9 results on '"Bizzotto, Roberto"'
Search Results
2. The Association of Cardiometabolic, Diet and Lifestyle Parameters With Plasma Glucagon-like Peptide-1: An IMI DIRECT Study.
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Eriksen, Rebeca, White, Margaret C, Dawed, Adem Y, Perez, Isabel Garcia, Posma, Joram M, Haid, Mark, Sharma, Sapna, Prehn, Cornelia, Thomas, E Louise, Koivula, Robert W, Bizzotto, Roberto, Mari, Andrea, Giordano, Giuseppe N, Pavo, Imre, Schwenk, Jochen M, Masi, Federico De, Tsirigos, Konstantinos D, Brunak, Søren, Viñuela, Ana, and Mahajan, Anubha
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TYPE 2 diabetes ,PEOPLE with diabetes ,MULTIPLE regression analysis ,INSULIN resistance ,FOOD consumption - Abstract
Context The role of glucagon-like peptide-1 (GLP-1) in type 2 diabetes (T2D) and obesity is not fully understood. Objective We investigate the association of cardiometabolic, diet, and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D. Methods We analyzed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1 (n = 2127) individuals at risk of diabetes; cohort 2 (n = 789) individuals with new-onset T2D. Results Our multiple regression analysis reveals that fasting total GLP-1 is associated with an insulin-resistant phenotype and observe a strong independent relationship with male sex, increased adiposity, and liver fat, particularly in the prediabetes population. In contrast, we showed that incremental GLP-1 decreases with worsening glycemia, higher adiposity, liver fat, male sex, and reduced insulin sensitivity in the prediabetes cohort. Higher fasting total GLP-1 was associated with a low intake of wholegrain, fruit, and vegetables in people with prediabetes, and with a high intake of red meat and alcohol in people with diabetes. Conclusion These studies provide novel insights into the association between fasting and incremental GLP-1, metabolic traits of diabetes and obesity, and dietary intake, and raise intriguing questions regarding the relevance of fasting GLP-1 in the pathophysiology T2D. [ABSTRACT FROM AUTHOR]
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- 2024
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3. Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models
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Allesøe, Rosa Lundbye, Lundgaard, Agnete Troen, Hernández Medina, Ricardo, Aguayo-Orozco, Alejandro, Johansen, Joachim, Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, Lili, Biel, Jorge Hernansanz, Brasas, Valentas, Webel, Henry, Benros, Michael Eriksen, Pedersen, Anders Gorm, Chmura, Piotr Jaroslaw, Jacobsen, Ulrik Plesner, Mari, Andrea, Koivula, Robert, Mahajan, Anubha, Vinuela, Ana, Tajes, Juan Fernandez, Sharma, Sapna, Haid, Mark, Hong, Mun-Gwan, Musholt, Petra B., de Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, Gwen, Bell, Jimmy, Thomas, E. Louise, Frost, Gary, Thomsen, Henrik, Hansen, Elizaveta, Hansen, Tue Haldor, Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T., ‘t Hart, Leen M., Pattou, Francois, Raverdy, Violeta, Brage, Soren, Kokkola, Tarja, Heggie, Alison, McEvoy, Donna, Mourby, Miranda, Kaye, Jane, Hattersley, Andrew, McDonald, Timothy, Ridderstråle, Martin, Walker, Mark, Forgie, Ian, Giordano, Giuseppe N., Pavo, Imre, Ruetten, Hartmut, Pedersen, Oluf, Hansen, Torben, Dermitzakis, Emmanouil, Franks, Paul W., Schwenk, Jochen M., Adamski, Jerzy, McCarthy, Mark I., Pearson, Ewan, Banasik, Karina, Rasmussen, Simon, Brunak, S. ren, Froguel, Philippe, Thomas, Cecilia Engel, Haussler, Ragna, Beulens, Joline, Rutters, Femke, Nijpels, Giel, van