Data on human genome sequences was obtained from the National Center for Biotechnology Information (NCBI) web portal for the International Nucleotide Sequence Database Consortium. The CKD genome sequence was located using a free search engine using the search term “chronic kidney disease genome sequence in Homo sapiens.” Following the removal of repetitive and inadequate sequences, a local nucleotide database dedicated to CKD-specific genome sequences was established. The reference sequence was obtained from human-reported miRNAs (http://www.mirbase.org/). The aforementioned CKD database was then queried to identify homologs within the miRNA dataset12.

Mature miRNAs were used as a starting point for searches to find homologs in the CKD database. miRNA sequences were used as search queries in homology searches using the Basic Local Alignment Search Tool (BLAST) 2.2.26+ against a recently created local database specific to hypothyroidism, employing 0.01 as the e-value threshold while keeping all other parameters at their default levels. For sequences with a maximum of three mismatches, BLAST was used to validate the non-protein encoding features. The aligned section was then designated as a potential precursor (pre)-miRNA sequence12.

Using RNA fold, a secondary structure was derived, yielding a mature miRNA sequence within the CKD sequence. Several criteria were employed for confirmation: 1) the RNA structure should exhibit a suitable stem-loop hairpin structure, 2) the mature miRNA should be located on one side of the hairpin structure, 3) the miRNA must have fewer than seven mismatches with the complementary miRNA in the opposing arm of the structure, and 4) the secondary structure should possess more negative energy and an A+U content of between 40 and 70%. Additionally, target prediction was performed using TargetScan to help find possible targets.

This study received approval from the Institutional Ethics Committee (581/03/2023/UG/S RB/SMCH), and all samples were gathered in strict adherence to the Helsinki Declaration. The sample size for the study was calculated using Gpower, and a set of 20 blood samples, comprising both CKD and normal cases, was acquired from patients who provided informed consent through the Department of Medicine at aveetha Medical College and Hospitals. The Department of Biochemistry at Saveetha Medical College and Hospitals confirmed the diagnosis of hypothyroidism. Following collection, the samples underwent centrifugation. While spinning the blood with an anticoagulant, the lighter plasma formed the upper layer and was carefully extracted13. This was then preserved in a deep freezer at −20 °C for subsequent analysis.

For the miR-149-5p and IL-6 genes, expression studies were conducted using the cDNA produced using Sybr Green (Takara, Japan). GAPDH was used as the housekeeping control for IL-6, and U6 was used for miR-149-5p. The primers required for this process were purchased from Origene, and the BioRad CFX96 Realtime System was used for expression experiments. The temperatures for PCR cycling were as follows: initial denaturation for one cycle at 95 ºC for 30 seconds, denaturation for 5 seconds at 95 ºC, and annealing for 30 seconds for a maximum of 40 cycles with a melt curve. The 2^-∆∆Cq technique was used to calculate the gene expression for each test in duplicate 14,15.

The mean of the duplicate experiments with the standard error of the mean (SEM) was calculated. Student’s t-test was applied using GraphPad Prism 10.1.0. to assess differences between the groups, with significance considered at a value less than 0.05 (*). Meanwhile, Tukey’s test was used to determine the statistical significance between the groups.

Figure 1

Figure 2

Figure 3

Figure 4

Table 1

S. No	Structure	Sequence
1	Stem-loop	GCCGGCGCCCGAGCUCUGGCUCCGUGUCU UCACUCCCGUGCUUGUCCGAGGAGGGAGGGAGGG ACGGGGGCUGUGCUGGGGCAGCUGGA
2	Mature miRNA	UCUGGCUCCGUGUCUUCACUCCC

Table 2

Source miRNA	Source organism	Pre-miRNA length	Minimum Free Energy	Mature Sequence	Match Extent	Strand	A+U%
miR-149-5p	Homo sapiens	89	- 52.70 kcal	UCUGGCUCCGUGU CUUCACUCCC	23/23	5p	26.9

Table 3

S. No	Target Protein	Molecular function	Molecular function
1	Interleukin 6	Multifunctional cytokine	Cellular function
2	BCL2 binding component 3	Binding of BCL2	Cell apoptosis
3	Transmembrane protein 234	Signal transmission	Transfer of molecules across the membrane
4	Tetraspanin 14	Enzyme binding activity	Notch signalling
5	Zinc finger protein 74	transcription	Inhibits acetylation

MiRNAs are crucial in modulating gene expression, exerting influence over the development and progression of diseases; thus, identifying the specific miRNA associated with CKD holds promise for early detection and therapeutic interventions. Employing a computational approach, we embarked on the task of identifying these miRNAs. To accomplish this, precursor miRNAs were collected from the miRbase database, while the CKD sequences were sourced from the NCBI database. After the meticulous examination of a substantial number of sequences, a single miRNA, hsa-miR-149a-5p, was discerned within the CKD genome sequences. This discovery was facilitated by employing RNA fold, which revealed hsa-miR-149-5p’s mature sequence, with the lowest free energy of 52.80 kcal.

Figure 1 illustrates the secondary structure of hsa-miR-149-5p, while Table 1 provides the stem-loop and mature sequence of miR-149-5p. Additionally, Table 2 presents comprehensive information regarding the length of the pre-miRNA, minimum free energy, mature sequence, match extent, and A+U% content of hsa-miR-149-5p.

TargetScan analysis pinpoints potential targets for the specific miRNA. Through this approach, several significant transcripts targeted by miR-149-5p, including IL-6, cyclin 1, BCL-2, cell division cycle 73, and transferrin receptor, among others, were identified. Table 3 provides an overview of these targets, along with their associated molecular functions and biological processes.

qRT-PCR gene expression analysis revealed the levels of miR-149-5p and IL-6 in blood samples from CKD patients, which were compared with those of normal individuals. When compared, CKD patients, particularly individuals with hypothyroidism, showed significant down-regulation in miR-149-5p levels and an increase in IL-6 levels. These findings suggest a potential role for miR-149-5p as well as IL-6 in CKD, which is to be further investigated. Figure 2 and Figure 3 depict the differential gene expression of miR-149-5p and IL-6 in CKD and normal blood samples. The relationship between increased IL-6 levels and decreased miR-149-5p levels in CKD patients suggests an inverse or negative correlation (as shown in Figure 4), thereby suggesting a systematic relationship between the two, with changes in one being associated with opposite changes in the other.