Published online Apr 15, 2019. doi: 10.4239/wjd.v10.i4.260
Peer-review started: February 10, 2019
First decision: March 11, 2015
Revised: April 11, 2015
Accepted: April 14, 2019
Article in press: April 14, 2019
Published online: April 15, 2019
Processing time: 66 Days and 22.5 Hours
Both obesity and vitamin D deficiency are important health issues in Pakistan. The connection between body composition, Vitamin D and leptin in young adults is important to be studied as body composition may affect bone health and therefore the possibility of osteoporosis in later life. Few studies have attempted to investigate the effect of body composition and leptin with vitamin D in adolescence.
To investigate the association of serum leptin with body composition, lipids and 25-hydroxyvitamin D (25OHD) in adults.
This cross-sectional study was conducted on 167 apparently healthy adults. Demographics were recorded, bioelectrical impedance analysis was performed and clinical history noted. Serum leptin was measured using DIA source kit on ELISA and total 25OHD was measured on ADVIA-Centaur; Siemens. Total cholesterol and high density lipoprotein cholesterol were quantified using Enzymatic Endpoint Method and Cholesterol Oxidase-Phenol Aminophenazone method respectively. Biochemical analysis was done in the Departments of Pathology and Laboratory Medicine and Biological and Biomedical Sciences, Aga Khan University Hospital Karachi Pakistan.
Median age of the group (n = 167) was 20 years (IQR 27-20); 55.7% were females. Majority (89.2%, n = 149) of the study group was 25OHD deficient, 6% (n = 10) had insufficient serum 25OHD levels and 4.8% (n = 8) had sufficient D levels. Females, had higher median leptin levels [2.71 (IQR 4.76-1.66 ng/mL)] compared to their counterparts [1.3 (3.60-0.54 ng/mL), P < 0.01]. Multiple regression analysis suggested that basal metabolic rate, muscle mass, body fat percent, bone mass and serum 25OHD were the most contributing factors to serum leptin levels. Bone mass and serum 25OHD in fact bore a negative correlation with leptin.
The results indicate that basal metabolic rate, muscle mass, body fat percent, bone mass and serum 25OHD have an impact on serum leptin. Being a cross sectional study causal relationship between leptin and other variables could not be determined.
Core tip: The paper explored variables like anthropometric measurements, body composition, vitamin D and lipoproteins as predictors for serum leptin levels among representative population of healthy adults in Pakistan. The cross-sectional nature of this study could not elucidate causal relationships. However, it outlines important interplay between circulating leptin, vitamin D and body composition. The results indicate that basal metabolic rate, muscle mass, body fat percent, bone mass and serum vitamin D have an impact on serum leptin.
- Citation: Khan AH, Fatima SS, Raheem A, Jafri L. Are serum leptin levels predicted by lipoproteins, vitamin D and body composition? World J Diabetes 2019; 10(4): 260-268
- URL: https://www.wjgnet.com/1948-9358/full/v10/i4/260.htm
- DOI: https://dx.doi.org/10.4239/wjd.v10.i4.260
Quite a few cross-sectional studies have explored leptin and obesity in relation to Vitamin D deficiency (VDD) but the findings is inconsistent and conflicting[1-4]. The limited available literature differs considerably in terms of study design, subjects studied and results reported, making it challenging to infer. The cause-effect relationship between leptin, VDD and obesity remains unclear. The link between vitamin D and obesity has been put forward by some genetic and secondary lines of evidences[5-7]. Secondary factors common to both obesity and VDD are environmental aspects like dietary, racial, topographical, seasonal, and environmental pollution[8-10]. Genetic studies have shown to link molecular variations of Vitamin D metabolism with obesity[11-13]. The hereditary risk factors include polycystic ovary disease, cytochrome P450, locus 20q13, vitamin D-binding protein gene polymorphisms, and aP2 gene. The VDR polymorphisms were described to be linked to adiposity phenotypes[14,15].
Given the potential for positive associations of VDD and leptin concentration with obesity and the development of cardiovascular disease, the identification of modifiable lifestyle factors associated with leptin levels is vitally important to prevent obesity and its associated complications[16]. Additionally, the connection between body composition, especially fat content in the body, and Vitamin D and leptin in young adults is clinically vital because management that modify body weight may affect bone health and therefore the possibility of osteoporosis in later life. Few studies have attempted to investigate the effect of body composition and leptin with vitamin D in adolescence[17,18]. This study was conducted to analyze serum leptin concentrations in samples from adult volunteers and correlate it with body composition parameters, difference in gender, 25-hydroxy vitamin D (25OHD) and lipids.
This cross sectional analysis was done from June 2014 till January 2016, in the Section of Clinical Chemistry, Department of Pathology and Laboratory Medicine and Department of Biological and Biomedical Sciences, Aga Khan University Hospital Karachi Pakistan. Apparently healthy adult volunteers were invited to join in the research once informed consent was taken. Approval from the Aga Khan University Ethical Review Committee was taken for conducting this study (ERC number: 2810-Pat-ERC-13). A 4-d phlebotomy camp was set up in the Multidisciplinary Laboratory on the University campus for collection of blood samples. Subjects were excluded if they reported having had: intramuscular supplementation of Vitamin D in the last 6 mo, remarkable changes in weight or diet in the last 6 mo, any disease that may affect their Vitamin D levels or any known metabolic disorder. Subjects taking small dose of oral Vitamin D supplements, for example such that may be contained in a daily multivitamin pill (400 IU) since such a low amount would not significantly change serum 25OHD levels, were allowed to participate[19].
