Nuclear Magnetic Resonance Derived Biomarkers for Evaluating Cardiometabolic Risk in Youth and Young Adults Across the Spectrum of Glucose Tolerance.

Youth with obesity have an increased risk for cardiometabolic disease, but identifying those at highest risk remains a challenge. Four biomarkers that might serve this purpose are "by products" of clinical NMR LipoProfile® lipid testing: LPIR (Lipoprotein Insulin Resistance Index), GlycA (inflammation marker), BCAA (total branched-chain amino acids), and glycine. All are strongly related to insulin resistance and type 2 diabetes (T2DM) in adults (glycine inversely) and are independent of biological and methodological variations in insulin assays. However, their clinical utility in youth is unclear. We compared fasting levels of these biomarkers in 186 youth (42 lean normal glucose tolerant (NGT), 88 obese NGT, 23 with prediabetes (PreDM), and 33 with T2DM. All four biomarkers were associated with obesity and glycemia in youth. LPIR and GlycA were highest in youth with PreDM and T2DM, whereas glycine was lowest in youth with T2DM. While all four were correlated with HOMA-IR (Homeostatic Model Assessment for Insulin Resistance), LPIR had the strongest correlation (LPIR: r = 0.6; GlycA: r = 0.4, glycine: r = -0.4, BCAA: r = 0.2, all P < 0.01). All four markers correlated with HbA1c (LPIR, GlycA, BCAA: r ≥ 0.3 and glycine: r = -0.3, all P < 0.001). In multi-variable regression models, LPIR, GlycA, and glycine were independently associated with HOMA-IR (Adjusted R2 = 0.473, P < 0.001) and LPIR, glycine, and BCAA were independently associated with HbA1c (Adjusted R2 = 0.33, P < 0.001). An LPIR index of >44 was associated with elevated blood pressure, BMI, and dyslipidemia. Plasma NMR-derived markers were related to adverse markers of cardiometabolic risk in youth. LPIR, either alone or in combination with GlycA, should be explored as a non-insulin dependent predictive tool for development of insulin resistance and diabetes in youth. Clinical Trial Registration: Clinicaltrials.gov, identifier NCT:02960659.

Metformin treatment and gastrointestinal symptoms in youth: Findings from a large tertiary care referral center.

OBJECTIVES: Metformin is the only oral therapy for youth with type 2 diabetes, but up to 50% require additional agents within 2 years of diagnosis. Extended-release (XR) metformin formulations may improve adherence and tolerability-important mediators of treatment response-but data in youth is lacking. To evaluate rates of gastrointestinal (GI) symptoms in patients treated with metformin (SR and XR) and the change in GI symptoms after changes in metformin therapy. RESEARCH DESIGN AND METHODS: Retrospective chart review of youth with Type 2 or prediabetes seen in a multidisciplinary clinic during 2016-2019. RESULTS: Of 488 eligible patients, 41.4% and 21.1% were taking metformin SR and XR respectively, with most (58%, n = 178/305) taking a total daily dose of ≥1500 mg/day. Those not on metformin tended to be younger, leaner, and had lower HbA1cs than those taking metformin, p < 0.05. Thirty percentage of patients described GI symptoms, most commonly, abdominal pain and diarrhea. There was no difference in GI symptoms in those on SR versus XR (18.3% vs. 14.6%, p = 0.41). Among patients who initiated metformin, rates of GI symptoms increased (13%-33%, p = 0.001, n = 99), while rates tended to decrease when metformin was discontinued (28%-12%, p = 0.076, n = 50). Rates of GI symptoms were unchanged among those that switched from SR to XR metformin (17% vs. 14%, p = 0.6, n = 58). CONCLUSIONS: GI symptoms are common in youth with type 2 diabetes taking metformin XR and SR. Adjuncts to mitigate GI symptoms in youth on metformin therapy are needed to improve quality of life and medication adherence.

Metformin improves blood glucose by increasing incretins independent of changes in gluconeogenesis in youth with type 2 diabetes.

