Association of beta 1 and beta 3 adrenergic receptors gene polymorphisms with insulin resistance and high lipid profiles related to type 2 diabetes and metabolic syndrome

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Association of beta 1 and beta 3 adrenergic receptors gene polymorphisms with insulin resistance and high lipid profiles related to type 2 diabetes and metabolic syndrome
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  1327 Nutr Hosp. 2014;29(6):1327-1334ISSN 0212-1611 • CODEN NUHOEQS.V.R. 318 Original / Síndrome metabólico Association of β 1 and β 3 adrenergic receptors gene polymorphisms withinsulin resistance and high lipid profiles related to type 2 diabetesand metabolic syndrome Ana I. Burguete-García 1 , Gabriela A. Martínez-Nava 1 , Adán Valladares-Salgado 2 , V. H. Bermúdez 1 , Bárbara Estrada-Velasco 1 , Niels Wacher 3 , Jesús Peralta-Romero 2 , Jaime Garcia-Mena 4 , Esteban Parra andMiguel Cruz 2 1  Dirección de Infecciones Crónicas y Cáncer, CISEI. Instituto Nacional de Salud Pública. 2 Unidad de Investigación Médica en Bioquímica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del IMSS, México. 3 Unidad de Investigación Médica en Epidemiología, Hospital de Especialidades, Centro Médico Nacional Siglo XXI de IMSS, México. 4  Departamentode Genética y Biología Molecular, Cinvestav-IPN Zacatenco, México. ASOCIACIÓN DE LOS POLIMORFISMOS GÉNICOSDE LOS RECEPTORES ADRENÉRGICOS 1 Y 3CON LA RESISTENCIA A LA INSULINA Y LOSPERFILES ELEVADOS DE LÍPIDOS RELACIONADOS CON LA DIABETES TIPO 2 Y EL SÍNDROME METABÓLICOResumen  Antecedentes: Entre los diversos genes asociados a la diabetestipo 2 (DT2), los receptores –adrenérgicos–son excelentes candi-datos para estudiar en la población mexicana dada la alta preva-lencia de estas patologías. El objetivo de este trabajo fue analizarla asociación de polimorfismos en los genes  ADRB1 (rs1801253)(Arg389Gly) y  ADRB3 (Trp64Arg) con DT2 y SM.  Métodos: Se estudiaron 445 pacientes con Síndrome Metabóli-co, 502 con diabetes tipo 2 y 552 controles sanos. Se evaluaron lascaracterísticas antropométricas, perfil bioquímico completo y lospolimorfismos Arg389Gly y Trp64Arg SNPs se determinaron me-diante ensayos TaqMan. El análisis de datos fue ajustado por por-centaje de ancestralidad.  Resultados: Para la variante ADRB1 Arg389Gly se observóuna asociación estadísticamente significativa con un aumento delos niveles de LDL (P < 0,008 ), y la variante ADRB3 Trp64Arg seasoció a mayor HOMA- IR (p < 0,018) y con un aumento de los ni-veles de insulina (P < 0,001). Mediante modelos de regresión logís-tica múltiple en los tres modelos de heredabilidad se evaluó la aso-ciación de ambos polimorfismos y DT2 y SM, observando unasociación significativa en los 3 modelos solo con DT2, ADRB3 enel modelo codominante Trp/Arg un OR de 1.53 (1.9 a 2.13 , P <0.003) que se incrementó hasta OR 2,99 (1,44 a 6,22 , P < 0,003) pa-ra el genotipo Arg/Arg . Se encontró bajo el modelo dominante ge-notipo Trp/Arg- Arg/Arg con OR 1.67 (1.21 a 2.30, p < 0.002). Enel modelo recesivo (Arg/Arg), también un OR 2.56 (1.24 a 5.26 , P <0.01). Conclusiones: La variante ADRB3 Trp64Arg se asoció signifi-cativamente con DT2 y ADRB1 Gly389Arg en alteraciones en elmetabolismo de lípidos. Nuestros resultados demuestran que estasvariantes son posibles biomarcadores para predecir las alteracio-nes metabólicas y la evolución en pacientes con síndrome Metabó-lico y diabetes tipo 2. (  Nutr Hosp. 2014;29:1327-1334) DOI:10.3305/nh.2014.29.6.7367 Palabras clave:  Diabetes. Síndrome metabólico. Receptor adrenérgico. Abstract  Background: Among the diverse genes associated to type 2diabetes (T2D), the -adrenergic receptors are an excellent candi-date to study in Mexican population. The objective of this workwas to analyze the association of polymorphisms in  ADRB1 (rs1801253) (Arg389Gly) and  ADRB3 (Trp64Arg) genes with T2Dand metabolic syndrome (MS).  