The Mediterranean diet, plasma metabolome, and cardiovascular disease risk

Assessing the causal relationship between metabolic biomarkers and coronary artery disease by Mendelian randomization studies

The development of coronary artery disease (CAD) is significantly affected by impaired endocrine and metabolic status. Under this circumstance, improved prevention and treatment of CAD may result from knowing the connection between metabolites and CAD. This study aims to delve into the causal relationship between human metabolic biomarkers and CAD by using two-sample Mendelian randomization (MR). Utilizing two-sample bidirectional MR analysis, we assessed the correlation between 1400 blood metabolites and CAD, and the metabolites data from the CLSA, encompassing 8299 participants. Metabolite analysis identified 1091 plasma metabolites and 309 ratios as instrumental variables. To evaluate the causal link between metabolites and CAD, we analyzed three datasets: ebi-a-GCST005195 (547,261 European & East Asian samples), bbj-a-159 (29,319 East Asian CAD cases & 183,134 East Asian controls), and ebi-a-GCST005194 (296,525 European & East Asian samples). To estimate causal links, we utilized the IVW method. To conduct sensitivity analysis, we used MR-Egger, Weighted Median, and MR-PRESSO. Additionally, we employed MR-Egger interception and Cochran's Q statistic to assess potential heterogeneity and pleiotropy. What's more, replication and reverse analyses were performed to verify the reliability of the results and the causal order between metabolites and disease. Furthermore, we conducted a pathway analysis to identify potential metabolic pathways. 59 blood metabolites and 27 metabolite ratios nominally associated with CAD (P < 0.05) were identified by IVW analysis method. A total of four known blood metabolites, namely beta-hydroxyisovaleroylcarnitine (OR 1.06, 95% CI 1.027-1.094, FDR 0.07), 1-palmitoyl-2-arachidonoyl (OR 1.07, 95% CI 1.029-1.110, FDR 0.09), 1-stearoyl-2- docosahexaenoyl (OR 1.07, 95% CI 1.034-1.113, FDR 0.07) and Linoleoyl-arachidonoyl-glycerol, (OR 1.07, 95% CI 1.036-1.105, FDR 0.05), and two metabolite ratios, namely spermidine to N-acetylputrescine ratio (OR 0.94, 95% CI 0.903-0.972, FDR 0.09) and benzoate to linoleoyl-arachidonoyl-glycerol ratio (OR 0.87, 95% CI 0.879-0.962, FDR 0.07), were confirmed as having a significant causal relationship with CAD, after correcting for the FDR method (p < 0. 1). A causal relationship was found to be established between beta -hydroxyisovalerylcarnitine and CAD with the validation in other two datasets. Moreover, multiple metabolic pathways were discovered to be associated with CAD. Our study supports the hypothesis that metabolites have an impact on CAD by demonstrating a causal relationship between human metabolites and CAD. This study is important for new strategies for the prevention and treatment of CAD.

Association of life's essential 8 with mortality among the individuals with cardiovascular disease

This study explores the association between LE8 scores and mortality risks among individuals diagnosed with cardiovascular disease (CVD). Utilizing data from the NHANES conducted between 2005 and 2018, survey-weighted multivariable Cox proportional hazards regression models were utilized. Life's Essential 8 (LE8) scores dose-response associations were assessed using restricted cubic spline regression. Sub-analyses were performed for different categories of CVD. The study consisted of 2164 participants diagnosed with CVD, ranging in age from 20 to 80 years (weighted mean [SE] age, 61.47 [0.34] years; The average total LE8 was 64.97 [0.54]. 499 participants experienced mortality, with 350 deaths attributed to CVD. After accounting for potential covariates, LE8 score was found to be associated with a decreased both all-cause mortality (OR 0.34, CI 0.22-0.51) and CVD mortality (OR 0.40, CI 0.23-0.68). A survey-weighted multivariable Cox model with restricted cubic splines identified the lowest all-cause mortality (P < 0.001) and CVD mortality (P < 0.001) risk when LE8 reach at 63.75 (P < 0.001). The results highlight the association between LE8 scores and reduced mortality in CVD patient population. The implementation of comprehensive initiatives that prioritize healthy dietary patterns, will play a crucial role in alleviating the impact of cardiovascular disease and improving cardiovascular health outcomes.

Dietary intake of potassium, vitamin E, and vitamin C emerges as the most significant predictors of cardiovascular disease risk in adults

Prediction models were developed to assess the risk of cardiovascular disease (CVD) based on micronutrient intake, utilizing data from 90,167 UK Biobank participants. Four machine learning models were employed to predict CVD risk, with performance evaluation metrics including area under the receiver operating characteristic curve (AUC), accuracy, recall, specificity, and F1-score. The eXtreme Gradient Boosting (XGBoost) model was utilized to rank the importance of 11 micronutrients in cardiovascular health. Results indicated that vitamin E, calcium, vitamin C, and potassium intake were associated with a reduced risk of CVD. The XGBoost model demonstrated the highest performance with an AUC of 0.952, highlighting potassium, vitamin E, and vitamin C as key predictors of CVD risk. Subgroup analysis revealed a stronger correlation between calcium intake and CVD risk in older adults and those with higher BMI, while vitamin B6 intake showed a link to CVD risk in women. Overall, the XGBoost model emphasized the significance of potassium, vitamin E, and vitamin C intake as primary predictors of CVD risk in adults, with age, sex, and BMI potentially influencing the importance of micronutrient intake in predicting CVD risk.

Persistent PTSD symptoms are associated with plasma metabolic alterations relevant to long-term health: A metabolome-wide investigation in women

Background

Posttraumatic stress disorder (PTSD) is characterized by severe distress and associated with cardiometabolic diseases. Studies in military and clinical populations suggest dysregulated metabolomic processes may be a key mechanism. Prior work identified and validated a metabolite-based distress score (MDS) linked with depression and anxiety and subsequent cardiometabolic diseases. Here, we assessed whether PTSD shares metabolic alterations with depression and anxiety and also if additional metabolites are related to PTSD.

Methods

We leveraged plasma metabolomics data from three subsamples nested within the Nurses' Health Study II, including 2835 women with 2950 blood samples collected across three timepoints (1996-2014) and 339 known metabolites consistently assayed by mass spectrometry-based techniques. Trauma and PTSD exposures were assessed in 2008 and characterized as follows: lifetime trauma without PTSD, lifetime PTSD in remission, and persistent PTSD symptoms. Associations between the exposures and the MDS or individual metabolites were estimated within each subsample adjusting for potential confounders and combined in random-effects meta-analyses.

Results

Persistent PTSD symptoms were associated with higher levels of the previously developed MDS for depression and anxiety. Out of 339 metabolites, we identified nine metabolites (primarily elevated glycerophospholipids) associated with persistent symptoms (false discovery rate<0.05). No metabolite associations were found with the other PTSD-related exposures.

Conclusions

As the first large-scale, population-based metabolomics analysis of PTSD, our study highlighted shared and distinct metabolic differences linked to PTSD versus depression or anxiety. We identified novel metabolite markers associated with PTSD symptom persistence, suggesting further connections with metabolic dysregulation that may have downstream consequences for health.

Dietary pattern modifies the risk of MASLD through metabolomic signature

Background & Aims

The EAT-Lancet Commission in 2019 advocated a plant-centric diet for health and environmental benefits, but its relation to metabolic dysfunction-associated steatotic liver disease (MASLD) is unclear. We aimed to discover the metabolite profile linked to the EAT-Lancet diet and its association with MASLD risk, considering genetic predisposition.

Methods

We analyzed data from 105,752 UK Biobank participants with detailed dietary and metabolomic information. We constructed an EAT-Lancet diet index and derived a corresponding metabolomic signature through elastic net regression. A weighted polygenic risk score for MASLD was computed from associated risk variants. The Cox proportional hazards model was employed to estimate hazard ratios (HRs) and 95% CIs for the risk of MASLD (defined as hospital admission or death).

Results

During a median follow-up period of 11.6 years, 1,138 cases of MASLD were documented. Participants in the highest group for the EAT-Lancet diet index had a multivariable HR of 0.79 (95% CI 0.66-0.95) for MASLD compared to the lowest group. The diet's impact was unaffected by genetic predisposition to MASLD (p = 0.42). Moreover, a robust correlation was found between the metabolomic signature and the EAT-Lancet diet index (Pearson r = 0.29; p <0.0001). Participants in the highest group for the metabolomic signature had a multivariable HR of 0.46 (95% CI 0.37-0.58) for MASLD, in comparison to those in the lowest group.

Conclusions

Higher intake of the EAT-Lancet diet and its associated metabolite signature are both linked to a reduced risk of MASLD, independently of traditional risk factors.

Impact and implications

Our analysis leveraging the UK Biobank study showed higher adherence to the EAT-Lancet diet was associated with a reduced risk of metabolic dysfunction-associated steatotic liver disease (MASLD). We identified a unique metabolite signature comprising 81 metabolites associated with the EAT-Lancet diet, potentially underlying the diet's protective mechanism against MASLD. These findings suggest the EAT-Lancet diet may offer substantial protective benefits against MASLD.

The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) Diet and Metabolites in Chronic Kidney Disease

The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) is a hybrid of the Mediterranean and DASH (Dietary Approaches to Stop Hypertension) diets, and its association with renal outcomes remains unclear. In the REasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort, diet data were collected at baseline using food frequency questionnaires. Modified Poisson regression was used to examine the association of MIND diet with incident chronic kidney disease (CKD). In the REGARDS stroke case-cohort, 357 metabolites were measured in baseline plasma. Weighted linear regression was used to test associations between MIND diet and metabolites. Weighted logistic regression was used to test associations between MIND-associated metabolites and incident CKD. Mediation analyses were conducted to determine whether metabolites mediated the relationship between MIND diet and CKD. A higher MIND diet score was associated with a decreased risk of incident CKD (risk ratio 0.90, 95% CI (0.86-0.94); p = 2.03 × 10-7). Fifty-seven metabolites were associated with MIND diet (p < 3 × 10-4). Guanosine was found to mediate the relationship between MIND diet and incident CKD (odds ratio for indirect effects 0.93, 95% CI (0.88-0.97); p < 0.05). These findings suggest a role of the MIND diet in renal outcomes.

