Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/ou_press/increased-plasma-proneurotensin-levels-identify-nafld-in-adults-with-cFf7UQ0782
- Publisher
- Oxford University Press
- Copyright
- Copyright © 2018 Endocrine Society
- ISSN
- 0021-972X
- eISSN
- 1945-7197
- DOI
- 10.1210/jc.2017-02751
- Publisher site
- See Article on Publisher Site
Abstract
Abstract Context Neurotensin (NT), an intestinal peptide released by fat ingestion, promotes lipid absorption; higher circulating NT levels are associated with type 2 diabetes (T2D), obesity, and cardiovascular disease. Whether NT is related to nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) has not been fully investigated. Objective To study the relationship between plasma proneurotensin 1 to 117 (pro-NT), a stable fragment of the NT precursor hormone, and the presence/severity of NAFLD/NASH and to unravel correlates of increased pro-NT levels. Design/Setting/Participants For this cross-sectional study, 60 obese individuals undergoing bariatric surgery for clinical purposes were recruited. The association between pro-NT and NAFLD was further investigated in 260 consecutive subjects referred to our outpatient clinics for metabolic evaluations, including liver ultrasonography. The study population underwent complete metabolic characterization; in the obese cohort, liver biopsies were performed during surgery. Main Outcome Measures Plasma pro-NT levels in relation to NAFLD/NASH. Results Obese subjects with biopsy-proven NAFLD (53%) had significantly higher plasma pro-NT than those without NAFLD (183.6 ± 81.4 vs 86.7 ± 56.8 pmol/L, P < 0.001). Greater pro-NT correlated with NAFLD presence (P < 0.001) and severity (P < 0.001), age, female sex, insulin resistance, and T2D. Higher pro-NT predicted NAFLD with an area under receiver operating characteristic curve of 0.836 [95% confidence interval (CI), 0.73 to 0.94; P < 0.001]. Belonging to the highest pro-NT quartile correlated with increased NAFLD risk (odds ratio, 2.62; 95% CI, 1.08 to 6.40) after adjustment for confounders. The association between higher pro-NT and NAFLD was confirmed in the second cohort independently from confounders. Conclusions Increased plasma pro-NT levels identify the presence/severity of NAFLD; in dysmetabolic individuals, NT may specifically promote hepatic fat accumulation through mechanisms likely related to increased insulin resistance. Nonalcoholic fatty liver disease (NAFLD) is a pathological condition characterized by the macrovesicular accumulation of triglycerides within hepatocytes (hepatic steatosis); in a number of cases, necroinflammatory activity and fibrosis coexist [nonalcoholic steatohepatitis (NASH)]; furthermore, cirrhosis and liver failure may occur in 20% to 25% of affected individuals (1, 2). Nowadays, NAFLD represents the most common cause of chronic liver disease in developed countries (3), being detectable in 20% to 30% of the general population (4, 5) in almost 75% of patients with type 2 diabetes (T2D) (6, 7) and in up to 90% of obese individuals with T2D (8, 9). In dysmetabolic conditions, NAFLD worsens inflammatory and metabolic outcomes (10–12) and is associated with a greater prevalence and severity of microvascular and macrovascular complications in patients with T2D (13–15). Indeed, NAFLD is universally recognized as an independent risk factor for cardiovascular mortality (16). Nowadays, despite the impressively high number of pharmacological interventions proposed, the identification of an effective therapy of NAFLD beyond standard lifestyle measures is still an open issue and represents a major challenge (17). Neurotensin (NT), a 13–amino acid peptide mainly secreted by neuroendocrine cells in the small intestine (18), displays an important role in regulating food ingestion and fat absorption (19). By doing so, NT influences energy balance and body weight (20). NT mainly acts as a neurotransmitter in the central nervous system and as a hormone in the periphery, exerting its physiological action by binding the specific NT receptors, NTSR1, NTSR12, and NTSR13 (21, 22). Experimental evidence has shown that the NT/NTSR1 system is involved in adaptive energy balance (23–25). Loss of the leptin action mediated by NT neurons coexpressing the long form of the leptin receptor determines overweight and impairs the ability to appropriately respond to energy deprivation in experimental mice (24), pointing out a crucial role of NT in mediating, among others, leptin (23–25) and ghrelin (25) pathways. Indeed, the leptin-mediated systems regulating appetite are controlled by NT-expressing neurons (23). In the periphery, NT influences body weight by controlling macronutrient absorption. Physiology studies have described an acute increase of intestinal NT release immediately after food ingestion, directly associated with meal fat content (26). In addition, several data have been produced on the role of NT in facilitating lipid digestion and fat absorption in the small intestine (27–29). The refined, complex control of energy balance exerted by NT at different levels provides a possible pathophysiological explanation about a correlation between its circulating levels and increased prevalence and incidence of obesity-related diseases (30, 31). In particular, within the large cohort of the Malmö Diet and Cancer Study (30), the fasting concentration of pro-NT, the circulating peptide secreted at equimolar levels to NT, was associated with the incidence of T2D, cardiovascular disease, breast cancer, and total and cardiovascular