Association of polymorphisms in TLR3 and TLR7 genes with susceptibility to COVID-19 among Iranian population: a retrospective case-control study.

Background and Objectives: Host genetic changes like single nucleotide polymorphisms (SNPs) are one of the main factors influencing susceptibility to viral infectious diseases. This study aimed to investigate the association between the host SNP of Toll-Like Receptor3 (TLR3) and Toll-Like Receptor7 (TLR7) genes involved in the immune system and susceptibility to COVID-19 in a sample of the Iranian population. Materials and Methods: This retrospective case-control study evaluated 244 hospitalized COVID-19 patients as the case group and 156 suspected COVID-19 patients with mild signs as the control group. The genomic DNA of patients was genotyped for TLR7 (rs179008 and rs179009) and TLR3 (rs3775291 and rs3775296) SNPs using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Results: A significant association between rs179008 SNP in the TLR7 gene and the susceptibility of COVID-19 was found between case and control groups. The AT genotype (Heterozygous) of TLR7 rs179008 A>T polymorphism showed a significant association with a 2.261-fold increased odds of COVID-19 (P=0.003; adjusted OR: 2.261; 99% CI: 1.117-4.575). In addition, a significant association between TC genotype of TLR7 rs179009 T>C polymorphism and increased odds of COVID-19 (P<0.0001; adjusted OR: 6.818; 99% CI: 3.149-14.134) were determined. The polymorphism frequency of TLR3 rs3775291 and rs3775296 genotypes were not significantly different between the case and control groups (P> 0.004167). Conclusion: SNPs in TLR7 rs179008 and rs179009 genotypes are considered host genetic factors that could be influenced individual susceptibility to COVID-19. The SNPs in TLR3 (rs3775296 and rs3775291) showed no significant association with COVID-19 in Iranian population.

Using ChatGPT to predict the future of personalized medicine.

Personalized medicine is a novel frontier in health care that is based on each person's unique genetic makeup. It represents an exciting opportunity to improve the future of individualized health care for all individuals. Pharmacogenomics, as the main part of personalized medicine, aims to optimize and create a more targeted treatment approach based on genetic variations in drug response. It is predicted that future treatments will be algorithm-based instead of evidence-based that will consider a patient's genetic, transcriptomic, proteomic, epigenetic, and lifestyle factors resulting in individualized medication. A generative pretrained transformer (GPT) is an artificial intelligence (AI) tool that generates language resembling human-like writing enabling users to engage in a manner that is practically identical to speaking with a human being. GPT's predictive algorithms can respond to questions that have never been addressed. Chat Generative Pretrained Transformer (ChatGPT) is an AI chatbot's advanced with conversational capabilities. In the present study, questions were asked from ChatGPT about the future of personalized medicine and pharmacogenomics. ChatGPT predicted both to be a promising approach with a bright future that holds great promises in improving patient outcomes and transforming the field of medicine. But it still has several limitations that need to be solved.

Upfront DPYD Genotype-Guided Treatment for Fluoropyrimidine-Based Chemotherapy in Advanced and Metastatic Colorectal Cancer: A Cost-Effectiveness Analysis.

OBJECTIVES: Fluoropyrimidines are the most widely used chemotherapy drugs for advanced and metastatic colorectal cancer (CRC). Individuals with certain DPYD gene variants are exposed to an increased risk of severe fluoropyrimidine-related toxicities. This study aimed to evaluate the cost-effectiveness of preemptive DPYD genotyping to guide fluoropyrimidine therapy in patients with advanced or metastatic CRC. METHODS: Overall survival of DPYD wild-type patients who received a standard dose and variant carriers treated with a reduced dose were analyzed by parametric survival models. A decision tree and a partitioned survival analysis model with a lifetime horizon were designed, taking the Iranian healthcare perspective. Input parameters were extracted from the literature or expert opinion. To address parameter uncertainty, scenario and sensitivity analyses were also performed. RESULTS: Compared with no screening, the genotype-guided treatment strategy was cost-saving ($41.7). Nevertheless, due to a possible reduction in the survival of patients receiving reduced-dose regimens, it was associated with fewer quality-adjusted life-years (9.45 vs 9.28). In sensitivity analyses, the prevalence of DPYD variants had the most significant impact on the incremental cost-effectiveness ratio. The genotyping strategy would remain cost-saving, as long as the genotyping cost is < $49 per test. In a scenario in which we assumed equal efficacy for the 2 strategies, genotyping was the dominant strategy, associated with less costs (∼$1) and more quality-adjusted life-years (0.1292). CONCLUSIONS: DPYD genotyping to guide fluoropyrimidine treatment in patients with advanced or metastatic CRC is cost-saving from the perspective of the Iranian health system.

