Plasma fatty acid patterns reflect dietary habits and metabolic health: A cross-sectional study

Erythrocyte Very Long-Chain Saturated Fatty Acids, Gut Microbiota-Bile Acid Axis, and Incident Coronary Artery Disease in Adults: A Prospective Cohort Study

BACKGROUND

Prior research has highlighted inverse associations between concentrations of circulating very long-chain saturated fatty acids (VLCSFAs) and coronary artery disease (CAD). However, the intricate links involving VLCSFAs, gut microbiota, and bile acids remain underexplored.

OBJECTIVES

This study examined the association of erythrocyte VLCSFAs with CHD incidence, focusing on the mediating role of gut microbiota and fecal bile acids.

METHODS

This 10-y prospective study included 2383 participants without CHD at baseline. Erythrocyte VLCSFAs [arachidic acid (C20:0), behenic acid (C22:0), and lignoceric acid (C24:0)] were measured using gas chromatography at baseline, and 274 CHD incidents were documented in triennial follow-ups. Gut microbiota in 1744 participants and fecal bile acid metabolites in 945 participants were analyzed using 16S ribosomal ribonucleic acid sequencing and ultra-performance liquid chromatography-tandem mass spectrometry at middle-term.

RESULTS

The multivariable-adjusted hazard ratios (95% confidence interval) for CHD incidence in highest compared with lowest quartiles were 0.87 (0.61, 1.25) for C20:0, 0.63 (0.42, 0.96) for C22:0, 0.59 (0.41, 0.85) for C24:0, and 0.57 (0.39, 0.83) for total VLCSFAs. Participants with higher total VLCSFA concentrations exhibited increased abundances of Holdemanella, Coriobacteriales Incertae Sedis spp., Ruminococcaceae UCG-005 and UCG-010, and Lachnospiraceae ND3007 group. These 5 genera generated overlapping differential microbial scores (ODMSs) that accounted for 11.52% of the total VLCSFAs-CHD association (Pmediation = 0.018). Bile acids tauro_α_ and tauro_β_muricholic acid were inversely associated with ODMS and positively associated with incident CHD. Opposite associations were found for glycolithocholic acid and glycodeoxycholic acid. Mediation analyses indicated that glycolithocholic acid, glycodeoxycholic acid, and tauro_α_ and tauro_β_muricholic acid explained 56.40%, 35.19%, and 26.17% of the ODMS-CHD association, respectively (Pmediation = 0.002, 0.008, and 0.020).

CONCLUSIONS

Elevated erythrocyte VLCSFAs are inversely associated with CHD risk in the Chinese population, with gut microbiota and fecal bile acid profiles potentially mediating this association. The identified microbiota and bile acid metabolites may serve as potential intervention targets in future studies. This trial was registered at www.

CLINICALTRIALS

gov as NCT03179657.

Association of Circulating Very Long-Chain Saturated Fatty Acids With Cardiovascular Mortality in NHANES 2003-2004, 2011-2012

CONTEXT

Limited studies have shown a protective effect of very long-chain saturated fatty acids (VLSFAs) on healthy aging, diabetes, heart failure, and risk factors related to cardiovascular disease (CVD), but the role of VLSFAs on mortality risk is unclear.

OBJECTIVE

We aimed to investigate the association of serum docosanoic acid (C22:0) and serum lignoceric acid (C24:0) with all-cause and disease-specific mortality and to confirm the effect of VLSFAs on mortality risk in the whole, hyperlipidemia, and hypertensive populations.

METHODS

A total of 4132 individuals from the 2003-2004, 2011-2012 National Health and Nutrition Examination Survey (NHANES) were included in this study. There were 1326 and 1456 participants in the hyperlipidemia and hypertensive population, respectively. Mortality information was confirmed using the National Death Index (NDI). Multiple model calibration was performed using Cox regression analysis for known risk factors to explore the association between circulating VLSFAs and all-cause or CVD or coronary heart disease (CHD) mortality.

