Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes

Machine learning approach reveals microbiome, metabolome, and lipidome profiles in type 1 diabetes

INTRODUCTION

Type 1 diabetes (T1D) is a complex disorder influenced by genetic and environmental factors. The gut microbiome, the serum metabolome, and the serum lipidome have been identified as key environmental factors contributing to the pathophysiological mechanisms of T1D.

OBJECTIVES

We aimed to explore the gut microbiota, serum metabolite, and serum lipid signatures in T1D patients by machine learning.

METHODS

We evaluated 137 individuals in a cross-sectional cohort involving 38 T1D patients, 38 healthy controls, and 61 T1D patients for validation. We characterized gut microbiome, serum metabolite, and serum lipid profiles with machine learning approaches (logistic regression, support vector machine, Gaussian naive Bayes, and random forest).

RESULTS

The machine learning approaches using the microbiota composition did not accurately diagnose T1D (model accuracy = 0.7555), while the accuracy of the model using the metabolite composition was 0.9333. Based on the metabolite composition, 3-hydroxybutyric acid and 9-oxo-ode (area under curve = 0.70 and 0.67, respectively, both increased in T1D) were meaningful overlap metabolites screened by multiple bioinformatics methods. We confirmed the biological relevance of the microbiome, metabolome, and lipidome features in the validation group.

CONCLUSION

By using machine learning algorithms and multi-omics, we demonstrated that T1D patients are associated with altered microbiota, metabolite, and lipidomic signatures or functions.

Exhaustive Search of Dietary Intake Biomarkers as Objective Tools for Personalized Nutrimetabolomics and Precision Nutrition Implementation

OBJECTIVE

To conduct an exhaustive scoping search of existing literature, incorporating diverse bibliographic sources to elucidate the relationships between metabolite biomarkers in human fluids and dietary intake.

BACKGROUND

The search for biomarkers linked to specific dietary food intake holds immense significance for precision health and nutrition research. Using objective methods to track food consumption through metabolites offers a more accurate way to provide dietary advice and prescriptions on healthy dietary patterns by healthcare professionals. An extensive investigation was conducted on biomarkers associated with the consumption of several food groups and consumption patterns. Evidence is integrated from observational studies, systematic reviews, and meta-analyses to achieve precision nutrition and metabolism personalization.

METHODS

Tailored search strategies were applied across databases and gray literature, yielding 158 primary research articles that met strict inclusion criteria. The collected data underwent rigorous analysis using STATA and Python tools. Biomarker-food associations were categorized into 5 groups: cereals and grains, dairy products, protein-rich foods, plant-based foods, and a miscellaneous group. Specific cutoff points (≥3 or ≥4 bibliographic appearances) were established to identify reliable biomarkers indicative of dietary consumption.

RESULTS

Key metabolites in plasma, serum, and urine revealed intake from different food groups. For cereals and grains, 3-(3,5-dihydroxyphenyl) propanoic acid glucuronide and 3,5-dihydroxybenzoic acid were significant. Omega-3 fatty acids and specific amino acids showcased dairy and protein foods consumption. Nuts and seafood were linked to hypaphorine and trimethylamine N-oxide. The miscellaneous group featured compounds like theobromine, 7-methylxanthine, caffeine, quinic acid, paraxanthine, and theophylline associated with coffee intake.

CONCLUSIONS

Data collected from this research demonstrate potential for incorporating precision nutrition into clinical settings and nutritional advice based on accurate estimation of food intake. By customizing dietary recommendations based on individualized metabolic profiles, this approach could significantly improve personalized food consumption health prescriptions and support integrating multiple nutritional data.This article is part of a Nutrition Reviews special collection on Precision Nutrition.

Explainable AI-prioritized plasma and fecal metabolites in inflammatory bowel disease and their dietary associations

Fecal metabolites effectively discriminate inflammatory bowel disease (IBD) and show differential associations with diet. Metabolomics and AI-based models, including explainable AI (XAI), play crucial roles in understanding IBD. Using datasets from the UK Biobank and the Human Microbiome Project Phase II IBD Multi'omics Database (HMP2 IBDMDB), this study uses multiple machine learning (ML) classifiers and Shapley additive explanations (SHAP)-based XAI to prioritize plasma and fecal metabolites and analyze their diet correlations. Key findings include the identification of discriminative metabolites like glycoprotein acetyl and albumin in plasma, as well as nicotinic acid metabolites andurobilin in feces. Fecal metabolites provided a more robust disease predictor model (AUC [95%]: 0.93 [0.87-0.99]) compared to plasma metabolites (AUC [95%]: 0.74 [0.69-0.79]), with stronger and more group-differential diet-metabolite associations in feces. The study validates known metabolite associations and highlights the impact of IBD on the interplay between gut microbial metabolites and diet.

Plant-Based Food for the Prevention of Type 2 Diabetes: Scoping Review

Type 2 Diabetes Mellitus (T2DM) is a chronic condition with growing worldwide prevalence. Besides genetic factors, a sedentary lifestyle, excess weight, and inadequate eating habits, characterized by an excess intake of refined carbohydrates and ultra-processed foods, are contributing factors for the development of the disease. In this scenario, promoting a plant-based diet, and limiting animal product consumption while increasing the intake of vegetables, concurrently with healthy lifestyle habits, is a promising strategy to prevent T2DM. This scoping review, carried out between 2017 and 2022, aimed to gather evidence substantiating the benefits of a plant-based diet in T2DM prevention, considering different eating patterns, such as vegetarian, vegan, Mediterranean, and DASH diets. Several studies demonstrate a significant reduction in T2DM incidence among individuals adopting plant-based eating patterns or emphasizing healthy plant-based food alongside decreased intake or exclusion of animal-based foods. There are still no robust data regarding plant-based diets and the prevention of diabetes without loss in body weight. Hence, prospective studies in plant-based diets with weight control are needed. Nevertheless, adopting plant-based diets appears to induce significant weight loss, which is crucial in an obesity-endemic context. Thus, embracing plant-based diets, along with healthy habits, emerges as a relevant strategy in obesity and T2DM prevention.

Fasting plasma metabolites reflecting meat consumption and their associations with incident type 2 diabetes in two Swedish cohorts

BACKGROUND

Consumption of processed red meat has been associated with increased risk of developing type 2 diabetes (T2D), but challenges in dietary assessment call for objective intake biomarkers.

OBJECTIVES

This study aimed to investigate metabolite biomarkers of meat intake and their associations with T2D risk.

METHODS

Fasting plasma samples were collected from a case-control study nested within Västerbotten Intervention Program (VIP) (214 females and 189 males) who developed T2D after a median follow-up of 7 years. Panels of biomarker candidates reflecting the consumption of total, processed, and unprocessed red meat and poultry were selected from the untargeted metabolomics data collected on the controls. Observed associations were then replicated in Swedish Mammography clinical subcohort in Uppsala (SMCC) (n = 4457 females). Replicated metabolites were assessed for potential association with T2D risk using multivariable conditional logistic regression in the discovery and Cox regression in the replication cohorts.

RESULTS

In total, 15 metabolites were associated with ≥1 meat group in both cohorts. Acylcarnitines 8:1, 8:2, 10:3, reflecting higher processed meat intake [r > 0.22, false discovery rate (FDR) < 0.001 for VIP and r > 0.05; FDR < 0.001 for SMCC) were consistently associated with higher T2D risk in both data sets. Conversely, lysophosphatidylcholine 17:1 and phosphatidylcholine (PC) 15:0/18:2 were associated with lower processed meat intake (r < -0.12; FDR < 0.023, for VIP and r < -0.05; FDR < 0.001, for SMCC) and with lower T2D risk in both data sets, except for PC 15:0/18:2, which was significant only in the VIP cohort. All associations were attenuated after adjustment for BMI (kg/m2).

CONCLUSIONS

Consistent associations of biomarker candidates involved in lipid metabolism between higher processed red meat intake with higher T2D risk and between those reflecting lower intake with the lower risk may suggest a relationship between processed meat intake and higher T2D risk. However, attenuated associations after adjusting for BMI indicates that such a relationship may at least partly be mediated or confounded by BMI.

The Association of Total Meat Intake with Cardio-Metabolic Disease Risk Factors and Measures of Sub-Clinical Atherosclerosis in an Urbanising Community of Southern India: A Cross-Sectional Analysis for the APCAPS Cohort

AIM

Meat is commonly consumed in India; however, in comparison to Western settings, it is eaten in relatively lower quantities and with minimal processing. The association between meat intake and cardio-metabolic diseases (CMDs) and their risk factors in India is currently uncertain. We examined whether meat intake is associated with risk factors for CMDs and the measures of subclinical atherosclerosis in urbanising villages in southern India.

METHODS

We conducted a cross-sectional analysis of 6012 adults (52.3% male) participating in the Andhra Pradesh Children and Parents' Study (APCAPS), which is a large prospective, intergenerational cohort study in Southern India that began with the long-term follow-up of the Hyderabad Nutrition Trial (1987-1990). We used cross-sectional data from the third wave of data collection conducted in 2010-2012, where total meat intake was assessed using 100-item, semi-quantitative validated food frequency questionnaires (FFQ). The FFQs were validated using multiple weighed 24 h dietary recalls. The main predictor, 'total meat intake', was calculated as the sum of chicken, red meat, and fish consumption. The risk factors for CMDs [systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), waist circumference (WC), fasting glucose, total cholesterol, homeostasis model assessment insulin resistance (HOMA-IR), total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, triglycerides, and C-reactive protein] and measures of subclinical atherosclerosis [Carotid Intima-Media Thickness, Pulse Wave Velocity, and Augmentation Index] were assessed using standardised clinical procedures. Stratified by gender, the association of meat intake with the risk factors of CMDs and measures of subclinical atherosclerosis was examined using linear multilevel models with random intercept at the household level.

