Type 2 diabetes mellitus (T2DM) is a complex heterogeneous disease resulting from the environment and genetic interactions. Lately, genetic association studies have shown that polymorphisms in long noncoding RNAs (lncRNAs) are associated with T2DM susceptibility. This preliminary study is aimed at investigating if HOX transcript antisense RNA (HOTAIR) polymorphisms contribute to T2DM development. Five hundred clinically diagnosed T2DM cases and 500 healthy controls were recruited from the southeast Iranian population. Genomic DNA was isolated from nucleated blood cells and genotyped for MspI (C/T) (rs920778) and AluI (A/G) (rs4759314) polymorphisms using the PCR-RFLP technique. For genotyping rs12826786 C/T and rs1899663 G/T variants, ARMS-PCR method was applied. Our findings indicated that HOTAIR rs920778 C/T, rs12826786 C/T, and rs4759314 A/G polymorphisms have a significant positive association with T2DM, while a negative association was observed between rs1899663 G/T T2DM susceptibility. Significant associations were also observed between rs920778 C/T and HDL-C as well as s4759314 A/G and both FBS and LDL-C in T2DM patients. Haplotype analysis indicated that the CGCG, CTTG, TGTA, and TTTG haplotypes of rs920778/rs1899663/rs12826786/rs4759314 significantly enhanced T2DM risk by 1.47, 1.96, 2.81, and 4.80 folds, respectively. No strong linkage disequilibrium was found between the four HOTAIR SNPs. We firstly reported that HOTAIR rs1899663 G/T, rs12826786 C/T, rs4759314 A/G, and rs920778 C/T polymorphisms might influence T2DM susceptibility by modulating different signaling pathways and could be regarded as potential prognostic markers in T2DM patients.

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It has been established that microRNAs (miRNAs) are involved in the regulation of immune responses and serve as biomarkers of inflammatory diseases as well as recurrent spontaneous miscarriage (RSM). Herein, we aimed to study the relationship between three functional miR146a gene polymorphisms with idiopathic RSM (IRSM) susceptibility. We recruited 161 patients with IRSM and 177 healthy women with at least one live birth and without a history of abortion. Genotyping was performed using RFLP-PCR and ARMS-PCR methods. We found that the rs6864584 T/C decreased the risk of IRSM under dominant TT+TC vs. CC ( OR = 0.029 ) and allelic C vs. T ( OR = 0.028 ) contrast models. Regarding rs2961920 A/C and rs57095329 A/G polymorphisms, the enhanced risk of IRSM was observed under different genetic contrasted models, including the codominant CC vs. AA ( OR = 2.81 for rs2961920) and codominant GG vs. AA ( OR = 2.36 for rs57095329). After applying a Bonferroni correction, haplotype analysis revealed a 51% decreased risk of IRSM regarding the ACA genotype combination. This is the first study reporting that miR146a rs57095329 A/G, rs2961920A/C, and rs6864584 T/C polymorphisms are associated with the risk of IRSM in a southern Iranian population. Performing replicated case-control studies on other ethnicities is warranted to outline the precise effects of the studied variants on the risk of gestational trophoblastic disorders.

Diabetes, a leading cause of death globally, has different types, with Type 2 Diabetes Mellitus (T2DM) being the most prevalent one. It has been established that variations in the SLC11A1 gene impact risk of developing infectious, inflammatory, and endocrine disorders. This study is aimed to investigate the association between the SLC11A1 gene polymorphisms (rs3731864 G/A, rs3731865 C/G, and rs17235416 + TGTG/− TGTG) and anthropometric and biochemical parameters describing T2DM. Eight hundred participants (400 in each case and control group) were genotyped using the polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP) and amplification-refractory mutation system-PCR (ARMS-PCR) methods. Lipid profile, fasting blood sugar (FBS), hemoglobin A1c level, and anthropometric indices were also recorded for each subject. Findings revealed that SLC11A1–rs3731864 G/A, –rs17235416 (+ TGTG/− TGTG) were associated with T2DM susceptibility, providing protection against the disease. In contrast, SLC11A1–rs3731865 G/C conferred an increased risk of T2DM. We also noticed a significant association between SLC11A1–rs3731864 G/A and triglyceride levels in patients with T2DM. In silico evaluations demonstrated that the SLC11A2 and ATP7A proteins also interact directly with the SLC11A1 protein in Homo sapiens. In addition, allelic substitutions for both intronic variants disrupt or create binding sites for splicing factors and serve a functional effect. Overall, our findings highlighted the role of SLC11A1 gene variations might have positive (rs3731865 G/C) or negative (rs3731864 G/A and rs17235416 + TGTG/− TGTG) associations with a predisposition to T2DM.

Aptamers (Apts) are synthetic nucleic acid ligands that can be engineered to target various molecules, including amino acids, proteins, and pharmaceuticals. Through a series of adsorption, recovery, and amplification steps, Apts are extracted from combinatorial libraries of synthesized nucleic acids. Using aptasensors in bioanalysis and biomedicine can be improved by combining them with nanomaterials. Moreover, Apt‐associated nanomaterials, including liposomes, polymeric, dendrimers, carbon nanomaterials, silica, nanorods, magnetic NPs, and quantum dots (QDs), have been widely used as promising nanotools in biomedicine. Following surface modifications and conjugation with appropriate functional groups, these nanomaterials can be successfully used in aptasensing. Advanced biological assays can use Apts immobilized on QD surfaces through physical interaction and chemical bonding. Accordingly, modern QD aptasensing platforms rely on interactions between QDs, Apts, and targets to detect them. QD‐Apt conjugates can be used to directly detect prostate, ovarian, colorectal, and lung cancers or simultaneously detect biomarkers associated with these malignancies. Tenascin‐C, mucin 1, prostate‐specific antigen, prostate‐specific membrane antigen, nucleolin, growth factors, and exosomes are among the cancer biomarkers that can be sensitively detected using such bioconjugates. Furthermore, Apt‐conjugated QDs have shown great potential for controlling bacterial infections such as Bacillus thuringiensis, Pseudomonas aeruginosa, Escherichia coli, Acinetobacter baumannii, Campylobacter jejuni, Staphylococcus aureus, and Salmonella typhimurium. This comprehensive review discusses recent advancements in the design of QD‐Apt bioconjugates and their applications in cancer and bacterial theranostics.