Epigenomics and metabolomics reveal the mechanism of the APOA2-saturated fat intake interaction affecting obesity

Differential weight-loss responses of APOA2 genotype carriers to low-carbohydrate and low-fat diets: the DIETFITS trial

OBJECTIVE

This study aimed to determine whether APOA2 genotypes and saturated fatty acid (SAT) intake affect weight-loss response to healthy low-carbohydrate (HLC) and healthy low-fat (HLF) diets.

METHODS

This is a secondary analysis of the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) study, a 12-month randomized clinical trial of HLC or HLF diets in 609 adults aged 18 to 50 years with BMI values between 28 and 40 kg/m2. The current study examined 3-, 6-, and 12-month weight loss in participants with different APOA2 genotypes (TT vs. C allele carriers, CT + CC) at variant rs5082 who met the SAT intake criterion of ≥22 g/day for an HLC diet and < 22 g/day for an HLF diet at all three study time points.

RESULTS

Participants with the TT APOA2 genotype lost significantly more weight consistently on an HLC diet than on an HLF diet at 3, 6, and 12 months, whereas C allele carriers lost more weight only at 3 months and not at 6 or 12 months. APOA2 genotype-by-SAT intake interaction affecting weight loss was observed only at 12 months. Among participants who did not consistently meet the SAT intake criterion, there were no significant weight-loss differences among APOA2 genotypes.

CONCLUSIONS

This study highlights the importance of evaluating genotype-diet interactions in weight-loss trials to better inform precision nutrition interventions.

CLINICAL TRIAL REGISTRATION

NCT01826591.

Dietary patterns derived by reduced rank regression, macronutrients as response variables, and variation by economic status: NHANES 1999-2018

PURPOSE

Macronutrient intakes vary across people and economic status, leading to a disparity in diet-related metabolic diseases. This study aimed to provide insight into this by: (1) identifying dietary patterns in adults using reduced rank regression (RRR), with macronutrients as response variables, and (2) investigating the associations between economic status and macronutrient based dietary patterns, and between dietary patterns with central obesity (waist circumference) and systemic inflammation (C-reactive protein [CRP]).

METHODS

41,849 US participants from the National Health and Nutrition Examination Survey (NHANES), 1999-2018 were included. The percentages of energy from protein, carbohydrates, saturated fats, and unsaturated fats were used as response variables in RRR. Multivariable generalized linear models with Gaussian distribution were employed to investigate the associations.

RESULTS

Four dietary patterns were identified. Economic status was positively associated with both the high fat, low carbohydrate [βHighVsLow = 0.22; 95% CI: 0.16, 0.28] and high protein patterns [βHighVsLow = 0.07; 95% CI: 0.03, 0.11], and negatively associated with both the high saturated fat [βHighVsLow = -0.06; 95% CI: -0.08, -0.03] and the low alcohol patterns [βHighVsLow = -0.08; 95% CI; -0.10, -0.06]. The high saturated fat pattern was positively associated with waist circumference [βQ5VsQ1 = 1.71; 95% CI: 0.97, 2.44] and CRP [βQ5VsQ1 = 0.37; 95% CI: 0.26, 0.47].

CONCLUSION

Macronutrient dietary patterns, which varied by economic status and were associated with metabolic health markers, may explain associations between economic status and health.

Barriers in Translating Existing Nutrigenetics Insights to Precision Nutrition for Cardiometabolic Health in Ethnically Diverse Populations

BACKGROUND

Cardiometabolic diseases pose a significant threat to global public health, with a substantial majority of cardiovascular disease mortality (more than three-quarters) occurring in low- and middle-income countries. There have been remarkable advances in recent years in identifying genetic variants that alter disease susceptibility by interacting with dietary factors. Despite the remarkable progress, several factors need to be considered before the translation of nutrigenetics insights to personalised and precision nutrition in ethnically diverse populations. Some of these factors include variations in genetic predispositions, cultural and lifestyle factors as well as socio-economic factors.

SUMMARY

This review aimed to explore the factors that need to be considered in bridging the gap between existing nutrigenetics insights and the implementation of personalised and precision nutrition across diverse ethnicities. Several factors might influence variations among individuals with regard to dietary exposures and metabolic responses, and these include genetic diversity, cultural and lifestyle factors as well as socio-economic factors. A multi-omics approach involving disciplines such as metabolomics, epigenetics, and the gut microbiome might contribute to improved understanding of the underlying mechanisms of gene-diet interactions and the implementation of precision nutrition although more research is needed to confirm the practicality and effectiveness of this approach. Conducting gene-diet interaction studies in diverse populations is essential and studies utilising large sample sizes are required as this improves the power to detect interactions with minimal effect sizes. Future studies should focus on replicating initial findings to enhance reliability and promote comparison across studies. Once findings have been replicated in independent samples, dietary intervention studies will be required to further strengthen the evidence and facilitate their application in clinical practice.

KEY MESSAGES

Nutrigenetics has a potential role to play in the prevention and management of cardiometabolic diseases. Conducting gene-diet interaction studies in diverse populations is essential giving the genetic diversity and variations in dietary patterns. Integrating data from disciplines such as metabolomics, epigenetics, and the gut microbiome could help in early identification of individuals at risk of cardiometabolic diseases as well as the implementation of precise dietary interventions for preventing and managing cardiometabolic diseases.

Tachol1 QTL on mouse chromosome 1 is responsible for hypercholesterolemia and diet-induced obesity

Hypercholesterolemia raises the risk for cardiovascular complications and overall health. Hypercholesterolemia is common, affecting 10% of the general population of the US, and heritable. Most individuals with hypercholesterolemia have a polygenic predisposition to the condition. Previously we identified a quantitative trait locus, Tachol1, linked to hypercholesterolemia on mouse chromosome 1 (Chr1) in a cross between C57BL/6J (B6) and TALLYHO/JngJ (TH) mice, a polygenic model for human obesity, type 2 diabetes and hyperlipidemia. Subsequently, using congenic mice that carry a TH-derived genomic segment of Chr1 on a B6 background, we demonstrated that the distal segment of Chr1, where Tachol1 maps, is necessary to cause hypercholesterolemia, as well as diet-induced obesity. In this study, we generated overlapping subcongenic lines to the distal segment of congenic region and characterized subcongenic mice carrying the smallest TH region of Tachol1, ~ 16.2 Mb in size (B6.TH-Chr1-16.2 Mb). Both male and female B6.TH-Chr1-16.2 Mb mice showed a significantly increased plasma total cholesterol levels compared to B6 on both chow and high fat (HF) diet. B6.TH-Chr1-16.2 Mb mice also had greater fat mass than B6 on HF diet, without increasing food intake. The gene and protein expression levels of absent in melanoma 2 (Aim2) gene were significantly upregulated in B6.TH-Chr1-16.2 Mb mice compared to B6. In summary, we confirmed the effect of Tachol1 on hypercholesterolemia and diet-induced obesity using subcongenic analysis.

A genomics perspective of personalized prevention and management of obesity

This review discusses the landscape of personalized prevention and management of obesity from a nutrigenetics perspective. Focusing on macronutrient tailoring, we discuss the impact of genetic variation on responses to carbohydrate, lipid, protein, and fiber consumption. Our bioinformatic analysis of genomic variants guiding macronutrient intake revealed enrichment of pathways associated with circadian rhythm, melatonin metabolism, cholesterol and lipoprotein remodeling and PPAR signaling as potential targets of macronutrients for the management of obesity in relevant genetic backgrounds. Notably, our data-based in silico predictions suggest the potential of repurposing the SYK inhibitor fostamatinib for obesity treatment in relevant genetic profiles. In addition to dietary considerations, we address genetic variations guiding lifestyle changes in weight management, including exercise and chrononutrition. Finally, we emphasize the need for a refined understanding and expanded research into the complex genetic landscape underlying obesity and its management.