RESULTS

The mean (SD) age of the male (n = 3128) and female participants (n = 2828) was 34.09 years (15.55) and 34.27 years (12.73), respectively. The median (IQR) intake of meat was 17.79 g/day (8.90, 30.26) in males and 8.90 g/day (4.15, 18.82) in females. In males, a 10 g increase in total meat intake/1000 Kcal/day was positively associated with DBP, BMI, WC, total cholesterol, LDL-C, and triglycerides, whereas in females, a 10 g increase in total meat intake/1000 Kcal/day was positively associated with SBP, DBP, fasting glucose, HOMA-IR, total cholesterol, LDL-C, and triglycerides. There was no relationship between meat consumption and measures of subclinical atherosclerosis.

CONCLUSIONS

Meat intake had a linear positive association with CMD risk factors among the relatively younger Indian population who were consuming meat at lower levels compared to their European counterparts.

Potential Mechanisms of Precision Nutrition-Based Interventions for Managing Obesity

Precision nutrition (PN) considers multiple individual-level and environmental characteristics or variables to better inform dietary strategies and interventions for optimizing health, including managing obesity and metabolic disorders. Here, we review the evidence on potential mechanisms-including ones to identify individuals most likely to respond-that can be leveraged in the development of PN interventions addressing obesity. We conducted a review of the literature and included laboratory, animal, and human studies evaluating biochemical and genetic data, completed and ongoing clinical trials, and public programs in this review. Our analysis describes the potential mechanisms related to 6 domains including genetic predisposition, circadian rhythms, physical activity and sedentary behavior, metabolomics, the gut microbiome, and behavioral and socioeconomic characteristics, i.e., the factors that can be leveraged to design PN-based interventions to prevent and treat obesity-related outcomes such as weight loss or metabolic health as laid out by the NIH 2030 Strategic Plan for Nutrition Research. For example, single nucleotide polymorphisms can modify responses to certain dietary interventions, and epigenetic modulation of obesity risk via physical activity patterns and macronutrient intake have also been demonstrated. Additionally, we identified limitations including questions of equitable implementation across a limited number of clinical trials. These include the limited ability of current PN interventions to address systemic influences such as supply chains and food distribution, healthcare systems, racial or cultural inequities, and economic disparities, particularly when designing and implementing PN interventions in low- and middle-income communities. PN has the potential to help manage obesity by addressing intra- and inter-individual variation as well as context, as opposed to "one-size fits all" approaches though there is limited clinical trial evidence to date.

Protein intake and type 2 diabetes mellitus: an umbrella review of systematic reviews for the evidence-based guideline for protein intake of the German Nutrition Society

PURPOSE

Protein-rich foods show heterogeneous associations with the risk of type 2 diabetes (T2D) and it remains unclear whether habitual protein intake is related to T2D risk. We carried out an umbrella review of systematic reviews (SR) of randomised trials and/or cohort studies on protein intake in relation to risks of T2D.

METHODS

Following a pre-specified protocol (PROSPERO: CRD42018082395), we retrieved SRs on protein intake and T2D risk published between July 1st 2009 and May 22nd 2022, and assessed the methodological quality and outcome-specific certainty of the evidence using a modified version of AMSTAR 2 and NutriGrade, respectively. The overall certainty of evidence was rated according to predefined criteria.

RESULTS

Eight SRs were identified of which six contained meta-analyses. The majority of SRs on total protein intake had moderate or high methodological quality and moderate outcome-specific certainty of evidence according to NutriGrade, however, the latter was low for the majority of SRs on animal and plant protein. Six of the eight SRs reported risk increases with both total and animal protein. According to one SR, total protein intake in studies was ~ 21 energy percentage (%E) in the highest intake category and 15%E in the lowest intake category. Relative Risks comparing high versus low intake in most recent SRs ranged from 1.09 (two SRs, 95% CIs 1.02-1.15 and 1.06-1.13) to 1.11 (1.05-1.16) for total protein (between 8 and 12 cohort studies included) and from 1.13 (1.08-1.19) to 1.19 (two SRs, 1.11-1.28 and 1.11-1.28) (8-9 cohort studies) for animal protein. However, SRs on RCTs examining major glycaemic traits (HbA1c, fasting glucose, fasting insulin) do not support a clear biological link with T2D risk. For plant protein, some recent SRs pointed towards risk decreases and non-linear associations, however, the majority did not support an association with T2D risk.

CONCLUSION

Higher total protein intake was possibly associated with higher T2D risk, while there is insufficient evidence for a risk increase with higher intakes of animal protein and a risk decrease with plant protein intake. Given that most SRs on plant protein did not indicate an association, there is possibly a lack of an effect.

Red meat intake and risk of type 2 diabetes in a prospective cohort study of United States females and males

BACKGROUND

Studies with methodological advancements are warranted to confirm the relation of red meat consumption to the incidence of type 2 diabetes (T2D).

OBJECTIVE

We aimed to assess the relationships of intakes of total, processed, and unprocessed red meat to risk of T2D and to estimate the effects of substituting different protein sources for red meats on T2D risk.

METHODS

Our study included 216,695 participants (81% females) from the Nurses' Health Study (NHS), NHS II, and Health Professionals Follow-up Study (HPFS). Red meat intakes were assessed with semiquantitative food frequency questionnaires (FFQs) every 2 to 4 y since the study baselines. We used multivariable-adjusted proportional hazards models to estimate the associations between red meats and T2D.

RESULTS

Over 5,483,981 person-years of follow-up, we documented 22,761 T2D cases. Intakes of total, processed, and unprocessed red meat were positively and approximately linearly associated with higher risks of T2D. Comparing the highest to the lowest quintiles, hazard ratios (HR) were 1.62 (95% confidence interval [CI]: 1.53, 1.71) for total red meat, 1.51 (95% CI: 1.44, 1.58) for processed red meat, and 1.40 (95% CI: 1.33, 1.47) for unprocessed red meat. The percentage lower risk of T2D associated with substituting 1 serving/d of nuts and legumes for total red meat was 30% (HR = 0.70, 95% CI: 0.66, 0.74), for processed red meat was 41% (HR = 0.59, 95% CI: 0.55, 0.64), and for unprocessed red meat was 29% (HR = 0.71, 95% CI: 0.67, 0.75); Substituting 1 serving/d of dairy for total, processed, or unprocessed red meat was also associated with significantly lower risk of T2D. The observed associations became stronger after we calibrated dietary intakes to intakes assessed by weighed diet records.

CONCLUSIONS

Our study supports current dietary recommendations for limiting consumption of red meat intake and emphasizes the importance of different alternative sources of protein for T2D prevention.

Precision Nutrition to Improve Risk Factors of Obesity and Type 2 Diabetes

PURPOSE OF REVIEW

Existing dietary and lifestyle interventions and recommendations, to improve the risk factors of obesity and type 2 diabetes with the target to mitigate this double global epidemic, have produced inconsistent results due to interpersonal variabilities in response to these conventional approaches, and inaccuracies in dietary assessment methods. Precision nutrition, an emerging strategy, tailors an individual's key characteristics such as diet, phenotype, genotype, metabolic biomarkers, and gut microbiome for personalized dietary recommendations to optimize dietary response and health. Precision nutrition is suggested to be an alternative and potentially more effective strategy to improve dietary intake and prevention of obesity and chronic diseases. The purpose of this narrative review is to synthesize the current research and examine the state of the science regarding the effect of precision nutrition in improving the risk factors of obesity and type 2 diabetes.

RECENT FINDINGS

The results of the research review indicate to a large extent significant evidence supporting the effectiveness of precision nutrition in improving the risk factors of obesity and type 2 diabetes. Deeper insights and further rigorous research into the diet-phenotype-genotype and interactions of other components of precision nutrition may enable this innovative approach to be adapted in health care and public health to the special needs of individuals. Precision nutrition provides the strategy to make individualized dietary recommendations by integrating genetic, phenotypic, nutritional, lifestyle, medical, social, and other pertinent characteristics about individuals, as a means to address the challenges of generalized dietary recommendations. The evidence presented in this review shows that precision nutrition markedly improves risk factors of obesity and type 2 diabetes, particularly behavior change.

Blood metabolite profiles linking dietary patterns with health-Toward precision nutrition

Diet is one of the most important exposures that may affect health throughout life span. Investigations on dietary patterns rather than single food components are gaining in popularity because they take the complexity of the whole dietary context into account. Adherence to such dietary patterns can be measured by using metabolomics, which allows measurements of thousands of molecules simultaneously. Derived metabolite signatures of dietary patterns may reflect the consumption of specific groups of foods or their constituents originating from the dietary pattern per se, or the physiological response toward the food-derived metabolites, their interaction with endogenous metabolism, and exogenous factors such as gut microbiota. Here, we review and discuss blood metabolite fingerprints of healthy dietary patterns. The plasma concentration of several food-derived metabolites-such as betaines from whole grains and n - 3 polyunsaturated fatty acids and furan fatty acids from fish-seems to consistently reflect the intake of common foods of several healthy dietary patterns. The metabolites reflecting shared features of different healthy food indices form biomarker panels for which specific, targeted assays could be developed. The specificity of such biomarker panels would need to be validated, and proof-of-concept feeding trials are needed to evaluate to what extent the panels may mediate the effects of dietary patterns on disease risk indicators or if they are merely food intake biomarkers. Metabolites mediating health effects may represent novel targets for precision prevention strategies of clinical relevance to be verified in future studies.

Habitual Tea Consumption Increases the Incidence of Metabolic Syndrome in Middle-Aged and Older Individuals

In middle-aged and elderly individuals, the relationship between tea consumption and incident metabolic syndrome (MetS) is still unclear. Therefore, this study intends to figure out the relationship between tea-drinking frequency and MetS in rural middle-aged and older Chinese residents. In the Northeast China Rural Cardiovascular Health Study, 3632 middle-aged or older individuals (mean age 57 ± 8, 55.2% men) without MetS were included at baseline during 2012–2013 and were followed up on between 2015–2017. Participants showing differential tea consumption frequency were divided into the following classes: non-habitual tea drinkers, occasional tea drinkers, 1–2 times/day drinkers, and ≥3 times/day drinkers. Data showed that non-habitual tea drinking was more common among women. The frequency of tea consumption was higher in ethnic groups other than Han and among singles, as well as in concurrent smokers and drinkers and individuals with primary or lower educational status. The increasing tea consumption was in line with baseline elevations in body mass index, systolic and diastolic blood pressure, high-density lipoprotein cholesterol (HDL-C), and AST/ALT ratio. Multivariate logistic regression analysis confirmed that occasional tea drinking increased the incidence of low HDL-C [OR (95% CI): 1.268 (1.015, 1.584)], high waist circumference [OR (95% CI): 1.336 (1.102, 1.621)], and MetS [OR (95% CI): 1.284 (1.050, 1.570)]. In addition, 1–2 times/day tea drinking increased the cumulative incidence of high TG [OR (95% CI): 1.296 (1.040, 1.616)], high waist circumference [OR (95% CI): 1.296 (1.044, 1.609)] and MetS [OR (95% CI): 1.376 (1.030, 1.760)]. We demonstrated that regular tea consumption is correlated with a greater incidence of metabolic disorders and MetS. Our findings may help clarify the contradictory association reported between tea drinking and MetS development in middle-aged and older residents of rural China.