Association of ABCC8 gene variants with response to sulfonylurea in type 2 diabetes mellitus.

Background: Diabetes mellitus (DM) is associated with high blood glucose levels and sulfonylureas (SFUs) are one of the treatment options for DM. SFUs bind to sulfonylurea-1 receptor (SUR1), which is encoded by the ABCC8 gene and leads to blood glucose reduction. Genetic variants like rs757110 and rs1799854 of ABCC8 can influence the response to the drug's efficiency. Therefore, this study aimed to investigate the association between the ABCC8 rs757110 and rs1799854 genetic variants and response to SFUs treatment. Methods: Totally, 61 DM patients with SFUs treatment were included. Baseline characteristics of the patients were recorded and 5 ml of blood was taken from each patient. After DNA extraction, a sequence containing rs757110 and rs1799854 was synthesized by the PCR method, and the PCR products were used for Sanger sequencing. Results: Frequencies of GG, GA, and AA genotypes of rs1799854 variant was 12 (40%), 14 (46.7%), and 4 (13.3%), and the frequencies of CC, AC, and AA genotypes for rs757110 variant was 3 (9.7%), 5 (16.1%) and 23 (74.2%) in, respectively. Patients with different genotypes had the same age, BMI (body mass index), initial FBS (Fasting blood sugar), initial HbA1c, treatment duration, gender and history of smoking, alcohol consumption, and exercise. There was no significant difference in FBS and HbA1c changes after SFUs treatment between patients with rs757110 variant (p = 0.39 for FBS and p = 0.76 for HbA1c) and rs1799854 (p = 0.24 for FBS and p = 0.36 for HbA1c). Conclusion: The rs1799854 and rs757110 variants of the ABCC8 gene had no significant influence on response to SFUs treatment.

Haplotypic variants of COVID-19 related genes are associated with blood pressure and metabolites levels.

The genetic association of coronavirus disease 2019 (COVID-19) with its complications has not been fully understood. This study aimed to identify variants and haplotypes of candidate genes implicated in COVID-19 related traits by combining the literature review and pathway analysis. To explore such genes, the protein-protein interactions and relevant pathways of COVID-19-associated genes were assessed. A number of variants on candidate genes were identified from Genome-wide association studies (GWASs) which were associated with COVID-19 related traits (p ˂ 10-6 ). Haplotypic blocks were assessed using haplotypic structures among the 1000 Genomes Project (r2 ≥ 0.8, D' ≥ 0.8). Further functional analyses were performed on the selected variants. The results demonstrated that a group of variants in ACE and AGT genes were significantly correlated with COVID-19 related traits. Three haplotypes were identified to be involved in the blood metabolites levels and the development of blood pressure. Functional analyses revealed that most GWAS index variants were expression quantitative trait loci and had transcription factor binding sites, exonic splicing enhancers or silencer activities. Furthermore, the proxy haplotype variants, rs4316, rs4353, rs4359, and three variants, namely rs2493133, rs2478543, and rs5051, were associated with blood metabolite and systolic blood pressure, respectively. These variants exerted more regulatory effects compared with other GWAS variants. The present study indicates that the genetic variants and candidate haplotypes of COVID-19 related genes are associated with blood pressure and blood metabolites. However, further observational studies are warranted to confirm these results.

COVID-19 anti-vaccine attitude and hesitancy.

