Modulation of the Association between the PEPD Variant and the Risk of Type 2 Diabetes by n-3 Fatty Acids in Chinese Hans

Triangulating nutrigenomics, metabolomics and microbiomics toward personalized nutrition and healthy living

The unique physiological and genetic characteristics of individuals influence their reactions to different dietary constituents and nutrients. This notion is the foundation of personalized nutrition. The field of nutrigenetics has witnessed significant progress in understanding the impact of genetic variants on macronutrient and micronutrient levels and the individual's responsiveness to dietary intake. These variants hold significant value in facilitating the development of personalized nutritional interventions, thereby enabling the effective translation from conventional dietary guidelines to genome-guided nutrition. Nevertheless, certain obstacles could impede the extensive implementation of individualized nutrition, which is still in its infancy, such as the polygenic nature of nutrition-related pathologies. Consequently, many disorders are susceptible to the collective influence of multiple genes and environmental interplay, wherein each gene exerts a moderate to modest effect. Furthermore, it is widely accepted that diseases emerge because of the intricate interplay between genetic predisposition and external environmental influences. In the context of this specific paradigm, the utilization of advanced "omic" technologies, including epigenomics, transcriptomics, proteomics, metabolomics, and microbiome analysis, in conjunction with comprehensive phenotyping, has the potential to unveil hitherto undisclosed hereditary elements and interactions between genes and the environment. This review aims to provide up-to-date information regarding the fundamentals of personalized nutrition, specifically emphasizing the complex triangulation interplay among microbiota, dietary metabolites, and genes. Furthermore, it highlights the intestinal microbiota's unique makeup, its influence on nutrigenomics, and the tailoring of dietary suggestions. Finally, this article provides an overview of genotyping versus microbiomics, focusing on investigating the potential applications of this knowledge in the context of tailored dietary plans that aim to improve human well-being and overall health.

Lipid extract from blue mussel (Mytilus edulis) improves glycemic traits in Chinese type 2 diabetic mellitus patients: a double-blind randomized controlled trial

BACKGROUND

Studies have shown that blue mussel lipid extract (BMLE) has strong anti-inflammatory activity in both rheumatoid arthritis patients and animal arthritis models. Chronic inflammation was closely related to type 2 diabetes mellitus (T2DM). Though the beneficial effects cannot be completely attributed to n-3 polyunsaturated fatty acids, the aim of this study was to investigate whether BMLE can improve glycemic traits of T2DM patients.

METHOD

In a double-blind randomized controlled trial, 133 Chinese T2DM participants were randomized to either fish oil (FO, n = 44), BMLE (n = 44), or corn oil (CO, n = 45) groups for 60 days. The participants were asked to take the corresponding oil capsules (two capsules per day, 0.8 g per capsule), which provided 1.6 g day^-1 of FO (29.9% eicosapentaenoic acid + 20.4% docosahexaenoic acid), BMLE (20.7% eicosapentaenoic acid + 26.7% docosahexaenoic acid), or CO (53.5% linoleic acid).

RESULTS

The fasting serum concentration of insulin (P = 0.005) and the homeostasis model of insulin resistance (P = 0.026) were significantly decreased in the BMLE group, whereas no significant change was found in the FO or CO groups. There was no significant difference between groups on serum glycosylated hemoglobin. Tumor necrosis factor-α was significantly decreased in the BMLE group (P = 0.003), but not in the FO or CO groups. A significant decrease of interleukin-1β was observed in the BMLE and CO groups (P = 0.004 and P = 0.011 respectively), but not in the FO group. The total cholesterol was significantly decreased in the BMLE and CO groups (P < 0.001 and P < 0.001 respectively), but not in the FO group. Triacylglycerol was significantly decreased in the BMLE group (P = 0.007), but not in the FO or CO groups. High-density lipoprotein cholesterol was significantly lower in the BMLE and CO groups than in the FO group (P = 0.003).

CONCLUSION

Blue mussel lipid supplements improved glycemic traits, inflammatory cytokines, and lipids profile in Chinese T2DM patients (Chinese Clinical Trial Registration number: ChiCTR1900025617). © 2022 Society of Chemical Industry.

Omega-3 index and type 2 diabetes: Systematic review and meta-analysis

BACKGROUND AND OBJECTIVES

The relationship between omega-3 index and type 2 diabetes (T2D) is not well established. It is unclear if the change of omega-3 index will affect T2D. Aiming of the present systematic review was to elucidate the correlation between omega-3 index and T2D.

