Association between dairy intake, lipids and vascular structure and function in diabetes

Deep phenotyping and biomarkers of various dairy fat intakes in an 8-week randomized clinical trial and 2-year swine study

Health effects of dairy fats (DF) are difficult to evaluate, as DF intakes are hard to assess epidemiologically and DF have heterogeneous compositions that influence biological responses. We set out to find biomarkers of DF intake and assess biological response to a summer DF diet (R2), a winter DF diet (R3), and a R3 supplemented with calcium (R4) compared to a plant-fat-based diet (R1) in a randomized clinical trial (n=173) and a 2-year study in mildly metabolically disturbed downsized pigs (n=32). Conventional clinical measures were completed by LC/MS plasma metabolomics/lipidomics. The measured effects were modeled as biological functions to facilitate interpretation. DF intakes in pigs specifically induced a U-shaped metabolic trajectory, reprogramming metabolism to close to its initial status after a one-year turnaround. Twelve lipid species repeatably predicted DF intakes in both pigs and humans (6.6% errors). More broadly, in pigs, quality of DF modulated the time-related biological response (R2: 30 regulated functions, primarily at 6 months; R3: 26 regulated functions, mostly at 6-12 months; R4: 43 regulated functions, mostly at 18 months). Despite this heterogeneity, 9 functions overlapped under all 3 DF diets in both studies, related to a restricted area of amino acids metabolism, cofactors, nucleotides and xenobiotic pathways and the microbiota. In conclusion, over the long-term, DF reprograms metabolism to close to its initial biological status in metabolically-disrupted pigs. Quality of the DF modulates its metabolic influence, although some effects were common to all DF. A resilient signature of DF consumption found in pigs was validated in humans.

Metabolomics of Arterial Stiffness

Arterial stiffness (AS) is one of the earliest detectable signs of structural and functional alterations of the vessel wall and an independent predictor of cardiovascular events and death. The emerging field of metabolomics can be utilized to detect a wide spectrum of intermediates and products of metabolism in body fluids that can be involved in the pathogenesis of AS. Research over the past decade has reinforced this idea by linking AS to circulating acylcarnitines, glycerophospholipids, sphingolipids, and amino acids, among other metabolite species. Some of these metabolites influence AS through traditional cardiovascular risk factors (e.g., high blood pressure, high blood cholesterol, diabetes, smoking), while others seem to act independently through both known and unknown pathophysiological mechanisms. We propose the term 'arteriometabolomics' to indicate the research that applies metabolomics methods to study AS. The 'arteriometabolomics' approach has the potential to allow more personalized cardiovascular risk stratification, disease monitoring, and treatment selection. One of its major goals is to uncover the causal metabolic pathways of AS. Such pathways could represent valuable treatment targets in vascular ageing.

Serum lysophospholipidome of dietary origin as a suitable susceptibility/risk biomarker of human hypercholesterolemia: A cross-sectional study

BACKGROUND & AIMS

Whether bioactive lysophospholipids (lyso-PLs) and trimethylamine-N-oxide (TMAO) serve as non-invasive biomarkers in early human hypercholesterolemia (HC) is unknown. This study aimed to assess whether serum lyso-PLs and plasma TMAO may be suitable susceptibility/risk biomarkers of HC in humans. Secondarily, we aimed to evaluate the relationships between targeted metabolites, diet composition and circulating liver transaminases, and verify these results in hamsters.

METHODS

A targeted metabolomics and lipidomics approach determined plasma TMAO and serum lysophosphatidylcholines (lyso-PCs) and lysophosphatidylethanolamines (lyso-PEs) in low (L-LDL-c) and moderate to high (MH-LDL-c) LDL-cholesterol subjects. Additionally, the relationships between targeted metabolites, liver transaminases and diet, particularly fatty acid intake, were tested. In parallel, plasma and liver lyso-PL profiles were studied in 16 hamsters fed a moderate high-fat (HFD) or low-fat (LFD) diet for 30 days.

RESULTS

Predictive models identified lyso-PC15:0 and lyso-PE18:2 as the most discriminant lyso-PLs among groups. In MH-LDL-c (n = 48), LDL-cholesterol and saturated FAs were positively associated with lyso-PC15:0, whereas in L-LDL-c (n = 70), LDL-cholesterol and polyunsaturated fatty acids (PUFAs) were negatively and positively related to lyso-PE18:2, respectively. Interestingly, in MH-LDL-c, the lower lyso-PE 18:2 concentrations were indicative of higher LDL-cholesterol levels. Intrahepatic accumulation of lyso-PLs-containing essential n-6 PUFAs, including lyso-PE18:2, were higher in HFD-fed hamsters than LFD-fed hamsters.

CONCLUSIONS

Overall, results revealed a possible hepatic adaptive mechanism to counteract diet-induced steatosis in animal and hypercholesterolemia progression in humans. In particular, low serum lyso-PE18:2 suggests a suitable susceptibility/risk biomarker of HC in humans.

Lipidomic profiling identifies signatures of metabolic risk

BACKGROUND

Metabolic syndrome (MetS), the clustering of metabolic risk factors, is associated with cardiovascular disease risk. We sought to determine if dysregulation of the lipidome may contribute to metabolic risk factors.

METHODS

We measured 154 circulating lipid species in 658 participants from the Framingham Heart Study (FHS) using liquid chromatography-tandem mass spectrometry and tested for associations with obesity, dysglycemia, and dyslipidemia. Independent external validation was sought in three independent cohorts. Follow-up data from the FHS were used to test for lipid metabolites associated with longitudinal changes in metabolic risk factors.

RESULTS

Thirty-nine lipids were associated with obesity and eight with dysglycemia in the FHS. Of 32 lipids that were available for replication for obesity and six for dyslipidemia, 28 (88%) replicated for obesity and five (83%) for dysglycemia. Four lipids were associated with longitudinal changes in body mass index and four were associated with changes in fasting blood glucose in the FHS.

CONCLUSIONS

We identified and replicated several novel lipid biomarkers of key metabolic traits. The lipid moieties identified in this study are involved in biological pathways of metabolic risk and can be explored for prognostic and therapeutic utility.

An Updated Review of Lysophosphatidylcholine Metabolism in Human Diseases

Lysophosphatidylcholine (LPC) is increasingly recognized as a key marker/factor positively associated with cardiovascular and neurodegenerative diseases. However, findings from recent clinical lipidomic studies of LPC have been controversial. A key issue is the complexity of the enzymatic cascade involved in LPC metabolism. Here, we address the coordination of these enzymes and the derangement that may disrupt LPC homeostasis, leading to metabolic disorders. LPC is mainly derived from the turnover of phosphatidylcholine (PC) in the circulation by phospholipase A₂ (PLA₂). In the presence of Acyl-CoA, lysophosphatidylcholine acyltransferase (LPCAT) converts LPC to PC, which rapidly gets recycled by the Lands cycle. However, overexpression or enhanced activity of PLA₂ increases the LPC content in modified low-density lipoprotein (LDL) and oxidized LDL, which play significant roles in the development of atherosclerotic plaques and endothelial dysfunction. The intracellular enzyme LPCAT cannot directly remove LPC from circulation. Hydrolysis of LPC by autotaxin, an enzyme with lysophospholipase D activity, generates lysophosphatidic acid, which is highly associated with cancers. Although enzymes with lysophospholipase A₁ activity could theoretically degrade LPC into harmless metabolites, they have not been found in the circulation. In conclusion, understanding enzyme kinetics and LPC metabolism may help identify novel therapeutic targets in LPC-associated diseases.