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Circulating betatrophin in healthy control and type 2 diabetic subjects and its association with metabolic parameters
Journal of Diabetes and Its Complications xxx (2016) xxx–xxx
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Journal of Diabetes and Its Complications j o u r n a l h o m e p a g e : W W W. J D C J O U R N A L . C O M
Circulating betatrophin in healthy control and type 2 diabetic subjects and its association with metabolic parameters Nasser M. Al-Daghri a, b,⁎, Shakilur Rahman a, Shaun Sabico a, Osama E. Amer a, Kaiser Wani a, Mohammed Ghouse Ahmed Ansari a, Omar S. Al-Attas a, b, Sudhesh Kumar c, Majed S. Alokail a, b a b c
Biomarkers Research Program, Biochemistry Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia Prince Mutaib Chair for Biomarkers of Osteoporosis, Biochemistry Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia Division of Metabolic and Vascular Health, Clinical Sciences Research Institute, University Hospitals Coventry and Warwickshire Trust, Walsgrave, Coventry, United Kingdom
a r t i c l e
i n f o
Article history: Received 22 November 2015 Received in revised form 10 May 2016 Accepted 27 May 2016 Available online xxxx Keywords: Betatrophin Diabetes mellitus Lipids Insulin resistance Cardiometabolic risk
a b s t r a c t Aims: Betatrophin, a newly identified liver and adipose tissue-derived hormone, has been suggested as an inducer of β-cell proliferation in mice. However, the physiological role of betatrophin remains poorly understood in humans. Hence, the aim of this study was to investigate circulating betatrophin concentrations in normal and type 2 diabetes mellitus (T2DM) Saudi subjects and its association with various metabolic parameters. Methods: In this cross-sectional study, 200 Saudi adults (81 healthy non-T2DM controls, age: 41.43 ± 8.35 [mean ± SD]; BMI: 31.58 ± 5.49 and 119 T2DM subjects, age: 48.78 ± 11.76 years; BMI: 30.25 ± 4.83 kg/m2) were studied. Anthropometric and fasting serum biochemical data were collected. Circulating betatrophin was measured using an enzyme-linked immunosorbent assay (ELISA) based kit. Results: We observed significantly higher levels of betatrophin in T2DM subjects compared to healthy controls (882.19 ± 329.06 vs 657.14 ± 261.04 pg/ml, p b 0.001). Furthermore, in T2DM subjects, betatrophin level was positively associated with blood pressure and serum fasting glucose (p b 0.05). Conclusions: Our results suggest that circulating betatrophin is significantly elevated in subjects with T2DM compared to healthy controls. Increase in the level of betatrophin in T2DM subjects might be a compensatory mechanism for enhanced insulin demand in T2DM condition. © 2016 Elsevier Inc. All rights reserved.
1. Introduction Betatrophin, a recently discovered hormone primarily expressed in liver and adipose tissue, has been shown to promote pancreatic β-cell proliferation and improve glucose tolerance in mice (Yi, Park & Melton, 2013). Betatrophin has been proposed to be a regulator of lipid metabolism and has also been referred to as hepatocellular carcinoma-associated protein TD26, refeeding-induced fat and liver (RIFL), lipasin and angiopoietin-like protein 8 (ANGPTL8) by several groups (Fu, Yao, Abou-Samra, & Zhang, 2013; Quagliarini et al., 2012; Ren, Kim, & Smas, 2012; Wang et al., 2013; Yamada et al., 2015; Zhang & Abou-Samra, 2013). Yi et al., (2013) observed strong liver betatrophin expression after insulin receptor blocking by antagonist S961 in mice, leading to significantly increased proliferation of pancreatic β cells. Hence, betatrophin was initially thought to be a promising therapeutic agent for treatment of diabetes. Despite
Conflict of interests: The authors declare that they have no conflict of interests. ⁎ Corresponding author at: Biomarkers Research Program, Biochemistry Department, College of Science, King Saud University, 11451 Riyadh, Saudi Arabia. Tel.: +966 14 675 939; fax: +966 14 675 931. E-mail address: [email protected] (N.M. Al-Daghri).
promising results from animal studies, results from humans are limited (Cox et al., 2015; Gusarova et al., 2014). Gusarova et al. (2014) showed that mice lacking betatrophin/ANGPTL8 had a normal β-cell expansion under states of insulin resistance induced by high-fat diet or treatment with insulin receptor antagonist S961 in experimental animals. However, Jiao, Le Lay, Yu, Naji, and Kaestner (2014) demonstrated that betatrophin was able to cause strong induction of the β-cells proliferation in mice but not in humans. Studies in humans have indicated that betatrophin level was elevated in both type 1 and type 2 diabetes mellitus (T2DM) (Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014; Fu, Abou-Samra, & Zhang, 2014; Fu et al., 2014; Hu et al., 2014) while a study suggested that betatrophin was reduced in subjects with T2DM (Gómez-Ambrosi et al., 2014). T2DM is characterized by insulin resistance and progressive pancreatic β cell failure (Vetere, Choudhary, Burns, & Wagner, 2014; Yamada et al., 2015). Thus, any expansion and proliferation of insulin-secreting β cells may have potential as a clinical application for DM patients (Vetere et al., 2014). Nonetheless, because of contradicting results regarding role of betatrophin in T2DM, its physiological relevance remains elusive. Thus, additional studies are needed to better understand its physiological importance particularly in the condition of diabetes mellitus.
http://dx.doi.org/10.1016/j.jdiacomp.2016.05.023 1056-8727/© 2016 Elsevier Inc. All rights reserved.
