*2.1. Participants*

One hundred and sixty-five unrelated military professionals were selected for this study. All participants were aged 19–54 years, ancestrally fitted (all volunteers were Polish and Eastern Europe residents for 3 generations), and they represented similar physical activity levels. The experimental protocols used in this study were conducted in accordance with the World Medical Association's Declaration of Helsinki and were positively verified by the Ethics Committee of the Military Institute of Hygiene and Epidemiology (no. 1/XXI /2016). The participants received an information sheet regarding the research details, aim of the study and procedures applied, as well as potential risks and benefits associated with their participation. All volunteers gave written, informed consent for the genotyping, and they were informed that the study will be anonymous and the results would be private.

#### *2.2. Body Composition Measurements*

Height was measured using a portable stadiometer (without shoes) (TANITA HR-001, Tanita Corporation, Tokyo, Japan). Body composition (including fat %) and body weight were measured using bioelectrical impedance analysis (BIA) using the TANITA MC-780 machine (Tanita Corporation, Japan) with an accuracy of 0.1 kg according to the procedure specified in the instruction manual (lightly dressed, without shoes). All measurements were performed according to the procedure specified in the instruction manual and without any metal objects. The following parameters were noted: BMI (kg/m2), height (cm), weight (kg), fat mass index (FMI; kg/m2) [24], visceral tissue index (VTI; level), and fat percentage (%).

The participants (*n* = 165) were divided into two groups depending on their BMI (body weight/height2; kg/m2). The control group (CONBMI; *n* = 77) comprised people with BMI between 20.0 and 25.0, while the overweight group (OVERBMI; *n* = 88) had a BMI of ≥25.0. They were also divided into two groups depending on their FMI (fat mass/height2; kg/m2). FMI values between 3 and 6 were classified as normal fat mass; FMI lower than 3 —fat deficit; FMI higher than 6—excess fat. Participants whose FMI values were 6 and lower were classified into the CONFMI group (*n* = 124), while those whose FMI values were higher than 6 were grouped into the OVERFMI group (*n* = 41). Statistically significant differences between participants in both groups were observed for parameters BMI (kg/m2), age (years), weight (kg), FMI (kg/m2), VTI (level) and Fat(%) (*p*-value < 0.01). No statistically significant difference was shown in the parameter height (cm) (*p*-value = 0.81, 0.34) (Table 2). Detailed characteristics of experimental groups are given in Table 2.

**Table 2.** Anthropometry and body composition of the participants.


#### *2.3. Genetic Analyses*

The buccal cells of the participants were collected using swabs (Copan FLOQSwabs, Interpath, Murrieta, Australia). Genomic DNA was extracted from the donated buccal cells using a High Pure PCR Template Preparation Kit (Roche Diagnostics, Munich, Germany)

according to the manufacturer's protocols. DNA samples of good quality and quantity were stored at -20 ◦C. The exclusion criteria were: failure in DNA extraction; DNA degradation; abnormal gene detection results; incomplete basic information. All samples were genotyped in duplicate, using TaqMan Pre-De-signed SNP Genotyping Assays, which are given in Table 3 (Applied Biosystems, Waltham, MA, USA) on a CFX Connect Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA) according to the manufacturer's recommendations. The assays contained primers and fluorescently labeled (FAM and VIC) minor groove binder (MGB) probes. The real-time PCR conditions were as follows: 5 min of initial denaturation (95 ◦C), then 40 cycles of denaturation (15 s, 95 ◦C) and annealing/extension (60 s, 60 ◦C).

**Table 3.** SNP genotyping assays used in the study.


#### *2.4. Statistical Analyses*

All statistical analyses were performed using the program R (version 2.0-1, The R Foundation for Statistical Computing; https://cran.r-project.org (accessed on 20 September 2021)). Anthropometric data are shown as mean values ± standard deviation and differences among experimental groups were analyzed with Student's t-test which was statistically significant when *p* < 0.05. To check the compliance of the variables with the normal distribution, the Shapiro–Wilk test was used and Levene's test was used for verification of the homogeneity of variance. Single-locus analysis was performed considering four genetic models (codominant, dominant, recessive and overdominant) and was calculated with the SNPassoc package for R. The models were constructed concerning the minor allele and were checked adjusted by age as a potential factor influencing the result. FDR-adjusted *p*-values were calculated with the fdrtool package for R. An odds ratio (OR) was used as a measure of association between an exposure and an outcome and to determine whether a particular genotype is a risk factor for being overweight. The Akaike information criterion (AIC) was used to evaluate how well a model fits the data. A genetic model-free Multifactor dimensionality reduction (MDR) was used to detect the influence of the common effect of gene × gene interactions on BMI and FMI, and it was calculated with MDR3.0.2 (http://sourceforge.net/projects/mdr/ (accessed on 20 September 2021)); chi-square test was used for checking the statistical significance of the model. Balance accuracy was used as the evaluation measure to rank potential models and cross-validation consistency was used to choose the best models. The association of single alleles with BMI was calculated with Pearson's chi-squared test with the STAT package for R. The level of statistical significance was set at the level of *p* < 0.05. Genotype frequencies were analyzed using Fisher's exact test with the STAT package for R.