RESULTS

In the whole population, individuals with higher circulating C22:0 and C24:0 as a percentage of total serum fatty acid levels reduced the risks of mortality of all-cause (C22:0: HR = .409; 95% CI, 0.271-0.618; C24:0: HR = 0.430; 95% CI, 0.283-0.651), CVD (C22:0: HR = 0.286; 95% CI, 0.134-0.612; C24:0: HR = 0.233; 95% CI, 0.101-0.538), and CHD (C22:0: HR = 0.401; 95% CI, 0.187-0.913; C24:0: HR = 0.263; 95% CI, 0.082-0.846). Similar to the whole population, individuals with higher circulating C22:0 and C24:0 as a percentage of total serum fatty acid levels in the hyperlipidemia and hypertensive populations were also protective for all-cause, CHD, and CVD mortality.

CONCLUSION

Our results confirm the protective effect of high levels of circulating VLSFAs (C22:0 and C24:0) on CVD, CHD, and all causes of death in the whole, hyperlipidemia, and hypertensive populations.

Optimized Metabotype Definition Based on a Limited Number of Standard Clinical Parameters in the Population-Based KORA Study

The aim of metabotyping is to categorize individuals into metabolically similar groups. Earlier studies that explored metabotyping used numerous parameters, which made it less transferable to apply. Therefore, this study aimed to identify metabotypes based on a set of standard laboratory parameters that are regularly determined in clinical practice. K-means cluster analysis was used to group 3001 adults from the KORA F4 cohort into three clusters. We identified the clustering parameters through variable importance methods, without including any specific disease endpoint. Several unique combinations of selected parameters were used to create different metabotype models. Metabotype models were then described and evaluated, based on various metabolic parameters and on the incidence of cardiometabolic diseases. As a result, two optimal models were identified: a model composed of five parameters, which were fasting glucose, HDLc, non-HDLc, uric acid, and BMI (the metabolic disease model) for clustering; and a model that included four parameters, which were fasting glucose, HDLc, non-HDLc, and triglycerides (the cardiovascular disease model). These identified metabotypes are based on a few common parameters that are measured in everyday clinical practice. These metabotypes are cost-effective, and can be easily applied on a large scale in order to identify specific risk groups that can benefit most from measures to prevent cardiometabolic diseases, such as dietary recommendations and lifestyle interventions.

Impact of DHA from Algal Oil on the Breast Milk DHA Levels of Lactating Women: A Randomized Controlled Trial in China

Population research on the intervention of docosahexaenoic acid (DHA) supplementation in lactating women is in its infancy in China. This study investigated the effect of DHA supplementation on DHA concentrations in the breast milk of lactating women, and the intervention effect, with respect to different dietary patterns. In this trial, 160 healthy lactating women in Nanjing (30−50 days postpartum) were recruited and randomly divided into control (one placebo capsule of similar appearance per day) and supplement (one capsule with 200 mg of DHA from algal oil per day) groups for 8 weeks. Before and after the intervention, all subjects were asked to maintain basic information, maternal anthropometric parameters, breast milk (10−15 mL) sample collection, and a dietary survey using a food frequency questionnaire. The concentrations of DHA and other fatty acids in breast milk were detected using capillary gas chromatography. This study was completed by 137 subjects, with 60 in the control group and 77 in the supplement group. Compared with the DHA concentrations in the breast milk at enrollment, the absolute concentrations of the control group showed a significant decrease at the end of the trial (p = 0.037). In addition, after intervention, the absolute and relative DHA concentrations in the supplement group (10.07 mg/100 mL and 0.40%, respectively) were higher than those in the control group (7.57 mg/100 mL and 0.28%, respectively), being statistically significant (p = 0.012 and p = 0.001). Furthermore, the maternal diet in the supplement group was divided into four dietary patterns. Pattern 1 mainly included fruits and livestock meat. Pattern 2 was dominated by milk and its products, eggs, fish, shrimp and shellfish, and soybeans and its products. Pattern 3 chiefly comprised cereal and beans other than soybeans, potatoes, and nuts. Pattern 4 was high in poultry meat and low in cooking oils. The change in the absolute concentration of DHA in Pattern 3 was lower than that in other patterns (p < 0.05). In conclusion, DHA supplementation in lactating mothers increased breast milk DHA concentrations. The dietary pattern mainly characterized by cereal and beans other than soybeans, potatoes, and nuts may contribute to the poor intervention effect.

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.

