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/lp/ou_press/cd36-modulates-fasting-and-preabsorptive-hormone-and-bile-acid-levels-3sFEBj0USm
- Publisher
- Oxford University Press
- Copyright
- Copyright © 2018 Endocrine Society
- ISSN
- 0021-972X
- eISSN
- 1945-7197
- DOI
- 10.1210/jc.2017-01982
- Publisher site
- See Article on Publisher Site
Abstract
Abstract Context Abnormal fatty acid (FA) metabolism contributes to diabetes and cardiovascular disease. The FA receptor CD36 has been linked to risk of metabolic syndrome. In rodents CD36 regulates various aspects of fat metabolism, but whether it has similar actions in humans is unknown. We examined the impact of a coding single-nucleotide polymorphism in CD36 on postprandial hormone and bile acid (BA) responses. Objective To examine whether the minor allele (G) of coding CD36 variant rs3211938 (G/T), which reduces CD36 level by ∼50%, influences hormonal responses to a high-fat meal (HFM). Design Obese African American (AA) women carriers of the G allele of rs3211938 (G/T) and weight-matched noncarriers (T/T) were studied before and after a HFM. Setting Two-center study. Participants Obese AA women. Intervention HFM. Main Outcome Measures Early preabsorptive responses (10 minutes) and extended excursions in plasma hormones [C-peptide, insulin, incretins, ghrelin fibroblast growth factor (FGF)19, FGF21], BAs, and serum lipoproteins (chylomicrons, very-low-density lipoprotein) were determined. Results At fasting, G-allele carriers had significantly reduced cholesterol and glycodeoxycholic acid and consistent but nonsignificant reductions of serum lipoproteins. Levels of GLP-1 and pancreatic polypeptide (PP) were reduced 60% to 70% and those of total BAs were 1.8-fold higher. After the meal, G-allele carriers displayed attenuated early (−10 to 10 minute) responses in insulin, C-peptide, GLP-1, gastric inhibitory peptide, and PP. BAs exhibited divergent trends in G allele carriers vs noncarriers concomitant with differential FGF19 responses. Conclusions CD36 plays an important role in the preabsorptive hormone and BA responses that coordinate brain and gut regulation of energy metabolism. Sustained elevations in serum levels of nonfasting or postprandial lipids are an independent risk factor for heart disease, diabetes, and stroke (1–3). A strong heritable component contributes to individual differences in these lipids and in susceptibility to diet-induced health complications (4–6). Dietary lipids are processed by the gut to generate triglyceride (TG)-rich lipoproteins [chylomicrons and very-low-density lipoproteins (VLDLs)] that are released into the circulation via the lymphatic network and then hydrolyzed in vascular beds by lipoprotein lipase to yield free fatty acids (FFAs) for uptake by tissues (7, 8). The fatty acid (FA) uptake process in rodents and humans is facilitated by the scavenger receptor CD36 (SR-B2) (9). CD36 also contributes via its ability to transduce intracellular signaling to the regulation of FA metabolism (10). The protein is abundant on the apical membrane of enterocytes in the small intestines, especially in the absorptive proximal segments (9). In rodents, CD36 deletion reduces FA and cholesterol uptake by the proximal small intestine, alters chylomicron generation, and reduces lipid secretion into the lymph (11). Additional proabsorptive roles of CD36 include mediation of orosensory fat taste perception (12–14) and enteroendocrine secretion of cholecystokinin and secretin (15). CD36 also regulates gallbladder function, and its deletion protects against gallstone formation (16). However, it remains unknown whether the findings in rodents can be translated to humans. The CD36 gene is highly polymorphic, and relatively common variants (5% to 45% frequency) have been identified that associate with interindividual variability of fasting and postprandial lipid levels (5) and/or with risk of metabolic syndrome (17, 18) and stroke (19). CD36-deficient mice lack orosensory fat perception and fat taste–induced secretions of pancreatic proteins and bile acids (BAs) (14), suggesting that CD36 signaling might be required for the preabsorptive phase of digestion. We explored the hypothesis that CD36 might play an important role in mediating the early regulatory responses that coordinate lipid absorption and tissue disposal of the absorbed lipid. Lipid absorption is a complex and highly regulated process (8, 9). In the intestinal lumen dietary fats (mainly TGs and phospholipids) are solubilized into micelles by BAs, digested by lipases, and the digestion products are internalized into enterocytes for repackaging into chylomicrons and VLDLs for export (20, 21). Upon anticipation of a meal or within minutes after its start, secretions can be measured, for example, in insulin (22, 23), BAs (12, 24), pancreatic polypeptide (PP), ghrelin, and GLP-1 (25–27). These secretions prepare the organism for incoming nutrients and play roles in absorption, satiety, and nutrient disposal. During fat intake, this early phase precedes significant absorption and is observed 10 to 30 minutes after the start of the meal (28, 29). It is induced by the sensing of FAs released by lipases in the mouth and duodenum (30) and serves to reduce the metabolic stress of nutrient fluctuations (31, 32). For example, the early phase of insulin release (5 to 10 minutes after onset of intake) is important for optimal glucose clearance by its ability to synchronize islets (23) by increasing blood flow to organs (33, 34) and enhancing insulin access to tissues (35). This early phase is impaired in prediabetics and patients with diabetes (26, 36) and its restoration improves glucose tolerance in people (37) and in mice with high-fat diet–induced insulin resistance (38). BAs, in addition to their fat-solubilizing role during digestion, exert metabolic regulation by activating their G-protein–coupled receptor TGR5, which is highly expressed in the small intestine and liver (39). BAs stimulate intestinal release of factors such as fibroblast growth factor (FGF)19, which modulates glucose and lipid metabolism and inhibits BA synthesis (40). In this study we examined the impact of partial CD36 deficiency on fat meal–induced release of various hormones and peptides, on the type and quantity of lipoproteins produced, and on changes in BA pool and species. The data indicate that reduced CD36 expression level is sufficient to markedly disrupt these responses and support a role of CD36 in determining a large part of the response to a meal. Materials and Methods Study participants and approvals African American participants were recruited and genotyped for the rs3211938 (G/T) coding single nucleotide polymorphism (SNP). None of the patients was related. This SNP, which reflects positive selection pressure, is almost exclusive to populations of African ancestry (minor allele frequency ∼20%). The SNP inserts a stop codon and results in a truncated protein that is degraded. Partial (∼50%) CD36 protein deficiency is observed in subjects carrying the G allele (G/T) of rs3211938 (41, 42), and complete CD36 deficiency is observed in subjects homozygous for the G allele (G/G) (18). Recruited study participants at Vanderbilt University had African ancestry based on four grandparents. Subjects were excluded when they had a history of cholecystectomy, bariatric surgery, severe chronic illness, type 2 diabetes mellitus, and cardiovascular disease other than hypertension. The primary outcome of the parent study (NCT02126735) was previously reported (41). We used existing samples from the parent study to address additional endpoints that may inform on the previous findings. Participants reported to the Vanderbilt Clinical Research Center for prescreening and blood collection. DNA was extracted, genotyped for rs3211938, and G-allele carriers and noncarriers were invited for a screening visit that