Genetically Predicted Vascular Proteins and Risk of Intracranial Aneurysms: A Mendelian Randomization Study

The relationship between vascular proteins (VPs) and intracranial aneurysms (IAs) has not been fully elucidated. We used Mendelian randomization (MR) analysis to explore the effect of VPs on IAs. Dataset of aneurysmal subarachnoid hemorrhage (aSAH) [5140 cases and 71,934 controls] and unruptured intracranial aneurysm (uIA) [2070 cases and 71,934 controls] were obtained from individuals of European ancestry. Univariate MR was used to explore the associations between 90 VPs and IAs. Then, we performed multivariate MR (MVMR) to further investigate the identified VP-to-IA estimates. Two-sample MR showed that TNFSF14 was inversely associated with aSAH (odds ratio [OR] = 0.831, 95% CI: 0.713-0.969, p = 0.018). IL-16 (OR = 1.218, 95% CI: 1.032-1.438, p = 0.020) and AgRP (OR = 1.394, 95% CI: 1.048-1.855, p = 0.023) were positively associated with aSAH. HBEGF (OR = 0.642, 95% CI: 0.461-0.894, p = 0.009), MCP-1 (OR = 1.537, 95% CI: 1.007-2.344, p = 0.046), and CX3CL1 (OR = 0.762, 95% CI: 0.581-0.999, 0.049 < p < 0.050) were associated with uIA risk. The MVMR showed that the TNFSF14-to-aSAH estimate remained statistically significant after adjustment for past tobacco smoking, alcohol consumption, systolic blood pressure and body mass index. Our study indicated that low serum TNFSF14 levels might be a potential risk factor for IA rupture. Five VPs (HBEGF, MCP-1, IL-6, CX3CL1, and AgRP) are associated with the risk of IAs (both uIA and aSAH).

Combined mediterranean diet-based sustainable healthy diet and multicomponent training intervention impact on plasma biomarkers and metabolome in older adults

BACKGROUND AND AIMS

Healthy dietary patterns and exercise practices have been associated with improved metabolic and inflammatory profiles. However, studies regarding the combined effect of these interventions on plasma biomarkers and metabolome in older adults are sparser. The primary aim of this study was to investigate the impact of a combined Mediterranean Diet-based Sustainable Healthy Diet (SHD) and Multicomponent Training (MT) intervention on the plasma biomarkers and metabolome and how dietary intake and exercise could modulate these effects.

METHODS

SHD intervention included a weekly supply of Mediterranean Diet-based SHD food and four nutrition sessions involving a Mediterranean-Diet culinary workshop, and the exercise program included 50-min MT group sessions, held three times a week, lasting both 12 weeks. Plasma biomarkers were obtained through standard biochemical analysis. A proton (1H) nuclear magnetic resonance (NMR) spectroscopy-based metabolomics approach was used to study the metabolome in blood plasma. Repeated measures ANOVA were performed and adjusted for confounders.

RESULTS

SHD + MT intervention significantly decreased HDL-C and calcium. SHD + MT showed some changes in common with the SHD and MT group, namely a significant decrease in citrate levels (p = 0.009 for SHD + MT; p = 0.037 for SHDT) and an increase in pyruvate (p < 0.001 for MT and SHD + MT). The SHD + MT group also revealed specific changes in the levels of some amino acids (decrease in alanine, glutamine and lysine: p = 0.026; p < 0.001; p = 0.038, respectively). Increases in formate (p = 0.025) and unsaturated lipids (p = 0.011) are consistent with changes in energy and lipoprotein metabolism.

CONCLUSION

Our data show that a combined lifestyle intervention program, including a Mediterranean Diet-based SHD and MT, could modulate biomarker and metabolome and there seems to be a metabolic path associated to these interventions in older adults. Due to its wide-ranging relevance, it is pertinent to assess to what extent combined SHD and MT can contribute to better clinical profiles.

Blood metabolomic shift links diet and gut microbiota to multiple health outcomes among Hispanic/Latino immigrants in the U.S

Immigrants from less industrialized countries who are living in the U.S. often bear an elevated risk of multiple disease due to the adoption of a U.S. lifestyle. Blood metabolome holds valuable information on environmental exposure and the pathogenesis of chronic diseases, offering insights into the link between environmental factors and disease burden. Analyzing 634 serum metabolites from 7,114 Hispanics (1,141 U.S.-born, 5,973 foreign-born) in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we identified profound blood metabolic shift during acculturation. Machine learning highlighted the prominent role of non-genetic factors, especially food and gut microbiota, in these changes. Immigration-related metabolites correlated with plant-based foods and beneficial gut bacteria for foreign-born Hispanics, and with meat-based or processed food and unfavorable gut bacteria for U.S.-born Hispanics. Cardiometabolic traits, liver, and kidney function exhibited a link with immigration-related metabolic changes, which were also linked to increased risk of diabetes, severe obesity, chronic kidney disease, and asthma.

Graphical abstract

Highlights

A substantial proportion of identified blood metabolites differ between U.S.-born and foreign-born Hispanics/Latinos in the U.S.Food and gut microbiota are the major modifiable contributors to blood metabolomic difference between U.S.-born and foreign-born Hispanics/Latinos.U.S. nativity related metabolites collectively correlate with a spectrum of clinical traits and chronic diseases.

Unraveling the metabolomic architecture of autism in a large Danish population-based cohort

BACKGROUND

The prevalence of autism in Denmark has been increasing, reaching 1.65% among 10-year-old children, and similar trends are seen elsewhere. Although there are several factors associated with autism, including genetic, environmental, and prenatal factors, the molecular etiology of autism is largely unknown. Here, we use untargeted metabolomics to characterize the neonatal metabolome from dried blood spots collected shortly after birth.

METHODS

We analyze the metabolomic profiles of a subset of a large Danish population-based cohort (iPSYCH2015) consisting of over 1400 newborns, who later are diagnosed with autism and matching controls and in two Swedish population-based cohorts comprising over 7000 adult participants. Mass spectrometry analysis was performed by a timsTOF Pro operated in QTOF mode, using data-dependent acquisition. By applying an untargeted metabolomics approach, we could reproducibly measure over 800 metabolite features.

RESULTS

We detected underlying molecular perturbations across several metabolite classes that precede autism. In particular, the cyclic dipeptide cyclo-leucine-proline (FDR-adjusted p = 0.003) and the carnitine-related 5-aminovaleric acid betaine (5-AVAB) (FDR-adjusted p = 0.03), were associated with an increased probability for autism, independently of known prenatal and genetic risk factors. Analysis of genetic and dietary data in adults revealed that 5-AVAB was associated with increased habitual dietary intake of dairy (FDR-adjusted p < 0.05) and with variants near SLC22A4 and SLC22A5 (p < 5.0e - 8), coding for a transmembrane carnitine transporter protein involved in controlling intracellular carnitine levels.

CONCLUSIONS

Cyclo-leucine-proline and 5-AVAB are associated with future diagnosis of autism in Danish neonates, both representing novel early biomarkers for autism. 5-AVAB is potentially modifiable and may influence carnitine homeostasis.

Effects of short-term carbohydrate deprivation on glycolipid metabolism and hepatic lipid accumulation in mice

To investigate the effect of dietary carbohydrate levels on liver glycolipid metabolism, this study used C57BL/6J male mice receiving standard diet (CON), no-carbohydrate high-fat diet (NCD), and high-carbohydrate no-fat diet (HCD). One week after intervention, mice in the NCD group showed lower blood glucose, HbA1c and LDL-C as well as liver weight and liver index compared with the CON group. Further research found that the liver fat synthesis genes of mice in the NCD group were significantly down-regulated at the gene level, and histopathological sections showed that the livers of mice in the NCD group had less lipid accumulation. Furthermore, liver metabolomic analysis showed that primary bile acid levels and acylcarnitine levels in the liver of mice in the NCD group were significantly increased, and conversely, lysophosphatidylcholine and fatty acyl metabolites were significantly decreased. KEGG metabolic pathway analysis showed that metabolic pathways such as biosynthesis of unsaturated fatty acids and starch and sucrose metabolism were significantly inhibited in mice in the NCD group, while metabolic pathways such as primary bile acid biosynthesis, linoleic acid metabolism and glycerophospholipid metabolism were enhanced. Taken together, these results indicate that short-term carbohydrate deprivation improves blood glucose and lipid metabolism levels in mice; the molecular mechanism of action may involve inhibition of de novo lipogenesis and enhancement of bile acid metabolism.

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.

A Mediterranean Diet-Based Metabolomic Score and Cognitive Decline in Older Adults: A Case-Control Analysis Nested within the Three-City Cohort Study

SCOPE

Evidence on the Mediterranean diet (MD) and age-related cognitive decline (CD) is still inconclusive partly due to self-reported dietary assessment. The aim of the current study is to develop an MD- metabolomic score (MDMS) and investigate its association with CD in community-dwelling older adults.

METHODS AND RESULTS

This study includes participants from the Three-City Study from the Bordeaux (n = 418) and Dijon (n = 422) cohorts who are free of dementia at baseline. Repeated measures of cognition over 12 years are collected. An MDMS is designed based on serum biomarkers related to MD key food groups and using a targeted metabolomics platform. Associations with CD are investigated through conditional logistic regression (matched on age, sex, and education level) in both sample sets. The MDMS is found to be inversely associated with CD (odds ratio [OR] [95% confidence interval (CI)] = 0.90 [0.80-1.00]; p = 0.048) in the Bordeaux (discovery) cohort. Results are comparable in the Dijon (validation) cohort, with a trend toward significance (OR [95% CI] = 0.91 [0.83-1.01]; p = 0.084).

CONCLUSIONS

A greater adherence to the MD, here assessed by a serum MDMS, is associated with lower odds of CD in older adults.

Metabolomic signatures of inflammation and metabolic dysregulation in relation to colorectal cancer risk

BACKGROUND

Inflammation and metabolic dysregulation are associated with increased risk of colorectal cancer (CRC); the underlying mechanisms are not fully understood. We characterized metabolomic signatures of inflammation and metabolic dysregulation and evaluated the association of the signatures and individual metabolites with CRC risk.