An interviewer-administered history form tailored for the adult Pakistani urban population[20], was used to assess the clinical history and health status of the study group. Waist circumference was measured in cm. Each subject’s weight (kg) and height (m) were recorded, and the resultant body mass index (BMI) was calculated and reported in kg/m2. BMI values were categorized as per the recommended reference ranges for the Pakistani population[21]. A bioelectrical impedance analyzer (BIA) by Tanita was used to assess body composition variables of the study group. BIA is a validated method of estimating adiposity in both clinical and non-clinical settings[22]. BIA measurements included total body fat percentage (reported as %), total body water percentage (reported as %), total muscle mass (reported in kg), basal metabolic rate (reported in kcal) and total bone mass (reported in kg). International body fat reference ranges for young adults were used to group subjects.
After informed consent blood was drawn in gel separation tubes and centrifuged at 3500 rpm for 5 min for separation of serum. Separated serum was transferred to aliquots, labeled with the participant’s serial number and immediately stored at -30°C.
A BIA was used to assess body composition variables of the study group. BIA is a validated method of estimating adiposity in both clinical and non-clinical settings[22]. BIA measurements included total body fat percentage, total body water percentage, total muscle mass, basal metabolic rate and metabolic age, total bone mass and visceral fat mass. International body fat reference ranges for young adults were used to group subjects.
Leptin was measured using manual ELISA on a kit from DIA source (Belgium). The microtiter wells were coated with a monoclonal anti-leptin antibody. 25OHD was quantified by chemiluminescence on ADVIA Centaur Immunoassay System (Siemens AG, Munich, Germany) in batch. The measuring range of the assay was 3.7-150 ng/mL. Total cholesterol was measured using an enzymatic endpoint method, while cholesterol oxidase-phenol aminophenazone method was used for analysis of high density lipoprotein (HDL) cholesterol by using kits from Randox Laboratories, United Kingdom on spectrophotometer. Non HDL was calculated by subtracting HDL from total cholesterol. To validate the biochemical results high and low levels of quality control material for leptin, 25OHD, cholesterol and HDL were run with the batches. Classification of VDD was based on the circulating 25OHD concentrations of less than 20 ng/mL. Levels between 20-30 ng/mL as insufficiency and > 30 ng/mL as sufficient D levels. Serum leptin was interpreted taking both BMI and gender into account.
All Statistical analysis was done on R-Software (R Version 3.5.3) and Statistical Package for Social Sciences (Version 22, SPSS Inc. Chicago, IL.). All parametric variables were reported as mean ± SD and non-parametric as median with interquartile ranges 75th-25th. Differences between two groups of parametric variables were evaluated using independent samples t-test. To compare median values between two groups Mann Whitney U test was applied. Serum leptin and 25OHD were not normally distributed and hence were log transformed before correlation was conducted. As an initial step, we explored Pearson correlational relationships and applied Chi-square for categorical data between the measured independent variables taking serum leptin as dependent variable. Univariate analysis was conducted and variables that had significant association with leptin in univariate analysis at P < 0.2 were entered in multivariable analysis. Multivariate regression analyses were conducted for the dependent variable (serum leptin) and independent variables [BMI, basal metabolic rate (BMR), muscle mass, body water %, body fat %, bone mass, waist circumference, log 25OHD, male gender]. For working out the magnitude of associations between independent-dependent variables, beta weight of the variables was calculated. All tests were two-tailed, and the level of significance was set to P-value less than 0.05 as significant and < 0.01 was considered greatly significant.
A total of 167 subjects were enrolled; there was a near equal gender distribution with Female: Male 93:74. No statistically significant difference for age was found between the two genders. None of the subjects studied had any clinical signs of disease associated with obesity and were not on any medications. Of the total seven were cigarette smokers (4.1%); 2 smokers were females and the rest were males. Characteristics of the study population are summarized in Table 1.
