Circulating metabolomic markers in association with overall burden of microvascular complications in type 1 diabetes

INTRODUCTION

Diabetic retinopathy (DR), diabetic kidney disease (DKD) and distal symmetric polyneuropathy (DSPN) share common pathophysiology and pose an additive risk of early mortality.

RESEARCH DESIGN AND METHODS

In adults with type 1 diabetes, 49 metabolites previously associated with either DR or DKD were assessed in relation to presence of DSPN. Metabolites overlapping in significance with presence of all three complications were assessed in relation to microvascular burden severity (additive number of complications-ie, presence of DKD±DR±DSPN) using linear regression models. Subsequently, the same metabolites were assessed with progression to endpoints: soft microvascular events (progression in albuminuria grade, ≥30% estimated glomerular filtration rate (eGFR) decline, or any progression in DR grade), hard microvascular events (progression to proliferative DR, chronic kidney failure, or ≥40% eGFR decline), and hard microvascular or macrovascular events (hard microvascular events, cardiovascular events (myocardial infarction, stroke, or arterial interventions), or cardiovascular mortality), using Cox models. All models were adjusted for sex, baseline age, diabetes duration, systolic blood pressure, HbA1c, body mass index, total cholesterol, smoking, and statin treatment.

RESULTS

The full cohort investigated consisted of 487 participants. Mean (SD) follow-up was 4.8 (2.9, 5.7) years. Baseline biothesiometry was available in 202 participants, comprising the cross-sectional cohort. Eight metabolites were significantly associated with presence of DR, DKD, and DSPN, and six with additive microvascular burden severity. In the full cohort longitudinal analysis, higher levels of 3,4-dihydroxybutanoic acid (DHBA), 2,4-DHBA, ribonic acid, glycine, and ribitol were associated with development of events in both crude and adjusted models. Adding 3,4-DHBA, ribonic acid, and glycine to a traditional risk factor model improved the discrimination of hard microvascular events.

CONCLUSIONS

While prospective studies directly assessing the predictive ability of these markers are needed, our results strengthen the role of clinical metabolomics in relation to risk assessment of diabetic complications in chronic type 1 diabetes.

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.

Metabolic effect of adrenaline infusion in people with type 1 diabetes and healthy individuals

AIMS/HYPOTHESIS

As a result of early loss of the glucagon response, adrenaline is the primary counter-regulatory hormone in type 1 diabetes. Diminished adrenaline responses to hypoglycaemia due to counter-regulatory failure are common in type 1 diabetes, and are probably induced by exposure to recurrent hypoglycaemia, however, the metabolic effects of adrenaline have received less research attention, and also there is conflicting evidence regarding adrenaline sensitivity in type 1 diabetes. Thus, we aimed to investigate the metabolic response to adrenaline and explore whether it is modified by prior exposure to hypoglycaemia.

METHODS

Eighteen participants with type 1 diabetes and nine healthy participants underwent a three-step ascending adrenaline infusion during a hyperinsulinaemic-euglycaemic clamp. Continuous glucose monitoring data obtained during the week before the study day were used to assess the extent of hypoglycaemia exposure.

RESULTS

While glucose responses during the clamp were similar between people with type 1 diabetes and healthy participants, plasma concentrations of NEFAs and glycerol only increased in the group with type 1 diabetes (p<0.001). Metabolomics revealed an increase in the most common NEFAs (p<0.01). Other metabolic responses were generally similar between participants with type 1 diabetes and healthy participants. Exposure to hypoglycaemia was negatively associated with the NEFA response; however, this was not statistically significant.

CONCLUSIONS/INTERPRETATION

In conclusion, individuals with type 1 diabetes respond with increased lipolysis to adrenaline compared with healthy participants by mobilising the abundant NEFAs in plasma, whereas other metabolic responses were similar. This may suggest that the metabolic sensitivity to adrenaline is altered in a pathway-specific manner in type 1 diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05095259.

Extracellular vesicles released by microglia and macrophages carry endocannabinoids which foster oligodendrocyte differentiation

Introduction

Microglia and macrophages can influence the evolution of myelin lesions through the production of extracellular vesicles (EVs). While microglial EVs promote in vitro differentiation of oligodendrocyte precursor cells (OPCs), whether EVs derived from macrophages aid or limit OPC maturation is unknown.

Methods

Immunofluorescence analysis for the myelin protein MBP was employed to evaluate the impact of EVs from primary rat macrophages on cultured OPC differentiation. Raman spectroscopy and liquid chromatography-mass spectrometry was used to define the promyelinating lipid components of myelin EVs obtained in vitro and isolated from human plasma.

Results and discussion

Here we show that macrophage-derived EVs do not promote OPC differentiation, and those released from macrophages polarized towards an inflammatory state inhibit OPC maturation. However, their lipid cargo promotes OPC maturation in a similar manner to microglial EVs. We identify the promyelinating endocannabinoids anandamide and 2-arachidonoylglycerol in EVs released by both macrophages and microglia in vitro and circulating in human plasma. Analysis of OPC differentiation in the presence of the endocannabinoid receptor antagonists SR141716A and AM630 reveals a key role of vesicular endocannabinoids in OPC maturation. From this study, EV-associated endocannabinoids emerge as important mediators in microglia/macrophage-oligodendrocyte crosstalk, which may be exploited to enhance myelin repair.

Binge drinking episode causes acute, specific alterations in systemic and hepatic inflammation-related markers

BACKGROUND

Frequent binge drinking is a known contributor to alcohol-related harm, but its impact on systemic and hepatic inflammation is not fully understood. We hypothesize that changes in immune markers play a central role in adverse effects of acute alcohol intake, especially in patients with early liver disease.

AIM

To investigate the effects of acute alcohol intoxication on inflammation-related markers in hepatic and systemic venous plasma in people with alcohol-related liver disease (ArLD), non-alcoholic fatty liver disease (NAFLD) and healthy controls.

METHODS

Thirty-eight participants (13 with ArLD, 15 with NAFLD and 10 healthy controls) received 2.5 mL of 40% ethanol per kg body weight via a nasogastric tube. Seventy-two inflammation-related markers were quantified in plasma from hepatic and systemic venous blood, at baseline, 60 and 180 min after intervention.

RESULTS

Alcohol intervention altered the levels of 31 of 72 and 14 of 72 markers in the systemic and hepatic circulation. All changes observed in the hepatic circulation were also identified in the systemic circulation after 180 min. Only FGF21 and IL6 were increased after alcohol intervention, while the remaining 29 markers decreased. Differences in response to acute alcohol between the groups were observed for 8 markers, and FGF21 response was blunted in individuals with steatosis.

CONCLUSION

Acute alcohol intoxication induced changes in multiple inflammation-related markers, implicated in alcohol metabolism and hepatocellular damage. Differences identified between marker response to binge drinking in ArLD, NAFLD and healthy controls may provide important clues to disease mechanisms and potential targets for treatment.

CLINICAL TRIAL NUMBER

NCT03018990.

Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning

BACKGROUND

Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences.

METHODS

We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects.

RESULTS

Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers.

CONCLUSIONS

These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine.

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.

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.

A combined DHA-rich fish oil and cocoa flavanols intervention does not improve cognition or brain structure in older adults with memory complaints: results from the CANN randomized, controlled parallel-design study

BACKGROUND

There is evidence that both omega-3 long-chain polyunsaturated fatty acids (PUFAs) (eicosapentaenoic acid [EPA] and docosahexaenoic acid [DHA]) and cocoa flavanols can improve cognitive performance in both healthy individuals and in those with memory complaints. However, their combined effect is unknown.

OBJECTIVES

To investigate the combined effect of EPA/DHA and cocoa flavanols (OM3FLAV) on cognitive performance and brain structures in older adults with memory complaints.