METHODS

Among 684 incident CRC cases and 684 age-matched controls in the Nurses' Health Study (n = 818 women) and Health Professionals Follow-up Study (n = 550 men), we applied reduced rank and elastic net regression to 277 metabolites for markers of inflammation (C-reactive protein, interleukin 6, tumor necrosis factor receptor superfamily member 1B, and growth differentiation factor 15) or metabolic dysregulation (body mass index, waist circumference, C-peptide, and adiponectin) to derive metabolomic signatures. We evaluated the association of the signatures and individual metabolites with CRC using multivariable conditional logistic regression. All statistical tests were 2-sided.

RESULTS

We derived a signature of 100 metabolites that explained 24% of variation in markers of inflammation and a signature of 73 metabolites that explained 27% of variation in markers of metabolic dysregulation. Among men, both signatures were associated with CRC (odds ratio [OR] = 1.34, 95% confidence interval [CI] = 1.07 to 1.68 per 1-standard deviation increase, inflammation; OR = 1.25, 95% CI = 1.00 to 1.55 metabolic dysregulation); neither signature was associated with CRC in women. A total of 11 metabolites were individually associated with CRC and biomarkers of inflammation or metabolic dysregulation among either men or women.

CONCLUSION

We derived metabolomic signatures and identified individual metabolites associated with inflammation, metabolic dysregulation, and CRC, highlighting several metabolites as promising candidates involved in the inflammatory and metabolic dysregulation pathways for CRC incidence.

Metabolite Profiles of Plant-Based Diets and Cardiometabolic Risk in the Mediators of Atherosclerosis in South Asians Living in America Study

BACKGROUND

Healthy plant-based diets have been associated with lower risk of type 2 diabetes (T2D). Metabolomics can be leveraged to identify potential pathways through which diet influences disease risk.

OBJECTIVES

This study aimed to identify profiles of serum metabolites reflective of plant-based diets of varying quality and examine associations with cardiometabolic risk and T2D.

METHODS

We included data from 687 participants of the Mediators of Atherosclerosis in South Asians Living in America (MASALA) cohort. An overall plant-based diet index (PDI), healthy PDI (hPDI), and unhealthy PDI (uPDI) were estimated from food frequency questionnaires. Serum metabolites were assayed using ultraperformance liquid chromatography mass spectrometry. Elastic net regression was used to identify sets of metabolites predictive of each diet index, and metabolite profile scores were calculated as the weighted sum of the selected metabolites. Cross-sectional associations between metabolite profile scores and cardiometabolic measures and prospective associations with incident T2D were evaluated with multivariable-adjusted linear and logistic regressions.

RESULTS

Metabolite profiles for PDI, hPDI, and uPDI consisted of n = 51, 55, and 45 metabolites, respectively. Metabolites strongly positively correlated with diet indices included phosphatidylcholine (16:0/18:3) for PDI, phosphatidylethanolamine (20:1/20:4) and pantothenate for hPDI, and lysophosphatidylglycerol (18:2/0:0), proline, and lauric acid for uPDI. Higher metabolite profile scores for PDI and hPDI were associated with lower glycemia and lipids measures, whereas a higher uPDI metabolite score was associated with higher triglycerides and lower low density lipoprotein cholesterol and high density lipoprotein cholesterol. A higher metabolite score for hPDI was additionally associated with lower adiposity measures, higher liver fat attenuation, higher adiponectin, lower odds of overweight (odds ratio [OR]: 0.64; 95% confidence interval [CI]: 0.51, 0.81) and obesity (OR: 0.59; 95% CI: 0.48, 0.74), and lower odds of incident T2D (OR: 0.66; 95% CI: 0.45, 0.97).

CONCLUSIONS

Metabolite profiles of different plant-based diets were identified. Metabolite profiles of overall and healthy plant-based diets were associated with favorable cardiometabolic risk profiles.

Development of a (Poly)phenol Metabolic Signature for Assessing (Poly)phenol-Rich Dietary Patterns

The objective assessment of habitual (poly)phenol-rich diets in nutritional epidemiology studies remains challenging. This study developed and evaluated the metabolic signature of a (poly)phenol-rich dietary score (PPS) using a targeted metabolomics method comprising 105 representative (poly)phenol metabolites, analyzed in 24 h of urine samples collected from healthy volunteers. The metabolites that were significantly associated with PPS after adjusting for energy intake were selected to establish a metabolic signature using a combination of linear regression followed by ridge regression to estimate penalized weights for each metabolite. A metabolic signature comprising 51 metabolites was significantly associated with adherence to PPS in 24 h urine samples, as well as with (poly)phenol intake estimated from food frequency questionnaires and diaries. Internal and external data sets were used for validation, and plasma, spot urine, and 24 h urine samples were compared. The metabolic signature proposed here has the potential to accurately reflect adherence to (poly)phenol-rich diets, and may be used as an objective tool for the assessment of (poly)phenol intake.

Metabolic profiling of smoking, associations with type 2 diabetes and interaction with genetic susceptibility

BACKGROUND

Smokers are at increased risk of type 2 diabetes (T2D), but the underlying mechanisms are unclear. We investigated if the smoking-T2D association is mediated by alterations in the metabolome and assessed potential interaction with genetic susceptibility to diabetes or insulin resistance.

METHODS

In UK Biobank (n = 93,722), cross-sectional analyses identified 208 metabolites associated with smoking, of which 131 were confirmed in Mendelian Randomization analyses, including glycoprotein acetyls, fatty acids, and lipids. Elastic net regression was applied to create a smoking-related metabolic signature. We estimated hazard ratios (HR) of incident T2D in relation to baseline smoking/metabolic signature and calculated the proportion of the smoking-T2D association mediated by the signature. Additive interaction between the signature and genetic risk scores for T2D (GRS-T2D) and insulin resistance (GRS-IR) on incidence of T2D was assessed as relative excess risk due to interaction (RERI).

FINDINGS

The HR of T2D was 1·73 (95% confidence interval (CI) 1·54 - 1·94) for current versus never smoking, and 38·3% of the excess risk was mediated by the metabolic signature. The metabolic signature and its mediation role were replicated in TwinGene. The metabolic signature was associated with T2D (HR: 1·61, CI 1·46 - 1·77 for values above vs. below median), with evidence of interaction with GRS-T2D (RERI: 0·81, CI: 0·23 - 1·38) and GRS-IR (RERI 0·47, CI: 0·02 - 0·92).

INTERPRETATION

The increased risk of T2D in smokers may be mediated through effects on the metabolome, and the influence of such metabolic alterations on diabetes risk may be amplified in individuals with genetic susceptibility to T2D or insulin resistance.

Differences in metabolomic profiles between Black and White women in the U.S.: Analyses from two prospective cohorts

There is growing interest in incorporating metabolomics into public health practice. However, Black women are under-represented in many metabolomics studies. If metabolomic profiles differ between Black and White women, this under-representation may exacerbate existing Black-White health disparities. We therefore aimed to estimate metabolomic differences between Black and White women in the U.S. We leveraged data from two prospective cohorts: the Nurses' Health Study (NHS; n = 2077) and Women's Health Initiative (WHI; n = 2128). The WHI served as the replication cohort. Plasma metabolites (n = 334) were measured via liquid chromatography-tandem mass spectrometry. Observed metabolomic differences were estimated using linear regression and metabolite set enrichment analyses. Residual metabolomic differences in a hypothetical population in which the distributions of 14 risk factors were equalized across racial groups were estimated using inverse odds ratio weighting. In the NHS, Black-White differences were observed for most metabolites (75 metabolites with observed differences ≥ |0.50| standard deviations). Black women had lower average levels than White women for most metabolites (e.g., for N6, N6-dimethlylysine, mean Black-White difference = - 0.98 standard deviations; 95% CI: - 1.11, - 0.84). In metabolite set enrichment analyses, Black women had lower levels of triglycerides, phosphatidylcholines, lysophosphatidylethanolamines, phosphatidylethanolamines, and organoheterocyclic compounds, but higher levels of phosphatidylethanolamine plasmalogens, phosphatidylcholine plasmalogens, cholesteryl esters, and carnitines. In a hypothetical population in which distributions of 14 risk factors were equalized, Black-White metabolomic differences persisted. Most results replicated in the WHI (88% of 272 metabolites available for replication). Substantial differences in metabolomic profiles exist between Black and White women. Future studies should prioritize racial representation.

Discovery and validation of plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance and diabetes progression or regression among Puerto Rican adults

AIMS/HYPOTHESIS

Many studies have examined the relationship between plasma metabolites and type 2 diabetes progression, but few have explored saliva and multi-fluid metabolites.

METHODS

We used LC/MS to measure plasma (n=1051) and saliva (n=635) metabolites among Puerto Rican adults from the San Juan Overweight Adults Longitudinal Study. We used elastic net regression to identify plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting baseline HOMA-IR in a training set (n=509) and validated these scores in a testing set (n=340). We used multivariable Cox proportional hazards models to estimate HRs for the association of baseline metabolomic scores predicting insulin resistance with incident type 2 diabetes (n=54) and prediabetes (characterised by impaired glucose tolerance, impaired fasting glucose and/or high HbA1c) (n=130) at 3 years, along with regression from prediabetes to normoglycaemia (n=122), adjusting for traditional diabetes-related risk factors.

RESULTS

Plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance included highly weighted metabolites from fructose, tyrosine, lipid and amino acid metabolism. Each SD increase in the plasma (HR 1.99 [95% CI 1.18, 3.38]; p=0.01) and multi-fluid (1.80 [1.06, 3.07]; p=0.03) metabolomic scores was associated with higher risk of type 2 diabetes. The saliva metabolomic score was associated with incident prediabetes (1.48 [1.17, 1.86]; p=0.001). All three metabolomic scores were significantly associated with lower likelihood of regressing from prediabetes to normoglycaemia in models adjusting for adiposity (HRs 0.72 for plasma, 0.78 for saliva and 0.72 for multi-fluid), but associations were attenuated when adjusting for lipid and glycaemic measures.

CONCLUSIONS/INTERPRETATION

The plasma metabolomic score predicting insulin resistance was more strongly associated with incident type 2 diabetes than the saliva metabolomic score. Only the saliva metabolomic score was associated with incident prediabetes.

