# Association between −308 G/A TNF-α Polymorphism and Appendicular Skeletal Muscle Mass Index as a Marker of Sarcopenia in Normal Weight Obese Syndrome

Authors: L. Di Renzo; F. Sarlo; L. Petramala; L. Iacopino; G. Monteleone; C. Colica; A. De Lorenzo
Journal: Disease Markers
 (2013)

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## Abstract

Background and Aim. Normal weight obese (NWO) syndrome is characterized by normal body mass index (BMI), but high amount of fat mass and reduced lean mass. We evaluated allelic frequency of the G/A −308 TNF-α polymorphism and prevalence of sarcopenia in NWO. Methods. We enrolled 120 Italian healthy women, distinguished into 3 groups:  normal weight (NW); NWO, and preobese-obese (PreOB/OB) and evaluated anthropometric parameters, body composition by dual X-ray absorptiometry, blood  tests, and genotyping of  G/A −308 TNF-α polymorphism. Results. We found a positive association between sarcopenic obesity and −308 TNF-α polymorphism. All obese women were sarcopenic and were no carrier of mutation (G/G). Among all G/G, NWO showed significant differences in lean mass and total body lean mass (TBLean) with respect to NW and PreOB/OB (P<0.001). Regarding  appendicular skeletal muscle mass index values, 4.21% of NW were sarcopenic (50% G/G and 50% G/A); the same percentage was observed in NWO subjects (100% G/G). Moreover, 2.10% of PreOB/OB  were sarcopenic and all were G/G. Conclusion. Our study suggests that TNF-α polymorphism contributes to sarcopenic obesity susceptibility, in association with body composition. This is the first study that shows the importance of TNF-α  polymorphism to determine TBLean variation in NWO syndrome.


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## Body

## 1. Introduction

Sarcopenia is defined according to the European consensus as a condition that involves a loss of muscle mass and declining strength and/or physical performance and has profound physiologic and clinical consequences, including but not limited to impaired protein turnover, mobility loss, osteoporosis, increased fracture risk, dyslipidemia, insulin resistance, overall frailty, and increased mortality.A necessary condition for a diagnosis of sarcopenia is therefore the extent of muscle mass loss that should be considered significant [1, 2].The combination of sarcopenia and obesity [3], defined as sarcopenic obesity, is an important public health that induces fragility in the elderly, and it is associated with functional limitations and increased mortality [4, 5].In order to avoid the risk of sarcopenic obesity in the elderly and to prevent in the young population, the diagnosis of obesity requires the utilization of various methods, including body composition evaluation, metabolic, functional, and a genetic approach [6–9].A number of candidate genes for obesity [10] and osteoporosis have been identified [11], but the genetic basis of sarcopenia is still largely unknown.Greater loss of muscle mass leading to sarcopenic obesity in women occurs increasingly with age. Body mass index (BMI) does not acknowledge this factor, exacerbating misclassifications [12]. DXA-derived total body lean mass (TBLean) measures can reflect both muscle mass and muscle strength, providing a reliable measure for assessment of sarcopenia and obesity [13, 14].De Lorenzo et al. have identified the normal weight obese (NWO) syndrome, characterized by normal body weight and BMI, but high total body fat mass (TBFat) accumulation (>30%) accompanied by TBLean deficiency [15] and high level of atherogenic indices and oxidative stress [16, 17]. The frequency of NWO syndrome in the worldwide population is near to 10%, and the prevalence is higher in women than in men [18–21].NWO had a higher prevalence of metabolic syndrome, dyslipidemia, hypertension (men), CVD (women), and a 2.2-fold increased risk of CVD mortality (women) compared with those with low TBFat [22]. Early inflammation and genetic predisposition characterizes the syndrome [7, 23–25]. Moreover, a cross-talk between skeletal muscle and adipose tissue in NWO syndrome has been supposed and linked with the control of body weight, both fat stores and muscle mass.Tumor necrosis factor alpha (TNF-α) could play a decisive role in the proposed cross-talk between adipose tissue and skeletal muscle [26], with development of muscular abnormalities resulting in a loss of skeletal muscle mass and function. TNF-α is a cytokine implicated in the metabolic disturbances of chronic inflammation with its biological actions including induction of insulin resistance, anorexia, and weight loss. It is overexpressed in adipose tissue, which is both a source of and a target for TNF-α [27].TNF-α human gene is located on the short arm of chromosome 6 [28]. The G/A −308 polymorphism in the TNF-α promoter gene increases transcriptional activation of the TNF-α gene [29].Given the clinical significance of sarcopenic obesity, the purpose of the present study was to investigate the allelic frequency of the G/A −308 polymorphism in the TNF-α promoter gene and to determine whether this polymorphism is associated with appendicular skeletal muscle mass index (ASMMI) in NWO Italian population.We comprehensively analyzed TBFat, TBLean, anthropometric, and biochemical and cardiovascular risk factors parameters in TNF-α gene association study in NWO subjects.


