{"id":52290,"date":"2023-09-30T10:06:57","date_gmt":"2023-09-30T10:06:57","guid":{"rendered":"https:\/\/biomedpharmajournal.org\/?p=52290"},"modified":"2023-11-10T09:49:53","modified_gmt":"2023-11-10T09:49:53","slug":"central-obesity-diminishes-circulating-betatrophin-level-in-middle-aged-male-subjects","status":"publish","type":"post","link":"https:\/\/biomedpharmajournal.org\/staging\/vol16no3\/central-obesity-diminishes-circulating-betatrophin-level-in-middle-aged-male-subjects\/","title":{"rendered":"Central Obesity Diminishes Circulating Betatrophin Level in Middle-aged Male Subjects"},"content":{"rendered":"\n

Introduction<\/strong><\/p>\n\n\n\n

Obesity is a\nmajor burden to people and to health care systems. The prevalence of obesity\nhas been increasing throughout the world. Obesity is linked to a range of\nmetabolic disorders including diabetes mellitus, atherosclerosis, gout,\nhypertension, ischemic heart disease, premature aging and untimely death1<\/sup>.\nCentral obesity, which is characterized by intra-abdominal visceral fat\naccumulation, is more prone to insulin resistance and diabetes mellitus than\ngeneral obesity, an accumulation of fat mainly in the subdermis2<\/sup>.<\/p>\n\n\n\n

About 40% of\noverweight but otherwise healthy subjects with no metabolic disorders are found\nto be insulin resistant. Ectopic fat accumulation and chronic low-grade\ninflammation can result in reduced sensitivity to insulin, which is known as\ninsulin resistance, in the body tissues such as skeletal muscles, adipose\ntissues, liver or even in pancreatic islet cells3<\/sup>. Under these\nconditions, pancreatic beta-cells respond by enhancing secretory capacity and\nnumber of cells. If this condition persists, failure of beta-cells to\ncounteract insulin resistance can lead to uncontrolled hyperglycemia and type 2\ndiabetes4<\/sup>. Several pre-clinical investigations have identified effective\nbeta-cell mitogens including insulin-like growth factor I, hepatocyte growth\nfactor, incretins (glucagon-like peptide-1), glucose-dependent insulinotropic\npolypeptide and many others, which benefit either type 1 or type 2 diabetes5<\/sup>.\n<\/p>\n\n\n\n

The discovery\nof betatrophin as a hormone capable of boosting beta-cell proliferation in\ninsulin-resistance state has been addressed as a significant scientific\nadvancement targeting to augment or replace insulin injection in clinical practice6<\/sup>.\nIt is a protein hormone, made up of 198 amino acids which involves in\nregulation of lipid and glucose metabolism. It has been named as lipasin,\nangiopoietin-like protein 8 (ANGPTL8), or refeeding-induced fat and liver\nprotein (RIFL)7<\/sup>. Betatrophin is produced in the liver and adipocytes\nthat are two crucial tissues involved in insulin signaling pathways. The\nabnormal buildup of fat tissue not only leads to insulin resistance but also\ndisrupts the production of betatrophin8<\/sup>. <\/p>\n\n\n\n

Lately,\nthere has been a growing interest in exploration of the connection between\nbetatrophin and obesity. Rodent studies demonstrated increased levels of\nbetatrophin in obesity, which could potentially play a role in promoting beta-cell\u2019s\ngrowth and insulin production9,10<\/sup>. Moreover, a large cohort study\nshowed a positive correlation of betatrophin to BMI, and to waist-hip ratio in\npeople without diabetes9<\/sup>. Elevated betatrophin levels were observed\nin cases of impaired glucose tolerance and type 2 diabetes as compared to\nhealthy subjects11<\/sup>. Conversely, some studies have shown that\nbetatrophin was diminished in diabetic subjects12<\/sup>. Also, betatrophin\nlevels were lower in new cases of type 2 diabetes and impaired glucose\ntolerance in young individuals13<\/sup>.<\/p>\n\n\n\n