METHODS

A randomized placebo-controlled trial of DHA-rich fish oil (providing 1.1 g/d DHA and 0.4 g/d EPA) and a flavanol-rich dark chocolate (providing 500 mg/d flavan-3-ols) was conducted in 259 older adults with either subjective cognitive impairment or mild cognitive impairment. Participants underwent assessment at baseline, 3 mo, and 12 mo. The primary outcome was the number of false-positives on a picture recognition task from the Cognitive Drug Research computerized assessment battery. Secondary outcomes included other cognition and mood outcomes, plasma lipids, brain-derived neurotrophic factor (BDNF), and glucose levels. A subset of 110 participants underwent structural neuroimaging at baseline and at 12 mo.

RESULTS

197 participants completed the study. The combined intervention had no significant effect on any cognitive outcomes, with the exception of reaction time variability (P = 0.007), alertness (P < 0.001), and executive function (P < 0.001), with a decline in function observed in the OM3FLAV group (118.6 [SD 25.3] at baseline versus 113.3 [SD 25.4] at 12 mo for executive function) relative to the control, and an associated decrease in cortical volume (P = 0.039). Compared with the control group, OM3FLAV increased plasma HDL, total cholesterol ratio (P < 0.001), and glucose (P = 0.008) and reduced TG concentrations (P < 0.001) by 3 mo, which were sustained to 12 mo, with no effect on BDNF. Changes in plasma EPA and DHA and urinary flavonoid metabolite concentrations confirmed compliance to the intervention.

CONCLUSIONS

These results suggest that cosupplementation with ω-3 PUFAs and cocoa flavanols for 12 mo does not improve cognitive outcomes in those with cognitive impairment. This trial was registered at clinicaltrials.gov as NCT02525198.

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.

Decreased branched-chain amino acids and elevated fatty acids during antecedent hypoglycemia in type 1 diabetes

INTRODUCTION

Hypoglycemia is a major limiting factor in achieving recommended glycemic targets for people with type 1 diabetes. Exposure to recurrent hypoglycemia results in blunted hormonal counter-regulatory and symptomatic responses to hypoglycemia. Limited data on metabolic adaptation to recurrent hypoglycemia are available. This study examined the acute metabolic responses to hypoglycemia and the effect of antecedent hypoglycemia on these responses in type 1 diabetes.

RESEARCH DESIGN AND METHODS

Twenty-one outpatients with type 1 diabetes with normal or impaired awareness of hypoglycemia participated in a study assessing the response to hypoglycemia on 2 consecutive days by a hyperinsulinemic glucose clamp. Participants underwent a period of normoglycemia and a period of hypoglycemia during the hyperinsulinemic glucose clamp. Plasma samples were taken during normoglycemia and at the beginning and the end of the hypoglycemic period. Metabolomic analysis of the plasma samples was conducted using comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry.

RESULTS

In total, 68 metabolites were studied. On day 1, concentrations of the branched-chain amino acids, leucine (p=3.8×10-3) and isoleucine (p=2.2×10-3), decreased during hypoglycemia. On day 2, during hypoglycemia, five amino acids (including leucine and isoleucine) significantly decreased, and two fatty acids (tetradecanoic and oleic acids) significantly increased (p<0.05). Although more metabolites responded to hypoglycemia on day 2, the responses of the single metabolites were not statistically significant between the 2 days.

CONCLUSIONS

In individuals with type 1 diabetes, one episode of hypoglycemia decreases leucine and isoleucine concentrations. Antecedent hypoglycemia results in the decrement of five amino acids and increases the concentrations of two fatty acids, suggesting an alteration between the two hypoglycemic episodes, which could indicate a possible adaptation. However, more studies are needed to gain a comprehensive understanding of the consequences of these alterations.

TRIAL REGISTRATION NUMBER

NCT01337362.

Circulating Metabolomic and Lipidomic Signatures Identify a Type 2 Diabetes Risk Profile in Low-Birth-Weight Men with Non-Alcoholic Fatty Liver Disease

The extent to which increased liver fat content influences differences in circulating metabolites and/or lipids between low-birth-weight (LBW) individuals, at increased risk of type 2 diabetes (T2D), and normal-birth-weight (NBW) controls is unknown. The objective of the study was to perform untargeted serum metabolomics and lipidomics analyses in 26 healthy, non-obese early-middle-aged LBW men, including five men with screen-detected and previously unrecognized non-alcoholic fatty liver disease (NAFLD), compared with 22 age- and BMI-matched NBW men (controls). While four metabolites (out of 65) and fifteen lipids (out of 279) differentiated the 26 LBW men from the 22 NBW controls (p ≤ 0.05), subgroup analyses of the LBW men with and without NAFLD revealed more pronounced differences, with 11 metabolites and 56 lipids differentiating (p ≤ 0.05) the groups. The differences in the LBW men with NAFLD included increased levels of ornithine and tyrosine (PFDR ≤ 0.1), as well as of triglycerides and phosphatidylcholines with shorter carbon-chain lengths and fewer double bonds. Pathway and network analyses demonstrated downregulation of transfer RNA (tRNA) charging, altered urea cycling, insulin resistance, and an increased risk of T2D in the LBW men with NAFLD. Our findings highlight the importance of increased liver fat in the pathogenesis of T2D in LBW individuals.

Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer's disease

BACKGROUND

Identifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46-the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer's disease (AD).

METHODS

Following quality control, levels of 1019 metabolites-detected with liquid chromatography-mass spectrometry-were available for 1740 participants at age 60-64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69-71). Regression analyses tested relationships between metabolite measures-modules and hub metabolites-and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant (p_FDR < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated (p_FDR < 0.05) with an imaging outcome (N = 1638).

RESULTS

In the fully adjusted model, three lipid modules were associated with a brain volume measure (p_FDR < 0.05): one enriched in sphingolipids (hippocampal volume: ß = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß =  - 0.072, 95%CI = [- 0.12, - 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß =  - 0.066, 95% CI = [- 0.11, - 0.020]). Twenty-two hub metabolites were associated (p_FDR < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction.

CONCLUSIONS

Our findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality.

Predicting AT(N) pathologies in Alzheimer’s disease from blood-based proteomic data using neural networks

Background and objective

Blood-based biomarkers represent a promising approach to help identify early Alzheimer’s disease (AD). Previous research has applied traditional machine learning (ML) to analyze plasma omics data and search for potential biomarkers, but the most modern ML methods based on deep learning has however been scarcely explored. In the current study, we aim to harness the power of state-of-the-art deep learning neural networks (NNs) to identify plasma proteins that predict amyloid, tau, and neurodegeneration (AT[N]) pathologies in AD.

Methods

We measured 3,635 proteins using SOMAscan in 881 participants from the European Medical Information Framework for AD Multimodal Biomarker Discovery study (EMIF-AD MBD). Participants underwent measurements of brain amyloid β (Aβ) burden, phosphorylated tau (p-tau) burden, and total tau (t-tau) burden to determine their AT(N) statuses. We ranked proteins by their association with Aβ, p-tau, t-tau, and AT(N), and fed the top 100 proteins along with age and apolipoprotein E (APOE) status into NN classifiers as input features to predict these four outcomes relevant to AD. We compared NN performance of using proteins, age, and APOE genotype with performance of using age and APOE status alone to identify protein panels that optimally improved the prediction over these main risk factors. Proteins that improved the prediction for each outcome were aggregated and nominated for pathway enrichment and protein–protein interaction enrichment analysis.

