diet. Predictions of WCR and TFATL by diet were modeled through recognized multiple linear regression models including genetic (single SNPs, uGRS, and wGRS), phenotypic (age, sex, and WC, or TFAT at baseline), and environment variables (physical activity level and energy intake at baselines) as well as eventual interactions between genes and environmental factors.

Results: Overall, 26 different SNPs were associated with differential adiposity outcomes, 9 with WCR and 17 with TFATL, most of which were specific for each dietary intervention. In addition to conventional predictors (age, sex, lifestyle, and adiposity status at baseline), the calculated uGRS/wGRS and interactions with environmental factors were major contributors of adiposity responses. Thus, variances in TFATL-LF diet, TFATL-MHP diet, WCR-LF diet, and WCR-MHP diet were predicted by approximately 38% (optimism-corrected adj. R² = 0.3792), 32% (optimism-corrected adj. R² = 0.3208), 22% (optimism-corrected adj. R² = 0.2208), and 21% (optimism-corrected adj. R² = 0.2081), respectively.

Conclusions: Different genetic variants and interactions with environmental factors modulate the differential individual responses to MHP and LF dietary interventions. These insights and models may help to optimize personalized nutritional strategies for modeling the prevention and management of excessive adiposity through precision nutrition approaches taking into account not only genetic information but also the lifestyle/clinical factors that interplay in addition to age and sex.

Methylome-Wide Association Study in Peripheral White Blood Cells Focusing on Central Obesity and Inflammation

Epigenetic signatures such as DNA methylation may be associated with specific obesity traits in different tissues. The onset and development of some obesity-related complications are often linked to visceral fat accumulation. The aim of this study was to explore DNA methylation levels in peripheral white blood cells to identify epigenetic methylation marks associated with waist circumference (WC). DNA methylation levels were assessed using Infinium Human Methylation 450K and MethylationEPIC beadchip (Illumina) to search for putative associations with WC values of 473 participants from the Methyl Epigenome Network Association (MENA) project. Statistical analysis and Ingenuity Pathway Analysis (IPA) were employed for assessing the relationship between methylation and WC. A total of 669 CpGs were statistically associated with WC (FDR < 0.05, slope ≥ |0.1|). From these CpGs, 375 CpGs evidenced a differential methylation pattern between females with WC ≤ 88 and > 88 cm, and 95 CpGs between males with WC ≤ 102 and > 102 cm. These differentially methylated CpGs are located in genes related to inflammation and obesity according to IPA. Receiver operating characteristic (ROC) curves of the top four significant differentially methylated CpGs separated by sex discriminated individuals with presence or absence of abdominal fat. ROC curves of all the CpGs from females and one CpG from males were validated in an independent sample (n = 161). These methylation results add further insights about the relationships between obesity, adiposity-associated comorbidities, and DNA methylation where inflammation processes may be involved.

Associations between olfactory pathway gene methylation marks, obesity features and dietary intakes

Background

Olfaction is an important sense influencing food preferences, appetite, and eating behaviors. This hypothesis-driven study aimed to assess associations between olfactory pathway gene methylation signatures, obesity features, and dietary intakes.

Methods

A nutriepigenomic analysis was conducted in 474 adults from the Methyl Epigenome Network Association (MENA) project. Anthropometric measurements, clinical data, and serum metabolic profiles of the study population were obtained from structured databases of the MENA cohorts. Habitual dietary intake was assessed using a validated semiquantitative food frequency questionnaire. DNA methylation was measured in circulating white blood cells by microarray (Infinium Human Methylation 450 K BeadChips). FDR values (p < 0.0001) were used to select those CpGs that showed the best correlation with body mass index (BMI) and waist circumference (WC). Pathway analyses involving the characterization of genes involved in the olfactory transduction system were performed using KEGG and pathDIP reference databases.

Results

Overall, 15 CpG sites at olfactory pathway genes were associated with BMI (p < 0.0001) and WC (p < 0.0001) after adjustments for potential confounding factors. Together, methylation levels at the15 CpG sites accounted for 22% and 20% of the variability in BMI and WC (r² = 0.219, p < 0.001, and r² = 0.204, p < 0.001, respectively). These genes encompassed olfactory receptors (OR4D2, OR51A7, OR2T34, and OR2Y1) and several downstream signaling molecules (SLC8A1, ANO2, PDE2A, CALML3, GNG7, CALML6, PRKG1, and CAMK2D), which significantly regulated odor detection and signal transduction processes within the complete olfactory cascade, as revealed by pathway enrichment analyses (p = 1.94 × 10^–10). Moreover, OR4D2 and OR2Y1 gene methylation patterns strongly correlated with daily intakes of total energy (p < 0.0001), carbohydrates (p < 0.0001), protein (p < 0.0001), and fat (p < 0.0001).

Conclusions

The results of this study suggest novel relationships between olfactory pathway gene methylation signatures, obesity indices, and dietary intakes.