Comparative Serum Proteome Profiling of Canine Benign Prostatic Hyperplasia before and after Castration

BPH is the most prevalent prostatic condition in aging dogs. Nevertheless, clinical diagnosis and management remain inconsistent. This study employed in-solution digestion coupled with nano-liquid chromatography tandem mass spectrometry to assess serum proteome profiling of dogs with BPH and those dogs after castration. Male dogs were divided into two groups; control and BPH groups. In the BPH group, each dog was evaluated at two time points: Day 0 (BF subgroup) and Day 30 after castration (AT subgroup). In the BF subgroup, three proteins were significantly upregulated and associated with dihydrotestosterone: solute carrier family 5 member 5, tyrosine-protein kinase, and FRAT regulator of WNT signaling pathway 1. Additionally, the overexpression of polymeric immunoglobulin receptors in the BF subgroup hints at its potential as a novel protein linked to the BPH development process. Conversely, alpha-1-B glycoprotein (A1BG) displayed significant downregulation in the BF subgroup, suggesting A1BG's potential as a predictive protein for canine BPH. Finasteride was associated with increased proteins in the AT subgroup, including apolipoprotein C-I, apolipoprotein E, apolipoprotein A-II, TAO kinase 1, DnaJ homolog subfamily C member 16, PH domain and leucine-rich repeat protein phosphatase 1, neuregulin 1, and pseudopodium enriched atypical kinase 1. In conclusion, this pilot study highlighted alterations in various serum proteins in canine BPH, reflecting different pathological changes occurring in this condition. These proteins could be a source of potential non-invasive biomarkers for diagnosing this disease.

UMI-77 Modulates the Complement Cascade Pathway and Inhibits Inflammatory Factor Storm in Sepsis Based on TMT Proteomics and Inflammation Array Glass Chip

Sepsis is a systemic inflammatory response syndrome caused by infection, which has no specific drug at present. UMI-77 can significantly improve the survival rate of septic mice; the detailed role of UMI-77 and its underlying mechanisms in sepsis are not clear. Inflammation array glass chip and proteomic analyses were performed to elucidate the latent mechanism of UMI-77 in the treatment of sepsis. The results showed that 7.0 mg/kg UMI-77 improved the 5 day survival rate in septic mice compared to the LPS group (60.964 vs 9.779%) and ameliorated the pathological conditions. Inflammation array glass chip analysis showed that sepsis treatment with UMI-77 may eventually through the suppression of the characteristic inflammatory storm-related cytokines such as KC, RANTES, LIX, IL-6, eotaxin, TARC, IL-1β, and so on. Proteomics analysis showed that 213 differential expression proteins and complement and coagulation cascades were significantly associated with the process for the UMI-77 treatment of sepsis. The top 10 proteins including Apoa2, Tgfb1, Serpinc1, Vtn, Apoa4, Cat, Hp, Serpinf2, Fgb, and Serpine1 were identified and verified, which play important roles in the mechanism of UMI-77 in the treatment of sepsis. Our findings indicate that UMI-77 exerts an antisepsis effect by modulating the complement cascade pathway and inhibiting inflammatory storm factors.

Network analysis of plasma proteomes in affective disorders

The conventional differentiation of affective disorders into major depressive disorder (MDD) and bipolar disorder (BD) has insufficient biological evidence. Utilizing multiple proteins quantified in plasma may provide critical insight into these limitations. In this study, the plasma proteomes of 299 patients with MDD or BD (aged 19-65 years old) were quantified using multiple reaction monitoring. Based on 420 protein expression levels, a weighted correlation network analysis was performed. Significant clinical traits with protein modules were determined using correlation analysis. Top hub proteins were determined using intermodular connectivity, and significant functional pathways were identified. Weighted correlation network analysis revealed six protein modules. The eigenprotein of a protein module with 68 proteins, including complement components as hub proteins, was associated with the total Childhood Trauma Questionnaire score (r = -0.15, p = 0.009). Another eigenprotein of a protein module of 100 proteins, including apolipoproteins as hub proteins, was associated with the overeating item of the Symptom Checklist-90-Revised (r = 0.16, p = 0.006). Functional analysis revealed immune responses and lipid metabolism as significant pathways for each module, respectively. No significant protein module was associated with the differentiation between MDD and BD. In conclusion, childhood trauma and overeating symptoms were significantly associated with plasma protein networks and should be considered important endophenotypes in affective disorders.

Advances in the study of the pathogenesis of obesity: Based on apolipoproteins

Obesity is a state presented by excessive accumulation and abnormal distribution of body fat, with metabolic disorders being one of its distinguishing features. Obesity is associated with dyslipidemia, apolipoproteins are important structural components of plasma lipoproteins, which influence lipid metabolism in the body by participating in lipoprotein metabolism and are closely related to the progression of obesity. Apolipoproteins influence the progression of obesity from lipid metabolism, energy expenditure and inflammatory response. In this review, we discuss the alterations of apolipoproteins in obesity, understand the potential mechanisms by which apolipoproteins affect obesity, as well as provide new targets for the treatment of obesity.

Interactions between genetic and lifestyle factors on cardiometabolic disease-related outcomes in Latin American and Caribbean populations: A systematic review

Introduction

The prevalence of cardiometabolic diseases has increased in Latin American and the Caribbean populations (LACP). To identify gene-lifestyle interactions that modify the risk of cardiometabolic diseases in LACP, a systematic search using 11 search engines was conducted up to May 2022.

Methods

Eligible studies were observational and interventional studies in either English, Spanish, or Portuguese. A total of 26,171 publications were screened for title and abstract; of these, 101 potential studies were evaluated for eligibility, and 74 articles were included in this study following full-text screening and risk of bias assessment. The Appraisal tool for Cross-Sectional Studies (AXIS) and the Risk Of Bias In Non-Randomized Studies-of Interventions (ROBINS-I) assessment tool were used to assess the methodological quality and risk of bias of the included studies.

Results

We identified 122 significant interactions between genetic and lifestyle factors on cardiometabolic traits and the vast majority of studies come from Brazil (29), Mexico (15) and Costa Rica (12) with FTO, APOE, and TCF7L2 being the most studied genes. The results of the gene-lifestyle interactions suggest effects which are population-, gender-, and ethnic-specific. Most of the gene-lifestyle interactions were conducted once, necessitating replication to reinforce these results.

Discussion

The findings of this review indicate that 27 out of 33 LACP have not conducted gene-lifestyle interaction studies and only five studies have been undertaken in low-socioeconomic settings. Most of the studies were cross-sectional, indicating a need for longitudinal/prospective studies. Future gene-lifestyle interaction studies will need to replicate primary research of already studied genetic variants to enable comparison, and to explore the interactions between genetic and other lifestyle factors such as those conditioned by socioeconomic factors and the built environment. The protocol has been registered on PROSPERO, number CRD42022308488.

Systematic review registration

https://clinicaltrials.gov, identifier CRD420223 08488.

Serum metabolites associated with wholegrain consumption using nontargeted metabolic profiling: a discovery and reproducibility study

PURPOSE

To identify fasting serum metabolites associated with WG intake in a free-living population adjusted for potential confounders.

METHODS

We selected fasting serum samples at baseline from a subset (n = 364) of the prospective population-based Kuopio Ischaemic Heart Disease Risk Factor Study (KIHD) cohort. The samples were analyzed using nontargeted metabolomics with liquid chromatography coupled with mass spectrometry (LC-MS). Association with WG intake was investigated using both random forest followed by linear regression adjusted for age, BMI, smoking, physical activity, energy and alcohol consumption, and partial Spearman correlation adjusted for the same covariates. Features selected by any of these models were shortlisted for annotation. We then checked if we could replicate the findings in an independent subset from the same cohort (n = 200).

RESULTS

Direct associations were observed between WG intake and pipecolic acid betaine, tetradecanedioic acid, four glucuronidated alkylresorcinols (ARs), and an unknown metabolite both in discovery and replication cohorts. The associations remained significant (FDR<0.05) even after adjustment for the confounders in both cohorts. Sinapyl alcohol was positively correlated with WG intake in both cohorts after adjustment for the confounders but not in linear models in the replication cohort. Some microbial metabolites, such as indolepropionic acid, were positively correlated with WG intake in the discovery cohort, but the correlations were not replicated in the replication cohort.

CONCLUSIONS

The identified associations between WG intake and the seven metabolites after adjusting for confounders in both discovery and replication cohorts suggest the potential of these metabolites as robust biomarkers of WG consumption.

