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Biological age & clocks
Research brief

Hashimoto's thyroiditis linked to higher biological and metabolic age in cross-sectional cohorts

In the cross-sectional cohorts described, people with Hashimoto's thyroiditis showed higher biological age indices and greater metabolic age acceleration than controls; the abstract reports associations, not causes. [1]

Automatic summary · not editorially reviewed

The key findings

  1. In the NHANES validation cohort, overall Hashimoto's thyroiditis was associated with higher Klemera-Doubal biological age (beta 3.16 years, 95% CI 1.77–4.56) after adjustment. [1]

  2. Metabolic age acceleration differed among controls, euthyroid Hashimoto and thyroid-dysfunction Hashimoto groups (Kruskal-Wallis P = 6.6 × 10⁻⁵). [1]

  3. Results for overt hypothyroid Hashimoto should be interpreted cautiously because of the small sample size and wide confidence intervals. [1]

The source at a glance

Study type / format
Cross-sectional study (abstract)
Population / context
People with Hashimoto's thyroiditis and healthy controls in the described clinical, NHANES and metabolomics cohorts.
Summary based on
Study abstract
Original publication
June 26, 2026

Biological age indices in Hashimoto cohorts

The abstract describes a cross-sectional study with two clinical discovery cohorts, an NHANES 2007–2012 validation cohort and a metabolomics cohort. Biological age was calculated from clinical biomarkers using the Klemera-Doubal method and Phenotypic Age, with corresponding age acceleration metrics. In the discovery cohorts, the Hashimoto group showed higher values on these indices and higher proportions of age acceleration than healthy controls. In the NHANES validation cohort, after adjustment for age, sex, socioeconomic and lifestyle factors, overall Hashimoto's thyroiditis was associated with higher Klemera-Doubal biological age (beta 3.16 years, 95% CI 1.77–4.56) and PhenoAge (beta 1.54 years, 95% CI 1.05–2.03).

Supporting source [1]

Metabolic age model and candidate metabolites

In the metabolomics cohort, a random forest metabolic age model was trained in healthy controls and internally evaluated by five-fold cross-validation; mean test-set performance was RMSE 8.75 years, MAE 7.11 years, R 0.634 and R² 0.427. Metabolic age acceleration, defined as predicted metabolic age minus chronological age, differed among controls, euthyroid Hashimoto and thyroid-dysfunction Hashimoto groups (Kruskal-Wallis P = 6.6 × 10⁻⁵), and both Hashimoto groups had higher values than controls after adjustment for age and sex. Integrated analysis identified 18 candidate metabolites; a classification model based on them had an AUC of 0.980. Citric acid, LPC 20:0 sn-1 and SM 34:2 were prioritized as core candidates.

Supporting source [1]

Cross-sectional scope and cautious subgroups

The abstract reports associations in cross-sectional cohorts, so it cannot show that Hashimoto's thyroiditis causes biological or metabolic age acceleration. Stage-specific analyses suggested relatively stable associations for euthyroid Hashimoto and subclinical hypothyroid Hashimoto, whereas results for overt hypothyroid Hashimoto should be interpreted cautiously because of the small sample size and wide confidence intervals. The metabolomics findings are described as exploratory, and the abstract does not report follow-up or whether the candidate metabolites predict later outcomes.

Supporting source [1]

How to interpret this

Abstract only; the full text was not reviewed. The design is cross-sectional, so associations cannot establish causation, and the metabolomics analyses are described as exploratory.

Based on the study abstract; the full paper, tables and supplementary data were not reviewed.

Source & supporting passages

Read the quoted passagesIn the language of the original source
  1. Finding 1 ↑

    beta = 3.16 years, 95% CI 1.77-4.56
  2. Finding 2 ↑

    Kruskal-Wallis P = 6.6 x 10^-5
  3. Finding 3 ↑

    small sample size and wide confidence intervals

AI-assisted summary with linked source passages. No independent editorial or clinical review.

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