mortality (30). The association between pro-NT and incident major cardiovascular events has been confirmed in the Framingham Heart Study Offspring cohort, independently of the presence of traditional cardiovascular risk factors (31). Very recently, an extensive investigation on a putative causal role of NT in determining aberrant fat accumulation and metabolic diseases has been carried out (29), showing reduced intestinal fat absorption, along with protection from obesity and NAFLD, in NT-deficient mice fed with a high-fat diet. Furthermore, the same study demonstrated that in humans, higher plasma pro-NT levels were associated with features of insulin resistance and doubled the risk of developing obesity later in life in nonobese individuals. Despite the strong rationale behind and encouraging evidence from animal models, little is known on circulating pro-NT levels and NAFLD/NASH in humans. Therefore, aims of this study were to investigate the relationship between plasma NT concentration and the presence and severity of NAFLD/NASH in adult obese individuals with or without T2D and to determine clinical correlates of impaired NT levels in this population. Materials and Methods Population For these purposes, we recruited 60 consecutive obese candidates for bariatric surgery referring to the endocrinology and diabetes outpatient clinics of Sapienza University of Rome for preoperative evaluations. The presence of an association between circulating pro-NT levels and NAFLD was further explored in a cohort of individuals (n = 260) referring to the same outpatient clinics for metabolic evaluations, including upper abdomen ultrasonography (US) for assessing the presence of fatty liver. To be eligible for the study, all study participants had to fulfill the following criteria: male and female aged between 20 and 65 years; no history of current or past excessive alcohol drinking, as defined by an average daily consumption of alcohol >30 g/d in men and >20 g/d in women; negative tests for the presence of hepatitis B surface antigen and antibody to hepatitis C virus; absence of history and findings consistent with cirrhosis and other causes of liver diseases (autoimmune hepatitis, hemochromatosis, Wilson disease); and no treatment with drugs known to cause liver steatosis (e.g., corticosteroids, estrogens, methotrexate, tetracycline, calcium channel blockers, or amiodarone). Furthermore, patients belonging to the morbidly obese cohort had a clinical indication for bariatric surgery. All participants underwent a complete workup, including medical history collection, clinical examination, anthropometric measurements, and laboratory tests. Clinical and laboratory assessment Weight and height were measured with patients wearing light clothing and no shoes. Body mass index (BMI, kg/m2) was calculated as weight in kilograms divided by height in meters squared. Waist circumference was measured midway between the 12th rib and the iliac crest. Systemic systolic blood pressure and diastolic blood pressure were measured after 5 minutes of rest; three measurements were taken, and the average of the second and third measurements was recorded and used in the analyses. Individuals without a previously formulated diagnosis of diabetes mellitus underwent a standard oral glucose tolerance test measuring blood glucose and insulin at baseline and 30, 60, 90, and 120 minutes after glucose ingestion. A 12-hour overnight fasting blood sample was obtained before surgery for metabolic profiling. Fasting blood glucose (mg/dL), glycosylated hemoglobin (%, mmol/mol), total cholesterol (mg/dL), high-density lipoprotein cholesterol (mg/dL), triglycerides (mg/dL), aspartate aminotransferase (AST, IU/L), alanine aminotransferase (ALT, IU/L), and creatinine (mg/dL) were measured by centralized standard methods. Fasting blood insulin (IU/mL) was measured by radioimmunoassay (ADVIA Insulin Ready Pack 100; Bayer Diagnostics, Milan, Italy), with intra-assay and interassay coefficients of variation <5%. Low-density lipoprotein cholesterol value was obtained the Friedewald formula. For our purposes, we measured the circulating concentration of pro-NT in plasma frozen immediately after separation and stored at −80°C. Pro-NT was measured using a chemiluminometric sandwich immunoassay to detect pro-NT amino acids 1 to 117 as described previously (32). The analytical assay sensitivity (mean relative light units of 10 determinations of sheep serum plus two standard deviations) was 4.8 pmol proNT/L. The interassay (10 assay runs) coefficient of variability was 6.2% at 48 pmol proNT/L and 4.1% at 191 pmol/L. Recovery and dilution was >85% in a measurement range of 25 to 850 pmol/L. The homeostasis model assessment of insulin resistance and homeostasis model assessment of insulin secretion were calculated as previously described (33). Diabetes mellitus was defined according to the American Diabetes Association 2009 criteria (34) and metabolic syndrome (MS) by the modified National Cholesterol Education Program Adult Treatment Panel III criteria (35). Liver biopsy and histology Study patients underwent intraoperative liver biopsy during surgery for sleeve gastrectomy. All procedures were conducted in accordance with recommendations set by the American Association for the Study of Liver Diseases (36). Liver fragments were fixed in buffered formalin for 2 to 4 hours and embedded in paraffin, and sections were cut and stained with hematoxylin and eosin and Masson trichrome stains. A single pathologist (C.D.C.) blinded to patients’ medical history and biochemistry performed the overall histological evaluations. A minimum biopsy length of 15 mm or the presence of 10 complete portal tracts was required (37). Liver biopsy samples were classified based on the presence of NASH by Brunt et al. (38) and graded according to the NAFLD activity score (NAS) (39); fibrosis was quantified on the basis of the NASH Clinical Research Network Scoring System Definition (39). NAFLD assessment in individuals not candidates for surgery In individuals who were not candidates for surgery, NAFLD was evaluated through liver US. This was performed using an Esaote (Genoa, Italy) instrument with a convex 3.5-MHz probe by the same operator blinded to laboratory values. Liver steatosis was defined according to Saverymuttu et al. (40) on the basis of abnormally intense, high-level echoes arising from the hepatic parenchyma, liver-kidney difference in echo amplitude, echo penetration into the deep portion of the liver, and clarity of liver blood vessel structure. Statistics SPSS version 23 was used to perform statistical analyses. Continuous variables are reported as the mean ± standard deviation, and categorical variables are reported as percentages. The Student t test for continuous variables and χ2 test for categorical variables were used to compare mean values between two independent groups; skewed variables underwent natural logarithmic transformations before performing the analyses. Correlations between parameters were explored by Pearson (continuous variables) or Spearman (categorical variables) coefficients or by age-, sex-, and BMI-adjusted partial correlations. Histological parameters are expressed by ordinal scales for NAS and Steatosis Activity Fibrosis score (38). NAS was used as a continuous scale for activity assessment, and comparisons between more than two were obtained by a Bonferroni-adjusted analysis of variance test. The predictive value of plasma pro-NT for NAFLD identification was estimated by the area under the receiver operating characteristic curve, with a 95% confidence interval (CI). Multivariate logistic regression models were built to identify determinants of NAFLD (yes/no, dependent variable) in our study population, entering all the variables significantly associated with the bivariate analyses as covariates. Data are shown as mean ± standard deviation. For all the above, a two-tailed P value <0.05 was considered significant. To our knowledge, no study has investigated circulating pro-NT levels in relation to NAFLD. Therefore, to confirm the statistical power of this study, we performed a post hoc sample size calculation considering the mean pro-NT concentration in individuals with and without NAFLD, and we calculated that 15 patients per subgroup would be enough to reach the statistical significance with power = 90% and α error = 0.05. For all the above, a P value <0.05 was considered significant. The study protocol was reviewed and approved by the Ethics Committee of Policlinico Umberto I, Sapienza University of Rome and conducted in conformance with the Helsinki Declaration. Written consent was obtained from all patients before the study. Results Pro-NT and biopsy-proven NAFLD/NASH Within our study population, 32 of 60 patients (53%) had histological features of NAFLD; clinical and biochemical characteristics of the study population in relation to the presence of NAFLD are shown in Table 1, along with results from age-, sex-, and BMI-adjusted partial correlation analyses. Table 1. Clinical and Biochemical Characteristics of Patients With and Without Biopsy-Proven NAFLD Characteristic No NAFLD (n = 28) NAFLD (n = 32) Partial Correlation Coefficient (Adjusted for Age, Sex, and BMI) P Value Age, y 40.5 ± 12 43.2 ± 9.4 — NSa Sex, male (%) 61.5 32 — 0.03b BMI, kg/m2 43.5 ± 6.3 41.8 ± 4.3 — NSa Waist circumference, cm 129.4 ± 16.9 128 ± 7.7 −0.31 0.20 SBP, mm Hg 133 ± 8.4 124.4 ± 7.7 −0.26 0.17 DBP, mm Hg 85 ± 8.7 85.9 ± 22.1 −0.07 0.72 Total cholesterol, mg/dL 213 ± 140.4 171 ± 126 −0.32 0.07 HDL-C, mg/dL 52 ± 8.8 46.7 ± 10.2 −0.05 0.77 LDL-C, mg/dL 141.9 ± 26.6 121.1 ± 22.3 −0.40 0.03 Triglycerides, mg/dL 118 ± 70.3 134 ± 43.1 0.34 0.056 FBG, mg/dL 102.1 ± 45.3 102.5 ± 17.3 0.41 0.017 HbA1c, %, mmol/mol 5.2 ± 0.25 5.5 ± 0.48 0.33 0.07 AST, IU/L 22.1 ± 7.9 24.1 ± 10.4 0.14 0.44 ALT, IU/L 25.3 ± 17.2 32.7 ± 15.6 0.37 0.03 AST/ALT 0.99 ± 0.3 0.78 ± 0.2 −0.45 0.008 FBI, µU/L 20.3 ± 13.2 16 ± 11.2 0.24 0.23 HOMA-IR 3.6 ± 3.1 4.1 ± 3.2 0.29 0.14 HOMA-β% 123 ± 140.4 171 ± 126 0.09 0.67 T2D, % 11 13 0.23 0.19 Pro-NT, pmol/L 86.7 ± 56.8 183.6 ± 81.4 0.35 <0.001a; 0.039 Characteristic No NAFLD (n = 28) NAFLD (n = 32) Partial Correlation Coefficient (Adjusted for Age, Sex, and BMI) P Value Age, y 40.5 ± 12 43.2 ± 9.4 — NSa Sex, male (%) 61.5 32 — 0.03b BMI, kg/m2 43.5 ± 6.3 41.8 ± 4.3 — NSa Waist circumference, cm 129.4 ± 16.9 128 ± 7.7 −0.31 0.20 SBP, mm Hg 133 ± 8.4 124.4 ± 7.7 −0.26 0.17 DBP, mm Hg 85 ± 8.7 85.9 ± 22.1 −0.07 0.72 Total cholesterol, mg/dL 213 ± 140.4 171 ± 126 −0.32 0.07 HDL-C, mg/dL 52 ± 8.8 46.7 ± 10.2 −0.05 0.77 LDL-C, mg/dL 141.9 ± 26.6 121.1 ± 22.3 −0.40 0.03 Triglycerides, mg/dL 118 ± 70.3 134 ± 43.1 0.34 0.056 FBG, mg/dL 102.1 ± 45.3 102.5 ± 17.3 0.41 0.017 HbA1c, %, mmol/mol 5.2 ± 0.25 5.5 ± 0.48 0.33 0.07 AST, IU/L 22.1 ± 7.9 24.1 ± 10.4 0.14 0.44 ALT, IU/L 25.3 ± 17.2 32.7 ± 15.6 0.37 0.03 AST/ALT 0.99 ± 0.3 0.78 ± 0.2 −0.45 0.008 FBI, µU/L 20.3 ± 13.2 16 ± 11.2 0.24 0.23 HOMA-IR 3.6 ± 3.1 4.1 ± 3.2 0.29 0.14 HOMA-β% 123 ± 140.4 171 ± 126 0.09 0.67 T2D, % 11 13 0.23 0.19 