The impact of alcoholic drinks and dietary factors on epigenetic markers associated with triglyceride levels

Background: Many epigenetic loci have been associated with plasma triglyceride (TG) levels, but epigenetic connections between those loci and dietary exposures are largely unknown. This study aimed to characterize the epigenetic links between diet, lifestyle, and TG. Methods: We first conducted an epigenome-wide association study (EWAS) for TG in the Framingham Heart Study Offspring population (FHS, n = 2,264). We then examined relationships between dietary and lifestyle-related variables, collected four times in 13 years, and differential DNA methylation sites (DMSs) associated with the last TG measures. Third, we conducted a mediation analysis to evaluate the causal relationships between diet-related variables and TG. Finally, we replicated three steps to validate identified DMSs associated with alcohol and carbohydrate intake in the Genetics of Lipid-Lowering Drugs and Diet Network (GOLDN) study (n = 993). Results: In the FHS, the EWAS revealed 28 TG-associated DMSs at 19 gene regions. We identified 102 unique associations between these DMSs and one or more dietary and lifestyle-related variables. Alcohol and carbohydrate intake showed the most significant and consistent associations with 11 TG-associated DMSs. Mediation analyses demonstrated that alcohol and carbohydrate intake independently affect TG via DMSs as mediators. Higher alcohol intake was associated with lower methylation at seven DMSs and higher TG. In contrast, increased carbohydrate intake was associated with higher DNA methylation at two DMSs (CPT1A and SLC7A11) and lower TG. Validation in the GOLDN further supports the findings. Conclusion: Our findings imply that TG-associated DMSs reflect dietary intakes, particularly alcoholic drinks, which could affect the current cardiometabolic risk via epigenetic changes. This study illustrates a new method to map epigenetic signatures of environmental factors for disease risk. Identification of epigenetic markers of dietary intake can provide insight into an individual's risk of cardiovascular disease and support the application of precision nutrition. Clinical Trial Registration: www.ClinicalTrials.gov, the Framingham Heart Study (FHS), NCT00005121; the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN), NCT01023750.

Research gaps and opportunities in precision nutrition: an NIH workshop report

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.

Holistic Integration of Omics Tools for Precision Nutrition in Health and Disease

The combination of multiple omics approaches has emerged as an innovative holistic scope to provide a more comprehensive view of the molecular and physiological events underlying human diseases (including obesity, dyslipidemias, fatty liver, insulin resistance, and inflammation), as well as for elucidating unique and specific metabolic phenotypes. These omics technologies include genomics (polymorphisms and other structural genetic variants), epigenomics (DNA methylation, histone modifications, long non-coding RNA, telomere length), metagenomics (gut microbiota composition, enterotypes), transcriptomics (RNA expression patterns), proteomics (protein quantities), and metabolomics (metabolite profiles), as well as interactions with dietary/nutritional factors. Although more evidence is still necessary, it is expected that the incorporation of integrative omics could be useful not only for risk prediction and early diagnosis but also for guiding tailored dietary treatments and prognosis schemes. Some challenges include ethical and regulatory issues, the lack of robust and reproducible results due to methodological aspects, the high cost of omics methodologies, and high-dimensional data analyses and interpretation. In this review, we provide examples of system biology studies using multi-omics methodologies to unravel novel insights into the mechanisms and pathways connecting the genotype to clinically relevant traits and therapy outcomes for precision nutrition applications in health and disease.

Dietary acid load modifies the effects of ApoA2-265 T > C polymorphism on lipid profile and serum leptin and ghrelin levels among type 2 diabetic patients

This investigation with aimed the effect of APOA2-265 T > C polymorphism and dietary acid load (DAL) as either potential renal acid load (PRAL) and net endogenous acid production (NEAP) intake interaction on metabolic markers in type 2 diabetes mellitus (T2DM). In present cross-sectional study, 737 patients with T2DM (290 men and 447 women) were enlisted from diabetes centers in Tehran. The dietary intakes of all participants during the last year was acquired by a validated semi-quantitative food frequency (FFQ) questionnaire. Polymerase chain reaction (PCR) was used for genotyping the APOA2-265 T > C. Biochemical indises containing leptin, ghrelin, total cholesterol (Bailey et al., J Clin Invest 97:1147-1453, 1996), low-density lipoprotein cholestrol (LDL-C), high-density lipoprotein cholestrol (HDL-C), triglyceride (TG), superoxide dismutase (SOD), high sensitivy C-reactive protein (hs-CRP), total antioxidant capacity (TAC), pentraxin-3 (PTX3), prostaglandin F2α (PGF2α) and interleukin 18 (IL18) were measured by standard method. Atherogenic indices (AIP, AC, CR-I, CR-II) were calculated. The gene-diet interactions were evaluated using an GLM. The frequency overall prevalence of rs5082 genotypes was 63.82 and 36.17% for T-allele and C-allele respectively. TG, Ghrelin, and hs-CRP concentrations were significantly higher among carriers with C allele than TT homozygotes. However, TC/CC genotypes have lower PTX3 than TT homozygotes (P < 0.05). C-allele carriers had highest mean of BMI (P_NEAP=0.04, P_PRAL = 0.006), WC (P_NEAP=0.04, P_PRAL = 0.04), TC (P_NEAP=0.03, P_PRAL = 0.01), ghrelin (P_NEAP=0.01, P_PRAL = 0.04), and leptin (P_NEAP=0.04, P_PRAL = 0.03) when placed in top tertiles of NEAP and PRAL.BMI, WC, TC, ghrelin, and leptin levels may be modified in C carriers by decreasing DAL, though, further investigations are required to confirm these findings.

Apolipoprotein A-II, a Player in Multiple Processes and Diseases

Apolipoprotein A-II (apoA-II) is the second most abundant apolipoprotein in high-density lipoprotein (HDL) particles, playing an important role in lipid metabolism. Human and murine apoA-II proteins have dissimilar properties, partially because human apoA-II is dimeric whereas the murine homolog is a monomer, suggesting that the role of apoA-II may be quite different in humans and mice. As a component of HDL, apoA-II influences lipid metabolism, being directly or indirectly involved in vascular diseases. Clinical and epidemiological studies resulted in conflicting findings regarding the proatherogenic or atheroprotective role of apoA-II. Human apoA-II deficiency has little influence on lipoprotein levels with no obvious clinical consequences, while murine apoA-II deficiency causes HDL deficit in mice. In humans, an increased plasma apoA-II concentration causes hypertriglyceridemia and lowers HDL levels. This dyslipidemia leads to glucose intolerance, and the ensuing high blood glucose enhances apoA-II transcription, generating a vicious circle that may cause type 2 diabetes (T2D). ApoA-II is also used as a biomarker in various diseases, such as pancreatic cancer. Herein, we provide a review of the most recent findings regarding the roles of apoA-II and its functions in various physiological processes and disease states, such as cardiovascular disease, cancer, amyloidosis, hepatitis, insulin resistance, obesity, and T2D.

ApoA2-256T > C polymorphism interacts with Healthy Eating Index, Dietary Quality Index-International and Dietary Phytochemical Index to affect biochemical markers among type 2 diabetic patients

Several investigations revealed the association between ApoA2 concentration and lipid profile, inflammation and oxidative stress markers. Dietary habits also play a major role in the health status of individuals with type 2 diabetes mellitus (T2DM). This study aimed to investigate the interaction of ApoA2-256T > C with dietary indexes on ghrelin and leptin hormones together with biochemical markers among individuals with T2DM. A cross-sectional study was conducted on 726 randomly selected individuals with T2DM. A validated FFQ was used to evaluate Healthy Eating Index, Dietary Quality Index-International (DQI-I) and Dietary Phytochemical Index (DPI). ApoA2-256T > C genotypes were detected by real-time-PCR. Ghrelin, leptin and biochemical markers were also assessed. ANCOVA was used for the interaction between the polymorphism and dietary indexes. A significant interaction was observed between ApoA2-256T > C and DQI-I on high-sensitivity C-reactive protein (hs-CRP) level and superoxide dismutase (SOD) activity. Besides, the interaction of the SNP and DPI significantly affected hs-CRP and 8-isoprostane F2α (PGF2α) levels. CC in the second tertile of DPI had the lowest hs-CRP level, and it was elevated due to adhering to DQI-I (P_interaction = 0·01 and 0·04, respectively). Moreover, T-allele (protective allele) carriers with the highest level of PGF2α and SOD activity were those in the second tertile of DPI and DQI-I, respectively (P_interaction = 0·03 and 0·007, respectively). SOD activity, hs-CRP and PGF2α concentration may be modified in T-allele carriers and CC by the adherence to DPI and DQI-I, though additional studies are required to confirm these findings.

