Lipidome changes due to improved dietary fat quality inform cardiometabolic risk reduction and precision nutrition.

Current cardiometabolic disease prevention guidelines recommend increasing dietary unsaturated fat intake while reducing saturated fats. Here we use lipidomics data from a randomized controlled dietary intervention trial to construct a multilipid score (MLS), summarizing the effects of replacing saturated fat with unsaturated fat on 45 lipid metabolite concentrations. In the EPIC-Potsdam cohort, a difference in the MLS, reflecting better dietary fat quality, was associated with a significant reduction in the incidence of cardiovascular disease (-32%; 95% confidence interval (95% CI): -21% to -42%) and type 2 diabetes (-26%; 95% CI: -15% to -35%). We built a closely correlated simplified score, reduced MLS (rMLS), and observed that beneficial rMLS changes, suggesting improved dietary fat quality over 10 years, were associated with lower diabetes risk (odds ratio per standard deviation of 0.76; 95% CI: 0.59 to 0.98) in the Nurses' Health Study. Furthermore, in the PREDIMED trial, an olive oil-rich Mediterranean diet intervention primarily reduced diabetes incidence among participants with unfavorable preintervention rMLS levels, suggestive of disturbed lipid metabolism before intervention. Our findings indicate that the effects of dietary fat quality on the lipidome can contribute to a more precise understanding and possible prediction of the health outcomes of specific dietary fat modifications.

Broadcasters, receivers, functional groups of metabolites, and the link to heart failure by revealing metabolomic network connectivity.

BACKGROUND AND OBJECTIVE: Blood-based small molecule metabolites offer easy accessibility and hold significant potential for insights into health processes, the impact of lifestyle, and genetic variation on disease, enabling precise risk prevention. In a prospective study with records of heart failure (HF) incidence, we present metabolite profiling data from individuals without HF at baseline. METHODS: We uncovered the interconnectivity of metabolites using data-driven and causal networks augmented with polygenic factors. Exploring the networks, we identified metabolite broadcasters, receivers, mediators, and subnetworks corresponding to functional classes of metabolites, and provided insights into the link between metabolomic architecture and regulation in health. We incorporated the network structure into the identification of metabolites associated with HF to control the effect of confounding metabolites. RESULTS: We identified metabolites associated with higher and lower risk of HF incidence, such as glycine, ureidopropionic and glycocholic acids, and LPC 18:2. These associations were not confounded by the other metabolites due to uncovering the connectivity among metabolites and adjusting each association for the confounding metabolites. Examples of our findings include the direct influence of asparagine on glycine, both of which were inversely associated with HF. These two metabolites were influenced by polygenic factors and only essential amino acids, which are not synthesized in the human body and are obtained directly from the diet. CONCLUSION: Metabolites may play a critical role in linking genetic background and lifestyle factors to HF incidence. Revealing the underlying connectivity of metabolites associated with HF strengthens the findings and facilitates studying complex conditions like HF.

Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies.

BACKGROUND: A healthy lifestyle is associated with a lower premature mortality risk and with longer life expectancy. However, the metabolic pathways of a healthy lifestyle and how they relate to mortality and longevity are unclear. We aimed to identify and replicate a healthy lifestyle metabolomic signature and examine how it is related to total and cause-specific mortality risk and longevity. METHODS: In four large cohorts with 13,056 individuals and 28-year follow-up, we assessed five healthy lifestyle factors, used liquid chromatography mass spectrometry to profile plasma metabolites, and ascertained deaths with death certificates. The unique healthy lifestyle metabolomic signature was identified using an elastic regression. Multivariable Cox regressions were used to assess associations of the signature with mortality and longevity. FINDINGS: The identified healthy lifestyle metabolomic signature was reflective of lipid metabolism pathways. Shorter and more saturated triacylglycerol and diacylglycerol metabolite sets were inversely associated with the healthy lifestyle score, whereas cholesteryl ester and phosphatidylcholine plasmalogen sets were positively associated. Participants with a higher healthy lifestyle metabolomic signature had a 17% lower risk of all-cause mortality, 19% for cardiovascular disease mortality, and 17% for cancer mortality and were 25% more likely to reach longevity. The healthy lifestyle metabolomic signature explained 38% of the association between the self-reported healthy lifestyle score and total mortality risk and 49% of the association with longevity. CONCLUSIONS: This study identifies a metabolomic signature that measures adherence to a healthy lifestyle and shows prediction of total and cause-specific mortality and longevity. FUNDING: This work was funded by the NIH, CIHR, AHA, Novo Nordisk Foundation, and SciLifeLab.