Pro-NT, pmol/L 86.7 ± 56.8 183.6 ± 81.4 0.35 <0.001a; 0.039 Values are presented as mean ± standard deviation unless otherwise indicated. DBP, diastolic blood pressure; FBG, fasting blood glucose; FBI, fasting blood insulin; HbA1c, glycosylated hemoglobin; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, insulin resistance; HOMA-β, homeostasis model assessment of insulin secretion; LDL-C, low-density lipoprotein cholesterol; NS, not significant; SBP, systolic blood pressure. a Student t test. P values refer to the age-, sex-, and BMI-adjusted partial correlation analyses unless differently specified. b χ2 test. View Large Table 1. Clinical and Biochemical Characteristics of Patients With and Without Biopsy-Proven NAFLD Characteristic No NAFLD (n = 28) NAFLD (n = 32) Partial Correlation Coefficient (Adjusted for Age, Sex, and BMI) P Value Age, y 40.5 ± 12 43.2 ± 9.4 — NSa Sex, male (%) 61.5 32 — 0.03b BMI, kg/m2 43.5 ± 6.3 41.8 ± 4.3 — NSa Waist circumference, cm 129.4 ± 16.9 128 ± 7.7 −0.31 0.20 SBP, mm Hg 133 ± 8.4 124.4 ± 7.7 −0.26 0.17 DBP, mm Hg 85 ± 8.7 85.9 ± 22.1 −0.07 0.72 Total cholesterol, mg/dL 213 ± 140.4 171 ± 126 −0.32 0.07 HDL-C, mg/dL 52 ± 8.8 46.7 ± 10.2 −0.05 0.77 LDL-C, mg/dL 141.9 ± 26.6 121.1 ± 22.3 −0.40 0.03 Triglycerides, mg/dL 118 ± 70.3 134 ± 43.1 0.34 0.056 FBG, mg/dL 102.1 ± 45.3 102.5 ± 17.3 0.41 0.017 HbA1c, %, mmol/mol 5.2 ± 0.25 5.5 ± 0.48 0.33 0.07 AST, IU/L 22.1 ± 7.9 24.1 ± 10.4 0.14 0.44 ALT, IU/L 25.3 ± 17.2 32.7 ± 15.6 0.37 0.03 AST/ALT 0.99 ± 0.3 0.78 ± 0.2 −0.45 0.008 FBI, µU/L 20.3 ± 13.2 16 ± 11.2 0.24 0.23 HOMA-IR 3.6 ± 3.1 4.1 ± 3.2 0.29 0.14 HOMA-β% 123 ± 140.4 171 ± 126 0.09 0.67 T2D, % 11 13 0.23 0.19 Pro-NT, pmol/L 86.7 ± 56.8 183.6 ± 81.4 0.35 <0.001a; 0.039 Characteristic No NAFLD (n = 28) NAFLD (n = 32) Partial Correlation Coefficient (Adjusted for Age, Sex, and BMI) P Value Age, y 40.5 ± 12 43.2 ± 9.4 — NSa Sex, male (%) 61.5 32 — 0.03b BMI, kg/m2 43.5 ± 6.3 41.8 ± 4.3 — NSa Waist circumference, cm 129.4 ± 16.9 128 ± 7.7 −0.31 0.20 SBP, mm Hg 133 ± 8.4 124.4 ± 7.7 −0.26 0.17 DBP, mm Hg 85 ± 8.7 85.9 ± 22.1 −0.07 0.72 Total cholesterol, mg/dL 213 ± 140.4 171 ± 126 −0.32 0.07 HDL-C, mg/dL 52 ± 8.8 46.7 ± 10.2 −0.05 0.77 LDL-C, mg/dL 141.9 ± 26.6 121.1 ± 22.3 −0.40 0.03 Triglycerides, mg/dL 118 ± 70.3 134 ± 43.1 0.34 0.056 FBG, mg/dL 102.1 ± 45.3 102.5 ± 17.3 0.41 0.017 HbA1c, %, mmol/mol 5.2 ± 0.25 5.5 ± 0.48 0.33 0.07 AST, IU/L 22.1 ± 7.9 24.1 ± 10.4 0.14 0.44 ALT, IU/L 25.3 ± 17.2 32.7 ± 15.6 0.37 0.03 AST/ALT 0.99 ± 0.3 0.78 ± 0.2 −0.45 0.008 FBI, µU/L 20.3 ± 13.2 16 ± 11.2 0.24 0.23 HOMA-IR 3.6 ± 3.1 4.1 ± 3.2 0.29 0.14 HOMA-β% 123 ± 140.4 171 ± 126 0.09 0.67 T2D, % 11 13 0.23 0.19 Pro-NT, pmol/L 86.7 ± 56.8 183.6 ± 81.4 0.35 <0.001a; 0.039 Values are presented as mean ± standard deviation unless otherwise indicated. DBP, diastolic blood pressure; FBG, fasting blood glucose; FBI, fasting blood insulin; HbA1c, glycosylated hemoglobin; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, insulin resistance; HOMA-β, homeostasis model assessment of insulin secretion; LDL-C, low-density lipoprotein cholesterol; NS, not significant; SBP, systolic blood pressure. a Student t test. P values refer to the age-, sex-, and BMI-adjusted partial correlation analyses unless differently specified. b χ2 test. View Large Plasma pro-NT levels were significantly higher in patients with NAFLD than in those without NAFLD (183.6 ± 81.4 vs 86.7 ± 56.8 pmol/L, P < 0.001; Fig. 1A) and directly correlated with the diagnosis of NASH, severity of steatosis, intrahepatocyte ballooning, and, subsequently, higher NAS and Steatosis Activity Fibrosis score, as shown in Table 2. In particular, pro-NT levels were significantly higher throughout increasing NAS severity subgroups (P < 0.001; Fig. 1B), and this association was strongly significant after correcting for sex and age in the partial correlation analysis (r = 0.62, P < 0.001). Among clinical parameters, greater pro-NT levels correlated with age, female sex, T2D, and parameters associated with insulin resistance and impaired glucose metabolism, as detailed in Table 2. In contrast, no association was found for BMI and waist circumference. Figure 1. View largeDownload slide Plasma pro-NT levels according to the presence of (A) NAFLD and (B) NAS score. *Student t test. §Analysis of variance test. Bonferroni comparison between subgroups: NAS ≤2 vs #3 to 4 vs ^≥5; NAS 3 to 4 vs °≥5. Figure 1. View largeDownload slide Plasma pro-NT levels according to the presence of (A) NAFLD and (B) NAS score. *Student t test. §Analysis of variance test. Bonferroni comparison between subgroups: NAS ≤2 vs #3 to 4 vs ^≥5; NAS 3 to 4 vs °≥5. Table 2. Pro-NT Bivariate Correlation Analyses Characteristic Correlation Coefficient P Value Age 0.41 0.002 Sex (male/female) 0.34 0.005a BMI 0.03 0.85 Waist circumference −0.15 0.49 FBG 0.17 0.19 FBI 0.54 0.002 HbA1c 0.62 <0.001 Total cholesterol −0.20 0.17 HDL-C −0.09 0.54 LDL-C −0.28 0.065 Triglycerides 0.30 0.05 AST 0.02 0.86 ALT 0.09 0.56 Serum creatinine 0.37 0.005 HOMA-β% 0.69 0.003 HOMA-IR 0.47 0.009 NAFLD, yes/no 0.59 <0.001a SAF score 0.36 0.02a NAS: steatosis 0.34 0.037a NAS: intrahepatocyte ballooning 0.54 <0.001a NAS score 0.46 0.003a T2D, yes/no 0.31 0.02a Characteristic Correlation Coefficient P Value Age 0.41 0.002 Sex (male/female) 0.34 0.005a BMI 0.03 0.85 Waist circumference −0.15 0.49 FBG 0.17 0.19 FBI 0.54 0.002 HbA1c 0.62 <0.001 Total cholesterol −0.20 0.17 HDL-C −0.09 0.54 LDL-C −0.28 0.065 Triglycerides 0.30 0.05 AST 0.02 0.86 ALT 0.09 0.56 Serum creatinine 