The Role of Genetics in a Personalized Approach in Patients with Feeding Problems, Overweight and Obesity

Aim: For the last 20 years a large amount of data was gathered showing a genetic predisposition to overweight and obesity. The aim of this study was to demonstrate a personalized, genetic-based approach in normalizing the patients’ weight and eating habits.

Materials and methods: Eight patients – seven women and one man – aged 28-51 years with BMI ranging from 17,58 to 38,95 kg/m2 were examined. Two of them were underweight, two – with normal weight, two – overweight, and two – obese. Patients were genotyped for: APOA2 (rs5082), ADIPOQ, (rs17300539), FTO (rs9939609), KCTD10 (rs10850219), LIPC (rs1800588), MMAB (rs2241201), PPARG (rs1801282), ANKK1/DRD2 (rs1800497), TAS2R38 (rs1726866), LEPR (rs2025804) and SLC2A2 (rs5400). Based on the genetic results, the type of diet (balanced, Mediterranean, low-fat and low-carbohydrate) was determined; the predisposition to unhealthy eating habits was described and followed by a genetic counseling to clarify the findings as well as a dietitian consultation to formulate a personalized diet.

Results: Our results showed that the patients’ actual diet was equivocally different from the genetically determined one. Аll patients, except for one, had hereditary predispositions to a particular unhealthy eating habit.

Conclusion: The inclusion of genetic testing and personalization of the diet facilitates the long-term maintenance of optimal body weight.

Role of macronutrient intake in the epigenetics of obesity

Obesity is caused by a combination of hereditary and environmental factors. Despite extensive study, contemporary through diet, exercise, education, surgery, and pharmacological treatments, no effective long-term solution has been found to this epidemic. Over the last decade, there has been a tremendous advancement in understanding the science of epigenetics, as well as a rise in public interest in learning more about the influence of diet and lifestyle choices on the health of an individual. Without affecting the underlying DNA sequence, epigenetic alterations impact gene expression. Previous animal studies have shown a link between the type of diet and expression or suppression of obesity genes, but there are very few human studies that demonstrate the relationship between dietary intake and obesity gene expression. This review highlights the effects of carbohydrates, lipids, and protein intake from the diet on obesity-related genes.

Using Machine Learning to Predict Obesity Based on Genome-Wide and Epigenome-Wide Gene-Gene and Gene-Diet Interactions

Obesity is associated with many chronic diseases that impair healthy aging and is governed by genetic, epigenetic, and environmental factors and their complex interactions. This study aimed to develop a model that predicts an individual's risk of obesity by better characterizing these complex relations and interactions focusing on dietary factors. For this purpose, we conducted a combined genome-wide and epigenome-wide scan for body mass index (BMI) and up to three-way interactions among 402,793 single nucleotide polymorphisms (SNPs), 415,202 DNA methylation sites (DMSs), and 397 dietary and lifestyle factors using the generalized multifactor dimensionality reduction (GMDR) method. The training set consisted of 1,573 participants in exam 8 of the Framingham Offspring Study (FOS) cohort. After identifying genetic, epigenetic, and dietary factors that passed statistical significance, we applied machine learning (ML) algorithms to predict participants' obesity status in the test set, taken as a subset of independent samples (n = 394) from the same cohort. The quality and accuracy of prediction models were evaluated using the area under the receiver operating characteristic curve (ROC-AUC). GMDR identified 213 SNPs, 530 DMSs, and 49 dietary and lifestyle factors as significant predictors of obesity. Comparing several ML algorithms, we found that the stochastic gradient boosting model provided the best prediction accuracy for obesity with an overall accuracy of 70%, with ROC-AUC of 0.72 in test set samples. Top predictors of the best-fit model were 21 SNPs, 230 DMSs in genes such as CPT1A, ABCG1, SLC7A11, RNF145, and SREBF1, and 26 dietary factors, including processed meat, diet soda, French fries, high-fat dairy, artificial sweeteners, alcohol intake, and specific nutrients and food components, such as calcium and flavonols. In conclusion, we developed an integrated approach with ML to predict obesity using omics and dietary data. This extends our knowledge of the drivers of obesity, which can inform precision nutrition strategies for the prevention and treatment of obesity. Clinical Trial Registration: [www.ClinicalTrials.gov], the Framingham Heart Study (FHS), [NCT00005121].

Plasma Fatty Acids, Not Dietary Fatty Acids, Associated with Obesity in Four Ethnic Minority Groups Unique to Southwest China: A Cross-Sectional Study

BACKGROUND

Dietary fatty acids (DFAs) and plasma fatty acids (PFAs) are linked to obesity. However, whether this association exists among ethnic minorities remains lacking. The present cross-sectional study was designed to investigate the correlation between DFAs, PFAs and obesity in four ethnic minority groups to Southwest China.

METHODS

A total of 166 obese people, and 166 normal-BMI subjects matched based on their age-, sex-, and ethnicity- were recruited from four different ethnic minority groups. DFAs were obtained through food frequency questionnaires. PFAs were assayed by GC/MS method. Binary and multiple regression analyses were performed to evaluate the correlation among DFAs, PFAs and obesity. Canonical correlation analysis (CCA) was conducted to assess the relationship between DFAs and PFAs.

RESULTS

FAs were found to be highest in the Naxi people and lowest in the Hani people. Multiple logistic regression analysis revealed that plasma C16:0 (OR = 1.310; 95% CI, 1.028-1.669) in the Hani people; plasma C20:3 n-6 (OR = 6.250; 95% CI, 1.224-31.927) and dietary C20:1 (OR = 9.231; 95% CI, 1.253-68.016) in the Wa people; plasma C18:0 (OR = 0.788; 95% CI, 0.681-0.912) in the Naxi people were seen to be independent predictive factors for obesity. CCA showed that DFAs were positively correlated with PFAs in the Naxi (r: 0.676; P < 0.05) and Bulang people (r: 0.897; P < 0.05), but there was no correlation in the Hani and Wa people.

CONCLUSION

In this study, PFAs but not DFAs were independently associated with obesity, and different among the four ethnic minorities.

The Molecular Effects of Dietary Acid Load on Metabolic Disease (The Cellular PasaDoble: The Fast-Paced Dance of pH Regulation)

Metabolic diseases are becoming more common and more severe in populations adhering to western lifestyle. Since metabolic conditions are highly diet and lifestyle dependent, it is suggested that certain diets are the cause for a wide range of metabolic dysfunctions. Oxidative stress, excess calcium excretion, inflammation, and metabolic acidosis are common features in the origins of most metabolic disease. These primary manifestations of "metabolic syndrome" can lead to insulin resistance, diabetes, obesity, and hypertension. Further complications of the conditions involve kidney disease, cardiovascular disease, osteoporosis, and cancers. Dietary analysis shows that a modern "Western-style" diet may facilitate a disruption in pH homeostasis and drive disease progression through high consumption of exogenous acids. Because so many physiological and cellular functions rely on acid-base reactions and pH equilibrium, prolonged exposure of the body to more acids than can effectively be buffered, by chronic adherence to poor diet, may result in metabolic stress followed by disease. This review addresses relevant molecular pathways in mammalian cells discovered to be sensitive to acid - base equilibria, their cellular effects, and how they can cascade into an organism-level manifestation of Metabolic Syndromes. We will also discuss potential ways to help mitigate this digestive disruption of pH and metabolic homeostasis through dietary change.

Dietary Patterns Characterized by Fat Type in Association with Obesity and Type 2 Diabetes: A Longitudinal Study of UK Biobank Participants

BACKGROUND

The fat type consumed is considered a risk factor for developing obesity and type 2 diabetes (T2D). However, these associations have not been investigated using a dietary patterns approach, which can capture combinations of foods and fat type consumed.

