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Lawrence J Appel

Publications and source records attributed to Lawrence J Appel.

2 recordsLinked to original sources

Blood Metabolomic Signatures of 1-Hour Glucose Predict Cardiometabolic Risk.

BACKGROUND: Elevated 1-hour glucose levels during an oral glucose tolerance test strongly predict type 2 diabetes (T2D) and cardiovascular disease. We investigated whether the fasting blood metabolome predicting 1-hour glucose could be a target for improving β-cell function, long-term glycemic trajectories, and reducing the risks of T2D and coronary heart disease. We also investigated whether plasma microRNAs derived from key metabolic organs regulate changes in a metabolomic risk score (MRS) for predicting 1-hour glucose. METHODS: Untargeted blood metabolomics and a frequently sampled 75-g oral glucose tolerance test were performed in participants from the OmniCarb trial (n=162). In an independent weight-loss dietary intervention trial (POUNDS Lost [Preventing Overweight Using Novel Dietary Strategies]), temporal changes in MRS and plasma microRNAs measured by genome-wide sequencing were analyzed. In addition, associations of MRS at baseline and its 10-year changes with long-term risk of incident T2D and coronary heart disease were prospectively investigated in the NHS (Nurses' Health Study). RESULTS: We created a fasting blood MRS for predicting 1-hour glucose (Pearson r=0.8) and found significant associations with half-day (diurnal) postprandial glucose excursions and insulin secretion after 5-week controlled feeding interventions varying in carbohydrate amount and glycemic index. In the POUNDS Lost trial, diet-induced changes in MRSs were related to 2-year trajectories of glucose metabolism; circulating microRNAs regulating cardiometabolic abnormalities were pivotal factors influencing these changes. In the NHS, women in the top 20% of MRS had a multivariate-adjusted relative risk of 3.80 (95% CI, 2.22-6.51) for T2D and 1.48 (95% CI, 1.04-2.12) for coronary heart disease compared with those in the lowest 20%. In addition, 10-year increases in plasma metabolites related to 1-hour glucose were linearly associated with a higher risk of T2D. CONCLUSIONS: Our findings indicate that fasting blood metabolomic signatures predicting elevated 1-hour glucose reflect disease pathophysiology and could be targets for preventing T2D and coronary heart disease.

blood glucose

Metabolomic Signatures of Inflammation in Chronic Kidney Disease.

RATIONALE & OBJECTIVE: Inflammation is associated with adverse kidney, cardiovascular, and mortality outcomes. Investigation of the metabolic milieu as it relates to inflammation may provide important insights into these disease processes. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: African American Study of Kidney Disease and Hypertension (AASK), Atherosclerosis Risk in Communities (ARIC) study, and Boston Kidney Biopsy Cohort (BKBC) participants with available metabolomics and inflammatory protein data. PREDICTORS: Baseline blood levels of 718 metabolites. OUTCOMES: Baseline and longitudinal changes in blood levels of tumor necrosis factor receptors 1 and 2 (TNFR1, TNFR2), tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), interleukins 6, 8, and 10 (IL-6, IL-8, IL-10), uromodulin (UMOD), and epidermal growth factor (EGF). ANALYTICAL APPROACH: Multivariable linear regression and linear mixed-effects models. RESULTS: Among 491 AASK participants (mean age 54 years; 37% women; mean glomerular filtration rate, 45 mL/min/1.73 m2), 367 cross-sectional associations between metabolites and inflammatory proteins were significant after correction for multiple comparisons. The direction of association was mostly positive for TNFR1 (97%), TNFR2 (97%), IL-8 (77%), and IL-10 (100%); negative for UMOD (80%) and EGF (97%); and variable for TNF-⍺, IFN-γ, and IL-6. Pathways were distinct for several inflammatory proteins (eg, tryptophan metabolism for TNFR2). Forty-five associations between metabolites and longitudinal change in inflammatory proteins were identified. Notable metabolites included tigylcarnitine and N 2,N 5-diacetylornithine, which were associated with 2-year increases in TNFR1 and/or TNFR2, and 1,5-anhydroglucitol, where lower levels were associated with decreases in UMOD. In ARIC (n = 3,773) and BKBC (n = 413), replication of cross-sectional associations was excellent for TNFR1 (ARIC 83%; BKBC 85%) and TNFR2 (ARIC 64%; BKBC 79%) but poor for IL-8 (ARIC 3%; BKBC 3%). LIMITATIONS: Metabolite data limited to baseline visit; potential for residual confounding. CONCLUSIONS: Using an untargeted approach, multiple metabolites were cross-sectionally and longitudinally associated with inflammatory proteins in persons with chronic kidney disease.

Chronic kidney disease