| Description | Overall | Males | Females | P value | Overweight and obese (BMI > 23 kg/m2) | Non obese (BMI < 23 kg/m2) | P value |
| n | 167 | 74 | 93 | 76 (50% Females) | 91 (60.4% Females) | ||
| Anthropometric parameters | |||||||
| Median age (IQR) in yr | 20 (27-20) | 21(29-20) | 20(23-20) | 0.136 | 21 (35.5-20) | 20 (21-20) | < 0.01 |
| Mean height (SD) in cm | 168 (9.2) | 172 (8.2) | 164.8 (8.7) | < 0.01 | 167.9 (9.7) | 168.1 (8.8) | 0.837 |
| Mean weight (SD) in kg | 65.0 (4.4) | 70.2 (14.9) | 60.9 (12.6) | < 0.01 | 75.1 (14.1) | 56.6 (7.7) | < 0.01 |
| Mean BMI (SD) in kg/m2 | 23 (4.6) | 23.7 (5.1) | 23.7 (5.1) | 0.056 | 26.6 (4.3) | 19.9 (1.8) | < 0.01 |
| Mean waist circumference (SD) in cm | 79.1 (12.8) | 83.3 (13.3) | 75.7 (11.3) | < 0.01 | 86.9 (12.4) | 72.5 (8.8) | < 0.01 |
| Body composition | |||||||
| Mean total body fat % (SD) | 22.1 (8.7) | 19.7 (9.0) | 23.9 (8.0) | < 0.01 | 27.5 (7.5) | 17.5 (6.8) | < 0.01 |
| Under fat n (%) | 44 (26.3) | 5 (6.8) | 39 (41.9) | < 0.01 | 3 (3.9) | 41 (45) | < 0.01 |
| Healthy n (%) | 78 (46.7) | 38 (51.4) | 40 (43) | < 0.01 | 33 (43.4) | 45 (49.4) | < 0.01 |
| Over fat n (%) | 21 (12.6) | 11 (14.9) | 10 (10.8) | < 0.01 | 19 (25) | 2 (2.1) | < 0.01 |
| Obese n (%) | 24 (14.4) | 20 (27) | 4 (4.3) | < 0.01 | 21 (27.6) | 3 (3.2) | < 0.01 |
| Mean total body water % | 55.7 (6.1) | 57.8 (6.3) | 54.1 (5.4) | < 0.01 | 52.3 (4.9) | 58.6 (5.5) | 0.255 |
| Ideal body water n (%) | 142 (85) | 61 (82.4) | 81 (87.1) | 0.235 | 68 (89.4%) | 74 (81.3%) | < 0.01 |
| Mean muscle mass (SD) in kg | 45.7 (7.9) | 50.2 (8.4) | 42 (5.1) | < 0.01 | 46.3 (8.7) | 45.1 (7.2) | 0.357 |
| Median BMR (IQR) in kcal | 1501 (1750-1336) | 1732 (1875-1551) | 1377 (1525-1300) | < 0.01 | 1690 (1892.5-1421.5) | 1417 (1612-1308) | < 0.01 |
| Median bone mass (IQR) in kg | 2.5 (3-2.1) | 2.9 (3.2-2.6) | 2.2 (2.4-2) | < 0.01 | 2.9 (3.2-2.3) | 2.2 (2.8-2.0) | < 0.01 |
| Healthy bone mass n (%) | 71 (42.5) | 31 (41.9) | 40 (43) | 0.884 | 36 (47.3%) | 35 (38.4%) | 0.273 |
| Biochemical parameters | |||||||
| Median leptin (ng/mL) | 2.2 (4.5-1.0) | 1.3 (3.60-0.54) | 2.71 (4.76-1.66) | < 0.01 | 3.0 (5.8-1.5) | 1.7 (3.4- -0.7) | < 0.01 |
| Elevated serum leptin n (%) | 17 (10.2) | 7 (9.5) | 10 (10.8) | 0.784 | 9 (11.8%) | 8 (8.8%) | 0.61 |
| Median 25OHD (IQR) in ng/mL | 12.1 (16.1-7.7) | 12.5 (16-8.5) | 11.5 (16.6-7.5) | 0.877 | 12.1 (16.8-8.5) | 12 (15.9-7.1) | 0.479 |
| 25OHD status: Deficiency n (%) | 149 (89.2) | 69 (93.2) | 80 (86) | 67 (88.1%) | 82 (90.1%) | ||
| 25OHD status: Insufficiency n (%) | 10 (6) | 5 (6.8) | 5 (5.4) | 0.03 | 4 (5.2%) | 6 (6.5%) | 0.585 |
| Sufficiency n (%) | 8 (4.8) | - | 8 (8.6) | 5 (6.5%) | 3 (3.2%) | ||
| Mean total cholesterol (SD) in mg/dL | 175.8 (46.3) | 172 (49.4) | 178.8 (43.7) | 0.345 | 180.8 (48.6) | 171 ± 44 | 0.199 |
| Mean HDL (SD) in mg/dL | 41.1 (9.6) | 40.4 (10) | 41.6 (9.2) | 0.44 | 40.5 (9.4) | 41.540.5 ± 9.49.7 | 0.498 |
| Mean non-HDL (SD) in mg/dL | 134.7 (47.2) | 131.5 (52.4) | 137.2 (42.8) | 0.446 | 14040.5 (9.450.1) | 13040.5 ± 9.444.4 | 0.163 |
No statistically significant difference in BMI between males and females was noted however, the male adolescents had significantly higher body height and weight than their female counterparts (P < 0.001). According to the South-Asian Classification of weight status, 14.4% (n = 24) of the study-subjects were categorized as underweight (less than 18.5 kg/m2), 40.1% (n = 67) as normal (from 18.5 to 22.9 kg/m2), 22.2% (n = 37) as overweight (from 23 to 25 kg/m2) and 23.4% (n = 39) as obese (greater than 25 kg/m2).