OBJECTIVES

This study aimed to investigate associations between dietary patterns with varying proportions of SFAs, MUFAs, or PUFAs and obesity, abdominal obesity, and self-reported T2D incidence.

METHODS

This study included UK Biobank participants with 2 or more 24-h dietary assessments, free from the outcome of interest at recruitment, and with outcome data at follow-up (n = 16,523; mean follow-up: 6.3 y). Reduced rank regression was used to derive dietary patterns with SFAs, MUFAs, and PUFAs (% of energy intake) as response variables. Logistic regression, adjusted for sociodemographic and health characteristics, was used to investigate the associations between dietary patterns and obesity [BMI (kg/m2) ≥30], abdominal obesity (waist circumference; men: ≥102 cm; women: ≥88 cm) and T2D incidence.

RESULTS

Two dietary patterns, DP1 and DP2, were identified: DP1 positively correlated with SFAs (r = 0.48), MUFAs (r = 0.67), and PUFAs (r = 0.56), characterized by higher intake of nuts, seeds, and butter and lower intake of fruit and low-fat yogurt; DP2 positively correlated with SFAs (r = 0.76) and negatively with PUFAs (r = -0.64) and MUFAs (r = -0.01), characterized by higher intake of butter and high-fat cheese and lower intake of nuts and seeds. Only DP2 was associated with higher obesity and abdominal obesity incidence (OR: 1.24; 95% CI: 1.02, 1.45; and OR: 1.19; 95% CI: 1.02, 1.38, respectively). Neither of the dietary patterns was associated with T2D incidence.

CONCLUSIONS

These findings provide evidence that a dietary pattern characterized by higher SFA and lower PUFA foods is associated with obesity and abdominal obesity incidence, but not T2D.

A Scoping Review of the Application of Metabolomics in Nutrition Research: The Literature Survey 2000-2019

Nutrimetabolomics is an emerging field in nutrition research, and it is expected to play a significant role in deciphering the interaction between diet and health. Through the development of omics technology over the last two decades, the definition of food and nutrition has changed from sources of energy and major/micro-nutrients to an essential exposure factor that determines health risks. Furthermore, this new approach has enabled nutrition research to identify dietary biomarkers and to deepen the understanding of metabolic dynamics and the impacts on health risks. However, so far, candidate markers identified by metabolomics have not been clinically applied and more efforts should be made to validate those. To help nutrition researchers better understand the potential of its application, this scoping review outlined the historical transition, recent focuses, and future prospects of the new realm, based on trends in the number of human research articles from the early stage of 2000 to the present of 2019 by searching the Medical Literature Analysis and Retrieval System Online (MEDLINE). Among them, objective dietary assessment, metabolic profiling, and health risk prediction were positioned as three of the principal applications. The continued growth will enable nutrimetabolomics research to contribute to personalized nutrition in the future.

Simple Energy Balance or Microbiome for Childhood Obesity Prevention?

Obesity prevention interventions generally have either not worked or had effects inadequate to mitigate the problem. They have been predicated on the simple energy balance model, which has been severely questioned by biological scientists. Numerous other etiological mechanisms have been proposed, including the intestinal microbiome, which has been related to childhood obesity in numerous ways. Public health research is needed in regard to diet and the microbiome, which hopefully will lead to effective child obesity prevention.

Functional Meat Products as Oxidative Stress Modulators: A Review

High meat consumption has been associated with increased oxidative stress mainly due to the generation of oxidized compounds in the body, such as malondialdehyde, 4-hydroxy-nonenal, oxysterols, or protein carbonyls, which can induce oxidative damage. Meat products are excellent matrices for introducing different bioactive compounds, to obtain functional meat products aimed at minimizing the pro-oxidant effects associated with high meat consumption. Therefore, this review aims to summarize the concept and preparation of healthy and functional meat, which could benefit antioxidant status. Likewise, the key strategies regarding meat production and storage as well as ingredients used (e.g., minerals, polyphenols, fatty acids, walnuts) for developing these functional meats are detailed. Although most effort has been made to reduce the oxidation status of meat, newly emerging approaches also aim to improve the oxidation status of consumers of meat products. Thus, we will delve into the relation between functional meats and their health effects on consumers. In this review, animal trials and intervention studies are discussed, ascertaining the extent of functional meat products' properties (e.g., neutralizing reactive oxygen species formation and increasing the antioxidant response). The effects of functional meat products in the frame of diet-gene interactions are analyzed to 1) discover target subjects that would benefit from their consumption, and 2) understand the molecular mechanisms that ensure precision in the prevention and treatment of diseases, where high oxidative stress takes place. Long-term intervention-controlled studies, testing different types and amounts of functional meat, are also necessary to ascertain their positive impact on degenerative diseases.

Recent advances and current controversies in genetic testing for personalized nutrition

PURPOSE OF REVIEW

Considerable interest in personalized nutrition exists among the general public, policymakers, healthcare organizations and the private sector, but there is also skepticism of its utility. The present review aims to provide a summary of current controversies in the field of nutrigenomics, and to highlight recent research on the potential impact of implementing genetic testing for personalized nutrition in practice.

RECENT FINDINGS

Numerous companies already offer genetic testing for personalized nutrition based on research developments in nutritional genomics. However, controversy exists over whethexr genetics contributes to interindividual responses to diet; the utility of single genetic variants versus genetic risk scores; the ability of DNA-based nutritional advice to elicit positive behavior change and health effects; and whether genetic information makes a difference on the type of dietary advice provided. Potential factors contributing to the discrepant viewpoints are discussed.

SUMMARY

Despite the existing controversies, a solid body of evidence demonstrates that genetic testing for personalized nutrition is a powerful tool to guide dietary recommendations to improve health and performance, and to elicit positive behavior change.

Diet-derived fruit and vegetable metabolites show sex-specific inverse relationships to osteoporosis status

BACKGROUND

The impact of nutrition on the metabolic profile of osteoporosis (OS) is unknown.

OBJECTIVE

Identify biochemical factors driving the association of fruit and vegetable (FV) intakes with OS prevalence using an untargeted metabolomics approach.

DESIGN

Cross-sectional dietary, anthropometric and plasma metabolite data were examined from the Boston Puerto Rican Osteoporosis Study, n = 600 (46-79 yr).

METHODS

Bone mineral density was assessed by DXA. OS was defined by clinical standards. A culturally adapted FFQ assessed usual dietary intake. Principal components analysis (PCA) of 42 FV items created 6 factors. Metabolomic profiles derived from plasma samples were assessed on a commercial platform. Differences in levels of 525 plasma metabolites between disease groups (OS vs no-OS) were compared using logistic regression; and associations with FV intakes by multivariable linear regression, adjusted for covariates. Metabolites significantly associated with OS status or with total FV intake were analyzed for enrichment in various biological pathways using Mbrole 2.0, MetaboAnalyst, and Reactome, using FDR correction of P-values. Correlation coefficients were calculated as Spearman's rho rank correlations, followed by hierarchical clustering of the resulting correlation coefficients using PCA FV factors and sex-specific sets of OS-associated metabolites.

RESULTS

High FV intake was inversely related to OS prevalence (Odds Ratio = 0.73; 95% CI = 0.57, 0.94; P = 0.01). Several biological processes affiliated with the FV-associating metabolites, including caffeine metabolism, carnitines and fatty acids, and glycerophospholipids. Important processes identified with OS-associated metabolites were steroid hormone biosynthesis in women and branched-chain amino acid metabolism in men. Factors derived from PCA were correlated with the OS-associated metabolites, with high intake of dark leafy greens and berries/melons appearing protective in both sexes.

CONCLUSIONS

These data warrant investigation into whether increasing intakes of dark leafy greens, berries and melons causally affect bone turnover and BMD among middle-aged and older adults at risk for osteoporosis via sex-specific metabolic pathways, and how gene-diet interactions alter these sex-specific metabolomic-osteoporosis links. ClinicalTrials.gov Identifier: NCT01231958.