Lifetime Duration of Breastfeeding and Cardiovascular Risk in Women With Type 2 Diabetes or a History of Gestational Diabetes: Findings From Two Large Prospective Cohorts.

OBJECTIVE: Breastfeeding duration is inversely associated with risks of cardiovascular disease (CVD) and type 2 diabetes in parous women. However, the association among women at high risk, including women with type 2 diabetes or gestational diabetes mellitus (GDM) is unclear. RESEARCH DESIGN AND METHODS: We included 15,146 parous women with type 2 diabetes from the Nurses' Health Study I and II (NHS, NHS II) and 4,537 women with a history of GDM from NHS II. Participants reported history of breastfeeding via follow-up questionnaires. Incident CVD by 2017 comprised stroke or coronary heart disease (CHD) (myocardial infarction, coronary revascularization). Adjusted hazard ratios (aHRs) and 95% CIs were estimated using Cox models. RESULTS: We documented 1,159 incident CVD cases among women with type 2 diabetes in both cohorts during 188,874 person-years of follow-up and 132 incident CVD cases among women with a GDM history during 100,218 person-years of follow-up. Longer lifetime duration of breastfeeding was significantly associated with lower CVD risk among women with type 2 diabetes, with pooled aHR of 0.68 (95% CI 0.54-0.85) for >18 months versus 0 months and 0.94 (0.91-0.98) per 6-month increment in breastfeeding. Similar associations were observed with CHD (pooled aHR 0.93 [0.88-0.97]) but not with stroke (0.96 [0.91-1.02]) per 6-month increment in breastfeeding. Among women with GDM history, >18 months versus 0 months of breastfeeding was associated with an aHR of 0.49 (0.28-0.86) for total CVD. CONCLUSIONS: Longer duration of breastfeeding was associated with lower risk of CVD in women with type 2 diabetes or GDM.

Plasma metabolite predictors of metabolic syndrome incidence and reversion.

BACKGROUND: Metabolic Syndrome (MetS) is a progressive pathophysiological state defined by a cluster of cardiometabolic traits. However, little is known about metabolites that may be predictors of MetS incidence or reversion. Our objective was to identify plasma metabolites associated with MetS incidence or MetS reversion. METHODS: The study included 1468 participants without cardiovascular disease (CVD) but at high CVD risk at enrollment from two case-cohort studies nested within the PREvención con DIeta MEDiterránea (PREDIMED) study with baseline metabolomics data. MetS was defined in accordance with the harmonized International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute criteria, which include meeting 3 or more thresholds for waist circumference, triglyceride, HDL cholesterol, blood pressure, and fasting blood glucose. MetS incidence was defined by not having MetS at baseline but meeting the MetS criteria at a follow-up visit. MetS reversion was defined by MetS at baseline but not meeting MetS criteria at a follow-up visit. Plasma metabolome was profiled by LC-MS. Multivariable-adjusted Cox regression models and elastic net regularized regressions were used to assess the association of 385 annotated metabolites with MetS incidence and MetS reversion after adjusting for potential risk factors. RESULTS: Of the 603 participants without baseline MetS, 298 developed MetS over the median 4.8-year follow-up. Of the 865 participants with baseline MetS, 285 experienced MetS reversion. A total of 103 and 88 individual metabolites were associated with MetS incidence and MetS reversion, respectively, after adjusting for confounders and false discovery rate correction. A metabolomic signature comprised of 77 metabolites was robustly associated with MetS incidence (HR: 1.56 (95 % CI: 1.33-1.83)), and a metabolomic signature of 83 metabolites associated with MetS reversion (HR: 1.44 (95 % CI: 1.25-1.67)), both p < 0.001. The MetS incidence and reversion signatures included several lipids (mainly glycerolipids and glycerophospholipids) and branched-chain amino acids. CONCLUSION: We identified unique metabolomic signatures, primarily comprised of lipids (including glycolipids and glycerophospholipids) and branched-chain amino acids robustly associated with MetS incidence; and several amino acids and glycerophospholipids associated with MetS reversion. These signatures provide novel insights on potential distinct mechanisms underlying the conditions leading to the incidence or reversion of MetS.