Please cite this article as: Al-Daghri, N.M., et al., Circulating betatrophin in healthy control and type 2 diabetic subjects and its association with metabolic parameters, Journal of Diabetes and Its Complications (2016), http://dx.doi.org/10.1016/j.jdiacomp.2016.05.023
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N.M. Al-Daghri et al. / Journal of Diabetes and Its Complications xxx (2016) xxx–xxx
T2DM is considered one of the main threats to human health globally and particularly in Saudi Arabia (Al-Daghri et al., 2011; Lam & LeRoith, 2012). A recent survey stated that the prevalence of T2DM in the country has reached around 31.6% in adults (Al-Daghri et al., 2011; Bahijri, Alissa, Akbar, & Ghabrah, 2010). The Saudi population, because of high incidence of T2DM, may be of particular interest for betatrophin study, but available data are lacking in this field. To the best of our knowledge there is no study on circulating betatrophin from Kingdom of Saudi Arabia. Hence, the study aims to compare the level of circulating betatrophin in healthy control and T2DM subjects in adult Saudi population and additionally the association of the betatrophin with different metabolic parameters. 2. Methods 2.1. Subjects and experimental design A total of 200 adult Saudi subjects (135 men; 65 women), aged 21–70 years were randomly selected from different Primary Health Care Centers (PHCCs) in Riyadh, KSA. These individuals were part of the Biomarker Screening in Riyadh Project (RIYADH COHORT). All participants provided written and informed consent prior to inclusion. Ethical approval was granted by the Ethics Committee of the College of Science Research Center, King Saud University, Riyadh, Kingdom of Saudi Arabia (KSA). Participants completed a questionnaire their general health status, demographic information, and past medical history. Subjects were subdivided into non-diabetic healthy controls (n = 81) and those having DMT2 (n = 119). Patients with fasting blood glucose (FBG) ≥ 7.0 mmol/L and/or taking oral hypoglycemic drugs were considered to have T2DM. While, FBG ≤ 5.6 was considered as non-diabetic controls. 2.2. Anthropometrics and blood collection Participants were advised to come to their respective PHCCs in the morning after an overnight fast (N 10 h). Anthropometric data collected include height (cm); weight (kg); waist and hip circumferences (cm); sagittal abdominal diameter (SAD, cm); and systolic and diastolic blood pressure (mm Hg) (average of 2 readings 15 minutes apart) measured using an appropriate mercury sphygmomanometer. Weight and height were recorded to the nearest 0.2 kg and 0.5 cm, respectively, using an appropriate international standard scale (Digital Pearson Scale, ADAM Equipment Inc., USA). Body mass index (BMI) was calculated as weight in kg divided by the square of the height in meters. Fasting blood samples were drawn and centrifuged. The collected sera were then transferred to a pre-labeled tube, stored in ice, and delivered to the Biomarkers Research Program (BRP) at King Saud University, Riyadh, KSA for immediate storage at −80 °C until analysis. 2.3. Biochemical analysis Fasting glucose (FG) and lipid profile were measured using a chemical analyzer (Konelab 20XTi, Thermo fisher Scientific, Vantaa, Finland). Glycosylated hemoglobin (HbA1c) was measured through Nyocard-HbA1c (Nyocard, Norway) utilizing boronated affinity assay. Betatrophin was measured by competitive inhibition enzyme linked immunosorbent assay (Wuhan EIAab Science, Wuhan, China; Catalogue No. E11644h) according to the manufacturer's protocol. The values were expressed in pg/ml units. The lower and upper limits of detection of the ELISA were 78.0 and 5,000 pg/mL. The intra- and inter-assay coefficients of variation were b5% and b 10%, respectively. All samples were analyzed in duplicate. Serum insulin, leptin and resistin, TNFα and aPAI-1 were analyzed using Luminex® xMAP® Technology platform (Luminexcorp, TX, USA). The intra-assay variation was 1.4–7.9% and inter-assay variation was b21%. Minimum detectable concentrations (MDC) were as follows: insulin, 50.9 pg/ml, leptin, 85.4 pg/ml, and resistin, 6.7 pg/ml.
Insulin resistance (HOMA-IR) was calculated as fasting insulin (mU/L) × fasting plasma glucose (mmol/L)/22.5 (Bonoram et al., 2002).
2.4. Statistical analyses Statistical analyses were carried out using the Statistical Package for Social Sciences software (SPSS release 16.0; SPSS Inc., Chicago, IL, USA). Data were expressed as mean ± SD. The Kolmogorov–Smirnov statistic was performed to test continuous variables for normality. All non-Gaussian parameters were logarithmically or square root transformed to normalize data before correlations and statistical analyses were performed. Independent Student t-test was employed to compare means among groups of normally distributed data. Pearson correlations between serum betatrophin and the rest of the variables were determined. In all statistical tests, p values b 0.05 were considered significant. Bonferroni corrected p-values were applied in the association analysis. Post-hoc power analysis showed sufficient sample size with a power (1 − β err prob) = 0.98 to detect a 225.05 pg/mL difference in calculated Betatrophin between groups.
