Functional annotation of lactase gene and its distal enhancer MCM6 for prediction of metabolically unhealthy obesity

INTRODUCTION

Recently, more and more data have been accumulating, indicating that single nucleotide variants (SNV) of genes make an important contribution to phenotypic differences between people, including personal characteristics of the development of compensatory reactions, and also determine the predisposition to the occurrence of a number of chronic diseases [1, 2].
According to the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, children and adolescents in the European Union have seen an increase in eating disorder-related mortality over the past 30 years (32.36% [95% UI 2.25 to 66.96]), and disability associated with the increasing incidence of type 2 diabetes mellitus (T2DM) [3–5]. Metabolically unhealthy obesity (MUO), including components such as abdominal obesity, insulin resistance, dyslipidemia, and hypertension, is highly hereditary and is caused by a combination of genetic and environmental factors [6]. One of the key triggers that initiates adipose tissue meta-inflammation in MUO is lactose maldigestion associated with the lactase (LCT) SNV gene [7].
The LCT gene is 49.3 kb long and is located on the long (q) arm of chromosome 2 at position 21 (2q21.3); it contains 17 exons and is translated into a 6 kb transcript. The LCT gene is transcribed towards the centromere. For efficient transcription of the LCT gene, the proximal promoter signal must be complemented by the activity of an enhancer located upstream of the LCT gene. It was found that the region located 850 bp upstream of the LCT gene has regulatory activity and is a necessary sequence to ensure high expression of the LCT gene in differentiated Caco-2 cells [8]. This regulatory region is called cis-regulatory element minichromosome maintenance complex component 6 (MCM6) [9]. The functional role of MCM6 in vertebrates is unknown, but it is associated with the “licensing” of DNA replication during the cell cycle. This association has been confirmed in a study of DNA collected from individuals of Finnish, South Korean, Italian, German, French, White, and African American ancestry [10].
Functional annotation of the LCT gene and its distal enhancer MCM6 opens up promising opportunities for predicting the effects of SNV in these regions in determining dietary and metabolic phenotypes: arterial hypertension (24–37%), dyslipidemia (58–66%), type 2 diabetes mellitus (26–69%) and obesity (40–70%) [11]. The results of the MiBioGen study, which involved 18,340 people from 11 countries, demonstrated that it is the 2q21.3 locus, which includes the LCT gene and 12 other genes associated with the synthesis of the LCT enzyme, that also determines the composition of the intestinal microbiome, thus, probably indirectly affecting human metabolism [12]. In this connection, the aim of our work was to study the contribution of SNV of the LCT gene and its distal enhancer MCM6 in the development of MUO in children.

MATERIALS AND METHODS

Ethical approval. Participants provided written informed consent, and research protocols and procedures were approved according to the ethical standards of the Helsinki Declaration 2013 and by the Human Research Ethics Committee of Dnipro State Medical University (meeting minutes No. 7 of December 11, 2019). Time of data collection: January 2020 – July 2022.
Study design: observational, analytical, longitudinal, cohort study [13]. Inclusion criteria: children with polygenic obesity (body mass index – BMI, ≥ 97th percentile) 6–18 years old. Exclusion criteria: children with monogenic and/or syndromic obesity, pregnancy, overweight children (BMI = 85–96th percentiles).
To test the hypothesis about the association of the studied SNV with obesity phenotypes, an analysis of the frequency of LCT/MCM6 genetic variants, along with measurements of anthropometric and biochemical parameters, according to the recommendations of IDEFICS 2014, was carried out in a cohort of 152 obese children aged 6–18 years in the children’s endocrinology department of CNE Dnipro Clinical Hospital No. 9 of the Dnipro City Council (children from an urban obesity clinic) [13, 14]. For the examination of children, the consent of their parents was obtained. The main group (n = 77) was represented by children with MUO. The control group (n = 75) consisted of children with metabolically healthy obesity (MHO). Each participant was identified by a code used in the database.
For inclusion in the main observation group, the presence of abdominal obesity and two of the following criteria were taken into account:

• fasting glycaemia ≥ 5.6 mmol/l [15],
• high-density lipoprotein cholesterol (HDL-C) ≤ 1.03 mmol/l or less than 10th percentile of the age norm [16],
• triglycerides (TG) ≥ 1.7 mmol/l or more than the 90th percentile of the age norm,
• systolic blood pressure (SBP) above the 90th percentile for a given age, gender and height [17].