In brief,\nbetatrophin hormone has been indicated to possess a trophic action on\npancreatic beta-cells in the various states of insulin resistance with the\npurpose to develop an effective anti-diabetic therapy. However, the\nrelationship between betatrophin and obesity, insulin resistance and various\nmetabolic disorders was still a controversial situation. Physiological action\nof betatrophin in glucose metabolism is not still well comprehended.\nAccordingly, this study was designed to explore the relationship between\nbetatrophin and central obesity in middle-aged population, who is high-risk\ngroup for developing metabolic syndrome. <\/p>\n\n\n\n

Materials\nand Methods<\/strong><\/p>\n\n\n\n

This research was designed as a cross-sectional\nanalytical (comparative) study conducted with healthy\nmiddle-aged male subjects with the age between 40-60 years. The participants\nwere recruited from seven community wards of North Okkalapa Township, by convenient sampling method, till the required sample size was\nfulfilled. The subjects were distinguished according to selection criteria:\nnon-obese subjects with waist circumference less than or equal 90cm and\ncentrally obese subjects with waist circumference more than 90cm. Individuals\nwho had acute illnesses, a prior history of diabetes mellitus, cardiovascular\nissues, or liver disease, those with a family background of diabetes mellitus,\nthose with fasting plasma glucose level more than or equal to 126 mg\/dL,\nsmokers or chronic alcoholics were excluded in this study. <\/p>\n\n\n\n

Operational definitions are as follows:\nCentrally-obese subject is defined as those with waist circumference more than\n90cm in male and more than 80cm in female (WHO, Australia, 2000). Middle-aged\nsubjects are those with age between 40-60 years. Chronic alcoholic is a person who drinks distilled spirits (such\nas vodka, whiskey, rum or gin with 40% alcohol) with an average amount of 140\nml per day for 5 years14<\/sup>. A smoker is one who currently smokes at least 5-10\ncigarettes per day continuously for at least one year15<\/sup>.<\/p>\n\n\n\n

Waist circumference (WC) in\ncentimeter was gauged to the nearest 0.5 cm at the level of the mid-point\nbetween the lower margin of the lowest rib and the iliac crest in the\nmid-axillary plane. Participants were measured without clothing,\nensuring that the tape was comfortably fitted but not exerting pressure on the\nskin. The measurement was taken at the end of regular breath-out, while\nstanding position with relaxed arms beside. Hip circumference (HC) was measured\nin centimeter by taking the average of two readings of the narrowest\ncircumference around the buttocks and symphysis pubis, over light clothing. Waist-hip ratio (WHR) was calculated by dividing the waist\ncircumference by the hip circumference1<\/sup>. Body\nweight was measured in kilogram to the nearest one decimal place using a\nbalanced beam scale. Body Mass Index (BMI) was calculated by dividing the\nweight in kilograms by the square of the height in meters.<\/p>\n\n\n\n

After taking written informed consent, all subjects were overnight-fasted\nand their blood samples were collected for biochemical tests. Plasma glucose\nwas measured by GOD-PAP (Glucose oxidase, phenol, 4-aminophenazone) method\n(enzymatic colorimetric test) using Glucose Liquicolor kit and serum insulin\nlevel was measured by DRG\u00ae Insulin ELISA (EIA-2935) (DRG International, Inc.\nNJ, USA) using sandwich enzyme-linked immunosorbent assay (ELISA). Serum betatrophin level was measured\nby Human Betatrophin (Total) ELISA kit (Catalog no. SK00528-08) (Aviscera\nBioscience, Inc. CA, USA) using quantitative sandwich ELISA method. HOMA indices were calculated as follows. HOMA-IR value more than\n2.58 was assumed as insulin resistance16<\/sup>. <\/p>\n\n\n\n