3. Results A total of 200 adults (81 healthy controls and 119 with T2DM) were included in the analysis. The clinical and laboratory characteristics of the subjects are presented in Table 1. Significantly higher levels of circulating betatrophin were observed in T2DM subjects compared to healthy controls (mean difference = 225.05, p b 0.01) (Table 1). This significant difference persisted, though weaker, after adjusting for age and blood pressure (p = 0.05), but lost significance after including HOMA-IR (p = 0.38) (not shown in table). No gender differences were observed. Additionally, age, systolic BP, systemic glucose, total cholesterol, LDL-cholesterol, HbA1c, triglycerides, resistin, leptin, HOMA-IR (p b 0.01) and HDL-cholesterol (p b 0.05) were significantly higher in T2DM subjects compared to control subjects (Table 1). Other parameters Table 1 Clinical characteristics of the subjects. Parameter
Control
Diabetic
p-Value
N Age (years) Female/Male Body mass index (kg/m2) Waist circumference (cm) Hip circumference (cm) Sagittal abdominal diameter (cm) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Cholesterol (mmol/L) Glucose (mmol/L) HDL-cholesterol (mmol/L) LDL-cholesterol (mmol/L) HbA1c (%) Triglycerides (mmol/L)a Betatrophin (pg/mL) Insulin (μU/mL)a Resistin (ng/mL)a
81 (40.50%) 41.43 ± 8.35 60/21 31.58 ± 5.49 97.60 ± 11.07 109.89 ± 12.65 23.73 ± 4.76
119 (59.50%) 48.78 ± 11.76 75/44 30.25 ± 4.83 98.76 ± 10.49 106.64 ± 11.73 23.96 ± 4.22
0.000⁎⁎ 0.101 0.086 0.552 0.128 0.779
117.64 ± 7.29
122.84 ± 10.68
0.006⁎⁎
76.64 ± 7.21
78.40 ± 5.96
0.125
4.70 ± 1.06 5.18 ± 0.68 0.88 ± 0.27 3.06 ± 0.83 4.62 ± 0.14 1.31 (0.97–1.90) 657.14 ± 261.04 9.91 (7.14–14.66) 1096.02 (16.66–3578)
5.65 ± 1.01 12.65 ± 3.56 0.98 ± 0.33 3.57 ± 0.89 7.91 ± 0.24 1.92 (1.41–2.62) 882.19 ± 329.06 15.72 (12.24–19.28) 2696.71 (820.86–4942.98) 7892.6 (6030.86–13,072.7) 9.03 ± 3.99
0.000⁎⁎ 0.000⁎⁎ 0.036⁎ 0.000⁎⁎ 0.000⁎⁎ 0.000⁎⁎ 0.000⁎⁎ 0.000⁎⁎ 0.010⁎⁎
Leptin (pg/mL)a HOMA-IR
15,726.9 (6649.6–21,620) 2.55 ± 1.52
0.003⁎⁎ 0.000⁎⁎
Note: Data presented as N (%) for frequencies; mean ± standard deviation for normal continuous variables. a Denotes continuous variables with non-Gaussian distribution presented median (25th–75th) percentiles. ⁎ Denotes significance at 0.05 level. ⁎⁎ Denotes significance at 0.01 level.
Please cite this article as: Al-Daghri, N.M., et al., Circulating betatrophin in healthy control and type 2 diabetic subjects and its association with metabolic parameters, Journal of Diabetes and Its Complications (2016), http://dx.doi.org/10.1016/j.jdiacomp.2016.05.023
N.M. Al-Daghri et al. / Journal of Diabetes and Its Complications xxx (2016) xxx–xxx
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4. Discussion
Table 2 Association between betatrophin with other metabolic parameters. Parameter
All
Control
Diabetic
N Age (years) Body mass index (kg/m2) Waist circumference (cm) Hip circumference (cm) Sagittal abdominal diameter (cm) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Cholesterol (mmol/L) Glucose (mmol/L) HDL-cholesterol (mmol/L) LDL-cholesterol (mmol/L) HbA1c (%) Triglycerides (mmol/L)a Insulin (μU/mL)a Resistin (ng/mL)a Leptin (pg/mL)a HOMAIRa
200 0.245⁎⁎ −0.032 0.031 −0.006 0.008 0.187 0.164 0.090 0.387⁎⁎ 0.015 0.082 0.384⁎ 0.251⁎ 0.343⁎⁎ 0.090 0.001 0.388⁎⁎
81 0.191 0.117 0.208 0.055 0.121 −0.104 −0.044 0.010 0.048 0.048 −0.009 0.290 0.036 0.218 0.022 0.155 0.116
119 0.157 −0.037 −0.056 −0.017 −0.042 0.214 0.247 −110 0.248 −0.065 −0.045 0.048 0.191 0.134 −0.070 −0.095 0.037
Note: Data presented as coefficient (R). a Denotes log transform. ⁎ Denotes significance at 0.05 level. ⁎⁎ Denotes significance at 0.01 level.
including gender, BMI, waist, hips, SAD, and diastolic BP, were not significantly different between control and T2DM groups. Correlations between betatrophin and metabolic parameters measured are presented in Table 2. Betatrophin level was positively associated with age (R = 0.245, p b 0.01), FBG (R = 0.387, p b 0.01), HbA1c (R = 0.384, p b 0.05), triglycerides (R = 0.251, p b 0.05), insulin (R = 0.343, p b 0.01), HOMA-IR (R = 0.388, p b 0.01) and systolic BP (R = 0.187, p b 0.05) in all groups. No significant assocations were elicited after stratification into T2DM and control group. Nevertheless, in the T2DM group, unadjusted circulating betatrophin levels were positively associated with FBG (R = 0.248, p b 0.05) (Fig. 1) while no such association was observed in control group (Table 2). Inter-tertile range for betatrophin was assessed to examine the associations between the levels of FBG (low, moderate, and high) and circulating betatrophin. It was observed that by increasing tertiles of glucose level there was a significant increase in betatrophin level as betatrophin levels were found to be highest in tertiles 3 (highest glucose level) with a significant increase as compared to tertile 1 (lowest level of glucose, p b 0.01) and tertile 2 (moderate glucose level, p b 0.05), in the diabetic group (Fig. 2).