The abdominal type of obesity was determined according to the consensus of the International Diabetes Federation, based on the excess of the waist circumference over the 90th percentile for children 6–15 years old or more than 94 cm for boys aged 16–18 years and more than 80 cm for girls 16–18 years old [18–20].
Anthropometric measurements were made in a child in underwear and without shoes. Height (cm) was measured using a Heightronic Digital Stadiometer to the nearest 0.1 cm. Weight (kg) was measured using a Tefal Bodysignal body composition analyzer (France). Waist circumference and hip circumference were measured using a standardized anthropometric tape, measuring the circumference at the midpoint between the top of the iliac crest and the lower part of the lateral rib cage to the nearest 0.1 cm. Body mass index was converted to SDS by means of the current World Health Organization growth references [21].
Systolic and diastolic blood pressure were measured using a digital oscillometric device, Dinamap ProCare (GE Healthcare).
Laboratory examination for the formation of observation groups for obesity phenotypes included general clinical methods. Blood samples were obtained after an overnight fast by venipuncture in vacutainer gel tubes, and serum was separated from cells by centrifugation in a certified laboratory (“Synevo”, Ukraine) using an analyzer and a Cobas 6000 test system; Roche Diagnostics (Switzerland). The analysis of serum glucose was carried out by the hexokinase method; the determination of TG and HDL-C of blood plasma was carried out by the enzymatic-colorimetric method. The determination of the level of basal insulin was carried out by electrochemiluminescent immunoassay. The level of basal insulin in the venous blood was considered normal: 2.6–24.9 μU/ml.
Genotyping LCT/MSM6 – 13910 (PCR-RT, Synevo, Ukraine) was performed in all examined children. DNA from peripheral blood mononuclear cells was isolated using the DNeasy Blood and Tissue Kit (Qiagen). TaqMan oligonucleotide primers and probes for LCT/MCM6 – 13910 genotypes were developed and synthesized by Applied Biosystems, USA (ID: C_15769614_10). Fluorescence data were analyzed with 7500 Allele Recognition Software, v.2.0.2. (Applied Biosystems, USA).
The sample population examined by whole genome sequencing (NGS, Illumina CSPro, CeGat, Germany) consisted of 27 children of the main and 15 children of the control group and was qualitatively homogeneous in relation to the general population. The average amount of DNA in samples was 0.875 μg. Library Preparation: Quantity used 50 ng. Library Preparation Kit: Twist Human Core Exome plus Kit (Twist Bioscience). Sequencing parameters: NovaSeq 6000; 2  100 bp.
Bioinformatic analysis – demultiplexing of the sequencing reads was performed with Illumina bcl2fastq (version 2.20). Adapters were trimmed with Skewer, version 0.2.2 [22]. DNA-Seq: Trimmed raw reads were aligned to the human reference genome (hg19-cegat) using the Burrows-Wheeler Aligner, BWA – mem version 0.7.17-cegat [23]. ABRA, version 2.18 and Genotype Harmonizer v.1.4.20 were used for local restructuring of readings in target regions to achieve more accurate detection of indels in the genome during mutagenesis [24, 25].
To evaluate the functional effects of SNV LCT/MCM6 in the development of MUO, nominal data analysis was performed using odds ratio (OR), 95% confidence interval (CI), Pearson correlation coefficients (C), normalized Pearson coefficient (C’), Cramer’s test (V), and Spearman’s criterion (r), where p-values less than 0.05 were considered statistically significant. Statistical processing of the results was performed using Microsoft Excel (Office Home Business 2KB4Y-6H9DB-BM47K-749PV-PG3KT) and STATISTICA 6.1 software (StatSoft Inc, no. AGAR909E415822FA).
The work is a part of the research work of the Department of Paediatrics 1 and Medical Genetics of the Dnipro State Medical University, “Prediction of the development of childhood diseases associated with civilization” (No. 0120U101324). The study was carried out according to the budget program of the Code of program classification of expenses and crediting 2301020, “Scientific and scientific and technical activities in the field of health care”, funded by the Ministry of Health of Ukraine from the state budget.