Results

Age and APOE alone predicted Aβ, p-tau, t-tau, and AT(N) burden with area under the curve (AUC) scores of 0.748, 0.662, 0.710, and 0.795. The addition of proteins significantly improved AUCs to 0.782, 0.674, 0.734, and 0.831, respectively. The identified proteins were enriched in five clusters of AD-associated pathways including human immunodeficiency virus 1 infection, p53 signaling pathway, and phosphoinositide-3-kinase–protein kinase B/Akt signaling pathway.

Conclusion

Combined with age and APOE genotype, the proteins identified have the potential to serve as blood-based biomarkers for AD and await validation in future studies. While the NNs did not achieve better scores than the support vector machine model used in our previous study, their performances were likely limited by small sample size.

Circulating metabolites and molecular lipid species are associated with future cardiovascular morbidity and mortality in type 1 diabetes

Background

Cardiovascular disease remains the leading cause of mortality in individuals with diabetes and improved understanding of its pathophysiology is needed. We investigated the association of a large panel of metabolites and molecular lipid species with future cardiovascular events in type 1 diabetes.

Methods

The study included 669 individuals with type 1 diabetes. Non-targeted serum metabolomics and lipidomics analyses were performed using mass spectrometry. Data on cardiovascular events (cardiovascular mortality, coronary artery disease, stroke, and peripheral arterial interventions) were obtained from Danish Health registries and analyzed by Cox hazards models. Metabolites and molecular lipid species were analyzed in univariate models adjusted for false discovery rate (FDR). Metabolites and molecular lipid species fulfilling a p_FDR < 0.05 were subsequently analyzed in adjusted models including age, sex, hemoglobin A_1c, mean arterial pressure, smoking, body mass index, low-density lipoprotein cholesterol, estimated glomerular filtration rate, urinary albumin excretion rate and previous cardiovascular disease. Analyses of molecular lipid species were further adjusted for triglycerides and statin use.

Results

Of the included participants, 55% were male and mean age was 55 ± 13 years. Higher 4-hydroxyphenylacetic acid (HR 1.35, CI [1.01–1.80], p = 0.04) and lower threonine (HR 0.81, CI [0.67–0.98] p = 0.03) were associated with development of cardiovascular events (n = 95). In lipidomics analysis, higher levels of three different species, diacyl-phosphatidylcholines (PC)(36:2) (HR 0.82, CI [0.70–0.98], p = 0.02), alkyl-acyl-phosphatidylcholines (PC-O)(34:2) (HR 0.76, CI [0.59–0.98], p = 0.03) and (PC-O)(34:3) (HR 0.75, CI [0.58–0.97], p = 0.03), correlated with lower risk of cardiovascular events, whereas higher sphingomyelin (SM)(34:1) (HR 1.32, CI [1.04–1.68], p = 0.02), was associated with an increased risk.

Conclusions

Circulating metabolites and molecular lipid species were associated with future cardiovascular events in type 1 diabetes. While the causal effect of these biomolecules on the cardiovascular system remains unknown, our findings support that omics-based technologies, although still in an early phase, may have the potential to unravel new pathways and biomarkers in the field of cardiovascular disease in type 1 diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01568-8.

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

Mitochondrial glucose metabolism is essential for stimulated insulin release from pancreatic β-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 β-cell-selective, adult-restricted deletion knock-out (dKO) of the mitofusin genes Mfn1 and Mfn2 (βMfn1/2 dKO). βMfn1/2-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 βMfn1/2-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 β-cell to maintain normal glucose, but not incretin, sensing. These findings broaden our understanding of the roles of mitofusins in β-cells, the potential contributions of altered mitochondrial dynamics to diabetes development, and the impact of incretins on this process.

Precision diagnostic approach to predict 5-year risk for microvascular complications in type 1 diabetes

Background

Individuals with long standing diabetes duration can experience damage to small microvascular blood vessels leading to diabetes complications (DCs) and increased mortality. Precision diagnostic tailors a diagnosis to an individual by using biomedical information. Blood small molecule profiling coupled with machine learning (ML) can facilitate the goals of precision diagnostics, including earlier diagnosis and individualized risk scoring.

Methods

Using data in a cohort of 537 adults with type 1 diabetes (T1D) we predicted five-year progression to DCs. Prediction models were computed first with clinical risk factors at baseline and then with clinical risk factors and blood-derived molecular data at baseline. Progression of diabetic kidney disease and diabetic retinopathy were predicted in two complication-specific models.

Findings

The model predicts the progression to diabetic kidney disease with accuracy: 0.96 ± 0.25 and 0.96 ± 0.06 area under curve, AUC, with clinical measurements and with small molecule predictors respectively and highlighted main predictors to be albuminuria, glomerular filtration rate, retinopathy status at baseline, sugar derivatives and ketones. For diabetic retinopathy, AUC 0.75 ± 0.14 and 0.79 ± 0.16 with clinical measurements and with small molecule predictors respectively and highlighted key predictors, albuminuria, glomerular filtration rate and retinopathy status at baseline. Individual risk scores were built to visualize results.

Interpretation

With further validation ML tools could facilitate the implementation of precision diagnosis in the clinic. It is envisaged that patients could be screened for complications, before these occur, thus preserving healthy life-years for persons with diabetes.

Funding

This study has been financially supported by Novo Nordisk Foundation grant NNF14OC0013659.

Rare variants in IFFO1, DTNB, NLRC3 and SLC22A10 associate with Alzheimer's disease CSF profile of neuronal injury and inflammation

Alzheimer's disease (AD) biomarkers represent several neurodegenerative processes, such as synaptic dysfunction, neuronal inflammation and injury, as well as amyloid pathology. We performed an exome-wide rare variant analysis of six AD biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and Neurogranin) to discover genes associated with these markers. Genetic and biomarker information was available for 480 participants from two studies: EMIF-AD and ADNI. We applied a principal component (PC) analysis to derive biomarkers combinations, which represent statistically independent biological processes. We then tested whether rare variants in 9576 protein-coding genes associate with these PCs using a Meta-SKAT test. We also tested whether the PCs are intermediary to gene effects on AD symptoms with a SMUT test. One PC loaded on NfL and YKL-40, indicators of neuronal injury and inflammation. Four genes were associated with this PC: IFFO1, DTNB, NLRC3, and SLC22A10. Mediation tests suggest, that these genes also affect dementia symptoms via inflammation/injury. We also observed an association between a PC loading on Neurogranin, a marker for synaptic functioning, with GABBR2 and CASZ1, but no mediation effects. The results suggest that rare variants in IFFO1, DTNB, NLRC3, and SLC22A10 heighten susceptibility to neuronal injury and inflammation, potentially by altering cytoskeleton structure and immune activity disinhibition, resulting in an elevated dementia risk. GABBR2 and CASZ1 were associated with synaptic functioning, but mediation analyses suggest that the effect of these two genes on synaptic functioning is not consequential for AD development.

Disentangling Independent and Mediated Causal Relationships Between Blood Metabolites, Cognitive Factors, and Alzheimer's Disease

Background

Education and cognition demonstrate consistent inverse associations with Alzheimer's disease (AD). The biological underpinnings, however, remain unclear. Blood metabolites reflect the end point of biological processes and are accessible and malleable. Identifying metabolites with etiological relevance to AD and disentangling how these relate to cognitive factors along the AD causal pathway could, therefore, offer unique insights into underlying causal mechanisms.

Methods

Using data from the largest metabolomics genome-wide association study (N ≈ 24,925) and three independent AD cohorts (N = 4725), cross-trait polygenic scores were generated and meta-analyzed. Metabolites genetically associated with AD were taken forward for causal analyses. Bidirectional two-sample Mendelian randomization interrogated univariable causal relationships between 1) metabolites and AD; 2) education and cognition; 3) metabolites, education, and cognition; and 4) education, cognition, and AD. Mediating relationships were computed using multivariable Mendelian randomization.