## 2. Materials and Methods

### 2.1. Subjects

The study was conducted on a sample of 120 Italian Caucasian women (aged 20 to 60), recruited from ongoing studies at the University of Rome Tor Vergata (Italy), from June 2012 to January 2013. A completed screening of anthropometry and body composition was assessed using standardized equipment.Exclusion criteria were exposure to hormonal treatment or development of secondary obesity due to endocrine diseases or serious intercurrent illness. Subjects with a history or symptoms of coronary artery, cerebrovascular or peripheral artery disease, heart failure, renal or hepatic diseases, alcohol abuse, or smoking were excluded, as well as those with established type 2 diabetes. It was ascertained that none were taking lipid-lowering or antidiabetic medications, insulin, nitro derivatives, systemic corticosteroids, or any hormonal contraception. A completed screening of anthropometry and body composition was assessed.The subjects were categorized into 3 different groups according to BMI and the percentage of TBFat (PBF): (1) normal weight (NW) women having a BMI < 25 kg/m2, PBF < 30%; (2) NWO women with BMI < 25 kg/m2, PBF > 30% [15]. NWO women had regular 28-day menstrual cycles; (3) preobese-obese (PreOB/OB) women with a BMI > 25 kg/m2, PBF > 30%.Study design was clearly written in lay person language and provided to each study subject. A written informed consent was obtained from each patient and the study protocol conforms to the ethical guidelines of the Declaration of Helsinki. The collection of serum and DNA as well as the experiments was approved, and the study was conducted according to the guidelines of the “Tor Vergata” University Medical Ethical Committee, Rome, Italy.


### 2.2. Anthropometric Measurements

Anthropometric parameters for all participants were performed by trained personnel (body weight, height, hip, and waist circumferences), with participants wearing only light underwear and without shoes.Waist and hip measures were taken using a flexible steel metric tape to the nearest 0.5 cm, with subjects standing with arms relaxed by their side and balanced on both feet. The tape was held tight to the skin but without compression of tissue. Hip circumference was taken at the greatest posterior protuberance of the buttocks. Waist circumference was measured just above the iliac crest. Body weight (kg) was measured to the nearest 0.1 kg, using a balance scale (Invernizzi, Rome, Italy). Height (m) was measured using a stadiometry to the nearest 0.1 cm (Invernizzi, Rome, Italy). Body mass index (BMI) was calculated as body weight (in kilograms) divided body height (in meters) squared.


### 2.3. Dual X-ray Absorptiometry (DXA)

The total body composition was assessed by DXA (iDXA, G.E. Medical Systems, WI, USA), according to the previously described procedure [30]. The CV value (S.D./mean) for repeated measurements is 1.0–2.2% in our laboratory depending on application.PBF was calculated as TBFat mass divided by total mass of tissues (TBFat + TBLean + Bone Mass) × 100. ASMMI was calculated as follows = (Appendicular skeletal muscle mass/height2; women were defined sarcopenic with ASMMI < 5.47 kg/m2) [1].


### 2.4. Analysis of Blood Samples

Blood samples were collected into sterile tubes containing EDTA (Vacutainer). All materials were immediately placed in ice and plasma was stored at −70°C, for cytokine determinations. Analyses were carried out according to the standard techniques by the accredited Clinical Chemical Laboratories of the “Tor Vergata” Polyclinic (PTV) of Rome, Italy.Insulin resistance was determined by homeostasis model assessment-insulin resistance (HOMA-IR) = [(fasting glucose (mmol/L) × fasting insulin (μIU/mL))/22.5].Atherogenic indices were calculated as follows: total cholesterol (mg/dL)/HDL cholesterol (mg/dL) (normal value < 5 for men and <4.5 for women), LDL cholesterol (mg/dL)/HDL cholesterol (mg/dL) (normal value < 3.5 for men and <3 for women), and log (triglycerides (mg/dL)/HDL (mg/dL)) (normal value < 0.5).


### 2.5. Cytokine Assay

Blood levels of TNF-α cytokine were quantified with an ELISA assay (Mabtech, Italy) according to the manufacturer’s instruction (lower limit of TNF-α detection was 1.6 pg/mL).


### 2.6. Genetic Analysis

TNF-α Polymorphism. Sequencing of the 5′-region (−595 to +390) of the human TNF-α gene revealed a G to a A transition polymorphism at position −308. Digestion with NcoI enzyme, revealed the presence of two alleles: allele A1 gives two fragments of 87 bp and 20 bp, allele 2 a single 107 bp fragment. Amplification of 100 ng of genomic DNA was performed using initial denaturation at 94°C for 4 min followed by 30 cycles of 95°C for 1 min, 60°C for 1 min, and 72°C for 1 min with a final extension at 72°C for 10 min. The buffer for PCR reaction contained 2.5 mM MgCl2, 9.9 mM Tris-HCl (pH 8.8), 50 mM KCl, 0.1% Triton_X 100, 0.200 μM deoxyribonucleotide triphosphate (dNTPs), 1 U of Taq DNA polymerase, and 0.2 μM of each primer. The primer sequences are 5′-AGGCAATAGGTTTTGAGGGCCAT-3′ and 5′-TCCTCCCTGCTCCGATTCCG-3′.The amplified product was digested with NcoI and analysed on agarose gel and visualized under UV light after ethidium bromide staining [31].


### 2.7. Statistical Analysis

Data are presented as group means ± standard deviations (SD). The Mann-Whitney test was used to assess the significance among the groups. The level of significance was fixed atP≤0.05 for all the procedures. Statistical analysis was performed using a computer software package (SPSS for Windows, version 13.0; SPSS, Chicago, IL).