METHODS AND STUDY DESIGN

A comprehensive search on PubMed, EMBASE and Web of Science (from 1948 to May 2021) was conducted. The overall effect size (standard mean difference) was combined using a random-effect model.

RESULTS

Eight eligible case-control studies were identified, and there were 1,357 patients with T2D and 1,616 non-diabetic controls. The result showed that the omega-3 index was significantly lower in diabetic cases than that in controls (SMD= -1.31; 95% confidence interval (CI): -1.40, -1.22), but with significant heterogeneity (I² = 99.0%). In subgroup analysis based on race, a negative correlation was found in Asians (SMD = -1.71; 95% CI: -1.82, -1.60), and heterogeneity was substantially decreased (I²=0).

CONCLUSIONS

omega-3 index is negatively correlated with T2D, which indicated that increased dietary intake of omega-3 fatty acids might have beneficial on T2D prevention.

Progress in Defining the Genetic Contribution to Type 2 Diabetes in Individuals of East Asian Ancestry

PURPOSE OF REVIEW

Prevalence of type 2 diabetes (T2D) and progression of complications differ between worldwide populations. While obesity is a major contributing risk factor, variations in physiological manifestations, e.g., developing T2D at lower body mass index in some populations, suggest other contributing factors. Early T2D genetic associations were mostly discovered in European ancestry populations. This review describes the progression of genetic discoveries associated with T2D in individuals of East Asian ancestry in the last 10 years and highlights the shared genetic susceptibility between the population groups and additional insights into genetic contributions to T2D.

RECENT FINDINGS

Through increased sample size and power, new genetic associations with T2D were discovered in East Asian ancestry populations, often with higher allele frequencies than European ancestry populations. As we continue to generate maps of T2D-associated variants across diverse populations, there will be a critical need to expand and diversify other omics resources to enable integration for clinical translation.

Fatty acids and cardiometabolic health: a review of studies in Chinese populations

Rapid nutrition transition from plant-based traditional diet to westernized diet has led to dramatically heightening burdens of cardiometabolic diseases in China in past decades. Recently, national surveys reported that poor dietary quality including low marine n-3 fatty acids and high intakes of red meat and processed meat was associated with considerably elevated cardiometabolic deaths. Previous studies mainly from Western population-based cohorts have indicated that not only fat quantity but also quality linked with different cardiometabolic outcomes. Compared with Western peoples, Asian peoples, including Chinese, are known to have different dietary patterns and lifestyle, as well as genetic heterogeneities, which may modify fatty acid metabolism and disease susceptibility in certain degree. To date, there were limited prospective studies investigating the relationships between fatty acids and cardiometabolic disease outcomes in Chinese, and most existing studies were cross-sectional nature and within one or two region(s). Notably, shifting dietary patterns could change not only amount, types, and ratio of fatty acids accounting for overall energy intake, but also their food sources and ratio to other macronutrients. Moreover, large geographic and urban-rural variations in prevalence of cardiometabolic diseases among Chinese may also reflect the effects of socioeconomic development and local diets on health status. Therefore, current review will summarize available literatures with more focus on the Chinese-based studies which may extend current knowledge about the roles of fatty acids in pathogenesis of cardiometabolic diseases for Asian populations and also provide useful information for trans-ethnic comparisons with other populations.

Prioritization of Variants for Investigation of Genotype-Directed Nutrition in Human Superpopulations

Dietary guidelines recommended by key health agencies are generally designed for a global population. However, ethnicity affects human disease and environment-gene interactions, including nutrient intake. Historically, isolated human populations with different genetic backgrounds have adapted to distinct environments with varying food sources. Ethnicity is relevant to the interaction of food intake with genes and disease susceptibility; yet major health agencies generally do not recommend food and nutrients codified by population genotypes and their frequencies. In this paper, we have consolidated published nutrigenetic variants and examine their frequencies in human superpopulations to prioritize these variants for future investigation of population-specific genotype-directed nutrition. The nutrients consumed by individuals interact with their genome and may alter disease risk. Herein, we searched the literature, designed a data model, and manually curated hundreds of papers. The resulting database houses 101 variants that reached significance (p < 0.05), from 35 population studies. Nutrigenetic variants associated with modified nutrient intake have the potential to reduce the risk of colorectal cancer, obesity, metabolic syndrome, type 2 diabetes, and several other diseases. Since many nutrigenetic studies have identified a major variant in some populations, we suggest that superpopulation-specific genotype-directed nutrition modifications be prioritized for future study and evaluation. Genotype-directed nutrition approaches to dietary modification have the potential to reduce disease risk in select human populations.

