Ancestry specific associations of a genetic risk score, dietary patterns and metabolic syndrome: a longitudinal ARIC study

Investigation of the interaction between genetic risk score (GRS) and fatty acid quality indices on metabolic syndrome among overweight and obese women

BACKGROUND AND AIM

Metabolic syndrome is one of the major public-health challenges, affecting one-quarter of the world population. Fatty acid quality indices are novel determinants of this disease and their interactions with genetic factors may have an impact on metabolic syndrome risk. Therefore, we aimed to investigate the interaction between genetic risk score (GRS) and fatty acid quality indices with metabolic syndrome (MetS) among overweight and obese women.

METHODS

In the present cross-sectional study, 279 overweight and obese women (18-48 years old) were included. Several anthropometric measurements such as weight, height, body mass index (BMI), waist circumference (WC), and body fat percent (BF%) were measured. Also, systolic and diastolic blood pressure (SBP and DBP) were measured. Biochemical determination was performed for fasting blood glucose (FBS), triglyceride (TG), and high-density lipoprotein (HDL). MetS was determined according to National Cholesterol Education Program (NCEP ATP III) criteria. Dietary intake was evaluated by a validated and reliable 147-item semi-quantitative food frequency questionnaire. Cholesterol-saturated fat index (CSI) and the ratio of omega-6/omega-3 (ω-6/ω-3) essential fatty acids were considered as fat quality indices. The salting-out method was used to extract the total DNA. The unweighted GRS was calculated using the risk alleles of the three single nucleotide polymorphisms. The total average GRS value was 2 and the sum of the risk alleles of the 3 polymorphisms was 6.

RESULT

The results of our analysis showed that after controlling for age, energy intake, BMI, and physical activity, there was a positive interaction between T2 of GRS and T2 of N6/N3 ratio on WC (β = 7.95, 95%CI = 0.83,15.08, P = 0.029), T3 of GRS and T2 of N6/N3 ratio on DBP (β = 5.93, 95%CI= -0.76,12.63, P = 0.083), and FBS (β = 6.47, 95%CI = 0.59,13.53, P = 0.073), T3 of GRS and T3 of N6/N3 ratio on TG (β = 54.42, 95%CI = 1.76,107.08, P = 0.043), and T3 of GRS and T3 of CSI on BF% (β = 3.55, 95%CI= -0.35,7.45, P = 0.075). Also T2 of GRS in the interaction with T3 of CSI leads to an decrease - 8.35 mg/dl in HDL level after adjustment in (β= -8.35, 95%CI= -17.34,0.62, P = 0.068).

CONCLUSION

It seems the interaction of GRS and fatty acid quality indices is positively associated with several components of metabolic syndrome such as WC, TG and BF%. Our findings are of importance to public health, considering the high consumption of foods that are high on fatty acids. Conflicting evidence of many previous studies regarding the effect of fat intake and obesity and cardiovascular diseases could be because of the gene-diet interactions and genetic heterogeneity across various ethnic groups. Hence, the synergism effect of genetic and dietay intakes should be considered in future studies.

A review of dairy food intake for improving health among black adults in the US

The adult life stage encompasses a range of new experiences, opportunities, and responsibilities that impact health and well-being. During this life stage, health disparities continue to increase for Black Americans, with Black adults having a disproportionate burden of obesity, chronic diseases, comorbidities, and worse treatment outcomes compared to their White peers. While many of the underlying factors for these disparities can be linked to longstanding sociopolitical factors such as systemic racism, food insecurity, and poor access to healthcare, there are also several modifiable risk factors that are known to significantly impact health outcomes, such as improving diet quality, increasing physical activity, and not smoking. Of all the modifiable risk factors known to impact health, improving dietary habits is the factor most consistently associated with better outcomes for body weight and chronic disease. Of the major food groups recommended by the 2020-2025 Dietary Guidelines for Americans (DGA) for achieving healthier dietary patterns, dairy foods have a nutrient profile which matches most closely to what Black Americans are inadequately consuming (e.g., vitamin A, vitamin D, calcium, magnesium). However, Black adults tend to consume less than half the recommended daily servings of dairy foods, in part, due to issues with lactose intolerance, making higher intake of dairy foods an ideal target for improving diet quality and health in this population. This review examines the current body of evidence exploring the links between dairy intake, obesity, cardiometabolic disease risk, chronic kidney disease, and the most common types of cancer, with a special focus on health and disparities among Black adults. Overall, the evidence from most systematic reviews and/or meta-analyses published in the last decade on dairy intake and health outcomes has been conducted on White populations and largely excluded research on Black populations. The findings from this extensive body of research indicate that when teamed with an energy-restricted diet, meeting or exceeding the DGA recommended 3 daily servings of dairy foods is associated with better body weight and composition outcomes and lower rates of most common chronic diseases than lower intake (<2 servings per day). In addition to the number of daily servings consumed, the specific types (e.g., milk, yogurt, cheese) and subtypes (e.g., low-fat, fermented, fortified) consumed have also been shown to play major roles in how these foods impact health. For example, higher intake of fermented dairy foods (e.g., yogurt) and vitamin D fortified dairy products appear to have the most protective effects for reducing chronic disease risk. Along with lactose-free milk and cheese, yogurt is also generally low in lactose, making it an excellent option for individuals with lactose intolerance, who are trying to meet the DGA recommendations for dairy food intake.