Results

Thirty-four metabolites were genetically associated with AD at p < .05. Of these, glutamine and free cholesterol in extra-large high-density lipoproteins demonstrated a protective causal effect (glutamine: 95% confidence interval [CI], 0.70 to 0.92; free cholesterol in extra-large high-density lipoproteins: 95% CI, 0.75 to 0.92). An AD-protective effect was also observed for education (95% CI, 0.61 to 0.85) and cognition (95% CI, 0.60 to 0.89), with bidirectional mediation evident. Cognition as a mediator of the education-AD relationship was stronger than vice versa, however. No evidence of mediation via any metabolite was found.

Conclusions

Glutamine and free cholesterol in extra-large high-density lipoproteins show protective causal effects on AD. Education and cognition also demonstrate protection, though education's effect is almost entirely mediated by cognition. These insights provide key pieces of the AD causal puzzle, important for informing future multimodal work and progressing toward effective intervention strategies.

Genome-Wide Association Study of Alzheimer's Disease Brain Imaging Biomarkers and Neuropsychological Phenotypes in the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Dataset

Alzheimer's disease (AD) is the most frequent neurodegenerative disease with an increasing prevalence in industrialized, aging populations. AD susceptibility has an established genetic basis which has been the focus of a large number of genome-wide association studies (GWAS) published over the last decade. Most of these GWAS used dichotomized clinical diagnostic status, i.e., case vs. control classification, as outcome phenotypes, without the use of biomarkers. An alternative and potentially more powerful study design is afforded by using quantitative AD-related phenotypes as GWAS outcome traits, an analysis paradigm that we followed in this work. Specifically, we utilized genotype and phenotype data from n = 931 individuals collected under the auspices of the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study to perform a total of 19 separate GWAS analyses. As outcomes we used five magnetic resonance imaging (MRI) traits and seven cognitive performance traits. For the latter, longitudinal data from at least two timepoints were available in addition to cross-sectional assessments at baseline. Our GWAS analyses revealed several genome-wide significant associations for the neuropsychological performance measures, in particular those assayed longitudinally. Among the most noteworthy signals were associations in or near EHBP1 (EH domain binding protein 1; on chromosome 2p15) and CEP112 (centrosomal protein 112; 17q24.1) with delayed recall as well as SMOC2 (SPARC related modular calcium binding 2; 6p27) with immediate recall in a memory performance test. On the X chromosome, which is often excluded in other GWAS, we identified a genome-wide significant signal near IL1RAPL1 (interleukin 1 receptor accessory protein like 1; Xp21.3). While polygenic score (PGS) analyses showed the expected strong associations with SNPs highlighted in relevant previous GWAS on hippocampal volume and cognitive function, they did not show noteworthy associations with recent AD risk GWAS findings. In summary, our study highlights the power of using quantitative endophenotypes as outcome traits in AD-related GWAS analyses and nominates several new loci not previously implicated in cognitive decline.

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.

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.

Multiomics signatures of type 1 diabetes with and without albuminuria

AIMS/HYPOTHESIS

To identify novel pathophysiological signatures of longstanding type 1 diabetes (T1D) with and without albuminuria we investigated the gut microbiome and blood metabolome in individuals with T1D and healthy controls (HC). We also mapped the functional underpinnings of the microbiome in relation to its metabolic role.

METHODS

One hundred and sixty-one individuals with T1D and 50 HC were recruited at the Steno Diabetes Center Copenhagen, Denmark. T1D cases were stratified based on levels of albuminuria into normoalbuminuria, moderate and severely increased albuminuria. Shotgun sequencing of bacterial and viral microbiome in stool samples and circulating metabolites and lipids profiling using mass spectroscopy in plasma of all participants were performed. Functional mapping of microbiome into Gut Metabolic Modules (GMMs) was done using EggNog and KEGG databases. Multiomics integration was performed using MOFA tool.

RESULTS

Measures of the gut bacterial beta diversity differed significantly between T1D and HC, either with moderately or severely increased albuminuria. Taxonomic analyses of the bacterial microbiota identified 51 species that differed in absolute abundance between T1D and HC (17 higher, 34 lower). Stratified on levels of albuminuria, 10 species were differentially abundant for the moderately increased albuminuria group, 63 for the severely increased albuminuria group while 25 were common and differentially abundant both for moderately and severely increased albuminuria groups, when compared to HC. Functional characterization of the bacteriome identified 23 differentially enriched GMMs between T1D and HC, mostly involved in sugar and amino acid metabolism. No differences in relation to albuminuria stratification was observed. Twenty-five phages were differentially abundant between T1D and HC groups. Six of these varied with albuminuria status. Plasma metabolomics indicated differences in the steroidogenesis and sugar metabolism and circulating sphingolipids in T1D individuals. We identified association between sphingolipid levels and Bacteroides sp. abundances. MOFA revealed reduced interactions between gut microbiome and plasma metabolome profiles albeit polar metabolite, lipids and bacteriome compositions contributed to the variance in albuminuria levels among T1D individuals.

CONCLUSIONS

Individuals with T1D and progressive kidney disease stratified on levels of albuminuria show distinct signatures in their gut microbiome and blood metabolome.

Cardiovascular Autonomic Neuropathy in Type 1 Diabetes Is Associated With Disturbances in TCA, Lipid, and Glucose Metabolism

INTRODUCTION

Diabetic cardiovascular autonomic neuropathy (CAN) is associated with increased mortality and morbidity. To explore metabolic mechanisms associated with CAN we investigated associations between serum metabolites and CAN in persons with type 1 diabetes (T1D).

MATERIALS AND METHODS

Cardiovascular reflex tests (CARTs) (heart rate response to: deep breathing; lying-to-standing test; and the Valsalva maneuver) were used to diagnose CAN in 302 persons with T1D. More than one pathological CARTs defined the CAN diagnosis. Serum metabolomics and lipidomic profiles were analyzed with two complementary non-targeted mass-spectrometry methods. Cross-sectional associations between metabolites and CAN were assessed by linear regression models adjusted for relevant confounders.

RESULTS

Participants were median (IQR) aged 55(49, 63) years, 48% males with diabetes duration 39(32, 47) years, HbA_1c 63(55,69) mmol/mol and 34% had CAN. A total of 75 metabolites and 106 lipids were analyzed. In crude models, the CAN diagnosis was associated with higher levels of hydroxy fatty acids (2,4- and 3,4-dihydroxybutanoic acids, 4-deoxytetronic acid), creatinine, sugar derivates (ribitol, ribonic acid, myo-inositol), citric acid, glycerol, phenols, phosphatidylcholines and lower levels of free fatty acids and the amino acid methionine (p<0.05). Upon adjustment, positive associations with the CAN diagnoses were retained for hydroxy fatty acids, tricarboxylic acid (TCA) cycle-based sugar derivates, citric acid, and phenols (P<0.05).

CONCLUSION

Metabolic pathways, including the TCA cycle, hydroxy fatty acids, phosphatidylcholines and sugar derivatives are associated with the CAN diagnosis in T1D. These pathway may be part of the pathogeneses leading to CAN and may be modifiable risk factors for the complication.