0.37 0.005 HOMA-β% 0.69 0.003 HOMA-IR 0.47 0.009 NAFLD, yes/no 0.59 <0.001a SAF score 0.36 0.02a NAS: steatosis 0.34 0.037a NAS: intrahepatocyte ballooning 0.54 <0.001a NAS score 0.46 0.003a T2D, yes/no 0.31 0.02a Pearson coefficient was applied for all the analyses unless otherwise indicated. Pro-NT is considered a continuous variable. Boldface indicates statistically significant correlations. Abbreviations: FBG, fasting blood glucose; FBI, fasting blood insulin; HbA1c, glycosylated hemoglobin; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, insulin resistance; HOMA-β, homeostasis model assessment of insulin secretion; LDL-C, low-density lipoprotein cholesterol; SAF, Steatosis Activity Fibrosis. a Spearman coefficient. View Large Table 2. Pro-NT Bivariate Correlation Analyses Characteristic Correlation Coefficient P Value Age 0.41 0.002 Sex (male/female) 0.34 0.005a BMI 0.03 0.85 Waist circumference −0.15 0.49 FBG 0.17 0.19 FBI 0.54 0.002 HbA1c 0.62 <0.001 Total cholesterol −0.20 0.17 HDL-C −0.09 0.54 LDL-C −0.28 0.065 Triglycerides 0.30 0.05 AST 0.02 0.86 ALT 0.09 0.56 Serum creatinine 0.37 0.005 HOMA-β% 0.69 0.003 HOMA-IR 0.47 0.009 NAFLD, yes/no 0.59 <0.001a SAF score 0.36 0.02a NAS: steatosis 0.34 0.037a NAS: intrahepatocyte ballooning 0.54 <0.001a NAS score 0.46 0.003a T2D, yes/no 0.31 0.02a Characteristic Correlation Coefficient P Value Age 0.41 0.002 Sex (male/female) 0.34 0.005a BMI 0.03 0.85 Waist circumference −0.15 0.49 FBG 0.17 0.19 FBI 0.54 0.002 HbA1c 0.62 <0.001 Total cholesterol −0.20 0.17 HDL-C −0.09 0.54 LDL-C −0.28 0.065 Triglycerides 0.30 0.05 AST 0.02 0.86 ALT 0.09 0.56 Serum creatinine 0.37 0.005 HOMA-β% 0.69 0.003 HOMA-IR 0.47 0.009 NAFLD, yes/no 0.59 <0.001a SAF score 0.36 0.02a NAS: steatosis 0.34 0.037a NAS: intrahepatocyte ballooning 0.54 <0.001a NAS score 0.46 0.003a T2D, yes/no 0.31 0.02a Pearson coefficient was applied for all the analyses unless otherwise indicated. Pro-NT is considered a continuous variable. Boldface indicates statistically significant correlations. Abbreviations: FBG, fasting blood glucose; FBI, fasting blood insulin; HbA1c, glycosylated hemoglobin; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, insulin resistance; HOMA-β, homeostasis model assessment of insulin secretion; LDL-C, low-density lipoprotein cholesterol; SAF, Steatosis Activity Fibrosis. a Spearman coefficient. View Large The presence of biopsy-proven NAFLD was associated with female sex (r = 0.31, P = 0.02), higher pro-NT (r = 0.56, P < 0.001), higher ALT (r = 0.30, P = 0.03), and lower AST/ALT (r = -0.37, P = 0.009). In the multivariate logistic regression analysis, higher pro-NT levels were associated with biopsy-proven NAFLD independently from possible confounders (Table 3). Higher pro-NT concentration predicts the presence of NAFLD, with an area under the receiver operating characteristic curve of 0.836 (95% CI, 0.73 to 0.94, P < 0.001; Fig. 2). Table 3. Multivariate Logistic Regression Analysis Characteristic B Standard Error Wald P Value Odds Ratio 95% CI Lower Limit Upper Limit Age −0.027 0.043 0.378 0.54 0.97 0.89 1.06 Sex (M/F) −2.146 1.281 2.807 0.09 0.12 0.01 1.44 AST/ALT −2.527 1.873 1.819 0.18 0.08 0.002 3.14 ALT, IU/L −0.010 0.032 0.106 0.74 0.99 0.93 1.05 Pro-NT, pmol/L 0.022 0.010 5.094 0.02 1.02 1.003 1.04 Constant 2.792 3.087 0.818 0.37 16.31 Characteristic B Standard Error Wald P Value Odds Ratio 95% CI Lower Limit Upper Limit Age −0.027 0.043 0.378 0.54 0.97 0.89 1.06 Sex (M/F) −2.146 1.281 2.807 0.09 0.12 0.01 1.44 AST/ALT −2.527 1.873 1.819 0.18 0.08 0.002 3.14 ALT, IU/L −0.010 0.032 0.106 0.74 0.99 0.93 1.05 Pro-NT, pmol/L 0.022 0.010 5.094 0.02 1.02 1.003 1.04 Constant 2.792 3.087 0.818 0.37 16.31 The presence of NAFLD is the dependent variable. Pro-NT is considered a continuous variable. Cox and Snell R2 = 0.412. View Large Table 3. Multivariate Logistic Regression Analysis Characteristic B Standard Error Wald P Value Odds Ratio 95% CI Lower Limit Upper Limit Age −0.027 0.043 0.378 0.54 0.97 0.89 1.06 Sex (M/F) −2.146 1.281 2.807 0.09 0.12 0.01 1.44 AST/ALT −2.527 1.873 1.819 0.18 0.08 0.002 3.14 ALT, IU/L −0.010 0.032 0.106 0.74 0.99 0.93 1.05 Pro-NT, pmol/L 0.022 0.010 5.094 0.02 1.02 1.003 1.04 Constant 2.792 3.087 0.818 0.37 16.31 Characteristic B Standard Error Wald P Value Odds Ratio 95% CI Lower Limit Upper Limit Age −0.027 0.043 0.378 0.54 0.97 0.89 1.06 Sex (M/F) −2.146 1.281 2.807 0.09 0.12 0.01 1.44 AST/ALT −2.527 1.873 1.819 0.18 0.08 0.002 3.14 ALT, IU/L −0.010 0.032 0.106 0.74 0.99 0.93 1.05 Pro-NT, pmol/L 0.022 0.010 5.094 0.02 1.02 1.003 1.04 Constant 2.792 3.087 0.818 0.37 16.31 The presence of NAFLD is the dependent variable. Pro-NT is considered a continuous variable. Cox and Snell R2 = 0.412. View Large Figure 2. View largeDownload slide Pro-NT area under the receiver operating characteristic (ROC) curve for NAFLD. Figure 2. View largeDownload slide Pro-NT area under the receiver operating characteristic (ROC) curve for NAFLD. Pro-NT and US-detected NAFLD Of the 260 consecutive individuals undergoing metabolic characterization and liver US, 60% (n = 157) had a diagnosis of NAFLD; patients with NAFLD had significantly higher plasma pro-NT levels than non-NAFLD individuals (190.78 ± 116.6 vs 154.3 ± 88.9 pmol/L, P = 0.003). Clinical and metabolic characteristics of this study cohort, according to the presence of NAFLD, are shown in Supplemental Data 1. In the bivariate analyses, greater pro-NT levels correlated with the presence of NAFLD (r = 0.19, P = 0.002), T2D (r = 0.25, P = 0.001), and female sex (r = 0.15, P = 0.05), whereas a trend toward a positive association that did not reach statistical significance was observed between higher pro-NT levels and the number of MS components (r = 0.11, P = 0.08). No association was found between pro-NT, age, and indexes of body adiposity, such as BMI and waist circumference (Supplemental Data 2). The multivariate logistic regression analysis confirmed that higher pro-NT correlated with the presence of NAFLD independently from age, sex, presence of T2D, and number of MS components (Supplemental Data 3). Discussion This study demonstrates the existence of an association between circulating pro-NT levels and the presence and severity of biopsy-proven NAFLD and NASH in obese adults. The relationship between higher pro-NT and NAFLD was confirmed in a larger population of adults with a diagnosis of fatty liver made with US examination but without signs of severe liver damage, thus reinforcing the evidence obtained in patients evaluated with liver histology. Recently Li et al. (29), in an extensive investigation on mechanisms behind the association between higher pro-NT and the development of obesity and cardiometabolic diseases (30, 31), found significantly reduced intestinal fat absorption in NT-deficient mice and protection toward high-fat diet-induced obesity, hepatic steatosis, and insulin resistance in comparison with wild-type mice (29). As NT-deficient mice (29), NTR3-deficient mice are protected from high-fat diet-induced obesity and fatty liver (41), indicating that NT-induced hepatic fat accumulation is mediated by both NTR1 and NTR3. In our study, higher pro-NT correlated with T2D and signatures of impaired glucose metabolism and insulin resistance, but not with adiposity per se, in line with previous reports (30, 31). NAFLD represents an established cardiovascular risk factor (16) and may determine and worsen insulin resistance, systemic inflammation (10), and metabolic complications of obesity (11, 12). Indeed, we observed a linear association between pro-NT, hepatic damage in NASH, and parameters related to glucose metabolism impairment. A possible weakness of this novel observation can be represented by the limited sample size of the cohort undergoing liver biopsy. However, obtaining samples for liver histology implies the use of invasive procedures, reasonably representing per se a limiting factor for study enrollment. On the other hand, all the study participants underwent accurate metabolic characterization; the study was monocentric, and all the procedures were performed by the same operator, strengthening the study design and the reliability of our results. Finally, the findings obtained in the main study population have been confirmed in an additional cohort undergoing hepatic US and metabolic phenotyping, reinforcing our results and making them applicable also in individuals with different degrees of body adiposity and nonclinically relevant hepatic damage. Indeed, the association between plasma pro-NT and different measurements of NAFLD broadens the clinical utility of our findings. Although the cross-sectional design of our study does not allow us to establish a causal nexus between these findings, it is plausible to hypothesize that increased pro-NT levels facilitate the absorption of fatty acids from the small intestine, promoting fat accumulation in specific sites, such as the liver. Thus, NT may lead to NAFLD/NASH in a dose-dependent manner and may act both directly and indirectly—through hepatic fat accumulation—in worsening insulin resistance and the metabolic profile. Gut hormone regulation is currently considered an appealing target for antiobesity treatment (42, 43); in this context, our findings are intriguing and may provide the basis for further investigation on novel therapeutic approaches to NAFLD. Moreover, pro-NT may represent a novel biomarker of NAFLD in individuals with and without obesity, with relevant implications in clinical practice. In conclusion, our study demonstrates for the first time, to our knowledge, that pro-NT levels predict the presence of biopsy-proven NAFLD in obese individuals and are associated with insulin resistance and a detrimental metabolic profile. Studies on larger cohorts and longitudinal designs are warranted to investigate the possible role of NT in the development, progression, and prognosis of NAFLD and NASH. Abbreviations: Abbreviations: ALT alanine aminotransferase AST aspartate aminotransferase BMI body mass index MS metabolic syndrome NAFLD nonalcoholic fatty liver disease NAS nonalcoholic fatty liver disease activity score NASH nonalcoholic steatohepatitis NT neurotensin pro-NT proneurotensin 1 to 117 T2D type 2 diabetes US ultrasonography Acknowledgments Financial Support: This study was founded by grants from Sapienza University (to M.G.C.). Author Contributions: I.B., O.M., M.O.-M., and M.G.C. conceived the study. I.B., M.G.C., F.L., D.C., and F.A.C. coordinated the study, oversaw patient recruitment, and finalized the data set. F.A.C., I.B., and D.C. oversaw collection and analysis of biological samples. M.O.-M. and O.M. performed the experiments. I.B., M.C.G., and O.M. performed the statistical analyses. G.S. performed all the liver biopsies. C.D.C. read all the biopsies and finalized the data set. and I.B. and M.G.C. drafted the paper, which was reviewed by all authors. All authors read and approved the final manuscript. Disclosure Summary: The authors have nothing to disclose. References 1. McCullough AJ . The clinical features, diagnosis and natural history of nonalcoholic fatty liver disease . Clin Liver Dis . 