Taking age and gender into account study subjects were additionally stratified according to body fat percent as under fat, healthy, over fat and obese. Upon stratification according to body fat percent 14.4 % (n = 24) were obese while 12.6% (n = 21) were overweight. Body fat % was significantly higher amongst subjects who were overweight and obese as per BMI [mean body fat %: 27.5 (7.5)] as compared to non-obese [mean body fat %: 17.5 (6.8)] as depicted in Table 2. Percent of body water in study subjects was ideal (i.e., 45%-60% in females and between 50%-65% in males) in 80% subjects (n = 142), low in 6% (n = 10) and excessive in 9% (n = 15).
| Gender | n | BMI (kg/m2) | Waist circumference (cm) | Total body fat % | Total body water % | Muscle mass (kg) | BMR (kcal) | Bone mass (kg) | Total cholesterol (mg/dL) | Mean HDL(mg/dL) | Mean non-HDL(mg/dL) | Log 25OHD (ng/mL) |
| Male | 74 | 0.2561 | 0.2561 | 0.472 | -0.3312 | -0.4992 | -0.018 | -0.206 | -0.053 | -0.139 | -0.023 | -0.4792 |
| Female | 93 | 0.3772 | 0.3622 | 0.3222 | -0.2712 | 0.02 | -0.332b | 0.247a | -0.169 | -0.176 | -0.135 | -0.102 |
| Overall | 167 | 0.2392 | 0.1811 | 0.4452 | -0.3642 | -0.4262 | -0.047 | -0.137 | -0.72 | -0.127 | -0.045 | -0.2752 |
A Shapiro Wilk test (P < 0.05) and visual scrutiny of 25OHD and leptin histograms, Q-Q plots and box plots showed that both analytes were not normally distributed, with a skewness of 1.8 (S.E 0.18) and 3.5 (S.E 0.18) respectively and kurtosis of 5.9 (S.E 0.37) and 17.4 (S.E 0.37) respectively. Majority (89.2%, n = 149) of the study group was 25OHD deficient, 6% (n = 10) had insufficient serum 25OHD levels and 4.8% (n = 8) had sufficient D levels. Of a total of 167 sera analyzed, the lowermost and uppermost serum leptin levels noted were 0.02 and 45.3 ng/mL, respectively. Females had higher median leptin levels [2.71 (IQR: 4.76-1.66 ng/mL)] compared to males [1.3 (3.60-0.54 ng/mL), P < 0.01]. Overall 17 (10.1%) study subjects had raised serum leptin levels with 88.2% (n = 15) of these subjects being Vitamin D deficient. However, 89.3% (n = 134) of the subjects with normal serum leptin were also deficient in 25OHD.
The Table 2 describes the relevant Pearson correlation coefficients and their degrees of significance between leptin and other variables in the total study population and in both genders separately. A greatly significant, moderate positive linear relationship was seen between log of leptin and BMI, waist circumference and also with total body fat percent in females (P < 0.01). While a greatly significant negative association was prominent between log of serum leptin and total water percent and basic metabolic rate in the females (P < 0.01). In males log leptin exhibited positive relation with BMI (P < 0.05), waist circumference (P < 0.05) and body fat percent (P < 0.01) and inverse correlation with total water percent, muscle mass and log 25OHD (P < 0.01). Variables that had significant association with leptin in univariate analysis at P < 0.2 were entered in multivariable analysis.
Multiple regression analysis displayed that BMR, muscle and bone mass, body fat percent, 25OHD and gender were the utmost contributing factors to serum leptin levels. Bone and muscle mass and serum 25OHD bore an inverse relation with serum leptin. The value of R square and adjusted R square was 0.387 and 0.352 respectively specifying strong association between various independent and dependent variables. This showed a positive relationship of 38.7% between independent and dependent variable (leptin). Corrected R square indicated the fit of the model more closely in population. Table 3 summarizes the results of multivariate regression analysis. It shows that among various parameters (like BMR, female gender and bone mass) which were contributing towards leptin levels body fat percent with standardized beta weight of 0.488 was the most influential factor in leptin values followed by muscle mass (beta of -0.265) and 25OHD (beta of -0.253). Body mass index, waist circumference and body water percent were not good predictors for serum leptin. Statistics from multi-collinearity displayed tolerance < 10 indicating good associations with leptin. Moreover, muscle mass, bone mass, 25OHD and male gender showed a negative influence on leptin levels.