Oort, Sabine, Groeneveld, Lenka, Elders, Petra, Giorgino, Toni, Rodriquez, Marianne, Nice, Rachel, Perry, Mandy, Bianzano, Susanna, Graefe-Mody, Ulrike, Hennige, Anita, Grempler, Rolf, Baum, Patrick, Stærfeldt, Hans-Henrik, Shah, Nisha, Teare, Harriet, Ehrhardt, Beate, Tillner, Joachim, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinevich, Iryna, Cabrelli, Louise, Loftus, Heather, Bizzotto, Roberto, Tura, Andrea, Dekkers, Koen, van Leeuwen, Nienke, Groop, Leif, Slieker, Roderick, Ramisch, Anna, Jennison, Christopher, McVittie, Ian, Frau, Francesca, Steckel-Hamann, Birgit, Adragni, Kofi, Thomas, Melissa, Pasdar, Naeimeh Atabaki, Fitipaldi, Hugo, Kurbasic, Azra, Mutie, Pascal, Pomares-Millan, Hugo, Bonnefond, Amelie, Canouil, Mickael, Caiazzo, Robert, Verkindt, Helene, Holl, Reinhard, Kuulasmaa, Teemu, Deshmukh, Harshal, Cederberg, Henna, Laakso, Markku, Vangipurapu, Jagadish, Dale, Matilda, Thorand, Barbara, Nicolay, Claudia, Fritsche, Andreas, Hill, Anita, Hudson, Michelle, Thorne, Claire, Allin, Kristine, Arumugam, Manimozhiyan, Jonsson, Anna, Engelbrechtsen, Line, Forman, Annemette, Dutta, Avirup, Sondertoft, Nadja, Fan, Yong, Gough, Stephen, Robertson, Neil, McRobert, Nicky, Wesolowska-Andersen, Agata, Brown, Andrew, Davtian, David, Dawed, Adem, Donnelly, Louise, Palmer, Colin, White, Margaret, Ferrer, Jorge, Whitcher, Brandon, Artati, Anna, Prehn, Cornelia, Adam, Jonathan, Grallert, Harald, Gupta, Ramneek, Sackett, Peter Wad, Nilsson, Birgitte, Tsirigos, Konstantinos, Eriksen, Rebeca, Jablonka, Bernd, Uhlen, Mathias, Gassenhuber, Johann, Baltauss, Tania, de Preville, Nathalie, Klintenberg, Maria, Abdalla, Moustafa, Lundgaard, Agnete Troen [0000-0001-7447-6560], Hernández Medina, Ricardo [0000-0001-6373-2362], Johansen, Joachim [0000-0001-7052-1870], Niu, Lili [0000-0003-4571-4368], Biel, Jorge Hernansanz [0000-0002-3125-2951], Benros, Michael Eriksen [0000-0003-4939-9465], Pedersen, Anders Gorm [0000-0001-9650-8965], Jacobsen, Ulrik Plesner [0000-0001-9181-6854], Koivula, Robert [0000-0002-1646-4163], Vinuela, Ana [0000-0003-3771-8537], Haid, Mark [0000-0001-6118-1333], Hong, Mun-Gwan [0000-0001-8603-8293], Kennedy, Gwen [0000-0002-9856-3236], Thomas, E Louise [0000-0003-4235-4694], Frost, Gary [0000-0003-0529-6325], Hansen, Tue Haldor [0000-0001-5948-8993], Kaye, Jane [0000-0002-7311-4725], Hattersley, Andrew [0000-0001-5620-473X], Ridderstråle, Martin [0000-0002-3270-9167], Pedersen, Oluf [0000-0002-3321-3972], Hansen, Torben [0000-0001-8748-3831], Schwenk, Jochen M [0000-0001-8141-8449], Rasmussen, Simon [0000-0001-6323-9041], Brunak, Søren [0000-0003-0316-5866], Apollo - University of Cambridge Repository, Epidemiology and Data Science, ACS - Diabetes & metabolism, APH - Health Behaviors & Chronic Diseases, General practice, ACS - Heart failure & arrhythmias, APH - Aging & Later Life, Graduate School, and APH - Methodology
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Biomedical Engineering ,Type 2 diabetes ,Bioengineering ,Applied Microbiology and Biotechnology ,Deep Learning ,SDG 3 - Good Health and Well-being ,Diabetes Mellitus, Type 2 ,Machine learning ,Molecular Medicine ,Humans ,Data integration ,IMI DIRECT Consortium ,Systems biology ,Algorithms ,Biotechnology - Abstract
The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug–omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug–drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.
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- 2023
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4. New Insights on the Interactions Between Insulin Clearance and the Main Glucose Homeostasis Mechanisms.