The Association Between Plasma Fatty Acid and Cognitive Function Mediated by Inflammation in Patients with Type 2 Diabetes Mellitus

PURPOSE

To verify the mediating role of inflammatory factors in plasma fatty acid-induced changes in cognitive function in patients with type 2 diabetes mellitus (T2DM).

PATIENTS AND METHODS

In this study, we evaluated the cognitive function of 372 Chinese patients (the average age was 58.00 (52.50, 63.00) years) with T2DM by using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), with plasma fatty acids measured by gas chromatography analysis and inflammatory cytokines determined by immune turbidimetric analysis and enzyme-linked immunosorbent assay (ELISA) to investigate whether there was a correlation between the plasma fatty acids, inflammatory cytokine levels and cognitive test scores in Chinese patients with T2DM.

RESULTS

We found that the increase of waist circumference and hip circumference might lead to cognitive impairment and induce the inflammatory response. Higher saturated fatty acids (SFAs) levels in plasma were linked to cognitive decline, while higher monounsaturated fatty acids (MUFAs) intake might be a protective factor for cognitive function. In addition, higher levels of plasma n-6 polyunsaturated fatty acids (n-6 PUFAs) stood out as having association with lower cognitive function scores, while higher level of plasma C22:6 n-3 could be a predictor of better cognitive function. In our study, higher SFAs led to higher proinflammatory factor levels. Apart from that, MUFAs and stearoyl-CoA desaturase-18 (SCD-18) were positively related to hypersensitive C-reactive protein (hs-CRP). Meanwhile, higher level of plasma C20:0 could lead to better MMSE delayed recall by reduce the expression of hs-CRP.

CONCLUSION

Levels of plasma SFAs, C18:3 n-6, and C20:3 n-6 could be a predictor for worse cognitive function, while MUFAs and C22:6 n-3 could be a predictor for better cognitive function. The level of hs-CRP could be a mediator of C20:0 induced the change of cognitive function.

Association between dietary fatty acid patterns based on principal component analysis and fatty acid compositions of serum and breast milk in lactating mothers in Nanjing, China

This study aimed to comprehensively analyze dietary fatty acids (FAs) to evaluate their association with FA compositions of maternal serum and breast milk and assess their effects on mothers and infants. Overall, 121 healthy lactating Chinese mothers at 30-50 days of postpartum were enrolled and instructed to complete a Food Frequency Questionnaire, together with venous blood and breast milk sample collections. Dietary FA patterns were derived by principal component analysis with varimax rotation. Serum and breast milk FA compositions were detected using capillary gas chromatography and presented as relative concentrations (weight percentage of total FAs, %). Daily energy intake, absolute intake of most nutrients, and percentage of energy intake provided by these nutrients significantly varied among the different dietary FA patterns. There were significant differences in serum polyunsaturated fatty acid (PUFA) levels (P = 0.011); in monounsaturated fatty acid and PUFA proportions in breast milk with respect to four patterns (P = 0.002 and P = 0.026, respectively); and in n-6 PUFA, n-3 PUFA, linoleic acid, γ-linolenic acid, α-linolenic acid, and docosahexaenoic acid levels in breast milk (P = 0.027, P = 0.007, P = 0.048, P = 0.034, P = 0.020, and P = 0.002, respectively). Furthermore, maternal weight retention and length-for-age z scores, weight-for-age z scores and head circumference-for-age z scores of infants with respect to the four patterns exhibited significant differences (P = 0.038, P = 0.030, P = 0.034, and P<0.001, respectively). The results demonstrated the effect of dietary FA patterns on FA compositions of serum and breast milk, and patterns mainly characterized by LC-PUFA may have potentially beneficial effects on maternal postpartum recovery and infant growth.