| Independent variables | Standardized β | T value | P value | 95%CI for B | Collinearity statistics | |
| Tolerance | VIF | |||||
| BMI | 0.017 | 1.057 | 0.292 | -0.015-0.049 | 0.238 | 4.208 |
| BMR | 0.000 | 2.281 | 0.024 | 0.000-0.001 | 0.396 | 2.526 |
| Muscle mass | -0.265 | -2.995 | 0.003 | -0.032-0.007 | 0.530 | 1.885 |
| Body water (%) | 0.308 | 1.875 | 0.063 | -0.002-0.060 | 0.147 | 6.792 |
| Body fat (%) | 0.488 | 2.588 | 0.011 | 0.008-0.058 | 0.129 | 7.751 |
| Bone mass | -0.191 | -2.137 | 0.034 | -0.032-0.007 | 0.523 | 1.912 |
| Waist Circumference | -0.022 | -0.201 | 0.841 | -0.011-0.009 | 0.468 | 2.138 |
| Log 25OHD | -0.253 | -3.816 | 0.000 | -0.720-0.232 | 0.944 | 1.060 |
| Male gender | -0.186 | -2.155 | 0.033 | -0.419-0.018 | 0.522 | 1.916 |
This study explored variables like anthropometric measurements, body composition, 25OHD and lipoproteins as predictors for serum leptin levels among representative population of healthy adults in Pakistan. Majority of the subjects were D deficient (89.2%). This is not surprising as previous published papers have shown high prevalence of VDD both in Pakistanis living abroad or residing in Pakistan[23,24]. Pakistan is among the sun-drenched countries and cutaneous production of vitamin D is possible throughout the year. However, despite this favorable climatic condition, research reports from our center showed widespread VDD[25-28]. Serum 25OHD showed non-significant and poor association with BMI in this study; contradicting to reports from other part of the world which showed inverse relationship of vitamin D with BMI[4]. The proposed hypothesis for could be attributed to Vitamin D lipophilic nature, that leads to 25OHD storage or sequestration in fat tissue. This volume-distribution effect could result in diminished vitamin D bioavailability and VDD in those with extra body weight. Reason for poor association of 25OHD with BMI could be that majority of our population was deficient in Vitamin D. Relationship could not be established as even non-obese subjects in this study were D deficient (88.7%). Similar trend was observed in previous study by our group, yet low vitamin D did not depict any change in BMD which may highlight the bone mineralization effects of raised leptin[29].
Obesity has been associated with both leptin and VDD[30,31]. Leptin regulates body fat mass and has a significant role in the control of body weight[32]. Leptin is directly associated with fat mass, circulating leptin molecules carry information to the brain (hypothalamus) regarding the energy stored in adipose tissue, diminishing appetite and affecting energy expenditure[33]. The receptors of leptin molecules are found in all places in the body indicating a general role[34]. Obesity is considered a leptin resistant state resulting in excessive growth of adipose tissue and high serum leptin levels. An indirect effect is of UVB radiation exposure and the latitude gradients on VDD and obesity. Hoseinzadeh et al[10] confirmed that the topographical factor varied with the variation in vitamin D levels in obese and the prevalence of VDD among African-American children and adolescents were 57% and 48.7% in Pennsylvania (latitude 40oN) and Wisconsin (latitude 43oN), respectively.
Going at par with VDD, obesity is also becoming a fast-growing health concern in Pakistan. Surplus body weight is a risk factor for many medical diseases, including cardiac disease, diabetes, arthritis and several cancers. According to recent studies, overweight and obesity have been shown to be related to low vitamin D status. For instance, according to a study in Oslo, Norway, the prevalence of VDD was highest in individuals with greater BMI regardless of their gender. Accumulating epidemiological evidence suggests that hypovitaminosis D may be associated with obesity and related metabolic risks[35]. The levels of 25OHD are associated with BMI, declining with increasing BMI[36]. This is because adipocytes take up the Vitamin D from the blood, hence reducing the serum Vitamin D concentrations. This indicates that there is a link between Vitamin D levels and BMI which is a measure of relative weight based on an individual's mass and height. Hence, we hypothesized that lower Vitamin D levels would be noted with increasing BMI status among healthy individuals.
Similar to our study findings multiple studies have reported higher levels of leptin in females and this can be explained by differences in sex hormones[37,38]. Our study findings showed that male gender inversely contributed towards leptin levels with standardized beta weight of -0.253.
The present study has few limitations. Firstly, it was a cross sectional study hence causal relationship between leptin and other variables could not be determined. Secondly, the sample size was limited to predict any valid conclusion for a large set of population. Some gender-specific interlink was also noted, but absence of data of follicle stimulating hormone, luteinizing hormone, estradiol and testosterone levels could not allow the confirmation of this hypothesis. However, the study overall adds to the scientific knowledge of the burden of vitamin D in relation to healthy individuals.
In conclusion, this cross sectional study confirmed the relation between basal metabolic rate, muscle mass, body fat percent, bone mass, serum 25OHD and serum leptin levels. Additional studies are obligatory to define the role of hypothalamic control of body in bone formation. Elucidation of such mechanism may lead to a novel therapeutic approach to osteoporosis. Another question that remains unanswered is whether overweight/obese requiring more intense vitamin D supplementation to achieve optimal levels of 25OHD. It will also be interesting how weight loss or vitamin D treatment could affect leptin levels in this population.
Obesity is considered a leptin resistant state leading to elevated leptin levels. Obesity in turn has also been linked to Vitamin D deficiency (VDD).
Going at par with VDD, obesity is also becoming a rapidly growing health problem in Pakistan. Obesity has been associated with both leptin and VDD. Few studies have attempted to investigate the effect of body composition and leptin with vitamin D in this part of the world.
We investigated the relation of serum leptin with body composition, lipids and vitamin D in adults.