Dissecting Efficacy and Metabolic Characteristic Mechanism of Taxifolin on Renal Fibrosis by Multivariate Approach and Ultra-Performance Liquid Chromatography Coupled With Mass Spectrometry-Based Metabolomics Strategy

Taxifolin (TFN) is an important natural compound with antifibrotic activity; however, its pharmacological mechanism is not clear. In this study, our aim is to gain insight into the effects of TFN and its potential mechanisms in unilateral ureteral obstruction (UUO) animal model using metabolomics approach to identify the metabolic biomarkers and perturbed pathways. Serum metabolomics analysis by UPLC-Q-TOF/MS was carried out to discover the changes in the metabolic profile. It showed that TFN has a significant protective effect on UUO-induced renal fibrosis and a total of 32 potential biomarkers were identified and related to RF progression. Of note, 27 biomarkers were regulated by TFN treatment, which participate in eight metabolic pathways, including phenylalanine, tyrosine and tryptophan biosynthesis, and phenylalanine metabolism. It also showed that metabolomics was a promising strategy to better dissect metabolic characteristics and pharmacological mechanisms of natural compounds by multivariate approach and ultra-performance liquid chromatography coupled with mass spectrometry.

Integrative Analysis of Gene-Specific DNA Methylation and Untargeted Metabolomics Data from the ELEMENT Cohort

Epigenetic modifications, such as DNA methylation, influence gene expression and cardiometabolic phenotypes that are manifest in developmental periods in later life, including adolescence. Untargeted metabolomics analysis provide a comprehensive snapshot of physiological processes and metabolism and have been related to DNA methylation in adults, offering insights into the regulatory networks that influence cellular processes. We analyzed the cross-sectional correlation of blood leukocyte DNA methylation with 3758 serum metabolite features (574 of which are identifiable) in 238 children (ages 8-14 years) from the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) study. Associations between these features and percent DNA methylation in adolescent blood leukocytes at LINE-1 repetitive elements and genes that regulate early life growth (IGF2, H19, HSD11B2) were assessed by mixed effects models, adjusting for sex, age, and puberty status. After false discovery rate correction (FDR q < 0.05), 76 metabolites were significantly associated with LINE-1 DNA methylation, 27 with HSD11B2, 103 with H19, and 4 with IGF2. The ten identifiable metabolites included dicarboxylic fatty acids (five associated with LINE-1 or H19 methylation at q < 0.05) and 1-octadecanoyl-rac-glycerol (q < 0.0001 for association with H19 and q = 0.04 for association with LINE-1). We then assessed the association between these ten known metabolites and adiposity 3 years later. Two metabolites, dicarboxylic fatty acid 17:3 and 5-oxo-7-octenoic acid, were inversely associated with measures of adiposity (P < .05) assessed approximately 3 years later in adolescence. In stratified analyses, sex-specific and puberty-stage specific (Tanner stage = 2 to 5 vs Tanner stage = 1) associations were observed. Most notably, hundreds of statistically significant associations were observed between H19 and LINE-1 DNA methylation and metabolites among children who had initiated puberty. Understanding relationships between subclinical molecular biomarkers (DNA methylation and metabolites) may increase our understanding of genes and biological pathways contributing to metabolic changes that underlie the development of adiposity during adolescence.

Chronological Age Interacts with the Circadian Melatonin Receptor 1B Gene Variation, Determining Fasting Glucose Concentrations in Mediterranean Populations. Additional Analyses on Type-2 Diabetes Risk

Gene-age interactions have not been systematically investigated on metabolic phenotypes and this modulation will be key for a better understanding of the temporal regulation in nutrigenomics. Taking into account that aging is typically associated with both impairment of the circadian system and a decrease in melatonin secretion, we focused on the melatonin receptor 1B (MTNR1B)-rs10830963 C>G variant that has been associated with fasting glucose concentrations, gestational diabetes, and type-2 diabetes. Therefore, our main aim was to investigate whether the association between the MTNR1B-rs10830963 polymorphism and fasting glucose is age dependent. Our secondary aims were to analyze the polymorphism association with type-2 diabetes and explore the gene-pregnancies interactions on the later type-2 diabetes risk. Three Mediterranean cohorts (n = 2823) were analyzed. First, a cross-sectional study in the discovery cohort consisting of 1378 participants (aged 18 to 80 years; mean age 41 years) from the general population was carried out. To validate and extend the results, two replication cohorts consisting of elderly individuals were studied. In the discovery cohort, we observed a strong gene-age interaction (p = 0.001), determining fasting glucose in such a way that the increasing effect of the risk G-allele was much greater in young (p = 5.9 × 10^-10) than in elderly participants (p = 0.805). Consistently, the association of the MTNR1B-rs10830963 polymorphism with fasting glucose concentrations in the two replication cohorts (mean age over 65 years) did not reach statistical significance (p > 0.05 for both). However, in the elderly cohorts, significant associations between the polymorphism and type-2 diabetes at baseline were found. Moreover, in one of the cohorts, we obtained a statistically significant interaction between the MTNR1B polymorphism and the number of pregnancies, retrospectively assessed, on the type-2 diabetes risk. In conclusion, the association of the MTNR1B-rs10830963 polymorphism with fasting glucose is age-dependent, having a greater effect in younger people. However, in elderly subjects, associations of the polymorphism with type-2 diabetes were observed and our exploratory analysis suggested a modulatory effect of the number of past pregnancies on the future type-2 diabetes genetic risk.

The effect of dietary Marula nut meal on the physical properties, proximate and fatty acid content of Japanese quail meat

Soyabean meal (SBM) is the major dietary protein source for the poultry industry in sub-Saharan Africa. Due to inadequate local soyabean production, alternative protein sources are required. Two hundred 9-day old Japanese quail chicks were randomly allocated to grower diets wherein Marula nut meal (MNM) substituted SBM on a crude protein (CP) basis at 0%, 25%, 50%, 75% and 100% and fed for 4 weeks, followed by being fed on similarly formulated finisher diets for 2 weeks, and thereafter they were humanely slaughtered and dressed. Initial pH (pH_i) and ultimate (pH_u), colour, thawing loss (TL), cooking loss (CL), tenderness, proximate and fatty acid (FA) composition of the breast and thigh meat were determined. The results showed that pH_i and pH_u of meat from carcasses of quail fed diet 1 was lower, but had lighter and less red meat than that from counterparts fed diet 5 (P < 0.01). Dietary MNM had no effect (P>0.05) on TL, CL and tenderness of the meat. The ash content of the meat increased with an increase in dietary MNM, but its CP and fat decreased (P < 0.05). In addition, the total saturated FA content of meat from birds fed diet 4 was lower (P < 0.05) than other counterparts. Meat from birds fed diets 1 and 2 had a lower oleic acid (OA) content in comparison to meat from birds fed diets 3, 4 and 5. MNM can potentially be utilised in quail feeds without compromising the physical and proximate properties of the meat. Also, it can be used to produce lean but OA-rich meat with possible potential health benefits to consumers.

Can Meat and Meat-Products Induce Oxidative Stress?

High meat and meat-products consumption has been related to degenerative diseases. In addition to their saturated fatty acids and cholesterol contents, oxidation products generated during their production, storage, digestion, and metabolization have been largely implicated. This review begins by summarizing the concept of meat and meat-products by the main international regulatory agencies while highlighting the nutritional importance of their consumption. The review also dials in the controversy of white/red meat classification and insists in the need of more accurate classification based on adequate scores. Since one of the negative arguments that meat receives comes from the association of its consumption with the increase in oxidative stress, main oxidation compounds (malondialdehyde, thermaloxidized compounds, 4-hydroxy-nonenal, oxysterols, or protein carbonyls) generated during its production, storage, and metabolization, are included as a central aspect of the work. The review includes future remarks addressed to study the effects meat consumption in the frame of diet-gene interactions, stressing the importance of knowing the genetic variables that make individuals more susceptible to a possible oxidative stress imbalance or antioxidant protection. The importance of consumed meat/meat-products in the frame of a personalized nutrition reach in plant-food is finally highlighted considering the importance of iron and plant biophenols on the microbiota abundance and plurality, which in turn affect several aspects of our physiology and metabolism.