Metabolic correlates of late midlife cognitive outcomes: findings from the 1946 British Birth Cohort

Investigating associations between metabolites and late midlife cognitive function could reveal potential markers and mechanisms relevant to early dementia. Here, we systematically explored the metabolic correlates of cognitive outcomes measured across the seventh decade of life, while untangling influencing life course factors. Using levels of 1019 metabolites profiled by liquid chromatography-mass spectrometry (age 60-64), we evaluated relationships between metabolites and cognitive outcomes in the British 1946 Birth Cohort (N = 1740). We additionally conducted pathway and network analyses to allow for greater insight into potential mechanisms, and sequentially adjusted for life course factors across four models, including sex and blood collection (Model 1), Model 1 + body mass index and lipid medication (Model 2), Model 2 + social factors and childhood cognition (Model 3) and Model 3 + lifestyle influences (Model 4). After adjusting for multiple tests, 155 metabolites, 10 pathways and 5 network modules were associated with cognitive outcomes. Of the 155, 35 metabolites were highly connected in their network module (termed 'hub' metabolites), presenting as promising marker candidates. Notably, we report relationships between a module comprised of acylcarnitines and processing speed which remained robust to life course adjustment, revealing palmitoylcarnitine (C16) as a hub (Model 4: β = -0.10, 95% confidence interval = -0.15 to -0.052, P = 5.99 × 10-5). Most associations were sensitive to adjustment for social factors and childhood cognition; in the final model, four metabolites remained after multiple testing correction, and 80 at P < 0.05. Two modules demonstrated associations that were partly or largely attenuated by life course factors: one enriched in modified nucleosides and amino acids (overall attenuation = 39.2-55.5%), and another in vitamin A and C metabolites (overall attenuation = 68.6-92.6%). Our other findings, including a module enriched in sphingolipid pathways, were entirely explained by life course factors, particularly childhood cognition and education. Using a large birth cohort study with information across the life course, we highlighted potential metabolic mechanisms associated with cognitive function in late midlife, suggesting marker candidates and life course relationships for further study.

Sex-Specific Metabolic Pathways Were Associated with Alzheimer's Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort

BACKGROUND

physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives.

METHODS

We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites' discriminatory performance in AD.

RESULTS

In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046).

CONCLUSIONS

metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.

Prediction of Type 1 Diabetes at Birth: Cord Blood Metabolites vs Genetic Risk Score in the Norwegian Mother, Father, and Child Cohort

BACKGROUND AND AIM

Genetic markers are established as predictive of type 1 diabetes, but unknown early life environment is believed to be involved. Umbilical cord blood may reflect perinatal metabolism and exposures. We studied whether selected polar metabolites in cord blood contribute to prediction of type 1 diabetes.

METHODS

Using a targeted UHPLC-QQQ-MS platform, we quantified 27 low-molecular-weight metabolites (including amino acids, small organic acids, and bile acids) in 166 children, who later developed type 1 diabetes, and 177 random control children in the Norwegian Mother, Father, and Child cohort. We analyzed the data using logistic regression (estimating odds ratios per SD [adjusted odds ratio (aOR)]), area under the receiver operating characteristic curve (AUC), and k-means clustering. Metabolites were compared to a genetic risk score based on 51 established non-HLA single-nucleotide polymorphisms, and a 4-category HLA risk group.

RESULTS

The strongest associations for metabolites were aminoadipic acid (aOR = 1.23; 95% CI, 0.97-1.55), indoxyl sulfate (aOR = 1.15; 95% CI, 0.87-1.51), and tryptophan (aOR = 0.84; 95% CI, 0.65-1.10), with other aORs close to 1.0, and none significantly associated with type 1 diabetes. K-means clustering identified 6 clusters, none of which were associated with type 1 diabetes. Cross-validated AUC showed no predictive value of metabolites (AUC 0.49), whereas the non-HLA genetic risk score AUC was 0.56 and the HLA risk group AUC was 0.78.

CONCLUSIONS

In this large study, we found no support of a predictive role of cord blood concentrations of selected bile acids and other small polar metabolites in the development of type 1 diabetes.

Exploration of Plasma Lipids in Mild Cognitive Impairment due to Alzheimer's Disease

BACKGROUND

Lipids have important structural roles in cell membranes and changes to these membrane lipids may influence β- and γ-secretase activities and thus contribute to Alzheimer's disease (AD) pathology.

OBJECTIVE

To explore baseline plasma lipid profiling in participants with mild cognitive impairment (MCI) with and without AD pathology.

METHODS

We identified 261 plasma lipids using reversed-phase liquid chromatography/mass spectrometry in cerebrospinal fluid amyloid positive (Aβ+) or negative (Aβ-) participants with MCI as compared to controls. Additionally, we analyzed the potential associations of plasma lipid profiles with performance on neuropsychological tests at baseline and after two years.

RESULTS

Sphingomyelin (SM) concentrations, particularly, SM(d43:2), were lower in MCI Aβ+ individuals compared to controls. Further, SM(d43:2) was also nominally reduced in MCI Aβ+ individuals compared to MCI Aβ-. No plasma lipids were associated with performance on primary neuropsychological tests at baseline or between the two time points after correction for multiple testing.

CONCLUSION

Reduced plasma concentrations of SM were associated with AD.

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, HbA_1c, 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.

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, HbA_1c, 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, HbA_1c, 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.

Intravital imaging of islet Ca2+ dynamics reveals enhanced β 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 β cell function, are difficult to monitor directly. In this study, we investigated the effect of Vertical Sleeve Gastrectomy (VSG) on β 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 β 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 β cell, in the latter case through changes in body weight. Thus, bariatric surgery leads to time-dependent increases in β cell function and intra-islet connectivity which are likely to contribute to diabetes remission.

Comprehensive lipidomics reveals phenotypic differences in hepatic lipid turnover in ALD and NAFLD during alcohol intoxication

Background & Aims

In experimental models, alcohol induces acute changes in lipid metabolism that cause hepatocyte lipoapoptosis and inflammation. Here we study human hepatic lipid turnover during controlled alcohol intoxication.

Methods

We studied 39 participants with 3 distinct hepatic phenotypes: alcohol-related liver disease (ALD), non-alcoholic fatty liver disease (NAFLD), and healthy controls. Alcohol was administrated via nasogastric tube over 30 min. Hepatic and systemic venous blood was sampled simultaneously at 3 time points: baseline, 60, and 180 min after alcohol intervention. Liver biopsies were sampled 240 min after alcohol intervention. We used ultra-high performance liquid chromatography mass spectrometry to measure levels of more than 250 lipid species from the blood and liver samples.

Results

After alcohol intervention, the levels of blood free fatty acid (FFA) and lysophosphatidylcholine (LPC) decreased, while triglyceride (TG) increased. FFA was the only lipid class to decrease in NAFLD after alcohol intervention, whereas LPC and FFA decreased and TG increased after intervention in ALD and healthy controls. Fatty acid chain uptake preference in FFAs and LPCs were oleic acid, linoleic acid, arachidonic acid, and docosahexaenoic acid. Hepatic venous blood FFA and LPC levels were lower when compared with systemic venous blood levels throughout the intervention. After alcohol intoxication, liver lipidome in ALD was similar to that in NAFLD.

Conclusions

Alcohol intoxication induces rapid changes in circulating lipids including hepatic turnaround from FFA and LPC, potentially leading to lipoapoptosis and steatohepatitis. TG clearance was suppressed in NAFLD, possibly explaining why alcohol and NAFLD are synergistic risk factors for disease progression. These effects may be central to the pathogenesis of ALD.

Clinical Trials Registration

The study is registered at Clinicaltrials.gov (NCT03018990).

Lay summary

We report that alcohol induces hepatic extraction of free unsaturated fatty acids and lysophosphatidylcholines, hepatotoxic lipids which have not been previously associated with alcohol-induced liver injury. We also found that individuals with non-alcoholic fatty liver disease have reduced lipid turnover during alcohol intoxication when compared with people with alcohol-related fatty liver disease. This may explain why alcohol is particularly more harmful in people with non-alcoholic fatty liver and why elevated BMI and alcohol have a synergistic effect on the risk of liver-related death.

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Alcohol intoxication induces rapid changes in the profile of circulating lipids.

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Alcohol has a profound effect on monosaturated fatty acids.

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Triglyceride clearance is suppressed in NAFLD during alcohol intoxication.

