Clinical Implications of Krüpple-like Transcription Factor KLF-14 and Certain Micro-RNA (miR-27a, miR-196a2, miR-423) Gene Variations as a Risk Factor in the Genetic Predisposition to PCOS

Potential Association of The Pathogenic Kruppel-like Factor 14 (KLF14) and Adiponectin (ADIPOQ) SNVs with Susceptibility to T2DM

AIM

To evaluate the associations of the pathogenic variants in Kruppel-like Factor 14 (KLF 14) and Adiponectin (ADIPOQ) with susceptibility to type 2 diabetes mellitus (T2DM).

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a pandemic metabolic disease characterized by increased blood sugar and caused by resistance to insulin in peripheral tissues and damage to pancreatic beta cells. Kruppel-like Factor 14 (KLF-14) is proposed to be a regulator of metabolic diseases, such as diabetes mellitus (DM) and obesity. Adiponectin (ADIPOQ) is an adipocytokine produced by the adipocytes and other tissues and was reported to be involved in T2DM.

OBJECTIVES

To study the possible association of the KLF-14 rs972283 and ADIPOQ-rs266729 with the risk of T2DM in the Saudi population.

METHODS

We have evaluated the association of KLF-14 rs972283 C>T and ADIPOQ-rs266729 C>G SNV with the risk to T2D in the Saudi population using the Amplification Refractory Mutation System PCR (ARMS-PCR), and blood biochemistry analysis. For the KLF-14 rs972283 C>T SNV we included 115 cases and 116 healthy controls, and ADIPOQ-rs266729 C>G SNV, 103 cases and 104 healthy controls were included.

RESULTS

Results indicated that the KLF-14 rs972283 GA genotype and A allele were associated with T2D risk with OR=2.14, p-value= 0.014 and OR=1.99, p-value=0.0003, respectively. Results also ADIPOQ-rs266729 CG genotype and C allele were associated with an elevated T2D risk with an OR=2.53, p=0.003 and OR=1.66, p-value =0.012, respectively.

CONCLUSION

We conclude that SNVs in KLF-14 and ADIPOQ are potential loci for T2D risk. Future large-scale studies to verify these findings are recommended. These results need further verifications in protein functional and large-scale case control studies before being introduced for genetic testing.

Progress of the application clinical prediction model in polycystic ovary syndrome

Clinical prediction models play an important role in the field of medicine. These can help predict the probability of an individual suffering from disease, complications, and treatment outcomes by applying specific methodologies. Polycystic ovary syndrome (PCOS) is a common disease with a high incidence rate, huge heterogeneity, short- and long-term complications, and complex treatments. In this systematic review study, we reviewed the progress of clinical prediction models in PCOS patients, including diagnosis and prediction models for PCOS complications and treatment outcomes. We aimed to provide ideas for medical researchers and clues for the management of PCOS. In the future, models with poor accuracy can be greatly improved by adding well-known parameters and validations, which will further expand our understanding of PCOS in terms of precision medicine. By developing a series of predictive models, we can make the definition of PCOS more accurate, which can improve the diagnosis of PCOS and reduce the likelihood of false positives and false negatives. It will also help discover complications earlier and treatment outcomes being known earlier, which can result in better outcomes for women with PCOS.

Potential Impact of PI3K-AKT Signaling Pathway Genes, KLF-14, MDM4, miRNAs 27a, miRNA-196a Genetic Alterations in the Predisposition and Progression of Breast Cancer Patients

Genome-wide association studies have reported link between SNPs and risk of breast cancer. This study investigated the association of the selected gene variants by predicting them as possible target genes. Molecular technique advances with the availability of whole-exome sequencing (WES), now offer opportunities for simultaneous investigations of many genes. The experimental protocol for PI3K, AKT-1, KLF-14, MDM4, miRNAs 27a, and miR-196a genotyping was done by ARMS-PCR and sanger sequencing. The novel and known gene variants were studied by Whole-exome sequencing using Illumina NovaSeq 6000 platform. This case control study reports significant association between BC patients, healthy controls with the polymorphic variants of PI3K C > T, AKT-1 G > A KLF 14 C > T, MDM4 A > G, miR-27a A > G, miR-196a-2 C > T genes (p < 0.05). MDM4 A > G genotypes were strongly associated with BC predisposition with OR 2.08 & 2.15, p < 0.05) in codominant and dominant models respectively. MDM4 A allele show the same effective (OR1.76, p < 0.05) whereas it remains protective in recessive model for BC risk. AKT1G > A genotypes were strongly associated with the BC susceptibility in all genetic models whereas PI3K C > T genotypes were associated with breast cancer predisposition in recessive model OR 6.96. Polymorphic variants of KLF-14 A > G, MDM4G > A, MiR-27aA >G, miR-196a-C > T were strongly associated with stage, tamoxifen treatment. Risk variants have been reported by whole exome sequencing in our BC patients. It was concluded that a strong association between the PI3K-AKT signaling pathway gene variants with the breast cancer susceptibility and progression. Similarly, KLF 14-AA, MDM4-GA, miR27a-GG and miR-196a-CT gene variants were associated with the higher risk probability of BC and were strongly correlated with staging of the BC patients. This study also reported Low, novel, and intermediate-genetic-risk variants of PI3K, AKT-1, MDM4G & KLF-14 by utilizing whole-exome sequencing. These variants should be further investigated in larger cohorts' studies.