Research Progress on the Correlation Between Hypertension and Gut Microbiota

Among cardiovascular diseases, hypertension is the most important risk factor for morbidity and mortality worldwide, and its pathogenesis is complex, involving genetic, dietary and environmental factors. The characteristics of the gut microbiota can vary in response to increased blood pressure (BP) and influence the development and progression of hypertension. This paper describes five aspects of the relationship between hypertension and the gut microbiota, namely, the different types of gut microbiota, metabolites of the gut microbiota, sympathetic activation, gut-brain interactions, the effects of exercise and dietary patterns and the treatment of the gut microbiota through probiotics, faecal microbiota transplantation (FMT) and herbal remedies, providing new clues for the future prevention of hypertension. Diet, exercise and traditional Chinese medicine may contribute to long-term improvements in hypertension, although the effects of probiotics and FMT still need to be validated in large populations.

Adipose tissue-derived metabolite risk scores and risk for type 2 diabetes in South Asians

BACKGROUND

South Asians are at higher risk for type 2 diabetes (T2D) than many other race/ethnic groups. Ectopic adiposity, specifically hepatic steatosis and visceral fat may partially explain this. Our objective was to derive metabolite risk scores for ectopic adiposity and assess associations with incident T2D in South Asians.

METHODS

We examined 550 participants in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) cohort study aged 40-84 years without known cardiovascular disease or T2D and with metabolomic data. Computed tomography scans at baseline assessed hepatic attenuation and visceral fat area, and fasting serum specimens at baseline and after 5 years assessed T2D. LC-MS-based untargeted metabolomic analysis was performed followed by targeted integration and reporting of known signals. Elastic net regularized linear regression analyses was used to derive risk scores for hepatic steatosis and visceral fat using weighted coefficients. Logistic regression models associated metabolite risk score and incident T2D, adjusting for age, gender, study site, BMI, physical activity, diet quality, energy intake and use of cholesterol-lowering medication.

RESULTS

Average age of participants was 55 years, 36% women with an average body mass index (BMI) of 25 kg/m2 and 6% prevalence of hepatic steatosis, with 47 cases of incident T2D at 5 years. There were 445 metabolites of known identity. Of these, 313 metabolites were included in the MET-Visc score and 267 in the MET-Liver score. In most fully adjusted models, MET-Liver (OR 2.04 [95% CI 1.38, 3.03]) and MET-Visc (OR 2.80 [1.75, 4.46]) were associated with higher odds of T2D. These associations remained significant after adjustment for measured adiposity.

CONCLUSIONS

Metabolite risk scores for intrahepatic fat and visceral fat were strongly related to incident T2D independent of measured adiposity. Use of these biomarkers to target risk stratification may help capture pre-clinical metabolic abnormalities.

Effects of plant extracts and derivatives on cardiac K+, Nav, and Cav channels: a review

Natural products (NPs) are endless sources of compounds for fighting against several pathologies. Many dysfunctions, including cardiovascular disorders, such as cardiac arrhythmias have their modes of action regulation of the concentration of electrolytes inside and outside the cell targeting ion channels. Here, we highlight plant extracts and secondary metabolites' effects on the treatment of related cardiac pathologies on hERG, Nav, and Cav of cardiomyocytes. The natural product's pharmacology of expressed receptors like alpha-adrenergic receptors causes an influx of Ca2+ ions through receptor-operated Ca2+ ion channels. We also examine the NPs associated with cardiac contractions such as myocardial contractility by reducing the L-type calcium current and decreasing the intracellular calcium transient, inhibiting the K+ induced contractions, decreasing amplitude of myocyte shortening and showed negative ionotropic and chronotropic effects due to decreasing cytosolic Ca2+. We examine whether the NPs block potassium channels, particular the hERG channel and regulatory effects on Nav1.7.

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.

Plasma lipidomic markers of diet quality are associated with incident coronary heart disease in American Indian adults: the Strong Heart Family Study

BACKGROUND

Identifying lipidomic markers of diet quality is needed to inform the development of biomarkers of diet, and to understand the mechanisms driving the diet- coronary heart disease (CHD) association.

OBJECTIVES

This study aimed to identify lipidomic markers of diet quality and examine whether these lipids are associated with incident CHD.

METHODS

Using liquid chromatography-mass spectrometry, we measured 1542 lipid species from 1694 American Indian adults (aged 18-75 years, 62% female) in the Strong Heart Family Study. Participants were followed up for development of CHD through 2020. Information on the past year diet was collected using the Block Food Frequency Questionnaire, and diet quality was assessed using the Alternative Healthy Eating Index-2010 (AHEI). Mixed-effects linear regression was used to identify individual lipids cross-sectionally associated with AHEI. In prospective analysis, Cox frailty model was used to estimate the hazard ratio (HR) of each AHEI-related lipid for incident CHD. All models were adjusted for age, sex, center, education, body mass index, smoking, alcohol drinking, level of physical activity, energy intake, diabetes, hypertension, and use of lipid-lowering drugs. Multiple testing was controlled at a false discovery rate of <0.05.

RESULTS

Among 1542 lipid species measured, 71 lipid species (23 known), including acylcarnitine, cholesterol esters, glycerophospholipids, sphingomyelins and triacylglycerols, were associated with AHEI. Most of the identified lipids were associated with consumption of ω-3 (n-3) fatty acids. In total, 147 participants developed CHD during a mean follow-up of 17.8 years. Among the diet-related lipids, 10 lipids [5 known: cholesterol ester (CE)(22:5)B, phosphatidylcholine (PC)(p-14:0/22:1)/PC(o-14:0/22:1), PC(p-38:3)/PC(o-38:4)B, phosphatidylethanolamine (PE)(p-18:0/20:4)/PE(o-18:0/20:4), and sphingomyelin (d36:2)A] were associated with incident CHD. On average, each standard deviation increase in the baseline level of these 5 lipids was associated with 17%-23% increased risk of CHD (from HR: 1.17; 95% CI: 1, 1.36; to HR: 1.23; 95% CI: 1.05, 1.43).

CONCLUSIONS

In this study, lipidomic markers of diet quality in American Indian adults are found. Some diet-related lipids are associated with risk of CHD beyond established risk factors.

Maternal Mediterranean-Style Diet Adherence during Pregnancy and Metabolomic Signature in Postpartum Plasma: Findings from the Boston Birth Cohort

BACKGROUND

The health benefits of a Mediterranean-style diet (MSD) are well observed, but the underlying mechanisms are unclear. Metabolomic profiling offers a systematic approach for identifying which metabolic biomarkers and pathways might be affected by an MSD.

OBJECTIVES

This study aimed to identify postpartum plasma metabolites that are associated with MSD adherence during pregnancy and to further test whether these identified metabolites may vary by maternal characteristics.

METHODS

We analyzed data from 1410 mothers enrolled in the Boston Birth Cohort (BBC). A maternal food frequency questionnaire (FFQ) was administered and epidemiologic information was obtained via an in-person standard questionnaire interview within 24-72 h postpartum. Maternal clinical information was extracted from electronic medical records. A Mediterranean-style diet score (MSDS) was calculated using responses to the FFQ. Metabolomic profiling in postpartum plasma was conducted by liquid chromatography-MS. Linear regression models were used to assess the associations of each metabolite with an MSDS, adjusting for covariates.

RESULTS

Among the 380 postpartum plasma metabolites analyzed, 24 were associated with MSDS during pregnancy (false discovery rate < 0.05). Of 24 MSDS-associated metabolites, 19 were lipids [for example, triacylglycerols, phosphatidylcholines (PCs), PC plasmalogen, phosphatidylserine, and phosphatidylethanolamine]; others were amino acids (methionine sulfoxide and threonine), tropane (nor-psi-tropine), vitamin (vitamin A), and nucleotide (adenosine). The association of adenosine and methionine sulfoxide with MSDS differed by race (P-interaction = 0.033) and maternal overweight or obesity status (P-interaction = 0.021), respectively.

CONCLUSIONS

In the BBC, we identified 24 postpartum plasma metabolites associated with MSDS during pregnancy. The associations of the 2 metabolites varied by maternal race and BMI. This study provides a new insight into dietary effects on health under the skin. More studies are needed to better understand the metabolic pathways underlying the short- and long-term health benefits of an MSD during pregnancy.

Metabolomic Association and Risk Prediction With Heart Failure in Older Adults

BACKGROUND

Older adults have markedly increased risks of heart failure (HF), specifically HF with preserved ejection fraction (HFpEF). Identifying novel biomarkers can help in understanding HF pathogenesis and improve at-risk population identification. This study aimed to identify metabolites associated with incident HF, HFpEF, and HF with reduced ejection fraction and examine risk prediction in older adults.

METHODS

Untargeted metabolomic profiling was performed in Black and White adults from the ARIC study (Atherosclerosis Risk in Communities) visit 5 (n=3719; mean age, 75 years). We applied Cox regressions to identify metabolites associated with incident HF and its subtypes. The metabolite risk score (MRS) was constructed and examined for associations with HF, echocardiographic measures, and HF risk prediction. Independent samples from visit 3 (n=1929; mean age, 58 years) were used for replication.

RESULTS

Sixty metabolites (hazard ratios range, 0.79-1.49; false discovery rate, <0.05) were associated with incident HF after adjusting for clinical risk factors, eGFR, and NT-proBNP (N-terminal pro-B-type natriuretic peptide). Mannonate, a hydroxy acid, was replicated (hazard ratio, 1.36 [95% CI, 1.19-1.56]) with full adjustments. MRS was associated with an 80% increased risk of HF per SD increment, and the highest MRS quartile had 8.7× the risk of developing HFpEF than the lowest quartile. High MRS was also associated with unfavorable values of cardiac structure and function. Adding MRS over clinical risk factors and NT-proBNP improved 5-year HF risk prediction C statistics from 0.817 to 0.850 (∆C, 0.033 [95% CI, 0.017-0.047]). The association between MRS and incident HF was replicated after accounting for clinical risk factors (P<0.05).

CONCLUSIONS

Novel metabolites associated with HF risk were identified, elucidating disease pathways, specifically HFpEF. An MRS was associated with HF risk and improved 5-year risk prediction in older adults, which may assist at at-risk population identification.