Serum levels of n-3 and n-6 polyunsaturated fatty acids in patients with systemic lupus erythematosus and their association with disease activity: a pilot study

Objective: Polyunsaturated fatty acids (PUFAs) may modulate the inflammatory process in systemic autoimmune diseases, including systemic lupus erythematosus (SLE). The aim of this study was to assess the serum concentrations of essential 18-carbon PUFAs and their long-chain derivatives in patients with SLE and healthy controls, and to analyse their associations with laboratory and clinical features of the disease.Method: n-6 and n-3 PUFA composition was assessed in the sera of 30 SLE patients and 20 healthy controls using gas chromatography-mass spectrometry. We investigated the associations between PUFAs and disease activity measured with Systemic Lupus Erythematosus Activity Index (SLEDAI) scores, erythrocyte sedimentation rate, C-reactive protein, complement C3 and C4 concentrations, anti-nuclear antibody (ANA) titre, anti-double-stranded DNA (anti-dsDNA) antibody concentration, and medications.Results: Serum linoleic acid (LA) and α-linolenic acid concentrations were significantly higher in SLE patients compared with healthy controls. LA concentration correlated positively with the ANA titre and corticosteroid doses; eicosapentaenoic acid (EPA) and docosahexaenoic acid correlated inversely with anti-dsDNA antibody concentration. Patients treated with immunosuppressants had significantly lower concentrations of LA, arachidonic acid, and EPA.Conclusion: Both n-6 and n-3 PUFA precursors can participate in the inflammatory process in SLE patients. The mechanism of the PUFA metabolism disturbance needs further exploration.

Optimisation of a metabotype approach to deliver targeted dietary advice

BACKGROUND

Targeted nutrition is defined as dietary advice tailored at a group level. Groups known as metabotypes can be identified based on individual metabolic profiles. Metabotypes have been associated with differential responses to diet, which support their use to deliver dietary advice. We aimed to optimise a metabotype approach to deliver targeted dietary advice by encompassing more specific recommendations on nutrient and food intakes and dietary behaviours.

METHODS

Participants (n = 207) were classified into three metabotypes based on four biomarkers (triacylglycerol, total cholesterol, HDL-cholesterol and glucose) and using a k-means cluster model. Participants in metabotype-1 had the highest average HDL-cholesterol, in metabotype-2 the lowest triacylglycerol and total cholesterol, and in metabotype-3 the highest triacylglycerol and total cholesterol. For each participant, dietary advice was assigned using decision trees for both metabotype (group level) and personalised (individual level) approaches. Agreement between methods was compared at the message level and the metabotype approach was optimised to incorporate messages exclusively assigned by the personalised approach and current dietary guidelines. The optimised metabotype approach was subsequently compared with individualised advice manually compiled.

RESULTS

The metabotype approach comprised advice for improving the intake of saturated fat (69% of participants), fibre (66%) and salt (18%), while the personalised approach assigned advice for improving the intake of folate (63%), fibre (63%), saturated fat (61%), calcium (34%), monounsaturated fat (24%) and salt (14%). Following the optimisation of the metabotype approach, the most frequent messages assigned to address intake of key nutrients were to increase the intake of fruit and vegetables, beans and pulses, dark green vegetables, and oily fish, to limit processed meats and high-fat food products and to choose fibre-rich carbohydrates, low-fat dairy and lean meats (60-69%). An average agreement of 82.8% between metabotype and manual approaches was revealed, with excellent agreements in metabotype-1 (94.4%) and metabotype-3 (92.3%).

CONCLUSIONS

The optimised metabotype approach proved capable of delivering targeted dietary advice for healthy adults, being highly comparable with individualised advice. The next step is to ascertain whether the optimised metabotype approach is effective in changing diet quality.

Circulating Very-Long-Chain Saturated Fatty Acids Were Inversely Associated with Cardiovascular Health: A Prospective Cohort Study and Meta-Analysis

Saturated fatty acids with different chain lengths have different biological activities, but little is known about very-long-chain saturated fatty acids (VLCSFAs). This study investigated the associations between the circulating VLCSFAs and cardiovascular health. This community-based cohort study included 2198 adults without carotid artery plaques (CAPs) at baseline. The percentage of baseline erythrocyte VLCSFA (arachidic acid (C20:0), behenic acid (C22:0), and lignoceric acid (C24:0)) was measured by gas chromatography. The presence of CAPs was determined at baseline and every 3 years thereafter by ultrasound examination. A meta-analysis was conducted to summarize the pooled associations between circulating VLCSFAs and the risk of cardiovascular diseases (CVDs). During a median of 7.2 years of follow-up, 573 women (35.1%) and 281 men (49.6%) were identified as CAP incident cases. VLCSFAs were inversely related with CAP risk in women (all p-trend <0.05) but not in men. Multivariate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of CAPs for the highest (vs. lowest) quartile were 0.80 (0.63–1.01) for C20:0, 0.71 (0.56–0.89) for C22:0, 0.75 (0.59–0.94) for C24:0, and 0.69 (0.55–0.87) for total VLCSFAs in women. The pooled HRs (95% CIs) of CVDs for the highest (vs. lowest) circulating VLCSFAs from seven studies including 8592 participants and 3172 CVD events were 0.67 (0.57–0.79) for C20:0, 0.66 (0.48–0.90) for C22:0, and 0.57 (0.42–0.79) for C24:0, respectively. Our findings suggested that circulating VLCSFAs were inversely associated with cardiovascular health.