## 2.1. Subjects

The study was conducted on a sample of 120 Italian Caucasian women (aged 20 to 60), recruited from ongoing studies at the University of Rome Tor Vergata (Italy), from June 2012 to January 2013. A completed screening of anthropometry and body composition was assessed using standardized equipment.Exclusion criteria were exposure to hormonal treatment or development of secondary obesity due to endocrine diseases or serious intercurrent illness. Subjects with a history or symptoms of coronary artery, cerebrovascular or peripheral artery disease, heart failure, renal or hepatic diseases, alcohol abuse, or smoking were excluded, as well as those with established type 2 diabetes. It was ascertained that none were taking lipid-lowering or antidiabetic medications, insulin, nitro derivatives, systemic corticosteroids, or any hormonal contraception. A completed screening of anthropometry and body composition was assessed.The subjects were categorized into 3 different groups according to BMI and the percentage of TBFat (PBF): (1) normal weight (NW) women having a BMI < 25 kg/m2, PBF < 30%; (2) NWO women with BMI < 25 kg/m2, PBF > 30% [15]. NWO women had regular 28-day menstrual cycles; (3) preobese-obese (PreOB/OB) women with a BMI > 25 kg/m2, PBF > 30%.Study design was clearly written in lay person language and provided to each study subject. A written informed consent was obtained from each patient and the study protocol conforms to the ethical guidelines of the Declaration of Helsinki. The collection of serum and DNA as well as the experiments was approved, and the study was conducted according to the guidelines of the “Tor Vergata” University Medical Ethical Committee, Rome, Italy.


## 2.2. Anthropometric Measurements

Anthropometric parameters for all participants were performed by trained personnel (body weight, height, hip, and waist circumferences), with participants wearing only light underwear and without shoes.Waist and hip measures were taken using a flexible steel metric tape to the nearest 0.5 cm, with subjects standing with arms relaxed by their side and balanced on both feet. The tape was held tight to the skin but without compression of tissue. Hip circumference was taken at the greatest posterior protuberance of the buttocks. Waist circumference was measured just above the iliac crest. Body weight (kg) was measured to the nearest 0.1 kg, using a balance scale (Invernizzi, Rome, Italy). Height (m) was measured using a stadiometry to the nearest 0.1 cm (Invernizzi, Rome, Italy). Body mass index (BMI) was calculated as body weight (in kilograms) divided body height (in meters) squared.


## 2.3. Dual X-ray Absorptiometry (DXA)

The total body composition was assessed by DXA (iDXA, G.E. Medical Systems, WI, USA), according to the previously described procedure [30]. The CV value (S.D./mean) for repeated measurements is 1.0–2.2% in our laboratory depending on application.PBF was calculated as TBFat mass divided by total mass of tissues (TBFat + TBLean + Bone Mass) × 100. ASMMI was calculated as follows = (Appendicular skeletal muscle mass/height2; women were defined sarcopenic with ASMMI < 5.47 kg/m2) [1].


## 2.4. Analysis of Blood Samples

Blood samples were collected into sterile tubes containing EDTA (Vacutainer). All materials were immediately placed in ice and plasma was stored at −70°C, for cytokine determinations. Analyses were carried out according to the standard techniques by the accredited Clinical Chemical Laboratories of the “Tor Vergata” Polyclinic (PTV) of Rome, Italy.Insulin resistance was determined by homeostasis model assessment-insulin resistance (HOMA-IR) = [(fasting glucose (mmol/L) × fasting insulin (μIU/mL))/22.5].Atherogenic indices were calculated as follows: total cholesterol (mg/dL)/HDL cholesterol (mg/dL) (normal value < 5 for men and <4.5 for women), LDL cholesterol (mg/dL)/HDL cholesterol (mg/dL) (normal value < 3.5 for men and <3 for women), and log (triglycerides (mg/dL)/HDL (mg/dL)) (normal value < 0.5).


## 2.5. Cytokine Assay

Blood levels of TNF-α cytokine were quantified with an ELISA assay (Mabtech, Italy) according to the manufacturer’s instruction (lower limit of TNF-α detection was 1.6 pg/mL).


## 2.6. Genetic Analysis

TNF-α Polymorphism. Sequencing of the 5′-region (−595 to +390) of the human TNF-α gene revealed a G to a A transition polymorphism at position −308. Digestion with NcoI enzyme, revealed the presence of two alleles: allele A1 gives two fragments of 87 bp and 20 bp, allele 2 a single 107 bp fragment. Amplification of 100 ng of genomic DNA was performed using initial denaturation at 94°C for 4 min followed by 30 cycles of 95°C for 1 min, 60°C for 1 min, and 72°C for 1 min with a final extension at 72°C for 10 min. The buffer for PCR reaction contained 2.5 mM MgCl2, 9.9 mM Tris-HCl (pH 8.8), 50 mM KCl, 0.1% Triton_X 100, 0.200 μM deoxyribonucleotide triphosphate (dNTPs), 1 U of Taq DNA polymerase, and 0.2 μM of each primer. The primer sequences are 5′-AGGCAATAGGTTTTGAGGGCCAT-3′ and 5′-TCCTCCCTGCTCCGATTCCG-3′.The amplified product was digested with NcoI and analysed on agarose gel and visualized under UV light after ethidium bromide staining [31].