In this study we described for the first time elevated serum betatrophin concentrations in T2DM Saudi patients as compared to non-T2DM subjects. Our results suggest that increasing demands for insulin as a result of insulin resistance may lead to an increased production of betatrophin in T2DM condition. Our findings are similar to those of Yi et al., who were the first to demonstrate that betatrophin levels were upregulated by insulin resistance in mice liver (Yi et al., 2013). Our findings are also in agreement with other studies that showed higher circulating levels of betatrophin in T2DM subjects (Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014; Fu, Abou-Samra, & Zhang, 2014; Fu et al., 2014; Hu et al., 2014; Yamada et al., 2015). However, unchanged (Fenzl et al., 2014) or even decreased (Gómez-Ambrosi et al., 2014) serum betatrophin levels have also been reported in DM patients. Fenzl et al. (2014) reported no difference in serum betatrophin level between non-diabetics and T2DM participants. The disparities may be due to the difference in sample sizes, oral hypoglycemic agents, and different disease duration of T2DM (Hu et al., 2014). In the study of Fenzl et al. (2014), all patients with T2DM received metformin as baseline therapy. Theoretically, treatment with metformin could decrease plasma betatrophin levels, since it reduces insulin resistance which is the main stimulus for betatrophin secretion (Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014). It is also possible that serum betatrophin levels could be affected by disease durations of T2DM, long-term or variable storage time or occurrence of any repeated freeze-thaw cycles, and differences in sample size and ethnic groups across studies (Abu-Farha et al., 2015; Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014; Hu et al., 2014). The role of betatrophin in glucose metabolism is nevertheless still argued (Jiao et al., 2014; Kaestner, 2014; Yi et al., 2013). Several landmark studies suggest that this association maybe in part due to effects of abnormal lipid metabolism (Gusarova et al., 2014; Wang et al., 2013; Zhang & Abou-Samra, 2013) which the present study was unable to reproduce after stratification between T2DM and control. Conflicting results exist on the associations of betatrophin levels with BMI values, FBG, lipid profiles or insulin sensitivity (Crujeiras et al., 2016; Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014; Fenzl et al., 2014; Fu, Abou-Samra, & Zhang, 2014; Fu et al., 2014; Hu et al., 2014). Abu-Farha et al. (2015) in their study on large sample size (1047 non-diabetic and 556 T2DM subjects) observed that betatrophin levels were associated with BMI, FBG, TG and HOMA-IR in non-diabetic subjects but not in diabetic subjects. The significant association of betatrophin and triglycerides also confirms the study of Gao et al. (2015). Discrepancies in the results may be because of sample selection criteria as they have randomly selected sample from a large cohort of multi-ethnic subjects. In our study we selected adult Saudi subjects specifically. Evidence suggests
Fig. 1. Unadjusted correlation between betatrophin (pg/mL) and glucose (mmol/L) in diabetic group.
Please cite this article as: Al-Daghri, N.M., et al., Circulating betatrophin in healthy control and type 2 diabetic subjects and its association with metabolic parameters, Journal of Diabetes and Its Complications (2016), http://dx.doi.org/10.1016/j.jdiacomp.2016.05.023
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N.M. Al-Daghri et al. / Journal of Diabetes and Its Complications xxx (2016) xxx–xxx
Fig. 2. Boxplot for betatrophin according to glucose tertiles [T1 (4.10–5.95), T2 (5.96–11.82) and T3 (11.83–19.89)].
that racial and ethnic differences may affect metabolic outcomes (Beydoun et al., 2008; Ervin, 2009). Moreover, differences in the handling of blood samples, time to separation of plasma/serum, and storing conditions could also affect the results. Lastly, the type of ELISA kit used may contribute in the contradictory findings observed in the literature. Betatrophin-recognizing antibodies used by EIAAB (Abu-Farha et al., 2015) and Phoenix kits (Crujeiras et al., 2016; Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014) are distinct in that the former and the latter recognize the N-terminus and the C-terminus of betatrophin, respectively, therefore, betatrophin proteolytic regulation likely results in different circulating levels determined by ELISA kits that rely on antibodies against either the N- or the C-terminus of the protein (Fu, Abou-Samra, & Zhang, 2014; Fu et al., 2014). The current limitations of this study include its cross-sectional nature and thus cannot determine cause and effect. Secondly, betatrophin measurement was made on stored samples, although the samples were relatively fresh. Moreover, betatrophin measurement was made once (single time point). It will be more interesting to see the changes in the level of betatrophin with different stages of diabetes development. Medication (metformin in particular) use was also lacking and this could have intoriduced bias in the results. Finally, some of the correlations between betatrophin and studied parameters were significant in the entire cohort but became insignificant after stratification. This could be explained by lack of statistical power, especially in cases where correlation in the expected direction was observed but did not reach conventional levels of significance. Therefore, confirming the present results using a larger population is important. In summary, our results indicate that circulating betatrophin concentrations were significantly increased in patients with T2DM compared to healthy controls. Additionally, betatrophin levels were positively associated with fasting blood glucose, systolic and diastolic pressure. Thus, an increased betatrophin level in T2DM possibly represents a compensatory cellular mechanism against insulin resistance. Future studies on betatrophin are clearly needed to confirm whether increased betatrophin in T2DM is a compensatory response or only a marker of insulin resistance. Moreover, the identification of the betatrophin receptor will undoubtedly help to elucidate exact role of
betatrophin in diabetes mellitus and to understand the reason behind increase circulatory betatrophin in T2DM condition. Acknowledgments The authors thank the Deanship of Scientific Research, Prolific Research Group Program (PRG-1436-15), Vice Rectorate for Graduate Studies and Scientific Research in King Saud University (KSU), Riyadh, Saudi Arabia for funding the study. The authors are also grateful to Mr. Malak Nawaz Khan Kattak and Mr. Syed Danish Hussain for the statistical analysis of the data. References Abu-Farha, M., Abubaker, J., Al-Khairi, I., Cherian, P., Noronha, F., Hu, F. B., ... Elkum, N. (2015). Higher plasma betatrophin/ANGPTL8 level in type 2 diabetes subjects does not correlate with blood glucose or insulin resistance. Scientific Reports, 5, 10949. Al-Daghri, N. M., Al-Attas, O. S., Alokail, M. S., Alkharfy, K. M., Yousef, M., Sabico, S. L., & Chrousos, G. P. (2011). Diabetes mellitus type 2 and other chronic noncommunicable diseases in the central region, Saudi Arabia (Riyadh cohort 2): a decade of an epidemic. BMC Medicine, 9, 76. Bahijri, S. M., Alissa, E. M., Akbar, D. H., & Ghabrah, T. M. (2010). Estimation of insulin resistance in non-diabetic normotensive Saudi adults by QUICKI, HOMA-IR and modified QUICKI: a comparative study. Annals of Saudi Medicine, 30, 257–264. Beydoun, M. A., Gary, T. L., Caballero, B. H., Lawrence, R. S., Cheskin, L. J., & Wang, Y. (2008). Ethnic differences in dairy and related nutrient consumption among US adults and their association with obesity, central obesity, and the metabolic syndrome. American Journal of Clinical Nutrition, 87, 1914–1925. Bonoram, E., Formentini, G., Calcaterra, F., Lombardi, S., Marini, F., Zenari, L., ... Rafaelli, A. (2002). HOMA-estimated insulin resistance is an independent predictor of cardiovascular disease in type 2 diabetic subjects prospective data from the Verona Database Complications Study. Diabetes Care, 25, 1135–1141. Cox, A. R., Lam, C. J., Bonnyman, C. W., Chavez, J., Rios, J. S., & Kushner, J. A. (2015). Angiopoietin-like protein 8 (ANGPTL8)/betatrophin overexpression does not increase beta cell proliferation in mice. Diabetologia, 58, 1523–1531. Crujeiras, A. B., Zulet, M. A., Abete, I., Amil, M., Carreira, M. C., Martinez, J. A., & Casanueva, F. F. (2016). Interplay of atherogenic factors, protein intake and betatrophin levels in obese-metabolic syndrome patients treated with hypocaloric diets. International Journal of Obesity (London), 40, 403–410. Ervin, R. B. (2009). Prevalence of metabolic syndrome among adults 20 years of age and over, by sex, age, race and ethnicity, and body mass index: United States. National Health Statistics Reports, 13, 1–7. Espes, D., Lau, J., & Carlsson, P. O. (2014a). Increased circulating levels of betatrophin in individuals with long-standing type 1 diabetes. Diabetologia, 57, 50–53.