Perspective: Metabotyping-A Potential Personalized Nutrition Strategy for Precision Prevention of Cardiometabolic Disease

Diet is an important, modifiable lifestyle factor of cardiometabolic disease risk, and an improved diet can delay or even prevent the onset of disease. Recent evidence suggests that individuals could benefit from diets adapted to their genotype and phenotype: that is, personalized nutrition. A novel strategy is to tailor diets for groups of individuals according to their metabolic phenotypes (metabotypes). Randomized controlled trials evaluating metabotype-specific responses and nonresponses are urgently needed to bridge the current gap of knowledge with regard to the efficacy of personalized strategies in nutrition. In this Perspective, we discuss the concept of metabotyping, review the current literature on metabotyping in the context of cardiometabolic disease prevention, and suggest potential strategies for metabotype-based nutritional advice for future work. We also discuss potential determinants of metabotypes, including gut microbiota, and highlight the use of metabolomics to define effective markers for cardiometabolic disease-related metabotypes. Moreover, we hypothesize that people at high risk for cardiometabolic diseases have distinct metabotypes and that individuals grouped into specific metabotypes may respond differently to the same diet, which is being tested in a project of the Joint Programming Initiative: A Healthy Diet for a Healthy Life.

Paving the Way to Precision Nutrition Through Metabolomics

Nutrition is an interdisciplinary science that studies the interactions of nutrients with the body in relation to maintenance of health and well-being. Nutrition is highly complex due to the underlying various internal and external factors that could model it. Thus, hacking this complexity requires more holistic and network-based strategies that could unveil these dynamic system interactions at both time and space scales. The ongoing omics era with its high-throughput molecular data generation is paving the way to embrace this complexity and is deeply reshaping the whole field of nutrition. Understanding the future paths of nutrition science is of importance from both translational and clinical perspectives. Basic nutrients which might include metabolites are important in nutrition science. Moreover, metabolites are key biological communication channels and represent an appealing functional readout at the interface of different major influential factors that define health and disease. Metabolomics is the technology that enables holistic and systematic analyses of metabolites in a biological system. Hence, given its intrinsic functionality, its tight connection to metabolism and its high clinical actionability potential, metabolomics is a very appealing technology for nutrition science. The ultimate goal is to deliver a tailored and clinically relevant nutritional recommendations and interventions to achieve precision nutrition. This work intends to present an update on the applications of metabolomics to personalize nutrition in translational and clinical settings. It also discusses the current conceptual shifts that are remodeling clinical nutrition practices in this Precision Medicine era. Finally, perspectives of clinical nutrition in the ever-growing, data-driven healthcare landscape are presented.

Application of metabolomics part II: Focus on fatty acids and their metabolites in healthy adults

Fatty acids (FAs) play critical roles in health and disease. The detection of FA imbalances through metabolomics can provide an overview of an individual’s health status, particularly as regards chronic inflammatory disorders. In this study, we aimed to establish sensitive reference value ranges for targeted plasma FAs in a well-defined population of healthy adults. Plasma samples were collected from 159 participants admitted as outpatients. A total of 24 FAs were analyzed using gas chromatography-mass spectrometry, and physiological values and 95% reference intervals were calculated using an approximate method of analysis. The differences among the age groups for the relative levels of stearic acid (P=0.005), the omega-6/omega-3 ratio (P=0.027), the arachidonic acid/eicosapentaenoic acid ratio (P<0.001) and the linoleic acid-produced dihomo-gamma-linolenic acid (P=0.046) were statistically significant. The majority of relative FA levels were higher in males than in females. The levels of myristic acid (P=0.0170) and docosahexaenoic acid (P=0.033) were signifi-cantly different between the sexes. The reference values for the FAs examined in this study represent a baseline for further studies examining the reproducibility of this methodology and sensitivities for nutrient deficiency detection and investigating the biochemical background of pathological conditions. The application of these values to clinical practice will allow for the discrimination between health and disease and contribute to early prevention and treatment.