The path between socioeconomic inequality and cognitive function: A mediation analysis based on the HAALSI cohort in rural South Africa

Background

Socioeconomic position (SEP) strongly predicts late-life cognitive health, yet the pathways between SEP and cognitive function remain unclear. This study assessed whether and to what extent the association between SEP and cognitive function in the adult population in rural South Africa is mediated by some health conditions, behavioral factors, and social capital factors.

Methods

In this cross-sectional study, we used data from the 2014–15 “Health and Aging Africa: A Longitudinal Study of an INDEPTH Community in South Africa” (HAALSI) cohort, including 5,059 adults aged 40+ years from the Agincourt sub-district in Mpumalanga Province, South Africa. SEP, the independent variable, was measured based on ownership of household goods. Cognitive function, the dependent variable, was assessed using questions related to time orientation and immediate and delayed word recall. We used the multiple-mediation analysis on 4125 individuals with complete values on all variables to assess the mediating roles of health conditions (hypertension, diabetes, obesity, and disability), behavioral factors (leisure physical activity, alcohol consumption, and tobacco smoking), and social capital factors (community's willingness to help, trust, sense of safety, and social network contact) in the association between SEP and cognitive function.

Results

Compared to adults in the poorest wealth quintile, those in the richest wealth quintile had better cognition (β = 0.903, p &lt; 0.001). The mediation analysis revealed that health conditions mediated 20.7% of the total effect of SEP on cognitive function. In comparison, 3.3% was mediated by behavioral factors and only 0.7% by social capital factors. In the multiple-mediator model, 17.9% of the effect of SEP on cognitive function was jointly mediated by health conditions, behavioral factors, and social capital factors.

Conclusion

Low socioeconomic position is a significant factor associated with poor cognitive function among adults aged 40 years and above in South Africa. Health conditions mainly mediate the effects between SEP and cognitive function. Therefore, actions to prevent and control chronic health conditions can serve as the entry point for intervention to prevent poor cognitive function among people with low socioeconomic status.

Friend or Foe? The Role of Animal-Source Foods in Healthy and Environmentally Sustainable Diets

Scientific and political discussions around the role of animal-source foods (ASFs) in healthy and environmentally sustainable diets are often polarizing. To bring clarity to this important topic, we critically reviewed the evidence on the health and environmental benefits and risks of ASFs, focusing on primary trade-offs and tensions, and summarized the evidence on alternative proteins and protein-rich foods. ASFs are rich in bioavailable nutrients commonly lacking globally and can make important contributions to food and nutrition security. Many populations in Sub-Saharan Africa and South Asia could benefit from increased consumption of ASFs through improved nutrient intakes and reduced undernutrition. Where consumption is high, processed meat should be limited, and red meat and saturated fat should be moderated to lower noncommunicable disease risk-this could also have cobenefits for environmental sustainability. ASF production generally has a large environmental impact; yet, when produced at the appropriate scale and in accordance with local ecosystems and contexts, ASFs can play an important role in circular and diverse agroecosystems that, in certain circumstances, can help restore biodiversity and degraded land and mitigate greenhouse gas emissions from food production. The amount and type of ASF that is healthy and environmentally sustainable will depend on the local context and health priorities and will change over time as populations develop, nutritional concerns evolve, and alternative foods from new technologies become more available and acceptable. Efforts by governments and civil society organizations to increase or decrease ASF consumption should be considered in light of the nutritional and environmental needs and risks in the local context and, importantly, integrally involve the local stakeholders impacted by any changes. Policies, programs, and incentives are needed to ensure best practices in production, curb excess consumption where high, and sustainably increase consumption where low.

Sex-Specific Associations of Red Meat and Processed Meat Consumption with Serum Metabolites in the UK Biobank

Red meat consumption has been found to closely related to cardiometabolic health, with sex disparity. However, the specific metabolic factors corresponding to red meat consumption in men and women have not been examined previously. We analyzed the sex-specific associations of meat consumption, with 167 metabolites using multivariable regression, controlling for age, ethnicity, Townsend deprivation index, education, physical activity, smoking, and drinking status among ~79,644 UK Biobank participants. We also compared the sex differences using an established formula. After accounting for multiple testing with false discovery rate < 5% and controlling for confounders, the positive associations of unprocessed red meat consumption with branched-chain amino acids and several lipoproteins, and the inverse association with glycine were stronger in women, while the positive associations with apolipoprotein A1, creatinine, and monounsaturated fatty acids were more obvious in men. For processed meat, the positive associations with branched-chain amino acids, several lipoproteins, tyrosine, lactate, glycoprotein acetyls and inverse associations with glutamine, and glycine were stronger in women than in men. The study suggests that meat consumption has sex-specific associations with several metabolites. This has important implication to provide dietary suggestions for individuals with or at high risk of cardiometabolic disease, with consideration of sex difference.

Plasma Metabolite Profiles Associated with the Amount and Source of Meat and Fish Consumption and the Risk of Type 2 Diabetes

SCOPE

Consumption of meat has been associated with a higher risk of type 2 diabetes (T2D), but if plasma metabolite profiles associated with these foods reflect this relationship is unknown. The objective is to identify a metabolite signature of consumption of total meat (TM), red meat (RM), processed red meat (PRM), and fish and examine if they are associated with T2D risk.

METHODS AND RESULTS

The discovery population includes 1833 participants from the PREDIMED trial. The internal validation sample includes 1522 participants with available 1-year follow-up metabolomic data. Associations between metabolites and TM, RM, PRM, and fish are evaluated with elastic net regression. Associations between the profiles and incident T2D are estimated using Cox regressions. The profiles included 72 metabolites for TM, 69 for RM, 74 for PRM, and 66 for fish. After adjusting for T2D risk factors, only profiles of TM (Hazard Ratio (HR): 1.25, 95% CI: 1.06-1.49), RM (HR: 1.27, 95% CI: 1.07-1.52), and PRM (HR: 1.27, 95% CI: 1.07-1.51) are associated with T2D.

CONCLUSIONS

The consumption of TM, its subtypes, and fish is associated with different metabolites, some of which have been previously associated with T2D. Scores based on the identified metabolites for TM, RM, and PRM show a significant association with T2D risk.

Polymorphisms, diet and nutrigenomics

Every human being possesses an exclusive nutritional blueprint inside their genes. Bioactive food components and nutrients affect the expression of such genes. Nutrigenomics is the science that analyzes gene-nutrient interactions (nutrigenetics), which can lead to the development of personalized nutritional recommendations to maintain optimal health and prevent disease. Genomic diversity among various ethnic groups might affect nutrients bioavailability as well as their metabolism. Nutrigenomics combines different branches of science including nutrition, bioinformatics, genomics, molecular biology, molecular medicine, and epidemiology. Genes regulate intake and metabolism of different nutrients, while nutrients positively or negatively influence the expression of a number of genes; testing of specific genetic polymorphisms may therefore become a useful tool to manage weight loss and to fully understand gene-nutrient interactions. Indeed, several approaches are used to study gene-nutrient interactions: epigenetics, the study of genome modification not related to changes in nucleotide sequence; transcriptomics, the study of tissue-specific and time-specific RNA transcripts; proteomics, the study of proteins involved in biological processes; and metabolomics, the study of changes of primary and secondary metabolites in body fluids and tissues. Hence, the use of nutrigenomics to improve and optimize a healthy, balanced diet in clinical settings could be an effective approach for long-term lifestyle changes that might lead to consistent weight loss and improve quality of life.

Determinants of blood acylcarnitine concentrations in healthy individuals of the European Prospective Investigation into Cancer and Nutrition

BACKGROUND & AIMS

Circulating levels of acylcarnitines (ACs) have been associated with the risk of various diseases such as cancer and type 2 diabetes. Diet and lifestyle factors have been shown to influence AC concentrations but a better understanding of their biological, lifestyle and metabolic determinants is needed.

METHODS

Circulating ACs were measured in blood by targeted (15 ACs) and untargeted metabolomics (50 ACs) in 7770 and 395 healthy participants of the European Prospective Investigation into Cancer and Nutrition (EPIC), respectively. Associations with biological and lifestyle characteristics, dietary patterns, self-reported intake of individual foods, estimated intake of carnitine and fatty acids, and fatty acids in plasma phospholipid fraction and amino acids in blood were assessed.

RESULTS

Age, sex and fasting status were associated with the largest proportion of AC variability (partial-r up to 0.19, 0.18 and 0.16, respectively). Some AC species of medium or long-chain fatty acid moiety were associated with the corresponding fatty acids in plasma (partial-r = 0.24) or with intake of specific foods such as dairy foods containing the same fatty acid. ACs of short-chain fatty acid moiety (propionylcarnitine and valerylcarnitine) were moderately associated with concentrations of branched-chain amino acids (partial-r = 0.5). Intake of most other foods and of carnitine showed little association with AC levels.

CONCLUSIONS

Our results show that determinants of ACs in blood vary according to their fatty acid moiety, and that their concentrations are related to age, sex, diet, and fasting status. Knowledge on their potential determinants may help interpret associations of ACs with disease risk and inform on potential dietary and lifestyle factors that might be modified for disease prevention.

Lipidomic Signatures of Dairy Consumption and Associated Changes in Blood Pressure and Other Cardiovascular Risk Factors Among Chinese Adults

BACKGROUND

Omics data may provide a unique opportunity to discover dairy-related biomarkers and their linked cardiovascular health.