Epigenome-wide association study in peripheral white blood cells involving insulin resistance

Insulin resistance (IR) is a hallmark of type 2 diabetes, metabolic syndrome and cardiometabolic risk. An epigenetic phenomena such as DNA methylation might be involved in the onset and development of systemic IR. The aim of this study was to explore the genetic DNA methylation levels in peripheral white blood cells with the objective of identifying epigenetic signatures associated with IR measured by the Homeostatic Model Assessment of IR (HOMA-IR) following an epigenome-wide association study approach. DNA methylation levels were assessed using Infinium Methylation Assay (Illumina), and were associated with HOMA-IR values of participants from the Methyl Epigenome Network Association (MENA) project, finding statistical associations for at least 798 CpGs. A stringent statistical analysis revealed that 478 of them showed a differential methylation pattern between individuals with HOMA-IR ≤ 3 and > 3. ROC curves of top four CpGs out of 478 allowed differentiating individuals between both groups (AUC≈0.88). This study demonstrated the association between DNA methylation in some specific CpGs and HOMA-IR values that will help to the understanding and in the development of new strategies for personalized approaches to predict and prevent IR-associated diseases.

Genetic and nongenetic factors explaining metabolically healthy and unhealthy phenotypes in participants with excessive adiposity: relevance for personalized nutrition

BACKGROUND

Different genetic and environmental factors can explain the heterogeneity of obesity-induced metabolic alterations between individuals. In this study, we aimed to screen factors that predict metabolically healthy (MHP) and unhealthy (MUP) phenotypes using genetic and lifestyle data in overweight/obese participants.

METHODS

In this cross-sectional study we enrolled 298 overweight/obese Spanish adults. The Adult Treatment Panel III criteria for metabolic syndrome were used to categorize MHP (at most, one trait) and MUP (more than one feature). Blood lipid and inflammatory profiles were measured by standardized methods. Body composition was determined by dual-energy X-ray absorptiometry. A total of 95 obesity-predisposing single-nucleotide polymorphisms (SNPs) were genotyped by a predesigned next-generation sequencing system. SNPs associated with a MUP were used to compute a weighted genetic-risk score (wGRS). Information concerning lifestyle (dietary intake and physical activity level) was collected using validated questionnaires.

RESULTS

The prevalence of MHP and MUP was 44.3% and 55.7%, respectively, in this sample. Overall, 12 obesity-related genetic variants were associated with the MUP. Multiple logistic regression analyses revealed that wGRS (OR = 4.133, p < 0.001), total dietary fat [odds ratio (OR) = 1.105, p = 0.002], age (OR = 1.064, p = 0.001), and BMI (OR = 1.408, p < 0.001) positively explained the MUP, whereas female sex (OR = 0.330, p = 0.009) produced a protective effect. The area under the receiver operating characteristic curve using the multivariable model was high (0.8820). Interestingly, the wGRS was the greatest contributor to the MUP (squared partial correlation = 0.3816, p < 0.001).

CONCLUSIONS

The genetic background is an important factor explaining MHP and MUP related to obesity, in addition to lifestyle variables. This information could be useful to metabolically categorize individuals, as well as for the design/implementation of personalized nutrition interventions aimed at promoting metabolic health and nutritional wellbeing.

Diet, Gut Microbiota, and Obesity: Links with Host Genetics and Epigenetics and Potential Applications

Diverse evidence suggests that the gut microbiota is involved in the development of obesity and associated comorbidities. It has been reported that the composition of the gut microbiota differs in obese and lean subjects, suggesting that microbiota dysbiosis can contribute to changes in body weight. However, the mechanisms by which the gut microbiota participates in energy homeostasis are unclear. Gut microbiota can be modulated positively or negatively by different lifestyle and dietary factors. Interestingly, complex interactions between genetic background, gut microbiota, and diet have also been reported concerning the risk of developing obesity and metabolic syndrome features. Moreover, microbial metabolites can induce epigenetic modifications (i.e., changes in DNA methylation and micro-RNA expression), with potential implications for health status and susceptibility to obesity. Also, microbial products, such as short-chain fatty acids or membrane proteins, may affect host metabolism by regulating appetite, lipogenesis, gluconeogenesis, inflammation, and other functions. Metabolomic approaches are being used to identify new postbiotics with biological activity in the host, allowing discovery of new targets and tools for incorporation into personalized therapies. This review summarizes the current understanding of the relations between the human gut microbiota and the onset and development of obesity. These scientific insights are paving the way to understanding the complex relation between obesity and microbiota. Among novel approaches, prebiotics, probiotics, postbiotics, and fecal microbiome transplantation could be useful to restore gut dysbiosis.

Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight

Background and Aim

Individual lipid phenotypes including circulating total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), and triglycerides (TG) determinations are influenced by gene-environment interactions. The aim of this study was to predict blood lipid level (TC, LDL-c, HDL-c, and TG) variability using genetic and lifestyle data in subjects with excessive body weight-for-height.