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Hepatic lipid turnover differentiates ALD and NAFLD during alcohol intoxication.

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A suppressed metabolic response may explain why alcohol is particularly harmful in NAFLD.

Plasma Proteomic Biomarkers Relating to Alzheimer's Disease: A Meta-Analysis Based on Our Own Studies

Background and Objective: Plasma biomarkers for the diagnosis and stratification of Alzheimer's disease (AD) are intensively sought. However, no plasma markers are well established so far for AD diagnosis. Our group has identified and validated various blood-based proteomic biomarkers relating to AD pathology in multiple cohorts. The study aims to conduct a meta-analysis based on our own studies to systematically assess the diagnostic performance of our previously identified blood biomarkers. Methods: To do this, we included seven studies that our group has conducted during the last decade. These studies used either Luminex xMAP or ELISA to measure proteomic biomarkers. As proteins measured in these studies differed, we selected protein based on the criteria that it must be measured in at least four studies. We then examined biomarker performance using random-effect meta-analyses based on the mean difference between biomarker concentrations in AD and controls (CTL), AD and mild cognitive impairment (MCI), MCI, and CTL as well as MCI converted to dementia (MCIc) and non-converted (MCInc) individuals. Results: An overall of 2,879 subjects were retrieved for meta-analysis including 1,053 CTL, 895 MCI, 882 AD, and 49 frontotemporal dementia (FTD) patients. Six proteins were measured in at least four studies and were chosen for meta-analyses for AD diagnosis. Of them, three proteins had significant difference between AD and controls, among which alpha-2-macroglobulin (A2M) and ficolin-2 (FCN2) increased in AD while fibrinogen gamma chain (FGG) decreased in AD compared to CTL. Furthermore, FGG significantly increased in FTD compared to AD. None of the proteins passed the significance between AD and MCI, or MCI and CTL, or MCIc and MCInc, although complement component 4 (CC4) tended to increase in MCIc individuals compared to MCInc. Conclusions: The results suggest that A2M, FCN2, and FGG are promising biomarkers to discriminate AD patients from controls, which are worthy of further validation.

Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories towards type 2 diabetes

Most research on human pancreatic islets is conducted on samples obtained from normoglycaemic or diseased brain-dead donors and thus cannot accurately describe the molecular changes of pancreatic islet beta cells as they progress towards a state of deficient insulin secretion in type 2 diabetes (T2D). Here, we conduct a comprehensive multi-omics analysis of pancreatic islets obtained from metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum, from normoglycemia to T2D. We find that islet pools isolated from surgical samples by laser-capture microdissection display remarkably more heterogeneous transcriptomic and proteomic profiles in patients with diabetes than in non-diabetic controls. The differential regulation of islet gene expression is already observed in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive, but disharmonic, remodelling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or transdifferentiation stages in T2D. Furthermore, through integration of islet transcriptomics with preoperative blood plasma lipidomics, we define the relative importance of gene coexpression modules and lipids that are positively or negatively associated with HbA1c levels, pointing to potential prognostic markers.

APOE ε4 alters associations between docosahexaenoic acid and preclinical markers of Alzheimer's disease

Docosahexaenoic acid is the main long-chain omega-3 polyunsaturated fatty acids in the brain and accounts for 30−40% of fatty acids in the grey matter of the human cortex. Although the influence of docosahexaenoic acid on memory function is widely researched, its association with brain volumes is under investigated and its association with spatial navigation is virtually unknown. This is despite the fact that spatial navigation deficits are a new cognitive fingerprint for symptomatic and asymptomatic Alzheimer’s disease. We investigated the cross-sectional relationship between docosahexaenoic acid levels and the major structural and cognitive markers of preclinical Alzheimer’s disease, namely hippocampal volume, entorhinal volume and spatial navigation ability. Fifty-three cognitively normal adults underwent volumetric magnetic resonance imaging, measurements of serum docosahexaenoic acid (DHA, including lysophosphatidylcholine DHA) and APOE ε4 genotyping. Relative regional brain volumes were calculated and linear regression models were fitted to examine DHA associations with brain volume. APOE genotype modulated serum DHA associations with entorhinal cortex volume and hippocampal volume. Linear models showed that greater serum DHA was associated with increased entorhinal cortex volume, but not hippocampal volume, in non APOΕ ε4 carriers. APOE also interacted with serum lysophosphatidylcholine DHA to predict hippocampal volume. After testing interactions between DHA and APOE on brain volume, we investigated whether DHA and APOE interact to predict spatial navigation performance on a novel virtual reality diagnostic test for Alzheimer’s disease in an independent population of APOE genotyped adults (n = 46). APOE genotype modulated DHA associations with spatial navigation performance, showing that DHA was inversely associated with path integration in APOE ε4 carriers only. This exploratory analysis suggests that interventions aiming to increase DHA blood levels to protect against cognitive decline should consider APOE ε4 carrier status. Future work should focus on replicating our initial findings and establishing whether a specific dose of supplementary DHA, at a particular time in the preclinical disease course can have a positive impact on Alzheimer’s disease progression in APOE ε4 carriers.

TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels

INTRODUCTION

Neurofilament light (NfL), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are biomarkers for Alzheimer's disease (AD) to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively.

METHODS

We performed genome-wide association studies (GWAS) using DNA and cerebrospinal fluid (CSF) samples from the EMIF-AD Multimodal Biomarker Discovery study for discovery, and the Alzheimer's Disease Neuroimaging Initiative study for validation analyses. GWAS were performed for all three CSF biomarkers using linear regression models adjusting for relevant covariates.

RESULTS

We identify novel genome-wide significant associations between DNA variants in TMEM106B and CSF levels of NfL, and between CPOX and YKL-40. We confirm previous work suggesting that YKL-40 levels are associated with DNA variants in CHI3L1.

DISCUSSION

Our study provides important new insights into the genetic architecture underlying interindividual variation in three AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.

Bile acid synthesis, modulation, and dementia: A metabolomic, transcriptomic, and pharmacoepidemiologic study

BACKGROUND

While Alzheimer disease (AD) and vascular dementia (VaD) may be accelerated by hypercholesterolemia, the mechanisms underlying this association are unclear. We tested whether dysregulation of cholesterol catabolism, through its conversion to primary bile acids (BAs), was associated with dementia pathogenesis.