Methods: We studied 445 MS patients, 502 with T2D and 552healthy controls. Anthropometric features and complete bioche-mical profile were evaluated, and Arg389Gly and Trp64Arg SNPswere determined by TaqMan assays. Data analysis was adjustedby African, Caucasian and Amerindian ancestral percentage.  Results: The variant Arg389Gly of  ADRB1 was statisticallyassociated with an increase of LDL levels (  P < 0.008), and thevariant  ADRB3 Trp64Arg was associated to larger HOMA-IR (  P < 0.018) and with an increase of insulin levels (  P < 0.001). Amultiple logistic regression analysis was made in three groupingmodels: For  ADRB3 in the codominant model Trp/Arg genotype,there was an OR of 1.53 (1.09–2.13,  P < 0.003) which was increasedup to OR 2.99 (1.44–6.22,  P < 0.003) for the Arg/Arg genotype.Similar risk association was found under the dominant modelTrp/Arg-Arg/Arg genotype with OR 1.67 (1.21–2.30;  P < 0.002). Inthe recessive model (Arg/Arg genotype), there was also a highassociation OR 2.56 (1.24–5.26,  P < 0.01). Conclusions: The  ADRB3 Trp64Arg variant is a susceptibilitygene polymorphism for T2D and the  ADRB1 Gly389Arg for lipidmetabolism disruption. These results show that these variants arepotential biomarkers for predicting metabolic alterations andevolution in diabetic and metabolic syndrome patients. (  Nutr Hosp. 2014;29:1327-1334) DOI:10.3305/nh.2014.29.6.7367 Key words: Polymorphism. Type 2 diabetes. Metabolicsyndrome. Adrenergic receptors. Correspondence: Ana I. Burguete-García.E-mail: aburguete@insp.mxRecibido: 21-II-2014.Aceptado: 12-III-2014.  1328 Ana I. Burguete-García et al.Nutr Hosp. 2014;29(6):1327-1334 Introduction Type 2 diabetes (T2D) is a complex multifactorialand polygenic metabolic disorder and its pathogenesisis influenced by diverse environmental factors 1 . Dia-betes is one of the most prevalent diseases and its com-plications are one of the leading causes of death world-wide, and also in México 2 . The prevalence of diabeteshas dramatically increased in Mexico since the secondhalf of last century 3 and it has recently been estimatedthat 14.4% of Mexican adults suffer diabetes 2 .Impaired fasting glucose and impaired glucose to -lerance are metabolic abnormalities known as predia-betes since they predict later occurrence of T2D. Theyare both associated with insulin resistance, as well asan increased risk of cardiovascular disease 4 . Metabolicsyndrome (MS) on the other hand is a combination of metabolic disorders that increase the risk of cardiovas-cular disease and T2D. Several criteria exist to defineMS 5-7 , however until now, there is not a universal crite-rion to define MS in different populations 8 . MS and im-paired glucose tolerance identify nearly 70% of sub- jects with high T2D risk  8,9 . The prevalence of metabolicsyndrome in Mexico is 26.6% or 21.4% if those withdiabetes are excluded. Genetic studies have shown avariety of genes associated to the development of MSand T2D; in particular genes that participate in the con-trol of adipose tissue metabolism, lipolysis, thermoge-nesis, and glucose metabolism in muscle 10 .Attempts to identify genes causing MS or T2D in hu-mans using candidate genes have reported diffe rences indifferent populations; therefore more work is required toidentify the causal variants, to test their role in diseaseprediction and to ascertain their therapeutic implica-tions 11-13 . The involvement of  ADRB1 and  ADRB2 adren-ergic receptors is a remarkable case since this type of Gprotein-coupled receptors, had been only associatedwith heart failure 14 . The  ADRB receptor are activatedby the specifically binding of their endogenous ligands,the catecholamines (adrenaline and nor adrenaline).  