Diminished Sphingolipid Metabolism, a Hallmark of Future Type 2 Diabetes Pathogenesis, Is Linked to Pancreatic β Cell Dysfunction

Khan, Sumsullah; Manialawy, Yousef; Obersterescu, Andreea; Cox, Brian; Gunderson, Erica P.; Wheeler, Michael B.

doi:10.1016/j.isci.2020.101566

Cited by 29 publications

(28 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In two population-based studies, the inclusion of metabolites in a prediction model that included conventional risk factors barely improved the discriminative capability of the model with clinical variables [ 34 , 35 ]. Findings were slightly different in a recent report in which the inclusion of metabolomic markers helped to identify additional people who might be at increased risk of type 2 diabetes [ 36 ]. Finally, the vast majority of these reports represent white American or European populations, and a recent report determined that metabolomic signatures associated with prediabetes may be distinct in African Americans (AA) and European Americans (EA) from that previously linked to type 2 diabetes in white individuals [ 37 ].…”

Section: Introductioncontrasting

confidence: 67%

Clinical and metabolomic predictors of regression to normoglycemia in a population at intermediate cardiometabolic risk

Sevilla-González

Merino

Moreno-Macías

et al. 2021

Cardiovasc Diabetol

View full text Add to dashboard Cite

Background Impaired fasting glucose (IFG) is a prevalent and potentially reversible intermediate stage leading to type 2 diabetes that increases risk for cardiometabolic complications. The identification of clinical and molecular factors associated with the reversal, or regression, from IFG to a normoglycemia state would enable more efficient cardiovascular risk reduction strategies. The aim of this study was to identify clinical and biological predictors of regression to normoglycemia in a non-European population characterized by high rates of type 2 diabetes. Methods We conducted a prospective, population-based study among 9637 Mexican individuals using clinical features and plasma metabolites. Among them, 491 subjects were classified as IFG, defined as fasting glucose between 100 and 125 mg/dL at baseline. Regression to normoglycemia was defined by fasting glucose less than 100 mg/dL in the follow-up visit. Plasma metabolites were profiled by Nuclear Magnetic Resonance. Multivariable cox regression models were used to examine the associations of clinical and metabolomic factors with regression to normoglycemia. We assessed the predictive capability of models that included clinical factors alone and models that included clinical factors and prioritized metabolites. Results During a median follow-up period of 2.5 years, 22.6% of participants (n = 111) regressed to normoglycemia, and 29.5% progressed to type 2 diabetes (n = 145). The multivariate adjusted relative risk of regression to normoglycemia was 1.10 (95% confidence interval [CI] 1.25 to 1.32) per 10 years of age increase, 0.94 (95% CI 0.91–0.98) per 1 SD increase in BMI, and 0.91 (95% CI 0.88–0.95) per 1 SD increase in fasting glucose. A model including information from age, fasting glucose, and BMI showed a good prediction of regression to normoglycemia (AUC = 0.73 (95% CI 0.66–0.78). The improvement after adding information from prioritized metabolites (TG in large HDL, albumin, and citrate) was non-significant (AUC = 0.74 (95% CI 0.68–0.80), p value = 0.485). Conclusion In individuals with IFG, information from three clinical variables easily obtained in the clinical setting showed a good prediction of regression to normoglycemia beyond metabolomic features. Our findings can serve to inform and design future cardiovascular prevention strategies.

show abstract

Section: Introductioncontrasting

confidence: 67%

Clinical and metabolomic predictors of regression to normoglycemia in a population at intermediate cardiometabolic risk

Sevilla-González

Merino

Moreno-Macías

et al. 2021

Cardiovasc Diabetol

View full text Add to dashboard Cite

show abstract

“… 41–43 This includes one large study in a mainly non-Hispanic white population (n=3082) 42 and a moderate-sized (n=1035) study in an ethnically diverse population. 43 We have expanded these findings to PR adults and identified the associations between sphingolipids and higher HDL-C concentrations. Previous studies have linked higher HDL-C concentrations to better pancreatic β cell function, 44 45 suggesting that further exploration of how metabolites in this sphingolipid cluster influence pancreatic β cell function may be fruitful.…”

Section: Discussionmentioning

confidence: 99%

Associations of network-derived metabolite clusters with prevalent type 2 diabetes among adults of Puerto Rican descent