Linking of metabolomic biomarkers with cardiometabolic health in Chinese population

Due to rapid nutrition transitions, the prevalence of cardiometabolic diseases, such as metabolic syndrome, type 2 diabetes, and cardiovascular diseases, has been increasing at an alarming rate in the Chinese population. Moreover, Asians, including Chinese, have been hypothesized to have a higher susceptibility to cardiometabolic diseases than Caucasians. Early prediction and prevention are key to controlling this epidemic trend; to this end, the identification of novel biomarkers is critical to reflect environmental exposure, as well as to reveal endogenous metabolic and pathophysiologic mechanisms. The emerging "omics" technologies, especially metabolomics, offer a unique opportunity to provide novel signatures or fingerprints to understand the effects of genetic and non-genetic factors on cardiometabolic health. During the past two decades, metabolomic approaches have been increasingly used in various epidemiological studies, primarily in Western populations. Although the field is still in its early stages, some studies have tried to identify novel compounds or confirm their metabolites and associations with cardiometabolic diseases in Chinese populations, including amino acids, fatty acids, acylcarnitines and other metabolites. Despite major efforts to discover novel biomarkers for disease prediction or intervention, the limits in current study design, analytical platforms, and data processing approaches are challenges in metabolomic research worldwide. Therefore, future research with more advanced technologies, rigorous study designs, standardized detection and analytic approaches, and integrated data from multiomics approaches are essential to evaluate the feasibility of using metabolomics in clinical settings. Finally, the functional roles and underlying biological mechanisms of metabolomic biomarkers should be elucidated by future mechanistic research.

Localization of adaptive variants in human genomes using averaged one-dependence estimation

Statistical methods for identifying adaptive mutations from population genetic data face several obstacles: assessing the significance of genomic outliers, integrating correlated measures of selection into one analytic framework, and distinguishing adaptive variants from hitchhiking neutral variants. Here, we introduce SWIF(r), a probabilistic method that detects selective sweeps by learning the distributions of multiple selection statistics under different evolutionary scenarios and calculating the posterior probability of a sweep at each genomic site. SWIF(r) is trained using simulations from a user-specified demographic model and explicitly models the joint distributions of selection statistics, thereby increasing its power to both identify regions undergoing sweeps and localize adaptive mutations. Using array and exome data from 45 ‡Khomani San hunter-gatherers of southern Africa, we identify an enrichment of adaptive signals in genes associated with metabolism and obesity. SWIF(r) provides a transparent probabilistic framework for localizing beneficial mutations that is extensible to a variety of evolutionary scenarios.

Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes: systematic review and findings from European Prospective Investigation into Cancer (EPIC)-InterAct

Background: Gene-diet interactions have been reported to contribute to the development of type 2 diabetes (T2D). However, to our knowledge, few examples have been consistently replicated to date.Objective: We aimed to identify existing evidence for gene-macronutrient interactions and T2D and to examine the reported interactions in a large-scale study.Design: We systematically reviewed studies reporting gene-macronutrient interactions and T2D. We searched the MEDLINE, Human Genome Epidemiology Network, and WHO International Clinical Trials Registry Platform electronic databases to identify studies published up to October 2015. Eligibility criteria included assessment of macronutrient quantity (e.g., total carbohydrate) or indicators of quality (e.g., dietary fiber) by use of self-report or objective biomarkers of intake. Interactions identified in the review were subsequently examined in the EPIC (European Prospective Investigation into Cancer)-InterAct case-cohort study (n = 21,148, with 9403 T2D cases; 8 European countries). Prentice-weighted Cox regression was used to estimate country-specific HRs, 95% CIs, and P-interaction values, which were then pooled by random-effects meta-analysis. A primary model was fitted by using the same covariates as reported in the published studies, and a second model adjusted for additional covariates and estimated the effects of isocaloric macronutrient substitution.Results: Thirteen observational studies met the eligibility criteria (n < 1700 cases). Eight unique interactions were reported to be significant between macronutrients [carbohydrate, fat, saturated fat, dietary fiber, and glycemic load derived from self-report of dietary intake and circulating n-3 (ω-3) polyunsaturated fatty acids] and genetic variants in or near transcription factor 7-like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) (P-interaction < 0.05). We found no evidence of interaction when we tried to replicate previously reported interactions. In addition, no interactions were detected in models with additional covariates.Conclusions: Eight gene-macronutrient interactions were identified for the risk of T2D from the literature. These interactions were not replicated in the EPIC-InterAct study, which mirrored the analyses undertaken in the original reports. Our findings highlight the importance of independent replication of reported interactions.