ADRBs are highly homologous; nevertheless they playclearly distinct roles in cardiac physiology and pathol-ogy. For example, to meet the increased metabolic de-mands of stress or exercise, the sympathetic nervoussystem stimulates cardiac function through activationof these closely related receptors, and chronic stimula-tion of  ADRB1 produces myo cyte hypertrophy andapoptosis, whereas  ADRB2 signaling promotes cellsurvival 15 .Some polymorphisms in the  ADRB genes have beenassociated with obesity 16 ; the Arg389Gly polymor-phism of  ADRB1 gene 17 showed differences for the Argallele frequency among several ethnic groups 17,18 . Thisvariant has been associated with obesity in some popu-lations, but it has not been associated with hyperten-sion and the association with obesity is not consistentamong the case-control studies reported 19-21 . The Trp64Arg polymorphism of the  ADRB3 genewas srcinally reported in Pima Indians with a particu-lar high frequency of 31% for the Arg allele. This va -riant is apparently present in all studied populations ex-cept in individuals of the Nauru Republic. In most ca -ses the Arg64 variant has been associated tooverweight, obesity and early onset of T2D 22-25 . Dis-crepancies in the association of this polymorphismwith metabolic risk factors, for instance lipids and in-sulin resistance, have been reported; however thismight be attributed to differences due to confoundingvariables such as age, ethnicity or low statistical po -wer 18,26,27 . Most authors agree the Arg/Arg and Trp/Argvariants of the  ADRB3 gene have a significant effect inthe increase of the relative risk for MS and T2D, asso-ciated with weight gain, increase of visceral fat, de-crease of insulin sensitivity and glucose control 26,28 . Al-though this variant is considered closely associated innumerous populations with susceptibility to T2D, ho -wever, no data has been reported for specific relation-ship with insulin resistance and lipid profile. The pur-pose of this work was to determine the possibleassociation of two important  ADRB genes polymor-phisms, Arg389Gly (  ADRB1 ) and Trp64Arg (  ADRB3 )with insulin resistance and lipid profiles related to T2Dand MS in a sample of adult population of Mexico City. Material and methods Study participants and phenotype definitions In a case-control design (table I), 502 subjects withT2D (according to the ADA criteria 29 )and 445 withMS 7 were compared to 552 controls aged 35 to 65years, selected from the Regional Hospital Number 1(Diabetes Research Unit) and the National MedicalCenter Blood Bank (controls and those with MS), fromthe Mexican Institute of Social Security (IMSS). In ourstudy we defined MS individuals as those without fam-ily history of diabetes (ADA criteria) and fasting glu-cose <126 mg/dL (no T2D patients were included inthis group). Parents and grandparents of all studiedsubjects were born in Mexico. The inclusion criteria toselect controls were the absence of family history of T2D among pa rents, brothers, sisters and siblings.Written consent was obtained from the participants andthe protocol was approved by the National EthicalCommittee of the IMSS).  Biochemical profile analyses The biochemical profile included fasting glucose(mg/dL), insulin (pmol/L), insulin sensitivity (HOMA-IR), total cholesterol (mg/dL), LDL (mg/dL), HDL(mg/dL) and triglycerides (mg/dL). These parameterswere determined using the ILab350 Clinical ChemistrySystem (Instrumentation Laboratory, BarcelonaSpain). Anthropometric measurements includedweight (kg), height (cm), waist to hip ratio (WHR) and  Association of β 1 and β 3 adrenergicreceptors gene polymorphisms withinsulin resistance... 