METHODS

Dairy-related lipidomic signatures were discovered in baseline data from a Chinese cohort study (n=2140) and replicated in another Chinese study (n=212). Dairy intake was estimated by a validated food-frequency questionnaire. Lipidomics was profiled by high-coverage liquid chromatography-tandem mass spectrometry. Associations of dairy-related lipids with 6-year changes in cardiovascular risk factors were examined in the discovery cohort, and their causalities were analyzed by 2-sample Mendelian randomization using available genome-wide summary data.

RESULTS

Of 350 lipid metabolites, 4 sphingomyelins, namely sphingomyelin (OH) C32:2, sphingomyelin C32:1, sphingomyelin (2OH) C30:2, and sphingomyelin (OH) C38:2, were identified and replicated to be positively associated with total dairy consumption (β=0.130 to 0.148; P<1.43×10^-4), but not or weakly with nondairy food items. The score of 4 sphingomyelins showed inverse associations with 6-year changes in systolic (-2.68 [95% CI, -4.92 to -0.43]; P=0.019), diastolic blood pressures (-1.86 [95% CI, -3.12 to -0.61]; P=0.004), and fasting glucose (-0.25 [95% CI, -0.41 to -0.08]; P=0.003). Mendelian randomization analyses further revealed that genetically inferred sphingomyelin (OH) C32:2 was inversely associated with systolic (-0.57 [95% CI, -0.85 to -0.28]; P=9.16×10^-5) and diastolic blood pressures (-0.39 [95% CI, -0.59 to -0.20]; P=7.09×10^-5).

CONCLUSIONS

The beneficial effects of dairy products on cardiovascular health might be mediated through specific sphingomyelins among Chinese with overall low dairy consumption.

Plasma metabolite profiles related to plant-based diets and the risk of type 2 diabetes

AIMS/HYPOTHESIS

Plant-based diets, especially when rich in healthy plant foods, have been associated with a lower risk of type 2 diabetes. However, whether plasma metabolite profiles related to plant-based diets reflect this association was unknown. The aim of this study was to identify the plasma metabolite profiles related to plant-based diets, and to evaluate the associations between the identified metabolite profiles and the risk of type 2 diabetes.

METHODS

Within three prospective cohorts (Nurses' Health Study, Nurses' Health Study II and Health Professionals Follow-up Study), we measured plasma metabolites from 10,684 participants using high-throughput LC MS. Adherence to plant-based diets was assessed by three indices derived from the food frequency questionnaire: an overall Plant-based Diet Index (PDI), a Healthy Plant-based Diet Index (hPDI), and an Unhealthy Plant-based Diet Index (uPDI). Multi-metabolite profiles related to plant-based diet were identified using elastic net regression with a training/testing approach. The prospective associations between metabolite profiles and incident type 2 diabetes were evaluated using multivariable Cox proportional hazards regression. Metabolites potentially mediating the association between plant-based diets and type 2 diabetes risk were further identified.

RESULTS

We identified multi-metabolite profiles comprising 55 metabolites for PDI, 93 metabolites for hPDI and 75 metabolites for uPDI. Metabolite profile scores based on the identified metabolite profiles were correlated with the corresponding diet index (Pearson r = 0.33-0.35 for PDI, 0.41-0.45 for hPDI, and 0.37-0.38 for uPDI, all p<0.001). Metabolite profile scores of PDI (HR per 1 SD higher = 0.81 [95% CI 0.75, 0.88]) and hPDI (HR per 1 SD higher = 0.77 [95% CI 0.71, 0.84]) showed an inverse association with incident type 2 diabetes, whereas the metabolite profile score for uPDI was not associated with the risk. Mutual adjustment for metabolites selected in the metabolite profiles, including trigonelline, hippurate, isoleucine and a subset of triacylglycerols, attenuated the associations of diet indices PDI and hPDI with lower type 2 diabetes risk. The explainable proportion of PDI/hPDI-related diabetes risk by these metabolites ranged between 8.5% and 37.2% (all p<0.05).

CONCLUSIONS/INTERPRETATION

Plasma metabolite profiles related to plant-based diets, especially a healthy plant-based diet, were associated with a lower risk of type 2 diabetes among a generally healthy population. Our findings support the beneficial role of healthy plant-based diets in diabetes prevention and provide new insights for future investigation.

Metabolomics application for the design of an optimal diet

Precision nutrition is an emerging branch of nutrition science that aims to use modern omics technologies (genomics, proteomics, and metabolomics) to assess an individual's response to specific foods or dietary patterns and thereby determine the most effective diet or lifestyle interventions to prevent or treat specific diseases. Metabolomics is vital to nearly every aspect of precision nutrition. It can be targeted or untargeted, and it has many applications. Indeed, it can be used to comprehensively characterize the thousands of chemicals in foods, identify food by-products in human biofluids or tissues, characterize nutrient deficiencies or excesses, monitor biochemical responses to dietary interventions, track long- or short-term dietary habits, and guide the development of nutritional therapies. Indeed, metabolomics can be coupled with genomics and proteomics to study and advance the field of precision nutrition. Integrating omics with epidemiological and clinical data will begin to define the beneficial effects of human food metabolites. In this review, we present the metabolome and its relationship to precision nutrition. Moreover, we describe the different techniques used in metabolomics and present how metabolomics has been applied to advance the field of precision nutrition by providing notable examples and cases.

Metabolic Signatures of Healthy Lifestyle Patterns and Colorectal Cancer Risk in a European Cohort

BACKGROUND & AIMS

Colorectal cancer risk can be lowered by adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) guidelines. We derived metabolic signatures of adherence to these guidelines and tested their associations with colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort.

METHODS

Scores reflecting adherence to the WCRF/AICR recommendations (scale, 1-5) were calculated from participant data on weight maintenance, physical activity, diet, and alcohol among a discovery set of 5738 cancer-free European Prospective Investigation into Cancer and Nutrition participants with metabolomics data. Partial least-squares regression was used to derive fatty acid and endogenous metabolite signatures of the WCRF/AICR score in this group. In an independent set of 1608 colorectal cancer cases and matched controls, odds ratios (ORs) and 95% CIs were calculated for colorectal cancer risk per unit increase in WCRF/AICR score and per the corresponding change in metabolic signatures using multivariable conditional logistic regression.

RESULTS

Higher WCRF/AICR scores were characterized by metabolic signatures of increased odd-chain fatty acids, serine, glycine, and specific phosphatidylcholines. Signatures were inversely associated more strongly with colorectal cancer risk (fatty acids: OR, 0.51 per unit increase; 95% CI, 0.29-0.90; endogenous metabolites: OR, 0.62 per unit change; 95% CI, 0.50-0.78) than the WCRF/AICR score (OR, 0.93 per unit change; 95% CI, 0.86-1.00) overall. Signature associations were stronger in male compared with female participants.

CONCLUSIONS

Metabolite profiles reflecting adherence to WCRF/AICR guidelines and additional lifestyle or biological risk factors were associated with colorectal cancer. Measuring a specific panel of metabolites representative of a healthy or unhealthy lifestyle may identify strata of the population at higher risk of colorectal cancer.

Genetic variants in ALDH1L1 and GLDC influence the serine-to-glycine ratio in Hispanic children

BACKGROUND

Glycine is a proteogenic amino acid that is required for numerous metabolic pathways, including purine, creatine, heme, and glutathione biosynthesis. Glycine formation from serine, catalyzed by serine hydroxy methyltransferase, is the major source of this amino acid in humans. Our previous studies in a mouse model have shown a crucial role for the 10-formyltetrahydrofolate dehydrogenase enzyme in serine-to-glycine conversion.

OBJECTIVES

We sought to determine the genomic influence on the serine-glycine ratio in 803 Hispanic children from 319 families of the Viva La Familia cohort.

METHODS

We performed a genome-wide association analysis for plasma serine, glycine, and the serine-glycine ratio in Sequential Oligogenic Linkage Analysis Routines while accounting for relationships among family members.

RESULTS

All 3 parameters were significantly heritable (h2 = 0.22-0.78; P < 0.004). The strongest associations for the serine-glycine ratio were with single nucleotide polymorphisms (SNPs) in aldehyde dehydrogenase 1 family member L1 (ALDH1L1) and glycine decarboxylase (GLDC) and for glycine with GLDC (P < 3.5 × 10-8; effect sizes, 0.03-0.07). No significant associations were found for serine. We also conducted a targeted genetic analysis with ALDH1L1 exonic SNPs and found significant associations between the serine-glycine ratio and rs2886059 (β = 0.68; SE, 0.25; P = 0.006) and rs3796191 (β = 0.25; SE, 0.08; P = 0.003) and between glycine and rs3796191 (β = -0.08; SE, 0.02; P = 0.0004). These exonic SNPs were further associated with metabolic disease risk factors, mainly adiposity measures (P < 0.006). Significant genetic and phenotypic correlations were found for glycine and the serine-glycine ratio with metabolic disease risk factors, including adiposity, insulin sensitivity, and inflammation-related phenotypes [estimate of genetic correlation = -0.37 to 0.35 (P < 0.03); estimate of phenotypic correlation = -0.19 to 0.13 (P < 0.006)]. The significant genetic correlations indicate shared genetic effects among glycine, the serine-glycine ratio, and adiposity and insulin sensitivity phenotypes.

CONCLUSIONS

Our study suggests that ALDH1L1 and GLDC SNPs influence the serine-to-glycine ratio and metabolic disease risk.