included a medical history, physical examination, and laboratory analyses (blood cell count, metabolic panel, pregnancy test). Antihypertensive, lipid-lowering medications, vitamins, and antioxidants were discontinued 2 weeks prior to the study. Genomic DNA was extracted from peripheral blood with a salting-out precipitation (Gentra Puregene), and CD36 SNP rs3211938 was detected using a predesigned TaqMan SNP genotyping assay (Applied Biosystems) on a 7900HT instrument. Presence of the G allele reduces CD36 expression by 50% as previously determined by western blot analysis of monocyte and platelet CD36 protein using anti-CD36 antibody (FA6-152, Abcam) with human β-actin antibody (SC47778, Santa Cruz Biotechnology) bound by goat anti-mouse IgG (Li-COR Biosciences) as loading control (18, 41, 42). All studies adhered to principles of the Declaration of Helsinki and Title 45 of the US Code of Federal Regulations (Part 46, Protection of Human Subjects). Studies were approved by the Vanderbilt Institutional Review Board and conducted in accordance with institutional guidelines. All subjects provided informed consent. High-fat meal test All assessments were performed in the early morning in a quiet, temperature-controlled room (22 to 23°C). Subjects were asked not to exercise or drink alcohol at least 24 hours before the study. A staff person called to remind the patient to fast starting at 8:00 pm the day before. Baseline blood samples were collected for assessments of lipids, BAs, and hormones. Subjects were then instructed to consume a high-fat meal (HFM) in 10 minutes. The HFM consisted of a shake (43) with 700 calories/m2 body surface area (2.93 MJ/m2 body surface area). Proteins constituted 3% of calories, carbohydrates 14%, and fat 83%. Cholesterol content was 240 mg. Blood samples were collected at 10, 20, 30, 60, 120, 240, 360, and 480 minutes and were assessed for FFAs, TGs, BAs, and gastrointestinal hormones. At the end of the study, body composition was evaluated with an air displacement plethysmograph, the BOD POD (Life Measurement, Concord, CA). Clinical chemistry Blood collected in chilled EDTA tubes was immediately centrifuged to separate plasma, which was stored at −80°C. For serum, blood was allowed to clot at room temperature for 20 minutes, centrifuged, and the serum was removed and stored at −80°C. Plasma glucose was measured bedside (YSI Life Sciences, Yellow Springs, OH). Serum FFAs were measured using NEFA-HR(2) (Wako/Sopachem BV, Ochten, Netherlands), phospholipids and cholesterol using the appropriate kits (Wako), and TGs (Roche Diagnostics, Indianapolis, IN) by enzymatic colorimetry Cliniqa (R84098 TGs GPO, San Marcos, CA) adapted for microtiter plates. Lipoprotein characterization Lipoprotein subclass concentration and particle size in serum were assessed via proton nuclear magnetic resonance spectroscopy (Liposcience, Raleigh, NC) as previously described (44). BA analysis BAs were measured by liquid chromatography–mass spectrometry as previously described (45, 46) and as detailed in the Supplemental Information. For one individual, enough plasma was not available for BA analysis. Hormone measurements For GLP-1 measurement, plasma was supplemented with aprotinin (1000 KIU/mL) and dipeptidyl peptidase-4 inhibitor (DPP4-010; 20 μL/mL plasma; EMD Millipore, St. Charles, MO), and for ghrelin it was acidified with 1 N hydrochloric acid (50 μL/mL) and treated with phenylmethylsulfonyl fluoride (0.1 mg/mL). Plasma insulin, C-peptide, glucagon, gastric inhibitory peptide (GIP), active GLP-1 (7-37 and 7-36 amide), peptide YY, PP, and leptin were measured by multiplex immunoassay (Luminex xMAP, Millipore). Total ghrelin was determined by radioimmunoassay (Millipore). FGF19 and FGF21 were measured by enzyme-linked immunosorbent assay (R&D Systems, Minneapolis, MN). Statistical analysis Data are presented as means ± standard error of the mean (SEM). Data were log transformed prior to statistical testing when not normally distributed by the Shapiro–Wilks test. Summary data were analyzed by an unpaired, nonparametric, two-tailed Student t test. P values of <0.05 were considered significant. Time course data were analyzed by two-way repeated measure analysis of variance with interaction when normally distributed. Area under the curve (AUC) for TGs, FFAs, BAs, and lipoproteins were calculated using the trapezoid method. All analyses used Prism 6.05 (GraphPad Software, La Jolla, CA). Results Study subjects Twenty-five African American women were enrolled and 20 completed the study. Five were excluded for not meeting inclusion criteria. The participants were divided in two groups based on the CD36 rs3211938 genotype. Individuals homozygous for the major allele (T/T) have normal CD36 expression whereas those carrying the minor allele G (G/T) have ∼50% reduced CD36 expression in monocytes and platelets (18, 41, 42). No subjects were homozygous (G/G) in the cohort studied. There were no differences in age, weight, body mass index (BMI), and body composition measures (fat mass, fat-free mass) between groups (T/T vs G/T). Both groups were obese with BMI > 30 kg/m2 and were similarly insulin resistant: homeostatic model assessment of insulin resistance, 2.55 ± 0.49 and 2.72 ± 0.52, P = 0.81 (T/T vs G/T). G-allele vs T-allele carriers had significantly reduced fasting serum cholesterol (P = 0.009) whereas TG and phospholipid levels trended lower (P = 0.11 and 0.16, respectively) (Table 1). Table 1. Characteristics of Subjects Carrying the G Allele (G/T) of Coding SNP rs3211938 as Compared With Control Subjects (T/T) Variable G/T T/T P Value n 9 11 Age, 44.2 ± 3.4 40.6 ± 3.9 0.48 Weight, kg 99.6 ± 3.4 97.7 ± 4.0 0.81 BMI, kg/m2 36.2 ± 1.2 38.2 ± 1.4 0.58 Body fat percentage 54.3 ± 1.0 55.7 ± 3.1 0.68 Fat mass, kg 44.7 ± 2.5 45.7 ± 6.5 0.88 Fat-free mass, kg 45.7 ± 1.0 44.3 ± 3.1 0.65 Waist circumference, cm 105.1 ± 1.6 102.4 ± 1.3 0.80 Hip, cm 122.1 ± 3.0 122.4 ± 3.5 0.97 Thigh, cm 67.2 ± 2.6 69.4 ± 3.1 0.62 Fasting glucose, mg/dL 92.7 ± 2.7 93.5 ± 3.1 0.94 Fasting insulin, µU/mL 21.4 ± 6.2 22.4 ± 7.1 0.91 Fasting TG, mg/dL 55.7 ± 9.0 66.8 ± 10.0 0.11 Fasting phospholipids, mmol/L 135.2 ± 12.7 155.6 ± 7.4 0.16 Fasting cholesterol, mmol/L 6.6 ± 0.6 8.6 ± 1.0 0.009a Variable G/T T/T P Value n 9 11 Age, 44.2 ± 3.4 40.6 ± 3.9 0.48 Weight, kg 99.6 ± 3.4 97.7 ± 4.0 0.81 BMI, kg/m2 36.2 ± 1.2 38.2 ± 1.4 0.58 Body fat percentage 54.3 ± 1.0 55.7 ± 3.1 0.68 Fat mass, kg 44.7 ± 2.5 45.7 ± 6.5 0.88 Fat-free mass, kg 45.7 ± 1.0 44.3 ± 3.1 0.65 Waist circumference, cm 105.1 ± 1.6 102.4 ± 1.3 0.80 Hip, cm 122.1 ± 3.0 122.4 ± 3.5 0.97 Thigh, cm 67.2 ± 2.6 69.4 ± 3.1 0.62 Fasting glucose, mg/dL 92.7 ± 2.7 93.5 ± 3.1 0.94 Fasting insulin, µU/mL 21.4 ± 6.2 22.4 ± 7.1 0.91 Fasting TG, mg/dL 55.7 ± 9.0 66.8 ± 10.0 0.11 Fasting phospholipids, mmol/L 135.2 ± 12.7 155.6 ± 7.4 0.16 Fasting cholesterol, mmol/L 6.6 ± 0.6 8.6 ± 1.0 0.009a Values are means ± SEM. a P ≤ 0.01 by unpaired two-tailed Student t test. View Large Table 1. Characteristics of Subjects Carrying the G Allele (G/T) of Coding SNP rs3211938 as Compared With Control Subjects (T/T) Variable G/T T/T P Value n 9 11 Age, 44.2 ± 3.4 40.6 ± 3.9 0.48 Weight, kg 99.6 ± 3.4 97.7 ± 4.0 0.81 BMI, kg/m2 36.2 ± 1.2 38.2 ± 1.4 0.58 Body fat percentage 54.3 ± 1.0 55.7 ± 3.1 0.68 Fat mass, kg 44.7 ± 2.5 45.7 ± 6.5 0.88 Fat-free mass, kg 45.7 ± 1.0 44.3 ± 3.1 0.65 Waist circumference, cm 105.1 ± 1.6 102.4 ± 1.3 0.80 Hip, cm 122.1 ± 3.0 122.4 ± 3.5 0.97 Thigh, cm 67.2 ± 2.6 69.4 ± 3.1 0.62 Fasting glucose, mg/dL 92.7 ± 2.7 93.5 ± 3.1 0.94 Fasting insulin, µU/mL 21.4 ± 6.2 22.4 ± 7.1 0.91 Fasting TG, mg/dL 55.7 ± 9.0 66.8 ± 10.0 0.11 Fasting phospholipids, mmol/L 135.2 ± 12.7 155.6 ± 7.4 0.16 Fasting cholesterol, mmol/L 6.6 ± 0.6 8.6 ± 1.0 0.009a Variable G/T T/T P Value n 9 11 Age, 44.2 ± 3.4 40.6 ± 3.9 0.48 Weight, kg 99.6 ± 3.4 97.7 ± 4.0 0.81 BMI, kg/m2 36.2 ± 1.2 38.2 ± 1.4 0.58 