HOMA-IR = Fasting\ninsulin (\u00b5IU\/ml) x Fasting glucose (mg\/dL) \/ 405.1<\/p>\n\n\n\n

HOMA-\u03b2  = [360 \u00d7 Fasting insulin (\u03bcIU\/ml)] \/ [Fasting glucose (mg\/dL) \u2212 63]\n\n\n\n

The statistical data analysis was performed using IBM SPSS Statistics\n20 software. All data were showed as mean \u00b1 standard error of the mean (SEM). A\nStudent’s two-sample “t” test was utilized to compare the mean values\nbetween different groups. Pearson’s correlation coefficient was employed to calculate\nbivariate correlations between variables. Statistical significance was\nconsidered for p<\/em>-values below 0.05.<\/p>\n\n\n\n

This study\nwas done according to guidelines of Protocol Board. The sampling procedure was\nstarted after approval of Research and Ethical Committee of Myanmar Medical\nUniversities. The subjects were invited to participate in the research and\ntheir participation was voluntary. Informed consent was obtained before any\nstudy procedure. The subjects had rights to decline participation and to\nwithdraw from the research at any time without any negative consequences or\nloss of any entitlements they would otherwise have received.<\/p>\n\n\n\n

Results<\/strong><\/p>\n\n\n\n

In the present study, 68 middle-aged male subjects (34 centrally obese and 34 non-obese subjects) had participated. The overall characteristics of the subjects were showcased in Table 1. No age difference was found between two groups. Obviously, obese group was composed of individuals with significantly higher body weight and BMI than non-obese group. Their WC, HC and WHR were also greater than non-obese subjects and therefore they were considered as centrally obese ones. <\/p>\n\n\n\n

Table 1: General characteristics of obese group and non-obese group<\/strong>.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Parameters<\/strong><\/p>\n<\/td>\n

\n

Obese group (n=34)<\/strong><\/p>\n<\/td>\n

\n

Non-obese group (n=34)<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

Age (yr)<\/p>\n<\/td>\n

\n

48.91 \u00b1 1.07<\/p>\n<\/td>\n

\n

49.29 \u00b1 0.90<\/p>\n<\/td>\n<\/tr>\n

\n

Body weight (kg)<\/p>\n<\/td>\n

\n

74.38 \u00b1 1.63<\/p>\n<\/td>\n

\n

52.82 \u00b1 1.54 *<\/p>\n<\/td>\n<\/tr>\n

\n

Height (cm)<\/p>\n<\/td>\n

\n

166.26 \u00b1 0.94<\/p>\n<\/td>\n

\n

163.48 \u00b1 1.08<\/p>\n<\/td>\n<\/tr>\n

\n

BMI (kg\/m2<\/sup>)<\/p>\n<\/td>\n

\n

26.83 \u00b1 0.42<\/p>\n<\/td>\n

\n

19.71 \u00b1 0.48 *<\/p>\n<\/td>\n<\/tr>\n

\n

Waist circumference, WC (cm)<\/p>\n<\/td>\n

\n

98.15 \u00b1 1.08<\/p>\n<\/td>\n

\n

76.03 \u00b1 1.34 *<\/p>\n<\/td>\n<\/tr>\n

\n

Hip circumference, HC (cm)<\/p>\n<\/td>\n

\n

100.01 \u00b1 0.97<\/p>\n<\/td>\n

\n

86.25 \u00b1 0.98 *<\/p>\n<\/td>\n<\/tr>\n

\n

Waist-hip ratio, WHR<\/p>\n<\/td>\n

\n

0.98 \u00b1 0.01<\/p>\n<\/td>\n

\n

0.88 \u00b1 0.01 *<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Data are mean\n\u00b1 SEM (n=34\/group). Unpaired \u201ct\u201d test was used to compare mean values. *p<0.05<\/em>\nbetween two groups.<\/p>\n\n\n\n