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Please cite this article as: Al-Daghri, N.M., et al., Circulating betatrophin in healthy control and type 2 diabetic subjects and its association with metabolic parameters, Journal of Diabetes and Its Complications (2016), http://dx.doi.org/10.1016/j.jdiacomp.2016.05.023
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Journal of Diabetes and Its Complications j o u r n a l h o m e p a g e : W W W. J D C J O U R N A L . C O M
Circulating betatrophin in healthy control and type 2 diabetic subjects and its association with metabolic parameters Nasser M. Al-Daghri a, b,⁎, Shakilur Rahman a, Shaun Sabico a, Osama E. Amer a, Kaiser Wani a, Mohammed Ghouse Ahmed Ansari a, Omar S. Al-Attas a, b, Sudhesh Kumar c, Majed S. Alokail a, b a b c
Biomarkers Research Program, Biochemistry Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia Prince Mutaib Chair for Biomarkers of Osteoporosis, Biochemistry Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia Division of Metabolic and Vascular Health, Clinical Sciences Research Institute, University Hospitals Coventry and Warwickshire Trust, Walsgrave, Coventry, United Kingdom
a r t i c l e
i n f o
Article history: Received 22 November 2015 Received in revised form 10 May 2016 Accepted 27 May 2016 Available online xxxx Keywords: Betatrophin Diabetes mellitus Lipids Insulin resistance Cardiometabolic risk
a b s t r a c t Aims: Betatrophin, a newly identified liver and adipose tissue-derived hormone, has been suggested as an inducer of β-cell proliferation in mice. However, the physiological role of betatrophin remains poorly understood in humans. Hence, the aim of this study was to investigate circulating betatrophin concentrations in normal and type 2 diabetes mellitus (T2DM) Saudi subjects and its association with various metabolic parameters. Methods: In this cross-sectional study, 200 Saudi adults (81 healthy non-T2DM controls, age: 41.43 ± 8.35 [mean ± SD]; BMI: 31.58 ± 5.49 and 119 T2DM subjects, age: 48.78 ± 11.76 years; BMI: 30.25 ± 4.83 kg/m2) were studied. Anthropometric and fasting serum biochemical data were collected. Circulating betatrophin was measured using an enzyme-linked immunosorbent assay (ELISA) based kit. Results: We observed significantly higher levels of betatrophin in T2DM subjects compared to healthy controls (882.19 ± 329.06 vs 657.14 ± 261.04 pg/ml, p b 0.001). Furthermore, in T2DM subjects, betatrophin level was positively associated with blood pressure and serum fasting glucose (p b 0.05). Conclusions: Our results suggest that circulating betatrophin is significantly elevated in subjects with T2DM compared to healthy controls. Increase in the level of betatrophin in T2DM subjects might be a compensatory mechanism for enhanced insulin demand in T2DM condition. © 2016 Elsevier Inc. All rights reserved.
1. Introduction Betatrophin, a recently discovered hormone primarily expressed in liver and adipose tissue, has been shown to promote pancreatic β-cell proliferation and improve glucose tolerance in mice (Yi, Park & Melton, 2013). Betatrophin has been proposed to be a regulator of lipid metabolism and has also been referred to as hepatocellular carcinoma-associated protein TD26, refeeding-induced fat and liver (RIFL), lipasin and angiopoietin-like protein 8 (ANGPTL8) by several groups (Fu, Yao, Abou-Samra, & Zhang, 2013; Quagliarini et al., 2012; Ren, Kim, & Smas, 2012; Wang et al., 2013; Yamada et al., 2015; Zhang & Abou-Samra, 2013). Yi et al., (2013) observed strong liver betatrophin expression after insulin receptor blocking by antagonist S961 in mice, leading to significantly increased proliferation of pancreatic β cells. Hence, betatrophin was initially thought to be a promising therapeutic agent for treatment of diabetes. Despite
Conflict of interests: The authors declare that they have no conflict of interests. ⁎ Corresponding author at: Biomarkers Research Program, Biochemistry Department, College of Science, King Saud University, 11451 Riyadh, Saudi Arabia. Tel.: +966 14 675 939; fax: +966 14 675 931. E-mail address: [email protected] (N.M. Al-Daghri).