METHODS AND FINDINGS

We used a 3-step study design to examine the role of the primary BAs, cholic acid (CA), and chenodeoxycholic acid (CDCA) as well as their principal biosynthetic precursor, 7α-hydroxycholesterol (7α-OHC), in dementia. In Step 1, we tested whether serum markers of cholesterol catabolism were associated with brain amyloid accumulation, white matter lesions (WMLs), and brain atrophy. In Step 2, we tested whether exposure to bile acid sequestrants (BAS) was associated with risk of dementia. In Step 3, we examined plausible mechanisms underlying these findings by testing whether brain levels of primary BAs and gene expression of their principal receptors are altered in AD. Step 1: We assayed serum concentrations CA, CDCA, and 7α-OHC and used linear regression and mixed effects models to test their associations with brain amyloid accumulation (N = 141), WMLs, and brain atrophy (N = 134) in the Baltimore Longitudinal Study of Aging (BLSA). The BLSA is an ongoing, community-based cohort study that began in 1958. Participants in the BLSA neuroimaging sample were approximately 46% male with a mean age of 76 years; longitudinal analyses included an average of 2.5 follow-up magnetic resonance imaging (MRI) visits. We used the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 1,666) to validate longitudinal neuroimaging results in BLSA. ADNI is an ongoing, community-based cohort study that began in 2003. Participants were approximately 55% male with a mean age of 74 years; longitudinal analyses included an average of 5.2 follow-up MRI visits. Lower serum concentrations of 7α-OHC, CA, and CDCA were associated with higher brain amyloid deposition (p = 0.041), faster WML accumulation (p = 0.050), and faster brain atrophy mainly (false discovery rate [FDR] p = <0.001-0.013) in males in BLSA. In ADNI, we found a modest sex-specific effect indicating that lower serum concentrations of CA and CDCA were associated with faster brain atrophy (FDR p = 0.049) in males.Step 2: In the Clinical Practice Research Datalink (CPRD) dataset, covering >4 million registrants from general practice clinics in the United Kingdom, we tested whether patients using BAS (BAS users; 3,208 with ≥2 prescriptions), which reduce circulating BAs and increase cholesterol catabolism, had altered dementia risk compared to those on non-statin lipid-modifying therapies (LMT users; 23,483 with ≥2 prescriptions). Patients in the study (BAS/LMT) were approximately 34%/38% male and with a mean age of 65/68 years; follow-up time was 4.7/5.7 years. We found that BAS use was not significantly associated with risk of all-cause dementia (hazard ratio (HR) = 1.03, 95% confidence interval (CI) = 0.72-1.46, p = 0.88) or its subtypes. We found a significant difference between the risk of VaD in males compared to females (p = 0.040) and a significant dose-response relationship between BAS use and risk of VaD (p-trend = 0.045) in males.Step 3: We assayed brain tissue concentrations of CA and CDCA comparing AD and control (CON) samples in the BLSA autopsy cohort (N = 29). Participants in the BLSA autopsy cohort (AD/CON) were approximately 50%/77% male with a mean age of 87/82 years. We analyzed single-cell RNA sequencing (scRNA-Seq) data to compare brain BA receptor gene expression between AD and CON samples from the Religious Orders Study and Memory and Aging Project (ROSMAP) cohort (N = 46). ROSMAP is an ongoing, community-based cohort study that began in 1994. Participants (AD/CON) were approximately 56%/36% male with a mean age of 85/85 years. In BLSA, we found that CA and CDCA were detectable in postmortem brain tissue samples and were marginally higher in AD samples compared to CON. In ROSMAP, we found sex-specific differences in altered neuronal gene expression of BA receptors in AD. Study limitations include the small sample sizes in the BLSA cohort and likely inaccuracies in the clinical diagnosis of dementia subtypes in primary care settings.

CONCLUSIONS

We combined targeted metabolomics in serum and amyloid positron emission tomography (PET) and MRI of the brain with pharmacoepidemiologic analysis to implicate dysregulation of cholesterol catabolism in dementia pathogenesis. We observed that lower serum BA concentration mainly in males is associated with neuroimaging markers of dementia, and pharmacological lowering of BA levels may be associated with higher risk of VaD in males. We hypothesize that dysregulation of BA signaling pathways in the brain may represent a plausible biologic mechanism underlying these results. Together, our observations suggest a novel mechanism relating abnormalities in cholesterol catabolism to risk of dementia.

Mendelian randomization identifies blood metabolites previously linked to midlife cognition as causal candidates in Alzheimer's disease

There are currently no disease-modifying treatments for Alzheimer's disease (AD), and an understanding of preclinical causal biomarkers to help target disease pathogenesis in the earliest phases remains elusive. Here, we investigated whether 19 metabolites previously associated with midlife cognition-a preclinical predictor of AD-translate to later clinical risk, using Mendelian randomization (MR) to tease out AD-specific causal relationships. Summary statistics from the largest genome-wide association studies (GWASs) for AD and metabolites were used to perform bidirectional univariable MR. Bayesian model averaging (BMA) was additionally performed to address high correlation between metabolites and identify metabolite combinations that may be on the AD causal pathway. Univariable MR indicated four extra-large high-density lipoproteins (XL.HDL) on the causal pathway to AD: free cholesterol (XL.HDL.FC: 95% CI = 0.78 to 0.94), total lipids (XL.HDL.L: 95% CI = 0.80 to 0.97), phospholipids (XL.HDL.PL: 95% CI = 0.81 to 0.97), and concentration of XL.HDL particles (95% CI = 0.79 to 0.96), significant at an adjusted P < 0.009. MR-BMA corroborated XL.HDL.FC to be among the top three causal metabolites, in addition to total cholesterol in XL.HDL (XL.HDL.C) and glycoprotein acetyls (GP). Both XL.HDL.C and GP demonstrated suggestive univariable evidence of causality (P < 0.05), and GP successfully replicated within an independent dataset. This study offers insight into the causal relationship between metabolites demonstrating association with midlife cognition and AD. It highlights GP in addition to several XL.HDLs-particularly XL.HDL.FC-as causal candidates warranting further investigation. As AD pathology is thought to develop decades prior to symptom onset, expanding on these findings could inform risk reduction strategies.

Replication study of plasma proteins relating to Alzheimer's pathology

INTRODUCTION

This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis.

METHODS

Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively.

RESULTS

Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis.

DISCUSSION

Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis.

Metabolic phenotyping reveals a reduction in the bioavailability of serotonin and kynurenine pathway metabolites in both the urine and serum of individuals living with Alzheimer's disease

BACKGROUND

Both serotonergic signalling disruption and systemic inflammation have been associated with the pathogenesis of Alzheimer's disease (AD). The common denominator linking the two is the catabolism of the essential amino acid, tryptophan. Metabolism via tryptophan hydroxylase results in serotonin synthesis, whilst metabolism via indoleamine 2,3-dioxygenase (IDO) results in kynurenine and its downstream derivatives. IDO is reported to be activated in times of host systemic inflammation and therefore is thought to influence both pathways. To investigate metabolic alterations in AD, a large-scale metabolic phenotyping study was conducted on both urine and serum samples collected from a multi-centre clinical cohort, consisting of individuals clinically diagnosed with AD, mild cognitive impairment (MCI) and age-matched controls.

METHODS

Metabolic phenotyping was applied to both urine (n = 560) and serum (n = 354) from the European-wide AddNeuroMed/Dementia Case Register (DCR) biobank repositories. Metabolite data were subsequently interrogated for inter-group differences; influence of gender and age; comparisons between two subgroups of MCI - versus those who remained cognitively stable at follow-up visits (sMCI); and those who underwent further cognitive decline (cMCI); and the impact of selective serotonin reuptake inhibitor (SSRI) medication on metabolite concentrations.

RESULTS

Results revealed significantly lower metabolite concentrations of tryptophan pathway metabolites in the AD group: serotonin (urine, serum), 5-hydroxyindoleacetic acid (urine), kynurenine (serum), kynurenic acid (urine), tryptophan (urine, serum), xanthurenic acid (urine, serum), and kynurenine/tryptophan ratio (urine). For each listed metabolite, a decreasing trend in concentrations was observed in-line with clinical diagnosis: control > MCI > AD. There were no significant differences in the two MCI subgroups whilst SSRI medication status influenced observations in serum, but not urine.

CONCLUSIONS

Urine and serum serotonin concentrations were found to be significantly lower in AD compared with controls, suggesting the bioavailability of the neurotransmitter may be altered in the disease. A significant increase in the kynurenine/tryptophan ratio suggests that this may be a result of a shift to the kynurenine metabolic route due to increased IDO activity, potentially as a result of systemic inflammation. Modulation of the pathways could help improve serotonin bioavailability and signalling in AD patients.

