Obesity-related genetic polymorphisms are associated with the risk of early puberty in Han Chinese girls

Variations in the LINGO2 and GLIS3 Genes and Gene-Environment Interactions Increase Gestational Diabetes Mellitus Risk in Chinese Women

Gestational diabetes mellitus (GDM) has been found to be a common complication in pregnant women, known to escalate the risk of negative obstetric outcomes. In our study, we genotyped 1,566 Chinese pregnant women for two single nucleotide polymorphisms (SNPs) in the LINGO2 gene and one SNP in the GLIS3 gene, utilizing targeted next-generation sequencing. The impact of two interacting genes, and the interaction of genes with the environment─including exposure to particulate matter (PM2.5), ozone (O3), and variations in prepregnancy body mass index (BMI)─on the incidence of GDM were analyzed using logistic regression. Our findings identify the variants LINGO2 rs10968576 (P = 0.022, OR = 1.224) and rs1412239 (P = 0.018, OR = 1.231), as well as GLIS3 rs10814916 (P = 0.028, OR = 1.172), as risk mutations significantly linked to increased susceptibility to GDM. Further analysis underscores the crucial role of gene-gene and gene-environment interactions in the development of GDM among Chinese women (P < 0.05). Particularly, the individuals carrying the rs10968576 G-rs1412239 G-rs10814916 C haplotype exhibit increased susceptibility to GDM during the prepregnancy period when interacting with PM2.5, O3, and BMI (P = 8.004 × 10-7, OR = 1.206; P = 6.3264 × 10-11, OR = 1.280; P = 9.928 × 10-7, OR = 1.334, respectively). In conclusion, our research emphasizes the importance of the interaction between specific gene variations─LINGO2 and GLIS3─and environmental factors in influencing GDM risk. Notably, we found significant associations between these gene variations and GDM risk across various environmental exposure periods.

Association of obesity and menarche SNPs and interaction with environmental factors on precocious puberty

BACKGROUND

Obesity is an important cause for the precocious or early puberty. However, the association between obesity-related loci and the risk of precocious puberty as well as the effect of gene-environment interaction are unclear, especially in the Chinese children population.

METHODS

This was a case-control study using baseline data from two cohorts and hospital cases in China. 15 SNPs loci and several environmental factors were included in the analysis of 1201 participants. Chi-square test and logistic regression were used to analyze the association between SNPs and precocious puberty. Additionally, exploratory factor analysis was conducted on 13 environmental variables, and then to explore their interaction with genes on precocious puberty.

RESULTS

The effect allele C of rs571312, and G of rs12970134 MC4R were associated with precocious puberty in girls with obesity. Regarding the gene-environment interaction, we found that when girls were in the high socioeconomic status, the rs571312 (OR: 3.996; 95% CI: 1.694-9.423) and rs12970134 (OR: 3.529; 95% CI: 1.452-8.573) risk genotypes had a greater effect on precocious puberty.

CONCLUSIONS

The obesity risk gene polymorphisms MC4R rs571312 and rs12970134 were associated with precocious puberty in Chinese girls with obesity, and girls with risk genotypes and high socioeconomic status should be given extra attention.

IMPACT

This is the first study that identified the association between rs571312 and rs12970134 of MC4R gene and precocious puberty in Chinese children. We found that when girls were in the high socioeconomic status, the risk genotypes of rs571312 and rs12970134 had a greater effect on precocious puberty. The results of this study have great public health implications. It is recommended that girls who are in high socioeconomic status and have a high genetic risk for early sexual maturity should closely monitor their pubertal development and consider early intervention strategies.

Is early or late biological maturation trigger obesity? A machine learning modeling research in Turkey boys and girls

Biological maturation status can affect individual differences, sex, height, body fat, and body weight in adolescents and thus may be associated with obesity. The primary aim of this study was to examine the relationship between biological maturation and obesity. Overall, 1,328 adolescents (792 boys and 536 girls) aged 12.00 ± 0.94-12.21 ± 0.99 years, respectively (measured for body mass, body stature, sitting stature). Body weights were deter-mined with Tanita body analysis system and adolescent obesity status was calculated according to the WHO classification. Biological maturation was determined according to the somatic maturation method. Our results showed that boys mature 3.077-fold later than girls. Obesity was an increasing effect on early maturation. It was determined that being obese, overweight and healthy-weight increased the risk of early maturation 9.80, 6.99 and 1.81-fold, respectively. The equation of the model predicting maturation is: Logit (P) = 1/(1 + exp. (- (-31.386 + sex-boy * (1.124) + [chronological age = 10] * (-7.031) + [chronological age = 11] * (-4.338) + [chronological age = 12] * (-1.677) + age * (-2.075) + weight * 0.093 + height * (-0.141) + obesity * (-2.282) + overweight * (-1.944) + healthy weight * (-0.592)))). Logistic regression model predicted maturity with 80.7% [95% CI: 77.2-84.1%] accuracy. In addition, the model had a high sensitivity value (81.7% [76.2-86.6%]), which indicates that the model can successfully distinguish adolescents with early maturation. In conclusion, sex and obesity are independent predictors of maturity, and the risk of early maturation is increased, especially in the case of obesity and in girls.

Oestrogenic Activity in Girls with Signs of Precocious Puberty as Exposure Biomarker to Endocrine Disrupting Chemicals: A Pilot Study

The relationship between endocrine disrupting chemical (EDC) exposure and Precocious Puberty (PP) was investigated in this pilot study, involving girls with signs of PP (P) and pre-pubertal girls (C). Risk factors for PP were assessed through questionnaires, while 17β-oestradiol (E2) levels and oestrogenic activity were quantified on sera. The oestrogenic activity, expressed as E2 equivalent concentration (EEQ), was applied as EDC exposure biomarker. Questionnaires showed a low EDC knowledge, a high EDC exposure, and a potential relationship between some habits at risk for EDC exposure and PP. EEQs were similar between C and P; however, they were significantly higher in girls living in an urban environment than in girls living in a rural environment, suggesting a potential higher EDC exposure in cities. The results of this pilot study highlighted the need to raise awareness on EDCs and can be considered a starting point to clarify the relationship between EDC exposure and PP.