promising results from animal studies, results from humans are limited (Cox et al., 2015; Gusarova et al., 2014). Gusarova et al. (2014) showed that mice lacking betatrophin/ANGPTL8 had a normal β-cell expansion under states of insulin resistance induced by high-fat diet or treatment with insulin receptor antagonist S961 in experimental animals. However, Jiao, Le Lay, Yu, Naji, and Kaestner (2014) demonstrated that betatrophin was able to cause strong induction of the β-cells proliferation in mice but not in humans. Studies in humans have indicated that betatrophin level was elevated in both type 1 and type 2 diabetes mellitus (T2DM) (Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014; Fu, Abou-Samra, & Zhang, 2014; Fu et al., 2014; Hu et al., 2014) while a study suggested that betatrophin was reduced in subjects with T2DM (Gómez-Ambrosi et al., 2014). T2DM is characterized by insulin resistance and progressive pancreatic β cell failure (Vetere, Choudhary, Burns, & Wagner, 2014; Yamada et al., 2015). Thus, any expansion and proliferation of insulin-secreting β cells may have potential as a clinical application for DM patients (Vetere et al., 2014). Nonetheless, because of contradicting results regarding role of betatrophin in T2DM, its physiological relevance remains elusive. Thus, additional studies are needed to better understand its physiological importance particularly in the condition of diabetes mellitus.
http://dx.doi.org/10.1016/j.jdiacomp.2016.05.023 1056-8727/© 2016 Elsevier Inc. All rights reserved.
Please cite this article as: Al-Daghri, N.M., et al., Circulating betatrophin in healthy control and type 2 diabetic subjects and its association with metabolic parameters, Journal of Diabetes and Its Complications (2016), http://dx.doi.org/10.1016/j.jdiacomp.2016.05.023
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N.M. Al-Daghri et al. / Journal of Diabetes and Its Complications xxx (2016) xxx–xxx
T2DM is considered one of the main threats to human health globally and particularly in Saudi Arabia (Al-Daghri et al., 2011; Lam & LeRoith, 2012). A recent survey stated that the prevalence of T2DM in the country has reached around 31.6% in adults (Al-Daghri et al., 2011; Bahijri, Alissa, Akbar, & Ghabrah, 2010). The Saudi population, because of high incidence of T2DM, may be of particular interest for betatrophin study, but available data are lacking in this field. To the best of our knowledge there is no study on circulating betatrophin from Kingdom of Saudi Arabia. Hence, the study aims to compare the level of circulating betatrophin in healthy control and T2DM subjects in adult Saudi population and additionally the association of the betatrophin with different metabolic parameters. 2. Methods 2.1. Subjects and experimental design A total of 200 adult Saudi subjects (135 men; 65 women), aged 21–70 years were randomly selected from different Primary Health Care Centers (PHCCs) in Riyadh, KSA. These individuals were part of the Biomarker Screening in Riyadh Project (RIYADH COHORT). All participants provided written and informed consent prior to inclusion. Ethical approval was granted by the Ethics Committee of the College of Science Research Center, King Saud University, Riyadh, Kingdom of Saudi Arabia (KSA). Participants completed a questionnaire their general health status, demographic information, and past medical history. Subjects were subdivided into non-diabetic healthy controls (n = 81) and those having DMT2 (n = 119). Patients with fasting blood glucose (FBG) ≥ 7.0 mmol/L and/or taking oral hypoglycemic drugs were considered to have T2DM. While, FBG ≤ 5.6 was considered as non-diabetic controls. 2.2. Anthropometrics and blood collection Participants were advised to come to their respective PHCCs in the morning after an overnight fast (N 10 h). Anthropometric data collected include height (cm); weight (kg); waist and hip circumferences (cm); sagittal abdominal diameter (SAD, cm); and systolic and diastolic blood pressure (mm Hg) (average of 2 readings 15 minutes apart) measured using an appropriate mercury sphygmomanometer. Weight and height were recorded to the nearest 0.2 kg and 0.5 cm, respectively, using an appropriate international standard scale (Digital Pearson Scale, ADAM Equipment Inc., USA). Body mass index (BMI) was calculated as weight in kg divided by the square of the height in meters. Fasting blood samples were drawn and centrifuged. The collected sera were then transferred to a pre-labeled tube, stored in ice, and delivered to the Biomarkers Research Program (BRP) at King Saud University, Riyadh, KSA for immediate storage at −80 °C until analysis. 2.3. Biochemical analysis Fasting glucose (FG) and lipid profile were measured using a chemical analyzer (Konelab 20XTi, Thermo fisher Scientific, Vantaa, Finland). Glycosylated hemoglobin (HbA1c) was measured through Nyocard-HbA1c (Nyocard, Norway) utilizing boronated affinity assay. Betatrophin was measured by competitive inhibition enzyme linked immunosorbent assay (Wuhan EIAab Science, Wuhan, China; Catalogue No. E11644h) according to the manufacturer's protocol. The values were expressed in pg/ml units. The lower and upper limits of detection of the ELISA were 78.0 and 5,000 pg/mL. The intra- and inter-assay coefficients of variation were b5% and b 10%, respectively. All samples were analyzed in duplicate. Serum insulin, leptin and resistin, TNFα and aPAI-1 were analyzed using Luminex® xMAP® Technology platform (Luminexcorp, TX, USA). The intra-assay variation was 1.4–7.9% and inter-assay variation was b21%. Minimum detectable concentrations (MDC) were as follows: insulin, 50.9 pg/ml, leptin, 85.4 pg/ml, and resistin, 6.7 pg/ml.
Insulin resistance (HOMA-IR) was calculated as fasting insulin (mU/L) × fasting plasma glucose (mmol/L)/22.5 (Bonoram et al., 2002).
2.4. Statistical analyses Statistical analyses were carried out using the Statistical Package for Social Sciences software (SPSS release 16.0; SPSS Inc., Chicago, IL, USA). Data were expressed as mean ± SD. The Kolmogorov–Smirnov statistic was performed to test continuous variables for normality. All non-Gaussian parameters were logarithmically or square root transformed to normalize data before correlations and statistical analyses were performed. Independent Student t-test was employed to compare means among groups of normally distributed data. Pearson correlations between serum betatrophin and the rest of the variables were determined. In all statistical tests, p values b 0.05 were considered significant. Bonferroni corrected p-values were applied in the association analysis. Post-hoc power analysis showed sufficient sample size with a power (1 − β err prob) = 0.98 to detect a 225.05 pg/mL difference in calculated Betatrophin between groups.