Should we remove wine from the Mediterranean diet?: a narrative review

Moderate alcohol intake (or, more specifically, red wine) represents one of the postulated beneficial components of the traditional Mediterranean diet. Many well-conducted nonrandomized studies have reported that light-to-moderate alcohol intake is not only associated with reduced risk of cardiovascular disease, but also of all-cause mortality. Nonetheless, alcohol is an addictive substance imposing huge threats for public health. Alcohol consumption is associated with increased risks of cancer, neurological harms, injuries, and other adverse outcomes. Both the Global Burden of Disease (2016) and Mendelian randomization studies recently supported that the healthiest level of alcohol intake should be 0. Therefore, despite findings of conventional observational epidemiologic studies supporting a potential beneficial role of wine in the context of a healthy Mediterranean dietary pattern, a strong controversy remains on this issue. Age, sex, and drinking patterns are likely to be strong effect modifiers. In this context, a new 4-y noninferiority pragmatic trial in Spain (University of Navarra Alumni Trialist Initiative or "UNATI"), publicly funded by the European Research Council, will randomly assign >10,000 current drinkers (males, 50-70 y; females, 55-75 y) to repeatedly receive advice on either abstention or moderation in alcohol consumption. The recruitment will begin in mid-2024. The primary endpoint is a composite of the main clinical outcomes potentially related to alcohol intake including all-cause mortality. Clinical trial registry number: PREDIMED, ISRCTN35739639, www.predimed.es; SUN, clinicaltrials.gov identifier: NCT02669602, https://medpreventiva.es/i2CmeL.

Effects of Chinese heart-healthy diet on blood lipids, glucose, and estimated 10-y cardiovascular disease risk among Chinese adults: results on secondary outcomes of a randomized controlled trial

BACKGROUND

Healthy diet is essential for cardiovascular disease risk management, but its effects among Chinese patients, whose diets differ from Western diets, remain largely unknown.

METHODS

In this multicenter, patient- and outcome assessor-blind, randomized controlled feeding trial, 265 Chinese adults with baseline systolic blood pressure 130 to 159 mmHg were randomly assigned into Chinese heart-healthy (CHH) diet or usual diet for a 28-d intervention after a 7-d run-in period on usual diet. Blood lipids and glucose were measured from overnight fasting blood samples before and after the intervention. Ten-year cardiovascular disease risk was estimated using models previously developed and validated in Chinese. The changes in secondary outcomes of serum total cholesterol (TC), blood glucose, and 10-y cardiovascular disease risk over the intervention period were compared between intervention groups, adjusting for center, among participants with baseline and follow-up blood samples available. Sensitivity analyses were done with further adjustment for baseline values and covariables; missing data imputed; and among per-protocol population.

RESULTS

Among 256 eligible participants (130 on CHH diet, 126 on control diet), 42% had hypercholesterolemia and 15% had diabetes at baseline. In the control group, TC and 10-y cardiovascular disease risk decreased after the intervention by 0.16 mmol/L and 0.91%, respectively, but blood glucose increased by 0.25 mmol/L. Compared with usual diet, the CHH diet lowered TC (-0.14 mmol/L, P = 0.017) and 10-y cardiovascular disease risk (-1.24%, P = 0.001) further. No effect on blood glucose was found. All sensitivity analyses confirmed the results on TC and 10-y cardiovascular disease risk, and analysis with multiple variables adjusted showed a borderline significant effect on blood glucose (-0.17 mmol/L, P = 0.051). The differences in intake of nutrients and food groups between intervention groups explained the results.

CONCLUSIONS

The CHH diet reduced TC and 10-y cardiovascular disease risk and was likely to reduce blood glucose among Chinese adults with mild hypertension. Further studies with longer terms are warranted. This trial was registered at clinicaltrials.gov as NCT03882645.

Salmon Food-Specific Compounds and Their Metabolites Increase in Human Plasma and Are Associated with Cardiometabolic Health Indicators Following a Mediterranean-Style Diet Intervention

BACKGROUND

Nutrimetabolomics allows for the comprehensive analysis of foods and human biospecimens to identify biomarkers of intake and begin to probe their associations with health. Salmon contains hundreds of compounds that may provide cardiometabolic benefits.

OBJECTIVES

We used untargeted metabolomics to identify salmon food-specific compounds (FSCs) and their predicted metabolites that were found in plasma after a salmon-containing Mediterranean-style (MED) diet intervention. Associations between changes in salmon FSCs and changes in cardiometabolic health indicators (CHIs) were also explored.

METHODS

For this secondary analysis of a randomized, crossover, controlled feeding trial, 41 participants consumed MED diets with 2 servings of salmon per week for 2 5-wk periods. CHIs were assessed, and fasting plasma was collected pre- and postintervention. Plasma, salmon, and 99 MED foods were analyzed using liquid chromatography-mass spectrometry-based metabolomics. Compounds were characterized as salmon FSCs if detected in all salmon replicates but none of the other foods. Metabolites of salmon FSCs were predicted using machine learning. For salmon FSCs and metabolites found in plasma, linear mixed-effect models were used to assess change from pre- to postintervention and associations with changes in CHIs.

RESULTS

Relative to the other 99 MED foods, there were 508 salmon FSCs with 237 unique metabolites. A total of 143 salmon FSCs and 106 metabolites were detected in plasma. Forty-eight salmon FSCs and 30 metabolites increased after the intervention (false discovery rate <0.05). Increases in 2 annotated salmon FSCs and 2 metabolites were associated with improvements in CHIs, including total cholesterol, low-density lipoprotein cholesterol, triglycerides, and apolipoprotein B.

CONCLUSIONS

A data-driven nutrimetabolomics strategy identified salmon FSCs and their predicted metabolites that were detectable in plasma and changed after consumption of a salmon-containing MED diet. Findings support this approach for the discovery of compounds in foods that may serve, upon further validation, as biomarkers or act as bioactive components influential to health. The trials supporting this work were registered at NCT02573129 (Mediterranean-style diet intervention) and NCT05500976 (ongoing clinical trial).

The metabolic potential of inflammatory and insulinaemic dietary patterns and risk of type 2 diabetes

AIMS/HYPOTHESIS

Diets with higher inflammatory and insulinaemic potential have been associated with an increased risk of type 2 diabetes. However, it remains unknown whether plasma metabolomic profiles related to proinflammatory/hyperinsulinaemic diets and to inflammatory/insulin biomarkers are associated with type 2 diabetes risk.

METHODS

We analysed 6840 participants from the Nurses' Health Study and Health Professionals Follow-up Study to identify the plasma metabolome related to empirical dietary inflammatory pattern (EDIP), empirical dietary index for hyperinsulinemia (EDIH), four circulating inflammatory biomarkers and C-peptide. Dietary intakes were assessed using validated food frequency questionnaires. Plasma metabolomic profiling was conducted by LC-MS/MS. Metabolomic signatures were derived using elastic net regression. Multivariable Cox regression was used to examine associations of the metabolomic profiles with type 2 diabetes risk.

RESULTS

We identified 27 metabolites commonly associated with both EDIP and inflammatory biomarker z score and 21 commonly associated with both EDIH and C-peptide. Higher metabolomic dietary inflammatory potential (MDIP), reflecting higher metabolic potential of both an inflammatory dietary pattern and circulating inflammatory biomarkers, was associated with higher type 2 diabetes risk. The HR comparing highest vs lowest quartiles of MDIP was 3.26 (95% CI 2.39, 4.44). We observed a strong positive association with type 2 diabetes risk for the metabolomic signature associated with EDIP-only (HR 3.75; 95% CI 2.71, 5.17) or inflammatory biomarkers-only (HR 4.07; 95% CI 2.91, 5.69). In addition, higher metabolomic dietary index for hyperinsulinaemia (MDIH), reflecting higher metabolic potential of both an insulinaemic dietary pattern and circulating C-peptide, was associated with greater type 2 diabetes risk (HR 3.00; 95% CI 2.22, 4.06); further associations with type 2 diabetes were HR 2.79 (95% CI 2.07, 3.76) for EDIH-only signature and HR 3.89 (95% CI 2.82, 5.35) for C-peptide-only signature. The diet scores were significantly associated with risk, although adjustment for the corresponding metabolomic signature scores attenuated the associations with type 2 diabetes, these remained significant.

CONCLUSIONS/INTERPRETATION

The metabolomic signatures reflecting proinflammatory or hyperinsulinaemic diets and related biomarkers were positively associated with type 2 diabetes risk, supporting that these dietary patterns may influence type 2 diabetes risk via the regulation of metabolism.

Bioinformatic platforms for clinical stratification of natural history of atherosclerotic cardiovascular diseases

Although bioinformatic methods gained a lot of attention in the latest years, their use in real-world studies for primary and secondary prevention of atherosclerotic cardiovascular diseases (ASCVD) is still lacking. Bioinformatic resources have been applied to thousands of individuals from the Framingham Heart Study as well as health care-associated biobanks such as the UK Biobank, the Million Veteran Program, and the CARDIoGRAMplusC4D Consortium and randomized controlled trials (i.e. ODYSSEY, FOURIER, ASPREE, and PREDIMED). These studies contributed to the development of polygenic risk scores (PRS), which emerged as novel potent genetic-oriented tools, able to calculate the individual risk of ASCVD and to predict the individual response to therapies such as statins and proprotein convertase subtilisin/kexin type 9 inhibitor. ASCVD are the first cause of death around the world including coronary heart disease (CHD), peripheral artery disease, and stroke. To achieve the goal of precision medicine and personalized therapy, advanced bioinformatic platforms are set to link clinically useful indices to heterogeneous molecular data, mainly epigenomics, transcriptomics, metabolomics, and proteomics. The DIANA study found that differential methylation of ABCA1, TCF7, PDGFA, and PRKCZ significantly discriminated patients with acute coronary syndrome from healthy subjects and their expression levels positively associated with CK-MB serum concentrations. The ARIC Study revealed several plasma proteins, acting or not in lipid metabolism, with a potential role in determining the different pleiotropic effects of statins in each subject. The implementation of molecular high-throughput studies and bioinformatic techniques into traditional cardiovascular risk prediction scores is emerging as a more accurate practice to stratify patients earlier in life and to favour timely and tailored risk reduction strategies. Of note, radiogenomics aims to combine imaging features extracted for instance by coronary computed tomography angiography and molecular biomarkers to create CHD diagnostic algorithms useful to characterize atherosclerotic lesions and myocardial abnormalities. The current view is that such platforms could be of clinical value for prevention, risk stratification, and treatment of ASCVD.