Methods

This cross-sectional study enrolled 304 unrelated overweight/obese adults of self-reported European ancestry. A total of 95 single nucleotide polymorphisms (SNPs) related to obesity and weight loss were analyzed by a targeted next-generation sequencing system. Relevant genotypes of each SNP were coded as 0 (nonrisk) and 1 (risk). Four genetic risk scores (GRS) for each lipid phenotype were calculated by adding the risk genotypes. Information concerning lifestyle (diet, physical activity, alcohol drinking, and smoking) was obtained using validated questionnaires. Total body fat (TFAT) and visceral fat (VFAT) were determined by dual-energy X-ray absorptiometry.

Results

Overall, 45 obesity-related genetic variants were associated with some of the studied blood lipids. In addition to conventional factors (age, sex, dietary intakes, and alcohol consumption), the calculated GRS significantly contributed to explain their corresponding plasma lipid trait. Thus, HDL-c, TG, TC, and LDL-c serum concentrations were predicted by approximately 28% (optimism-corrected adj. R² = 0.28), 25% (optimism-corrected adj. R² = 0.25), 24% (optimism-corrected adj. R² = 0.24), and 21% (optimism-corrected adj. R²=0.21), respectively. Interestingly, GRS were the greatest contributors to TC (squared partial correlation (PC²) = 0.18) and LDL-c (PC² = 0.18) features. Likewise, VFAT and GRS had a higher impact on HDL-c (PC² = 0.09 and PC² = 0.06, respectively) and TG levels (PC² = 0.20 and PC² = 0.07, respectively) than the rest of variables.

Conclusions

Besides known lifestyle influences, some obesity-related genetic variants could help to predict blood lipid phenotypes.

Dopamine gene methylation patterns are associated with obesity markers and carbohydrate intake

INTRODUCTION

Dopamine (DA) is a neurotransmitter that regulates the rewarding and motivational processes underlying food intake and eating behaviors. This study hypothesized associations of DNA methylation signatures at genes modulating DA signaling with obesity features, metabolic profiles, and dietary intake.

METHODS

An adult population within the Methyl Epigenome Network Association project was included (n = 473). DNA methylation levels in white blood cells were measured by microarray (450K). Differentially methylated genes were mapped within the dopaminergic synapse pathway using the KEGG reference database (map04728). Subsequently, network enrichment analyses were run in the pathDIP portal. Associations of methylation patterns with anthropometric markers of general (BMI) and abdominal obesity (waist circumference), the blood metabolic profile, and daily dietary intakes were screened.

RESULTS

After applying a correction for multiple comparisons, 12 CpG sites were strongly associated (p < 0.0001) with BMI: cg03489495 (ITPR3), cg22851378 (PPP2R2D), cg04021127 (PPP2R2D), cg22441882 (SLC18A1), cg03045635 (DRD5), cg23341970 (ITPR2), cg13051970 (DDC), cg08943004 (SLC6A3), cg20557710 (CACNA1C), cg24085522 (GNAL), cg16846691 (ITPR2), and cg09691393 (SLC6A3). Moreover, average methylation levels of these genes differed according to the presence or absence of abdominal obesity. Pathway analyses revealed a statistically significant contribution of the aforementioned genes to dopaminergic synapse transmission (p = 4.78E-08). Furthermore, SLC18A1 and SLC6A3 gene methylation signatures correlated with total energy (p < 0.001) and carbohydrate (p < 0.001) intakes.

CONCLUSIONS

The results of this investigation reveal that methylation status on DA signaling genes may underlie epigenetic mechanisms contributing to carbohydrate and calorie consumption and fat deposition.

Dopamine D2 receptor polymorphism (C957T) is associated with sugar consumption and triglyceride levels in West Mexicans

Genetic variations in the dopamine receptor D2 (DRD2) may alter dopamine signaling and modify the rewarding effects of food. This study aimed to analyze the association of the C957T DRD2 polymorphism with sugar consumption in West Mexican subjects. In a cross-sectional and analytical study, a total of 215 Mexican subjects were enrolled. DRD2 genotyping was performed by an allelic discrimination assay. Habitual dietary intake and the biochemical profile were evaluated. Genotype frequencies of the C957T DRD2 polymorphism were CC (12.1%), CT (40.9%) and TT (47.0%). Carriers of the CC genotype had a higher intake of sugar (g/day) than heterozygotes (67.4 g vs. 41.3 g, p = 0.001) and TT homozygotes (67.4 g vs. 45.2 g, p = 0.004). Also, the habitual consumption of soda (daily or at least 3 times per week) was more frequent among CC genotype carriers compared with heterozygotes (81% vs. 51%, p = 7.5 × 10^-6) and TT homozygotes (81% vs. 57%, p = 2.4 × 10^-4). Furthermore, the CC genotype was associated with elevated serum triglyceride levels (>150 mg/dL) than the CT genotype (OR = 2.80, 95% CI 1.08-7.24, p = 0.034). In conclusion, our results suggest a genetic background associated with sugar consumption among West Mexicans, which may contribute to increases in serum triglyceride levels.