Mapping of the gene network that regulates glycan clock of ageing.

Glycans are an essential structural component of immunoglobulin G (IgG) that modulate its structure and function. However, regulatory mechanisms behind this complex posttranslational modification are not well known. Previous genome-wide association studies (GWAS) identified 29 genomic regions involved in regulation of IgG glycosylation, but only a few were functionally validated. One of the key functional features of IgG glycosylation is the addition of galactose (galactosylation), a trait which was shown to be associated with ageing. We performed GWAS of IgG galactosylation (N=13,705) and identified 16 significantly associated loci, indicating that IgG galactosylation is regulated by a complex network of genes that extends beyond the galactosyltransferase enzyme that adds galactose to IgG glycans. Gene prioritization identified 37 candidate genes. Using a recently developed CRISPR/dCas9 system we manipulated gene expression of candidate genes in the in vitro IgG expression system. Upregulation of three genes, EEF1A1, MANBA and TNFRSF13B, changed the IgG glycome composition, which confirmed that these three genes are involved in IgG galactosylation in this in vitro expression system.

Plasma metabolomic profiles associated with mortality and longevity in a prospective analysis of 13,512 individuals.

Experimental studies reported biochemical actions underpinning aging processes and mortality, but the relevant metabolic alterations in humans are not well understood. Here we examine the associations of 243 plasma metabolites with mortality and longevity (attaining age 85 years) in 11,634 US (median follow-up of 22.6 years, with 4288 deaths) and 1878 Spanish participants (median follow-up of 14.5 years, with 525 deaths). We find that, higher levels of N2,N2-dimethylguanosine, pseudouridine, N4-acetylcytidine, 4-acetamidobutanoic acid, N1-acetylspermidine, and lipids with fewer double bonds are associated with increased risk of all-cause mortality and reduced odds of longevity; whereas L-serine and lipids with more double bonds are associated with lower mortality risk and a higher likelihood of longevity. We further develop a multi-metabolite profile score that is associated with higher mortality risk. Our findings suggest that differences in levels of nucleosides, amino acids, and several lipid subclasses can predict mortality. The underlying mechanisms remain to be determined.

Broadcasters, receivers, functional groups of metabolites and the link to heart failure progression using polygenic factors.

In a prospective study with records of heart failure (HF) incidence, we present metabolite profiling data from individuals without HF at baseline. We uncovered the interconnectivity of metabolites using data-driven and causal networks augmented with polygenic factors. Exploring the networks, we identified metabolite broadcasters, receivers, mediators, and subnetworks corresponding to functional classes of metabolites, and provided insights into the link between metabolomic architecture and regulation in health. We incorporated the network structure into the identification of metabolites associated with HF to control the effect of confounding metabolites. We identified metabolites associated with higher or lower risk of HF incidence, the associations that were not confounded by the other metabolites, such as glycine, ureidopropionic and glycocholic acids, and LPC 18:2. We revealed the underlying relationships of the findings. For example, asparagine directly influenced glycine, and both were inversely associated with HF. These two metabolites were influenced by polygenic factors and only essential amino acids which are not synthesized in the human body and come directly from the diet. Metabolites may play a critical role in linking genetic background and lifestyle factors to HF progression. Revealing the underlying connectivity of metabolites associated with HF strengthens the findings and facilitates a mechanistic understanding of HF progression.

Association of the human gut microbiota with vascular stiffness.