2004 ; 8 ( 3 ): 521 – 533, viii . Google Scholar CrossRef Search ADS PubMed 2. Farrell GC , Larter CZ . Nonalcoholic fatty liver disease: from steatosis to cirrhosis . Hepatology . 2006 ; 43 ( 2 , Suppl 1 ): S99 – S112 . Google Scholar CrossRef Search ADS PubMed 3. Clark JM , Brancati FL , Diehl AME . Nonalcoholic fatty liver disease: the most common cause of abnormal liver enzymes in the US population . Gastroenterology . 2011 ; 120 ( 5 , Suppl 1 ): A65 . Google Scholar CrossRef Search ADS 4. Browning JD , Szczepaniak LS , Dobbins R , Nuremberg P , Horton JD , Cohen JC , Grundy SM , Hobbs HH . Prevalence of hepatic steatosis in an urban population in the United States: impact of ethnicity . Hepatology . 2004 ; 40 ( 6 ): 1387 – 1395 . Google Scholar CrossRef Search ADS PubMed 5. Bedogni G , Miglioli L , Masutti F , Castiglione A , Crocè LS , Tiribelli C , Bellentani S . Incidence and natural course of fatty liver in the general population: the Dionysos study . Hepatology . 2007 ; 46 ( 5 ): 1387 – 1391 . Google Scholar CrossRef Search ADS PubMed 6. Leite NC , Salles GF , Araujo AL , Villela-Nogueira CA , Cardoso CR . Prevalence and associated factors of non-alcoholic fatty liver disease in patients with type-2 diabetes mellitus . Liver Int . 2009 ; 29 ( 1 ): 113 – 119 . Google Scholar CrossRef Search ADS PubMed 7. Gupte P , Amarapurkar D , Agal S , Baijal R , Kulshrestha P , Pramanik S , Patel N , Madan A , Amarapurkar A , Hafeezunnisa . Non-alcoholic steatohepatitis in type 2 diabetes mellitus . J Gastroenterol Hepatol . 2004 ; 19 ( 8 ): 854 – 858 . Google Scholar CrossRef Search ADS PubMed 8. Chalasani N , Younossi Z , Lavine JE , Diehl AM , Brunt EM , Cusi K , Charlton M , Sanyal AJ . The diagnosis and management of non-alcoholic fatty liver disease: practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association . Hepatology . 2012 ; 55 ( 6 ): 2005 – 2023 . Google Scholar CrossRef Search ADS PubMed 9. Tolman KG , Fonseca V , Dalpiaz A , Tan MH . Spectrum of liver disease in type 2 diabetes and management of patients with diabetes and liver disease . Diabetes Care . 2007 ; 30 ( 3 ): 734 – 743 . Google Scholar CrossRef Search ADS PubMed 10. Kotronen A , Westerbacka J , Bergholm R , Pietiläinen KH , Yki-Järvinen H . Liver fat in the metabolic syndrome . J Clin Endocrinol Metab . 2007 ; 92 ( 9 ): 3490 – 3497 . Google Scholar CrossRef Search ADS PubMed 11. Fabbrini E , Magkos F , Mohammed BS , Pietka T , Abumrad NA , Patterson BW , Okunade A , Klein S . Intrahepatic fat, not visceral fat, is linked with metabolic complications of obesity . Proc Natl Acad Sci USA . 2009 ; 106 ( 36 ): 15430 – 15435 . Google Scholar CrossRef Search ADS PubMed 12. Korenblat KM , Fabbrini E , Mohammed BS , Klein S . Liver, muscle, and adipose tissue insulin action is directly related to intrahepatic triglyceride content in obese subjects . Gastroenterology . 2008 ; 134 ( 5 ): 1369 – 1375 . Google Scholar CrossRef Search ADS PubMed 13. Lomonaco R , Bril F , Portillo-Sanchez P , Ortiz-Lopez C , Orsak B , Biernacki D , Lo M , Suman A , Weber MH , Cusi K . Metabolic impact of nonalcoholic steatohepatitis in obese patients with type 2 diabetes . Diabetes Care . 2016 ; 39 ( 4 ): 632 – 638 . Google Scholar CrossRef Search ADS PubMed 14. Mantovani A , Pernigo M , Bergamini C , Bonapace S , Lipari P , Pichiri I , Bertolini L , Valbusa F , Barbieri E , Zoppini G , Bonora E , Targher G . Nonalcoholic fatty liver disease is independently associated with early left ventricular diastolic dysfunction in patients with type 2 diabetes . PLoS One . 2015 ; 10 ( 8 ): e0135329 . Google Scholar CrossRef Search ADS PubMed 15. Targher G , Bertolini L , Rodella S , Zoppini G , Lippi G , Day C , Muggeo M . Non-alcoholic fatty liver disease is independently associated with an increased prevalence of chronic kidney disease and proliferative/laser-treated retinopathy in type 2 diabetic patients . Diabetologia . 2007 ; 51 ( 3 ): 444 – 450 . Google Scholar CrossRef Search ADS PubMed 16. Targher G , Day CP , Bonora E . Risk of cardiovascular disease in patients with nonalcoholic fatty liver disease . N Engl J Med . 2010 ; 363 ( 14 ): 1341 – 1350 . Google Scholar CrossRef Search ADS PubMed 17. Brodosi L , Marchignoli F , Petroni ML , Marchesini G . NASH: a glance at the landscape of pharmacological treatment . Ann Hepatol . 2016 ; 15 ( 5 ): 673 – 681 . Google Scholar PubMed 18. Goedert M , Emson PC . The regional distribution of neurotensin-like immunoreactivity in central and peripheral tissues of the cat . Brain Res . 1983 ; 272 ( 2 ): 291 – 297 . Google Scholar CrossRef Search ADS PubMed 19. Ferris CF , Hammer RA , Leeman SE . Elevation of plasma neurotensin during lipid perfusion of rat small intestine . Peptides . 1981 ; 2 ( Suppl 2 ): 263 – 266 . Google Scholar CrossRef Search ADS PubMed 20. Mazella J , Béraud-Dufour S , Devader C , Massa F , Coppola T . Neurotensin and its receptors in the control of glucose homeostasis . Front Endocrinol (Lausanne) . 2012 ; 3 : 143 . Google Scholar PubMed 21. Uhl GR , Snyder SH . Regional and subcellular distributions of brain neurotensin . Life Sci . 1976 ; 19 ( 12 ): 1827 – 1832 . Google Scholar CrossRef Search ADS PubMed 22. Vincent JP , Mazella J , Kitabgi P . Neurotensin and neurotensin receptors . Trends Pharmacol Sci . 1999 ; 20 ( 7 ): 302 – 309 . Google Scholar CrossRef Search ADS PubMed 23. Cui H , Cai F , Belsham DD . Leptin signaling in neurotensin neurons involves STAT, MAP kinases ERK1/2, and p38 through c-Fos and ATF1 . FASEB J . 