Plasma Metabolite Profiles Following Consumption of Animal Protein and Soybean-Based Diet in Hypercholesterolemic Postmenopausal Women

Subjective reporting of food intake can be unreliable. No objective method is available to distinguish between diets differing in protein type. To address this gap, a secondary analysis of a randomized controlled cross-over feeding trial was conducted. Assessed were fasting plasma metabolite profiles and their associations with cardiometabolic risk factors (CMRFs). Hypercholesterolemic post-menopausal women (N = 11) were provided with diets containing predominantly animal protein (AP) and soy protein (SP). Untargeted metabolomics were used to determine the plasma metabolite profiles at the end of each diet phase. Concentrations of identified metabolites (N = 829) were compared using paired t-tests adjusted for false discovery rate, partial least square-discrimination analysis (PLS-DA) and receiver operating characteristics (ROC). Among the identified metabolites, 58 differed significantly between the AP and SP diets; the majority were phospholipids (n = 36), then amino acids (n = 10), xenobiotics (n = 7), vitamin/vitamin-related (n = 3) and lipids (n = 2). Of the top 10 metabolites, amino acid-derived metabolites, phospholipids and xenobiotics comprised the main categories differing due to dietary protein type. ROC curves confirmed that the top 10 metabolites were potential discriminating biomarkers for AP- and SP-rich diets. In conclusion, amino acid-derived metabolites, phosphatidylethanolamine-derived metabolites and isoflavones were identified as potential metabolite biomarkers distinguishing between dietary protein type.

Age, Sex, Body Mass Index, Diet and Menopause Related Metabolites in a Large Homogeneous Alpine Cohort

Metabolomics in human serum samples provide a snapshot of the current metabolic state of an individuum. Metabolite concentrations are influenced by both genetic and environmental factors. Concentrations of certain metabolites can further depend on age, sex, menopause, and diet of study participants. A better understanding of these relationships is pivotal for the planning of metabolomics studies involving human subjects and interpretation of their results. We generated one of the largest single-site targeted metabolomics data sets consisting of 175 quantified metabolites in 6872 study participants. We identified metabolites significantly associated with age, sex, body mass index, diet, and menopausal status. While most of our results agree with previous large-scale studies, we also found novel associations including serotonin as a sex and BMI-related metabolite and sarcosine and C2 carnitine showing significantly higher concentrations in post-menopausal women. Finally, we observed strong associations between higher consumption of food items and certain metabolites, mostly phosphatidylcholines and lysophosphatidylcholines. Most, and the strongest, relationships were found for habitual meat intake while no significant relationships were found for most fruits, vegetables, and grain products. Summarizing, our results reconfirm findings from previous population-based studies on an independent cohort. Together, these findings will ultimately enable the consolidation of sets of metabolites which are related to age, sex, BMI, and menopause as well as to participants’ diet.

Dihydroceramide- and ceramide-profiling provides insights into human cardiometabolic disease etiology

Metabolic alterations precede cardiometabolic disease onset. Here we present ceramide- and dihydroceramide-profiling data from a nested case-cohort (type 2 diabetes [T2D, n = 775]; cardiovascular disease [CVD, n = 551]; random subcohort [n = 1137]) in the prospective EPIC-Potsdam study. We apply the novel NetCoupler-algorithm to link a data-driven (dihydro)ceramide network to T2D and CVD risk. Controlling for confounding by other (dihydro)ceramides, ceramides C18:0 and C22:0 and dihydroceramides C20:0 and C22:2 are associated with higher and ceramide C20:0 and dihydroceramide C26:1 with lower T2D risk. Ceramide C16:0 and dihydroceramide C22:2 are associated with higher CVD risk. Genome-wide association studies and Mendelian randomization analyses support a role of ceramide C22:0 in T2D etiology. Our results also suggest that (dh)ceramides partly mediate the putative adverse effect of high red meat consumption and benefits of coffee consumption on T2D risk. Thus, (dihydro)ceramides may play a critical role in linking genetic predisposition and dietary habits to cardiometabolic disease risk.

Associations of plasma glycerophospholipid profile with modifiable lifestyles and incident diabetes in middle-aged and older Chinese

AIMS/HYPOTHESIS

Glycerophospholipid (GPL) perturbance was linked to the pathogenesis of diabetes in animal studies but prospective studies in humans are rare, particularly in Asians. We aimed to investigate the associations between plasma GPLs and incident diabetes and to explore effects of lifestyle on the associations in a Chinese population.

METHODS

The study included 1877 community-dwelling Chinese individuals aged 50-70 years (751 men and 1126 women), free of diabetes at baseline and followed for 6 years. A total of 160 GPL species were quantified in plasma at baseline by using high-throughput targeted lipidomics. Log-Poisson regression was used to assess the associations between GPLs and incidence of diabetes.

RESULTS

Over the 6 years of follow-up, 499 participants (26.6%) developed diabetes. After multivariable adjustment, eight GPLs were positively associated with incident diabetes (RR_{per SD} 1.13-1.25; all false-discovery rate [FDR]-corrected p < 0.05), including five novel GLPs, namely phosphatidylcholines (PCs; 16:0/18:1, 18:0/16:1, 18:1/20:3), lysophosphatidylcholine (LPC; 20:3) and phosphatidylethanolamine (PE; 16:0/16:1), and three reported GPLs (PCs 16:0/16:1, 16:0/20:3 and 18:0/20:3). In network analysis, a PC-containing module was positively associated with incident diabetes (RR_{per SD} 1.16 [95% CI 1.06, 1.26]; FDR-corrected p < 0.05). Notably, three of the diabetes-associated PCs (16:0/16:1, 16:0/18:1 and 18:0/16:1) and PE (16:0/16:1) were associated not only with fatty acids in the de novo lipogenesis (DNL) pathway, especially 16:1n-7 (Spearman correlation coefficients = 0.35-0.62, p < 0.001), but also with an unhealthy dietary pattern high in refined grains and low in fish, dairy and soy products (|factor loadings| ≥0.2). When stratified by physical activity levels, the associations of the eight GPLs and the PC module with incident diabetes were stronger in participants with lower physical activity (RR_{per SD} 1.24-1.49, FDR-corrected p < 0.05) than in those with the median and higher physical activity levels (RR_{per SD} 1.03-1.12, FDR-corrected p ≥ 0.05; FDR-corrected p_interaction < 0.05).

CONCLUSIONS/INTERPRETATION

Eight GPLs, especially PCs associated with the DNL pathway, were positively associated with incident diabetes in a cohort of Chinese men and women. The associations were most prominent in participants with a low level of physical activity.

Mass Spectrometry as a Crucial Analytical Basis for Omics Sciences

This review is devoted to the consideration of mass spectrometric platforms as applied to omics sciences. The most significant attention is paid to omics related to life sciences (genomics, proteomics, meta-bolomics, lipidomics, glycomics, plantomics, etc.). Mass spectrometric approaches to solving the problems of petroleomics, polymeromics, foodomics, humeomics, and exosomics, related to inorganic sciences, are also discussed. The review comparatively presents the advantages of various principles of separation and mass spectral techniques, complementary derivatization, used to obtain large arrays of various structural and quantitative information in the mentioned omics sciences.

Dietary Animal to Plant Protein Ratio Is Associated with Risk Factors of Metabolic Syndrome in Participants of the AHS-2 Calibration Study

BACKGROUND

Few research studies have focused on the effects of dietary protein on metabolic syndrome and its components. Our objective was to determine the relationship between the type of dietary protein intake and animal to plant (AP) protein ratio with metabolic syndrome and its components.

METHODS

This population-based study had a cross sectional design and conducted on 518 participants of the Adventist Health Study 2 (AHS-2) Calibration Study. Two sets of three dietary 24-h recalls were obtained six months apart. Anthropometric measures and biochemical tests were performed in clinics. Regression calibration models were used to determine the association of type of dietary protein with metabolic syndrome and its components (raised triglyceride, raised blood pressure, reduced high-density lipoprotein cholesterol (HDL), raised fasting blood glucose and increased waist circumference).

RESULTS

The likelihood of metabolic syndrome was lower in those with higher total dietary protein and animal protein intake (p = 0.02).Total protein (β = 0.004, [95%CI: 0.002, 0.007]), animal protein intake (β = 0.004, [95%CI: 0.001, 0.007]) and AP protein intake ratio (β = 0.034, [95%CI: 0.021, 0.047]) were positively associated with waist circumference. Higher AP protein ratio was related to higher fasting blood glucose (β = 0.023, [95%CI: 0.005, 0.041]).

CONCLUSION

Our study suggests that considering a significant amount of plant protein as a part of total dietary protein has beneficial effects on cardiometabolic risk factors.

Processed and Unprocessed Red Meat Consumption and Risk for Type 2 Diabetes Mellitus: An Updated Meta-Analysis of Cohort Studies

Type II diabetes mellitus (T2DM) is a metabolic disorder that occurs in the body because of decreased insulin activity and/or insulin secretion. The incidence of T2DM has rapidly increased over recent decades. The relation between consumption of different types of red meats and risk of T2DM remains uncertain. This meta-analysis was conducted to quantitatively assess the associations of processed red meat (PRM) and unprocessed red meat (URM) consumption with T2DM. We searched PubMed, Embase, Web of Science and The Cochrane Library for English-language cohort studies published before January 2021. Summary relative risks (RR) with 95% confidence interval (CI) were estimated using fixed effects and random effects. Additionally, dose-response relationships were explored using meta-regression. Fifteen studies (n = 682,963 participants, cases = 50,675) were identified. Compared with the lowest intake group, high consumption of PRM and URM increased T2DM risk by 27% (95% CI 1.15-1.40) and 15% (95% CI 1.08-1.23), respectively. These relationships were consistently strongest for U.S-based studies, though the effects of sex are inconclusive. In conclusion, PRM and URM are both positively associated with T2DM incidence, and these relationships are strongest in the U.S. reduction of red meat consumption should be explored as a target for T2DM prevention initiatives.