Figure 1 illustrated glucose\nmetabolic parameters of two subject groups. Fasting plasma glucose levels of\nboth groups were not significantly different. However, obese subjects had considerably\nhigher plasma insulin level (p<0.001<\/em>) compared with the non-obese. From\nthe calculations, HOMA index showing insulin resistance (HOMA-IR) and that\nshowing pancreatic beta-cell function (HOMA-\u03b2) were notably increased in subjects\nwith central obesity. On the other hand, centrally-obese individuals coupled\nwith markedly lower serum betatrophin level than non-obese males. <\/p>\n\n\n\n\n\n
\"\"<\/td>\nFigure 1: Metabolic parameters of the subjects indicating (A) fasting plasma glucose levels (B) fasting plasma insulin levels (C) HOMA-IR (D) HOMA-\u03b2 and (E) serum betatrophin levels. <\/strong>

<\/p>\n

Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Next, we investigated if there was any correlation between serum betatrophin concentration and glucose or insulin levels in all subjects including obese and normal ones (Figure 2A-B) after removing some outliners. Fasting plasma glucose as well as insulin concentration were negatively correlated with betatrophin level. <\/p>\n\n\n\n

Moreover, Pearson\u2019s\ncorrelation test showed that betatrophin level was of negative correlation with\nHOMA-IR and HOMA-\u03b2 values but this did not show statistically significant\ncorrelation (Figure 2C-D). Interestingly, we observed that waist circumference\nhad a significantly negative correlation with betatrophin level in the calculation\n(Figure 2E). <\/p>\n\n\n\n\n\n
\"\"<\/td>\nFigure 2: Correlation between serum betatrophin level and (A) fasting plasma glucose (B) fasting plasma insulin levels (C) HOMA-IR (D) HOMA-\u03b2.<\/strong>

<\/p>\n

Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Discussion<\/strong><\/p>\n\n\n\n

To our\nunderstanding, this is the first study conducted in Myanmar which showed a\ncorrelation between hepatic hormone, betatrophin, and central obesity among middle-aged\nmen. One of the important findings was the significant reduction in betatrophin\nlevels in individuals with central obesity. Additionally, the obese group\nexhibited significantly higher insulin resistance, and beta-cell hyperfunction\nas compared with non-obese group. There was no significant relationship of\nserum betatrophin level with HOMA-IR and HOMA-\u03b2. However, a strong negative\ncorrelation was uncovered between betatrophin level and fasting glucose level\nand fasting insulin level. <\/p>\n\n\n\n

The current\nstudy strictly limited the age of participants because age-related changes in\nadipose tissue can impact insulin sensitivity17<\/sup>, and hence, only\nmale subjects within the 40 to 60-year age range were included in our research.\nFurthermore, the key criterion to allocate two groups of subjects, those with\ncentral obesity and those without, was waist circumference. BMI, which is the\nmost widely used weight-for-height index, generally correlates well with\nadiposity although it can occasionally misclassify as total body fat contents. Moreover,\nBMI may lead to misinterpretation in cases of highly muscular athletes or\nindividuals with extreme heights. Therefore, BMI does not accurately reflect\ntrue obesity. The important factor that determines risks of cardiovascular,\ncerebrovascular, metabolic disorders is the distribution of fat, not just the\namount of fat. Intra-abdominal or visceral fat specifically poses a higher risk\nof metabolic syndromes. Although magnetic resonance imaging (MRI), computed\ntomography (CT), and dual-energy X-ray absorptiometry (DEXA) can measure this,\nthey are expensive and not readily accessible1<\/sup>. The ratio of waist\nto hip circumferences (WHR) serves as a useful measure of abdominal fat\naccumulation, yet waist circumference (WC) is a more reliable surrogate marker\nof visceral obesity, as hip circumference can be prone to inaccuracies in\ntranslation. And WC measurement is recommended in evaluating patients for\nobesity-related disease risk1<\/sup>. In our study, male participants with\na waist circumference exceeding 90cm were classified as centrally obese.<\/p>\n\n\n\n