High vaccination rates are required around the world to create herd immunity and terminate the current COVID-19 pandemic growth. With the steady rise in COVID-19 vaccine supplies, hesitancy and rejection to be vaccinated has become a problem worldwide for large vaccine coverage. Understanding the causes of vaccine avoidance or hesitancy can help to increase vaccination intentions in the general population. A number of factors contributed to increasing hesitancy. Some causes of COVID-19 vaccine hesitancy include anti-vaccine myths and confusing messages about some severe side effects of few vaccines, confusion over protection levels, poor health literacy (lack of accurate knowledge about vaccines and virus), deficient legal liability from the vaccine manufacturers, political and economic intentions, mistrust and suspicion of medical companies, concern of efficacy against to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants, safety concerns (elderly, people with preexisting comorbidities) and some socio-demographic factors. Urgent interventions and policies targeting the corresponding factors are needed. Recognizing obstacles to vaccine uptake helps in the development of effective solutions to solve them. Evidence-based and behaviorally guided approaches should be used to achieve high acceptance and uptake. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-022-01018-y.

A scoping review on patient heterogeneity in economic evaluations of precision medicine based on basket trials.

INTRODUCTION: Considerable challenges in the economic evaluation of precision medicines have been mentioned in previous studies. However, they have not addressed how an economic assessment would be conducted based on basket trials (novel studies for evaluation of precision medicine effects) in which the included populations have specific biomarkers and various cancers. Since basket trial populations have remarkable heterogeneity, this study aims to investigate the concept of heterogeneity and specific method(s) for considering it in economic evaluations through guidelines and studies that could be applicable in economic evaluation based on basket trials. AREA COVERED: We searched PubMed, Web of Science, Scopus, Google Scholar, and Google to find studies and pharmacoeconomics guidelines. The inclusion criteria included subjects of patient heterogeneity and suggested explicit method(s). Thirty-nine guidelines and 43 studies were included and evaluated. None of these materials mentioned disease types in a target population as a factor causing heterogeneity. Moreover, in economic evaluations, patient heterogeneity has been considered with four general approaches subgroup analysis, individual-based models, sensitivity analysis, and regression models. EXPERT OPINION: Type of disease is not considered a contributing factor in population heterogeneity, and the probable appropriate method for this issue could be individual-based models.

VDR gene polymorphisms are associated with the increased susceptibility to COVID-19 among iranian population: A case-control study.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but the pathogenesis is unclear. Host genetic background is one of the main factors influencing the patients' susceptibility to several viral infectious diseases. This study aimed to investigate the association between host genetic polymorphisms of two genes, including vitamin D receptor (VDR) and vitamin D binding protein (DBP), and susceptibility to COVID-19 in a sample of the Iranian population. This case-control study enrolled 188 hospitalized COVID-19 patients as the case group and 218 suspected COVID-19 patients with mild signs as the control group. The VDR (rs7975232, rs731236 and rs2228570) and DBP (rs7041) gene single nucleotide polymorphisms (SNPs) were genotyped by Polymerase Chain Reaction Restriction - Fragment Length Polymorphism (PCR-RFLP) method. A significant association between rs2228570 SNP in the VDR gene and the susceptibility of COVID-19 was found between case and control groups. The CT genotype (Heterozygous) of rs2228570 C > T polymorphism showed significant association with a 3.088 fold increased odds of COVID-19 (p < .0001; adjusted OR: 3.088; 95% CI: 1.902-5.012). In addition, a significant association between CC genotype of rs2228570 CT polymorphism and increased odds of COVID-19 in male and female groups (p = .001; adjusted OR: 3.125; 95% CI: 1.630-5.991 and p = .002; adjusted OR: 3.071; 95% CI: 1.485-6.354 respectively) were determined. Our results revealed no significant differences in the frequency of genotype and allele of VDR (rs7975232 and rs731236) and DBP (rs7041) between SARS-CoV-2-infected patients and controls (p > .05). Our results showed that polymorphism of VDR (rs2228570) probably could influence individual susceptibility to COVID-19. The polymorphisms of VDR (rs7975232 and rs731236) and DBP (rs7041) were not associated with SARS-CoV-2 infection susceptibility.