Gene-Diet Interactions in Type 2 Diabetes: The Chicken and Egg Debate

Consistent evidence from both experimental and human studies indicates that Type 2 diabetes mellitus (T2DM) is a complex disease resulting from the interaction of genetic, epigenetic, environmental, and lifestyle factors. Nutrients and dietary patterns are important environmental factors to consider in the prevention, development and treatment of this disease. Nutritional genomics focuses on the interaction between bioactive food components and the genome and includes studies of nutrigenetics, nutrigenomics and epigenetic modifications caused by nutrients. There is evidence supporting the existence of nutrient-gene and T2DM interactions coming from animal studies and family-based intervention studies. Moreover, many case-control, cohort, cross-sectional cohort studies and clinical trials have identified relationships between individual genetic load, diet and T2DM. Some of these studies were on a large scale. In addition, studies with animal models and human observational studies, in different countries over periods of time, support a causative relationship between adverse nutritional conditions during in utero development, persistent epigenetic changes and T2DM. This review provides comprehensive information on the current state of nutrient-gene interactions and their role in T2DM pathogenesis, the relationship between individual genetic load and diet, and the importance of epigenetic factors in influencing gene expression and defining the individual risk of T2DM.

Genetic Risk Score of Nine Type 2 Diabetes Risk Variants that Interact with Erythrocyte Phospholipid Alpha-Linolenic Acid for Type 2 Diabetes in Chinese Hans: A Case-Control Study

Modulation of n-3 fatty acids on genetic susceptibility to type 2 diabetes (T2D) is still not clear. In a case-control study of 622 Chinese T2D patients and 293 healthy controls, a genetic risk score (GRS) was created based on nine T2D genetic variants. Logistic regression was used to examine the interaction of the GRS with erythrocyte phospholipid n-3 fatty acids for T2D risk. Every 1-unit (corresponding to 1 risk allele) increase in GRS was associated with 12% (Odds ratio (OR): 1.12; 95% confidence intervals (CI): 1.04–1.20) higher risk of T2D. Compared with the lowest quartile, participants had lower T2D risk in the 2nd (OR: 0.55; 95% CI: 0.36–0.84), 3rd (OR: 0.58; 95% CI: 0.38–0.88) and 4th (OR: 0.67; 95% CI: 0.44–1.03) quartile of alpha-linolenic acid (ALA) levels. Significant interaction (p-interaction = 0.029) of GRS with ALA for T2D risk was observed. Higher ALA levels were associated with lower T2D risk only among participants within the lowest GRS tertile, with ORs 0.51 (95% CI: 0.26–1.03), 0.44 (95% CI: 0.22–0.89) and 0.49 (95% CI: 0.25–0.96) for the 2nd, 3rd and 4th ALA quartile, compared with the 1st. This study suggests that higher erythrocyte ALA levels are inversely associated with T2D risk only among participants with low T2D genetic risk, with high genetic risk abolishing the ALA-T2D association.

Effects of n-3 fatty acid supplements on glycemic traits in Chinese type 2 diabetic patients: A double-blind randomized controlled trial

SCOPE

To investigate the effects of n-3 fatty acid supplements, both marine and plant-based, on glycemic traits in Chinese type 2 diabetes patients.

METHOD AND RESULTS

In a double-blind randomized controlled trial, 185 recruited Chinese type 2 diabetes patients were randomized to either fish oil (FO, n = 63), flaxseed oil (FSO, n = 61), or corn oil group (served as control group, n = 61) for 180 days. The patients were asked to take corresponding oil capsules (four capsules/day), which totally provided 2 g/day of eicosapentaenoic acid + docosahexaenoic acid in FO group and 2.5 g/day of alpha-linolenic acid in FSO group. No group × time interaction was observed for homeostatic model assessment of insulin resistance, fasting insulin, or glucose. Significant group × time interaction (P = 0.035) was observed for glycated hemoglobin A_1c (HbA1c), with HbA1c decreased in FO group compared with corn oil group (P = 0.037). We also found significant group × time interactions for lipid traits, including LDL cholesterol (P = 0.043), total cholesterol (P = 0.021), total cholesterol/HDL cholesterol (P = 0.009), and triacylglycerol (P = 0.003), with the lipid profiles improved in FO group. No significant effects of FSO on glycemic traits or blood lipids were observed.

CONCLUSIONS

Marine n-3 PUFA supplements may improve glycemic control and lipid profiles among Chinese type 2 diabetic patients.