Plasma\nglucose level is greatly variable with age, sex or nutritional status. In the\npresent study, age-matched male subjects without diabetes mellitus were chosen\nto participate and hence no difference in fasting glucose level was observed.\nConsistent with our study, non-diabetic individuals showed no significant\ndifference in fasting blood glucose among different BMI groups while higher\nfasting insulin level was found in overweight\/obese group18,19<\/sup>. Unlike\nour study, fasting glucose level was markedly higher in overweight\/obese group\nthan non-obese group in the study involving adult men and women9,12<\/sup>\nas well as in the study including children of 5-14 years of age20<\/sup>. Actually,\nblood glucose homeostatic mechanism of young individuals is effective though it\nmay be impaired in advanced age. Whether fasting glucose differs or not,\nfasting insulin was greatly increased in obese people compared with lean people\nin those reports. <\/p>\n\n\n\n

This\nsuggested that normal fasting plasma glucose level was maintained by\ncompensatory hyperinsulinemia. Initially, pancreatic beta-cells compensate for\nthe insulin resistance associated with obesity by secreting more insulin to\nmaintain normal glucose levels in centrally-obese individuals21<\/sup>. Clinical\nand experimental study reports suggested that hyperinsulinemia comes before and\ncontributes to the development of both obesity and insulin resistance. This is\nbecause insulin stimulates adipocyte differentiation, hyperplasia, or\nhypertrophy, leading to weight gain. Additionally, chronic obesity can result\nin the fat accumulation in non-adipose tissues, along with generation of proinflammatory\ncytokines, which promotes insulin resistance22<\/sup>. During the early\nstate of insulin resistance, glucose level is maintained to be normal by increasing\ninsulin production from beta-cells to counterbalance. Later, beta-cells become\nexhausted since elevated blood glucose level further stimulates insulin\nsecretion. In summary, obesity and hyperinsulinemia appear to be closely interlinked23<\/sup>.<\/p>\n\n\n\n

Although\nHyper-insulinemic Euglycemic Clamp (HIEC) was widely accepted as the \u201cgold\nstandard\u201d for evaluating insulin sensitivity, HOMA-IR) value above 2.9 units\ncan be considered a simple indicator of insulin resistance. This is because the\nformer method is time-consuming, expensive, and technically complex24<\/sup>.\nMoreover, HOMA-IR results were considerably correlated with the euglycemic\nclamp, fasting insulin concentration and hyperglycemic clamp16,25<\/sup>. Researchers\nsuggested that fasting sample-derived indices were more reliable in\nnon-diabetic subjects than type 2 diabetic ones26<\/sup>. The participants\nin the present study were literally non-diabetic individuals.<\/p>\n\n\n\n

The possible\ncauses of insulin resistance include abnormal beta-cell secretion, circulating\ninsulin antagonists, down-regulation of insulin-responsive glucose transporter\nGLUT-4, and defects in mechanisms of insulin action22<\/sup>. Insulin\nsensitivity was significantly decreased in overweight\/obese individuals when\ncompared with age-matched normal weight persons9,12,18<\/sup> and it was\nalso significantly lower in older age than BMI-matched young adults27<\/sup>.\nIt can be concluded that insulin sensitivity was markedly decreased in central\nobesity. In\u2002the pathogenesis\u2002of\u2002obesity-associated insulin\u2002resistance,\nadipocytes become a source of many adipokines including leptin,\u2002TNF-\u03b1,\u2002resistin,\u2002adiponectin,\u2002and\nso on28<\/sup>. Our study did not exclude dyslipidemia and hypertension\nwhich may be associated with insulin resistance.<\/p>\n\n\n\n

