This study was approved by the institutional review board (IRB) of Kyoto Prefectural University of Medicine (IRB number: RBMR-G-71-7). According to Japanese guidelines, individuals with a percentage of overweight (POW) ≥ 20% are classified as obese (12). POW, which is the modified weight-for-height method, is widely used as a surrogate marker of childhood obesity in Japan (13). POW is calculated using the following formula:
POW (%) = 100 × (measured weight − standard weight)/standard weight
Japanese standard weight is the age- and sex-specific weight for height, which is based on data from the Annual Report of School Health Statistics 2000 by the Ministry of Education, Culture, Sports, Science, and Technology, Japan. POW is reported to be a more appropriate method than BMI % for school-age children. A POW of 20% is equivalent to approximately the 90th BMI % of children with average height and weight, and the criteria for obesity are defined as POW ≥ 20% (≥ 120 % of the standard weight) (14). For non-obese children (NOB), study participants were recruited during an annual medical check-up at a junior high school in Kyoto. The NOB group did not include children with underlying conditions. Informed consent was obtained from 288 children and their parents. Eighteen children were excluded from the NOB group due to a high POW. These children were included in the obese children group (OB). Eventually, 270 children were enrolled in the NOB group. The median (range) age was 13.5 years (12.1-15.2). In the OB group, 68 obese children who visited our outpatient clinic were selected. Informed written consent of these children was obtained through their parents. Finally, we enrolled 86 children as OB (18 children as above were added to this group) (Fig 1). The median (range) age was 11.1 years (4.6-17.5) (Table 1). POW is unique to Japan; thus, the Rohrer index was used to verify that the same results could be obtained using global obesity standards. The presence or absence of obesity was determined using the Rohrer index, and the same analysis was performed. The Rohrer index was determined in kilograms per cubic meter, and the criteria for obesity were defined as Rohrer’s index ≥ 145. Based on the Rohrer index, we classified 265 and 91 children into the NOB and OB groups, respectively (Table 2).
Genomic DNA was extracted from blood leukocytes using a genomic DNA separation kit (DnaQuick Ⅱ, DS Pharma Biomedical, Osaka, Japan). We analyzed the following polymorphisms of three genes; DIO2 Thr92Ala (rs225014), UCP1-3826 A/G (rs1800592), and β3AR Trp64Arg (rs4994). Each gene was detected via polymerase chain reaction (PCR) using with the forward and reverse primers as follows: DIO2 forward primer = 5’-GGTACCATTGCCACTGTTGTCA-3’, DIO2 reverse primer = 5’-GTCAGGTGAAATTGGGTGAGGAT-3’, UCP1 forward primer = 5’-CCAGTGGTGGCTAATGAGAGAA-3’, UCP1 reverse primer = 5’-GCACAAAGAAGAAGCAGAGAGG-3’, β3AR forward primer = 5’-CGCCCAATACCGCCAACAC-3’, β3AR reverse primer = 5’-CCACCAGGAGTCCCATCACC-3’.
Genotyping was performed by using ABI 7500 Fast Real-time PCR System (Applied Biosystems, Foster City, CA, USA), TaqMan®︎Genotyping PCR Master Mix (Thermo Fisher Scientific, Waltham, MA, USA), and TaqMan®︎SNP Genotyping Assay (Thermo Fisher Scientific).
Clinical data were collected as follows: sex, age at first visit, height, weight, BMI, POW, serum total cholesterol (TC), high-density lipoprotein cholesterol (HDLC), Low-density lipoprotein cholesterol (LDLC), triglycerides (TGs), random blood glucose (RBG), insulin, and hemoglobin A1c (HbA1c). Blood samples were randomly collected.
Clinical and laboratory data were summarized as median (P25-P75) for continuous variables and number (%) for categorical variables and compared between groups stratified according to obesity status (NOB, OB) and genotype prevalence using Mann-Whitney U test or Fisher’s exact test. The association between DIO2/UCP1/β3AR genotypes and obesity was analyzed using cross tabulation and Fisher’s exact test. Simple and multiple logistic regression analyses were performed to evaluate the contribution of gene polymorphism to obesity. For multiple logistic analysis, each genotype in each gene was included as an independent variable: DIO2 Thr/Thr, DIO2 Thr/Ala, DIO2 Ala/Ala, UCP1 AA, UCP1 AG, UCP1 GG, ß3AR Trp/Trp, ß3AR Trp/Arg, and ß3AR Arg/Arg. In multiple logistic analysis, a backward stepwise selection method was applied and the best-fit model was determined according to the Akaike information criterion. In this exploratory study, sample size was not determined statistically, and multiplicity adjustment was not considered in the statistical analysis. A P value less than 0.05 was considered statistically significant. All statistical analyses were performed using SPSS version 26.0 (IBM, Armonk, NY, USA).