Olive oil consumption, plasma metabolites, and risk of type 2 diabetes and cardiovascular disease

BACKGROUND

Olive oil consumption has been inversely associated with the risk of type 2 diabetes (T2D) and cardiovascular disease (CVD). However, the impact of olive oil consumption on plasma metabolites remains poorly understood. This study aims to identify plasma metabolites related to total and specific types of olive oil consumption, and to assess the prospective associations of the identified multi-metabolite profiles with the risk of T2D and CVD.

METHODS

The discovery population included 1837 participants at high cardiovascular risk from the PREvención con DIeta MEDiterránea (PREDIMED) trial with available metabolomics data at baseline. Olive oil consumption was determined through food-frequency questionnaires (FFQ) and adjusted for total energy. A total of 1522 participants also had available metabolomics data at year 1 and were used as the internal validation sample. Plasma metabolomics analyses were performed using LC-MS. Cross-sectional associations between 385 known candidate metabolites and olive oil consumption were assessed using elastic net regression analysis. A 10-cross-validation (CV) procedure was used, and Pearson correlation coefficients were assessed between metabolite-weighted models and FFQ-derived olive oil consumption in each pair of training-validation data sets within the discovery sample. We further estimated the prospective associations of the identified plasma multi-metabolite profile with incident T2D and CVD using multivariable Cox regression models.

RESULTS

We identified a metabolomic signature for the consumption of total olive oil (with 74 metabolites), VOO (with 78 metabolites), and COO (with 17 metabolites), including several lipids, acylcarnitines, and amino acids. 10-CV Pearson correlation coefficients between total olive oil consumption derived from FFQs and the multi-metabolite profile were 0.40 (95% CI 0.37, 0.44) and 0.27 (95% CI 0.22, 0.31) for the discovery and validation sample, respectively. We identified several overlapping and distinct metabolites according to the type of olive oil consumed. The baseline metabolite profiles of total and extra virgin olive oil were inversely associated with CVD incidence (HR per 1SD: 0.79; 95% CI 0.67, 0.92 for total olive oil and 0.70; 0.59, 0.83 for extra virgin olive oil) after adjustment for confounders. However, no significant associations were observed between these metabolite profiles and T2D incidence.

CONCLUSIONS

This study reveals a panel of plasma metabolites linked to the consumption of total and specific types of olive oil. The metabolite profiles of total olive oil consumption and extra virgin olive oil were associated with a decreased risk of incident CVD in a high cardiovascular-risk Mediterranean population, though no associations were observed with T2D incidence.

TRIAL REGISTRATION

The PREDIMED trial was registered at ISRCTN ( http://www.isrctn.com/ , ISRCTN35739639).

Association of age at first sexual intercourse and lifetime number of sexual partners with cardiovascular diseases: a bi-directional Mendelian randomization study

Background

Limited studies have explored the association between sexual factors [age at first sexual intercourse (AFS) and lifetime number of sexual partners (LNSP)] and cardiovascular diseases (CVDs), leaving the causality inconclusive.

Methods

We performed a bi-directional Mendelian randomization (MR) study to investigate the causality between sexual factors and CVDs, including coronary artery disease, myocardial infarction, atrial fibrillation (AF), heart failure (HF), and ischemic stroke (IS). Single-nucleotide polymorphisms (SNPs) for sexual factors were extracted from the UK Biobank. Statistics for each CVD were derived from two different databases. MR estimates were calculated per outcome database and were combined through meta-analysis. Several complementary sensitivity analyses were also performed.

Results

The primary analysis suggested that AFS was causally associated with the risk of CVDs; the odds ratios (ORs) ranged from 0.686 [95% confidence interval (CI), 0.611-0.770] for HF to 0.798 (95% CI, 0.719-0.886) for AF. However, the association between AFS and IS (OR, 0.844; 95% CI, 0.632-1.126) was not consistent in the meta-analysis after excluding SNPs related to confounders. Moreover, non-significant associations were found between LNSP and CVDs. Reverse direction MR analysis showed that CVDs were not associated with sexual factors.

Conclusions

Genetic evidence suggested that AFS was causally associated with the risk of CVDs except for IS, whereas non-significant association of LNSP with CVDs was detected. Further investigation into AFS could be warranted in preventing the progression of CVDs.

Dietary Patterns and Cardiovascular Risk: Are the Mediterranean Diet, the Heart-Healthy Diet, and Phytochemicals Associated with Lower Cardiovascular Risks?

Background

Dietary pattern may be one of the determinants of cardiovascular health. This study aimed to examine the relationship between a heart-healthy diet, the phytochemical content of a diet, and Mediterranean diet and cardiovascular disease (CVD) risks.

Methods

This study was conducted with healthy volunteers (n=1446) from Turkey between August 2022 and September 2022. As risk assessment systems to determine CVD risks, SCORE (Systematic Coronary Risk Evaluation) and ASCVD (Atherosclerotic Cardiovascular Disease) were used. We utilized MEDFICTS (Meats, Eggs, Dairy, Fried foods, Fat in Baked Goods, Convenience Foods, Fats Added at the Table, and Snacks) to establish the suitability of the current diet for heart health, and MEDAS (Mediterranean Diet Adherence Screener) to examine the Mediterranean diet characteristics of the current diet. The phytochemical content of the diet was determined using the Phytochemical Index method developed by McCarty.

Results

The lifetime and 10-year risk scores of SCORE and ASCVD were positively correlated with the MEDFICTS score (r=0.12, P<0.001; r=0.06, P=0.020; r=0.10, P=0.001, respectively). Mediterranean diet characteristics were correlated with lower CVD risk as per the SCORE categories (r=-0.07, P=0.009). A one-unit increase in MEDFICTS scores increased high-to-very high CVD risk and 10-year moderate-to-high CVD risk by 1.01 times, while a one-unit increase in the Mediterranean diet score decreased high-to-very high CVD risk and 10-year moderate-to-high CVD risk by 0.91 times and 0.95 times, respectively. In addition, high values of body weight, body mass index, waist circumference, waist-height ratio, and neck circumference were associated with higher CVD risk (P<0.001).

Conclusion

Adopting a Mediterranean diet and a heart-healthy diet may be a good strategy to reduce CVD risks.

Metabolite Signature of Life's Essential 8 and Risk of Coronary Heart Disease Among Low-Income Black and White Americans

BACKGROUND

Life's essential 8 (LE8) is a comprehensive construct of cardiovascular health. Yet, little is known about the LE8 score, its metabolic correlates, and their predictive implications among Black Americans and low-income individuals.

METHODS

In a nested case-control study of coronary heart disease (CHD) among 299 pairs of Black and 298 pairs of White low-income Americans from the Southern Community Cohort Study, we estimated LE8 score and applied untargeted plasma metabolomics and elastic net with leave-one-out cross-validation to identify metabolite signature (MetaSig) of LE8. Associations of LE8 score and MetaSig with incident CHD were examined using conditional logistic regression. The mediation effect of MetaSig on the LE8-CHD association was also examined. The external validity of MetaSig was evaluated in another nested CHD case-control study among 299 pairs of Chinese adults.

RESULTS

Higher LE8 score was associated with lower CHD risk (standardized odds ratio, 0.61 [95% CI, 0.53-0.69]). The MetaSig, consisting of 133 metabolites, showed significant correlation with LE8 score (r=0.61) and inverse association with CHD (odds ratio, 0.57 [0.49-0.65]), robust to adjustment for LE8 score and across participants with different sociodemographic and health status ([odds ratios, 0.42-0.69]; all P<0.05). MetaSig mediated a large portion of the LE8-CHD association: 53% (32%-80%). Significant associations of MetaSig with LE8 score and CHD risk were found in validation cohort (r=0.49; odds ratio, 0.57 [0.46-0.69]).

CONCLUSIONS

Higher LE8 score and its MetaSig were associated with lower CHD risk among low-income Black and White Americans. Metabolomics may offer an objective measure of LE8 and its metabolic phenotype relevant to CHD prevention among diverse populations.

Correlation between dietary inflammation and mortality among hyperlipidemics

BACKGROUND AND OBJECTIVE

Although the the Dietary Inflammatory Index (DII) serves to be one of the reliable indicator for hyperlipidaemia, there is still uncertainty about its relationship to prognosis in the hyperlipidaemic population. In current study, the DII levels were analyzed in relation to the mortality risk among among the hyperlipidaemic individuals with the aim of determining any prospective correlation.

METHODS

14,460 subjects with hyperlipidaemia from the 10-year (2001-2010) National Health and Nutrition Examination Survey (NHANES) were chosen for this study. The endpoint event for follow-up was all-cause mortality, and subjects were tracked for up to December 31, 2019, or death, whichever occurred first. The tertiles of the DII levels were utilized for categorizing the study population into three groups. Survival curves, Cox proportional hazards regression models, restricted cubic spline (RCS), subgroup and interaction analyses, and sensitivity analyses were employed sequentially for the purpose of evaluating the association of the DII with mortality.

RESULTS

3170 (21.92%) all-cause deaths were recorded during an average 148-month follow-up period. Kaplan-Meier survival curves indicated that the survival rate of participants divided into the low DII group was substantially improved compared to that of those in the higher DII group (log-rank P < 0.001). After controlling for confounders, higher levels of DII were observed to be meaningfully linked to an elevated risk of death, no matter whether DII was specified for the continuous (hazard ratio (HR): 1.06; 95% confidence interval (CI): 1.04-1.08) or the categorical variable (HR: 1.22; 95% CI: 1.11-1.33). The DII and mortality displayed a linear association, according to the RCS. Stratified and sensitivity analyses reinforced the proof that these findings were reliable.

CONCLUSION

Among patients with hyperlipidaemia, the risk of death was positively and linearly linked with DII levels.