Liver was\naccepted as a critical source of beta-cell growth factors in insulin-resistance\nstate. Betatrophin, formally known as ANGPTL8, a member of Angiopoietin-like protein\nfamily, have been detected in mammalian liver, and white or brown adipose\ntissues7,29<\/sup>. Nowadays, there has been a number of studies exploring\nthe functions of betatrophin in glucose metabolism, lipid metabolism, insulin\nresistance, and metabolic syndromes. Undoubtedly, betatrophin is nutritionally\nregulated and its hepatic expression was increased after feeding. There might\nbe discrepancies in circulating levels of betatrophin unless the nutritional\nstatus was strictly controlled10<\/sup>. Therefore, only fasting blood\nsamples were collected to determine serum betatrophin concentration in our\nstudy.<\/p>\n\n\n\n

Betatrophin is\nsecreted from the liver as well as from white adipose tissues in humans, therefore,\nits level might be elevated in obesity. It was proved that obesity was\nassociated with increased level of betatrophin10<\/sup>. Additionally,\nprevious study of found that circulating betatrophin level was greater in\ncentrally obese persons than non-obese ones and decreased significantly after\nthree-month exercise training in obese persons9<\/sup>. A cross-sectional\nstudy reported that normal glucose tolerant people exhibited an increase in the\ncirculating betatrophin concentration as visceral fat expanded, while it\ndecreased with lower limb fat. There was no notable association between\nbetatrophin and body fat distribution in the impaired-glucose tolerant group30<\/sup>.\nThese results were in contradiction to our own findings. On the other hand, it\nhad signi\ufb01cantly inverse correlation between waist circumference, HOMA-IR and\nfasting and two-hour postprandial glucose12,13,31<\/sup>. Betatrophin level\nwas significantly decreased in morbid obesity but increased in anorexic women\nwhen compared with normal-weighted healthy women32<\/sup>. Besides, some\nresearch showed that betatrophin level had no significant difference between\nobese and lean subjects19<\/sup>. That body weight and body fat\ndistribution are the main factors in considering circulating betatrophin\nconcentration, has verified in the 6-month randomized control trial study with\ndietary modification and lifestyle intervention33<\/sup>. <\/p>\n\n\n\n

Nevertheless,\nour present study reported a significant reduction of betatrophin level in\nobese group. The reduced levels of circulating betatrophin in obesity might be\nexplained by the impaired ability of adipose tissue to secrete this hormone.\nThis is because the capacity of white adipose tissue to secrete betatrophin can\nbe impaired in the presence of obesity32<\/sup>. Moreover, betatrophin\nlevel may be affected by numerous uncontrollable obesity-associated changes that\noccur in adipose tissue and liver. The degree of inflammation, dyslipidemia or\nliver damage might have an impact on betatrophin secretion19<\/sup>. In the\npresent study, inflammatory cytokines, lipid profiles, serological markers that\nindicate liver damage were not measured. Discrepancies in relation between\nbetatrophin and obesity might be affected by ethnic variations, age difference\nand different kit used.<\/p>\n\n\n\n

Researchers\nemphasized upon the positive or negative correlation between betatrophin\nhormone and glucose metabolism since the interest about betatrophin has raised\nassuming it as a favorable hormone in beta-cell replication, insulin secretion\nand glucose homeostasis. There has been demonstrated that betatrophin had\nnegative correlation with fasting plasma glucose in our study consistently with\nthe previous studies10<\/sup> and it was significantly associated with\ntwo-hour post-prandial glucose13,19,34<\/sup>. It pointed out betatrophin\nwould be involved in glucose homeostasis.<\/p>\n\n\n\n

Previous reports\ndemonstrated that betatrophin was significantly increased in the state of glucose\nintolerance34<\/sup>, insulin resistance10,19,35<\/sup>, polycystic\novarian syndrome36<\/sup>, type 2 diabetes37<\/sup>, and gestational\ndiabetes38<\/sup> in comparison to normal people. They suggested that\nbetatrophin was a potential biomarker in insulin resistance state and diabetes\nmellitus. Conversely, in some reports betatrophin was reduced in diabetic\nsubjects12,13<\/sup>. Due to these conflicting results, it was not clear that\nboosted betatrophin expression serves as a compensatory reaction or simply acts\nas a marker of insulin resistance. In the present study, centrally-obese group\nconsisted of only two obese persons (BMI more than 30kg\/m2<\/sup>) and all\nsubjects were non-diabetic. That betatrophin was not correlated with insulin\nresistance might be as a result of only a few participations of subjects with\nextreme BMI and no involvement of diabetic subjects.<\/p>\n\n\n\n