A Scoping Review: Metabolomics Signatures Associated with Animal and Plant Protein Intake and Their Potential Relation with Cardiometabolic Risk

The dietary shift from animal protein (AP) to plant protein (PP) sources is encouraged for both environmental and health reasons. For instance, PPs are associated with lower cardiovascular and diabetes risks compared with APs, although the underlying mechanisms mostly remain unknown. Metabolomics is a valuable tool for globally and mechanistically characterizing the impact of AP and PP intake, given its unique ability to provide integrated signatures and specific biomarkers of metabolic effects through a comprehensive snapshot of metabolic status. This scoping review is aimed at gathering and analyzing the available metabolomics data associated with PP- and AP-rich diets, and discusses the metabolic effects underlying these metabolomics signatures and their potential implication for cardiometabolic health. We selected 24 human studies comparing the urine, plasma, or serum metabolomes associated with diets with contrasted AP and PP intakes. Among the 439 metabolites reported in those studies as able to discriminate AP- and PP-rich diets, 46 were considered to provide a robust level of evidence, according to a scoring system, especially amino acids (AAs) and AA-related products. Branched-chain amino acids, aromatic amino acids (AAAs), glutamate, short-chain acylcarnitines, and trimethylamine-N-oxide, which are known to be related to an increased cardiometabolic risk, were associated with AP-rich diets, whereas glycine (rather related to a reduced risk) was associated with PP-rich diets. Tricarboxylic acid (TCA) cycle intermediates and products from gut microbiota AAA degradation were also often reported, but the direction of their associations differed across studies. Overall, AP- and PP-rich diets result in different metabolomics signatures, with several metabolites being plausible candidates to explain some of their differential associations with cardiometabolic risk. Additional studies specifically focusing on protein type, with rigorous intake control, are needed to better characterize the associated metabolic phenotypes and understand how they could mediate differential AP and PP effects on cardiometabolic risk.

Plasma Sphingolipid Profile in Association with Incident Metabolic Syndrome in a Chinese Population-Based Cohort Study

Although bioactive sphingolipids have been shown to regulate cardiometabolic homeostasis and inflammatory signaling pathways in rodents, population-based longitudinal studies of relationships between sphingolipids and onset of metabolic syndrome (MetS) are sparse. We aimed to determine associations of circulating sphingolipids with inflammatory markers, adipokines, and incidence of MetS. Among 1242 Chinese people aged 50–70 years who completed the 6-year resurvey, 76 baseline plasma sphingolipids were quantified by high-throughput liquid chromatography-tandem mass spectrometry. There were 431 incident MetS cases at 6-year revisit. After multivariable adjustment including lifestyle characteristics and BMI, 21 sphingolipids mainly from ceramide and hydroxysphingomyelin subclasses were significantly associated with incident MetS. Meanwhile, the baseline ceramide score was positively associated (RR_{Q4 versus Q1} = 1.31; 95% CI 1.05, 1.63; p_trend = 0.010) and the hydroxysphingomyelin score was inversely associated (RR_{Q4 versus Q1} = 0.60; 95% CI 0.45, 0.79; p_trend < 0.001) with incident MetS. When further controlling for clinical lipids, both associations were attenuated but remained significant. Comparing extreme quartiles, RRs (95% CIs) of MetS risk were 1.34 (95% CI 1.06, 1.70; p_trend = 0.010) for ceramide score and 0.71 (95% CI 0.51, 0.97; p_trend = 0.018) for hydroxysphingomyelin score, respectively. Furthermore, a stronger association between ceramide score and incidence of MetS was evidenced in those having higher inflammation levels (RR_{Q4 versus Q1} 1.57; 95% CI 1.16, 2.12; p_interaction = 0.004). Our data suggested that elevated ceramide concentrations were associated with a higher MetS risk, whereas raised hydroxysphingomyelin levels were associated with a lower MetS risk beyond traditional clinical lipids.

Meat consumption and risk of 25 common conditions: outcome-wide analyses in 475,000 men and women in the UK Biobank study

BACKGROUND

There is limited prospective evidence on the association between meat consumption and many common, non-cancerous health outcomes. We examined associations of meat intake with risk of 25 common conditions (other than cancer).

METHODS

We used data from 474,985 middle-aged adults recruited into the UK Biobank study between 2006 and 2010 and followed up until 2017 (mean follow-up 8.0 years) with available information on meat intake at baseline (collected via touchscreen questionnaire), and linked hospital admissions and mortality data. For a large sub-sample (~ 69,000), dietary intakes were re-measured three or more times using an online, 24-h recall questionnaire.

RESULTS

On average, participants who reported consuming meat regularly (three or more times per week) had more adverse health behaviours and characteristics than participants who consumed meat less regularly, and most of the positive associations observed for meat consumption and health risks were substantially attenuated after adjustment for body mass index (BMI). In multi-variable adjusted (including BMI) Cox regression models corrected for multiple testing, higher consumption of unprocessed red and processed meat combined was associated with higher risks of ischaemic heart disease (hazard ratio (HRs) per 70 g/day higher intake 1.15, 95% confidence intervals (CIs) 1.07-1.23), pneumonia (1.31, 1.18-1.44), diverticular disease (1.19, 1.11-1.28), colon polyps (1.10, 1.06-1.15), and diabetes (1.30, 1.20-1.42); results were similar for unprocessed red meat and processed meat intakes separately. Higher consumption of unprocessed red meat alone was associated with a lower risk of iron deficiency anaemia (IDA: HR per 50 g/day higher intake 0.80, 95% CIs 0.72-0.90). Higher poultry meat intake was associated with higher risks of gastro-oesophageal reflux disease (HR per 30 g/day higher intake 1.17, 95% CIs 1.09-1.26), gastritis and duodenitis (1.12, 1.05-1.18), diverticular disease (1.10, 1.04-1.17), gallbladder disease (1.11, 1.04-1.19), and diabetes (1.14, 1.07-1.21), and a lower IDA risk (0.83, 0.76-0.90).

CONCLUSIONS

Higher unprocessed red meat, processed meat, and poultry meat consumption was associated with higher risks of several common conditions; higher BMI accounted for a substantial proportion of these increased risks suggesting that residual confounding or mediation by adiposity might account for some of these remaining associations. Higher unprocessed red meat and poultry meat consumption was associated with lower IDA risk.

Associations of TMPRSS6 Polymorphisms with Gestational Diabetes Mellitus in Chinese Han Pregnant Women: a Preliminary Cohort Study

Body iron status is likely to be associated with type 2 diabetes (T2DM) and gestational diabetes mellitus (GDM); transmembrane protease serine 6 (TMPRSS6) polymorphisms may be associated with T2DM risk through their effects on body iron status. However, it remains unknown whether the TMPRSS6 single nucleotide polymorphisms (SNPs) affect the risk of GDM development. We aimed to determine whether the TMPRSS6 SNPs rs855791 (V736A) and rs4820268 (D521D) are associated with the risk of GDM in pregnant women. The two SNPs in TMPRSS6 gene were genotyped and examined for their associations with body iron status and GDM risk in 398 unrelated Chinese Han pregnant women. The 2 TMPRSS6 SNPs rs855791 and rs4820268 were both significantly associated with serum iron and transferrin saturation (P < 0.01 for all) rather than ferritin. After adjustment for covariates, the C allele of rs4820268 was nominally and significantly associated with an increased risk of GDM (OR = 2.531; 95%CI = 1.044-6.136, P = 0.040); when concentrations of ferritin were further adjusted, the association was still significant (OR = 2.528; 95%CI = 1.043-6.126, P = 0.040). There was a significant trend (P = 0.065) in the association between the T allele of rs855791 and an increased GDM risk in this study population. The 2 TMPRSS6 SNPs rs855791 and rs4820268 were both significantly associated with serum iron and transferrin saturation, and TMPRSS6 variants might be associated with the risk of GDM. Furthermore, the effects of TMPRSS6 SNPs on the risk of GDM may not be completely explained by the mediation of body iron status. Further studies are warranted.

Replacement of Red and Processed Meat With Other Food Sources of Protein and the Risk of Type 2 Diabetes in European Populations: The EPIC-InterAct Study

OBJECTIVE

There is sparse evidence for the association of suitable food substitutions for red and processed meat on the risk of type 2 diabetes. We modeled the association between replacing red and processed meat with other protein sources and the risk of type 2 diabetes and estimated its population impact.

RESEARCH DESIGN AND METHODS

The European Prospective Investigation into Cancer (EPIC)-InterAct case cohort included 11,741 individuals with type 2 diabetes and a subcohort of 15,450 participants in eight countries. We modeled the replacement of self-reported red and processed meat with poultry, fish, eggs, legumes, cheese, cereals, yogurt, milk, and nuts. Country-specific hazard ratios (HRs) for incident type 2 diabetes were estimated by Prentice-weighted Cox regression and pooled using random-effects meta-analysis.

RESULTS

There was a lower hazard for type 2 diabetes for the modeled replacement of red and processed meat (50 g/day) with cheese (HR 0.90, 95% CI 0.83-0.97) (30 g/day), yogurt (0.90, 0.86-0.95) (70 g/day), nuts (0.90, 0.84-0.96) (10 g/day), or cereals (0.92, 0.88-0.96) (30 g/day) but not for replacements with poultry, fish, eggs, legumes, or milk. If a causal association is assumed, replacing red and processed meat with cheese, yogurt, or nuts could prevent 8.8%, 8.3%, or 7.5%, respectively, of new cases of type 2 diabetes.

CONCLUSIONS

Replacement of red and processed meat with cheese, yogurt, nuts, or cereals was associated with a lower rate of type 2 diabetes. Substituting red and processed meat by other protein sources may contribute to the prevention of incident type 2 diabetes in European populations.

Relationship between fermented dairy consumption, circulating short-chain acylcarnitines and angiographic severity of coronary artery disease

BACKGROUND AND AIMS

Current epidemiologic data suggest beneficial cardiovascular effects of fermented dairy products (FDP). However, the relationship between FDP consumption and angiographic coronary status has not been previously studied. Furthermore, the role of novel metabolomic biomarkers of cardiovascular risk in this context is unclear. We hypothesize that short-chain acylcarnitines (SCA) reflect the link between FDP intake and angiographic extent of stable coronary artery disease (CAD).

METHODS AND RESULTS

We recruited 1185 patients admitted for suspected CAD [median age 62 years (interquartile range: 54-69); 714 men (60.3%)]. Prior to coronary angiography, each patient completed a validated Food Frequency Questionnaire. In addition, venous blood was collected from each patient for whole blood metabolomic analysis, using targeted mass-spectrometry. CAD was defined by the presence of ≥1 coronary stenosis ≥50%. Patients with CAD (n = 441) reported lower median FDP intake [86.8 g/day (IQR: 53.4-127.6)] than patients without CAD [n = 744; 103.9 g/day (IQR: 62.9-152.7); p < 0.001]. Upon adjustment for relevant confounders, increased circulating SCA, particularly level of acetylcarnitine (C2) associated with both higher CAD probability [SCA:β(SE) = 0.584 (0.235), p = 0.013; C2:β(SE) = 0.575 (0.242), p = 0.017] and decreased FDP consumption [SCA:β/100 g FDP-increment/day (SE) = -0.785 (0.242), p = 0.001; C2:β(SE) = -0.560 (0.230), p = 0.015]. By mediation analysis, neither SCA nor C2 showed relevant mediator effect linking FDP consumption to the risk of CAD.