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Bizzotto, Roberto, Tricò, Domenico, Natali, Andrea, Gastaldelli, Amalia, Muscelli, Elza, De Fronzo, Ralph A., Arslanian, Silva, Ferrannini, Ele, and Mari, Andrea
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INSULIN , *GLUCOSE , *INSULIN resistance , *GLUCOSE tolerance tests , *TYPE 2 diabetes - Abstract
Objective: Endogenous insulin clearance (EIC) is physiologically reduced at increasing insulin secretion rate (ISR). Computing EIC at the prevailing ISR does not distinguish the effects of hypersecretion from those of other mechanisms of glucose homeostasis. We aimed to measure EIC in standardized ISR conditions (i.e., at fixed ISR levels) and to analyze its associations with relevant physiologic factors.Research Design and Methods: We estimated standardized EIC (EICISR) by mathematical modeling in nine different studies with insulin and glucose infusions (N = 2,067). EICISR association with various traits was analyzed by stepwise multivariable regression in studies with both euglycemic clamp and oral glucose tolerance test (OGTT) (N = 1,410). We also tested whether oral glucose ingestion, as opposed to intravenous infusion, has an independent effect on EIC (N = 1,555).Results: Insulin sensitivity (as M/I from the euglycemic clamp) is the strongest determinant of EICISR, approximately four times more influential than insulin resistance-related hypersecretion. EICISR independently associates positively with M/I, fasting and mean OGTT glucose or type 2 diabetes, and β-cell glucose sensitivity and negatively with African American or Hispanic race, female sex, and female age. With oral glucose ingestion, an ISR-independent ∼10% EIC reduction is necessary to explain the observed insulin concentration profiles.Conclusions: Based on EICISR, we posit the existence of two adaptive processes involving insulin clearance: the first reduces EICISR with insulin resistance (not with higher BMI per se) and is more relevant than the concomitant hypersecretion; the second reduces EICISR with β-cell dysfunction. These processes are dysregulated in type 2 diabetes. Finally, oral glucose ingestion per se reduces insulin clearance. [ABSTRACT FROM AUTHOR]- Published
- 2021
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5. Processes Underlying Glycemic Deterioration in Type 2 Diabetes: An IMI DIRECT Study.
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Bizzotto, Roberto, Jennison, Christopher, Jones, Angus G., Kurbasic, Azra, Tura, Andrea, Kennedy, Gwen, Bell, Jimmy D., Thomas, E. Louise, Frost, Gary, Eriksen, Rebeca, Koivula, Robert W., Brage, Soren, Kaye, Jane, Hattersley, Andrew T., Heggie, Alison, McEvoy, Donna, 't Hart, Leen M., Beulens, Joline W., Elders, Petra, and Musholt, Petra B.
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TYPE 2 diabetes , *GLUCAGON-like peptide 1 , *INSULIN sensitivity , *RECEIVER operating characteristic curves , *GLUCAGON-like peptides , *LIVER enzymes - Abstract
Objective: We investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D).Research Design and Methods: A total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), β-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA1c deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression.Results: Faster HbA1c progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles (R2 = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8-10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07-0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role.Conclusions: Deteriorating insulin sensitivity and β-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, β-cell function, and insulin clearance may be relevant to prevent progression. [ABSTRACT FROM AUTHOR]- Published
- 2021
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6. Mathematical Modeling for the Physiological and Clinical Investigation of Glucose Homeostasis and Diabetes.