2006 ; 20 ( 14 ): 2654 – 2656 . Google Scholar CrossRef Search ADS PubMed 24. Brown JA , Bugescu R , Mayer T , Gata-Garcia A , Kurt G , Woodworth HL . Loss of action via neurotensin-leptin receptor neurons disrupts leptin and ghrelin-mediated control of energy balance . Endocrinology . 2017 ; 158 ( 5 ): 1271 – 1288 . Google Scholar CrossRef Search ADS PubMed 25. Opland D , Sutton A , Woodworth H , Brown J , Bugescu R , Garcia A , Christensen L , Rhodes C , Myers M Jr , Leinninger G . Loss of neurotensin receptor-1 disrupts the control of the mesolimbic dopamine system by leptin and promotes hedonic feeding and obesity . Mol Metab . 2013 ; 2 ( 4 ): 423 – 434 . Google Scholar CrossRef Search ADS PubMed 26. Leeman SE , Carraway RE . Neurotensin: discovery, isolation, characterization, synthesis and possible physiological roles . Ann N Y Acad Sci . 1982 ; 400 ( 1 ): 1 – 16 . Google Scholar CrossRef Search ADS PubMed 27. Gui X , Carraway RE . Enhancement of jejunal absorption of conjugated bile acid by neurotensin in rats . Gastroenterology . 2001 ; 120 ( 1 ): 151 – 160 . Google Scholar CrossRef Search ADS PubMed 28. Gui X , Dobner PR , Carraway RE . Endogenous neurotensin facilitates enterohepatic bile acid circulation by enhancing intestinal uptake in rats . Am J Physiol Gastrointest Liver Physiol . 2001 ; 281 ( 6 ): G1413 – G1422 . Google Scholar CrossRef Search ADS PubMed 29. Li J , Song J , Zaytseva YY , Liu Y , Rychahou P , Jiang K , Starr ME , Kim JT , Harris JW , Yiannikouris FB , Katz WS , Nilsson PM , Orho-Melander M , Chen J , Zhu H , Fahrenholz T , Higashi RM , Gao T , Morris AJ , Cassis LA , Fan TW , Weiss HL , Dobner PR , Melander O , Jia J , Evers BM . An obligatory role for neurotensin in high-fat-diet-induced obesity . Nature . 2016 ; 533 ( 7603 ): 411 – 415 . Google Scholar CrossRef Search ADS PubMed 30. Melander O , Maisel AS , Almgren P , Manjer J , Belting M , Hedblad B , Engström G , Kilger U , Nilsson P , Bergmann A , Orho-Melander M . Plasma proneurotensin and incidence of diabetes, cardiovascular disease, breast cancer, and mortality . JAMA . 2012 ; 308 ( 14 ): 1469 – 1475 . Google Scholar CrossRef Search ADS PubMed 31. Januzzi JL Jr , Lyass A , Liu Y , Gaggin H , Trebnick A , Maisel AS , D’Agostino RB Sr , Wang TJ , Massaro J , Vasan RS . Circulating proneurotensin concentrations and cardiovascular disease events in the community: the Framingham Heart Study . Arterioscler Thromb Vasc Biol . 2016 ; 36 ( 8 ): 1692 – 1697 . Google Scholar CrossRef Search ADS PubMed 32. Ernst A , Hellmich S , Bergmann A . Proneurotensin 1-117, a stable neurotensin precursor fragment identified in human circulation . Peptides . 2006 ; 27 ( 7 ): 1787 – 1793 . Google Scholar CrossRef Search ADS PubMed 33. Matsuda M , DeFronzo RA . Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp . Diabetes Care . 1999 ; 22 ( 9 ): 1462 – 1470 . Google Scholar CrossRef Search ADS PubMed 34. American Diabetes Association . Standards of medical care in diabetes—2009 . Diabetes Care . 2008 ; 32 ( Suppl 1 ): S13 – S61 . 35. Grundy SM , Cleeman JI , Daniels SR , Donato KA , Eckel RH , Franklin BA , Gordon DJ , Krauss RM , Savage PJ , Smith SC Jr , Spertus JA , Costa F . Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Executive Summary . Circulation . 2005 ; 112 ( 17 ): e285 – e290 . Google Scholar CrossRef Search ADS 36. Rockey DC , Caldwell SH , Goodman ZD , Nelson RC , Smith AD ; American Association for the Study of Liver Diseases . Liver biopsy . Hepatology . 2008 ; 49 ( 3 ): 1017 – 1044 . Google Scholar CrossRef Search ADS 37. Colloredo G , Guido M , Sonzogni A , Leandro G . Impact of liver biopsy size on histological evaluation of chronic viral hepatitis: the smaller the sample, the milder the disease . J Hepatol . 2003 ; 39 ( 2 ): 239 – 244 . Google Scholar CrossRef Search ADS PubMed 38. Brunt EM , Janney CG , Di Bisceglie AM , Neuschwander-Tetri BA , Bacon BR . Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions . Am J Gastroenterol . 1999 ; 94 ( 9 ): 2467 – 2474 . Google Scholar CrossRef Search ADS PubMed 39. Kleiner DE , Brunt EM , Van Natta M , Behling C , Contos MJ , Cummings OW , Ferrell LD , Liu YC , Torbenson MS , Unalp-Arida A , Yeh M , McCullough AJ , Sanyal AJ ; Nonalcoholic Steatohepatitis Clinical Research Network . Design and validation of a histological scoring system for nonalcoholic fatty liver disease . Hepatology . 2005 ; 41 ( 6 ): 1313 – 1321 . Google Scholar CrossRef Search ADS PubMed 40. Saverymuttu SH , Joseph AE , Maxwell JD . Ultrasound scanning in the detection of hepatic fibrosis and steatosis . Br Med J (Clin Res Ed) . 1986 ; 292 ( 6512 ): 13 – 15 . Google Scholar CrossRef Search ADS PubMed 41. Rabinowich L , Fishman S , Hubel E , Thurm T , Park WJ , Pewzner-Jung Y , Saroha A , Erez N , Halpern Z , Futerman AH , Zvibel I . Sortilin deficiency improves the metabolic phenotype and reduces hepatic steatosis of mice subjected to diet-induced obesity . J Hepatol . 2015 ; 62 ( 1 ): 175 – 181 . Google Scholar CrossRef Search ADS PubMed 42. Sharkey KA . Targeting the gut to treat obesity and its metabolic consequences: view from the Chair . Int J Obes Suppl . 2016 ; 6 ( Suppl 1 ): S3 – S5 . Google Scholar CrossRef Search ADS PubMed 43. Crunkhorn S . Neurotensin inhibition prevents weight gain . Nat Rev Drug Discov . 2016 ; 15 ( 7 ): 453 . Google Scholar CrossRef Search ADS PubMed Copyright © 2018 Endocrine Society
Journal
Journal of Clinical Endocrinology and Metabolism – Oxford University Press
Published: Mar 23, 2018