Generation of Gene-Knockout Mongolian Gerbils via CRISPR/Cas9 System

The Mongolian gerbil (Meriones unguiculatus), a well-known "multifunctional" experimental animal, plays a crucial role in the research of hearing, cerebrovascular diseases and Helicobacter pylori infection. Although the whole-genome sequencing of Mongolian gerbils has been recently completed, lack of valid gene-editing systems for gerbils largely limited the further usage of Mongolian gerbils in biomedical research. Here, efficient targeted mutagenesis in Mongolian gerbils was successfully conducted by pronuclear injection with Cas9 protein and single-guide RNAs (sgRNAs) targeting Cystatin C (Cst3) or Apolipoprotein A-II (Apoa2). We found that 22 h after human chorionic gonadotropin (hCG) injection, zygote microinjection was conducted, and the injected zygotes were transferred into the pseudopregnant gerbils, which were induced by injecting equine chorionic gonadotropin (eCG) and hCG at a 70 h interval and being caged with ligated male gerbils. We successfully obtained Cst3 and Apoa2 gene knockout gerbils with the knockout efficiencies of 55 and 30.9%, respectively. No off-target effects were detected in all knockout gerbils and the mutations can be germline-transmitted. The absence of CST3 protein was observed in the tissues of homozygous Cst3 knockout (Cst3-KO) gerbils. Interestingly, we found that disruption of the Cst3 gene led to more severe brain damage and neurological deficits after unilateral carotid artery ligation, thereby indicating that the gene modifications happened at both genetic and functional levels. In conclusion, we successfully generated a CRISPR/Cas9 system based genome editing platform for Mongolian gerbils, which provided a foundation for obtaining other genetically modified gerbil models for biomedical research.

Nutrigenetics-personalized nutrition in obesity and cardiovascular diseases

Epidemiological data support the view that both obesity and cardiovascular diseases (CVD) account for a high proportion of total morbidity and mortality in adults throughout the world. Obesity and CVD have complex interplay mechanisms of genetic and environmental factors, including diet. Nutrition is an environmental factor and it has a predominant and recognizable role in health management and in the prevention of obesity and obesity-related diseases, including CVD. However, there is a marked variation in CVD in patients with obesity and the same dietary pattern. The different genetic polymorphisms could explain this variation, which leads to the emergence of the concept of nutrigenetics. Nutritional genomics or nutrigenetics is the science that studies and characterizes gene variants associated with differential response to specific nutrients and relating this variation to various diseases, such as CVD related to obesity. Thus, the personalized nutrition recommendations, based on the knowledge of an individual's genetic background, might improve the outcomes of a specific dietary intervention and represent a new dietary approach to improve health, reducing obesity and CVD. Given these premises, it is intuitive to suppose that the elucidation of diet and gene interactions could support more specific and effective dietary interventions in both obesity and CVD prevention through personalized nutrition based on nutrigenetics. This review aims to briefly summarize the role of the most important genes associated with obesity and CVD and to clarify the knowledge about the relation between nutrition and gene expression and the role of the main nutrition-related genes in obesity and CVD.

Saturated Fats and Health: A Reassessment and Proposal for Food-Based Recommendations: JACC State-of-the-Art Review

The recommendation to limit dietary saturated fatty acid (SFA) intake has persisted despite mounting evidence to the contrary. Most recent meta-analyses of randomized trials and observational studies found no beneficial effects of reducing SFA intake on cardiovascular disease (CVD) and total mortality, and instead found protective effects against stroke. Although SFAs increase low-density lipoprotein (LDL) cholesterol, in most individuals, this is not due to increasing levels of small, dense LDL particles, but rather larger LDL particles, which are much less strongly related to CVD risk. It is also apparent that the health effects of foods cannot be predicted by their content in any nutrient group without considering the overall macronutrient distribution. Whole-fat dairy, unprocessed meat, and dark chocolate are SFA-rich foods with a complex matrix that are not associated with increased risk of CVD. The totality of available evidence does not support further limiting the intake of such foods.

Statin Use Associates With Risk of Type 2 Diabetes via Epigenetic Patterns at ABCG1

Statin is the medication most widely prescribed to reduce plasma cholesterol levels. Yet, how the medication contributes to diabetes risk and impaired glucose metabolism is not clear. This study aims to examine the epigenetic mechanisms of ABCG1 through which statin use associates with risk of type 2 diabetes. We determined the association between the statin use, DNA methylation at ABCG1 and type 2 diabetes/glycemic traits in the Framingham Heart Study Offspring (FHS, n = 2741), with validation in the Women’s Health Initiative Study (WHI, n = 2020). The causal effect of statin use on the risk of type 2 diabetes was examined using a two-step Mendelian randomization approach. Next, based on transcriptome analysis, we determined the links between the medication-associated epigenetic status of ABCG1 and biological pathways on the pathogenesis of type 2 diabetes. Our results showed that DNA methylation levels at cg06500161 of ABCG1 were positively associated with the use of statin, type 2 diabetes and related traits (fasting glucose and insulin) in FHS and WHI. Two-step Mendelian randomization suggested a causal effect of statin use on type 2 diabetes and related traits through epigenetic mechanisms, specifically, DNA methylation at cg06500161. Our results highlighted that gene expression of ABCG1, ABCA1 and ACSL3, involved in both cholesterol metabolism and glycemic pathways, was inversely associated with statin use, CpG methylation, and diabetic signatures. We concluded that DNA methylation site cg06500161 at ABCG1 is a mediator of the association between statins and risk of type 2 diabetes.

Contribution of macronutrients to obesity: implications for precision nutrition

The specific metabolic contribution of consuming different energy-yielding macronutrients (namely, carbohydrates, protein and lipids) to obesity is a matter of active debate. In this Review, we summarize the current research concerning associations between the intake of different macronutrients and weight gain and adiposity. We discuss insights into possible differential mechanistic pathways where macronutrients might act on either appetite or adipogenesis to cause weight gain. We also explore the role of dietary macronutrient distribution on thermogenesis or energy expenditure for weight loss and maintenance. On the basis of the data discussed, we describe a novel way to manage excessive body weight; namely, prescribing personalized diets with different macronutrient compositions according to the individual's genotype and/or enterotype. In this context, the interplay of macronutrient consumption with obesity incidence involves mechanisms that affect appetite, thermogenesis and metabolism, and the outcomes of these mechanisms are altered by an individual's genotype and microbiota. Indeed, the interactions of the genetic make-up and/or microbiota features of a person with specific macronutrient intakes or dietary pattern consumption help to explain individualized responses to macronutrients and food patterns, which might represent key factors for comprehensive precision nutrition recommendations and personalized obesity management.

Current Status of Metabolomic Biomarker Discovery: Impact of Study Design and Demographic Characteristics

Widespread application of omic technologies is evolving our understanding of population health and holds promise in providing precise guidance for selection of therapeutic interventions based on patient biology. The opportunity to use hundreds of analytes for diagnostic assessment of human health compared to the current use of 10–20 analytes will provide greater accuracy in deconstructing the complexity of human biology in disease states. Conventional biochemical measurements like cholesterol, creatinine, and urea nitrogen are currently used to assess health status; however, metabolomics captures a comprehensive set of analytes characterizing the human phenotype and its complex metabolic processes in real-time. Unlike conventional clinical analytes, metabolomic profiles are dramatically influenced by demographic and environmental factors that affect the range of normal values and increase the risk of false biomarker discovery. This review addresses the challenges and opportunities created by the evolving field of clinical metabolomics and highlights features of study design and bioinformatics necessary to maximize the utility of metabolomics data across demographic groups.

Salivary AMY1 Copy Number Variation Modifies Age-Related Type 2 Diabetes Risk

BACKGROUND

Copy number variation (CNV) in the salivary amylase gene (AMY1) modulates salivary α-amylase levels and is associated with postprandial glycemic traits. Whether AMY1-CNV plays a role in age-mediated change in insulin resistance (IR) is uncertain.

METHODS

We measured AMY1-CNV using duplex quantitative real-time polymerase chain reaction in two studies, the Boston Puerto Rican Health Study (BPRHS, n = 749) and the Genetics of Lipid-Lowering Drug and Diet Network study (GOLDN, n = 980), and plasma metabolomic profiles in the BPRHS. We examined the interaction between AMY1-CNV and age by assessing the relationship between age with glycemic traits and type 2 diabetes (T2D) according to high or low copy numbers of the AMY1 gene. Furthermore, we investigated associations between metabolites and interacting effects of AMY1-CNV and age on T2D risk.