Body fat percentage 54.3 ± 1.0 55.7 ± 3.1 0.68 Fat mass, kg 44.7 ± 2.5 45.7 ± 6.5 0.88 Fat-free mass, kg 45.7 ± 1.0 44.3 ± 3.1 0.65 Waist circumference, cm 105.1 ± 1.6 102.4 ± 1.3 0.80 Hip, cm 122.1 ± 3.0 122.4 ± 3.5 0.97 Thigh, cm 67.2 ± 2.6 69.4 ± 3.1 0.62 Fasting glucose, mg/dL 92.7 ± 2.7 93.5 ± 3.1 0.94 Fasting insulin, µU/mL 21.4 ± 6.2 22.4 ± 7.1 0.91 Fasting TG, mg/dL 55.7 ± 9.0 66.8 ± 10.0 0.11 Fasting phospholipids, mmol/L 135.2 ± 12.7 155.6 ± 7.4 0.16 Fasting cholesterol, mmol/L 6.6 ± 0.6 8.6 ± 1.0 0.009a Values are means ± SEM. a P ≤ 0.01 by unpaired two-tailed Student t test. View Large Fasting and postprandial lipids in rs3211938 carriers (G/T) and controls (T/T) Fasting serum lipoprotein distribution was similar for the two groups (Supplemental Table 1). G-allele carriers as compared with noncarriers displayed a trend toward lower serum levels (nmol/L) of total VLDL (26.4 ± 3.3 vs 34.6 ± 2.9, P = 0.08) and medium VLDL (2.3 ± 1.2 vs 7.8, P = 0.13) in G/T and T/T groups, respectively. Total low-density lipoprotein and high-density lipoprotein and relative content of respective subfractions were similar. The postprandial lipid response was assessed starting at 10 min and up to eight hours after the HFM. G-allele carriers and noncarriers had similar plasma glucose at fasting and levels did not change after the HFM (data not shown), which was low in carbohydrates. Serum TGs started rising at 60 minutes and peaked (2.5-fold) in both groups at 240 minutes after the HFM with similar excursion curves (P = 0.80; Fig. 1A). Free FA levels trended higher in G-allele carriers vs noncarriers at fasting and throughout the postmeal interval (Fig. 1B), with levels decreasing the first 120 minutes and returning to baseline by 480 minutes. TG-rich particles (VLDL plus chylomicron) (Fig. 1C) and medium VLDL (Fig. 1D) which trended lower at baseline in the G/T group as compared with the T/T group continued to trend lower throughout the postprandial study without reaching significance (details in Supplemental Table 2). Serum phospholipid and cholesterol levels were measured at baseline and 240 minutes after the HFM (Fig. 1E). Phospholipid levels were similar at baseline but were lower at 240 min in G-allele carriers G/T as compared with noncarriers. Cholesterol levels were significantly lower in G/T vs T/T subjects at fasting and at 240 minutes after the meal (Fig. 1F). Figure 1. View largeDownload slide Serum nutrient and lipoprotein responses to high-fat feeding in individuals carrying the G allele of rs3211938 (G/T) and control (T/T) noncarriers. (A) Serum TGs, (B) FFAs, (C) total VLDL and chylomicrons, and (D) medium VLDL particle concentrations in carriers compared with noncarriers are shown. (E) Serum phospholipid and (F) cholesterol concentrations at baseline and 240 minutes after an HFM are shown. Values shown as means ± SEM (n = 11 for T/T and n = 9 for G/T). *P ≤ 0.05 by unpaired, two-tailed Student t test. Figure 1. View largeDownload slide Serum nutrient and lipoprotein responses to high-fat feeding in individuals carrying the G allele of rs3211938 (G/T) and control (T/T) noncarriers. (A) Serum TGs, (B) FFAs, (C) total VLDL and chylomicrons, and (D) medium VLDL particle concentrations in carriers compared with noncarriers are shown. (E) Serum phospholipid and (F) cholesterol concentrations at baseline and 240 minutes after an HFM are shown. Values shown as means ± SEM (n = 11 for T/T and n = 9 for G/T). *P ≤ 0.05 by unpaired, two-tailed Student t test. Fasting and early preabsorptive hormone levels We investigated impact of CD36 insufficiency (rs3211938) on early fat-sensitive hormone release before significant absorption occurred and later as absorption proceeded after the HFM. After an overnight fast, plasma insulin and C-peptide levels did not differ between genotypes (Supplemental Table 3). PP was reduced ∼70% in G-allele carriers at baseline, but the difference fell short of significance (P = 0.07) due to levels in one G-allele subject. GLP-1 level was significantly (>70%) lower in G-allele carriers as compared with noncarriers. Fasting levels of acyl-ghrelin and glucagon trended lower at baseline in G-allele carriers whereas levels of GIP, leptin, and peptide YY were unaltered. After the HFM, insulin and C-peptide levels peaked at 60 minutes (Fig. 2A and 2B), concurrent with suppression of serum-free FA concentrations (seen in Fig. 1B), and were generally lower in G/T as compared with T/T subjects. The marked reductions in baseline levels of PP (Fig. 2C), GLP-1 (Fig. 2D), GIP (Fig. 2E), and ghrelin (Fig. 2F) observed in G/T as compared with T/T subjects were maintained for the study duration. However, differences in AUCs for the complete postprandial excursions (AUC0–360) of assayed hormones did not reach significance (Table 2). Figure 2. View largeDownload slide CD36 insufficiency alters the hormonal responses to an HFM. Plasma levels at −10 to 360 minutes after the meal of (A) C-peptide, (B) insulin, (C) PP, (D) GLP-1, (E) GIP, and (F) acyl-ghrelin in G-allele and T-allele carriers are shown. Early preabsorptive changes −10 to 10 minutes after the meal in levels of (G) C-peptide, (H) insulin , (I) PP, (J) GLP-1, (K) GIP, and (L) ghrelin are shown. Data are means ± SEM (n = 9 for G/T and n = 11 for T/T). *P ≤ 0.05, **P ≤ 0.01. Figure 2. View largeDownload slide CD36 insufficiency alters the hormonal responses to an HFM. Plasma levels at −10 to 360 minutes after the meal of (A) C-peptide, (B) insulin, (C) PP, (D) GLP-1, (E) GIP, and (F) acyl-ghrelin in G-allele and T-allele carriers are shown. Early preabsorptive changes −10 to 10 minutes after the meal in levels of (G) C-peptide, (H) insulin , (I) PP, (J) GLP-1, (K) GIP, and (L) ghrelin are shown. Data are means ± SEM (n = 9 for G/T and n = 11 for T/T). *P ≤ 0.05, **P ≤ 0.01. Table 2. Hormone AUC Values After HFM in Subjects Carrying CD36 rs3211938 (G/T) and Controls Variable AUC at 0–360 min AUC at 0–30 min G/T T/T P Value G/T T/T P Value n 9 11 9 11 Insulin 6,552 ± 1,100 8,978 ± 2,002 0.33 264.2 ± 121.5 477.4 ± 101.3 0.05a C-peptide 316,185 ± 31,814 394,952 ± 69,462 0.56 6,859 ± 2,790 16,158 ± 3,118 0.02a PP 26,674 ± 5,650 37,157 ± 10,183 0.52 2,175 ± 516.7 4,011 ± 1,124 0.24 GIP 174,796 ± 21,788 146,128 ± 10,780 0.23 1,467 ± 346.1 3,633 ± 724.2 0.02a GLP-1 10,222 ± 1,605 11,797 ± 1,947 0.55 363.0 ± 94.80 424.3 ± 104.1 0.68 Leptin 941,042 ± 211,253 1.08 × 106 ± 167,762 0.60 1.42 × 106 ± 200,987 1.51 × 106 ± 110,093 0.67 Glucagon 4,531 ± 987 5,449 ± 1,929 0.50 336.5 ± 98.46 435.2 ± 59.68 0.12 Ghrelin −7,609 ± 3,162 −8,856 ± 3,126 0.50 411.6 ± 132.2 524.6 ± 202.3 0.80 Peptide YY 17,924 ± 15,472 ± 3,328 0.33 657.1 ± 133.6 526.6 ± 155.8 0.53 Variable AUC at 0–360 min AUC at 0–30 min G/T T/T P Value G/T T/T P Value n 9 11 9 11 Insulin 6,552 ± 1,100 8,978 ± 2,002 0.33 264.2 ± 121.5 477.4 ± 101.3 0.05a C-peptide 316,185 ± 31,814 394,952 ± 69,462 0.56 6,859 ± 2,790 16,158 ± 3,118 0.02a PP 26,674 ± 5,650 37,157 ± 10,183 0.52 2,175 ± 516.7 4,011 ± 1,124 0.24 GIP 174,796 ± 21,788 146,128 ± 10,780 0.23 1,467 ± 346.1 3,633 ± 724.2 0.02a GLP-1 10,222 ± 1,605 11,797 ± 1,947 0.55 363.0 ± 94.80 424.3 ± 104.1 0.68 Leptin 941,042 ± 211,253 1.08 × 106 ± 167,762 0.60 1.42 × 106 ± 200,987 1.51 × 106 ± 110,093 0.67 Glucagon 4,531 ± 987 5,449 ± 1,929 0.50 336.5 ± 98.46 435.2 ± 59.68 0.12 Ghrelin −7,609 ± 3,162 −8,856 ± 3,126 0.50 411.6 ± 132.2 524.6 ± 202.3 0.80 Peptide YY 17,924 ± 15,472 ± 3,328 0.33 657.1 ± 133.6 526.6 ± 155.8 0.53 Values are means ± SEM. a P ≤ 0.05 by unpaired two-tailed Student t test. View Large Table 2. Hormone AUC Values After HFM in Subjects Carrying CD36 rs3211938 (G/T) and Controls Variable AUC at 0–360 min AUC at 0–30 min G/T T/T P Value G/T T/T P Value n 9 11 9 11 Insulin 6,552 ± 1,100 8,978 ± 2,002 0.33 264.2 ± 121.5 477.4 ± 101.3 0.05a C-peptide 316,185 ± 31,814 394,952 ± 69,462 0.56 6,859 ± 2,790 16,158 ± 3,118 0.02a PP 26,674 ± 5,650 