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Mari, Andrea, Tura, Andrea, Grespan, Eleonora, and Bizzotto, Roberto
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TYPE 2 diabetes ,PHYSIOLOGICAL models ,GLUCOSE ,HOMEOSTASIS ,MATHEMATICAL models - Abstract
Mathematical modeling in the field of glucose metabolism has a longstanding tradition. The use of models is motivated by several reasons. Models have been used for calculating parameters of physiological interest from experimental data indirectly, to provide an unambiguous quantitative representation of pathophysiological mechanisms, to determine indices of clinical usefulness from simple experimental tests. With the growing societal impact of type 2 diabetes, which involves the disturbance of the glucose homeostasis system, development and use of models in this area have increased. Following the approaches of physiological and clinical investigation, the focus of the models has spanned from representations of whole body processes to those of cells, i.e., from in vivo to in vitro research. Model-based approaches for linking in vivo to in vitro research have been proposed, as well as multiscale models merging the two areas. The success and impact of models has been variable. Two kinds of models have received remarkable interest: those widely used in clinical applications, e.g., for the assessment of insulin sensitivity and β-cell function and some models representing specific aspects of the glucose homeostasis system, which have become iconic for their efficacy in describing clearly and compactly key physiological processes, such as insulin secretion from the pancreatic β cells. Models are inevitably simplified and approximate representations of a physiological system. Key to their success is an appropriate balance between adherence to reality, comprehensibility, interpretative value and practical usefulness. This has been achieved with a variety of approaches. Although many models concerning the glucose homeostasis system have been proposed, research in this area still needs to address numerous issues and tackle new opportunities. The mathematical representation of the glucose homeostasis processes is only partial, also because some mechanisms are still only partially understood. For in vitro research, mathematical models still need to develop their potential. This review illustrates the problems, approaches and contribution of mathematical modeling to the physiological and clinical investigation of glucose homeostasis and diabetes, focusing on the most relevant and stimulating models. [ABSTRACT FROM AUTHOR]
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- 2020
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7. Effect of single‐dose DPP‐4 inhibitor sitagliptin on β‐cell function and incretin hormone secretion after meal ingestion in healthy volunteers and drug‐naïve, well‐controlled type 2 diabetes subjects.
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Alsalim, Wathik, Ahrén, Bo, Göransson, Olga, Carr, Richard D., Bizzotto, Roberto, Tura, Andrea, Pacini, Giovanni, and Mari, Andrea
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SITAGLIPTIN ,TYPE 2 diabetes treatment ,PANCREATIC beta cells ,GLUCAGON-like peptide 1 ,CD26 antigen - Abstract
To explore the effects of a single dose of the DPP‐4 inhibitor sitagliptin on glucose‐standardized insulin secretion and β‐cell glucose sensitivity after meal ingestion, 12 healthy and 12 drug‐naïve, well‐controlled type 2 diabetes (T2D) subjects (mean HbA1c 43 mmol/mol, 6.2%) received sitagliptin (100 mg) or placebo before a meal (525 kcal). β‐cell function was measured as the insulin secretory rate at a standardized glucose concentration and the β‐cell glucose sensitivity (the slope between glucose and insulin secretory rate). Incretin levels were also monitored. Sitagliptin increased standardized insulin secretion, in both healthy and T2D subjects, compared to placebo, but without increasing β‐cell glucose sensitivity. Sitagliptin also increased active glucose‐dependent insulinotropic polypeptide (GIP) and glucagon‐like peptide‐1 (GLP‐1) and reduced total (reflecting the secretion) GIP, but not total GLP‐1 levels. We conclude that a single dose of DPP‐4 inhibition induces dissociated effects on different aspects of β‐cell function and incretin hormones after meal ingestion in both healthy and well‐controlled T2D subjects. [ABSTRACT FROM AUTHOR]
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- 2018
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8. Shift to Fatty Substrate Utilization in Response to Sodium-Glucose Cotransporter 2 Inhibition in Subjects Without Diabetes and Patients With Type 2 Diabetes.
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Ferrannini, Ele, Baldi, Simona, Frascerra, Silvia, Astiarraga, Brenno, Heise, Tim, Bizzotto, Roberto, Mari, Andrea, Pieber, Thomas R., and Muscelli, Elza
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GLYCOSURIA ,HOMEOSTASIS ,TYPE 2 diabetes ,SODIUM cotransport systems ,LIPIDS ,DRUG side effects - Abstract
Pharmacologically induced glycosuria elicits adaptive responses in glucose homeostasis and hormone release. In type 2 diabetes (T2D), along with decrements in plasma glucose and insulin levels and increments in glucagon release, sodium-glucose cotransporter 2 (SGLT2) inhibitors induce stimulation of endogenous glucose production (EGP) and a suppression of tissue glucose disposal (TGD). We measured fasting and postmeal glucose fluxes in 25 subjects without diabetes using a double glucose tracer technique; in these subjects and in 66 previously reported patients with T2D, we also estimated lipolysis (from [(2)H5]glycerol turnover rate and circulating free fatty acids, glycerol, and triglycerides), lipid oxidation (LOx; by indirect calorimetry), and ketogenesis (from circulating β-hydroxybutyrate concentrations). In both groups, empagliflozin administration raised EGP, lowered TGD, and stimulated lipolysis, LOx, and ketogenesis. The pattern of glycosuria-induced changes was similar in subjects without diabetes and in those with T2D but quantitatively smaller in the former. With chronic (4 weeks) versus acute (first dose) drug administration, glucose flux responses were attenuated, whereas lipid responses were enhanced; in patients with T2D, fasting β-hydroxybutyrate levels rose from 246 ± 288 to 561 ± 596 µmol/L (P < 0.01). We conclude that by shunting substantial amounts of carbohydrate into urine, SGLT2-mediated glycosuria results in a progressive shift in fuel utilization toward fatty substrates. The associated hormonal milieu (lower insulin-to-glucagon ratio) favors glucose release and ketogenesis. [ABSTRACT FROM AUTHOR]
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- 2016
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9. Lipid-induced glucose intolerance is driven by impaired glucose kinetics and insulin metabolism in healthy individuals.