Gut microbiota metabolites have been mechanistically linked to inflammatory pathway activation and atherosclerosis, which are major causes of vascular stiffness (VS). Aiming to investigate if the gut microbiome might be involved in VS development, we performed a cross-sectional study (n = 3,087), nested within the population-based European Prospective Investigations into Cancer and Nutrition (EPIC) Potsdam. We investigated the correlation of the gut microbiota (alpha diversity and taxa abundance) with 3 vascular stiffness measures: carotid-femoral (PWV), aortic augmentation index (AIX) and ankle-brachial index (ABI). Shannon index was not significantly associated with VS but the number of observed Amplicon Sequence Variants (ASV) was positively associated with PWV and AIX. We found a total of 19 ASVs significantly associated with at least one VS measure in multivariable-adjusted models. One ASV (classified as Sutterella wadsworthensis) was associated with 2 VS measures, AIX (- 0.11 ± 0.04) and PWV (-0.14 ± 0.03). Other examples of ASVs associated with VS were Collinsella aerofaciens, previously reported to be affected by diet and Bacteroides uniformis, commercially available as probiotics. In conclusion, our study suggests a potential role of individual components of the gut microbiota in the aetiology of VS.

Plasma lipidome and risk of atrial fibrillation: results from the PREDIMED trial

The potential role of the lipidome in atrial fibrillation (AF) development is still widely unknown. We aimed to assess the association between lipidome profiles of the Prevención con Dieta Mediterránea (PREDIMED) trial participants and incidence of AF. We conducted a nested case–control study (512 incident centrally adjudicated AF cases and 735 controls matched by age, sex, and center). Baseline plasma lipids were profiled using a Nexera X2 U-HPLC system coupled to an Exactive Plus orbitrap mass spectrometer. We estimated the association between 216 individual lipids and AF using multivariable conditional logistic regression and adjusted the p values for multiple testing. We also examined the joint association of lipid clusters with AF incidence. Hitherto, we estimated the lipidomics network, used machine learning to select important network-clusters and AF-predictive lipid patterns, and summarized the joint association of these lipid patterns weighted scores. Finally, we addressed the possible interaction by the randomized dietary intervention.Forty-one individual lipids were associated with AF at the nominal level (p < 0.05), but no longer after adjustment for multiple-testing. However, the network-based score identified with a robust data-driven lipid network showed a multivariable-adjusted ORper+1SD of 1.32 (95% confidence interval: 1.16–1.51; p < 0.001). The score included PC plasmalogens and PE plasmalogens, palmitoyl-EA, cholesterol, CE 16:0, PC 36:4;O, and TG 53:3. No interaction with the dietary intervention was found. A multilipid score, primarily made up of plasmalogens, was associated with an increased risk of AF. Future studies are needed to get further insights into the lipidome role on AF. (AU)

Replacement of dietary saturated with unsaturated fatty acids is associated with beneficial effects on lipidome metabolites: a secondary analysis of a randomized trial.

BACKGROUND: The effects of replacing dietary saturated fatty acids (SFAs) with monounsaturated fatty acids (MUFAs) and/or polyunsaturated fatty acids (PUFAs) on the plasma lipidome in relation to the cardiometabolic disease (CMD) risk is poorly understood. OBJECTIVES: We aimed to assess the impact of substituting dietary SFAs with unsaturated fatty acids (UFAs) on the plasma lipidome and examine the relationship between lipid metabolites modulated by diet and CMD risk. METHODS: Plasma fatty acid (FA) concentrations among 16 lipid classes (within-class FAs) were measured in a subgroup from the Dietary Intervention and VAScular function (DIVAS) parallel randomized controlled trial (n = 113/195), which consisted of three 16-wk diets enriched in SFAs (target SFA:MUFA:n-6PUFA ratio = 17:11:4% total energy [TE]), MUFAs (9:19:4% TE), or a MUFA/PUFA mixture (9:13:10% TE). Similar lipidomics analyses were conducted in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study (specific case/cohorts: n = 775/1886 for type 2 diabetes [T2D], n = 551/1671 for cardiovascular disease [CVD]). Multiple linear regression and multivariable Cox models identified within-class FAs sensitive to replacement of dietary SFA with UFA in DIVAS and their association with CMD risk in EPIC-Potsdam. Elastic-net regression models identified within-class FAs associated with changes in CMD risk markers post-DIVAS interventions. RESULTS: DIVAS high-UFA interventions reduced plasma within-class FAs associated with a higher CVD risk in EPIC-Potsdam, especially SFA-containing glycerolipids and sphingolipids (e.g., diacylglycerol (20:0) z-score = -1.08; SE = 0.17; P value < 10-8), whereas they increased those inversely associated with CVD risk. The results on T2D were less clear. Specific sphingolipids and phospholipids were associated with changes in markers of endothelial function and ambulatory blood pressure, whereas higher low-density lipoprotein cholesterol concentrations were characterized by higher plasma glycerolipids containing lauric and stearic acids. CONCLUSIONS: These results suggest a mediating role of plasma lipid metabolites in the association between dietary fat and CMD risk. Future research combining interventional and observational findings will further our understanding of the role of dietary fat in CMD etiology. This trial was registered in ClinicalTrials.gov as NCT01478958.