Bile Acids in Dementia: Brain Amyloid, White Matter Lesions, and Atrophy

While Alzheimer’s disease (AD) and vascular dementia (VaD) may be accelerated by hypercholesterolemia, the mechanisms underlying this association is unclear. Using a novel, 3-step study design we examined the role of cholesterol catabolism in dementia by testing whether 1) the synthesis of the primary cholesterol breakdown products (bile acids (BA)) were associated with neuroimaging markers of dementia; 2) pharmacological modulation of BAs alters dementia risk; and 3) brain BA concentrations and gene expression were associated with AD. We found that higher serum concentrations of BAs are associated with lower brain amyloid deposition, slower WML accumulation, and slower brain atrophy in males. Opposite effects were observed in females. Modulation of BA levels alters risk of incident VaD in males. Altered brain BA signaling at the metabolite and gene expression levels occurs in AD. Dysregulation of peripheral cholesterol catabolism and BA synthesis may impact dementia pathogenesis through signaling pathways in the brain.

Gut microbiota profile and selected plasma metabolites in type 1 diabetes without and with stratification by albuminuria

AIMS/HYPOTHESIS

Abnormal gut microbiota and blood metabolome profiles have been reported both in children and adults with uncomplicated type 1 diabetes as well as in adults with type 1 diabetes and advanced stages of diabetic nephropathy. In this study we aimed to investigate the gut microbiota and a panel of targeted plasma metabolites in individuals with type 1 diabetes of long duration without and with different levels of albuminuria.

METHODS

In a cross-sectional study we included 161 individuals with type 1 diabetes and 50 healthy control individuals. Individuals with type 1 diabetes were categorised into three groups according to historically measured albuminuria: (1) normoalbuminuria (<3.39 mg/mmol); (2) microalbuminuria (3.39-33.79 mg/mmol); and (3) macroalbuminuria (≥33.90 mg/mmol). From faecal samples, the gut microbiota composition at genus level was characterised by 16S rRNA gene amplicon sequencing and in plasma a targeted profile of 31 metabolites was analysed with ultra HPLC coupled to MS/MS.

RESULTS

Study participants were aged 60 ± 11 years (mean ± SD) and 42% were women. The individuals with type 1 diabetes had had diabetes for a mean of 42 ± 15 years and had an eGFR of 75 ± 25 ml min^-1 (1.73 m)^-2. Measures of the gut microbial beta diversity differed significantly between healthy controls and individuals with type 1 diabetes, either with micro- or macroalbuminuria. Taxonomic analyses showed that 79 of 324 genera differed in relative abundance between individuals with type 1 diabetes and healthy controls and ten genera differed significantly among the three albuminuria groups with type 1 diabetes. For the measured plasma metabolites, 11 of 31 metabolites differed significantly between individuals with type 1 diabetes and healthy controls. When individuals with type 1 diabetes were stratified by the level of albuminuria, individuals with macroalbuminuria had higher plasma concentrations of indoxyl sulphate and L-citrulline than those with normo- or microalbuminuria and higher plasma levels of homocitrulline and L-kynurenine compared with individuals with normoalbuminuria. Whereas plasma concentrations of tryptophan were lower in individuals with macroalbuminuria compared with those with normoalbuminuria.

CONCLUSIONS/INTERPRETATION

We demonstrate that individuals with type 1 diabetes of long duration are characterised by aberrant profiles of gut microbiota and plasma metabolites. Moreover, individuals with type 1 diabetes with initial stages of diabetic nephropathy show different gut microbiota and plasma metabolite profiles depending on the level of albuminuria. Graphical abstract.

Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (Aβ) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to Aβ42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-Aβ38 and CSF-Aβ40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-Aβ and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.

Circulating Metabolites and Lipids Are Associated to Diabetic Retinopathy in Individuals With Type 1 Diabetes

Omics-based methods may provide new markers associated to diabetic retinopathy (DR). We investigated a wide omics panel of metabolites and lipids related to DR in type 1 diabetes. Metabolomic analyses were performed using two-dimensional gas chromatography with time-of-flight mass spectrometry and lipidomic analyses using an ultra-high-performance liquid chromatography quadruple time-of-flight mass spectrometry method in 648 individuals with type 1 diabetes. Subjects were subdivided into no DR, mild nonproliferative DR (NPDR), moderate NPDR, proliferative DR, and proliferative DR with fibrosis. End points were any progression of DR, onset of DR, and progression from mild to severe DR tracked from standard ambulatory care and investigated using Cox models. The cohort consisted of 648 participants aged a mean of 54.4 ± 12.8 years, 55.5% were men, and follow-up was 5.1-5.5 years. Cross-sectionally, 2,4-dihydroxybutyric acid (DHBA), 3,4-DHBA, ribonic acid, ribitol, and the triglycerides 50:1 and 50:2 significantly correlated (P < 0.042) to DR stage. Longitudinally, higher 3,4-DHBA was a risk marker for progression of DR (n = 133) after adjustment (P = 0.033). We demonstrated multiple metabolites being positively correlated to a higher grade of DR in type 1 diabetes and several triglycerides being negatively correlated. Furthermore, higher 3,4-DHBA was an independent risk marker for progression of DR; however, confirmation is required.

Correction: Dysregulation of multiple metabolic networks related to brain transmethylation and polyamine pathways in Alzheimer disease: A targeted metabolomic and transcriptomic study

[This corrects the article DOI: 10.1371/journal.pmed.1003012.].

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.

Deregulation of the Purine Pathway in Pre-Transplant Liver Biopsies Is Associated with Graft Function and Survival after Transplantation

The current shortage of livers for transplantation has increased the use of marginal organs sourced from donation after circulatory death (DCD). However, these organs have a higher incidence of graft failure, and pre-transplant biomarkers which predict graft function and survival remain limited. Here, we aimed to find biomarkers of liver function before transplantation to allow better clinical evaluation. Matched pre- and post-transplant liver biopsies from DCD (n = 24) and donation after brain death (DBD, n = 70) were collected. Liver biopsies were analysed using mass spectroscopy molecular phenotyping. Discrimination analysis was used to parse metabolites differentiated between the two groups. Five metabolites in the purine pathway were investigated. Of these, the ratios of the levels of four metabolites to those of urate differed between DBD and DCD biopsies at the pre-transplantation stage (q < 0.05). The ratios of Adenosine monophosphate (AMP) and adenine levels to those of urate also differed in biopsies from recipients experiencing early graft function (EGF) (q < 0.05) compared to those of recipients experiencing early allograft dysfunction (EAD). Using random forest, a panel consisting of alanine aminotransferase (ALT) and the ratios of AMP, adenine, and hypoxanthine levels to urate levels predicted EGF with area under the curve (AUC) of 0.84 (95% CI (0.71, 0.97)). Survival analysis revealed that the metabolite classifier could stratify six-year survival outcomes (p = 0.0073). At the pre-transplantation stage, a panel composed of purine metabolites and ALT could improve the prediction of EGF and survival.

Describing the fecal metabolome in cryogenically collected samples from healthy participants

The chemical composition of feces plays an important role in human metabolism. Metabolomics and lipidomics are valuable tools for screening the metabolite composition in feces. Here we set out to describe fecal metabolite composition in healthy participants in frozen stools. Frozen stool samples were collected from 10 healthy volunteers and cryogenically drilled in four areas along the specimen. Polar metabolites were analyzed using derivatization followed by two-dimensional gas chromatography and time of flight mass spectrometry. Lipids were detected using ultra high-performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry. 2326 metabolic features were detected. Out of a total of 298 metabolites that were annotated we report here 185 that showed a technical variation of x < 30%. These metabolites included amino acids, fatty acid derivatives, carboxylic acids and phenolic compounds. Lipids predominantly belonged to the groups of diacylglycerols, triacylglycerols and ceramides. Metabolites varied between sampling areas, some were broadly homogeneous, others varied 80%. A LASSO-computed network using metabolites present in all areas showed two main clusters describing the system, DAG lipids and phenyllactic acid. In feces from healthy participants, the main groups detected were phenolic compounds, ceramides, diacylglycerols and triacylglycerols.