37,157 ± 10,183 0.52 2,175 ± 516.7 4,011 ± 1,124 0.24 GIP 174,796 ± 21,788 146,128 ± 10,780 0.23 1,467 ± 346.1 3,633 ± 724.2 0.02a GLP-1 10,222 ± 1,605 11,797 ± 1,947 0.55 363.0 ± 94.80 424.3 ± 104.1 0.68 Leptin 941,042 ± 211,253 1.08 × 106 ± 167,762 0.60 1.42 × 106 ± 200,987 1.51 × 106 ± 110,093 0.67 Glucagon 4,531 ± 987 5,449 ± 1,929 0.50 336.5 ± 98.46 435.2 ± 59.68 0.12 Ghrelin −7,609 ± 3,162 −8,856 ± 3,126 0.50 411.6 ± 132.2 524.6 ± 202.3 0.80 Peptide YY 17,924 ± 15,472 ± 3,328 0.33 657.1 ± 133.6 526.6 ± 155.8 0.53 Variable AUC at 0–360 min AUC at 0–30 min G/T T/T P Value G/T T/T P Value n 9 11 9 11 Insulin 6,552 ± 1,100 8,978 ± 2,002 0.33 264.2 ± 121.5 477.4 ± 101.3 0.05a C-peptide 316,185 ± 31,814 394,952 ± 69,462 0.56 6,859 ± 2,790 16,158 ± 3,118 0.02a PP 26,674 ± 5,650 37,157 ± 10,183 0.52 2,175 ± 516.7 4,011 ± 1,124 0.24 GIP 174,796 ± 21,788 146,128 ± 10,780 0.23 1,467 ± 346.1 3,633 ± 724.2 0.02a GLP-1 10,222 ± 1,605 11,797 ± 1,947 0.55 363.0 ± 94.80 424.3 ± 104.1 0.68 Leptin 941,042 ± 211,253 1.08 × 106 ± 167,762 0.60 1.42 × 106 ± 200,987 1.51 × 106 ± 110,093 0.67 Glucagon 4,531 ± 987 5,449 ± 1,929 0.50 336.5 ± 98.46 435.2 ± 59.68 0.12 Ghrelin −7,609 ± 3,162 −8,856 ± 3,126 0.50 411.6 ± 132.2 524.6 ± 202.3 0.80 Peptide YY 17,924 ± 15,472 ± 3,328 0.33 657.1 ± 133.6 526.6 ± 155.8 0.53 Values are means ± SEM. a P ≤ 0.05 by unpaired two-tailed Student t test. View Large The early preabsorptive secretions were blunted in G-allele carriers. Significantly less secretion of C-peptide, insulin, GLP-1, and GIP was observed by 10 minutes (Fig. 2G, 2H, 2J and 2K, respectively). PP trended lower at 10 minutes and its levels were significantly lower between 10 and 30 minutes (P ≤ 0.05). Ghrelin also trended lower in G-allele carriers (Fig. 2L). There was similar suppression of plasma acyl-ghrelin in both groups starting at 30 minutes after the HFM and a return to levels slightly lower than baseline by 360 minutes (Fig. 2F). Leptin, peptide YY, and glucagon responded similarly in both groups (data not shown). Differences in AUC for early postprandial excursions (AUC0–30) of C-peptide, insulin, and GIP were significantly reduced in G-allele carriers (Table 2). The lower early (0 to 30 minutes) secretions of C-peptide, insulin, PP, GLP-1, and GIP are preabsorptive, as no rise in blood TG was detected before 60 minutes. Fasting and postprandial BA levels The BA pool is recycled several times during a meal. BAs transported by the ileum feedback to inhibit liver cholesterol 7α-hydroxylase 1 (CYP7A1), the rate-limiting enzyme of BA synthesis. Also, BA-induced secretion by ileal enteroendocrine cells of FGF19 inhibits CYP7A1 expression (40) and hepatic BA synthesis (Supplemental Fig. 1A). Changes in plasma BA species, BA classes (primary, secondary, conjugated, unconjugated, 12α-OH, and non–12α-OH), and ratios of various classes were compared at baseline (Supplemental Table 5) and from baseline to 360 minutes or 0 to 30 minutes after the HFM (Table 3). The BA measurements for G-allele carriers and noncarriers at all time points assayed are listed in Supplemental Table 6. Table 3. BA AUC Values After HFM in Subjects Carrying CD36 rs3211938 (G/T) and Controls Variable AUC at 0–360 min AUC at 0–30 min G/T T/T P Value G/T T/T P Value n 9 11 9 11 Total BAs 700,900 ± 83,687 800,810 ± 353,210 0.94 20,711 ± 5,790 −8,090 ± 8,527 0.009a 12α-OH 215,085 ± 37,407 135,078 ± 109,619 0.38 6,991 ± 2,904 −11,238 ± 6,286 0.01b Non–12α-OH 556,677 ± 68,422 772,958 ± 303,691 0.43 16,034 ± 3,941 3,977 ± 5,377 0.08 Conjugated 637,699 ± 83,349 711,210 ± 282,987 0.32 19,686 ± 5,698 −7,463 ± 6,789 0.007a Unconjugated 53,499 ± 35,740 76,978 ± 97,718 0.80 662 ± 616 −918 ± 3,705 0.62 Primary 27,571 ± 28,020 49,680 ± 54,856 0.70 286 ± 566 902 ± 1,735 0.70 Secondary 25,748 ± 12,176 27,360 ± 45,220 0.97 376 ± 350 −1,821 ± 2,426 0.31 Cholic acid −8,807 ± 12,799 −5,281 ± 13,186 0.85 −247 ± 375 143 ± 178 0.42 CDCA 37,216 ± 18,806 54,925 ± 44,199 0.69 533 ± 252 761 ± 1,782 0.88 DCA 8,948 ± 2,166 13,019 ± 5,381 0.45 271 ± 46 188 ± 76 0.34 GCA 9,784 ± 2,090 13,100 ± 4,644 0.65 364 ± 124 84.6 ± 54 0.16 GCDCA 278,613 ± 40,341 346,213 ± 94,480 0.61 8,405 ± 2,354 1,786 ± 1,122 0.04b GDCA 131,865 ± 26,477 −356 ± 71,378 0.07 4,184 ± 1,882 −12,714 ± 6,138 0.008a UDCA 8,052 ± 5,367 16,706 ± 16,360 0.58 233 ± 86 126 ± 70 0.37 GUDCA 37,953 ± 6,121 66,386 ± 47,360 0.44 1,325 ± 468 649 ± 536 0.35 TLCA 1,159 ± 550 1,650 ± 469 0.53 41 ± 21 13 ± 9 0.28 TCDCA 114,084 ± 21,332 182,268 ± 65,202 0.44 3,329 ± 871 1,751 ± 789 0.22 TDCA 70,881 ± 14,409 108,164 ± 45,286 0.50 2,314 ± 822 1,078 ± 522 0.04b Lithocholic acid 1,159 ± 550 1,650 ± 469 0.52 41 ± 21 13 ± 9 0.28 HDCA 7,535 ± 7,357 −3,451 ± 32,908 0.71 −163 ± 230 −2,344 ± 2,408 0.30 12α-OH/ non–12α-OH −33.6 ± 30.7 −246.6 ± 97.8 0.03b −1.1 ± 1.4 −18.5 ± 9.7 0.05b Conjugated/unconjugated −416.4 ± 139 −176.8 ± 134.7 0.25 −25.2 ± 8.1 14.7 ± 5.0 0.001a Primary/secondary −29.0 ± 130.2 190.0 ± 165.9 0.31 −2.7 ± 4.5 22.4 ± 18.8 0.15 Variable AUC at 0–360 min AUC at 0–30 min G/T T/T P Value G/T T/T P Value n 9 11 9 11 Total BAs 700,900 ± 83,687 800,810 ± 353,210 0.94 20,711 ± 5,790 −8,090 ± 8,527 0.009a 12α-OH 215,085 ± 37,407 135,078 ± 109,619 0.38 6,991 ± 2,904 −11,238 ± 6,286 0.01b Non–12α-OH 556,677 ± 68,422 772,958 ± 303,691 0.43 16,034 ± 3,941 3,977 ± 5,377 0.08 Conjugated 637,699 ± 83,349 711,210 ± 282,987 0.32 19,686 ± 5,698 −7,463 ± 6,789 0.007a Unconjugated 53,499 ± 35,740 76,978 ± 97,718 0.80 662 ± 616 −918 ± 3,705 0.62 Primary 27,571 ± 28,020 49,680 ± 54,856 0.70 286 ± 566 902 ± 1,735 0.70 Secondary 25,748 ± 12,176 27,360 ± 45,220 0.97 376 ± 350 −1,821 ± 2,426 0.31 Cholic acid −8,807 ± 12,799 −5,281 ± 13,186 0.85 −247 ± 375 143 ± 178 0.42 CDCA 37,216 ± 18,806 54,925 ± 44,199 0.69 533 ± 252 761 ± 1,782 0.88 DCA 8,948 ± 2,166 13,019 ± 5,381 0.45 271 ± 46 188 ± 76 0.34 GCA 9,784 ± 2,090 13,100 ± 4,644 0.65 364 ± 124 84.6 ± 54 0.16 GCDCA 278,613 ± 40,341 346,213 ± 94,480 0.61 8,405 ± 2,354 1,786 ± 1,122 0.04b GDCA 131,865 ± 26,477 −356 ± 71,378 0.07 4,184 ± 1,882 −12,714 ± 6,138 0.008a UDCA 8,052 ± 5,367 16,706 ± 16,360 0.58 233 ± 86 126 ± 70 0.37 GUDCA 37,953 ± 6,121 66,386 ± 47,360 0.44 1,325 ± 468 649 ± 536 0.35 TLCA 1,159 ± 550 1,650 ± 469 0.53 41 ± 21 13 ± 9 0.28 TCDCA 114,084 ± 21,332 182,268 ± 65,202 0.44 3,329 ± 871 1,751 ± 789 0.22 TDCA 70,881 ± 14,409 108,164 ± 45,286 0.50 2,314 ± 822 1,078 ± 522 0.04b Lithocholic acid 1,159 ± 550 1,650 ± 469 0.52 41 ± 21 13 ± 9 0.28 HDCA 7,535 ± 7,357 −3,451 ± 32,908 0.71 −163 ± 230 −2,344 ± 2,408 0.30 12α-OH/ non–12α-OH −33.6 ± 30.7 −246.6 ± 97.8 0.03b −1.1 ± 1.4 −18.5 ± 9.7 0.05b Conjugated/unconjugated −416.4 ± 139 −176.8 ± 134.7 0.25 −25.2 ± 8.1 14.7 ± 5.0 0.001a Primary/secondary −29.0 ± 130.2 190.0 ± 165.9 0.31 −2.7 ± 4.5 22.4 ± 18.8 0.15 Values are means ± SEM. Abbreviations: CDCA, chenodeoxycholic acid; GCA, glycolic acid; GCDCA, glycochenodeoxycholic acid; GUDCA, glycoursodeoxycholic acid; HDCA, hyodeoxycholic acid; TCDCA, taurochenodeoxycholic acid; TDCA, taurodeoxycholic acid; TLCA, taurolithocholic acid; UDCA, ursodeoxycholic acid. a P ≤ 0.01 by unpaired two-tailed Student t test. b P ≤ 0.05 by unpaired two-tailed Student t test. View Large Table 3. BA AUC Values After HFM in Subjects Carrying CD36 rs3211938 (G/T) and Controls Variable AUC at 0–360 min AUC at 0–30 min G/T T/T P Value G/T T/T P Value n 9 11 9 11 Total BAs 700,900 ± 83,687 800,810 ± 353,210 0.94 20,711 ± 5,790 −8,090 ± 8,527 0.009a 12α-OH 215,085 ± 37,407 135,078 ± 109,619 0.38 6,991 ± 2,904 −11,238 ± 6,286 0.01b Non–12α-OH 556,677 ± 68,422 772,958 ± 303,691 0.43 16,034 ± 3,941 3,977 ± 5,377 0.08 Conjugated 637,699 ± 83,349 711,210 ± 282,987 0.32 19,686 ± 5,698 −7,463 ± 6,789 0.007a Unconjugated 53,499 ± 35,740 76,978 ± 97,718 0.80 662 ± 616 −918 ± 3,705 0.62 Primary 27,571 ± 28,020 49,680 ± 54,856 0.70 286 ± 566 902 ± 1,735 0.70 Secondary 25,748 ± 12,176 27,360 ± 45,220 0.97 376 ± 350 −1,821 ± 2,426 