Plasma lipidome and risk of atrial fibrillation: results from the PREDIMED trial.

The potential role of the lipidome in atrial fibrillation (AF) development is still widely unknown. We aimed to assess the association between lipidome profiles of the Prevención con Dieta Mediterránea (PREDIMED) trial participants and incidence of AF. We conducted a nested case-control study (512 incident centrally adjudicated AF cases and 735 controls matched by age, sex, and center). Baseline plasma lipids were profiled using a Nexera X2 U-HPLC system coupled to an Exactive Plus orbitrap mass spectrometer. We estimated the association between 216 individual lipids and AF using multivariable conditional logistic regression and adjusted the p values for multiple testing. We also examined the joint association of lipid clusters with AF incidence. Hitherto, we estimated the lipidomics network, used machine learning to select important network-clusters and AF-predictive lipid patterns, and summarized the joint association of these lipid patterns weighted scores. Finally, we addressed the possible interaction by the randomized dietary intervention.Forty-one individual lipids were associated with AF at the nominal level (p < 0.05), but no longer after adjustment for multiple-testing. However, the network-based score identified with a robust data-driven lipid network showed a multivariable-adjusted ORper+1SD of 1.32 (95% confidence interval: 1.16-1.51; p < 0.001). The score included PC plasmalogens and PE plasmalogens, palmitoyl-EA, cholesterol, CE 16:0, PC 36:4;O, and TG 53:3. No interaction with the dietary intervention was found. A multilipid score, primarily made up of plasmalogens, was associated with an increased risk of AF. Future studies are needed to get further insights into the lipidome role on AF.Current Controlled Trials number, ISRCTN35739639.

Dietary intake of total, heme and non-heme iron and the risk of colorectal cancer in a European prospective cohort study.

BACKGROUND: Iron is an essential micronutrient with differing intake patterns and metabolism between men and women. Epidemiologic evidence on the association of dietary iron and its heme and non-heme components with colorectal cancer (CRC) development is inconclusive. METHODS: We examined baseline dietary questionnaire-assessed intakes of total, heme, and non-heme iron and CRC risk in the EPIC cohort. Sex-specific multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were computed using Cox regression. We modelled substitution of a 1 mg/day of heme iron intake with non-heme iron using the leave one-out method. RESULTS: Of 450,105 participants (318,680 women) followed for 14.2 ± 4.0 years, 6162 (3511 women) developed CRC. In men, total iron intake was not associated with CRC risk (highest vs. lowest quintile, HRQ5vs.Q1:0.88; 95%CI:0.73, 1.06). An inverse association was observed for non-heme iron (HRQ5vs.Q1:0.80, 95%CI:0.67, 0.96) whereas heme iron showed a non-significant association (HRQ5vs.Q1:1.10; 95%CI:0.96, 1.27). In women, CRC risk was not associated with intakes of total (HRQ5vs.Q1:1.11, 95%CI:0.94, 1.31), heme (HRQ5vs.Q1:0.95; 95%CI:0.84, 1.07) or non-heme iron (HRQ5vs.Q1:1.03, 95%CI:0.88, 1.20). Substitution of heme with non-heme iron demonstrated lower CRC risk in men (HR:0.94; 95%CI: 0.89, 0.99). CONCLUSIONS: Our findings suggest potential sex-specific CRC risk associations for higher iron consumption that may differ by dietary sources.