Haslam

Liang

Wang

et al. 2021

BMJ Open Diab Res Care

View full text Add to dashboard Cite

IntroductionWe investigated whether network analysis revealed clusters of coregulated metabolites associated with prevalent type 2 diabetes (T2D) among Puerto Rican adults.Research design and methodsWe used liquid chromatography-mass spectrometry to measure fasting plasma metabolites (>600) among participants aged 40–75 years in the Boston Puerto Rican Health Study (BPRHS; discovery) and San Juan Overweight Adult Longitudinal Study (SOALS; replication), with (n=357; n=77) and without (n=322; n=934) T2D, respectively. Among BPRHS participants, we used unsupervised partial correlation network-based methods to identify and calculate metabolite cluster scores. Logistic regression was used to assess cross-sectional associations between metabolite clusters and prevalent T2D at the baseline blood draw in the BPRHS, and significant associations were replicated in SOALS. Inverse-variance weighted random-effect meta-analysis was used to combine cohort-specific estimates.ResultsSix metabolite clusters were significantly associated with prevalent T2D in the BPRHS and replicated in SOALS (false discovery rate (FDR) <0.05). In a meta-analysis of the two cohorts, the OR and 95% CI (per 1 SD increase in cluster score) for prevalent T2D were as follows for clusters characterized primarily by glucose transport (0.21 (0.16 to 0.30); FDR <0.0001), sphingolipids (0.40 (0.29 to 0.53); FDR <0.0001), acyl cholines (0.35 (0.22 to 0.56); FDR <0.0001), sugar metabolism (2.28 (1.68 to 3.09); FDR <0.0001), branched-chain and aromatic amino acids (2.22 (1.60 to 3.08); FDR <0.0001), and fatty acid biosynthesis (1.54 (1.29 to 1.85); FDR <0.0001). Three additional clusters characterized by amino acid metabolism, cell membrane components, and aromatic amino acid metabolism displayed significant associations with prevalent T2D in the BPRHS, but these associations were not replicated in SOALS.ConclusionsAmong Puerto Rican adults, we identified several known and novel metabolite clusters that associated with prevalent T2D.

show abstract

“…The levels of two sphingomyelin species (sphingomyelin (d18:2/14:0, d18:1/14:1) and sphingomyelin (d18:2/24:2)) were also lower in the SIDD cluster. Downregulated sphingolipid metabolism can affect insulin sensitivity and lead to β cell dysfunction 61 .…”

Section: Resultsmentioning

confidence: 99%

Metabolic and proteomic signatures of type 2 diabetes subtypes in an Arab population

Zaghlool

Halama

Stephan

et al. 2022

Preprint

View full text Add to dashboard Cite

Background. Type 2 diabetes (T2D) has a heterogeneous etiology which is increasingly recognized to influence the risk of complications and choice of treatment. A data driven cluster analysis in four separate European populations of patients with type 2 diabetes identified four subtypes of severe insulin dependent (SIDD), severe insulin resistant (SIRD), mild obesity-related (MOD), and mild age-related (MARD) (Ahlqvist et al., Lancet Diabetes Endocrinology, 2018). Our aim was to extend this classification to the Arab population of Qatar and characterize the biological processes that differentiate these subtypes in relation to metabolomic and proteomic signatures. Methods. The Ahlqvist et al. subtype clustering approach was applied to 631 individuals with T2D from the Qatar Biobank (QBB) and validated in an independent set of 420 participants from the same population. The association between blood metabolites (n=1,159) and protein levels (n=1,305) with each cluster were established. Findings. The four subtypes of T2D were reproduced and validated in the population of Qatar. Cluster-specific metabolomic and proteomic associations revealed subtype-specific molecular processes. Activation of the complement system with many features of autoimmune diabetes and reduced 1,5-anhydroglucitol (1,5-AG) characterized SIDD, with evidence of impaired insulin signaling in SIRD, elevated leptin and fatty acid binding protein in MOD, whilst MARD appeared to be the healthiest subgroup. Interpretation. We have replicated the four T2D clusters in an Arab population and identified distinct metabolic and proteomic signatures, providing insights into underlying etiology with the potential to deploy subtype-specific treatment options.

show abstract

Diminished Sphingolipid Metabolism, a Hallmark of Future Type 2 Diabetes Pathogenesis, Is Linked to Pancreatic β Cell Dysfunction

Cited by 29 publications

References 50 publications

Clinical and metabolomic predictors of regression to normoglycemia in a population at intermediate cardiometabolic risk

Clinical and metabolomic predictors of regression to normoglycemia in a population at intermediate cardiometabolic risk

Associations of network-derived metabolite clusters with prevalent type 2 diabetes among adults of Puerto Rican descent

Metabolic and proteomic signatures of type 2 diabetes subtypes in an Arab population

Contact Info

Product

Resources

About