0.31 Cholic acid −8,807 ± 12,799 −5,281 ± 13,186 0.85 −247 ± 375 143 ± 178 0.42 CDCA 37,216 ± 18,806 54,925 ± 44,199 0.69 533 ± 252 761 ± 1,782 0.88 DCA 8,948 ± 2,166 13,019 ± 5,381 0.45 271 ± 46 188 ± 76 0.34 GCA 9,784 ± 2,090 13,100 ± 4,644 0.65 364 ± 124 84.6 ± 54 0.16 GCDCA 278,613 ± 40,341 346,213 ± 94,480 0.61 8,405 ± 2,354 1,786 ± 1,122 0.04b GDCA 131,865 ± 26,477 −356 ± 71,378 0.07 4,184 ± 1,882 −12,714 ± 6,138 0.008a UDCA 8,052 ± 5,367 16,706 ± 16,360 0.58 233 ± 86 126 ± 70 0.37 GUDCA 37,953 ± 6,121 66,386 ± 47,360 0.44 1,325 ± 468 649 ± 536 0.35 TLCA 1,159 ± 550 1,650 ± 469 0.53 41 ± 21 13 ± 9 0.28 TCDCA 114,084 ± 21,332 182,268 ± 65,202 0.44 3,329 ± 871 1,751 ± 789 0.22 TDCA 70,881 ± 14,409 108,164 ± 45,286 0.50 2,314 ± 822 1,078 ± 522 0.04b Lithocholic acid 1,159 ± 550 1,650 ± 469 0.52 41 ± 21 13 ± 9 0.28 HDCA 7,535 ± 7,357 −3,451 ± 32,908 0.71 −163 ± 230 −2,344 ± 2,408 0.30 12α-OH/ non–12α-OH −33.6 ± 30.7 −246.6 ± 97.8 0.03b −1.1 ± 1.4 −18.5 ± 9.7 0.05b Conjugated/unconjugated −416.4 ± 139 −176.8 ± 134.7 0.25 −25.2 ± 8.1 14.7 ± 5.0 0.001a Primary/secondary −29.0 ± 130.2 190.0 ± 165.9 0.31 −2.7 ± 4.5 22.4 ± 18.8 0.15 Variable AUC at 0–360 min AUC at 0–30 min G/T T/T P Value G/T T/T P Value n 9 11 9 11 Total BAs 700,900 ± 83,687 800,810 ± 353,210 0.94 20,711 ± 5,790 −8,090 ± 8,527 0.009a 12α-OH 215,085 ± 37,407 135,078 ± 109,619 0.38 6,991 ± 2,904 −11,238 ± 6,286 0.01b Non–12α-OH 556,677 ± 68,422 772,958 ± 303,691 0.43 16,034 ± 3,941 3,977 ± 5,377 0.08 Conjugated 637,699 ± 83,349 711,210 ± 282,987 0.32 19,686 ± 5,698 −7,463 ± 6,789 0.007a Unconjugated 53,499 ± 35,740 76,978 ± 97,718 0.80 662 ± 616 −918 ± 3,705 0.62 Primary 27,571 ± 28,020 49,680 ± 54,856 0.70 286 ± 566 902 ± 1,735 0.70 Secondary 25,748 ± 12,176 27,360 ± 45,220 0.97 376 ± 350 −1,821 ± 2,426 0.31 Cholic acid −8,807 ± 12,799 −5,281 ± 13,186 0.85 −247 ± 375 143 ± 178 0.42 CDCA 37,216 ± 18,806 54,925 ± 44,199 0.69 533 ± 252 761 ± 1,782 0.88 DCA 8,948 ± 2,166 13,019 ± 5,381 0.45 271 ± 46 188 ± 76 0.34 GCA 9,784 ± 2,090 13,100 ± 4,644 0.65 364 ± 124 84.6 ± 54 0.16 GCDCA 278,613 ± 40,341 346,213 ± 94,480 0.61 8,405 ± 2,354 1,786 ± 1,122 0.04b GDCA 131,865 ± 26,477 −356 ± 71,378 0.07 4,184 ± 1,882 −12,714 ± 6,138 0.008a UDCA 8,052 ± 5,367 16,706 ± 16,360 0.58 233 ± 86 126 ± 70 0.37 GUDCA 37,953 ± 6,121 66,386 ± 47,360 0.44 1,325 ± 468 649 ± 536 0.35 TLCA 1,159 ± 550 1,650 ± 469 0.53 41 ± 21 13 ± 9 0.28 TCDCA 114,084 ± 21,332 182,268 ± 65,202 0.44 3,329 ± 871 1,751 ± 789 0.22 TDCA 70,881 ± 14,409 108,164 ± 45,286 0.50 2,314 ± 822 1,078 ± 522 0.04b Lithocholic acid 1,159 ± 550 1,650 ± 469 0.52 41 ± 21 13 ± 9 0.28 HDCA 7,535 ± 7,357 −3,451 ± 32,908 0.71 −163 ± 230 −2,344 ± 2,408 0.30 12α-OH/ non–12α-OH −33.6 ± 30.7 −246.6 ± 97.8 0.03b −1.1 ± 1.4 −18.5 ± 9.7 0.05b Conjugated/unconjugated −416.4 ± 139 −176.8 ± 134.7 0.25 −25.2 ± 8.1 14.7 ± 5.0 0.001a Primary/secondary −29.0 ± 130.2 190.0 ± 165.9 0.31 −2.7 ± 4.5 22.4 ± 18.8 0.15 Values are means ± SEM. Abbreviations: CDCA, chenodeoxycholic acid; GCA, glycolic acid; GCDCA, glycochenodeoxycholic acid; GUDCA, glycoursodeoxycholic acid; HDCA, hyodeoxycholic acid; TCDCA, taurochenodeoxycholic acid; TDCA, taurodeoxycholic acid; TLCA, taurolithocholic acid; UDCA, ursodeoxycholic acid. a P ≤ 0.01 by unpaired two-tailed Student t test. b P ≤ 0.05 by unpaired two-tailed Student t test. View Large G-allele carriers (G/T) had nearly twofold (1.8) increases in fasting total plasma BA (Supplemental Fig. 1B). These differences were largely due to increases in the secondary BA glycodeoxycholic acid (GDCA), a glycine-conjugated derivative of deoxycholic acid (DCA), the 12α-dehydroxylated form of primary cholic acid. Glycine conjugation and to a minor extent taurine conjugation occur in the liver following reabsorption of DCA and ursodeoxycholic acid. Plasma DCA levels were relatively low in both groups. Lithocholic acid, a lipophilic, toxic acid that is not reabsorbed and excreted in the feces, was significantly reduced in fasting G-allele carriers; however, the difference was modest by comparison with that observed with GDCA. Fasting ratios of conjugated/unconjugated BA (Supplemental Fig. 1C) and of 12α-hydroxylated/non–12α-hydroxylated BA (Supplemental Fig. 1D) were increased in G-allele carriers whereas the primary/secondary BA ratio was similar (Supplemental Fig. 1E). In the noncarriers (T/T) group, total BAs (Fig. 3A) as well as most individual BA species exhibited rapid changes (0 to 30 minutes) followed by monophasic increases, peaking at 120 to 240 minutes after the HFM (Supplemental Fig. 2; Supplemental Table 6). Postprandial AUC0–360 values for total BAs as well as individual species and fractions did not significantly differ between groups (Table 3). However, excursion curves were biphasic in G-allele carriers (G/T) with a rapid initial drop in levels followed by exaggerated increases above levels in T/T noncarriers. Figure 3. View largeDownload slide CD36 insufficiency alters fasting and HFM-stimulated BA levels and fasting levels of FGF19. (A) Plasma total BAs from −10 to 360 minutes after the HFM. Early changes (from −10 to 10 minutes) of (B) total BAs, (C) conjugated BAs, and (D) GDCA are shown. (E) Excursion curves of total BAs from −10 to 360 minutes after HFM. Early changes in (F) 12α-hydroxylated BAs and (G) 12α-hydroxylated/non–12α-hydroxylated ratio are shown. (H and I) Levels of FGF19 (H) and FGF21 (I) at 0 and 120 minutes after the HFM. n = 8 for G/T and n = 11 for T/T. *P ≤ 0.05, ***P ≤ 0.001, ****P ≤ 0.0001 by unpaired, two-tailed Student t test. Figure 3. View largeDownload slide CD36 insufficiency alters fasting and HFM-stimulated BA levels and fasting levels of FGF19. (A) Plasma total BAs from −10 to 360 minutes after the HFM. Early changes (from −10 to 10 minutes) of (B) total BAs, (C) conjugated BAs, and (D) GDCA are shown. (E) Excursion curves of total BAs from −10 to 360 minutes after HFM. Early changes in (F) 12α-hydroxylated BAs and (G) 12α-hydroxylated/non–12α-hydroxylated ratio are shown. (H and I) Levels of FGF19 (H) and FGF21 (I) at 0 and 120 minutes after the HFM. n = 8 for G/T and n = 11 for T/T. *P ≤ 0.05, ***P ≤ 0.001, ****P ≤ 0.0001 by unpaired, two-tailed Student t test. The early changes in BA responses to the HFM differed between groups. At 10 minutes after a meal, total BAs (Fig. 3B; P ≤ 0.0001) and conjugated BAs (Fig. 3C; P ≤ 0.001) were reduced in G/T as compared with T/T subjects, with the difference driven by a dramatic drop in the most abundant conjugated BA, GDCA (Fig. 3D; P ≤ 0.0001). In T/T subjects, postprandial GDCA concentrations increased steadily, peaking at 120 minutes, whereas in G/T subjects GDCA remained suppressed until 60 minutes and then increased, reaching levels that exceeded those in noncarriers (Fig. 3E). A similar, significant decrease was observed at 10 minutes after meal onset in 12α-hydroxylated BAs (Fig. 3F) and in the 12α-hydroxylated/non–12α-hydroxylated BA acid ratio in G/T vs T/T subjects (Fig. 3G). BA measurements at each time point assayed from 0 to 360 minutes after the HFM are shown in Supplemental Table 6. Significantly reduced BA AUC0–30 measurements for total BAs, 12α-hydroxylated BAs, conjugated BAs, glycochenodeoxycholic acid, GDCA, taurodeoxycholic acid, as well as the 12α-hydroxylated/non–12α-hydroxylated BA ratio and the conjugated/unconjugated BA ratio are listed in Table 3. Taken together, these data indicate that CD36 insufficiency alters the fasting BA profile, impairs early preabsorptive BA secretion, and alters BA excursions during absorption. The conjugated and 12α-hydroxylated BA species account for a large part of the changes observed in the total BA pool. We next examined whether the differences in the BA pool observed in subjects with CD36 insufficiency can be related to altered secretions of FGF19. At baseline, FGF19 levels were significantly lower in G/T vs T/T subjects (Fig. 3H; P = 0.02), and both