Low-Carbohydrate Diet Scores and Mortality Among Adults With Incident Type 2 Diabetes.

OBJECTIVE: The current study aims to prospectively examine the association between postdiagnosis low-carbohydrate diet (LCD) patterns and mortality among individuals with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: Among participants with incident diabetes identified in the Nurses' Health Study and Health Professionals Follow-up Study, an overall total LCD score (TLCDS) was calculated based on the percentage of energy as total carbohydrates. In addition, vegetable (VLCDS), animal (ALCDS), healthy (HLCDS), and unhealthy (ULCDS) LCDS were further derived that emphasized different sources and quality of macronutrients. Multivariable-adjusted Cox models were used to assess the association between the LCDS and mortality. RESULTS: Among 10,101 incident T2D cases contributing 139,407 person-years during follow-up, we documented 4,595 deaths of which 1,389 cases were attributed to cardiovascular disease (CVD) and 881 to cancer. The pooled multivariable-adjusted hazard ratios (HRs, 95% CIs) of total mortality per 10-point increment of postdiagnosis LCDS were 0.87 (0.82, 0.92) for TLCDS, 0.76 (0.71, 0.82) for VLCDS, and 0.78 (0.73, 0.84) for HLCDS. Both VLCDS and HLCDS were also associated with significantly lower CVD and cancer mortality. Each 10-point increase of TLCDS, VLCDS, and HLCDS from prediagnosis to postdiagnosis period was associated with 12% (7%, 17%), 25% (19%, 30%), and 25% (19%, 30%) lower total mortality, respectively. No significant associations were observed for ALCDS and ULCDS. CONCLUSIONS: Among people with T2D, greater adherence to LCD patterns that emphasize high-quality sources of macronutrients was significantly associated with lower total, cardiovascular, and cancer mortality.

Plasma Lipidomic n-6 Polyunsaturated Fatty Acids and Type 2 Diabetes Risk in the EPIC-Potsdam Prospective Cohort Study.

OBJECTIVE: Evidence on plasma n-6 polyunsaturated fatty acids (PUFAs) and type 2 diabetes risk is inconsistent. We examined the associations of lipid class-specific PUFA concentrations with type 2 diabetes risk. RESEARCH DESIGN AND METHODS: In the prospective European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (nested case-cohort study: subcohort 1,084 participants, 536 participants with type 2 diabetes, median follow-up 6.5 years), we measured plasma 18:2, 20:3, and 20:4 concentrations in 12 lipid (sub)classes, likely reflecting the plasma concentrations of linoleic acid (18:2n-6), dihomo-γ-linolenic acid (20:3n-6), and arachidonic acid (20:4n-6). The Δ-5 desaturase (D5D) activity was estimated as the 20:4/20:3 ratio. Associations with diabetes were estimated with Cox proportional hazards models. RESULTS: Higher concentrations of 18:2 were inversely associated with type 2 diabetes risk, particularly in lysophosphatidylcholines (hazard ratio [HR] per 1 SD 0.53; 95% CI 0.23-1.26) and monoacylglycerols (HR 0.59; 0.38-0.92). Higher concentrations of 20:3 in phospholipid classes phosphatidylcholines (HR 1.63; 1.23-2.14), phosphatidylethanolamines (HR 1.87; 1.32-2.65), and phosphatidylinositol (HR 1.40; 1.05-1.87); free fatty acids (HR 1.44; 1.10-1.90); and cholesteryl esters (HR 1.47; 1.09-1.98) were linked to higher type 2 diabetes incidence, and these associations remained statistically significant after correction for multiple testing. Higher 20:4 concentrations were not associated with risk. The estimated D5D activity in phospholipids and cholesteryl esters was associated with lower type 2 diabetes risk. Single nucleotide polymorphisms in the D5D-encoding FADS genes explained relatively high proportions of variation of estimated D5D activity in those lipid classes. CONCLUSIONS: Plasma n-6 PUFAs were associated differently with type 2 diabetes, depending on fatty acid and the lipid class.

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.

Immunoglobulin G N-Glycosylation Signatures in Incident Type 2 Diabetes and Cardiovascular Disease.