RESULTS

We found positive associations of IR with age among subjects with low AMY1-copy-numbers in both studies. T2D was marginally correlated with age in participants with low AMY1-copy-numbers but not with high AMY1-copy-numbers in the BPRHS. Metabolic pathway enrichment analysis identified the pentose metabolic pathway based on metabolites that were associated with both IR and the interactions between AMY1-CNV and age. Moreover, in older participants, high AMY1-copy-numbers tended to be associated with lower levels of ribonic acid, erythronic acid, and arabinonic acid, all of which were positively associated with IR.

CONCLUSIONS

We found evidence supporting a role of AMY1-CNV in modifying the relationship between age and IR. Individuals with low AMY1-copy-numbers tend to have increased IR with advancing age.

Metabolomic Links between Sugar-Sweetened Beverage Intake and Obesity

BACKGROUND

Sugar-sweetened beverage (SSB) consumption is highly associated with obesity, but the metabolic mechanism underlying this correlation is not understood.

OBJECTIVE

Our objective was to examine metabolomic links between SSB intake and obesity to understand metabolic mechanisms.

DESIGN

We examined the association of plasma metabolomic profiles with SSB intake and obesity risk in 781 participants, aged 45-75 y, in the Boston Puerto Rican Health Study (BPRHS) using generalized linear models, controlling for potential confounding factors. Based on identified metabolites, we conducted pathway enrichment analysis to identify potential metabolic pathways that link SSB intake and obesity risk. Variants in genes encoding enzymes known to function in identified metabolic pathways were examined for their interactions with SSB intake on obesity.

RESULTS

SSB intake was correlated with BMI (β = 0.607, P=0.045). Among 526 measured metabolites, 86 showed a significant correlation with SSB intake and 148 with BMI (P ≤ 0.05); 28 were correlated with both SSB intake and BMI (P ≤ 0.05). Pathway enrichment analysis identified the phosphatidylcholine and lysophospholipid pathways as linking SSB intake to obesity, after correction for multiple testing. Furthermore, 8 of 10 genes functioning in these two pathways showed strong interaction with SSB intake on BMI. Our results further identified participants who may exhibit an increased risk of obesity when consuming SSB.

CONCLUSIONS

We identified two key metabolic pathways that link SSB intake to obesity, revealing the potential of phosphatidylcholine and lysophospholipid to modulate how SSB intake can increase obesity risk. The interaction between genetic variants related to these pathways and SSB intake on obesity further supports the mechanism.

DNA methylation markers in obesity, metabolic syndrome, and weight loss

The fact that not all individuals exposed to the same environmental risk factors develop obesity supports the hypothesis of the existence of underlying genetic and epigenetic elements. There is suggestive evidence that environmental stimuli, such as dietary pattern, particularly during pregnancy and early life, but also in adult life, can induce changes in DNA methylation predisposing to obesity and related comorbidities. In this context, the DNA methylation marks of each individual have emerged not only as a promising tool for the prediction, screening, diagnosis, and prognosis of obesity and metabolic syndrome features, but also for the improvement of weight loss therapies in the context of precision nutrition. The main objectives in this field are to understand the mechanisms involved in transgenerational epigenetic inheritance, and featuring the nutritional and lifestyle factors implicated in the epigenetic modifications. Likewise, DNA methylation modulation caused by diet and environment may be a target for newer therapeutic strategies concerning the prevention and treatment of metabolic diseases.

Exploring Coronary Artery Disease GWAs Targets With Functional Links to Immunometabolism

Finding genetic variants that cause functional disruption or regulatory change among the many implicated GWAs variants remains a key challenge to translating the findings from GWAs to therapeutic treatments. Defining the causal mechanisms behind the variants require functional screening experiments that can be complex and costly. Prioritizing variants for functional characterization using techniques that capture important functional and regulatory elements can assist this. The genetic architecture of complex traits such as cardiovascular disease and type II diabetes comprise an enormously large number of variants of small effect contributing to heritability and spread throughout the genome. This makes it difficult to distinguish which variants or core genes are most relevant for prioritization and how they contribute to the regulatory networks that become dysregulated leading to disease. Despite these challenges, recent GWAs for CAD prioritized genes associated with lipid metabolism, coagulation and adhesion along with novel signals related to innate immunity, adipose tissue and, vascular function as important core drivers of risk. We focus on three examples of novel signals associated with CAD which affect risk through missense or UTR mutations indicating their potential for therapeutic modification. These variants play roles in adipose tissue function vascular function and innate immunity which form the cornerstones of immuno-metabolism. In addition we have explored the putative, but potentially important interactions between the environment, specifically food and nutrition, with respect to key processes.

FADS1-FADS2 genetic polymorphisms are associated with fatty acid metabolism through changes in DNA methylation and gene expression

Background

Genome-wide association studies (GWASs) have shown that genetic variants are important determinants of free fatty acid levels. The mechanisms underlying the associations between genetic variants and free fatty acid levels are incompletely understood. Here, we aimed to identify genetic markers that could influence diverse fatty acid levels in a Chinese population and uncover the molecular mechanisms in terms of DNA methylation and gene expression.

Results

We identified strong associations between single-nucleotide polymorphisms (SNPs) in the fatty acid desaturase (FADS) region and multiple polyunsaturated fatty acids. Expression quantitative trait locus (eQTL) analysis of rs174570 on FADS1 and FADS2 mRNA levels proved that minor allele of rs174570 was associated with decreased FADS1 and FADS2 expression levels (P < 0.05). Methylation quantitative trait locus (mQTL) analysis of rs174570 on DNA methylation levels in three selected regions of FADS region showed that the methylation levels at four CpG sites in FADS1, one CpG site in intragenic region, and three CpG sites in FADS2 were strongly associated with rs174570 (P < 0.05). Then, we demonstrated that methylation levels at three CpG sites in FADS1 were negatively associated with FADS1 and FADS2 expression, while two CpG sites in FADS2 were positively associated with FADS1 and FADS2 expression. Using mediation analysis, we further show that the observed effect of rs174570 on gene expression was tightly correlated with the effect predicted through association with methylation.

Conclusions

Our findings suggest that genetic variants in the FADS region are major genetic modifiers that can regulate fatty acid metabolism through epigenetic gene regulation.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0545-5) contains supplementary material, which is available to authorized users.

Dietary epicatechin improves survival and delays skeletal muscle degeneration in aged mice

We recently reported that epicatechin, a bioactive compound that occurs naturally in various common foods, promoted general health and survival of obese diabetic mice. It remains to be determined whether epicatechin extends health span and delays the process of aging. In the present study, epicatechin or its analogue epigallocatechin gallate (EGCG) (0.25% w/v in drinking water) was administered to 20-mo-old male C57BL mice fed a standard chow. The goal was to determine the antiaging effect. The results showed that supplementation with epicatechin for 37 wk strikingly increased the survival rate from 39 to 69%, whereas EGCG had no significant effect. Consistently, epicatechin improved physical activity, delayed degeneration of skeletal muscle (quadriceps), and shifted the profiles of the serum metabolites and skeletal muscle general mRNA expressions in aging mice toward the profiles observed in young mice. In particular, we found that dietary epicatechin significantly reversed age-altered mRNA and protein expressions of extracellular matrix and peroxisome proliferator–activated receptor pathways in skeletal muscle, and reversed the age-induced declines of the nicotinate and nicotinamide pathway both in serum and skeletal muscle. The present study provides evidence that epicatechin supplementation can exert an antiaging effect, including an increase in survival, an attenuation of the aging-related deterioration of skeletal muscles, and a protection against the aging-related decline in nicotinate and nicotinamide metabolism.—Si, H., Wang, X., Zhang, L., Parnell, L. D., Ahmed, B., LeRoith, T., Ansah, T.-A., Zhang, L., Li, J., Ordovás, J. M., Si, H., Liu, D., Lai, C.-Q. Dietary epicatechin improves survival and delays skeletal muscle degeneration in aged mice.