groups showed significant and similar increases in FGF19 measured at 120 minutes after the HFM. The liver secretes FGF21, a growth factor that enhances BA synthesis by antagonizing the inhibitory effect of FGF19 on CYP7A1 expression (47). However, fasting and postprandial levels of FGF21 did not differ in G/T vs T/T subjects (Fig. 3I). Discussion This study documents an important role of CD36 in mediating the signaling pathways that coordinate brain and gut control of energy homeostasis. The preabsorptive hormonal and BA responses induced by a fat-rich meal serve to coordinate absorption and subsequent tissue metabolism of the absorbed lipid. These responses are significantly impaired in individuals carrying the G allele of coding SNP rs3211938, which reduces CD36 expression. In fasting, G-allele carriers (G/T) had 60% to 70% reductions in levels of GLP-1, PP, and ghrelin and with a 1.8-fold increase in total BA levels. After the fat meal, early (10 to 30 minutes) preabsorptive release of C-peptide, insulin, PP, GLP-1, and GIP was blunted in the G/T group as compared with the T/T group of noncarriers. Postprandial BA levels in the G/T group exhibited bimodal changes that diverged from the steady increases observed in controls (T/T). Thus, reduced CD36 level exerts profound influence on the coordinated metabolic response to a meal. Polymorphisms in the CD36 gene are relatively common (4% to 45%) and frequently impact CD36 expression (5). Several were identified to associate with altered levels of fasting lipids in African Americans (18) and whites (5). The coding SNP rs3299138 (G/T) is exclusive to populations of African ancestry and results in 50% lower CD36 levels in ∼20% of this population (42). In HyperGEN samples (n = ∼2020) of African Americans, the G allele associated with significantly lower fasting serum TG (18). Findings from the Genetics of Lipid Lowering Drugs and Diet Network study of postprandial lipids after a fatty meal in whites (n = 1117) identified CD36 promoter SNPs and DNA methylation sites that independently reduced CD36 expression in heart and adipose tissues and impacted postprandial lipids (5). The most significantly associated SNPs were in strong linkage disequilibrium with CD36 SNPs previously linked to metabolic syndrome risk (5). The present study participants were obese females with moderate insulin resistance. Presence of the G allele resulted in trends for lower fasting and postprandial TG and in significantly lower cholesterol levels. In contrast to promoter SNPs, which can impact CD36 in a tissue-specific fashion, the coding SNP studied here would impact its level in all tissues, including the small intestine and the lymphatic network where CD36 is normally abundant. Thus, the trends to lower lipid levels in G-allele carriers might reflect diminished absorption of dietary fat and reduced fat secretion into the lymph, as previously demonstrated in rodents (11), and they suggest that targeting intestinal CD36 might be beneficial for reducing serum lipids in obesity. CD36 insufficiency impaired HFM-induced preabsorptive responses of BAs, insulin, C-peptide, PP, and the incretins GLP-1 and GIP. In particular, the response of GLP-1 was dramatically reduced. To our knowledge, this is the first documentation of the role of CD36 in mediating the acute phase of insulin and incretin response to meal intake in humans. Because acute release of these factors is implicated in the ability to maintain long-term glycemia and insulin sensitivity, the findings suggest that additional studies are warranted to determine whether reduced CD36 expression can impact metabolism of dietary lipids and carbohydrates over the long term. The early release of insulin, C-peptide, BA, and PP at the onset of fat intake is induced by orosensory neural stimulation (30, 31, 48) whereas FA sensing by enteroendocrine cells mediates release of GLP-1 (49) and GIP (50). The present findings suggest that both orosensory and enteroendocrine FA sensing are impaired in individuals with CD36 insufficiency, and this will require further validation in larger cohorts and with other CD36 SNPs. G-allele carriers (G/T) had nearly twofold increases in fasting total plasma BAs with differences largely reflecting increases in the secondary conjugated GDCA. Selective hepatic recapture of conjugated BA by active BA transporters influences systemic BA levels. The higher GDCA in G/T subjects might be related to the reduced levels of FGF19/15, which disinhibit hepatic uptake of conjugated BA (51). The altered enterohepatic BA circulation, in particular the early postmeal BA drop in G/T subjects, might reflect abnormal gallbladder function. Hypercontractility of gallbladder tissue in response to acetylcholine and smaller gallbladder volumes were measured in CD36−/− mice, suggesting dysregulated bile emptying (16). The marked early postmeal drop in BA seen in G/T subjects could have contributed to the blunted GLP-1 response. Glycochenodeoxycholic acid (52) and other BA (53) augment nutrient-stimulated GLP-1 secretion through activating the BA receptor Gpbar1 (TGR5) in enteroendocrine cells (54). Our study has limitations that include the small sample size, which reflects the selection criteria applied to avoid confounding factors on lipid metabolism. Analyses were interpreted without adjustment for multiple testing, which may increase the possibility of chance findings. Additional studies that examine insulin-sensitive, lean subjects and include males would be important to dissect out obesity or sex-associated effects. The study participants, that is, obese, insulin-resistant, African American females, are an ethnic group at high risk of obesity-associated complications (55) and are representative of trends still prevalent in the United States and worldwide (56). Our data support the role of CD36 in the metabolic response to a meal and possibly for long-term maintenance of insulin sensitivity. However, in obese insulin-resistant subjects, partial CD36 loss might be beneficial, as it lowers fasting and postprandial lipids and increases BA levels, phenotypes associated with significant metabolic improvements (45, 46). Abbreviations: Abbreviations: AUC area under the curve BA bile acid BMI body mass index CYP7A1 cholesterol 7α-hydroxylase 1 DCA deoxycholic acid FA fatty acid FFA free fatty acid FGF fibroblast growth factor GDCA glycodeoxycholic acid GIP gastric inhibitory peptide HFM high-fat meal PP pancreatic polypeptide SEM standard error of the mean SNP single nucleotide polymorphism TG triglyceride VLDL very-low-density lipoprotein Acknowledgments We thank the nursing staff of the Vanderbilt University Clinical Research Center for help in performing the studies. Financial Support: This work was supported by American Heart Association Grant 10SDG4350042, National Institute of Diabetes and Digestive and Kidney Diseases Grants DK33301, DK060022 (to N.A.A.), DK100431 (to R.T.), DK37948, DK10937, DK105847 (to N.N.A. and C.R.F.), and K23HL103976 (to C.A.S), the Washington University Nutrition Obesity Research Center (supported by National Institute of Diabetes and Digestive and Kidney Diseases Grant DK56341, Vanderbilt Clinical and Translational Science Award UL1TR000445 from National Center for Advancing Translational Sciences/National Institutes of Health, and by a Doris Duke Foundation Clinical Scientist Career Development Award (to C.A.S). Clinical Trial Information: ClinicalTrials.gov no. NCT02126735 (registered 14 April 2014). Author Contributions: C.R.F. C.A.S, N.N.A, and N.A.A designed the study, reviewed all data analyses, and wrote the manuscript. C.R.F. and C.A.S. coordinated and supervised the studies and conducted data analysis. L.L.