Serum thyrotropin concentration in children with isolated thyroid nodules.

OBJECTIVE: To investigate the correlation between serum thyroid-stimulating hormone (TSH) concentration and nodule nature in pediatric patients with thyroid nodules, with the aim of identifying a marker able to differentiate benign and malignant nodules. STUDY DESIGN: This was a retrospective analysis of serum TSH concentrations in a multicentric case series of 125 pediatric patients with benign and malignant thyroid nodules. RESULTS: Of the 125 patients, 99 had benign thyroid nodules and 26 had differentiated thyroid cancer (24 papillary and 2 follicular). Final diagnosis was based on surgery in 57 cases and on a benign cytology plus clinical follow-up in 68 cases. Serum TSH concentration was significantly higher in patients with thyroid cancer compared with those with benign nodules (3.23 ± 1.59 mU/L vs 1.64 ± 0.99 mU/L; P < .001). Binary logistic regression analysis revealed that serum TSH was the sole predictor of malignancy (P < .001). Dividing the patient cohort into 5 groups based on serum TSH quintiles (TSH cutoffs 0.40, 1.00, 1.50, 1.80, and 2.80 mU/L), we observed that cancer prevalence increased in parallel with serum TSH (P < .001), with respective rates of 0%, 4%, 16%, 32%, and 52% in the 5 quintile groups. CONCLUSION: Because cases with malignant nodules are most likely seen in the upper normal serum TSH range (ie, >2.8 mU/L), serum TSH concentration can serve as a predictor of thyroid cancer in pediatric patients with thyroid nodules and can inform the decision of when to submit patients to further investigation by cytology

Stochastic epigenetic mutations as possible explanation for phenotypical discordance among twins with congenital hypothyroidism

Purpose The elevated frequency of discordance for congenital hypothyroidism (CH) phenotype between monozygotic twins suggests the involvement of non-mendelian mechanisms. The aim of the study was to investigate the role of epigenetics in CH pathogenesis. Methods A genome-wide DNA methylation analysis was performed on the peripheral blood of 23 twin pairs (10 monozygotic and 13 dizygotic), 4 concordant and 19 discordant pairs for CH at birth. Results Differential methylation analysis did not show significant differences in methylation levels between CH cases and controls, but a different methylation status of several genes may explain the CH discordance of a monozygotic twin couple carrying a monoallelic nonsense mutation of DUOX2. In addition, the median number of hypo-methylated Stochastic Epigenetic Mutations (SEMs) resulted significantly increased in cases compared to controls. The prioritization analysis for CH performed on the genes epimutated exclusively in the cases identified SLC26A4, FOXI1, NKX2-5 and TSHB as the genes with the highest score. The analysis of significantly SEMs-enriched regions led to the identification of two genes (FAM50B and MEG8) that resulted epigenetically dysregulated in cases. Conclusion Epigenetic modifications may potentially account for CH pathogenesis and explain discordance among monozygotic twins

Identification of a Shared Microbiomic and Metabolomic Profile in Systemic Autoimmune Diseases

Dysbiosis has been described in systemic autoimmune diseases (SADs), including systemic lupus erythematosus (SLE), Sjögren’s syndrome (SjS), and primary anti-phosholipid syndrome (PAPS), however the biological implications of these associations are often elusive. Stool and plasma samples from 114 subjects, including in SLE (n = 27), SjS (n = 23), PAPs (n = 11) and undifferentiated connective tissue (UCTD, n = 26) patients, and geographically-matched healthy controls (HCs, n = 27), were collected for microbiome (16s rRNA gene sequencing) and metabolome (high-performance liquid chromatography coupled to mass spectrometry) analysis to identify shared characteristics across diseases. Out of 130 identified microbial genera, a subset of 29 bacteria was able to differentiate study groups (area under receiver operating characteristics (AUROC) = 0.730 ± 0.025). A fair classification was obtained with a subset of 41 metabolic peaks out of 254 (AUROC = 0.748 ± 0.021). In both models, HCs were well separated from SADs, while UCTD largely overlapped with the other diseases. In all of the SADs pro-tolerogenic bacteria were reduced, while pathobiont genera were increased. Metabolic alterations included two clusters comprised of: (a) members of the acylcarnitine family, positively correlating with a Prevotella-enriched cluster and negatively correlating with a butyrate-producing bacteria-enriched cluster; and (b) phospholipids, negatively correlating with butyrate-producing bacteria. These findings demonstrate a strong interaction between intestinal microbiota and metabolic function in patients with SADs.This work was supported by EU/EFPIA/Innovative Medicines Initiative Joint Undertaking PRECISESADS grant No. 115565