1329 Nutr Hosp. 2014;29(6):1327-1334 body mass index (BMI in kg/m 2 ) using the Body Com-position Analyzer BC-418 (TANITA Corporation, Illi-nois, USA). Systolic and diastolic blood pressureswere measured using a sphygmomanometer (AmericaDiagnostic Corp., NY). MS was defined according tothe criteria of the AHA/NHLBI (American Heart Asso-ciation/National Heart, Lung and Blood InstituteScientific Statement) 7 . Atherogenic index was calcula -ted according to the formula: AI = Totalcholesterol/HDL-C, a cardiovascular risk was consi -dered as a value ≥  4.5 30 . Genotyping Genomic DNA was extracted from a peripheralblood sample using QIAamp kit (Qiagen, Germany),and analyzed by electrophoresis in 0.8% agarose gelsstained with ethidium bromide and visualized in a GelDoc 2000 (BIORAD, California). DNA concentrationwas determined using a VICTOR3 1420 spectropho-tometer (Perkin-Elmer, Germany). The SNPs analyseswere made using real time PCR by TaqMan technology(7900HT Applied Biosystems, Foster City, USA), u -sing probes for the  ADRB1 gene Arg389Gly(rs1801253) polymorphism, and the  ADRB3 geneTrp64Arg (rs4994) according to the manufacturer(Applied Biosystems, Foster City, USA). In order to control for the potential effect of popula-tion stratification ( eg . variation of individual admixtureproportions in the samples), we also genotyped a panelof Ancestry Informative Markers (AIMs), which aremarkers showing large allele frequency differencesbet ween European, West African and Native Americanpopulations. In the sample of T2D, SM subjects andcontrols, we genotyped 27 AIMs (rs2814778,rs723822, rs1008984, rs1435090, rs17203, rs768324,rs719776, rs1112828, rs1403454, rs3340, rs2077681,rs1935946, rs1320892, rs1373302, rs2695, rs1980888,rs1327805, rs2207782, rs1487214, rs2078588,rs724729, rs292932, rs1369290, rs386569, rs718092,rs878825 and rs16383). Information on the parentalfrequencies for these markers in Mexicans is availablein a previous report from our group 31 . The AIMs weregenotyped using a modified allele-specific PCRmethod with universal energy transfer-labeled primersby the company Prevention Genetics (Marshfield, Wis-consin, USA). Statistical analysis Comparison between groups was made usingKruskal–Wallis test for continuous variables and chi-square ( χ 2 ) test for categorical variables. The allelicand phenotypic frequencies were calculated, and withthe allelic frequencies of the control group the Hardy-Weinberg equilibrium was corroborated We performed a logistic regression analysis to pre-dict the risk of either T2D or MS in relation to the dif-ferent genotypes in the three main inheritance models:codominant, dominant and recessive; adjusting by age,gender, BMI and individual ancestry. Odds ratio ( OR )were estimated to assess the strength of the association. To examine the likelihood that the results were false-positive findings, false-positive report probabilities(FPRP) were calculated using the methods describedby Wacholder et al. 31 . We set 0.5 as the FPRP cut-off for a noteworthy value. The expected odds ratios ( ORs )were based on reported ORs from previous stu - Table I Characteristics of MS and T2D Mexico City subjectsParametersControls (552)MS (445)T2D (502) Age (years)43.47 ± 6.645.00 ± 7.0*53.40 ± 7.50*BMI27.50 ± 3.630.50 ± 4.3*29.30 ± 4.70*WHR 0.89 ± 0.580.92 ± 0.08*0.92 ± 0.17*SBP (mm Hg)116.30 ± 9.8126.40 ± 12.9*118.10 ± 14.20*DBP (mm Hg)73.80 ± 7.378.20 ± 8.975.90 ± 8.70*Glucose (mg/dL)88.00 ± 15.796.24 ± 12.6182.60 ± 80.00*Insulin (pmol/L)9.40 ± 5.1512.00 ± 7.8*14.20 ± 10.10*HOMA-IR2.07 ± 1.23.00 ± 2.0*6.30 ± 5.00*Total cholesterol (mg/dL)199.90 ± 40.0206.10 ± 40.3221.60 ± 65.00*LDL (mg/dL)128.00 ± 34.2127.50 ± 35.0138.30 ± 38.90*HDL (mg/dL)44.50 ± 11.437.80 ± 9.848.60 ± 15.20*Triglycerides (mg/dL)166.90 ± 93.0257.90 ± 149.9*236.30 ± 169.60*Atherogenic index4.73 ± 1.345.71 ± 1.51*4.76 ± 1.33Ancestral contributionAmerindian0.64 ± 0.130.67 ± 0.110.64 ± 0.11European0.33 ± 0.120.30 ± 0.100.33 ± 0.10African0.03 ± 0.020.03 ± 0.020.03 ± 0.025 The results are shown as mean ± standard deviation *P < 0.05 (Controls versus T2D or MS). BMI: Body mass index. WHR: waist hip ratio. SBP:systolic blood pressure. DBP: diastolic blood pressure. LDL: low density lipoprotein. HDL: high density lipoprotein.  dies 18,24,25,27,28,33 . Taking the previous literature recom-mendations between these polymorphisms, we set theprior probability of an association between each SNPand T2D and MS at 0.1-0.01. A prior probability of 0.1represents a moderate to high prior probability of asso-ciation and has been used in studies involving candi-date genes/SNPs with prior evidence of associationwith disease 29 . Finally, we performed multiple linear regressionanalysis to examine the differences and the impact of these variants on insulin resistance and lipid profilesvariables, (related to T2D and MS) including fastinginsulin, HOMA-IR and LDL levels; all the modelswhere adjusted by BMI, age, disease status and gender.A bootstrap bias-corrected confidence intervals and  p -value was performed with 1473 Jacknife replications,and 10,000 bootstrap replications. Also we evaluatedthe potential interaction model between the two SNP’s,but we didn’t find a significative interaction (data notshown). All Statistical analysis was performed with the Sta-tistical Package STATA v9.1 software (Incorporation,Chicago). Power Analysis We used the power program v.3.00 (US NationalIns titutes of Health (NIH), National Cancer Institute(NCI)) and Stata v9.1 software (Incorporation, Chica-go) to estimate the statistical power of the study usingthe allele frequency reported in dbSNP database. Power calculation T2D (CASES: 502,SM (CASES:445, CONTROLS: 552)CONTROLS: 552)  ADRB1 ADRB3 ADRB1 ADRB3 (rs1801253) (rs4994) (rs1801253) (rs4994) OR  (Arg389Gly (trp64Arg) (Arg389Gly) (trp64Arg) 1.50.690.860.630.8320.980.990.970.992.51111 Results Clinical data General information and ethnic admixture of partici-pants in the study is shown in table I. Mean age of con-trols was lower than the mean age of those with MS orwith T2D. Patients with T2D were characterized by hy-perglycemia, hyperinsulinemia and insulin resistance,while those with MS showed obesity, hypertension,hyperinsulinemia, low HDL levels, hypertrigly -ceridemia and a high atherogenic index. Genotype and allele frequencies for the Arg389Glyvariant of  ADRB1 gene were in Hardy-Weinberg equi-librium ( P > 0.05). For the  ADRB1 gene, the MAF (mi-nor allele frequency) was similar in the three groups(controls 13.8%, MS 11.52% and T2D 11.25%). The  ADRB3 gene was in Hardy-Wenberg equilibrium (p <0.05), the MAF showed a higher frequency in the T2Dgroup (26.49%), followed by the observed in the MSgroup (23.48%), compared with the frequency ob-tained for the control group (21.20%).  