Human Cerebrospinal Fluid Sample Preparation and Annotation for Integrated Lipidomics and Metabolomics Profiling Studies.

Cerebrospinal fluid (CSF) is a metabolically diverse biofluid and a key specimen for exploring biochemical changes in neurodegenerative diseases. Detecting lipid species in CSF using mass spectrometry (MS)-based techniques remains challenging because lipids are highly complex in structure, and their concentrations span over a broad dynamic range. This work aimed to develop a robust lipidomics and metabolomics method based on commonly used two-phase extraction systems from human CSF samples. Prioritizing lipid detection, biphasic extraction methods, Folch, Bligh and Dyer (B&D), Matyash, and acidified Folch and B&D (aFolch and aB&D) were compared using 150 µL of human CSF samples for the simultaneous extraction of lipids and metabolites with a wide range of polarity. Multiple chromatographical separation approaches, including reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), and gas chromatography (GC), were utilized to characterize human CSF metabolome. The aB&D method was found as the most reproducible technique (RSD < 15%) for lipid extraction. The aB&D and B&D yielded the highest peak intensities for targeted lipid internal standards and displayed superior extracting power for major endogenous lipid classes. A total of 674 unique metabolites with a wide polarity range were annotated in CSF using, combining RPLC-MS/MS lipidomics (n = 219), HILIC-MS/MS (n = 304), and GC-quadrupole time of flight (QTOF) MS (n = 151). Overall, our findings show that the aB&D extraction method provided suitable lipid coverage, reproducibility, and extraction efficiency for global lipidomics profiling of human CSF samples. In combination with RPLC-MS/MS lipidomics, complementary screening approaches enabled a comprehensive metabolite signature that can be employed in an array of clinical studies.

Ceramides are decreased after liraglutide treatment in people with type 2 diabetes: a post hoc analysis of two randomized clinical trials.

BACKGROUND: Specific ceramides have been identified as risk markers for cardiovascular disease (CVD) years before onset of disease. Treatment with the glucagon-like peptide-1 receptor agonist (GLP-1RA) liraglutide has been shown to induce beneficial changes in the lipid profile and reduce the risk of CVD. Reducing lipotoxic lipids with an antidiabetic drug therapy could be a path towards precision medicine approaches for the treatment of complications to diabetes. In this post-hoc study, an investigation was carried out on the effect of liraglutide on CVD-risk associated ceramides in two randomized clinical trials including participants with type 2 diabetes (T2D). METHODS: This study analyzed plasma samples from two independent randomized placebo-controlled clinical trials. The first trial, Antiproteinuric Effects of Liraglutide Treatment (LirAlbu12) followed a crossover design where 27 participants were treated for 12 weeks with either liraglutide (1.8 mg/d) or placebo, followed by a four-week washout period, and then another 12 weeks of the other treatment. The second clinical trial, Effect of Liraglutide on Vascular Inflammation in Type-2 Diabetes (LiraFlame26), lasted for 26 weeks and followed a parallel design, where 102 participants were randomized 1:1 to either liraglutide or placebo. Heresix prespecified plasma ceramides were measured using liquid chromatography mass spectrometry and assessed their changes using linear mixed models. Possible confounders were assessed with mediation analyses. RESULTS: In the LiraFlame26 trial, 26-week treatment with liraglutide resulted in a significant reduction of two ceramides associated with CVD risk, C16 Cer and C24:1 Cer (p < 0.05) compared to placebo. None of the remaining ceramides showed statistically significant changes in response to liraglutide treatment compared to placebo. Significant changes in ceramides were not found after 12-weeks of liraglutide treatment in the LirAlbu12 trial. Mediation analyses showed that weight loss did not affect ceramide reduction. CONCLUSIONS: It was demonstrated that treatment with liraglutide resulted in a reduction in C16 Cer and C24:1 Cer after 26 weeks of treatment. These findings suggest the GLP-1RA can be used to modulate ceramides in addition to its other properties. TRIAL REGISTRATION: Clinicaltrial.gov identifier: NCT02545738 and NCT03449654.