3. Results A total of 200 adults (81 healthy controls and 119 with T2DM) were included in the analysis. The clinical and laboratory characteristics of the subjects are presented in Table 1. Significantly higher levels of circulating betatrophin were observed in T2DM subjects compared to healthy controls (mean difference = 225.05, p b 0.01) (Table 1). This significant difference persisted, though weaker, after adjusting for age and blood pressure (p = 0.05), but lost significance after including HOMA-IR (p = 0.38) (not shown in table). No gender differences were observed. Additionally, age, systolic BP, systemic glucose, total cholesterol, LDL-cholesterol, HbA1c, triglycerides, resistin, leptin, HOMA-IR (p b 0.01) and HDL-cholesterol (p b 0.05) were significantly higher in T2DM subjects compared to control subjects (Table 1). Other parameters Table 1 Clinical characteristics of the subjects. Parameter
Control
Diabetic
p-Value
N Age (years) Female/Male Body mass index (kg/m2) Waist circumference (cm) Hip circumference (cm) Sagittal abdominal diameter (cm) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Cholesterol (mmol/L) Glucose (mmol/L) HDL-cholesterol (mmol/L) LDL-cholesterol (mmol/L) HbA1c (%) Triglycerides (mmol/L)a Betatrophin (pg/mL) Insulin (μU/mL)a Resistin (ng/mL)a
81 (40.50%) 41.43 ± 8.35 60/21 31.58 ± 5.49 97.60 ± 11.07 109.89 ± 12.65 23.73 ± 4.76
119 (59.50%) 48.78 ± 11.76 75/44 30.25 ± 4.83 98.76 ± 10.49 106.64 ± 11.73 23.96 ± 4.22
0.000⁎⁎ 0.101 0.086 0.552 0.128 0.779
117.64 ± 7.29
122.84 ± 10.68
0.006⁎⁎
76.64 ± 7.21
78.40 ± 5.96
0.125
4.70 ± 1.06 5.18 ± 0.68 0.88 ± 0.27 3.06 ± 0.83 4.62 ± 0.14 1.31 (0.97–1.90) 657.14 ± 261.04 9.91 (7.14–14.66) 1096.02 (16.66–3578)
5.65 ± 1.01 12.65 ± 3.56 0.98 ± 0.33 3.57 ± 0.89 7.91 ± 0.24 1.92 (1.41–2.62) 882.19 ± 329.06 15.72 (12.24–19.28) 2696.71 (820.86–4942.98) 7892.6 (6030.86–13,072.7) 9.03 ± 3.99
0.000⁎⁎ 0.000⁎⁎ 0.036⁎ 0.000⁎⁎ 0.000⁎⁎ 0.000⁎⁎ 0.000⁎⁎ 0.000⁎⁎ 0.010⁎⁎
Leptin (pg/mL)a HOMA-IR
15,726.9 (6649.6–21,620) 2.55 ± 1.52
0.003⁎⁎ 0.000⁎⁎
Note: Data presented as N (%) for frequencies; mean ± standard deviation for normal continuous variables. a Denotes continuous variables with non-Gaussian distribution presented median (25th–75th) percentiles. ⁎ Denotes significance at 0.05 level. ⁎⁎ Denotes significance at 0.01 level.
Please cite this article as: Al-Daghri, N.M., et al., Circulating betatrophin in healthy control and type 2 diabetic subjects and its association with metabolic parameters, Journal of Diabetes and Its Complications (2016), http://dx.doi.org/10.1016/j.jdiacomp.2016.05.023
N.M. Al-Daghri et al. / Journal of Diabetes and Its Complications xxx (2016) xxx–xxx
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4. Discussion
Table 2 Association between betatrophin with other metabolic parameters. Parameter
All
Control
Diabetic
N Age (years) Body mass index (kg/m2) Waist circumference (cm) Hip circumference (cm) Sagittal abdominal diameter (cm) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Cholesterol (mmol/L) Glucose (mmol/L) HDL-cholesterol (mmol/L) LDL-cholesterol (mmol/L) HbA1c (%) Triglycerides (mmol/L)a Insulin (μU/mL)a Resistin (ng/mL)a Leptin (pg/mL)a HOMAIRa
200 0.245⁎⁎ −0.032 0.031 −0.006 0.008 0.187 0.164 0.090 0.387⁎⁎ 0.015 0.082 0.384⁎ 0.251⁎ 0.343⁎⁎ 0.090 0.001 0.388⁎⁎
81 0.191 0.117 0.208 0.055 0.121 −0.104 −0.044 0.010 0.048 0.048 −0.009 0.290 0.036 0.218 0.022 0.155 0.116
119 0.157 −0.037 −0.056 −0.017 −0.042 0.214 0.247 −110 0.248 −0.065 −0.045 0.048 0.191 0.134 −0.070 −0.095 0.037
Note: Data presented as coefficient (R). a Denotes log transform. ⁎ Denotes significance at 0.05 level. ⁎⁎ Denotes significance at 0.01 level.
including gender, BMI, waist, hips, SAD, and diastolic BP, were not significantly different between control and T2DM groups. Correlations between betatrophin and metabolic parameters measured are presented in Table 2. Betatrophin level was positively associated with age (R = 0.245, p b 0.01), FBG (R = 0.387, p b 0.01), HbA1c (R = 0.384, p b 0.05), triglycerides (R = 0.251, p b 0.05), insulin (R = 0.343, p b 0.01), HOMA-IR (R = 0.388, p b 0.01) and systolic BP (R = 0.187, p b 0.05) in all groups. No significant assocations were elicited after stratification into T2DM and control group. Nevertheless, in the T2DM group, unadjusted circulating betatrophin levels were positively associated with FBG (R = 0.248, p b 0.05) (Fig. 1) while no such association was observed in control group (Table 2). Inter-tertile range for betatrophin was assessed to examine the associations between the levels of FBG (low, moderate, and high) and circulating betatrophin. It was observed that by increasing tertiles of glucose level there was a significant increase in betatrophin level as betatrophin levels were found to be highest in tertiles 3 (highest glucose level) with a significant increase as compared to tertile 1 (lowest level of glucose, p b 0.01) and tertile 2 (moderate glucose level, p b 0.05), in the diabetic group (Fig. 2).