CONCLUSION

Increased consumption of fermented milk was associated with lower prevalence of CAD and correlated inversely with circulating SCA, in particular with acetylcarnitine. No substantial mediator effect of SCA linking fermented milk intake with risk of CAD was found.

CLINICAL TRIAL REGISTRY

NCT00497887.

A metabolomic study of red and processed meat intake and acylcarnitine concentrations in human urine and blood

BACKGROUND

Acylcarnitines (ACs) play a major role in fatty acid metabolism and are potential markers of metabolic dysfunction with higher blood concentrations reported in obese and diabetic individuals. Diet, and in particular red and processed meat intake, has been shown to influence AC concentrations but data on the effect of meat consumption on AC concentrations is limited.

OBJECTIVES

To investigate the effect of red and processed meat intake on AC concentrations in plasma and urine using a randomized controlled trial with replication in an observational cohort.

METHODS

In the randomized crossover trial, 12 volunteers successively consumed 2 different diets containing either pork or tofu for 3 d each. A panel of 44 ACs including several oxidized ACs was analyzed by LC-MS in plasma and urine samples collected after the 3-d period. ACs that were associated with pork intake were then measured in urine (n = 474) and serum samples (n = 451) from the European Prospective Investigation into Cancer and nutrition (EPIC) study and tested for associations with habitual red and processed meat intake derived from dietary questionnaires.

RESULTS

In urine samples from the intervention study, pork intake was positively associated with concentrations of 18 short- and medium-chain ACs. Eleven of these were also positively associated with habitual red and processed meat intake in the EPIC cross-sectional study. In blood, C18:0 was positively associated with red meat intake in both the intervention study (q = 0.004, Student's t-test) and the cross-sectional study (q = 0.033, linear regression).

CONCLUSIONS

AC concentrations in urine and blood were associated with red meat intake in both a highly controlled intervention study and in subjects of a cross-sectional study. Our data on the role of meat intake on this important pathway of fatty acid and energy metabolism may help understanding the role of red meat consumption in the etiology of some chronic diseases. This trial was registered at Clinicaltrials.gov as NCT03354130.

Iron metabolism and type 2 diabetes mellitus: A meta-analysis and systematic review

AIMS/INTRODUCTION

Iron metabolism can directly or indirectly affect the occurrence and development of type 2 diabetes. This meta-analysis and systematic review aimed to analyze the association between serum iron metabolism indicators and type 2 diabetes.

MATERIALS AND METHODS

The databases PubMed and Embase were searched for studies on the correlations between serum iron metabolism indicators (iron, ferritin, transferrin, hepcidin and soluble transferrin receptor) and type 2 diabetes since January 2006. Relevant data were extracted from the included studies, and meta-analysis was carried out.

RESULTS

A total of 12 case-control and cohort studies were analyzed. Of the 12 studies, 11 described the correlation between serum ferritin levels and type 2 diabetes. The median and high serum ferritin concentrations were significantly associated with the risks of type 2 diabetes (odds ratio [OR] 1.20, 95% confidence interval [CI] 1.08-1.33 and OR 1.43, 95% CI 1.29-1.59, respectively). However, the low concentration was not correlated with the risk of type 2 diabetes (OR 0.99, 95% CI 0.89-1.11). No significant association was observed between serum soluble transferrin receptor and type 2 diabetes, whereas the soluble transferrin receptor-to-ferritin ratio was significantly inversely related to the risk of type 2 diabetes in the median and high ratio subgroups (OR 0.71, 95% CI 0.51, 0.99 and OR 0.65, 95% CI 0.45-0.95).

CONCLUSIONS

The elevated serum ferritin was one of the risk factors for type 2 diabetes, and soluble transferrin receptor-to-ferritin ratio was inversely related to the risk of type 2 diabetes. A systematic review showed that serum transferrin and hepcidin might be directly or indirectly related to the development of diabetes.

The Molecular Link from Diet to Cancer Cell Metabolism

Malignant cells remodel their metabolism to meet the demands of uncontrolled cell proliferation. These demands lead to differential requirements in energy, biosynthetic precursors, and signaling intermediates. Both genetic programs arising from oncogenic events and transcriptional programs and epigenomic events are important in providing the necessary metabolic network activity. Accumulating evidence has established that environmental factors play a major role in shaping cancer cell metabolism. For metabolism, diet and nutrition are the major environmental aspects and have emerged as key components in determining cancer cell metabolism. In this review, we discuss these emerging concepts in cancer metabolism and how diet and nutrition influence cancer cell metabolism.

Meat and fish intake and type 2 diabetes: Dose-response meta-analysis of prospective cohort studies

AIMS

This meta-analysis aimed to quantitatively examine the possible associations between total meat, red meat, processed meat, poultry and fish intakes and type 2 diabetes (T2D).

METHODS

Relevant articles were identified in PubMed, Embase and Web of Science databases using a search time up to January 2019. Generalized least-squares trend estimations and restricted cubic spline regression models were used for analysis.

RESULTS

Twenty-eight articles were included in the analysis. When comparing the highest with the lowest category of meat intake, the summary relative risk of T2D was 1.33 (95% CI: 1.16-1.52) for total meat, 1.22 (95% CI: 1.16-1.28) for red meat, 1.25 (95% CI: 1.13-1.37) for processed meat, 1.00 (95% CI: 0.93-1.07) for poultry and 1.01 (95% CI: 0.93-1.10) for fish. In the dose-response analysis, each additional 100g/day of total and red meat, and 50g/day of processed meat, were found to be associated with a 36% (95% CI: 1.23-1.49), 31% (95% CI: 1.19-1.45) and 46% (95% CI: 1.26-1.69) increased risk of T2D, respectively. In addition, there was evidence of a non-linear dose-response association between processed meat and T2D (P=0.004), with the risk increasing by 30% with increasing intakes up to 30g/day.

CONCLUSION

Our meta-analysis has shown a linear dose-response relationship between total meat, red meat and processed meat intakes and T2D risk. In addition, a non-linear relationship of intake of processed meat with risk of T2D was detected.

Red meat, poultry and fish consumption and risk of diabetes: a 9 year prospective cohort study of the China Kadoorie Biobank

AIMS/HYPOTHESIS

Previous evidence linking red meat consumption with diabetes risk mainly came from western countries, with little evidence from China, where patterns of meat consumption are different. Moreover, global evidence remains inconclusive about the associations of poultry and fish consumption with diabetes. Therefore we investigated the associations of red meat, poultry and fish intake with incidence of diabetes in a Chinese population.

METHODS

The prospective China Kadoorie Biobank recruited ~512,000 adults (59% women, mean age 51 years) from ten rural and urban areas across China in 2004-2008. At the baseline survey, a validated interviewer-administered laptop-based questionnaire was used to collect information on the consumption frequency of major food groups including red meat, poultry, fish, fresh fruit and several others. During ~9 years of follow-up, 14,931 incidences of new-onset diabetes were recorded among 461,036 participants who had no prior diabetes, cardiovascular diseases or cancer at baseline. Cox regression analyses were performed to calculate adjusted HRs for incident diabetes associated with red meat, poultry and fish intake.

RESULTS

At baseline, 47.0%, 1.3% and 8.9% of participants reported a regular consumption (i.e. ≥4 days/week) of red meat, poultry and fish, respectively. After adjusting for adiposity and other potential confounders, each 50 g/day increase in red meat and fish intake was associated with 11% (HR 1.11 [95% CI 1.04, 1.20]) and 6% (HR 1.06 [95% CI 1.00, 1.13]) higher risk of incident diabetes, respectively. For both, the associations were more pronounced among men and women from urban areas, with an HR (95% CI) of 1.42 (1.15, 1.74) and 1.18 (1.03, 1.36), respectively, per 50 g/day red meat intake and 1.15 (1.02, 1.30) and 1.11 (1.01, 1.23), respectively, per 50 g/day fish intake. There was no significant association between diabetes and poultry intake, either overall (HR 0.96 [95% CI 0.83, 1.12] per 50 g/day intake) or in specific population subgroups.

CONCLUSIONS/INTERPRETATION

In Chinese adults, both red meat and fish, but not poultry, intake were positively associated with diabetes risk, particularly among urban participants. Our findings add new evidence linking red meat and fish intake with cardiometabolic diseases.

DATA AVAILABILITY

Details of how to access the China Kadoorie Biobank data and rules of China Kadoorie Biobank data release are available from www.ckbiobank.org/site/Data+Access.

Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: A prospective study of 3,057 matched case-control sets from EPIC

Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case-control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR1SD ) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR1SD  = 0.77, 95% confidence interval 0.66-0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR1SD  = 0.72, 0.57-0.90), or lysophosphatidylcholines (OR1SD  = 0.81, 0.69-0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR1SD  = 0.77, 0.61-0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.

Dietary Patterns Are Associated with Serum Metabolite Patterns and Their Association Is Influenced by Gut Bacteria among Older German Adults

BACKGROUND

Although dietary intakes and dietary intake patterns (DPs) have been associated with single metabolites, it is unclear whether DPs are also reflected in specific metabolite patterns (MPs). Moreover, the influence of groups of gut bacteria on the relationship between DPs and MPs is underexplored.

OBJECTIVES

We aimed to investigate the association of DPs and serum MPs and also the modifying effect of the gut bacteria compositional patterns (BCPs).

METHODS

This is a cross-sectional investigation among 225 individuals (median age: 63 y; 53% women) from the European Prospective Investigation into Cancer and Nutrition study. Dietary intakes were assessed by three 24-h dietary recalls, gut bacteria composition was quantified by 16S rRNA gene sequencing, and the serum metabolome was profiled by an untargeted approach. We identified DPs and BCPs by the treelet transform analysis. We modeled associations between DPs and 8 previously published MPs and the modifying effect of BCPs by fitting generalized linear models using DataSHIELD R.