Multinomial machine learning identifies independent biomarkers by integrated metabolic analysis of acute coronary syndrome

A multi-class classification model for acute coronary syndrome (ACS) remains to be constructed based on multi-fluid metabolomics. Major confounders may exert spurious effects on the relationship between metabolism and ACS. The study aims to identify an independent biomarker panel for the multiclassification of HC, UA, and AMI by integrating serum and urinary metabolomics. We performed a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics study on 300 serum and urine samples from 44 patients with unstable angina (UA), 77 with acute myocardial infarction (AMI), and 29 healthy controls (HC). Multinomial machine learning approaches, including multinomial adaptive least absolute shrinkage and selection operator (LASSO) regression and random forest (RF), and assessment of the confounders were applied to integrate a multi-class classification biomarker panel for HC, UA and AMI. Different metabolic landscapes were portrayed during the transition from HC to UA and then to AMI. Glycerophospholipid metabolism and arginine biosynthesis were predominant during the progression from HC to UA and then to AMI. The multiclass metabolic diagnostic model (MDM) dependent on ACS, including 2-ketobutyric acid, LysoPC(18:2(9Z,12Z)), argininosuccinic acid, and cyclic GMP, demarcated HC, UA, and AMI, providing a C-index of 0.84 (HC vs. UA), 0.98 (HC vs. AMI), and 0.89 (UA vs. AMI). The diagnostic value of MDM largely derives from the contribution of 2-ketobutyric acid, and LysoPC(18:2(9Z,12Z)) in serum. Higher 2-ketobutyric acid and cyclic GMP levels were positively correlated with ACS risk and atherosclerosis plaque burden, while LysoPC(18:2(9Z,12Z)) and argininosuccinic acid showed the reverse relationship. An independent multiclass biomarker panel for HC, UA, and AMI was constructed using the multinomial machine learning methods based on serum and urinary metabolite signatures.

Metabolomic profiles of chronic distress are associated with cardiovascular disease risk and inflammation-related risk factors

BACKGROUND

Chronic psychological distress is associated with increased risk of cardiovascular disease (CVD) and investigators have posited inflammatory factors may be centrally involved in these relationships. However, mechanistic evidence and molecular underpinnings of these processes remain unclear, and data are particularly sparse among women. This study examined if a metabolite profile linked with distress was associated with increased CVD risk and inflammation-related risk factors.

METHODS

A plasma metabolite-based distress score (MDS) of twenty chronic psychological distress-related metabolites was developed in cross-sectional, 1:1 matched case-control data comprised of 558 women from the Nurses' Health Study (NHS; 279 women with distress, 279 controls). This MDS was then evaluated in two other cohorts: the Women's Health Initiative Observational Cohort (WHI-OS) and the Prevención con Dieta Mediterránea (PREDIMED) trial. We tested the MDS's association with risk of future CVD in each sample and with levels of C-reactive protein (CRP) in the WHI-OS. The WHI-OS subsample included 944 postmenopausal women (472 CHD cases; mean time to event = 5.8 years); the PREDIMED subsample included 980 men and women (224 CVD cases, mean time to event = 3.1 years).

RESULTS

In the WHI-OS, a 1-SD increase in the plasma MDS was associated with a 20% increased incident CHD risk (odds ratio [OR] = 1.20, 95% CI: 1.04 - 1.38), adjusting for known CVD risk factors excluding total and HDL cholesterol. This association was attenuated after including total and HDL cholesterol. CRP mediated an average 12.9% (95% CI: 4.9% - 28%, p < 10-15) of the total effect of MDS on CHD risk when adjusting for matching factors. This effect was attenuated after adjusting for known CVD risk factors. Of the metabolites in the MDS, tryptophan and threonine were inversely associated with incident CHD risk in univariate models. In PREDIMED, each one SD increase in the MDS was associated with an OR of 1.19 (95% CI: 1.00 - 1.41) for incident CVD risk, after adjusting all risk factors. Similar associations were observed in men and women. Four metabolites in the MDS were associated with incident CVD risk in PREDIMED in univariate models. Biliverdin and C36:5 phosphatidylcholine (PC) plasmalogen had inverse associations; C16:0 ceramide and C18:0 lysophosphatidylethanolamine(LPE) each had positive associations with CVD risk.

CONCLUSIONS

Our study points to molecular alterations that may underlie the association between chronic distress and subsequent risk of cardiovascular disease in adults.

Sex differences in associations of plasma metabolites with blood pressure and heart rate variability: The HELIUS study

BACKGROUND AND AIMS

Since plasma metabolites can modulate blood pressure (BP) and vary between men and women, we examined sex differences in plasma metabolite profiles associated with BP and sympathicovagal balance. Our secondary aim was to investigate associations between gut microbiota composition and plasma metabolites predictive of BP and heart rate variability (HRV).

METHODS

From the HELIUS cohort, we included 196 women and 173 men. Office systolic BP and diastolic BP were recorded, and heart rate variability (HRV) and baroreceptor sensitivity (BRS) were calculated using finger photoplethysmography. Plasma metabolomics was measured using untargeted LC-MS/MS. Gut microbiota composition was determined using 16S sequencing. We used machine learning models to predict BP and HRV from metabolite profiles, and to predict metabolite levels from gut microbiota composition.

RESULTS

In women, best predicting metabolites for systolic BP included dihomo-lineoylcarnitine, 4-hydroxyphenylacetateglutamine and vanillactate. In men, top predictors included sphingomyelins, N-formylmethionine and conjugated bile acids. Best predictors for HRV in men included phenylacetate and gentisate, which were associated with lower HRV in men but not in women. Several of these metabolites were associated with gut microbiota composition, including phenylacetate, multiple sphingomyelins and gentisate.

CONCLUSIONS

Plasma metabolite profiles are associated with BP in a sex-specific manner. Catecholamine derivatives were more important predictors for BP in women, while sphingomyelins were more important in men. Several metabolites were associated with gut microbiota composition, providing potential targets for intervention.

Association of healthy dietary patterns and cardiorespiratory fitness in the community

AIMS

To evaluate the associations of dietary indices and quantitative cardiorespiratory fitness (CRF) measures in a large, community-based sample harnessing metabolomic profiling to interrogate shared biology.

METHODS AND RESULTS

Framingham Heart Study (FHS) participants underwent maximum effort cardiopulmonary exercise tests for CRF quantification (via peak VO2) and completed semi-quantitative food frequency questionnaires. Dietary quality was assessed by the Alternative Healthy Eating Index (AHEI) and Mediterranean-style Diet Score (MDS), and fasting blood concentrations of 201 metabolites were quantified. In 2380 FHS participants (54 ± 9 years, 54% female, body mass index 28 ± 5 kg/m2), 1 SD higher AHEI and MDS were associated with 5.2% (1.2 mL/kg/min, 95% CI 4.3-6.0%, P < 0.0001) and 4.5% (1.0 mL/kg/min, 95% CI 3.6-5.3%, P < 0.0001) greater peak VO2 in linear models adjusted for age, sex, total daily energy intake, cardiovascular risk factors, and physical activity. In participants with metabolite profiling (N = 1154), 24 metabolites were concordantly associated with both dietary indices and peak VO2 in multivariable-adjusted linear models (FDR < 5%). Metabolites that were associated with lower CRF and poorer dietary quality included C6 and C7 carnitines, C16:0 ceramide, and dimethylguanidino valeric acid, and metabolites that were positively associated with higher CRF and favourable dietary quality included C38:7 phosphatidylcholine plasmalogen and C38:7 and C40:7 phosphatidylethanolamine plasmalogens.

CONCLUSION

Higher diet quality is associated with greater CRF cross-sectionally in a middle-aged community-dwelling sample, and metabolites highlight potential shared favourable effects on cardiometabolic health.

Metabolomic epidemiology offers insights into disease aetiology

Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.

Targeting microbiota to alleviate the harm caused by sleep deprivation

Sleep deprivation has become a common health hazard, affecting 37-58% of the population and promoting the occurrence and development of many diseases. To date, effective treatment strategies are still elusive. Accumulating evidence indicates that modulating the intestinal microbiota harbors significant potential for alleviating the deleterious impacts of sleep deprivation. This paper first reviews the effects of sleep deprivation on gastrointestinal diseases, metabolic diseases, and neuropsychiatric diseases, discussing its specific mechanisms of influence. We then focus on summarizing existing interventions, including probiotics, melatonin, prebiotics, diet, and fecal microbiota transplantation (FMT). Finally, we have discussed the advantages and limitations of each strategy. Compared with other strategies, probiotics showed a high potential in alleviating sleep deprivation-related hazards due to their reduced risk and high security. We suggest that future research should focus on the specific mechanisms by which probiotics mitigate the harms of sleep deprivation, such insights may unveil novel pathways for treating diseases exacerbated by insufficient sleep.

Plasma metabolomic profiles of plant-based dietary indices reveal potential pathways for metabolic syndrome associations

BACKGROUND AND AIMS

Plant-based dietary patterns have been associated with improved health outcomes. This study aims to describe the metabolomic fingerprints of plant-based diet indices (PDI) and examine their association with metabolic syndrome (MetS) and its components in a Danish population.

METHODS

The MAX study comprised 676 participants (55% women, aged 18-67 y) from Copenhagen. Sociodemographic and dietary data were collected using questionnaires and three 24-h dietary recalls over one year (at baseline, and at 6 and 12 months). Mean dietary intakes were computed, as well as overall PDI, healthful (hPDI) and unhealthful (uPDI) scores, according to food groups for each plant-based index. Clinical variables were also collected at the same time points in a health examination that included complete blood tests. MetS was defined according to the International Diabetes Federation criteria. Plasma metabolites were measured using a targeted metabolomics approach. Metabolites associated with PDI were selected using random forest models and their relationships with PDIs and MetS were analyzed using generalized linear mixed models.

RESULTS

The mean prevalence of MetS was 10.8%. High, compared to low, hPDI and uPDI scores were associated with a lower and higher odd of MetS, respectively [odds ratio (95%CI); hPDI: 0.56 (0.43-0.74); uPDI: 1.61 (1.26-2.05)]. Out of 411 quantified plasma metabolites, machine-learning metabolomics fingerprinting revealed 13 metabolites, including food and food-related microbial metabolites, like hypaphorine, indolepropionic acid and lignan-derived enterolactones. These metabolites were associated with all PDIs and were inversely correlated with MetS components (p < 0.05). Furthermore, they had an explainable contribution of 12% and 14% for the association between hPDI or uPDI, respectively, and MetS only among participants with overweight/obesity.