## 2.7. Statistical Analysis

Data are presented as group means ± standard deviations (SD). The Mann-Whitney test was used to assess the significance among the groups. The level of significance was fixed atP≤0.05 for all the procedures. Statistical analysis was performed using a computer software package (SPSS for Windows, version 13.0; SPSS, Chicago, IL).


## 3. Results

One hundred twenty Caucasian Italian women gave informed consent and were enrolled: 95 subjects were eligible for the study design according to inclusion criteria, with mean age of33.61±12.01 years and mean BMI of 26.46±5.64 Kg/m2. Characterization of the nutritional status by BMI revealed that 3.16% (n=3) were underweight, 45.26% (n=43) were normal weight (eutrophic), 26.32% (n=25) were overweight, and 25.26% (n=24) were obese. None of the subjects classified as obese by BMI were sarcopenic, according to ASMMI. When all women were classified by DXA, the majority (82.10%, n=78) were classified as obese, and 7.69% (n=6) of them presented sarcopenic obesity.Significant difference in the diagnosis of obesity between BMI and PBF was observed with an error percentage of 30.39% (P<0.005).Characterization of sarcopenic obesity, determined by BMI or DXA, and the relative ASMMI are presented in Table1. No association between sarcopenia and BMI was found. There was no association with sarcopenic obesity independent of body composition determined by DXA.Table 1
Prevalence of sarcopenic obesity distinguished  by BMI or DXA.
SarcopeniaBMIDXAEutrophic(n. 71)Obese(n. 24)Eutrophic(n. 17)Obese(n. 78)Relative ASMMI kg/m2 <5.5n.7046%9.85023.537.69Relative ASMMI kg/m2 >5.5n.64241372%90.1510076.4792.31ASMMI: appendicular skeletal muscle mass index; BMI: body mass index; DXA: dual-energy X-ray absorptiometry.The baseline characteristics of subjects, classified according to their genotypes, were shown in Table2. All subjects were successfully genotyped for the G/A −308 TNF-α polymorphism, distinguishing in wild type homozygote (G/G), heterozygosis (G/A), and mutant homozygote (A/A) genotypes. No carrier homozygote A/A was found. A total of 70 subjects (73.68%) defined as carrier (–) group had the G/G −308 TNF-α genotype with an average age of 33.64±12.05 years. 25 subjects (26.32%) defined as carrier (+) group had the G/A −308 TNF-α genotype with an average age of 33.24±12.29 years, without statistical differences in the mean age. Allelic frequency of the A substitution −308 was 27.36%. The observed genotype frequencies in our sample were in the Hardy-Weinberg equilibrium. No statistical differences were detected.Table 2
Anthropometric and body composition parameters according to genotype.
ParametersCarrier (−)n. 70Carrier (+)n. 25Mean ± SDMean ± SDHeight (cm)161,58 ± 6,51161,02 ± 4,75Weight (Kg)69,14 ± 16,6967,64 ± 13,01BMI(Kg/m2)26,38 ± 5,6226,17 ± 5,29WC (cm)78,74 ± 12,4279,10 ± 12,35HC (cm)100,93 ± 14,81104,55 ± 10,52W/H0,79 ± 0,110,75 ± 0,06TBMD (g/cm²)1,16 ± 0,091,17 ± 0,06TBMC (g)2491,88 ± 405,412506,52 ± 261,07PBF (%)39,01 ± 9,5739,21 ± 8,57TBFat (Kg)27,46 ± 11,8127,15 ± 10,13TBLean (Kg)38,17 ± 7,0937,40 ± 4,26ASMMI (kg/m2)6,47 ± 0,866,48 ± 0,79Carrier (−): −308 TNF-α G/G genotype; carrier (+): −308 TNF-α A/G genotype; BMI: body mass index; WC: waist circumference; HC: hip circumference; TBMD: total bone mineral density; TBMC: total bone mineral content; PBF: percentage of total body fat mass; TBFat: total body fat mass; TBLean: total body lean mass; ASMMI: appendicular skeletal muscle mass index.There was a positive association between sarcopenia, sarcopenic obesity, and −308 TNF-α genotype; hence all the obese women with sarcopenia present sarcopenic obesity and were carrier (–) (data not show).Table3 shows biochemical parameters and cardiovascular risk factors according to genotype. The carrier (+) group did not have a worse metabolic profile than carrier (–) group. Only hs-CRP (μg/dL) values were significantly different between the two groups (0.73±1.78μg/dL versus 0.20±0.50 μg/dL; P≤0.05). The anthropometric, biochemical and body composition (DXA) data of NW, NWO, and PreOB/OB groups, in accordance with the genotype polymorphism at positions −308 of the TNF-α gene promoter, were reported in Table 4.Table 3