In a cross sectional study design bioelectrical impedance analysis was performed on 167 apparently healthy adults along with recording their demographics and clinical history. Blood was drawn for biochemical analysis of serum leptin, total vitamin D, total cholesterol and HDL cholesterol.
Majority of the study group was vitamin D deficient. Females had higher median leptin levels compared to their counterparts. Overall 17 (10.1%) study subjects had raised serum leptin levels with 88.2% of these subjects being Vitamin D deficient. Basic metabolic rate, muscle mass, bone mass, body fat percent, lipids and 25-hydroxyvitamin D (25OHD) and gender were associated with serum leptin levels. Bone and muscle mass and serum 25OHD bore an inverse relation with serum leptin.
The cross-sectional nature of this study could not elucidate causal relationships. However, it outlines important interplay between circulating leptin, vitamin D and body composition. The results indicate that basal metabolic rate, muscle mass, body fat percent, bone mass and serum vitamin D have an impact on serum leptin levels. 25OHD did not vary between obese and non-obese. This probably could be because > 80% of the study group was D deficient.
Future studies addressing the causal relationships between these essential molecules, leptin, vitamin D and lipids is needed to better understand their use as biomarkers of risk for obesity and diseases associated with obesity.
Manuscript source: Unsolicited manuscript
Specialty type: Endocrinology and metabolism
Country of origin: Pakistan
Peer-review report classification
Grade A (Excellent): 0
Grade B (Very good): B
Grade C (Good): 0
Grade D (Fair): D
Grade E (Poor): 0
P-Reviewer: Richardson WS, Feizi A S-Editor: Dou Y L-Editor: A E-Editor: Zhang YL
| 1. | Wu N, Wang QP, Li H, Wu XP, Sun ZQ, Luo XH. Relationships between serum adiponectin, leptin concentrations and bone mineral density, and bone biochemical markers in Chinese women. Clin Chim Acta. 2010;411:771-775. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 29] [Cited by in F6Publishing: 35] [Article Influence: 2.5] [Reference Citation Analysis (0)] |
| 2. | Kocot J, Dziemidok P, Kiełczykowska M, Kurzepa J, Szcześniak G, Musik I. Is There Any Relationship between Plasma 25-Hydroxyvitamin D₃, Adipokine Profiles and Excessive Body Weight in Type 2 Diabetic Patients? Int J Environ Res Public Health. 2017;15. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 8] [Cited by in F6Publishing: 8] [Article Influence: 1.1] [Reference Citation Analysis (0)] |
| 3. | Ismail MM, Abdel Hamid TA, Ibrahim AA, Marzouk H. Serum adipokines and vitamin D levels in patients with type 1 diabetes mellitus. Arch Med Sci. 2017;13:738-744. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 15] [Cited by in F6Publishing: 16] [Article Influence: 2.3] [Reference Citation Analysis (0)] |
| 4. | Mai S, Walker GE, Vietti R, Cattaldo S, Mele C, Priano L, Mauro A, Bona G, Aimaretti G, Scacchi M, Marzullo P. Acute Vitamin D₃ Supplementation in Severe Obesity: Evaluation of Multimeric Adiponectin. Nutrients. 2017;9. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 16] [Cited by in F6Publishing: 16] [Article Influence: 2.3] [Reference Citation Analysis (0)] |
| 5. | Grethen E, Hill KM, Jones R, Cacucci BM, Gupta CE, Acton A, Considine RV, Peacock M. Serum leptin, parathyroid hormone, 1,25-dihydroxyvitamin D, fibroblast growth factor 23, bone alkaline phosphatase, and sclerostin relationships in obesity. J Clin Endocrinol Metab. 2012;97:1655-1662. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 111] [Cited by in F6Publishing: 108] [Article Influence: 9.0] [Reference Citation Analysis (0)] |
| 6. | Taes YE, Goemaere S, Huang G, Van Pottelbergh I, De Bacquer D, Verhasselt B, Van den Broeke C, Delanghe JR, Kaufman JM. Vitamin D binding protein, bone status and body composition in community-dwelling elderly men. Bone. 2006;38:701-707. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 49] [Cited by in F6Publishing: 50] [Article Influence: 2.8] [Reference Citation Analysis (0)] |
| 7. | Ruiz-Ojeda FJ, Anguita-Ruiz A, Leis R, Aguilera CM. Genetic Factors and Molecular Mechanisms of Vitamin D and Obesity Relationship. Ann Nutr Metab. 2018;73:89-99. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 34] [Cited by in F6Publishing: 60] [Article Influence: 10.0] [Reference Citation Analysis (0)] |
| 8. | Iqbal R, Jafri L, Haroon A, Habib Khan A. Illuminating the dark side--vitamin D status in different localities of Karachi. J Coll Physicians Surg Pak. 2013;23:604-606. [PubMed] [Cited in This Article: ] |