Ceramides as Risk Markers for Future Cardiovascular Events and All-Cause Mortality in Long-standing Type 1 Diabetes.

Ceramides are lipid molecules involved in inflammation-related signaling. Recent studies have shown that higher amounts of specific circulating ceramides and their ratios are associated with future development of cardiovascular (CV) disease (CVD). We examined the associations between serum ceramide levels with CVD, kidney failure, and all-cause mortality in individuals with long-standing type 1 diabetes (T1D). We included 662 participants with T1D and 6-year follow-up, with a mean age of 55 years and mean diabetes duration of 33 years. Baseline serum samples were analyzed using liquid chromatography-mass spectrometry. Six predefined ceramide levels were measured, and predefined ratios were calculated. Adjusted Cox regression analyses on ceramide levels in relation to future CV events (CVE), kidney failure, and all-cause mortality were performed, with and without adjustment for age, sex, BMI, LDL, triglycerides, systolic blood pressure, HbA1c, history of CVD, smoking status, statin use, estimated glomerular filtration rate (eGFR), and urinary albumin excretion rate (UAER). The ceramide ratio cer(d18:1/18:0)/cer(d18:1/24:0) was significantly associated with risk of CVE (hazard ratio [HR] = 1.33, P = 0.01) and all-cause mortality (HR = 1.48, P = 0.01) before and after adjustments. All five investigated ceramide ratios were associated with kidney failure, before adjusting for the kidney markers eGFR and UAER. In this study, we demonstrate specific ceramides and ratios associated with 6-year cardiovascular risk and all-cause mortality in a T1D cohort. This highlights the strength of ceramide association with vascular complications and presents a new potential tool for early risk assessment if validated in other cohorts. ARTICLE HIGHLIGHTS: Improved tools for assessing risk for diabetes complication before onset will help in complication prevention. We investigated a set of six predefined ceramides and their ratios versus 6-year outcomes of cardiovascular events, kidney failure, and all-cause mortality in people with long-standing type 1 diabetes, using Cox regression with and without adjustment for potential confounders. We found that several ceramides and ceramide ratios associated with cardiovascular events and all-cause mortality. The ratio of cer(d18:1/18:0)/cer(d18:1/24:0) was an especially robust marker. These finding show that ceramides can be biomarkers of cardiovascular disease and all-cause mortality in individuals with long-standing type 1 diabetes.

Multiomics profiling of human plasma and cerebrospinal fluid reveals ATN-derived networks and highlights causal links in Alzheimer's disease.

INTRODUCTION: This study employed an integrative system and causal inference approach to explore molecular signatures in blood and CSF, the amyloid/tau/neurodegeneration [AT(N)] framework, mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD), and genetic risk for AD. METHODS: Using the European Medical Information Framework (EMIF)-AD cohort, we measured 696 proteins in cerebrospinal fluid (n = 371), 4001 proteins in plasma (n = 972), 611 metabolites in plasma (n = 696), and genotyped whole-blood (7,778,465 autosomal single nucleotide epolymorphisms, n = 936). We investigated associations: molecular modules to AT(N), module hubs with AD Polygenic Risk scores and APOE4 genotypes, molecular hubs to MCI conversion and probed for causality with AD using Mendelian randomization (MR). RESULTS: AT(N) framework associated with protein and lipid hubs. In plasma, Proprotein Convertase Subtilisin/Kexin Type 7 showed evidence for causal associations with AD. AD was causally associated with Reticulocalbin 2 and sphingomyelins, an association driven by the APOE isoform. DISCUSSION: This study reveals multi-omics networks associated with AT(N) and causal AD molecular candidates.

Mitofusins Mfn1 and Mfn2 Are Required to Preserve Glucose- but Not Incretin-Stimulated ß-Cell Connectivity and Insulin Secretion.

