Showing papers by "Richard N. Bergman published in 2023"
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TL;DR: The Type 2 Diabetes Knowledge Portal (T2DKP) as discussed by the authors is a public resource of genetic datasets and genomic annotations dedicated to type 2 diabetes and related traits, which can be used for access to complex disease genetic results.
5 citations
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2 citations
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TL;DR: In this paper , the effects of the SGLT2i dapagliflozin (DAPA) on subcutaneous (SC) and visceral (VIS) adipose tissue function remain unclear.
Abstract: Sodium‐glucose cotransporter 2 inhibitors (SGLT2i) promote urinary glucose excretion, induce weight loss, and reduce fat accumulation. The effects of the SGLT2i dapagliflozin (DAPA) on subcutaneous (SC) and visceral (VIS) adipose tissue function remain unclear. The objective of this study is to evaluate SC and VIS adipose tissue function in an insulin‐resistant canine model.
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TL;DR: In this paper , the authors developed estimation models for the dynamic measure of insulin sensitivity (SI) and the basal measure of homeostatic model assessment of IR (HOMAIR) from metabolomics data combined with minimal clinical data, e.g. age, sex, BMI.
Abstract: Insulin resistance (IR) is constantly invoked as a contributor to numerous common diseases, e.g. diabetes, cardiovascular disease and Alzheimer’s disease; however, with the exception of a narrow segment of diabetes-related studies, IR is infrequently measured and rarely measured well. Our goal was to develop IR estimation models for the dynamic measure of insulin sensitivity (SI) and the basal measure of homeostatic model assessment of IR (HOMAIR) from metabolomics data combined with minimal clinical data, e.g. age, sex, BMI. Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net regression were used to build estimation models using 1274 metabolites, prioritized by trait associations and collected in the Insulin Resistance Atherosclerosis Family Study (IRASFS). Three metabolite transformations were implemented (inverse normal transformation, standardization, and Box Cox transformation) to account for distributional differences and tested to optimize estimation. The analysis was performed in one Mexican American (MA) recruitment site (San Luis Valley, CO (SLV), N=450) and tested in another MA recruitment site (San Antonio, TX (SA), N=473). In addition, the two MA recruitment sites were combined and estimation models tested in the African American recruitment site (AA; Los Angeles, California, N=495) to assess generalizability. Estimated SI was correlated with empiric SI in the SA (r2=0.77) and AA (r2=0.74) testing datasets. Further, we tested estimated SI for association with BMI, low-density lipoprotein cholesterol and triglycerides with results consistent with those observed for empiric SI. The same framework was used to estimate HOMAIR, and yielded similar results. In summary, we have developed methods for estimating multiple measures of IR from a single blood sample. This approach will greatly expand our ability to provide meaningful insight into the role of IR in disease, supporting the potential for application to a wide-range of biomedical studies.
N.Allred: None. D.W.Bowden: None. F.Hsu: None. S.Chen: None. M.Ng: None. M.O.Goodarzi: Advisory Panel; Nestlé Health Science, Other Relationship; Nestlé Health Science. J.I.Rotter: None. L.E.Wagenknecht: None. M.Bancks: None. R.N.Bergman: Consultant; Lilly, ReCor Medical, Inc., Research Support; AstraZeneca.
National Institutes of Health (DK118062)
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TL;DR: Bergman et al. as discussed by the authors showed that a single injection of fibroblast growth factor 1 (FGF1) has glucose-lowering activity in diabetic animals and induces concomitant increases in glucokinase (GCK) activity and plasma lactate.
Abstract: Rodent studies performed in Dr. Schwartz's lab showed that a single injection of fibroblast growth factor 1 (FGF1) has glucose-lowering activity in diabetic animals and induces concomitant increases in glucokinase (GCK) activity and plasma lactate (Scarlett, JM, Nat Med, 2016). In addition, in vivo experiments performed by our group demonstrated that hepatic lactate export is a surrogate for GCK activity. The mechanism by which FGF1 exerts these effects at cellular level in hepatocytes is unknown. In this study, we treated C57BL/6 mouse hepatocytes with different concentrations of FGF1 (100, 200, or 400 ng/ml) and evaluated GCK gene expression and lactate export from hepatocytes into the medium after 24 h of treatment. FGF1 increased lactate export with 200 to 400 ng/ml FGF1 increased lactate export by 1.5-fold (P<0.05). FGF1 concentration from 100-400 ng/ml did not change cell proliferation, and 200 to 400 ng/ml FGF1 upregulated the expression of GCK by 2.3 and 3-fold (P<0.05), respectively. Thus, these data provide a possible mechanism by which of FGF1 upregulates GCK and, consequently, increases lactate export by hepatocytes.
M.Kabir: None. M.Ader: None. N.Thomas: None. E.Seki: Research Support; Nippon Zoki Ltd, Jubilant. R.N.Bergman: Consultant; Lilly, ReCor Medical, Inc., Research Support; AstraZeneca.
National Institutes of Health (R01DK027619-33A1)