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Tricò, Domenico, Mengozzi, Alessandro, Baldi, Simona, Bizzotto, Roberto, Olaniru, Oladapo, Toczyska, Klaudia, Huang, Guo Cai, Seghieri, Marta, Frascerra, Silvia, Amiel, Stephanie A., Persaud, Shanta, Jones, Peter, Mari, Andrea, and Natali, Andrea
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INSULIN ,GLUCOSE intolerance ,GLUCOSE ,GLUCOSE analysis ,GLUCOSE tolerance tests ,TYPE 2 diabetes - Abstract
Hypertriglyceridemia is associated with an increased risk of type 2 diabetes. We aimed to comprehensively examine the effects of hypertriglyceridemia on major glucose homeostatic mechanisms involved in diabetes progression. In this randomized, cross-over, single-blinded study, two dual-labeled, 3-hour oral glucose tolerance tests were performed during 5-hour intravenous infusions of either 20 % Intralipid or saline in 12 healthy subjects (age 27.9 ± 2.6 years, 11 men, BMI 22.6 ± 1.4 kg/m
2 ) to evaluate lipid-induced changes in insulin metabolism and glucose kinetics. Insulin sensitivity, β cell secretory function, and insulin clearance were assessed by modeling glucose, insulin and C-peptide data. Intestinal glucose absorption, endogenous glucose production, and glucose clearance were assessed from glucose tracers. The effect of triglycerides on β-cell secretory function was examined in perifusion experiments in murine pseudoislets and human pancreatic islets. Mild acute hypertriglyceridemia impaired oral glucose tolerance (mean glucose: +0.9 [0.3, 1.5] mmol/L, p = 0.008) and whole-body insulin sensitivity (Matsuda index: −1.67 [−0.50, −2.84], p = 0.009). Post-glucose hyperinsulinemia (mean insulin: +99 [17, 182] pmol/L, p = 0.009) resulted from reduced insulin clearance (−0.16 [−0.32, −0.01] L min−1 m−2 , p = 0.04) and enhanced hyperglycemia-induced total insulin secretion (+11.9 [1.1, 22.8] nmol/m2 , p = 0.02), which occurred despite a decline in model-derived β cell glucose sensitivity (−41 [−74, −7] pmol min−1 m−2 mmol−1 L, p = 0.04). The analysis of tracer-derived glucose metabolic fluxes during lipid infusion revealed lower glucose clearance (−96 [−152, −41] mL/kg FFM , p = 0.005), increased 2-hour oral glucose absorption (+380 [42, 718] μmol/kg FFM , p = 0.04) and suppressed endogenous glucose production (−448 [−573, −123] μmol/kg FFM , p = 0.005). High-physiologic triglyceride levels increased acute basal insulin secretion in murine pseudoislets (+11 [3, 19] pg/aliquot, p = 0.02) and human pancreatic islets (+286 [59, 512] pg/islet, p = 0.02). Our findings support a critical role for hypertriglyceridemia in the pathogenesis of type 2 diabetes in otherwise healthy individuals and dissect the glucose homeostatic mechanisms involved, encompassing insulin sensitivity, β cell function and oral glucose absorption. [Display omitted] • Mild acute hypertriglyceridemia has marked negative effects on oral glucose tolerance. • Mechanisms include whole body insulin resistance and faster glucose absorption. • These effects are attenuated by lipid-induced hyperinsulinemia. [ABSTRACT FROM AUTHOR]- Published
- 2022
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