Human reference sequences for key thyroid-related genes (TSHB, TSHR, TG, DIO1, and TPO) were retrieved from the National Center for Biotechnology Information (NCBI). These genes were selected based on their well-established roles in thyroid hormone synthesis, regulation, and action. After removing repetitive and low-quality regions, these sequences were used to construct a local nucleotide database.

Pre-miRNA and mature miRNA sequences were obtained from miRBase (http://www.mirbase.org). Candidate miRNAs were shortlisted using bioinformatic predictions (TargetScan, miRDB, miRTarBase) and prioritized based on:

Mature miRNA sequences were used to identify homologs in the hypothyroidism-specific database via BLAST 2.2.26+ (e-value threshold: 0.01). For non-protein-coding regions, sequences with ≤3 mismatches were retained. Putative pre-miRNA sequences within aligned regions were extracted12.

Secondary structures of pre-miRNAs were predicted using RNAfold13, requiring:

Putative targets were validated using TargetScan.

The study was approved by the institutional ethics committee and adhered to the Helsinki Declaration. After obtaining informed consent, blood samples were collected from 20 primary hypothyroidism patients and 20 healthy controls at Saveetha Medical College and Hospital14. Hypothyroidism was confirmed via Thyroid Function Tests (TSH, T3, T4). Samples were centrifuged and stored at –80°C.

Inclusion: Participants aged ≥18 years with informed consent.e.g., diabetes, hypertension).

Total RNA was extracted from blood using TRIzol reagent (Invitrogen) per manufacturer’s protocol. RNA purity and concentration were measured via NanoDrop 2000 Lite spectrophotometer (Thermo Fisher). Samples were stored at –20°C15.

RNA was reverse-transcribed using: nuclease-free water, universal miRNA adapter, oligo(dT)₁₈ primer (Promega, 50 μM), and dNTPs (10 mM each). The mixture (10 μL) was incubated at 65°C (5 min), chilled, then expanded to 20 μL with 5× PrimeScript Buffer (NEB), murine RNase inhibitor (NEB), reverse transcriptase (NEB), and water. Cycling conditions (MiniAmp Plus Thermocycler): 30°C (10 min), 42°C (30 min), 95°C (5 min), 40°C (1 min). cDNA was stored at –20°C16.

STAT3 and miR-124-3p expression was analyzed using SYBR Green (Takara) on a Bio-Rad CFX96 system. GAPDH and U6 served as endogenous controls17, 18, 19. Primers (Origene; Table 1) were used under cycling conditions: 95°C (30 sec), then 40 cycles of 95°C (5 sec) and annealing (30 sec), followed by a melt curve. Experiments were run in duplicate, and expression was quantified via 2^–ΔΔCq 16.

Table 1

miRNA/Gene	Forward Sequence (5'-3')	Reverse Sequence (5'-3')
miR-124-3p	CGCGTAAGGCACGCGGTG	ATCCAGTGCAGGGTCCGAGG
STAT3	GGGCATTTTTATGGCTTTCAAT	GTTAACCCAGGCACACAGACTTC

Data are presented as mean ± SEM. Intergroup differences were assessed via Student’s t-test (Microsoft Excel 365), with significance at P < 0.05 (*). Pearson correlation and 95% confidence intervals for mean differences were calculated.

Figure 1

Table 2

No	Structure	Sequence (5'-3')
1	Stem-loop	AGGCCUCUCUCUCCGUGUUCACAGCGGACC UUGAUUUAAAUGUCCAUACAAUUAAGGCA CGCGGUGAAUGCCAAGAAUGGGGCUG
2	Mature miRNA	UAAGGCACGCGGUGAAUGCCAA

Table 3

Source miRNA	Source organism	Pre-miRNA length	Minimum Free Energy	Mature Sequence	Match Extent	Strand	A+U%
miR-124-3p	Homo sapiens	85	- 35.30 kcal	UAAGGCACGCGG UGAAUGCCAA	22/22	3p	49.41

MicroRNAs (miRNAs) play a critical role in regulating gene expression and are increasingly recognized as key contributors to disease progression, including endocrine disorders such as hypothyroidism. Dysregulation of specific miRNAs could contribute to the onset or progression of this condition, highlighting their potential as early diagnostic biomarkers or therapeutic targets.

In this study, we employed a bioinformatic approach to identify candidate miRNAs associated with hypothyroidism. Reference sequences for hypothyroidism-related genes were sourced from the NCBI database, and pre-miRNA sequences were obtained from miRBase. Through sequence alignment and secondary structure prediction, miR-124-3p emerged as a candidate with strong potential relevance. Secondary structure analysis using RNAfold confirmed the mature form of this miRNA, predicting a minimum free energy of –35.50 kcal/mol, consistent with a stable hairpin structure (Figure 1; Table 2, Table 3). Thus, miR-124-3p was selected for further expression analysis in clinical samples.

Table 4

No	Target Protein	Molecular function	Biological process
1	Signal Transducer and activator of transcription 3	Proinflammatory gene expression	Cell survival, cytokine release
2	Ephrin B3	Regulates signalling for tissue boundaries	Receptor tyrosine kinase
3	Filamin B beta	Cell structure	Carry nutrients
4	Tubulin gamma 1	Microtubule nucleating factor	Cell division
5	Paired box 3	Signalling pathways	Embryonic development

Potential targets of miR-124-3p were identified using TargetScan. The analysis revealed several significant target transcripts, including PAX3, STAT3, PARP8, KRR1, SP3, SIK1, and others (Table 4).

Figure 2

Figure 3

Figure 4

We used qRT-PCR to analyze miR-124-3p and STAT3 expression in blood samples from hypothyroid patients and healthy controls. Compared with controls, hypothyroid patients exhibited significantly reduced miR-124-3p levels and elevated STAT3 levels (Figure 2 and Figure 3). The inverse relationship between STAT3 upregulation and miR-124-3p downregulation suggests a negative correlation (Figure 4), where changes in one mirror opposing changes in the other. These findings warrant further investigation into their significance in hypothyroidism.

Additionally, STAT3’s role in thyroid function remains underexplored but potentially significant. Studies indicate that thyroid hormone (T4) promotes STAT3 phosphorylation and nuclear translocation, linking thyroid hormones directly to STAT3 signaling pathways critical for thyroid function20. STAT3 also participates in autoimmune processes; its dysregulation is implicated in autoimmune thyroid diseases like Hashimoto's thyroiditis21. Hypothyroidism reduces hypothalamic and pituitary ObRb–STAT3 signaling, potentially impairing leptin-mediated thyroid regulation22. Furthermore, STAT3 may act as a tumor suppressor in thyroid cancer, highlighting its complex involvement in both normal and pathological thyroid states23. Collectively, these findings underscore the need to further explore STAT3’s role in thyroid hormone synthesis and autoimmunity in this context.