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

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.

Low sphingolipid levels predict poor survival in patients with alcohol-related liver disease

Background & Aims

Alcohol-related hepatitis (AH) and alcohol-related cirrhosis are grave conditions with poor prognoses. Altered hepatic lipid metabolism can impact disease development and varies between different alcohol-related liver diseases. Therefore, we aimed to investigate lipidomics and metabolomics at various stages of alcohol-related liver diseases and their correlation with survival.

Methods

Patients with newly diagnosed alcohol-related cirrhosis, who currently used alcohol (ALC-A), stable outpatients with decompensated alcohol-related cirrhosis with at least 8 weeks of alcohol abstinence (ALC), and patients with AH, were compared with each other and with healthy controls (HC). Circulating lipids and metabolites were analysed using HPLC and mass spectrometry.

Results

Forty patients with ALC, 95 with ALC-A, 30 with AH, and 42 HC provided plasma. Lipid levels changed according to disease severity, with generally lower levels in AH and cirrhosis than in the HC group; this was most pronounced for AH, followed by ALC-A. Nine out of 10 free fatty acids differed between cirrhosis groups by relative increases of 0.12-0.66 in ALC compared with the ALC-A group (p <0.0005). For metabolomics, total bile acids increased by 19.7, 31.3, and 80.4 in the ALC, ALC-A, and AH groups, respectively, compared with HC (all p <0.0001). Low sphingolipid ([d42:1] and [d41:1]) levels could not predict 180-day mortality (AUC = 0.73, p = 0.95 and AUC = 0.73, p = 0.95) more accurately than the model for end-stage liver disease score (AUC = 0.71), but did predict 90-day mortality (AUC d42:1 = 0.922, AUC d41:1 = 0.893; pd42:1 = 0.005, pd41:1 = 0.007) more accurately than the MELD score AUCMELD = 0.70, pMELD = 0.19).

Conclusions

Alcohol-related severe liver disease is characterised by low lipid levels progressing with severity of liver disease, especially low sphingomyelins, which also associate to poor prognoses.

Impact and implications

Lipidomics has the potential to diagnose and risk stratify patients with liver diseases. Lipidomics differed between patients with alcohol-related hepatitis and alcohol-related cirrhosis with and without recent alcohol use. Furthermore, lipidomics could predict short-term mortality and might be suitable as a prognostic tool in the future.

Clinical Trials Registration

Scientific Ethics Committee of the Capital Region of Denmark, journal no. H-21013476.

Atorvastatin for patients with cirrhosis. A randomized, placebo-controlled trial

BACKGROUND

Patients with cirrhosis and portal hypertension face a high risk of complications. Besides their anti-inflammatory and antifibrotic effects, statins may reduce portal pressure and thus the risk of complications and mortality. We aimed to investigate the effects of atorvastatin on hospital admissions, mortality, inflammation, and lipidomics in cirrhosis with portal hypertension.

METHODS

We performed a double-blinded, randomized, placebo-controlled clinical trial among patients with cirrhosis and portal hypertension. Atorvastatin (10-20 mg/d) was administered for 6 months. We measured splanchnic hemodynamics, analyzed inflammatory markers, and performed lipidomics at baseline and after 6 months.

RESULTS

Seventy-eight patients were randomized, with 38 patients allocated to atorvastatin and 40 patients to placebo. Fifty-nine patients completed 6 months of intervention. Comparisons between changes in each group were calculated. Liver-related complications and mortality were similar between the groups. The HVPG and Model for End-stage Liver Disease score did not change between groups (p=0.95 and 0.87, respectively). Atorvastatin decreased 3 of 42 inflammatory markers, CD62-L-selectin, matrix metalloproteinases-2, and TNF-α (p-values: 0.005, 0.011, and 0.023, respectively), while lipidomics was not significantly changed.

CONCLUSIONS

In patients with cirrhosis, atorvastatin was safe to use, but did not reduce mortality, the risk of liver-related complications, or the HVPG. Atorvastatin induced minor anti-inflammatory effects and minor effects on lipids during a 6-month treatment period.