Mitochondrial glucose metabolism is essential for stimulated insulin release from pancreatic ß-cells. Whether mitofusin gene expression, and hence, mitochondrial network integrity, is important for glucose or incretin signaling has not previously been explored. Here, we generated mice with ß-cell-selective, adult-restricted deletion knock-out (dKO) of the mitofusin genes Mfn1 and Mfn2 (ßMfn1/2 dKO). ßMfn1/2-dKO mice displayed elevated fed and fasted glycemia and a more than fivefold decrease in plasma insulin. Mitochondrial length, glucose-induced polarization, ATP synthesis, and cytosolic and mitochondrial Ca2+ increases were all reduced in dKO islets. In contrast, oral glucose tolerance was more modestly affected in ßMfn1/2-dKO mice, and glucagon-like peptide 1 or glucose-dependent insulinotropic peptide receptor agonists largely corrected defective glucose-stimulated insulin secretion through enhanced EPAC-dependent signaling. Correspondingly, cAMP increases in the cytosol, as measured with an Epac-camps-based sensor, were exaggerated in dKO mice. Mitochondrial fusion and fission cycles are thus essential in the ß-cell to maintain normal glucose, but not incretin, sensing. These findings broaden our understanding of the roles of mitofusins in ß-cells, the potential contributions of altered mitochondrial dynamics to diabetes development, and the impact of incretins on this process.

High-Throughput UHPLC-MS to Screen Metabolites in Feces for Gut Metabolic Health.

Feces are the product of our diets and have been linked to diseases of the gut, including Chron's disease and metabolic diseases such as diabetes. For screening metabolites in heterogeneous samples such as feces, it is necessary to use fast and reproducible analytical methods that maximize metabolite detection. As sample preparation is crucial to obtain high quality data in MS-based clinical metabolomics, we developed a novel, efficient and robust method for preparing fecal samples for analysis with a focus in reducing aliquoting and detecting both polar and non-polar metabolites. Fecal samples (n = 475) from patients with alcohol-related liver disease and healthy controls were prepared according to the proposed method and analyzed in an UHPLC-QQQ targeted platform in order to obtain a quantitative profile of compounds that impact liver-gut axis metabolism. MS analyses of the prepared fecal samples have shown reproducibility and coverage of n = 28 metabolites, mostly comprising bile acids and amino acids. We report metabolite-wise relative standard deviation (RSD) in quality control samples, inter-day repeatability, LOD (limit of detection), LOQ (limit of quantification), range of linearity and method recovery. The average concentrations for 135 healthy participants are reported here for clinical applications. Our high-throughput method provides a novel tool for investigating gut-liver axis metabolism in liver-related diseases using a noninvasive collected sample.

Liraglutide Lowers Palmitoleate Levels in Type 2 Diabetes. A Post Hoc Analysis of the LIRAFLAME Randomized Placebo-Controlled Trial.

Background: Liraglutide is a glucose-lowering medication used to treat type 2 diabetes and obesity. It is a GLP-1 receptor agonist with downstream metabolic changes beyond the incretin system, such as reducing the risk of cardiovascular complications. The understanding of these changes is critical for improving treatment outcomes. Herein, we present a post hoc experimental analysis using metabolomic phenotyping to discover molecular mecphanisms in response to liraglutide. Method: Plasma samples were obtained from The LiraFlame Study (ClinicalTrials.gov identifier: NCT03449654), a randomized double-blinded placebo-controlled clinical trial, including 102 participants with type 2 diabetes randomized to either liraglutide or placebo treatment for 26 weeks. Mass spectrometry-based metabolomics analyses were carried out on samples from baseline and the end of the trial. Metabolites (n=114) were categorized into pathways and linear mixed models were constructed to evaluate the association between changes in metabolites and liraglutide treatment. Results: We found the free fatty acid palmitoleate was significantly reduced in the liraglutide group compared to placebo (adjusted for multiple testing p-value = 0.04). The activity of stearoyl-CoA desaturase-1 (SCD1), the rate limiting enzyme for converting palmitate into palmitoleate, was found significantly downregulated by liraglutide treatment compared to placebo (p-value = 0.01). These metabolic changes have demonstrated to be linked to insulin sensitivity and cardiovascular health.