OBJECTIVE: N-glycosylation is a functional posttranslational modification of immunoglobulins (Igs). We hypothesized that specific IgG N-glycans are associated with incident type 2 diabetes and cardiovascular disease (CVD). RESEARCH DESIGN AND METHODS: We performed case-cohort studies within the population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (2,127 in the type 2 diabetes subcohort [741 incident cases]; 2,175 in the CVD subcohort [417 myocardial infarction and stroke cases]). Relative abundances of 24 IgG N-glycan peaks (IgG-GPs) were measured by ultraperformance liquid chromatography, and eight glycosylation traits were derived based on structural similarity. End point-associated IgG-GPs were preselected with fractional polynomials, and prospective associations were estimated in confounder-adjusted Cox models. Diabetes risk associations were validated in three independent studies. RESULTS: After adjustment for confounders and multiple testing correction, IgG-GP7, IgG-GP8, IgG-GP9, IgG-GP11, and IgG-GP19 were associated with type 2 diabetes risk. A score based on these IgG-GPs was associated with a higher diabetes risk in EPIC-Potsdam and independent validation studies (843 total cases, 3,149 total non-cases, pooled estimate per SD increase 1.50 [95% CI 1.37-1.64]). Associations of IgG-GPs with CVD risk differed between men and women. In women, IgG-GP9 was inversely associated with CVD risk (hazard ratio [HR] per SD 0.80 [95% CI 0.65-0.98]). In men, a weighted score based on IgG-GP19 and IgG-GP23 was associated with higher CVD risk (HR per SD 1.47 [95% CI 1.20-1.80]). In addition, several derived traits were associated with cardiometabolic disease incidence. CONCLUSIONS: Selected IgG N-glycans are associated with cardiometabolic risk beyond classic risk factors, including clinical biomarkers.

Retinol and Retinol Binding Protein 4 Levels and Cardiometabolic Disease Risk.

BACKGROUND: Despite mechanistic studies linking retinol and RBP4 (retinol binding protein 4) to the pathogenesis of cardiovascular diseases (CVD) and type 2 diabetes (T2D), epidemiological evidence is still conflicting. We investigated whether conflicting results of previous studies may be explained by differences in the association of retinol and RBP4 with cardiometabolic risk across subgroups with distinct sex, hypertension state, liver, or kidney function. METHODS: We used case-cohorts nested in the EPIC (European Prospective Investigation Into Cancer and Nutrition)-Potsdam cohort (N=27 548) comprising a random sample of participants (n=2500) and all physician-verified cases of incident CVD (n=508, median follow-up time 8.2 years) and T2D (n=820, median follow-up time 6.3 years). We estimated nonlinear and linear multivariable-adjusted associations between the biomarkers and cardiometabolic diseases by restricted cubic splines and Cox regression, respectively, testing potential interactions with hypertension, liver, and kidney function. Additionally, we performed 2-sample Mendelian Randomization analyses in publicly available data. RESULTS: The association of retinol with cardiometabolic risk was modified by hypertension state (P interaction CVD<0.001; P interaction T2D<0.001). Retinol was associated with lower cardiometabolic risk in participants with treated hypertension (hazard ratioper SD [95% CI]: CVD, 0.71 [0.56-0.90]; T2D, 0.81 [0.70-0.94]) but with higher cardiometabolic risk in normotensive participants (CVD, 1.32 [1.06-1.64]; T2D, 1.15 [0.98-1.36]). Our analyses also indicated a significant interaction between RBP4 and hypertension on CVD risk (P interaction=0.04). Regarding T2D risk, we observed a u-shaped association with RBP4 in women (P nonlinearity=0.01, P effect=0.02) and no statistically significant association in men. The biomarkers' interactions with liver or kidney function were not statistically significant. Hypertension state-specific associations for retinol concentrations with cardiovascular mortality risk were replicated in National Health and Nutrition Examination Survey III. CONCLUSIONS: Our findings suggest a hypertension-dependent relationship between plasma retinol and cardiometabolic risk and complex interactions of RBP4 with sex and hypertension on cardiometabolic risk.

Arginine catabolism metabolites and atrial fibrillation or heart failure risk: 2 case-control studies within the Prevención con Dieta Mediterránea (PREDIMED) trial.