| 9. | Khan AH, Iqbal R, Naureen G, Dar FJ, Ahmed FN. Prevalence of vitamin D deficiency and its correlates: results of a community-based study conducted in Karachi, Pakistan. Arch Osteoporos. 2012;7:275-282. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 28] [Cited by in F6Publishing: 36] [Article Influence: 3.0] [Reference Citation Analysis (0)] |
| 10. | Hoseinzadeh E, Taha P, Wei C, Godini H, Ashraf GM, Taghavi M, Miri M. The impact of air pollutants, UV exposure and geographic location on vitamin D deficiency. Food Chem Toxicol. 2018;113:241-254. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 38] [Cited by in F6Publishing: 30] [Article Influence: 5.0] [Reference Citation Analysis (0)] |
| 11. | Sergeev IN. Vitamin D-Cellular Ca2+ link to obesity and diabetes. J Steroid Biochem Mol Biol. 2016;164:326-330. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 22] [Cited by in F6Publishing: 16] [Article Influence: 2.0] [Reference Citation Analysis (0)] |
| 12. | Yao Y, Zhu L, He L, Duan Y, Liang W, Nie Z, Jin Y, Wu X, Fang Y. A meta-analysis of the relationship between vitamin D deficiency and obesity. Int J Clin Exp Med. 2015;8:14977-14984. [PubMed] [Cited in This Article: ] |
| 13. | Pereira-Santos M, Costa PR, Assis AM, Santos CA, Santos DB. Obesity and vitamin D deficiency: a systematic review and meta-analysis. Obes Rev. 2015;16:341-349. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 491] [Cited by in F6Publishing: 543] [Article Influence: 60.3] [Reference Citation Analysis (0)] |
| 14. | Angel B, Lera L, Márquez C, Albala C. The association of VDR polymorphisms and type 2 diabetes in older people living in community in Santiago de Chile. Nutr Diabetes. 2018;8:31. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 28] [Cited by in F6Publishing: 30] [Article Influence: 5.0] [Reference Citation Analysis (0)] |
| 15. | Al-Hazmi AS, Al-Mehmadi MM, Al-Bogami SM, Shami AA, Al-Askary AA, Alomery AM, Al-Shehri SS, Dahlawi H, Abdulrazag K, Ali T, Al-Bogami A, Sheshah E, Al-Mutairi A, Al-Suhimi S, Alharb F. Vitamin D receptor gene polymorphisms as a risk factor for obesity in Saudi men. Electron Physician. 2017;9:5427-5433. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 16] [Cited by in F6Publishing: 18] [Article Influence: 2.6] [Reference Citation Analysis (0)] |
| 16. | Mechanick JI, Zhao S, Garvey WT. Leptin, An Adipokine With Central Importance in the Global Obesity Problem. Glob Heart. 2018;13:113-127. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 30] [Cited by in F6Publishing: 34] [Article Influence: 4.9] [Reference Citation Analysis (0)] |
| 17. | Cirmanova V, Zofkova I, Kasalicky P, Lanska V, Bayer M, Starka L, Kanceva R. Hormonal and bone parameters in pubertal girls. Physiol Res. 2017;66:S419-S424. [PubMed] [Cited in This Article: ] |
| 18. | Giudici KV PhD, Fisberg RM, Marchioni DML, Peters BSE, Martini LA. Crosstalk Between Bone and Fat Tissue: Associations Between Vitamin D, Osteocalcin, Adipokines, and Markers of Glucose Metabolism Among Adolescents. J Am Coll Nutr. 2017;36:273-280. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 13] [Cited by in F6Publishing: 13] [Article Influence: 1.9] [Reference Citation Analysis (0)] |
| 19. | Holick MF, Biancuzzo RM, Chen TC, Klein EK, Young A, Bibuld D, Reitz R, Salameh W, Ameri A, Tannenbaum AD. Vitamin D2 is as effective as vitamin D3 in maintaining circulating concentrations of 25-hydroxyvitamin D. J Clin Endocrinol Metab. 2008;93:677-681. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 553] [Cited by in F6Publishing: 572] [Article Influence: 35.8] [Reference Citation Analysis (0)] |
| 20. | Iqbal R, Haroon MA, Dar FJ, Bilgirami M, Bano G, Khan AH. Validation of a food frequency questionnaire for assessing macronutrient and calcium intake in adult Pakistani population. J Coll Physicians Surg Pak. 2014;24:224-227. [PubMed] [Cited in This Article: ] |
| 21. | Nanan DJ. The obesity pandemic--implications for Pakistan. J Pak Med Assoc. 2002;52:342-346. [PubMed] [Cited in This Article: ] |
| 22. | Houtkooper LB, Lohman TG, Going SB, Howell WH. Why bioelectrical impedance analysis should be used for estimating adiposity. Am J Clin Nutr. 1996;64:436S-448S. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 228] [Cited by in F6Publishing: 212] [Article Influence: 7.6] [Reference Citation Analysis (0)] |
| 23. | Iqbal K, Islam N, Azam I, Asghar A, Mehboobali N, Iqbal MP. Association of Vitamin D binding protein polymorphism with risk of type 2 diabetes mellitus in a Pakistani urban population: A case control study. J Pak Med Assoc. 2017;67:1658-1663. [PubMed] [Cited in This Article: ] |