Blood biochemical parameters and cardiovascular risk factors according to genotype.
ParametersCarrier (−)n. 70Carrier (+)n. 25Mean ± SDMean ± SDFG (mg/dL)91,33 ± 7,3389,88 ± 7,15FI  (μU/mL)7,98 ± 4,648,00 ± 4,35HOMA-IR3,35 ± 2,053,21 ± 1,70TC (mg/dL)203,44 ± 41,45192,12 ± 31,96HDL-chol (mg/dL)65,16 ± 15,6665,82 ± 14,38LDL-chol (mg/dL)116,18 ± 35,68110,33 ± 32,53TG (mg/dL)96,12 ± 39,7587,06 ± 33,79TC/HDL-chol ratio3,25 ± 0,853,03 ± 0,77LDL/HDL-chol ratio1,74 ± 0,791,71 ± 0,74Log TG/HDL-chol ratio1,58 ± 0,841,37 ± 0,58hs-CRP (μg/dL)0,73 ± 1,780,20 ± 0,50*TNF-α (pg/mL)26,42 ± 15,3320,62 ± 11,66*P<0.05.Carrier (−): −308 TNF-α G/G genotype; carrier (+): −308 TNF-α A/G genotype; FG: fasting glucose; FI: fasting insulin; HOMA-IR: homeostasis model of assessment-insulin resistance; TC: total cholesterol; HDL-chol: HDL cholesterol; LDL-chol: LDL cholesterol; TG: triglycerides; hs-CRP: high-sensitivity C-reactive protein.Table 4
Anthropometric and body composition (DXA) parameters in study groups in accordance with G/A −308 TNF-α polymorphism.
ParametersNWn. 17NWOn. 30Preobesen. 48All(n. 17)Carrier (−)(n. 13)Carrier (+)(n. 4)All(n. 30)Carrier (−)(n. 22)Carrier (+)(n. 8)All(n. 48)Carrier (−)(n. 35)Carrier (+)(n. 13)Weight (Kg)52,43 ± 7,3355,19 ± 12,1451,95 ± 5,7558,68 ± 5,07a57,86 ± 5,04d60,93 ± 4,75s80,80 ± 12,78bc81,91 ± 13,18ef76,60 ± 10,85hiBMI (Kg/m2)19,61 ± 1,8020,91 ± 4,3819,03 ± 1,7122,88 ± 1,48a22,77 ± 1,61d23,17 ± 1,07s30,88 ± 4,03bc30,90 ± 3,98ef30,21 ± 3,72tWC (cm)66,03 ± 4,9567,00 ± 4,8962,17 ± 3,4073,97 ± 7,78a71,95 ± 4,22d79,25 ± 12,14w88,01 ± 10,84bc88,52 ± 11,01ef84,61 ± 9,40tHC (cm)87,10 ± 12,6186,29 ± 14,1090,33 ± 0,5899,29 ± 6,8997,31 ± 4,31d104,50 ± 9,68110,01 ± 13,33bc109,60 ± 14,37e109,33 ± 8,90W/H0,77 ± 0,140,80 ± 0,140,69 ± 0,040,74 ± 0,040,74 ± 0,040,76 ± 0,050,81 ± 0,10nc0,82 ± 0,11e0,77 ± 0,07PBF24,47 ± 2,9525,68 ± 6,1925,43 ± 3,3735,94 ± 4,79a36,05 ± 4,86d35,64 ± 4,90g46,00 ± 5,21bc45,96 ± 5,71ef45,65 ± 3,65hiTBFat (Kg)12,77 ± 2,9314,59 ± 7,5713.16 ± 3,1120,98 ± 3,88a20,74 ± 3,93d21,63 ± 3,93s36,57 ± 7,92bc36,85 ± 8,19ef34,86 ± 6,62hiLean (Kg) arms3,63 ± 0,753,85 ± 0,833,27 ± 0,603,59 ± 0,383,58 ± 0,403,62 ± 0,344,14 ± 1,04bc4,17 ± 1,18f4,09 ± 0,66Lean (Kg) legs12,40 ± 1,5412,74 ± 1,8112,02 ± 0,9012,10 ± 1,3411,77 ± 1,1512,96 ± 1,4913,90 ± 2,45nc14,15 ± 2,77ef13,27 ± 1,85Lean (Kg) trunk17,75 ± 2,3318,13 ± 2,7817.52 ± 0,1016,32 ± 1,6716,10 ± 1,68d16,90 ± 1,6019,29 ± 3,95c19,62 ± 4,28f18,14 ± 2,79TBLean (Kg)36,82 ± 4,6637,79 ± 5,5035.80 ± 0.2334,92 ± 3,2734,34 ± 3,1336,46 ± 3,3340,30 ± 7,47c40,90 ± 8,25f38,48 ± 5,07ASMMI (kg/m2)6,00 ± 0,546,27 ± 0,725,61 ± 0,446,11 ± 0,476,03 ± 0,466,30 ± 0,456,87 ± 0,91bc6,87 ± 0,96ef6,85 ± 0,82tCarrier (−): G/G −308 TNF-α genotype; carrier (+): A/G −308 TNF-α genotype; BMI: body mass index; WC: waist circumference; HC: hip circumference; PBF: percentage of total body fat mass; TBFat: total body fat mass; TBLean: total body lean mass; ASMMI: appendicular skeletal muscle mass index.aP<0.001 NW all versus NWO all; bP<0.001 NW all versus PreOB Ob all; cP<0.001 NWO all versus Preob-Ob all; dP<0.001 NW carrier (−) versus NWO carrier (−); eP<0.001 NW carrier (−) versus Preob-Ob carrier (−); fP<0.001 NWO carrier (−) versus Preob-Ob carrier (−); gP<0.001 NW carrier (+) versus NWO carrier (+); hP<0.001 NW carrier (+) versus Preob-Ob carrier (+); iP<0.001 NWO carrier (+) versus Preob-Ob carrier (+); jP<0.001 NW carrier (−) versus NW carrier (+); kP<0.001 NWO carrier (−) versus NWO carrier  (+); lP<0.001 Preob-Ob carrier (−) versus Preob-Ob carrier (+); mP<0.05 NW all versus NWO all; nP<0.05 NW all versus Preob-Ob all; oP<0.05 NWO all versus Preob-Ob all; pP<0.05 NW carrier (−) versus NWO carrier (−); qP<0.05 NW carrier (−) versus Preob-Ob carrier (−); rP<0.05 NWO carrier (−) versus Preob-Ob carrier (−); sP<0.05 NW carrier (+) versus NWO carrier (+); tP<0.05 NW carrier (+) versus Preob-Ob carrier (+); uP<0.05 NWO carrier (+) versus Preob-Ob carrier (+); vP<0.05 NW carrier (−) versus NW carrier (+); wP<0.05 NWO carrier (−) versus NWO carrier  (+); xP<0.05 Preob-Ob carrier (−) versus Preob-Ob carrier (+).Distinguishing population in 3 different groups we foundn. 17 NW subjects (26.3±6.6 years, range 19–39); n. 30 NWO subjects (29.7±9.4 years; range 17–59); n. 48 PreOB/OB (38.4±12.8 years, range 17–59).Significant differences between NW, NWO, and PreOB/OB subjects were observed. No significant differences in HC and W/H ratio, lean arms, lean legs, and lean trunk were observed between the NWO and NW women, whereas BMI, PBF, TBFat weight, and waist circumference were significantly different (P<0.001).As expected, body weight, BMI, HC, WC, W/H ratio, PBF, TBLean, and lean legs were significantly different between the PreOB/OB and NW groups.PreOB/OB subjects with respect to NWO showed higher weight, BMI, WC, HC, W/H ratio, PBF, and TBLean (P<0.001).Respect to groups NW and NWO, PreOB/OB subjects showed higher amount of fat mass, evaluated as PBF (P<0.001) and TBFat (P<0.001). Moreover, PreOB/OB subjects showed higher sarcopenic index with respect to other groups (P<0.001).In NW subjects no differences were observed between carrier (−) and carrier (+). However, significant inter and intragenotype differences between NW, NWO, and PreOB/OB in all evaluated parameters were remarked (P<0.001).Carrier (+) NWO subjects showed significantly higher HC with respect to carrier (−) (P<0.001).Among overall carrier (−), NWO showed significant differences in lean arms, lean legs, lean trunk, and TBLean with respect to NW and PreOB/OB (P<0.001). However, these similar results have not been confirmed between carrier (+); in fact there are differences in terms of lean mass, but they are not significant.Among overall carrier (+), PreOB/OB showed higher weight, BMI, WC, HC, PBF, and TBFat with respect to NW and NWO (P 0.05) and higher ASMMI with respect to NW (P 0.05), whereas NWO showed higher BMI, PBF, and TBFat with respect to NW (P 0.05).Regarding sarcopenic index values, among NW, 4.21% (n=4) of them were sarcopenic (50% were carrier (–) and 50% carrier (+)); the same percentage was observed in NWO subjects (100% carrier (−)). Moreover, in PreOB/OB, 2.10% of them were sarcopenic and all were carrier (−).Table5 shows the biochemical parameters in study groups in accordance with genotype. No significant differences between NW and NWO were observed. With respect to NW and NWO, PreOB/OB subjects showed significantly higher levels of insulin (P 0.01), HOMA-IR (P 0.01), total cholesterol (P 0.01), LDL cholesterol (P 0.01), and triglycerides (P 0.01) and lower levels of HDL cholesterol (P 0.01).Table 5
Biochemical parameters in study groups in accordance with the genotype of the G/A polymorphism at positions −308 of the TNF-α gene promoter.