RESULTS

We identified 5 DPs and 7 BCPs. The "bread, margarine, and processed meat" and "fruiting vegetables and vegetable oils" DPs were positively associated with the "amino acids" (β = 0.35; 95% CI: 0.02, 0.69; P = 0.03) and "fatty acids" MPs (β = 0.45; 95% CI: 0.16, 0.74; P = 0.01), respectively. The "tea and miscellaneous" was inversely associated with the "amino acids" (β = -0.28; 95% CI: -0.52, -0.05; P = 0.02) and "amino acid derivatives" MPs (β = -0.21; 95% CI: -0.39, -0.02; P = 0.03). One BCP negatively modified the association between the "bread, margarine, and processed meat" DP and the "amino acids" MP (P-interaction = 0.01).

CONCLUSIONS

In older German adults, DPs are reflected in MPs, and the gut bacteria attenuate 1 DP-MP association. These MPs should be explored as biomarkers of these jointly consumed foods while taking into account a potentially modifying role of the gut bacteria.

Biomarkers of meat and seafood intake: an extensive literature review

Meat, including fish and shellfish, represents a valuable constituent of most balanced diets. Consumption of different types of meat and fish has been associated with both beneficial and adverse health effects. While white meats and fish are generally associated with positive health outcomes, red and especially processed meats have been associated with colorectal cancer and other diseases. The contribution of these foods to the development or prevention of chronic diseases is still not fully elucidated. One of the main problems is the difficulty in properly evaluating meat intake, as the existing self-reporting tools for dietary assessment may be imprecise and therefore affected by systematic and random errors. Dietary biomarkers measured in biological fluids have been proposed as possible objective measurements of the actual intake of specific foods and as a support for classical assessment methods. Good biomarkers for meat intake should reflect total dietary intake of meat, independent of source or processing and should be able to differentiate meat consumption from that of other protein-rich foods; alternatively, meat intake biomarkers should be specific to each of the different meat sources (e.g., red vs. white; fish, bird, or mammal) and/or cooking methods. In this paper, we present a systematic investigation of the scientific literature while providing a comprehensive overview of the possible biomarker(s) for the intake of different types of meat, including fish and shellfish, and processed and heated meats according to published guidelines for biomarker reviews (BFIrev). The most promising biomarkers are further validated for their usefulness for dietary assessment by published validation criteria.

Blood biomarkers of various dietary patterns correlated with metabolic indicators in Taiwanese type 2 diabetes

Background

Metabolic alterations correlate with adverse outcomes in type 2 diabetes. Dietary modification serves as an integral part in its treatment.

Objective

We examined the relationships among dietary patterns, dietary biomarkers, and metabolic indicators in type 2 diabetes (n = 871).

Design

Diabetic patients (n = 871) who provided complete clinical and dietary data in both 2008 and 2009 were selected from a cohort participating in a diabetic control study in Taiwan. Dietary data were obtained using a short, semiquantitative food frequency questionnaires, and dietary pattern identified by factor analysis. Multiple linear regressions were used to analyze the association between dietary biomarkers (ferritin, folate, and erythrocyte n-3 polyunsaturated fatty acids [n-3 PUFAs]) and metabolic control upon adjusting for confounders.

Results

Three dietary patterns (high-fat meat, traditional Chinese food–snack, and fish–vegetable) were identified. Ferritin correlated positively with high-fat meat factor scores (P for trend <0.001). Erythrocyte n-3 PUFAs (eicosapentaenoic acid [EPA] + docosahexaenoic acid [DHA], n-3/n-6 PUFA ratio) correlated positively with fish–vegetable factor scores (all P for trends <0.001). Multiple linear regressions revealed a positive relationship between ferritin concentrations and fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), and triglycerides, but a negative relationship with high-density lipoprotein cholesterol (HDL-C). Erythrocyte n-3 PUFA, EPA+DHA, and n-3/n-6 PUFA ratio were negatively linked to FPG, HbA1c, and triglycerides (all P < 0.05) and positively with HDL-C (though n-3/n-6 ratio marginally correlated).

Conclusions

Ferritin and n-3 PUFA can serve as valid biomarkers for high-fat meat and fish–vegetable dietary patterns. Unlike ferritin, erythrocyte n-3 PUFA status was related to better glycemic and blood lipid profiles. Our results suggest that habitual consumption of diet pattern rich in fish and vegetables may contribute in part to a healthier metabolic profile in type 2 diabetes.

Associations of short stature and components of height with incidence of type 2 diabetes: mediating effects of cardiometabolic risk factors

AIMS/HYPOTHESIS

This study aimed to evaluate associations of height as well as components of height (sitting height and leg length) with risk of type 2 diabetes and to explore to what extent associations are explainable by liver fat and cardiometabolic risk markers.

METHODS

A case-cohort study within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study comprising 26,437 participants who provided blood samples was designed. We randomly selected a subcohort of 2500 individuals (2029 diabetes-free at baseline and with anamnestic, anthropometrical and metabolic data for analysis). Of the 820 incident diabetes cases identified in the full cohort during 7 years of follow-up, 698 remained for analyses after similar exclusions.

RESULTS

After adjustment for age, potential lifestyle confounders, education and waist circumference, greater height was related to lower diabetes risk (HR per 10 cm, men 0.59 [95% CI 0.47, 0.75] and women 0.67 [0.51, 0.88], respectively). Leg length was related to lower risk among men and women, but only among men if adjusted for total height. Adjustment for liver fat and triacylglycerols, adiponectin and C-reactive protein substantially attenuated associations between height and diabetes risk, particularly among women.

CONCLUSIONS/INTERPRETATION

We observed inverse associations between height and risk of type 2 diabetes, which was largely related to leg length among men. The inverse associations may be partly driven by lower liver fat content and a more favourable cardiometabolic profile.

Dietary Protein Consumption and the Risk of Type 2 Diabetes: ADose-Response Meta-Analysis of Prospective Studies

The relationship between dietary protein consumption and the risk of type 2 diabetes (T2D) has been inconsistent. The aim of this meta-analysis was to explore the relations between dietary protein consumption and the risk of T2D. We conducted systematic retrieval of prospective studies in PubMed, Embase, and Web of Science. Summary relative risks were compiled with a fixed effects model or a random effects model, and a restricted cubic spline regression model and generalized least squares analysis were used to evaluate the diet–T2D incidence relationship. T2D risk increased with increasing consumption of total protein and animal protein, red meat, processed meat, milk, and eggs, respectively, while plant protein and yogurt had an inverse relationship. A non-linear association with the risk for T2D was found for the consumption of plant protein, processed meat, milk, yogurt, and soy. This meta-analysis suggests that substitution of plant protein and yogurt for animal protein, especially red meat and processed meat, can reduce the risk for T2D.

Protective Effects of Dietary MUFAs Mediating Metabolites against Hypertension Risk in the Korean Genome and Epidemiology Study

Background and Aims: Metabolites related to dietary factors can be used to identify biological markers to prevent metabolic disease. However, most studies have been conducted in the United States and Europe, and those in the Asian region are limited. We investigated the effects of dietary monounsaturated fatty acids (MUFAs) and metabolites on new-onset hypertension in the Korean Genome and Epidemiology Study. Method and Results: A total of 1529 subjects without hypertension were divided into tertiles of dietary MUFAs intake. After a 4-year follow-up, 135 serum metabolites were measured using the AbsoluteIDQ p180 kit. During the 4-year follow-up period, 193 new-onset hypertension incidences were observed. The highest MUFAs intake group was inversely associated with the risk of hypertension compared with the lowest MUFAs intake group (odds ratio (OR) = 0.49, (95% confidence interval (CI) = 0.29–0.82)). Of the 135 metabolites, eight were significantly associated with MUFAs intake. Phosphatidylcholine-diacyl (PC aa) C 38:1 and hydroxysphingomyelin (SM OH) C 16:1 were associated with a decrease in hypertension risk (PC aa C 38:1, OR = 0.60 (95% CI = 0.37–0.96); SM OH C 16:1, OR = 0.42 (95% CI = 0.20–0.90)). The highest MUFAs intake group had a significantly decreased risk of hypertension, even considering PC aa C 38:1 and SM (OH) C 16:1 as a mediator. Conclusion: We confirmed that dietary MUFAs intake, and PC aa C 38:1 and SM (OH) C 16:1 had protective effects against hypertension. Furthermore, high MUFAs intake combined with PC aa C 38:1 and SM (OH) C 16:1 has the most significant effect on reducing the risk hypertension.

Dietary protein intake and subsequent risk of type 2 diabetes: a dose-response meta-analysis of prospective cohort studies

AIMS

Dietary proteins, including those obtained from animal and plant sources, have inconsistently been correlated with type 2 diabetes mellitus (T2DM) risk. Therefore, a meta-analysis was conducted to evaluate the association between dietary proteins and the risk of T2DM.

METHODS

Prospective cohort studies published until November 2018 were systematically searched in PubMed, Embase, and the Cochrane library. The pooled relative risks (RRs) were calculated with 95% confidence intervals (CIs) using the random-effects model.

RESULTS

Ten articles involving a total of 21 cohorts were included in the final meta-analysis. A total of 487,956 individuals were recruited in these studies and 38,350 T2DM cases were reported. Analysis of the pooled RRs indicated that high total protein intake was associated with an increased risk of T2DM (RR 1.10; P = 0.006), whereas moderate total protein intake was not significantly associated with T2DM risk (RR 1.00; P = 0.917). Moreover, a higher risk of T2DM was observed with high animal protein intake (RR 1.13; P = 0.013), whereas moderate animal protein intake had little or no effect on T2DM risk (RR 1.06; P = 0.058). Finally, high intake of plant protein did not affect T2DM risk (RR 0.93; P = 0.074), whereas moderate intake was associated with a reduced risk of T2DM (RR 0.94; P < 0.001).

CONCLUSIONS

The results of this study indicate that high total protein and animal protein intakes are associated with an increased risk of T2DM, whereas moderate plant protein intake is associated with a decreased risk of T2DM.