AIMS/HYPOTHESIS: Metformin is the only approved oral agent for youth with type 2 diabetes but its mechanism of action remains controversial. Recent data in adults suggest a primary role for the enteroinsular pathway, but there are no data in youth, in whom metformin efficacy is only ~50%. Our objectives were to compare incretin concentrations and rates of glucose production and gluconeogenesis in youth with type 2 diabetes before and after short-term metformin therapy compared with peers with normal glucose tolerance (NGT). METHODS: This is a case-control observational study in youth with type 2 diabetes who were not on metformin (n = 18) compared with youth with NGT (n = 10) who were evaluated with a 2 day protocol. A 75 g OGTT was administered to measure intact glucagon-like 1 peptide (iGLP-1), gastric inhibitory polypeptide (GIP) and peptide YY (PYY). Insulinogenic index (IGI) and whole-body insulin sensitivity were calculated using glucose and insulin levels from the OGTT. Basal rates of gluconeogenesis (2H2O), glucose production ([6,6-2H2]glucose) and whole-body lipolysis ([2H5]glycerol) were measured after an overnight fast on study day 2. Youth with type 2 diabetes (n = 9) were subsequently evaluated with an identical 2 day protocol after 3 months on the metformin study. RESULTS: Compared with individuals with NGT, those with type 2 diabetes had higher fasting (7.8 ± 2.5 vs 5.1 ± 0.3 mmol/l, mean ± SD p = 0.002) and 2 h glucose concentrations (13.8 ± 4.5 vs 5.9 ± 0.9 mmol/l, p = 0.001), higher rates of absolute gluconeogenesis (10.0 ± 1.7 vs 7.2 ± 1.1 µmol [kg fat-free mass (FFM)]-1 min-1, p < 0.001) and whole-body lipolysis (5.2 ± 0.9 vs 4.0 ± 1.4 µmol kgFFM-1 min-1, p < 0.01), but lower fasting iGLP-1 concentrations (0.5 ± 0.5 vs 1.3 ± 0.7 pmol/l, p < 0.01). Metformin decreased 2 h glucose (pre metformin 11.4 ± 2.8 vs post metformin 9.9 ± 1.9 mmol/l, p = 0.04) and was associated with ~20-50% increase in IGI (median [25th-75th percentile] pre 1.39 [0.89-1.47] vs post 1.43 [0.88-2.70], p = 0.04), fasting iGLP-1 (pre 0.3 ± 0.2 vs post 1.0 ± 0.7 pmol/l, p = 0.02), 2 h iGLP (pre 0.4 ± 0.2 vs post 1.2 ± 0.9 pmol/l, p = 0.06), fasting PYY (pre 6.3 ± 2.2 vs post 10.5 ± 4.3 pmol/l, p < 0.01) and 2 h PYY (pre 6.6 ± 2.9 vs post 9.0 ± 4.0 pmol/l, p < 0.01). There was no change in BMI, insulin sensitivity or GIP concentrations pre vs post metformin. There were no differences pre vs post metformin in rates of glucose production (15.0 ± 3.9 vs 14.9 ± 2.2 µmol kgFFM-1 min-1, p = 0.84), absolute gluconeogenesis (9.9 ± 1.8 vs 9.7 ± 1.7 µmol kgFFM-1 min-1, p = 0.76) or whole-body lipolysis (5.0 ± 0.7 vs 5.3 ± 1.3 µmol kgFFM-1 min-1, p = 0.20). Post metformin iGLP-1 and PYY concentrations in youth with type 2 diabetes were comparable to levels in youth with NGT. CONCLUSIONS/INTERPRETATION: Overall, the improved postprandial blood glucose levels and increase in incretins observed in the absence of changes in insulin sensitivity and gluconeogenesis, support an enteroinsular mechanistic pathway in youth with type 2 diabetes treated with short-term metformin.

Review of methods for detecting glycemic disorders.

Prediabetes (intermediate hyperglycemia) consists of two abnormalities, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) detected by a standardized 75-gram oral glucose tolerance test (OGTT). Individuals with isolated IGT or combined IFG and IGT have increased risk for developing type 2 diabetes (T2D) and cardiovascular disease (CVD). Diagnosing prediabetes early and accurately is critical in order to refer high-risk individuals for intensive lifestyle modification. However, there is currently no international consensus for diagnosing prediabetes with HbA1c or glucose measurements based upon American Diabetes Association (ADA) and the World Health Organization (WHO) criteria that identify different populations at risk for progressing to diabetes. Various caveats affecting the accuracy of interpreting the HbA1c including genetics complicate this further. This review describes established methods for detecting glucose disorders based upon glucose and HbA1c parameters as well as novel approaches including the 1-hour plasma glucose (1-h PG), glucose challenge test (GCT), shape of the glucose curve, genetics, continuous glucose monitoring (CGM), measures of insulin secretion and sensitivity, metabolomics, and ancillary tools such as fructosamine, glycated albumin (GA), 1,5- anhydroglucitol (1,5-AG). Of the approaches considered, the 1-h PG has considerable potential as a biomarker for detecting glucose disorders if confirmed by additional data including health economic analysis. Whether the 1-h OGTT is superior to genetics and omics in providing greater precision for individualized treatment requires further investigation. These methods will need to demonstrate substantially superiority to simpler tools for detecting glucose disorders to justify their cost and complexity.

Triglyceride Paradox Is Related to Lipoprotein Size, Visceral Adiposity and Stearoyl-CoA Desaturase Activity in Black Versus White Women.

RATIONALE: In black women, triglycerides are paradoxically normal in the presence of insulin resistance. This relationship may be explained by race-related differences in central adiposity and SCD (stearoyl-CoA desaturase)-1 enzyme activity index. OBJECTIVE: In a cross-sectional study, to compare fasting and postprandial triglyceride-rich lipoprotein particle (TRLP) concentrations and size in black compared with white pre- and postmenopausal women and determine the relationship between TRLP subfractions and whole-body insulin sensitivity, hepatic and visceral fat, and SCD-1 levels. METHODS AND RESULTS: In 122 federally employed women without diabetes mellitus, 73 black (58 African American and 15 African immigrant) and 49 white; age, 44±10 (mean±SD) years; body mass index, 30.0±5.6 kg/m2, we measured lipoprotein subfractions using nuclear magnetic resonance. Hepatic fat was measured by proton magnetic resonance spectroscopy, insulin sensitivity index calculated by minimal modeling from a frequently sampled intravenous glucose test, and red blood cell fatty acid profiles were measured by gas chromatography and were used to estimate SCD-1 indices. Hepatic fat, insulin sensitivity index, and SCD-1 were similar in black women and lower than in whites, regardless of menopausal status. Fasting and postprandial large, medium, and small TRLPs, but not very small TRLPs, were lower in black women. Fasting large, medium, and very small TRLPs negatively correlated with insulin sensitivity index and positively correlated with visceral and hepatic fat and SCD-1 activity in both groups. In multivariate models, visceral fat and SCD-1 were associated with total fasting TRLP concentrations (adjR2, 0.39; P=0.001). Black women had smaller postprandial changes in large (P=0.005) and medium TRLPs (P=0.007). CONCLUSIONS: Lower visceral fat and SCD-1 activity may contribute to the paradoxical association of lower fasting and postprandial TRLP subfractions despite insulin resistance in black compared with white pre- and postmenopausal women. Similar concentrations of very small TRLPs are related to insulin resistance and could be important mediators of cardiometabolic disease risk in women. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01809288.