Metabolic Syndrome: An Overview on Its Genetic Associations and Gene-Diet Interactions

Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors that includes central obesity, hyperglycemia, hypertension, and dyslipidemias and whose inter-related occurrence may increase the odds of developing type 2 diabetes and cardiovascular diseases. MetS has become one of the most studied conditions, nevertheless, due to its complex etiology, this has not been fully elucidated. Recent evidence describes that both genetic and environmental factors play an important role on its development. With the advent of genomic-wide association studies, single nucleotide polymorphisms (SNPs) have gained special importance. In this review, we present an update of the genetics surrounding MetS as a single entity as well as its corresponding risk factors, considering SNPs and gene-diet interactions related to cardiometabolic markers. In this study, we focus on the conceptual aspects, diagnostic criteria, as well as the role of genetics, particularly on SNPs and polygenic risk scores (PRS) for interindividual analysis. In addition, this review highlights future perspectives of personalized nutrition with regard to the approach of MetS and how individualized multiomics approaches could improve the current outlook.

The Role of Artificial Intelligence in Deciphering Diet-Disease Relationships: Case Studies

Modernization of society from a rural, hunter-gatherer setting into an urban and industrial habitat, with the associated dietary changes, has led to an increased prevalence of cardiometabolic and additional noncommunicable diseases, such as cancer, inflammatory bowel disease, and neurodegenerative and autoimmune disorders. However, while dietary sciences have been rapidly evolving to meet these challenges, validation and translation of experimental results into clinical practice remain limited for multiple reasons, including inherent ethnic, gender, and cultural interindividual variability, among other methodological, dietary reporting-related, and analytical issues. Recently, large clinical cohorts with artificial intelligence analytics have introduced new precision and personalized nutrition concepts that enable one to successfully bridge these gaps in a real-life setting. In this review, we highlight selected examples of case studies at the intersection between diet-disease research and artificial intelligence. We discuss their potential and challenges and offer an outlook toward the transformation of dietary sciences into individualized clinical translation.

Differences in dietary patterns related to metabolic health by gut microbial enterotypes of Korean adults

Diet has a profound impact on the progression of metabolic syndrome (MetS) into various diseases. The gut microbiota could modulate the effect of diet on metabolic health. We examined whether dietary patterns related to MetS differed according to gut microbial enterotypes among 348 Korean adults aged 18-60 years recruited between 2018∼2021 in a cross-sectional study. The enterotype of each participant was identified based on 16S rRNA gut microbiota data. The main dietary pattern predicting MetS (MetS-DP) of each enterotype was derived using reduced-rank regression (RRR) models. In the RRR models, 27 food group intakes assessed by a semi-quantitative food frequency questionnaire and MetS prediction markers including triglyceride to high-density lipoprotein cholesterol (TG/HDL) ratio and homeostatic model assessment for insulin resistance (HOMA-IR) were used as predictor and response variables, respectively. The MetS-DP extracted in Bacteroides enterotype (B-type) was characterized by high consumption of refined white rice and low consumption of eggs, vegetables, and mushrooms. The MetS-DP derived among Prevotella enterotype (P-type) was characterized by a high intake of sugary food and low intakes of bread, fermented legumes, and fermented vegetables. The MetS-DP of B-type was positively associated with metabolic unhealthy status (OR T3 vs. T1 = 3.5; 95% CI = 1.5-8.2), comparing the highest tertile to the lowest tertile. Although it was not significantly associated with overall metabolic unhealthy status, the MetS-DP of P-type was positively associated with hyperglycemia risk (OR T3 vs. T1 = 6.2; 95% CI = 1.6-24.3). These results suggest that MetS-DP may differ according to the gut microbial enterotype of each individual. If such associations are found to be causal, personalized nutrition guidelines based on the enterotypes could be recommended to prevent MetS.