CONCLUSIONS

Metabolites associated with PDIs were inversely associated with MetS and its components, and may partially explain the effects of plant-based diets on cardiometabolic risk factors.

Yearly attained adherence to Mediterranean diet and incidence of diabetes in a large randomized trial

BACKGROUND

Several large observational prospective studies have reported a protection by the traditional Mediterranean diet against type 2 diabetes, but none of them used yearly repeated measures of dietary intake. Repeated measurements of dietary intake are able to improve subject classification and to increase the quality of the assessed relationships in nutritional epidemiology. Beyond observational studies, randomized trials provide stronger causal evidence. In the context of a randomized trial of primary cardiovascular prevention, we assessed type 2 diabetes incidence according to yearly repeated measures of compliance with a nutritional intervention based on the traditional Mediterranean diet.

METHODS

PREDIMED (''PREvención con DIeta MEDiterránea'') was a Spanish trial including 7447 men and women at high cardiovascular risk. We assessed 3541 participants initially free of diabetes and originally randomized to 1 of 3 diets: low-fat diet (n = 1147, control group), Mediterranean diet supplemented with extra virgin olive (n = 1154) or Mediterranean diet supplemented with mixed nuts (n = 1240). As exposure we used actual adherence to Mediterranean diet (cumulative average), yearly assessed with the Mediterranean Diet Adherence Screener (scoring 0 to 14 points), and repeated up to 8 times (baseline and 7 consecutive follow-up years). This score was categorized into four groups: < 8, 8-< 10, 10- < 12, and 12-14 points. The outcome was new-onset type 2 diabetes.

RESULTS

Multivariable-adjusted hazard ratios from time-varying Cox models were 0.80 (95% confidence interval, 0.70-0.92) per + 2 points in Mediterranean Diet Adherence Screener (linear trend p = .001), and 0.46 (0.25-0.83) for the highest (12-14 points) versus the lowest (< 8) adherence. This inverse association was maintained after additionally adjusting for the randomized arm. Age- and sex-adjusted analysis of a validated plasma metabolomic signature of the Mediterranean Diet Adherence Screener (constituted of 67 metabolites) in a subset of 889 participants also supported these results.

CONCLUSIONS

Dietary intervention trials should quantify actual dietary adherence throughout the trial period to enhance the benefits and to assist results interpretation. A rapid dietary assessment tool, yearly repeated as a screener, was able to capture a strong inverse linear relationship between Mediterranean diet and type 2 diabetes. Trial registration ISRCTN35739639.

Systematic comparison of Mendelian randomisation studies and randomised controlled trials using electronic databases

OBJECTIVE

To scope the potential for (semi)-automated triangulation of Mendelian randomisation (MR) and randomised controlled trials (RCTs) evidence since the two methods have distinct assumptions that make comparisons between their results invaluable.

METHODS

We mined ClinicalTrials.Gov, PubMed and EpigraphDB databases and carried out a series of 26 manual literature comparisons among 54 MR and 77 RCT publications.

RESULTS

We found that only 13% of completed RCTs identified in ClinicalTrials.Gov submitted their results to the database. Similarly low coverage was revealed for Semantic Medline (SemMedDB) semantic triples derived from MR and RCT publications -36% and 12%, respectively. Among intervention types that can be mimicked by MR, only trials of pharmaceutical interventions could be automatically matched to MR results due to insufficient annotation with Medical Subject Headings ontology. A manual survey of the literature highlighted the potential for triangulation across a number of exposure/outcome pairs if these challenges can be addressed.

CONCLUSIONS

We conclude that careful triangulation of MR with RCT evidence should involve consideration of similarity of phenotypes across study designs, intervention intensity and duration, study population demography and health status, comparator group, intervention goal and quality of evidence.

Sleep Patterns, Plasma Metabolome, and Risk of Incident Type 2 Diabetes Mellitus

CONTEXT

A healthy sleep pattern has been related to a lower risk of type 2 diabetes mellitus (T2DM).

OBJECTIVE

We aimed to identify the metabolomic signature for the healthy sleep pattern and assess its potential causality with T2DM.

METHODS

This study included 78 659 participants with complete phenotypic data (sleep information and metabolomic measurements) from the UK Biobank study. Elastic net regularized regression was applied to calculate a metabolomic signature reflecting overall sleep patterns. We also performed genome-wide association analysis of the metabolomic signature and one-sample mendelian randomization (MR) with T2DM risk.

RESULTS

During a median of 8.8 years of follow-up, we documented 1489 incident T2DM cases. Compared with individuals who had an unhealthy sleep pattern, those with a healthy sleep pattern had a 49% lower risk of T2DM (multivariable-adjusted hazard ratio [HR], 0.51; 95% CI, 0.40-0.63). We further constructed a metabolomic signature using elastic net regularized regressions that comprised 153 metabolites, and robustly correlated with sleep pattern (r = 0.19; P = 3×10-325). In multivariable Cox regressions, the metabolomic signature showed a statistically significant inverse association with T2DM risk (HR per SD increment in the signature, 0.56; 95% CI, 0.52-0.60). Additionally, MR analyses indicated a significant causal relation between the genetically predicted metabolomic signature and incident T2DM (P for trend < .001).

CONCLUSION

In this large prospective study, we identified a metabolomic signature for the healthy sleep pattern, and such a signature showed a potential causality with T2DM risk independent of traditional risk factors.

Plasma metabolite profiles associated with the World Cancer Research Fund/American Institute for Cancer Research lifestyle score and future risk of cardiovascular disease and type 2 diabetes

BACKGROUND

A healthy lifestyle (HL) has been inversely related to type 2 diabetes (T2D) and cardiovascular disease (CVD). However, few studies have identified a metabolite profile associated with HL. The present study aims to identify a metabolite profile of a HL score and assess its association with the incidence of T2D and CVD in individuals at high cardiovascular risk.

METHODS

In a subset of 1833 participants (age 55-80y) of the PREDIMED study, we estimated adherence to a HL using a composite score based on the 2018 Word Cancer Research Fund/American Institute for Cancer Research recommendations. Plasma metabolites were analyzed using LC-MS/MS methods at baseline (discovery sample) and 1-year of follow-up (validation sample). Cross-sectional associations between 385 known metabolites and the HL score were assessed using elastic net regression. A 10-cross-validation procedure was used, and correlation coefficients or AUC were assessed between the identified metabolite profiles and the self-reported HL score. We estimated the associations between the identified metabolite profiles and T2D and CVD using multivariable Cox regression models.

RESULTS

The metabolite profiles that identified HL as a dichotomous or continuous variable included 24 and 58 metabolites, respectively. These are amino acids or derivatives, lipids, and energy intermediates or xenobiotic compounds. After adjustment for potential confounders, baseline metabolite profiles were associated with a lower risk of T2D (hazard ratio [HR] and 95% confidence interval (CI): 0.54, 0.38-0.77 for dichotomous HL, and 0.22, 0.11-0.43 for continuous HL). Similar results were observed with CVD (HR, 95% CI: 0.59, 0.42-0.83 for dichotomous HF and HR, 95%CI: 0.58, 0.31-1.07 for continuous HL). The reduction in the risk of T2D and CVD was maintained or attenuated, respectively, for the 1-year metabolomic profile.

CONCLUSIONS

In an elderly population at high risk of CVD, a set of metabolites was selected as potential metabolites associated with the HL pattern predicting the risk of T2D and, to a lesser extent, CVD. These results support previous findings that some of these metabolites are inversely associated with the risk of T2D and CVD.

TRIAL REGISTRATION

The PREDIMED trial was registered at ISRCTN ( http://www.isrctn.com/ , ISRCTN35739639).

Impact of dietary interventions on pre-diabetic oral and gut microbiome, metabolites and cytokines

Diabetes and associated comorbidities are a global health threat on the rise. We conducted a six-month dietary intervention in pre-diabetic individuals (NCT03222791), to mitigate the hyperglycemia and enhance metabolic health. The current work explores early diabetes markers in the 200 individuals who completed the trial. We find 166 of 2,803 measured features, including oral and gut microbial species and pathways, serum metabolites and cytokines, show significant change in response to a personalized postprandial glucose-targeting diet or the standard of care Mediterranean diet. These changes include established markers of hyperglycemia as well as novel features that can now be investigated as potential therapeutic targets. Our results indicate the microbiome mediates the effect of diet on glycemic, metabolic and immune measurements, with gut microbiome compositional change explaining 12.25% of serum metabolites variance. Although the gut microbiome displays greater compositional changes compared to the oral microbiome, the oral microbiome demonstrates more changes at the genetic level, with trends dependent on environmental richness and species prevalence in the population. In conclusion, our study shows dietary interventions can affect the microbiome, cardiometabolic profile and immune response of the host, and that these factors are well associated with each other, and can be harnessed for new therapeutic modalities.

Utilising the precision nutrition toolkit in the path towards precision medicine

The overall aim of precision nutrition is to replace the 'one size fits all' approach to dietary advice with recommendations that are more specific to the individual in order to improve the prevention or management of chronic disease. Interest in precision nutrition has grown with advancements in technologies such as genomics, proteomics, metabolomics and measurement of the gut microbiome. Precision nutrition initiatives have three major applications in precision medicine. First, they aim to provide more 'precision' dietary assessments through artificial intelligence, wearable devices or by employing omic technologies to characterise diet more precisely. Secondly, precision nutrition allows us to understand the underlying mechanisms of how diet influences disease risk and identify individuals who are more susceptible to disease due to gene-diet or microbiota-diet interactions. Third, precision nutrition can be used for 'personalised nutrition' advice where machine-learning algorithms can integrate data from omic profiles with other personal and clinical measures to improve disease risk. Proteomics and metabolomics especially provide the ability to discover new biomarkers of food or nutrient intake, proteomic or metabolomic signatures of diet and disease, and discover potential mechanisms of diet-disease interactions. Although there are several challenges that must be overcome to improve the reproducibility, cost-effectiveness and efficacy of these approaches, precision nutrition methodologies have great potential for nutrition research and clinical application.