Cardiovascular autonomic neuropathy in patients with type 2 diabetes with and without sensorimotor polyneuropathy

BACKGROUND AND AIMS

Cardiovascular autonomic neuropathy (CAN) in patients with diabetes is associated with poor prognosis. We aimed to assess signs of CAN and autonomic symptoms and to investigate the impact of sensorimotor neuropathy on CAN by examining type 2 diabetes patients with (DPN [distal sensorimotor polyneuropathy]) and without distal sensorimotor polyneuropathy (noDPN) and healthy controls (HC). Secondarily, we aimed to describe the characteristics of patients with CAN.

METHODS

A population of 374 subjects from a previously described cohort of the Danish Centre for Strategic Research in Type 2 Diabetes (DD2) were included. Subjects were examined with the Vagus™ device for the diagnosis of CAN, where two or more abnormal cardiovascular autonomic reflex tests indicate definite CAN. Autonomic symptoms were assessed with Composite Autonomic Symptom Score 31 (COMPASS 31) questionnaire. DPN was defined according to the Toronto consensus panel definition.

RESULTS

Definite CAN was present in 22% with DPN, 7% without DPN and 3% of HC, and 91% of patients with definite CAN had DPN. Patients with DPN and definite CAN reported higher COMPASS 31 scores compared to patients with noDPN (20.0 vs. 8.3, p < 0.001) and no CAN (22.1 vs. 12.3, p = 0.01). CAN was associated with HbA1c and age in a multivariate logistic regression analysis but was not associated with IEFND or triglycerides.

INTERPRETATION

One in five patients with DPN have CAN and specific CAN characteristics may help identify patients at risk for developing this severe diabetic complication. Autonomic symptoms were strongly associated with having both DPN and CAN, but too unspecific for diagnosing CAN.

Metabolomics in diabetes mellitus: clinical insight

INTRODUCTION

Diabetes Mellitus (DM) is a chronic heterogeneous metabolic disorder characterized by hyperglycemia due to the destruction of insulin-producing pancreatic β cells and/or insulin resistance. It is now considered a global epidemic disease associated with serious threats to a patient's life. Understanding the metabolic pathways involved in disease pathogenesis and progression is important and would improve prevention and management strategies. Metabolomics is an emerging field of research that offers valuable insights into the metabolic perturbation associated with metabolic diseases, including DM.

AREA COVERED

Herein, we discussed the metabolomics in type 1 and 2 DM research, including its contribution to understanding disease pathogenesis and identifying potential novel biomarkers clinically useful for disease screening, monitoring, and prognosis. In addition, we highlighted the metabolic changes associated with treatment effects, including insulin and different anti-diabetic medications.

EXPERT OPINION

By analyzing the metabolome, the metabolic disturbances involved in T1DM and T2DM can be explored, enhancing our understanding of the disease progression and potentially leading to novel clinical diagnostic and effective new therapeutic approaches. In addition, identifying specific metabolites would be potential clinical biomarkers for predicting the disease and thus preventing and managing hyperglycemia and its complications.

Diagnostic and predictive values of serum metabolic profiles in sudden sensorineural hearing loss patients

Sudden sensorineural hearing loss (SSNHL) is an otologic emergency, and metabolic disturbance is involved in its pathogenesis. This study recruited 20 SSNHL patients and 20 healthy controls (HCs) and collected their serum samples. Serum metabolites were detected by liquid chromatography-mass spectrometry, and metabolic profiles were analyzed. All patients were followed up for 3 months and categorized into recovery and non-recovery groups. The distinctive metabolites were assessed between two groups, and their predictive values for hearing recovery were evaluated. Analysis results revealed that SSNHL patients exhibited significantly characteristic metabolite signatures compared to HCs. The top 10 differential metabolites were further analyzed, and most of them showed potential diagnostic values based on receiver operator characteristic (ROC) curves. Finally, 14 SSNHL patients were divided into the recovery group, and six patients were included in the non-recovery group. Twelve distinctive metabolites were observed between the two groups, and ROC curves demonstrated that N4-acetylcytidine, p-phenylenediamine, sphingosine, glycero-3-phosphocholine, and nonadecanoic acid presented good predictabilities in the hearing recovery. Multivariate analysis results demonstrated that serum N4-Acetylcytidine, sphingosine and nonadecanoic acid levels were associated with hearing recovery in SSNHL patients. Our results identified that SSNHL patients exhibited distinctive serum metabolomics signatures, and several serum biomarkers were proved to be potential in predicting hearing recovery. The discriminative metabolites might contribute to illustrating the mechanisms of SSNHL and provide possible clues for its treatments.

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.