Associations between dietary patterns and the metabolic syndrome in older adults in New Zealand: the REACH study

The metabolic syndrome is common in older adults and may be modified by the diet. The aim of this study was to examine associations between a posteriori dietary patterns and the metabolic syndrome in an older New Zealand population. The REACH study (Researching Eating, Activity, and Cognitive Health) included 366 participants (aged 65-74 years, 36 % male) living independently in Auckland, New Zealand. Dietary data were collected using a 109-item FFQ with demonstrated validity and reproducibility for assessing dietary patterns using principal component analysis. The metabolic syndrome was defined by the National Cholesterol Education Program Adult Treatment Panel III. Associations between dietary patterns and the metabolic syndrome, adjusted for age, sex, index of multiple deprivation, physical activity, and energy intake were analysed using logistic regression analysis. Three dietary patterns explained 18 % of dietary intake variation - 'Mediterranean style' (salad/leafy cruciferous/other vegetables, avocados/olives, alliums, nuts/seeds, shellfish and white/oily fish, berries), 'prudent' (dried/fresh/frozen legumes, soya-based foods, whole grains and carrots) and 'Western' (processed meat/fish, sauces/condiments, cakes/biscuits/puddings and meat pies/hot chips). No associations were seen between 'Mediterranean style' (OR = 0·75 (95 % CI 0·53, 1·06), P = 0·11) or 'prudent' (OR = 1·17 (95 % CI 0·83, 1·59), P = 0·35) patterns and the metabolic syndrome after co-variate adjustment. The 'Western' pattern was positively associated with the metabolic syndrome (OR = 1·67 (95 % CI 1·08, 2·63), P = 0·02). There was also a small association between an index of multiple deprivation (OR = 1·04 (95 % CI 1·02, 1·06), P < 0·001) and the metabolic syndrome. This cross-sectional study provides further support for a Western dietary pattern being a risk factor for the metabolic syndrome in an older population.

2022 Prevention of chronic non-communicable diseases in Of the Russian Federation. National guidelines

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Structural Equation Modelling for Predicting the Relative Contribution of Each Component in the Metabolic Syndrome Status Change

Understanding the factor weighting in the development of metabolic syndrome (MetS) may help to predict the progression for cardiovascular and metabolic diseases. Thus, the aim of this study was to develop a confirmatory model to describe and explain the direct and indirect effect of each component in MetS status change. A total of 3581 individuals diagnosed with MetS, aged 18−102 years, were selected between January 2019 and December 2020 from a community-representative sample of Portuguese adults in a north-eastern Portuguese region to test the model’s goodness of fit. A structural equation modelling (SEM) approach and a two-way ANOVA (age × body composition) were performed to compare the relative contribution of each MetS component using joint interim statement (JIS). Waist circumference (β = 0.189−0.373, p < 0.001), fasting glucose (β = 0.168−0.199, p < 0.001) and systolic blood pressure (β = 0.140−0.162, p < 0.001) had the highest direct effect on the change in MetS status in the overall population and concerning both sexes. Moreover, diastolic blood pressure (DBP), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-c) had a low or non-significant effect. Additionally, an indirect effect was reported for age and body composition involving the change in MetS status. The findings may suggest that other components with higher specificity and sensitivity should be considered to empirically validate the harmonised definition of MetS. Current research provides the first multivariate model for predicting the relative contribution of each component in the MetS status change, specifically in Portuguese adults.

