Relationship between Thyroid Hormones and Metabolic Syndrome

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Relationship between Thyroid Hormones and Metabolic Syndrome in a Normal Thyroid Function Population in Western China: A Cross-Sectional Study Based on Both Epidemiological and Genetic Analysis

Metabolic syndrome (MetS) is a significant health concern worldwide. It is defined as a set of metabolic disorders including abdominal obesity, hyperglycemia, hypertension, and dyslipidemia. Thyroid hormones play a crucial role in cellular energy homeostasis and regulation. Over the past decade, the association between thyroid hormones and MetS in euthyroid subjects has been a topic of extensive research, but with inconsistent results. Some studies found a link between high thyrotropin (TSH) levels and increased MetS incidence or unfavorable metabolic parameters, while others did not. Similarly, the relationship between free thyroxin (FT4) levels and MetS has also been controversial.

This cross-sectional study, conducted in Shaanxi Province as part of the China National Diabetes and Metabolic disorders Study (CNDMDS) from June 2007 to May 2008, aimed to evaluate the association and causal relationship between thyroid hormones and MetS in people with normal thyroid function. The study involved 2903 individuals (1190 men) after excluding those with thyroid dysfunction, under 20 years of age, diagnosed with diabetes and taking medication, or with missing data.

Data Collection and Measurements

  • Questionnaire Data: A standardized questionnaire was used to collect demographic characteristics, lifestyle risk factors (such as cigarette smoking, alcohol drinking), personal medical history, and family history of diseases.
  • Metabolic Parameters: Body weight, height, body mass index (BMI), waist circumference (WC), hip circumference, waist/hip ratio, blood pressure, body fat rate, fasting glucose, fasting insulin, homeostasis model assessment of insulin resistance (HOMA-IR), area under curve (AUC) of glucose (AUCglu), and AUC of insulin (AUCins) were measured.
  • Thyroid Hormone Levels: Serum TSH, FT4, and FT3 levels were measured using electrochemiluminescence immunoassays.
  • Genetic Analysis: Genomic DNA was extracted, and single-nucleotide polymorphisms (SNPs) associated with TSH (NR3C2 – rs10032216, PDE10A – rs753760, CAPZB – rs10799824, PDE8B – rs2046045) and FT3/FT4 (DIO1 – rs2235544) were analyzed.

Statistical Analyses

  • Variable Comparison: Parametric continuous variables were compared using unpaired Student’s t-test, and categorical variables using the Chi-squared test.
  • Correlation Analysis: Univariate combined with multivariate linear regression was used to evaluate the linear correlation between thyroid hormones and metabolic parameters.
  • SNP Association: Multivariate logistic regression analysis was used to identify SNPs independently associated with MetS. Independent SNPs were then integrated into univariate linear regression to screen those associated with thyroid hormones.
  • Mendelian Randomization: Based on the coefficients from the previous steps, Mendelian randomization analysis was conducted using the “Mendelian Randomization” package of R and inverse variance-weighted method to determine causal relationships.

Results

  • Gender Differences: Demographic and metabolic indexes showed significant differences between genders. Female subjects had higher body fat percentage, heart rate, TSH, and HDL-C levels, while other indicators were lower.
  • Thyroid Hormone – Metabolic Parameter Correlations:
    • Serum FT3, FT4, and log-TSH levels were negatively correlated with HDL-C levels (after adjusting for age, sex, smoking, and alcohol history).
    • FT3 and FT4 were positively correlated with BMI, WC, systolic blood pressure (SBP), and various blood glucose-related indexes.
    • TSH was negatively correlated with blood glucose-related indexes.
    • The FT3/FT4 ratio was negatively correlated with most metabolic parameters.
  • MetS Incidence and Thyroid Hormones: The incidence of MetS was positively correlated with FT3 and TSH levels and negatively correlated with the FT3/FT4 ratio.
  • SNP Association with MetS and Thyroid Hormones: rs10799824 G-G, rs10799824 G-A, rs2235544 C-C, and rs2235544 C-A were independently related to MetS. Among them, rs2235544 C-C was the only one independently related to thyroid hormones (FT3/FT4).
  • Mendelian Randomization: The regression coefficients of rs2235544 C-C and MetS and rs2235544 C-C and FT3/FT4 were included in Mendelian randomization. The inverse variance-weighted method suggested a causal relationship between FT3/FT4 and MetS.

Genetic Considerations (DIO1 Gene)

The SNPs in the human DIO1 gene affect the serum T3:T4 ratio. The SNP – rs2235544 in intron 3 of the DIO1 gene is an important genetic determinant of DIO1 activity. Previous studies showed that the minor allele “A” was associated with a decreased FT3/FT4 ratio and increased FT4 levels. In this study, allele “C” of rs2235544 was positively correlated with FT3/FT4 and negatively correlated with MetS. Analysis using co-dominant and dominant models showed that allele “A” increased MetS risk and FT4 level and decreased the FT3/FT4 ratio. This supports the negative correlation between MetS risk and the FT3/FT4 ratio.

Conclusion

The highlight of this study was the finding that MetS risk was negatively associated with the FT3/FT4 ratio in the euthyroid Chinese population. This result was not consistent with some other studies, possibly due to differences in results regarding the association between FT4 level and metabolic parameters. However, the study used genetic association analysis to confirm the nature of the association between the FT3/FT4 ratio and MetS. This suggests that the balance of FT3 and FT4 may be more important than previously recognized.

In conclusion, this study provides valuable insights into the relationship between thyroid hormones and MetS in a normal thyroid function population. The use of both epidemiological and genetic analysis methods adds strength to the findings. Further research is needed to better understand the underlying mechanisms and to confirm these results in different populations.

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doi.org/10.1097/CM9.0000000000001553

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