Risk analysis Table II shows a multiple logistic regression analy-sis adjusted by age, gender, BMI and individual ances-try in three inheritance models: codominant, dominantand recessive. For  ADRB3 Trp/Arg genotype in thecodominant model, there was an OR of 1.53 (1.09–2.13, P < 0.003) which was increased up to2.99 (1.44–6.22, P < 0.003) for the Arg/Arg genotype. Similar risk association was found under the dominant modelTrp/Arg-Arg/Arg genotypes with an OR of 1.67 (1.21–2.30; P < 0.002). In the recessive model (Arg/Arggenotype), there was also a high association ( OR =2.56, 95%CI=1.24–5.26, P < 0.01).Based on a moderate to high prior probability of 0.1to an expected OR of 3, the FPRP for an associationbet ween  ADRB3 (rs4994) and T2D was 0.026. TheFPRP ranged from 0.026 for a prior probability of 0.1and an OR of 3, to 0.88 for a prior probability of 0.01and an OR of 1.5 (see supplementary material 1).Finally, to explore the possible mechanisms of thesevariants we tested their effects in the quantitative traitsfor insulin resistance and lipid profile measured by in-sulin level, glucose, HOMA-IR, LDL, HDL, trigly -cerides and cholesterol The variant Arg389Gly of   ADRB1 was statistically associated with an increase of LDL levels ( P < 0.008), and the variant  ADRB3 Trp64Arg was associated to higher HOMA-IR ( P <0.018) and to an increase of insulin levels ( P < 0.001)(table III).After resampling 1,473 Jacknife and 10,000bootstrap replications, bias-corrected confidence inter-vals and  p -value were significant (table III). An asso -ciation analysis of these two SNPs with quantitativetraits such as body mass index, fasting glucose, bloodHDL cholesterol, fasting blood triglycerides, systolicblood pressure, diastolic blood pressure, waist-hip ra-tio was also performed using a linear regression tocompare the equality of means across genotypes. Thisanalysis was adjusted by gender, age and disease sta-tus; however, we did not find any suggestion of asso -ciation for the quantitative traits assessed (see supple-mentary material 2). Discussion In this study we verified the association of Arg389Gly  ADRB1 and Trp64Arg  ADRB3 polymor-phismswith the phenotype of adult population of Me -1330 Ana I. Burguete-García et al.Nutr Hosp. 2014;29(6):1327-1334  A s  s  o c i   a  t  i   on of      β   1  a n d     β    3  a  d r  e n e r  gi   c r  e  c  e  p t   or  s  g e n e  p ol   ym or  ph i   s m s  wi   t  h i  n s  ul  i  nr  e  s i   s  t   a n c  e  . . . 1  3  3 1   N u t  r H o s  p .2  0 1 4  ; 2  9  (   6  )   : 1  3 2  7 -1  3  3 4  Table II  ADRB1 and ADRB3 association with MS and T2D (n = 997)  ADRB1 (rs1801253)Genotype (Arg389Gly)ControlsMSOR (95% CI) §  p § OR (95% CI) &  p & T2DOR (95% CI) §  p § OR (95% CI) &  p & CodominantArg/Arg408 (73.9%)340 (76.4%)10.6410.60398 (79.4%)10.2910.74Arg/Gly136 (24.6%)99 (22.2%)0.90 (0.65−1.23)0.90(0.63- 1.27)94 (18.8%)0.72 (0.48−1.09)0.81(0.55,1.18)Gly/Gly8 (1.4%)6 (1.4%)0.66 (0.21−2.07)1.23(0.28-5.34)9 (1.8%)0.79 (0.22−2.84)1.26 (0.30, 5.15)DominantArg/Arg408 (73.9%)340 (76.4%)10.4310.50398 (79.4%)10.1210.33Arg/Gly−Gly/Gly144 (26.1%)105 (23.6%)0.88 (0.65−1.20)0.90(0.65-1.21)103 (20.6%)0.73 (0.49−1.08)0.83(0.57, 1.20)RecessiveArg/Arg−Arg/Gly544 (98.5%)439 (98.7%)10.5010.67492 (98.2%)10.8010.70Gly/Gly8 (1.4%)6 (1.4%)0.68 (0.22−2.12)0.78(0.24-2.46) 9 (1.8%)0.85 (0.24−3.04)1.32(0.32,5.40)ADRB3Genotype(rs4994)(Trp64Arg)ControlsMSOR (95% CI)POR (95% CI) & P & T2DOR (95% CI)POR (95% CI) & P & CodominantTrp/Trp336 (60.9%)261 (58.6%)10.3810.44276 (55.1%)10.00110.003Trp/Arg198 (35.9%)159 (35.7%)1.12 (0.84−1.49)1.31 (0.82-1.55)184 (36.7%)1.42 (1.00−2.01)1.53(1.09, 2.13)Arg/Arg18 (3.3%)25 (5.6%)1.53(0.79−2.97)1.58(0.75-3.33)41 (8.2%)3.37 (1.62−6.99)2.99(1.44, 6.22)DominantTrp/Trp336 (60.9%)251 (58.6%)10.2910.30276 (55.1%)10.00510.002Trp/Arg−Arg/Arg216 (39.1%)184 (41.4%)1.16 (0.88−1.53)1.17(0.86-1.59)225 (44.9%)1.60 (1.15−2.24)1.67(1.21, 2.30)RecessiveTrp/Trp−Trp/Arg534 (96.7%)420 (94.4%)10.2410.27460 (91.8%)10.00210.01Arg/Arg18 (3.3%)25 (5.6%)1.47 (0.77−2.83)1.51(0.72-3.14)41 (8.2%)2.93 (1.44−5.99)2.56 (1.24, 5.26) § Adjusted by age, gender and BMI, & Adjusted by age, gender, BMI and ancestral percentage of African, Caucasian and Amerindian.
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