From biobanking to personalized prevention of obesity, diabetes and metabolic syndrome

The growing prevalence of metabolic disorders creates an increasing demand for novel approaches to their prevention and therapy. Novel genetic diagnostic technologies are developed every year, which makes it possible to identify people who are at the highest genetic risk of diabetes, non-alcoholic fatty liver disease, and metabolic syndrome. Early intervention strategies can be used to prevent metabolic disorders in this group of people. Genetic risk scores (GRSs) are a powerful tool to identify people with a high genetic risk. Millions of genetic variants are analyzed in genome-wide association studies in order to combine them into GRSs. It has become possible to store and process such huge amounts of data with the help of biobanks, where biological samples are stored according to international standards. Genetic studies include more and more people every year that increases the predictive power of GRSs. It has already been demonstrated that the use of GRSs makes future preventive measures more effective. In the near future, GRSs are likely to become part of clinical guidelines so that they can be widely used to identify people at high risk for metabolic syndrome and its components.

Modulation of gut microbiota and markers of metabolic syndrome in mice on cholesterol and fat enriched diet by butterfly pea flower kombucha

Clitoria ternatea, with an alternative name, Butterfly pea, is increasingly being explored for medical purposes and the development of a wide range of processed products. This study aimed to incorporate Butterfly pea into an innovative probiotic drink through a symbiotic culture of bacteria and yeast (SCOBY) fermentation and to evaluate the biological activity. The benefits of the drink, referred to as butterfly pea flower kombucha (KBPF) was determined in vitro and in metabolically disorder mice that receive a diet rich in cholesterol and fat (CFED). Forty white male were categorized into four groups, i.e., A = Control/Normal Diet; B = CFED alone; C = CFED + KBPF 65 mg/kg BW (Body Weight); D = CFED + KBPF 130 mg/kg BW, and then sacrificed after 6 weeks of intervention. Seventy-nine secondary metabolite compounds were successfully identified in KBPF using LC-HRMS. In vitro studies showed the potential activity of KBPF in inhibiting not only ABTS, but also lipid (lipase) and carbohydrate (α-amylase, α-glucosidase) hydrolyzing enzymes to levels similar to acarbose control at 50–250 μg/mL. In the in vivo study, the administration of KBPF (130 mg/kg BW) significantly alleviated metabolic disorders caused by high-fat diet. Specifically, lipid profile (HDL, LDL, TC, TG), blood glucose, markers of oxidative stress (SOD liver), metabolic enzymes (lipase, amylase), and markers of inflammation (PGC-1α, TNF-α, and IL-10) were in most cases restored to normal values. Additionally, the gut microbiota community analysis showed that KBPF has a positive effect (p = 0.01) on both the Bacteroidetes phylum and the Firmicutes phylum. The new KBPF drink is a promising therapeutic functional food for preventing metabolic diseases.

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Clitoria ternatea or Butterfly pea flower processed or innovated into a functional probiotic drink, namely KBPF.

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A total of 79 Secondary metabolite compounds of KBPF were successfully identified.

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In vitro studies showed the potential activity of KBPF in inhibiting ABTS, lipase, α-glucosidase, and α-amylase.

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Administering a dose of 130 mg/kg BW KBPF was significantly promising in the alleviation of biomarker metabolic disorders with immunomodulatory effects.

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By modulating the diversity of the gut microbiome, KBPF can be a promising nutraceutical in preventing metabolic syndrome with inflammatory diseases.

Recent Progress in Metabolic Syndrome Research and Therapeutics

Metabolic syndrome (MetS) is a well-defined yet difficult-to-manage disease entity. Both the precipitous rise in its incidence due to contemporary lifestyles and the growing heterogeneity among affected populations present unprecedented challenges. Moreover, the predisposed risk for developing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in populations with MetS, and the viral impacts on host metabolic parameters, underscores the need to investigate this mechanism thoroughly. Recent investigations of metabolomics and proteomics have revealed not only differentially expressed substances in MetS, but also the consequences of diet consumption and physical activity on energy metabolism. These variations in metabolites, as well as protein products, also influence a wide spectrum of host characteristics, from cellular behavior to phenotype. Research on the dysregulation of gut microbiota and the resultant inflammatory status has also contributed to our understanding of the underlying pathogenic mechanisms. As for state-of-the-art therapies, advancing depictions of the bio-molecular landscape of MetS have emerged and now play a key role in individualized precision medicine. Fecal microbiota transplantation, aiming to restore the host's homeostasis, and targeting of the bile acid signaling pathway are two approaches to combatting MetS. Comprehensive molecular inquiries about MetS by omics measures are mandatory to facilitate the development of novel therapeutic modalities.