ParametersNWn. 17NWOn. 30Preobesen. 48All(n. 17)Carrier (−)(n. 13)Carrier (+)(n. 4)All(n. 30)Carrier (−)(n. 22)Carrier (+)(n. 8)All(n. 48)Carrier (−)(n. 35)Carrier (+)(n. 13)FG (mg/dL)91,92 ± 4,4492,22 ± 3,8791,25 ± 6,1890,42 ± 6,7590,69 ± 7,1289,83 ± 6,4690,76 ± 8,3291,34 ± 8,3489,14 ± 8,97FI  (μU/mL)6,47 ± 4,616,60 ± 4,986,13 ± 4,426,35 ± 3,505,58 ± 2,617,88 ± 4,819,71 ± 4,57nc9,83 ± 4,72ef9,24 ± 4,38HOMA-IR2,70 ± 2,022,75 ± 2,192,58 ± 1,912,62 ± 1,542,32 ± 1,153,22 ± 2,154,03 ± 1,96nc4,14 ± 2,11er3,58 ± 1,33TC (mg/dL)182,92 ± 38,62183,33 ± 45,76182,00 ± 19,51191,50 ± 30,57196,29 ± 29,04180,33 ± 33,82210,74 ± 42,06n213,85 ± 43,49e208,00 ± 32,85HDL (mg/dL)70,92 ± 11,6472,44 ± 11,6667,50 ± 12,5069,70 ± 15,6068,21 ± 15,7673,17 ± 16,0860,62 ± 15,11b61,15 ± 15,99e58,57 ± 11,86LDL (mg/dL)97,58 ± 34,5396,22 ± 38,34101,67 ± 25,40104,11 ± 26,73109,38 ± 26,2292,67 ± 26,33129,21 ± 34,64no128,36 ± 36,04e132,33 ± 31,78TG (mg/dL)74,77 ± 27,0372,78 ± 24,1679,25 ± 36,4390,00 ± 34,5394,00 ± 39,7880,67 ± 16,33101,97 ± 41,83n105,00 ± 41,64e97,00 ± 44,29TC/HDL ratio2,60 ± 0,482,54 ± 0,482,76 ± 0,522,84 ± 0,643,00 ± 0,692,49 ± 0,313,63 ± 0,81bc3,63 ± 0,83r3,64 ± 0,77uTC/LDL ratio1,36 ± 0,471,33 ± 0,481,44 ± 0,511,47 ± 0,681,55 ± 0,781,28 ± 0,352,07 ± 0,80bco2,02 ± 0,81er2,27 ± 0,80uLDL/HDL1,98 ± 0,332,01 ± 0,361,88 ± 0,281,90 ± 0,281,86 ± 0,262,01 ± 0,301,75 ± 0,44b1,77 ± 0,481,66 ± 0,26uLog TG/HDL ratio1,09 ± 0,511,02 ± 0,341,26 ± 0,831,34 ± 0,571,43 ± 0,641,14 ± 0,341,80 ± 0,88bo1,85 ± 0,95e1,63 ± 0,56hs-CRP (μg/dL)0,10 ± 0,170,12 ± 0,200,04 ± 0,060,40 ± 0,850,57 ± 1,010,06 ± 0,090,94 ± 2,11bo1,06 ± 2,32e0,44 ± 0,78TNF-α (pg/mL)27,51 ± 19,7730,50 ± 22,2518,53 ± 2,7823,55 ± 11,4723,01 ± 10,6424,90 ± 14,3723,11 ± 15,2125,55 ± 15,5810,91 ± 1,29xCarrier (−): G/G −308 TNF-α genotype; carrier (+): G/A −308 TNF-α genotype; FG: fasting glucose; FI: fasting insulin; HOMA-IR: homeostasis model of assessment-insulin resistance; TC: total cholesterol; HDL-chol: HDL cholesterol; LDL-chol: LDL cholesterol; TG: triglycerides; hs-CRP: high-sensitivity C-reactive protein.aP<0.001 NW all versus NWO all; bP<0.001 NW all versus Preob-Ob all; cP<0.001 NWO all versus Preob-Ob all; dP<0.001 NW carrier (−) versus NWO carrier (−); eP<0.001 NW carrier (−) versus Preob-Ob carrier (−);  fP<0.001 NWO carrier (−) versus Preob-Ob carrier (−); gP<0.001 NW carrier (+) versus NWO carrier (+); hP<0.001 NW carrier (+) versus Preob-Ob carrier (+); iP<0.001 NWO carrier (+) versus Preob-Ob carrier (+); jP<0.001 NW carrier (−) versus NW carrier (+); kP<0.001 NWO carrier (−) versus NWO carrier  (+); lP<0.001 Preob-Ob carrier (−) versus Preob-Ob carrier (+); mP<0.05 NW all versus NWO all; nP<0.05 NW all versus Preob-Ob all; oP<0.05 NWO all versus Preob-Ob all; pP<0.05 NW carrier (−) versus NWO carrier (−); qP<0.05 NW carrier (−) versus Preob-Ob carrier (−); rP<0.05 NWO carrier (−) versus Preob-Ob carrier (−); sP<0.05 NW carrier (+) versus NWO carrier (+); tP<0.05 NW carrier (+) versus Preob-Ob carrier (+); uP<0.05 NWO carrier (+) versus Preob-Ob carrier (+); vP<0.05 NW carrier (−) versus NW carrier (+); wP<0.05 NWO carrier (−) versus NWO carrier (+); xP<0.05 Preob-Ob carrier (−) versus Preob-Ob carrier (+).Regarding atherogenic indices, PreOB/OB showed higher values of TC/HDL ratio (P 0.02), LDL/HDL ratio (P 0.02), and log TG/HDL ratio (P 0.03) and reduced values of TC/LDL (P 0.01) than NW and NWO groups. PreOB/OB subjects showed higher levels of PCR than other groups (P 0.01). In PreOB/OB subjects we found slightly higher levels of TNF-α than NW and NWO subjects (P 0.01). PreOB/OB carrier (+) genotype had significantly reduced levels of TNF-α with respect to carrier (−) (P 0.03). No statistical differences of TNF-α circulating levels between NW and NWO were observed.