The vitamin D receptor gene variants, ApaI, TaqI, BsmI, and FokI in diabetic foot ulcer and their association with oxidative stress.

INTRODUCTION: To date, numerous disorders have been linked to vitamin D deficiency. Several lines of evidence indicate a relationship between vitamin D deficiency and the risk of developing type 2 diabetes. It has been postulated that vitamin D may influence insulin activity, which can predispose individuals to develop type 2 diabetes. MATERIALS AND METHODS: In this case-control study, 262 patients with definite type 2 diabetes were enrolled, considering whether they were being affected by diabetic foot ulcers or not. The plasma levels of vitamin D and homocysteine were measured using ELISA, and the PCR-RFLP technique was utilized to determine allele and genotype frequencies. The antioxidant capacity of plasma samples of diabetic patients was analyzed using the thiobarbituric acid reactive substance (TBARS) and ferric reducing ability of plasma (FRAP) assays. RESULTS: The obtained results demonstrated no significant difference in the frequency of TaqI and BsmI polymorphisms between the case and control groups. However, the frequency of genotypes and alleles of the ApaI polymorphism in the VDR gene significantly differed between the case and control groups. A significant correlation was found between ApaI polymorphism and oxidative stress, as patients with the GG genotype had lower levels of TBARS than those with other genotypes. Furthermore, in the case group, patients with the CC genotype of BsmI showed a significant decrease in TBARS levels. DISCUSSION: It seems that the plasma levels of vitamin D do not differ between patients with or without diabetic foot ulcers; however, the presence of some VDR gene polymorphisms is thought to be involved in the development of diabetic foot ulcers via increasing oxidative stress.

Breast cancer in the era of precision medicine.

Breast cancer is a heterogeneous disorder with different molecular subtypes and biological characteristics for which there are diverse therapeutic approaches and clinical outcomes specific to any molecular subtype. It is a global health concern due to a lack of efficient therapy regimens that might be used for all disease subtypes. Therefore, treatment customization for each patient depending on molecular characteristics should be considered. Precision medicine for breast cancer is an approach to diagnosis, treatment, and prevention of the disease that takes into consideration the patient's genetic makeup. Precision medicine provides the promise of highly individualized treatment, in which each individual breast cancer patient receives the most appropriate diagnostics and targeted therapies based on the genetic profile of cancer. The knowledge about the molecular features and development of breast cancer treatment approaches has increased, which led to the development of new targeted therapeutics. Tumor genomic profiling is the standard of care for breast cancer that could contribute to taking steps to better management of malignancies. It holds great promise for accurate prognostication, prediction of response to common systemic therapies, and individualized monitoring of the disease. The emergence of targeted treatment has significantly enhanced the survival of patients with breast cancer and contributed to reducing the economic costs of the health system. In this review, we summarized the therapeutic approaches associated with the molecular classification of breast cancer to help the best treatment selection specific to the target patient.

Precision medicine journey through omics approach.

It has been well established that understanding the underlying heterogeneity of numerous complex disease process needs new strategies that present in precision medicine for prediction, prevention and personalized treatment strategies. This approach must be tailored for each individual's unique omics that lead to personalized management of disease. The correlation between different omics data should be considered in precision medicine approach. The interaction provides a hypothesis which is called domino effect in the present minireview. Here we review the various potentials of omics data including genomics, transcriptomics, proteomics, metabolomics, pharmacogenomics. We comprehensively summarize the impact of omics data and its major role in precision medicine and provide a description about the domino effect on the pathophysiology of diseases. Each constituent of the omics data typically provides different information in associated with disease. Current research, although inadequate, clearly indicate that the information of omics data can be applicable in the concept of precision medicine. Integration of different omics data type in domino effect hypothesis can explain the causative changes of disease as it is discussed in the system biology too. While most existing studies investigate the omics data separately, data integration is needed on the horizon of precision medicine by using machine learning.

Genomic medicine on the frontier of precision medicine.