-G, T.P., and R.S. helped with data analysis. R.S. collated and analyzed the metabolic data. Y.W. and Y.X. collated and analyzed the BA data and edited the manuscript. R.T. reviewed the hormone data and edited the manuscript. J.E.C. collated the metabolic data, supervised the conduct of the study, and edited the manuscript. C.R.F. and C.A.S. are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for data integrity and accuracy of data analysis. Disclosure Summary: The authors have nothing to disclose. References 1. Mora S , Rifai N , Buring JE , Ridker PM . Fasting compared with nonfasting lipids and apolipoproteins for predicting incident cardiovascular events . Circulation . 2008 ; 118 ( 10 ): 993 – 1001 . Google Scholar CrossRef Search ADS PubMed 2. Nordestgaard BG , Varbo A . Triglycerides and cardiovascular disease . Lancet . 2014 ; 384 ( 9943 ): 626 – 635 . Google Scholar CrossRef Search ADS PubMed 3. Varbo A , Nordestgaard BG , Tybjaerg-Hansen A , Schnohr P , Jensen GB , Benn M . Nonfasting triglycerides, cholesterol, and ischemic stroke in the general population . Ann Neurol . 2011 ; 69 ( 4 ): 628 – 634 . Google Scholar CrossRef Search ADS PubMed 4. Irvin MR , Zhi D , Aslibekyan S , Claas SA , Absher DM , Ordovas JM , Tiwari HK , Watkins S , Arnett DK . Genomics of post-prandial lipidomic phenotypes in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study . PLoS One . 2014 ; 9 ( 6 ): e99509 . Google Scholar CrossRef Search ADS PubMed 5. Love-Gregory L , Kraja AT , Allum F , Aslibekyan S , Hedman AK , Duan Y , Borecki IB , Arnett DK , McCarthy MI , Deloukas P , Ordovas JM , Hopkins PN , Grundberg E , Abumrad NA . Higher chylomicron remnants and LDL particle numbers associate with common CD36 SNPs and DNA methylation sites that reduce CD36 . J Lipid Res . 2016 ; 57 ( 12 ): 2176 – 1284 . Google Scholar CrossRef Search ADS PubMed 6. Perez-Martinez P , Lopez-Miranda J , Perez-Jimenez F , Ordovas JM . Influence of genetic factors in the modulation of postprandial lipemia . Atheroscler Suppl . 2008 ; 9 ( 2 ): 49 – 55 . Google Scholar CrossRef Search ADS PubMed 7. Kohan A , Yoder S , Tso P . Lymphatics in intestinal transport of nutrients and gastrointestinal hormones . Ann N Y Acad Sci . 2010 ; 1207 ( Suppl 1 ): E44 – E51 . Google Scholar CrossRef Search ADS PubMed 8. Mansbach II CM , Siddiqi S . Control of chylomicron export from the intestine . Am J Physiol Gastrointest Liver Physiol . 2016 ; 310 ( 9 ): G659 – G668 . Google Scholar CrossRef Search ADS PubMed 9. Abumrad NA , Davidson NO . Role of the gut in lipid homeostasis . Physiol Rev . 2012 ; 92 ( 3 ): 1061 – 1085 . Google Scholar CrossRef Search ADS PubMed 10. Pepino MY , Kuda O , Samovski D , Abumrad NA . Structure-function of CD36 and importance of fatty acid signal transduction in fat metabolism . Annu Rev Nutr . 2014 ; 34 ( 1 ): 281 – 303 . Google Scholar CrossRef Search ADS PubMed 11. Drover VA , Ajmal M , Nassir F , Davidson NO , Nauli AM , Sahoo D , Tso P , Abumrad NA . CD36 deficiency impairs intestinal lipid secretion and clearance of chylomicrons from the blood . J Clin Invest . 2005 ; 115 ( 5 ): 1290 – 1297 . Google Scholar CrossRef Search ADS PubMed 12. Besnard P , Passilly-Degrace P , Khan NA . Taste of fat: a sixth taste modality ? Physiol Rev . 2016 ; 96 ( 1 ): 151 – 176 . Google Scholar CrossRef Search ADS PubMed 13. Dramane G , Abdoul-Azize S , Hichami A , Vögtle T , Akpona S , Chouabe C , Sadou H , Nieswandt B , Besnard P , Khan NA . STIM1 regulates calcium signaling in taste bud cells and preference for fat in mice . J Clin Invest . 2012 ; 122 ( 6 ): 2267 – 2282 . Google Scholar CrossRef Search ADS PubMed 14. Laugerette F , Passilly-Degrace P , Patris B , Niot I , Febbraio M , Montmayeur JP , Besnard P . CD36 involvement in orosensory detection of dietary lipids, spontaneous fat preference, and digestive secretions . J Clin Invest . 2005 ; 115 ( 11 ): 3177 – 3184 . Google Scholar CrossRef Search ADS PubMed 15. Sundaresan S , Shahid R , Riehl TE , Chandra R , Nassir F , Stenson WF , Liddle RA , Abumrad NA . CD36-dependent signaling mediates fatty acid-induced gut release of secretin and cholecystokinin . FASEB J . 2013 ; 27 ( 3 ): 1191 – 1202 . Google Scholar CrossRef Search ADS PubMed 16. Xie Y , Cifarelli V , Pietka T , Newberry EP , Kennedy SM , Khalifeh-Soltani A , Clugston R , Atabai K , Abumrad NA , Davidson NO . Cd36 knockout mice are protected against lithogenic diet induced gallstones . J Lipid Res . 2017 ; 58 ( 8 ): 1692 – 1701 . Google Scholar CrossRef Search ADS PubMed 17. Avery CL , He Q , North KE , Ambite JL , Boerwinkle E , Fornage M , Hindorff LA , Kooperberg C , Meigs JB , Pankow JS , Pendergrass SA , Psaty BM , Ritchie MD , Rotter JI , Taylor KD , Wilkens LR , Heiss G , Lin DY . A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains . PLoS Genet . 2011 ; 7 ( 10 ): e1002322 . Google Scholar CrossRef Search ADS PubMed 18. Love-Gregory L , Sherva R , Sun L , Wasson J , Schappe T , Doria A , Rao DC , Hunt SC , Klein S , Neuman RJ , Permutt MA , Abumrad NA . Variants in the CD36 gene associate with the metabolic syndrome and high-density lipoprotein cholesterol . Hum Mol Genet . 2008 ; 17 ( 11 ): 1695 – 1704 . Google Scholar CrossRef Search ADS PubMed 19. Ikram MA , Seshadri S , Bis JC , Fornage M , DeStefano AL , Aulchenko YS , Debette S , Lumley T , Folsom AR , van den Herik EG , Bos MJ , Beiser A , Cushman M , Launer LJ , Shahar E , Struchalin M , Du Y , Glazer NL , Rosamond WD , Rivadeneira F , Kelly-Hayes M , Lopez OL , Coresh J , Hofman A , DeCarli C , Heckbert SR , Koudstaal PJ , Yang Q , Smith NL , Kase CS , Rice K , Haritunians T , Roks G , de Kort PL , Taylor KD , de Lau LM , Oostra BA , Uitterlinden AG , Rotter JI , Boerwinkle E , Psaty BM , Mosley TH , van Duijn CM , Breteler MM , Longstreth WT Jr , Wolf PA . Genomewide association studies of stroke . N Engl J Med . 2009 ; 360 ( 17 ): 1718 – 1728 . Google Scholar CrossRef Search ADS PubMed 20. Nauli AM , Nassir F , Zheng S , Yang Q , Lo CM , Vonlehmden SB , Lee D , Jandacek RJ , Abumrad NA , Tso P . CD36 is important for chylomicron formation and secretion and may mediate cholesterol uptake in the proximal intestine . Gastroenterology . 2006 ; 131 ( 4 ): 1197 – 1207 . Google Scholar CrossRef Search ADS PubMed 21. Tytgat GN , Rubin CE , Saunders DR . Synthesis and transport of lipoprotein particles by intestinal absorptive cells in man . J Clin Invest . 1971 ; 50 ( 10 ): 2065 – 2078 . Google Scholar CrossRef Search ADS PubMed 22. Glendinning JI , Frim YG , Hochman A , Lubitz GS , Basile AJ , Sclafani A . Glucose elicits cephalic-phase insulin release in mice by activating KATP channels in taste cells . Am J Physiol Regul Integr Comp Physiol . 2017 ; 312 ( 4 ): R597 – R610 . Google Scholar CrossRef Search ADS PubMed 23. Ahrén B . Autonomic regulation of islet hormone secretion—implications for health and disease . Diabetologia . 2000 ; 43 ( 4 ): 393 – 410 . Google Scholar CrossRef Search ADS PubMed 24. Scott RB , Tan DT . Neural modulation of canine duodenal bile acid delivery in the interdigestive and postprandial periods . Am J Physiol . 1993 ; 264 ( 2 Pt 1 ): G357 – G366 . Google Scholar PubMed 25. Berthoud HR , Trimble ER , Siegel EG , Bereiter DA , Jeanrenaud B . Cephalic-phase insulin secretion in normal and pancreatic islet-transplanted rats . Am J Physiol . 1980 ; 238 ( 4 ): E336 – E340 . Google Scholar PubMed 26. Glasbrenner B , Bruckel J , Gritzmann R , Adler G . Cephalic phase of pancreatic polypeptide release: a valid test of autonomic neuropathy in diabetics ? Diabetes Res Clin Pract . 1995 ; 30 ( 2 ): 117 – 123 . Google Scholar CrossRef Search ADS PubMed 27. Kokrashvili Z , Yee KK , Ilegems E , Iwatsuki K , Li Y , Mosinger B , Margolskee RF . Endocrine taste cells . Br J Nutr . 2014 ; 111 ( S1 , Suppl 1 ) S23 – S29 . Google Scholar CrossRef Search ADS PubMed 28. Lambert JE , Parks EJ . Postprandial metabolism of meal triglyceride in humans . Biochim Biophys Acta. 2012 ; 1821 ( 5 ): 721 – 726 . Google Scholar CrossRef Search ADS PubMed 29. Chavez-Jauregui RN , Mattes RD , Parks EJ . Dynamics of fat absorption and effect of sham feeding on postprandial lipema . Gastroenterology . 