RESULTS

The average age of children in the main group was 12.09 ±0.59 years, in the control group 12.27 ±0.79 years. By gender, boys predominated in clinical groups among children with MUO, and their relative number exceeded that among children with MHO (72.7% vs. 61.5%), while girls predominated among MHO children, the percentage of which was 58.33% versus 41.66% boys, but these differences was not statistically significant (p > 0.05).
The mean BMI (in percentiles) in the main group was 99.54 ±0.31, while in the control group it was 98.74 ±0.39 (p = 0.12) and it was not statistically significant.
As shown by the results of the nominal analysis, the development of MUO is due to the influence of a number of factors (Table 1).
According to the data obtained, the factors contributing to the formation of MUO are: a high level of basal insulinemia (18.36 μU/ml and above); hereditary burden for metabolic syndrome; daily consumption of red meat, sausages, potatoes, rice, margarine, sugary carbonated drinks; “wild” genotype LCT/MCM6-13910.
Factors that reduce the risk of developing MUO can be considered: prolonged mealtime (20 minutes or more) and daily consumption of up to 2–3 servings of fresh vegetables and fruits, which is consistent with other literature data [26].
According to the data of LCT/MCM6 gene genotyping by PCR, the frequency of MUO (r = 0.22; p = 0.02) and extreme obesity (r = 0.22; p = 0.022) was higher in children with the “wild” genotype LCT/MCM6-13910 and was respectively OR = 80% (95% CI 66.96–88.76) and OR = 54% (95% CI 40.4–67.03), compared with carriers of mutant genotypes (r = –0.37; p < 0.001) (Table 2).
Whole genome sequencing using the NGS method allowed us to identify 20 SNV of the LCT gene among obese children: rs3816088, rs748841, rs6719488, rs3213890, rs2236783, rs2278544, rs375845174, rs147652514, rs3739022, rs2322659, rs3213891, rs116951780, rs140994860, rs17699796, rs35093754, rs2304371, rs148298513, rs3754689, rs4954449, rs147290601 (Table 2) и 11 SNV MCM6: rs61752701, rs141448886, rs201537325, rs2289049, rs3087353, rs1057031, rs143348934, rs3087348, rs4988270, rs2070068, rs141917101 (Table 3).
According to our data, the most significant functional effect on the development of MUO is caused by three SNV genotypes of the LCT gene: A/G rs3213891, Chr. 2: 136552371 (GRCh37); G/A rs3213890, Chr. 2:136552188 (GRCh37); C/T rs3754689, Chr. 2:136590746 (GRCh37) and one SNV genotype of the MCM6 gene – G/A rs105703,Chr. 2:136633962 (GRCh37). The risk of developing MUO among obese children in the presence of such SNV genotypes of the LCT gene as A/G rs3213891 increased by 1.75 times (95% CI 0.17–18.4); G/A rs3213890, 2.5 times (95% CI 0.65–10.06); C/T rs3754689 – 3.4 times (95% CI 1–13.6) and in the presence of the SNV genotype of the MCM6 gene G/A rs105703 – 2.6 times (95% CI 0.65v10).
We have established a direct correlation between SNV LCT and the risk of MUO in the A/G rs3213891 genotype (V = 0.073; C = 0.072; C’ = 0.102) of weak strength and in the G/A rs3213890 genotypes (V = 0.284; C = 0.273; C’ = 0.386), C/T rs3754689 (V = 0.278; C = 0.268; C’ = 0.379) of medium strength. There was also a direct correlation between SNV MCM6 G/A rs1057031 (V = 0.143; C = 0.142; C’ = 0.201) and the risk of moderate-strength MUO (p < 0.05).
The CADD indicators calculated by us for SNV LCT/MCM6 were characterized as follows: G/A rs3213890-0.216 (mutation in the intron region of the LCT gene); A/G rs3213891-2.787 (mutation in the intron region of the LCT gene); G/A rs1057031-9.898 (mutation in the 5’-untranslated region with a basic change in the 13th intervening sequence (IVS13 c.-13910) of the MCM6 gene, regarded as a variant of uncertain significance, according to the GnomAD browser); C/T rs3754689-10.09 (missense mutation in the LCT gene).

DISCUSSION

Metabolic disorders associated with MUO have a significant impact on the health of the younger generation [19, 27]. The lack of generally accepted criteria for the verification of the obesity phenotype required the search for new markers for identifying disorders of various metabolic pathways that would allow one to reliably distinguish between MHO and MUO.
We found a high correlation between an increased level of basal insulinemia and the development of MUO, which is caused by hyperlipidemia and cytokine adiposopathy and leads to the development of insulin resistance. Prolonged insulin resistance is accompanied by depletion of the possibilities of insulin secretion by β-cells, the secretion level of which becomes insufficient to maintain the physiological level of glucose in the blood, which leads to the development of stable hyperglycemia and increases the risk of developing T2DM, as shown earlier, by 5–20 times, compared with individuals with physiological body weight [28].
Along with other authors, we detected a high risk of MUO among children who regularly violate dietary recommendations and consume high-calorie foods from the “red zone” of the food traffic light system, as well as sugary carbonated drinks, in their daily diet [29, 30].
Despite the significant contribution of exofactors, a key role in the development of MUO is played by a genetic predisposition to the metabolic syndrome associated with adult-type hypolactasia due to the presence of mutations in the LCT gene or LCT non-persistence associated with a mutation in the MCM6 gene [31].
An excess of lactose in the modern human diet can initiate the development of meta-inflammation and insulin resistance. Violation of lactose degradation (MedGen UID: 75659), due to a deficiency in LCT activity, leads to an increase in the level of LCT in the blood serum [32]. So, lactose, by binding to galectin 9 (Gal-9), prevents activation of the Tim-3 receptor, which has an inhibitory effect on Th1 and Th17 cells [33, 34].
Unlike previous investigators, we have identified functional effects of previously undescribed SNV LCT (rs3213890, rs3213891, rs3754689) and MCM6 (rs1057031) in MUO formation [35–37].

CONCLUSIONS

The formation of MUO is caused by the following negative factors: the level of basal insulinemia is more than 18.36 μU/ml; hereditary burden for metabolic syndrome; daily consumption of red meat, sausages, potatoes, rice, margarine, sugary drinks; “wild” genotype LCT/MCM6-13910.
Among genetic biomarkers, three of the following genotypes provide a significant contribution to the development of MUO in children out of 20 SNV LCT that we identified in obesity: A/G rs3213891, G/A rs3213890, C/T rs3754689. Among the 11 SNV MCM6 diagnosed by us, G/A rs1057031 makes the greatest contribution to the development of MUO in children.

DISCLOSURE

The authors declare no conflict of interest.

REFERENCES