In the\npresent study, centrally-obese group had significantly higher HOMA-\u03b2 value than\nnon-obese group. Thus, pancreatic beta-cells in central obesity may compensate\nthe condition of peripheral insulin resistance. Beyond the compensated state, beta-cells\nwould be exhausted and diabetes mellitus might develop. Not a significant\ncorrelation was found between beta-cell function (as indicated as HOMA-\u03b2) and\nserum betatrophin level. Therefore, serum betatrophin level was not associated\nwith beta-cell\u2019s compensation ability and might not be responsible hormone to\nbeta-cell proliferation. Supporting to it, in the study of mice lacking betatrophin,\nnormal glucose homeostasis was found39<\/sup> and normal beta-cell mass was\nexhibited40<\/sup>. Elevated hepatic betatrophin expression was showed to increase\nmice beta-cell mass but not human beta-cells transplanted into mice41<\/sup>.\nThese animal studies verified that betatrophin was not recommended to be\nbeta-cell mitogen. On the other hand, in human study, increased serum\nbetatrophin was noted in individuals with deprived beta-cell function, serving as\na compensated hormone. Likewise, betatrophin levels were found to be elevated\nin cases of type 2 diabetes characterized by diminished beta-cell function as\nopposed to normal or impaired glucose tolerance but better beta-cell function34<\/sup>.\nTherefore, the role of betatrophin in glucose homeostasis and insulin secretion\nremains complicated.<\/p>\n\n\n\n

Limitations<\/strong><\/p>\n\n\n\n

The present\nstudy was cross-sectional analytical study, and it focused only on the\nrelationship of betatrophin and glucose metabolic parameters. Thus, it cannot\nestablish a cause-effect relationship between betatrophin hormone and\nobesity-related metabolic diseases. Due to the conflicting findings in various\nstudies, including the current one, the mechanism of betatrophin in glucose\nmetabolism remains unclear. Further advanced research is recommended to\ninvestigate and confirm the regulation, function, and clinical significance of\nthe betatrophin hormone. <\/p>\n\n\n\n

Conclusion<\/strong><\/p>\n\n\n\n

To conclude,\nthe current study showed that central obesity was associated with insulin\nresistance, hyperinsulinemia without hyperglycemia, beta-cell hyperfunction,\nplus significant reduction in betatrophin hormone. It was also observed that\nbetatrophin was appreciably reduced in central obesity and strongly concomitant\nwith lower blood glucose and insulin levels. These findings suggest that the\nprimary reason for the lower levels of serum betatrophin in central obesity is\nlikely the diminished capacity of adipose tissues to form betatrophin. Another\nsignificant observation is that betatrophin did not demonstrate an ability to\nenhance beta-cell function and might not involve in compensatory mechanism to\ninsulin resistance in central obesity. Therefore, our study did not support the\nprevious assumption that betatrophin acts as a mitogen for human beta-cells. <\/p>\n\n\n\n

Acknowledgement<\/strong><\/p>\n\n\n\n

We would like to\nacknowledge the valuable guidance and support of our supervisors. We declare that\nthis work was done by the authors named in this article and all liabilities pertaining\nto claims relating to the content of this article will be borne by the authors.<\/p>\n\n\n\n

Conflict of Interest<\/strong><\/p>\n\n\n\n

The authors declare that\nthere are no conflicts of interest regarding the publication of this paper.<\/p>\n\n\n\n

References<\/strong><\/p>\n\n\n\n

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