2010 ; 139 ( 5 ): 1538 – 1548 . Google Scholar CrossRef Search ADS PubMed 30. Niot I , Besnard P . Appetite control by the tongue-gut axis and evaluation of the role of CD36/SR-B2 . Biochimie . 2017 ; 136 : 27 – 32 . Google Scholar CrossRef Search ADS PubMed 31. Teff KL . How neural mediation of anticipatory and compensatory insulin release helps us tolerate food . Physiol Behav . 2011 ; 103 ( 1 ): 44 – 50 . Google Scholar CrossRef Search ADS PubMed 32. Siegel EG , Trimble ER , Renold AE , Berthoud HR . Importance of preabsorptive insulin release on oral glucose tolerance: studies in pancreatic islet transplanted rats . Gut . 1980 ; 21 ( 11 ): 1002 – 1009 . Google Scholar CrossRef Search ADS PubMed 33. Buss C , Kraemer-Aguiar LG , Maranhão PA , Marinho C , de Souza M , Wiernsperger N , Bouskela E . Novel findings in the cephalic phase of digestion: a role for microcirculation ? Physiol Behav . 2012 ; 105 ( 4 ): 1082 – 1087 . Google Scholar CrossRef Search ADS PubMed 34. Eguchi K , Kashima H , Yokota A , Miura K , Yamaoka Endo M , Hirano H , Tsuji T , Fukuba Y . Acute effect of oral sensation of sweetness on celiac artery blood flow and gastric myoelectrical activity in humans . Auton Neurosci . 2016 ; 197 : 41 – 45 . Google Scholar CrossRef Search ADS PubMed 35. Getty L , Hamilton-Wessler M , Ader M , Dea MK , Bergman RN . Biphasic insulin secretion during intravenous glucose tolerance test promotes optimal interstitial insulin profile . Diabetes . 1998 ; 47 ( 12 ): 1941 – 1947 . Google Scholar CrossRef Search ADS PubMed 36. Thorens B . Neural regulation of pancreatic islet cell mass and function . Diabetes Obes Metab . 2014 ; 16 ( S1 , Suppl 1 ) 87 – 95 . Google Scholar CrossRef Search ADS PubMed 37. Bruttomesso D , Pianta A , Mari A , Valerio A , Marescotti MC , Avogaro A , Tiengo A , Del Prato S . Restoration of early rise in plasma insulin levels improves the glucose tolerance of type 2 diabetic patients . Diabetes . 1999 ; 48 ( 1 ): 99 – 105 . Google Scholar CrossRef Search ADS PubMed 38. Kaihara KA , Dickson LM , Ellenbroek JH , Orr CM , Layden BT , Wicksteed B . PKA enhances the acute insulin response leading to the restoration of glucose control . Diabetes . 2015 ; 64 ( 5 ): 1688 – 1697 . Google Scholar CrossRef Search ADS PubMed 39. Guo C , Chen WD , Wang YD . TGR5, not only a metabolic regulator . Front Physiol . 2016 ; 7 : 646 . Google Scholar PubMed 40. Inagaki T , Choi M , Moschetta A , Peng L , Cummins CL , McDonald JG , Luo G , Jones SA , Goodwin B , Richardson JA , Gerard RD , Repa JJ , Mangelsdorf DJ , Kliewer SA . Fibroblast growth factor 15 functions as an enterohepatic signal to regulate bile acid homeostasis . Cell Metab . 2005 ; 2 ( 4 ): 217 – 225 . Google Scholar CrossRef Search ADS PubMed 41. Love-Gregory L , Sherva R , Schappe T , Qi JS , McCrea J , Klein S , Connelly MA , Abumrad NA . Common CD36 SNPs reduce protein expression and may contribute to a protective atherogenic profile . Hum Mol Genet . 2011 ; 20 ( 1 ): 193 – 201 . Google Scholar CrossRef Search ADS PubMed 42. Shibao CA , Celedonio JE , Ramirez CE , Love-Gregory L , Arnold AC , Choi L , Okamoto LE , Gamboa A , Biaggioni I , Abumrad NN , Abumrad NA . A common CD36 variant influences endothelial function and response to treatment with phosphodiesterase 5 inhibition . J Clin Endocrinol Metab . 2016 ; 101 ( 7 ): 2751 – 2758 . Google Scholar CrossRef Search ADS PubMed 43. Patsch JR , Miesenböck G , Hopferwieser T , Mühlberger V , Knapp E , Dunn JK , Gotto AM Jr , Patsch W . Relation of triglyceride metabolism and coronary artery disease. Studies in the postprandial state . Arterioscler Thromb . 1992 ; 12 ( 11 ): 1336 – 1345 . Google Scholar CrossRef Search ADS PubMed 44. Garcia AE , Kasim N , Tamboli RA , Gonzalez RS , Antoun J , Eckert EA , Marks-Shulman PA , Dunn J , Wattacheril J , Wallen T , Abumrad NN , Flynn CR . Lipoprotein profiles in class III obese Caucasian and African American women with nonalcoholic fatty liver disease . PLoS One . 2015 ; 10 ( 11 ): e0142676 Google Scholar CrossRef Search ADS PubMed 45. Albaugh VL , Flynn CR , Cai S , Xiao Y , Tamboli RA , Abumrad NN . Early increases in bile acids post Roux-en-Y gastric bypass are driven by insulin-sensitizing, secondary bile acids . J Clin Endocrinol Metab . 2015 ; 100 ( 9 ): E1225 – E1233 . Google Scholar CrossRef Search ADS PubMed 46. Flynn CR , Albaugh VL , Cai S , Cheung-Flynn J , Williams PE , Brucker RM , Bordenstein SR , Guo Y , Wasserman DH , Abumrad NN . Bile diversion to the distal small intestine has comparable metabolic benefits to bariatric surgery . Nat Commun . 2015 ; 6 ( 1 ): 7715 . Google Scholar CrossRef Search ADS PubMed 47. Zhang J , Gupte J , Gong Y , Weiszmann J , Zhang Y , Lee KJ , Richards WG , Li Y . Chronic over-expression of fibroblast growth factor 21 increases bile acid biosynthesis by opposing FGF15/19 action . EBioMedicine . 2017 ; 15 : 173 – 183 . Google Scholar CrossRef Search ADS PubMed 48. Ahrén B , Holst JJ . The cephalic insulin response to meal ingestion in humans is dependent on both cholinergic and noncholinergic mechanisms and is important for postprandial glycemia . Diabetes . 2001 ; 50 ( 5 ): 1030 – 1038 . Google Scholar CrossRef Search ADS PubMed 49. Liou AP , Lu X , Sei Y , Zhao X , Pechhold S , Carrero RJ , Raybould HE , Wank S . The G-protein–coupled receptor GPR40 directly mediates long-chain fatty acid-induced secretion of cholecystokinin . Gastroenterology . 2011 ; 140 ( 3 ): 903 – 912 . Google Scholar CrossRef Search ADS PubMed 50. Chu ZL , Carroll C , Alfonso J , Gutierrez V , He H , Lucman A , Pedraza M , Mondala H , Gao H , Bagnol D , Chen R , Jones RM , Behan DP , Leonard J . A role for intestinal endocrine cell-expressed g protein-coupled receptor 119 in glycemic control by enhancing glucagon-like peptide-1 and glucose-dependent insulinotropic peptide release . Endocrinology . 2008 ; 149 ( 5 ): 2038 – 2047 . Google Scholar CrossRef Search ADS PubMed 51. Slijepcevic D , Roscam Abbing RLP , Katafuchi T , Blank A , Donkers JM , van Hoppe S , de Waart DR , Tolenaars D , van der Meer JHM , Wildenberg M , Beuers U , Oude Elferink RPJ , Schinkel AH , van de Graaf SFJ . Hepatic uptake of conjugated bile acids is mediated by both sodium taurocholate cotransporting polypeptide and organic anion transporting polypeptides and modulated by intestinal sensing of plasma bile acid levels in mice . Hepatology . 2017 ; 66 ( 5 ): 1631 – 1643 . Google Scholar CrossRef Search ADS PubMed 52. Roberts RE , Glicksman C , Alaghband-Zadeh J , Sherwood RA , Akuji N , le Roux CW . The relationship between postprandial bile acid concentration, GLP-1, PYY and ghrelin . Clin Endocrinol (Oxf) . 2011 ; 74 ( 1 ): 67 – 72 . Google Scholar CrossRef Search ADS PubMed 53. Brighton CA , Rievaj J , Kuhre RE , Glass LL , Schoonjans K , Holst JJ , Gribble FM , Reimann F . Bile acids trigger GLP-1 release predominantly by accessing basolaterally located G protein–coupled bile acid receptors . Endocrinology . 2015 ; 156 ( 11 ): 3961 – 3970 . Google Scholar CrossRef Search ADS PubMed 54. Katsuma S , Hirasawa A , Tsujimoto G . Bile acids promote glucagon-like peptide-1 secretion through TGR5 in a murine enteroendocrine cell line STC-1 . Biochem Biophys Res Commun . 2005 ; 329 ( 1 ): 386 – 390 . Google Scholar CrossRef Search ADS PubMed 55. Samson R , Qi A , Jaiswal A , Le Jemtel TH , Oparil S . Obesity-associated hypertension: the upcoming phenotype in African-American women . Curr Hypertens Rep . 2017 ; 19 ( 5 ): 41 . Google Scholar CrossRef Search ADS PubMed 56. Morgen CS , Sørensen TI . Obesity: global trends in the prevalence of overweight and obesity . Nat Rev Endocrinol . 2014 ; 10 ( 9 ): 513 – 514 . Google Scholar CrossRef Search ADS PubMed Copyright © 2018 Endocrine Society
Journal
Journal of Clinical Endocrinology and Metabolism – Oxford University Press
Published: Mar 12, 2018