BACKGROUND: Arginine-derived metabolites are involved in oxidative and inflammatory processes related to endothelial functions and cardiovascular risks. OBJECTIVES: We prospectively examined the associations of arginine catabolism metabolites with the risks of atrial fibrillation (AF) or heart failure (HF), and evaluated the potential modifications of these associations through Mediterranean diet (MedDiet) interventions in a large, primary-prevention trial. METHODS: Two nested, matched, case-control studies were designed within the Prevención con Dieta Mediterránea (PREDIMED) trial. We selected 509 incident cases and 547 matched controls for the AF case-control study and 326 cases and 402 matched controls for the HF case-control study using incidence density sampling. Fasting blood samples were collected at baseline and arginine catabolism metabolites were measured using LC-tandem MS. Multivariable conditional logistic regression models were applied to test the associations between the metabolites and incident AF or HF. Interactions between metabolites and intervention groups (MedDiet groups compared with control group) were analyzed with the likelihood ratio test. RESULTS: Inverse association with incident AF was observed for arginine (OR per 1 SD, 0.83; 95% CI: 0.73-0.94), whereas a positive association was found for N1-acetylspermidine (OR for Q4 compared with Q1 1.58; 95% CI: 1.13-2.25). For HF, inverse associations were found for arginine (OR per 1 SD, 0.82; 95% CI: 0.69-0.97) and homoarginine (OR per 1 SD, 0.81; 95% CI: 0.68-0.96), and positive associations were found for the asymmetric dimethylarginine (ADMA) and symmetric dimethlyarginine (SDMA) ratio (OR per 1 SD, 1.19; 95% CI: 1.02-1.41), N1-acetylspermidine (OR per 1 SD, 1.34; 95% CI: 1.12-1.60), and diacetylspermine (OR per 1 SD, 1.20; 95% CI: 1.02-1.41). In the stratified analysis according to the dietary intervention, the lower HF risk associated with arginine was restricted to participants in the MedDiet groups (P-interaction = 0.044). CONCLUSIONS: Our results suggest that arginine catabolism metabolites could be involved in AF and HF. Interventions with the MedDiet may contribute to strengthen the inverse association between arginine and the risk of HF. This trial was registered at controlled-trials.com as ISRCTN35739639.

Intrapersonal Stability of Plasma Metabolomic Profiles over 10 Years among Women.

In epidemiological studies, samples are often collected long before disease onset or outcome assessment. Understanding the long-term stability of biomarkers measured in these samples is crucial. We estimated within-person stability over 10 years of metabolites and metabolite features (n = 5938) in the Nurses' Health Study (NHS): the primary dataset included 1880 women with 1184 repeated samples donated 10 years apart while the secondary dataset included 1456 women with 488 repeated samples donated 10 years apart. We quantified plasma metabolomics using two liquid chromatography mass spectrometry platforms (lipids and polar metabolites) at the Broad Institute (Cambridge, MA, USA). Intra-class correlations (ICC) were used to estimate long-term (10 years) within-person stability of metabolites and were calculated as the proportion of the total variability (within-person + between-person) attributable to between-person variability. Within-person variability was estimated among participants who donated two blood samples approximately 10 years apart while between-person variability was estimated among all participants. In the primary dataset, the median ICC was 0.43 (1st quartile (Q1): 0.36; 3rd quartile (Q3): 0.50) among known metabolites and 0.41 (Q1: 0.34; Q3: 0.48) among unknown metabolite features. The three most stable metabolites were N6,N6-dimethyllysine (ICC = 0.82), dimethylguanidino valerate (ICC = 0.72), and N-acetylornithine (ICC = 0.72). The three least stable metabolites were palmitoylethanolamide (ICC = 0.05), ectoine (ICC = 0.09), and trimethylamine-N-oxide (ICC = 0.16). Results in the secondary dataset were similar (Spearman correlation = 0.87) to corresponding results in the primary dataset. Within-person stability over 10 years is reasonable for lipid, lipid-related, and polar metabolites, and varies by metabolite class. Additional studies are required to estimate within-person stability over 10 years of other metabolites groups.