Identification of Comprehensive Metabotypes Associated with Cardiometabolic Diseases in the Population-Based KORA Study

SCOPE

"Metabotyping" describes the grouping of metabolically similar individuals. We aimed to identify valid metabotypes in a large cohort for targeted dietary intervention, for example, for disease prevention.

METHODS AND RESULTS

We grouped 1729 adults aged 32-77 years of the German population-based KORA F4 study (2006-2008) using k-means cluster analysis based on 34 biochemical and anthropometric parameters. We identified three metabolically distinct clusters showing significantly different biochemical parameter concentrations. Cardiometabolic disease status was determined at baseline in the F4 study and at the 7 year follow-up termed FF4 (2013/2014) to compare disease prevalence and incidence between clusters. Cluster 3 showed the most unfavorable marker profile with the highest prevalence of cardiometabolic diseases. Also, disease incidence was higher in cluster 3 compared to clusters 2 and 1, respectively, for hypertension (41.2%/25.3%/18.2%), type 2 diabetes (28.3%/5.1%/2.0%), hyperuricemia/gout (10.8%/2.3%/0.7%), dyslipidemia (19.2%/18.3%/5.6%), all metabolic (54.5%/36.8%/19.7%), and all cardiovascular (6.3%/5.5%/2.3%) diseases together.

CONCLUSION

Cluster analysis based on an extensive set of biochemical and anthropometric parameters allows the identification of comprehensive metabotypes that were distinctly different in cardiometabolic disease occurrence. As a next step, targeted dietary strategies should be developed with the goal of preventing diseases, especially in cluster 3.

Processed red meat contribution to dietary patterns and the associated cardio-metabolic outcomes

Evidence suggests that processed red meat consumption is a risk factor for CVD and type 2 diabetes (T2D). This analysis investigates the association between dietary patterns, their processed red meat contributions, and association with blood biomarkers of CVD and T2D, in 786 Irish adults (18–90 years) using cross-sectional data from a 2011 national food consumption survey. All meat-containing foods consumed were assigned to four food groups (n 502) on the basis of whether they contained red or white meat and whether they were processed or unprocessed. The remaining foods (n 2050) were assigned to twenty-nine food groups. Two-step and k-means cluster analyses were applied to derive dietary patterns. Nutrient intakes, plasma fatty acids and biomarkers of CVD and T2D were assessed. A total of four dietary patterns were derived. In comparison with the pattern with lower contributions from processed red meat, the dietary pattern with greater processed red meat intakes presented a poorer Alternate Healthy Eating Index (21·2 (sd 7·7)), a greater proportion of smokers (29 %) and lower plasma EPA (1·34 (sd 0·72) %) and DHA (2·21 (sd 0·84) %) levels (P<0·001). There were no differences in classical biomarkers of CVD and T2D, including serum cholesterol and insulin, across dietary patterns. This suggests that the consideration of processed red meat consumption as a risk factor for CVD and T2D may need to be re-assessed.