Ceramides and phospholipids are downregulated with liraglutide treatment: results from the LiraFlame randomized controlled trial.

INTRODUCTION: Treatment with glucagon-like peptide-1 receptor agonists (GLP-1 RAs) can reduce risk of cardiovascular disease (CVD) in persons living with type 2 diabetes, however the mechanisms explaining this cardiovascular benefit are still debated. We investigated changes in the plasma lipidome following treatment with the GLP-1 RA liraglutide. RESEARCH DESIGN AND METHODS: In a double-blind placebo-controlled trial, we randomized 102 persons with type 2 diabetes to liraglutide or placebo for 26 weeks. Fasting blood plasma was collected at baseline and at end-of-treatment. The lipidome was measured using liquid-chromatography-coupled mass-spectrometry as a secondary end point in the study. Treatment response of each lipid was tested with lipid-specific linear mixed-effect models comparing liraglutide with placebo. Bonferroni p<7.1e-03 was employed. The independence of the findings from clinical covariates was evaluated with adjustment for body mass index, HbA1c, fasting status, lipid-lowering treatment and change in lipid-lowering treatment during the trial. RESULTS: In total, 260 lipids were identified covering 11 lipid families. We observed significant decreases following liraglutide treatment compared with placebo in 21 lipids (p<7.1e-03) from the following lipid families: ceramides, hexocyl-ceramides, phosphatidylcholines, phosphatidylethanolamines and triglycerides. We confirmed these findings in adjusted models (p≤0.01). In the liraglutide-treated group, the individual lipids were reduced in the range of 14%-61% from baseline level, compared with 19% decrease to 27% increase from baseline level in the placebo group. CONCLUSIONS: Compared with placebo, liraglutide treatment led to a significant downregulation in ceramides, phospholipids and triglycerides, which all are linked to higher risk of CVD. These findings were independent of relevant clinical covariates. Our findings are hypothesis generating and shed light on the biological mechanisms underlying the cardiovascular benefits observed with GLP-1 RAs in outcome studies, and further strengthen the evidence base for recommending GLP-1 RAs to prevent CVD in type 2 diabetes. TRIAL REGISTRATION NUMBER: NCT03449654.

Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study.

Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic (N = 12,828), metabolomic (N = 2,945), lipidomic (N = 2,593), and proteomic (N = 1,170) data were obtained in plasma. For each data type, each cluster was compared with the other four clusters as the reference. The insulin-resistant cluster showed the most distinct molecular signature, with higher branched-chain amino acid, diacylglycerol, and triacylglycerol levels and aberrant protein levels in plasma were enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher levels of cytokines. The mild diabetes cluster with high HDL showed the most beneficial molecular profile with effects opposite of those seen in the insulin-resistant cluster. This study shows that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease.

Intravital imaging of islet Ca2+ dynamics reveals enhanced ß cell connectivity after bariatric surgery in mice.

Bariatric surgery improves both insulin sensitivity and secretion and can induce diabetes remission. However, the mechanisms and time courses of these changes, particularly the impact on ß cell function, are difficult to monitor directly. In this study, we investigated the effect of Vertical Sleeve Gastrectomy (VSG) on ß cell function in vivo by imaging Ca2+ dynamics in islets engrafted into the anterior eye chamber. Mirroring its clinical utility, VSG in mice results in significantly improved glucose tolerance, and enhanced insulin secretion. We reveal that these benefits are underpinned by augmented ß cell function and coordinated activity across the islet. These effects involve changes in circulating GLP-1 levels which may act both directly and indirectly on the ß cell, in the latter case through changes in body weight. Thus, bariatric surgery leads to time-dependent increases in ß cell function and intra-islet connectivity which are likely to contribute to diabetes remission.

Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study.