Genomic medicine has created a great deal of hope since the completion of the Human Genome Project (HGP). Genomic medicine promises disease prevention and early diagnosis in the context of precision medicine. Precision medicine as a scientific discipline has introduced as an evolution in medicine. The rapid growth of high-development technologies permits the assessment of biological systems. Study of the integrated profiles of omics, such as genome, transcriptome, proteome and other omics information lead to significant advances in personalized and precision medicine. In the context of precision medicine, pharmacogenomics can play an important role in order to discriminate responders and non-responders to medications and avoiding toxicity and achieving the optimum dose. So precision medicine in accordance with genomic medicine will transform medicine from conventional evidence-based medicine in the diagnosis and treatment towards precision based-medicine. In this review, we have summarized the related issues for genomic medicine and precision medicine.

Artificial intelligence perspective in the future of endocrine diseases.

In recent years, artificial intelligence (AI) shows promising results in the diagnosis, prediction, and management of diseases. The move from handwritten medical notes to electronic health records and a huge number of digital data commenced in the era of big data in medicine. AI can improve physician performance and help better clinical decision making which is called augmented intelligence. The methods applied in the research of AI and endocrinology include machine learning, artificial neural networks, and natural language processing. Current research in AI technology is making major efforts to improve decision support systems for patient use. One of the best-known applications of AI in endocrinology was seen in diabetes management, which includes prediction, diagnosis of diabetes complications (measuring microalbuminuria, retinopathy), and glycemic control. AI-related technologies are being found to assist in the diagnosis of other endocrine diseases such as thyroid cancer and osteoporosis. This review attempts to provide insight for the development of prospective for AI with a focus on endocrinology.

Influence of cytotoxic T lymphocyte antigen 4 genetic variants on acute rejection in kidney transplant patients: precision medicine perspective.

Background: The most effective and common treatment for end-stage renal disease is kidney transplantation.The personalized approach to kidney transplantation, which utilizes precision medicine principles, determines distinctive genomics characteristics of candidates/recipients that must be taken into account. Cytotoxic T lymphocyte associated protein 4 (CTLA4) may be a suitable candidate gene for studying allograft rejection. The aim of this study was to understand whether we can consider two common variants of the CTLA4 gene as a risk factor of transplant rejection in a group of Iranian population. Methods: Totally, 169 kidney transplant recipients, including acute rejections (N=39) and non-rejection (N=130) groups who underwent transplantation were included in this study. The genotyping of rs5742909 (-318C/T) and rs231775 (+49A/G) variants of the CTLA4 gene were performed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique. Results: The AG genotype frequency of rs231775 variant was the same in both patients with and without a history of rejection while, none of those groups had homozygote genotype. In rs5742909, both CT and TT frequencies of patients with rejected transplant were lower than patients with a normal outcome. Conclusions: The results of the presented study suggest that rs231775 and rs5742909 of CTLA4 genetic variants are not linked to acute rejection who underwent kidney transplantation. So, these variants cannot be considered as risk factors of acute allograft rejection in a group of Iranian renal transplantation recipients. However, the transplantation precision medicine may be an important area for the improvement of patients outcome as the precision medicine has already entered clinical practice in kidney transplantation.

Effects of the TCF7L2 and KCNQ1 common variant on sulfonylurea response in type 2 diabetes mellitus patients: a preliminary pharmacogenetic study.