Metabotyping and its application in targeted nutrition: an overview

Metabolic diversity leads to differences in nutrient requirements and responses to diet and medication between individuals. Using the concept of metabotyping – that is, grouping metabolically similar individuals – tailored and more efficient recommendations may be achieved. The aim of this study was to review the current literature on metabotyping and to explore its potential for better targeted dietary intervention in subjects with and without metabolic diseases. A comprehensive literature search was performed in PubMed, Google and Google Scholar to find relevant articles on metabotyping in humans including healthy individuals, population-based samples and patients with chronic metabolic diseases. A total of thirty-four research articles on human studies were identified, which established more homogeneous subgroups of individuals using statistical methods for analysing metabolic data. Differences between studies were found with respect to the samples/populations studied, the clustering variables used, the statistical methods applied and the metabotypes defined. According to the number and type of the selected clustering variables, the definitions of metabotypes differed substantially; they ranged between general fasting metabotypes, more specific fasting parameter subgroups like plasma lipoprotein or fatty acid clusters and response groups to defined meal challenges or dietary interventions. This demonstrates that the term ‘metabotype’ has a subjective usage, calling for a formalised definition. In conclusion, this literature review shows that metabotyping can help identify subgroups of individuals responding differently to defined nutritional interventions. Targeted recommendations may be given at such metabotype group levels. Future studies should develop and validate definitions of generally valid metabotypes by exploiting the increasingly available metabolomics data sets.

Polymorphisms of the TNF-α gene interact with plasma fatty acids on inflammatory biomarker profile: a population-based, cross-sectional study in São Paulo, Brazil

The aim of the present study was to investigate the relationship of four TNF-α SNP with inflammatory biomarkers and plasma fatty acids (FA), and the interaction among them in a population-based, cross-sectional study in São Paulo, Brazil. A total of 281 subjects, aged >19 and <60 years, participated in a cross-sectional, population-based study performed in Brazil. The following SNP spanning the TNF-α gene were genotyped: -238G/A (rs361525), -308G/A (rs1800629), -857C/T (rs1799724) and -1031T/C (rs1799964). In all, eleven plasma inflammatory biomarkers and plasma FA profile were determined. To analyse the interaction between TNF-α SNP and plasma FA, a cluster analysis was performed to stratify individuals based on eleven inflammatory biomarkers into two groups used as outcome: inflammatory (INF) and non-inflammatory clusters. The -238A allele carriers had higher TNF-α (P=0·033), IL-6 (P=0·013), IL-1β (P=0·037), IL-12 (0·048) and IL-10 (P=0·010) than the GG genotype. The -308A allele carriers also had lower levels of plasma palmitoleic acid (P=0·009), oleic acid (P=0·039), total MUFA (P=0·014), stearoyl-CoA desaturase (SCD) activity index-16 (P=0·007), SCD-18 (P=0·020) and higher levels of PUFA (P=0·046) and DHA (P=0·044). Significant interactions modifying the risk of belonging to the INF cluster were observed with inflammatory cluster as outcome between -857C/T and plasma α-linolenic acid (P=0·026), and also between -308G/A and plasma stearic acid (P=0·044) and total SFA (P=0·040). Our study contributes to knowledge on TNF-α SNP and their association with inflammatory biomarker levels, plasma FA and the interaction among them, of particular interest for the Brazilian population.

The profile of polyunsaturated fatty acids in juvenile idiopathic arthritis and association with disease activity

We investigated the association between dietary intake of n-3 and n-6 polyunsaturated fatty acids (PUFAs), serum profiles, and immune and inflammatory markers in juvenile idiopathic arthritis (JIA) in relation to onset, activity, and duration. A total of 66 JIA patients and 42 controls were included. Serum PUFA levels were assessed by gas-liquid chromatography-mass spectrometry, a dietary intake by 7-day dietary record method, and IL-6, IL-10, and IL-17A levels using ELISA. Dietary PUFA intake did not differ between the JIA group and controls. Intakes of n-6 and n-3 PUFA and serum levels were not associated. Levels of total n-6 PUFA and linoleic acid (LA) were higher in inactive JIA than in active JIA. Patients with active and short-lasting disease (less than 3 months from diagnosis) had significantly lower levels of arachidonic acid (AA) and docosahexaenoic acid (DHA) than the control. Serum α-linolenic acid (ALA) levels were significantly higher in poly-JIA than in oligo-JIA and in controls. We found significantly higher serum IL-10 levels in JIA than in controls. Serum n-6 and n-3 levels were significantly negatively correlated with active joint count, erythrocyte sedimentation rate, and C-reactive protein and positively with platelet count. Our study presents the low levels of AA and DHA in the active phase of short-lasting JIA, particularly poly-JIA, and the relationship between n-6 and n-3 PUFA and classic markers of inflammation. PUFAs may contribute to the pathogenesis of JIA and support a necessity to identify new targets suitable for successful interventional studies in JIA patients.