AIMS/HYPOTHESIS: Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes. In the current study we replicate and cross-validate these type 2 diabetes clusters in three large cohorts using variables readily measured in the clinic. METHODS: In three independent cohorts, in total 15,940 individuals were clustered based on age, BMI, HbA1c, random or fasting C-peptide, and HDL-cholesterol. Clusters were cross-validated against the original clusters based on HOMA measures. In addition, between cohorts, clusters were cross-validated by re-assigning people based on each cohort's cluster centres. Finally, we compared the time to insulin requirement for each cluster. RESULTS: Five distinct type 2 diabetes clusters were identified and mapped back to the original four All New Diabetics in Scania (ANDIS) clusters. Using C-peptide and HDL-cholesterol instead of HOMA2-B and HOMA2-IR, three of the clusters mapped with high sensitivity (80.6-90.7%) to the previously identified severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD) and mild obesity-related diabetes (MOD) clusters. The previously described ANDIS mild age-related diabetes (MARD) cluster could be mapped to the two milder groups in our study: one characterised by high HDL-cholesterol (mild diabetes with high HDL-cholesterol [MDH] cluster), and the other not having any extreme characteristic (mild diabetes [MD]). When these two milder groups were combined, they mapped well to the previously labelled MARD cluster (sensitivity 79.1%). In the cross-validation between cohorts, particularly the SIDD and MDH clusters cross-validated well, with sensitivities ranging from 73.3% to 97.1%. SIRD and MD showed a lower sensitivity, ranging from 36.1% to 92.3%, where individuals shifted from SIRD to MD and vice versa. People belonging to the SIDD cluster showed the fastest progression towards insulin requirement, while the MDH cluster showed the slowest progression. CONCLUSIONS/INTERPRETATION: Clusters based on C-peptide instead of HOMA2 measures resemble those based on HOMA2 measures, especially for SIDD, SIRD and MOD. By adding HDL-cholesterol, the MARD cluster based upon HOMA2 measures resulted in the current clustering into two clusters, with one cluster having high HDL levels. Cross-validation between cohorts showed generally a good resemblance between cohorts. Together, our results show that the clustering based on clinical variables readily measured in the clinic (age, HbA1c, HDL-cholesterol, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts. Adding HDL-cholesterol to the clustering resulted in the identification of a cluster with very slow glycaemic deterioration.

Integrated lipidomics and proteomics network analysis highlights lipid and immunity pathways associated with Alzheimer's disease.

BACKGROUND: There is an urgent need to understand the pathways and processes underlying Alzheimer's disease (AD) for early diagnosis and development of effective treatments. This study was aimed to investigate Alzheimer's dementia using an unsupervised lipid, protein and gene multi-omics integrative approach. METHODS: A lipidomics dataset comprising 185 AD patients, 40 mild cognitive impairment (MCI) individuals and 185 controls, and two proteomics datasets (295 AD, 159 MCI and 197 controls) were used for weighted gene co-expression network analyses (WGCNA). Correlations of modules created within each modality with clinical AD diagnosis, brain atrophy measures and disease progression, as well as their correlations with each other, were analyzed. Gene ontology enrichment analysis was employed to examine the biological processes and molecular and cellular functions of protein modules associated with AD phenotypes. Lipid species were annotated in the lipid modules associated with AD phenotypes. The associations between established AD risk loci and the lipid/protein modules that showed high correlation with AD phenotypes were also explored. RESULTS: Five of the 20 identified lipid modules and five of the 17 identified protein modules were correlated with clinical AD diagnosis, brain atrophy measures and disease progression. The lipid modules comprising phospholipids, triglycerides, sphingolipids and cholesterol esters were correlated with AD risk loci involved in immune response and lipid metabolism. The five protein modules involved in positive regulation of cytokine production, neutrophil-mediated immunity, and humoral immune responses were correlated with AD risk loci involved in immune and complement systems and in lipid metabolism (the APOE ε4 genotype). CONCLUSIONS: Modules of tightly regulated lipids and proteins, drivers in lipid homeostasis and innate immunity, are strongly associated with AD phenotypes.