## 4. Discussion

Obesity plays relevant pathophysiological role in the development of health problems, arising as result of complex interaction of genetic, nutritional, and metabolic factors [32].Adipokines and myokines appear to be involved, respectively, in autocrine/paracrine interactions within adipose tissue and muscle, involved in the endocrine bidirectional cross-talk between these tissues [33]. Use of adiposity measures rather than BMI could be a better cardiovascular risk predictor and obesity-related diseases [33, 34].Our results confirm these recent data, highlighting the problem of obesity misclassification by BMI, especially in women subjects. We confirmed that BMI significantly underestimates prevalence of obesity when compared to DXA direct measurement of percent body fat. The majority of women classified as normal by BMI were found to be obese by PBF [35]. In our study, according to PBF classification, the overall percentage of obese women was 82.10%, with error percentage between the two classifications  relevant (30.39%) (P<0.005). None of the subjects classified as obese by BMI were sarcopenic; however when all women were classified by DXA, the 7.69% of them presented sarcopenic obesity. Characterization of sarcopenic obesity and the ASMMI revealed that 9.85% of the eutrophic subjects determined by BMI exhibited sarcopenic obesity, while none of the obese was sarcopenic. Moreover, by DXA the 23.53% were eutrophic and sarcopenic subjects.Several genetic studies were performed in order to discover the genes involved in the development of obesity susceptibility, and more than 300 genes have been putatively identified [4]. Certain single nucleotide polymorhisms (SNPs), occurring within the promoter region of a large number of genes, influence the transcriptional activity of genes, resulting in intraindividual differences in the amount of protein produced by the gene.TNF-α has a direct paracrine function in adipose tissue, reducing fat mass through stimulation of lipolysis and reduction of LPL expression and activity [36].In human skeletal muscle and adipose tissue, TNF-α messenger RNA levels were positively correlated with downregulation of the GLUT4 glucose transporter, body mass index (BMI), fat mass, and serum levels of insulin and inversely correlated with lipoprotein lipase activity [37].The promoter region of the TNF-α gene contains several single nucleotide polymorphisms (SNPs), such as G/A −238, G/A −308, and C/A −863, altering transcriptional activity of TNF-α mRNA [38]. The functional role of the G/A −308 TNF-α polymorphism is currently unclear.In the present study, the genetic variation of the G/A −308 polymorphism in the TNF-α promoter gene was firstly analyzed in NWO syndrome [15], comparing NW and PreOB/OB subjects.Our data partially match the previously published data [16, 23–25]. In our subjects BMI, weight, WC, and TBFat were not different across genotypes.Several studies showed that G/A polymorphism is not useful to promote obesity or metabolic abnormalities [37]. In Italian and Danish population, G/A polymorphism is unlikely to play an important role in the development of obesity and its related metabolic abnormalities [39, 40].The allele A was associated with obesity, in individuals between 50 and 60 years [41]. Our result obtained in a young population confirmed the previous data [29, 42]. In Spanish obese subjects (70% females) any differences of anthropometric, metabolic profile and adipokines levels in accordance with G/A −308 TNF-α polymorphism were found. The conflicting data can be due to differences in methodologies of study, suggesting that obesity could be related to this polymorphism after the fifth decade of life.In our study, no differences in allele frequency of G/A −308 TNF-α polymorphism were observed in NW, NWO, and PreOB/OB subjects, as well as no differences in serum levels of TNF-α cytokine in the study groups with the exception of PreOB/OB carrier (+).Moreover, HOMA-IR values were significantly higher in all and PreOB/OB carrier (−) subjects compared to NW and NWO women. However, no differences were observed between the HOMA-IR of NW and NWO women.One of the aftermath of insulin resistance is sarcopenia. In this study, we found significant associations with TBLean and the TNF-α gene polymorphism.To understand the role of the proinflammatory cytokines in skeletal muscle differentiation, which appear to be controversial [43, 44], it is important to clarify the several mechanisms of TNF-α.TNF-α promotes the activation of transcription factors such as nuclear factor-κB (NF-κB) and AP-1 (activator protein-1).Transforming growth factor-β-activated kinase-1 (TAK-1) is critical for TNF-α-induced activation of NF-κB and mitogen-activated protein kinases (MAPK) signaling pathways, especially p38 [45, 46]. TAK-1 connects TNF-α to activin signaling, explaining how these cytokines can inhibit myogenesis, establishing the physiologic relevance of this pathway in the impaired regeneration observed in sarcopenia [47]. The induction of activin A secretion downstream of cytokine pathway stimulation suggests a mechanism explaining how cytokines alter muscle differentiation, because it is well established that TGF-β family members such as myostatin and Activin A can block myoblast differentiation [48]. Moreover, TNF-α drastically increases the production of matrix metalloproteinase (MMP)-9, leading to skeletal muscle tissue loss in various pathological conditions [49].This is the first study that shows the importance of the TNF-α gene polymorphism to TBLean variation in NWO syndrome, representing our pilot effort to further studies.Finally, we mention some limitations of the study: (1) our study was performed only in adult female subjects, excluding elderlies [50]; (2) the number of included subjects was relatively low; thus validation of the results in larger and independent cohorts is recommended to confirm our hypothesis of etiology of sarcopenic obesity susceptibility, depending on body composition, BMI, and TNF-α gene polymorphism and to exclude the risk of false negative findings.These findings may be used to develop a prediction model for sarcopenia; if confirmed in a larger population, it could represent a new management approach for the correct diagnosis and therapeutic choice in the prediction and prevention of sarcopenic obesity.



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*Source: 983424-2013-10-30.xml*