In this study we described for the first time elevated serum betatrophin concentrations in T2DM Saudi patients as compared to non-T2DM subjects. Our results suggest that increasing demands for insulin as a result of insulin resistance may lead to an increased production of betatrophin in T2DM condition. Our findings are similar to those of Yi et al., who were the first to demonstrate that betatrophin levels were upregulated by insulin resistance in mice liver (Yi et al., 2013). Our findings are also in agreement with other studies that showed higher circulating levels of betatrophin in T2DM subjects (Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014; Fu, Abou-Samra, & Zhang, 2014; Fu et al., 2014; Hu et al., 2014; Yamada et al., 2015). However, unchanged (Fenzl et al., 2014) or even decreased (Gómez-Ambrosi et al., 2014) serum betatrophin levels have also been reported in DM patients. Fenzl et al. (2014) reported no difference in serum betatrophin level between non-diabetics and T2DM participants. The disparities may be due to the difference in sample sizes, oral hypoglycemic agents, and different disease duration of T2DM (Hu et al., 2014). In the study of Fenzl et al. (2014), all patients with T2DM received metformin as baseline therapy. Theoretically, treatment with metformin could decrease plasma betatrophin levels, since it reduces insulin resistance which is the main stimulus for betatrophin secretion (Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014). It is also possible that serum betatrophin levels could be affected by disease durations of T2DM, long-term or variable storage time or occurrence of any repeated freeze-thaw cycles, and differences in sample size and ethnic groups across studies (Abu-Farha et al., 2015; Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014; Hu et al., 2014). The role of betatrophin in glucose metabolism is nevertheless still argued (Jiao et al., 2014; Kaestner, 2014; Yi et al., 2013). Several landmark studies suggest that this association maybe in part due to effects of abnormal lipid metabolism (Gusarova et al., 2014; Wang et al., 2013; Zhang & Abou-Samra, 2013) which the present study was unable to reproduce after stratification between T2DM and control. Conflicting results exist on the associations of betatrophin levels with BMI values, FBG, lipid profiles or insulin sensitivity (Crujeiras et al., 2016; Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014; Fenzl et al., 2014; Fu, Abou-Samra, & Zhang, 2014; Fu et al., 2014; Hu et al., 2014). Abu-Farha et al. (2015) in their study on large sample size (1047 non-diabetic and 556 T2DM subjects) observed that betatrophin levels were associated with BMI, FBG, TG and HOMA-IR in non-diabetic subjects but not in diabetic subjects. The significant association of betatrophin and triglycerides also confirms the study of Gao et al. (2015). Discrepancies in the results may be because of sample selection criteria as they have randomly selected sample from a large cohort of multi-ethnic subjects. In our study we selected adult Saudi subjects specifically. Evidence suggests
Fig. 1. Unadjusted correlation between betatrophin (pg/mL) and glucose (mmol/L) in diabetic group.
Please cite this article as: Al-Daghri, N.M., et al., Circulating betatrophin in healthy control and type 2 diabetic subjects and its association with metabolic parameters, Journal of Diabetes and Its Complications (2016), http://dx.doi.org/10.1016/j.jdiacomp.2016.05.023
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N.M. Al-Daghri et al. / Journal of Diabetes and Its Complications xxx (2016) xxx–xxx
Fig. 2. Boxplot for betatrophin according to glucose tertiles [T1 (4.10–5.95), T2 (5.96–11.82) and T3 (11.83–19.89)].
that racial and ethnic differences may affect metabolic outcomes (Beydoun et al., 2008; Ervin, 2009). Moreover, differences in the handling of blood samples, time to separation of plasma/serum, and storing conditions could also affect the results. Lastly, the type of ELISA kit used may contribute in the contradictory findings observed in the literature. Betatrophin-recognizing antibodies used by EIAAB (Abu-Farha et al., 2015) and Phoenix kits (Crujeiras et al., 2016; Espes, Lau, & Carlsson, 2014; Espes, Martinell, & Carlsson, 2014) are distinct in that the former and the latter recognize the N-terminus and the C-terminus of betatrophin, respectively, therefore, betatrophin proteolytic regulation likely results in different circulating levels determined by ELISA kits that rely on antibodies against either the N- or the C-terminus of the protein (Fu, Abou-Samra, & Zhang, 2014; Fu et al., 2014). The current limitations of this study include its cross-sectional nature and thus cannot determine cause and effect. Secondly, betatrophin measurement was made on stored samples, although the samples were relatively fresh. Moreover, betatrophin measurement was made once (single time point). It will be more interesting to see the changes in the level of betatrophin with different stages of diabetes development. Medication (metformin in particular) use was also lacking and this could have intoriduced bias in the results. Finally, some of the correlations between betatrophin and studied parameters were significant in the entire cohort but became insignificant after stratification. This could be explained by lack of statistical power, especially in cases where correlation in the expected direction was observed but did not reach conventional levels of significance. Therefore, confirming the present results using a larger population is important. In summary, our results indicate that circulating betatrophin concentrations were significantly increased in patients with T2DM compared to healthy controls. Additionally, betatrophin levels were positively associated with fasting blood glucose, systolic and diastolic pressure. Thus, an increased betatrophin level in T2DM possibly represents a compensatory cellular mechanism against insulin resistance. Future studies on betatrophin are clearly needed to confirm whether increased betatrophin in T2DM is a compensatory response or only a marker of insulin resistance. Moreover, the identification of the betatrophin receptor will undoubtedly help to elucidate exact role of
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Please cite this article as: Al-Daghri, N.M., et al., Circulating betatrophin in healthy control and type 2 diabetic subjects and its association with metabolic parameters, Journal of Diabetes and Its Complications (2016), http://dx.doi.org/10.1016/j.jdiacomp.2016.05.023