| 24. | Ahmed AS, Ahmed T, Long KZ, Magalhaes RJS, Hossain MI, Islam MM, Mahfuz M, Gaffar SA, Sharmeen A, Haque R, Guerrant RL, Petri WA, Mamun AA. Prevalence and risk factors of vitamin D insufficiency and deficiency among 6-24-month-old underweight and normal-weight children living in an urban slum of Bangladesh. Public Health Nutr. 2017;20:1718-1728. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 6] [Cited by in F6Publishing: 7] [Article Influence: 1.2] [Reference Citation Analysis (0)] |
| 25. | Di Cesare M, Bhatti Z, Soofi SB, Fortunato L, Ezzati M, Bhutta ZA. Geographical and socioeconomic inequalities in women and children's nutritional status in Pakistan in 2011: an analysis of data from a nationally representative survey. Lancet Glob Health. 2015;3:e229-e239. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 76] [Cited by in F6Publishing: 66] [Article Influence: 8.3] [Reference Citation Analysis (0)] |
| 26. | Dar FJ, Iqbal R, Ghani F, Siddiqui I, Khan AH. Bone health status of premenopausal healthy adult females in Pakistani females. Arch Osteoporos. 2012;7:93-99. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 0.8] [Reference Citation Analysis (0)] |
| 27. | Mansoor S, Habib A, Ghani F, Fatmi Z, Badruddin S, Mansoor S, Siddiqui I, Jabbar A. Prevalence and significance of vitamin D deficiency and insufficiency among apparently healthy adults. Clin Biochem. 2010;43:1431-1435. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 53] [Cited by in F6Publishing: 58] [Article Influence: 4.1] [Reference Citation Analysis (0)] |
| 28. | Zuberi LM, Habib A, Haque N, Jabbar A. Vitamin D Deficiency in ambulatory patients. J Pak Med Assoc. 2008;58:482-484. [PubMed] [Cited in This Article: ] |
| 29. | Fatima SS, Farooq S, Tauni MA, Irfan O, Alam F. Effect of raised body fat on vitamin D, leptin and bone mass. J Pak Med Assoc. 2015;65:1315-1319. [PubMed] [Cited in This Article: ] |
| 30. | Pourshahidi LK. Vitamin D and obesity: current perspectives and future directions. Proc Nutr Soc. 2015;74:115-124. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 112] [Cited by in F6Publishing: 127] [Article Influence: 12.7] [Reference Citation Analysis (0)] |
| 31. | Stokić E, Kupusinac A, Tomić-Naglić D, Zavišić BK, Mitrović M, Smiljenić D, Soskić S, Isenović E. Obesity and vitamin D deficiency: trends to promote a more proatherogenic cardiometabolic risk profile. Angiology. 2015;66:237-243. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 23] [Cited by in F6Publishing: 32] [Article Influence: 3.2] [Reference Citation Analysis (0)] |
| 32. | Paracchini V, Pedotti P, Taioli E. Genetics of leptin and obesity: a HuGE review. Am J Epidemiol. 2005;162:101-114. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 208] [Cited by in F6Publishing: 220] [Article Influence: 11.6] [Reference Citation Analysis (0)] |
| 33. | Margetic S, Gazzola C, Pegg GG, Hill RA. Leptin: a review of its peripheral actions and interactions. Int J Obes Relat Metab Disord. 2002;26:1407-1433. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 639] [Cited by in F6Publishing: 619] [Article Influence: 28.1] [Reference Citation Analysis (0)] |
| 34. | Mantzoros CS. The role of leptin in human obesity and disease: a review of current evidence. Ann Intern Med. 1999;130:671-680. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 381] [Cited by in F6Publishing: 366] [Article Influence: 14.6] [Reference Citation Analysis (0)] |
| 35. | Maggi S, Siviero P, Brocco E, Albertin M, Romanato G, Crepaldi G. Vitamin D deficiency, serum leptin and osteoprotegerin levels in older diabetic patients: an input to new research avenues. Acta Diabetol. 2014;51:461-469. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 24] [Cited by in F6Publishing: 18] [Article Influence: 1.8] [Reference Citation Analysis (0)] |
| 36. | Ulutas O, Taskapan H, Taskapan MC, Temel I. Vitamin D deficiency, insulin resistance, serum adipokine, and leptin levels in peritoneal dialysis patients. Int Urol Nephrol. 2013;45:879-884. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 17] [Cited by in F6Publishing: 19] [Article Influence: 1.6] [Reference Citation Analysis (0)] |
| 37. | Chow VT, Phoon MC. Measurement of serum leptin concentrations in university undergraduates by competitive ELISA reveals correlations with body mass index and sex. Adv Physiol Educ. 2003;27:70-77. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 23] [Cited by in F6Publishing: 24] [Article Influence: 1.1] [Reference Citation Analysis (0)] |
| 38. | Wang HC, Yang YK, Chen PS, Lee IH, Yeh TL, Lu RB. Increased plasma leptin in antipsychotic-naïve females with schizophrenia, but not in males. Neuropsychobiology. 2007;56:213-215. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 31] [Cited by in F6Publishing: 29] [Article Influence: 1.8] [Reference Citation Analysis (0)] |