Background: Type 2 diabetes mellitus (T2DM) is a common chronic condition characterized by high blood glucose levels which is caused by genetic and environmental factors. Currently, pharmacogenomics (PGx) is anticipated to enable the development of personalized treatment in a wide range of health issues. Sulfonylureas (SFUs) are among the oral anti-diabetic drugs that are very popular due to their low cost. Genetic variants in transcription factor 7 like 2 (TCF7L2) and potassium voltage-gated channel subfamily Q member 1 (KCNQ1) have been reported for altered therapeutic response to sulfonylurea. The aim of the present study is to evaluate any association between common genetic variant of the TCF7L2 and KCNQ1 (rs7903146 and rs2237892, respectively) and the response to sulfonylurea in a group of Iranian patients for the first time. Methods: Genotyping was carried out in 30 T2DM patients who received sulfonylurea treatment for more than two months in addition to previous medication using the Sanger sequencing method. Results: In 30 T2DM patients who received SFUs treatment, 60%, 33.3% and 6.7% had CC, CT and TT genotypes, respectively. After treatment, adjusted fasting blood sugar (FBS) mean reduction level in CT and TT carriers was lower than CC carriers. Adjusted hemoglobin A1c (HbA1c) mean reduction level was also lower in CT and TT compared with CC carriers, but, none of these differences were statistically significant. Genotype frequencies of TT, CT and CC genotypes of rs2237892 variant of KCNQ1 gene were 0 (0%), 3 (10%) and 27 (90%) respectively. Patients with CT and CC genotypes of rs2237892 variant had also similar changes in FBS (P=0.200) and HbA1c (P=0.436) after treatment with SFUs. Conclusions: Genotypes of TCF7L2 and KCNQ1 common variant did not show any impact on the treatment response among T2DM patients receiving SFUs.

Diabetes and COVID-19: a bitter nightmare.

Initial studies found a bidirectional interaction between coronavirus disease 2019 (COVID-19) and diabetes. In this article we intend to review the association and consequences of COVID-19 in the future of diabetes in case of prevalence and treatment. There is substantial evidence that COVID-19 may result in the new-onset of hyperglycaemia. Therefore, it seems that COVID-19 will change the predictions for the prevalence of diabetes. Moreover, it raises numerous challenges for the clinical management of diabetes. In COVID-19 patients, new-onset hyperglycemia is associated with a poor prognosis. Diabetes mellitus and other comorbidities should be strictly controlled. But, with the emergence of COVID-19 disease, the future of diabetes mellitus in terms of prevalence and treatment will change and policymakers should consider developing new management strategies in this regard. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-022-00994-5.

Vascular Endothelial Growth Factor Genetic Variant Is Associated with in-Stent Restenosis after Percutaneous Coronary Intervention.

Background: In-stent restenosis (ISR) is an inevitable complication of percutaneous coronary intervention, with genetic factors thought to play a role in its pathogenesis. The vascular endothelial growth factor (VEGF) gene can have an inhibitory effect on ISR development. Accordingly, in the present study, we investigated the role of -2549 VEGF (insertion/deletion [I/D]) variants in ISR formation. Methods: Patients with ISR (ISR+) (n=53) and patients without ISR (ISR-) (n=67) were enrolled in this case-control study based on follow-up angiography 1 year after percutaneous coronary intervention between 2019 and 2020. The clinical characteristics of the patients were evaluated, and the frequencies of the alleles and genotypes of -2549 VEGF (I/D) variants were determined using polymerase chain reaction. The χ2 test was performed for the calculation of genotypes and alleles. A P value of less than 0.05 was considered the level of significance. Results: This study recruited 120 individuals at a mean age of 61.43±8.91 years in the ISR+ group and 62.09±7.94 years in the ISR- group. Women and men, respectively, comprised 26.4% and 73.6% of the ISR+ group and 43.3% and 56.7% of the ISR- group. A significant association was observed between the VEGF -2549 genotype frequency and ISR. The frequency of the insertion/insertion (I/I) allele was significantly higher in the ISR+ group than in the ISR- group, while the frequency of the D/D allele was higher in the latter group. Conclusion: Regarding ISR development, the I/I allele may be a risk allele and the D/D allele a protective allele.

The role of the PPARG (Pro12Ala) common genetic variant on type 2 diabetes mellitus risk.

BACKGROUND: Type 2 diabetes (T2DM) prevalence has been rapidly increasing in the last decades. T2DM pathogenesis is related to insulin resistance and beta-cell dysfunction. Peroxisome proliferator-activated receptor gamma (PPARG) is concerned about T2DM risk through the involvement in adipocyte differentiation and energy homeostasis. The present study aimed to find the risk associated with a common genetic variant (Pro12Ala) of the PPARG gene in the development of T2DM in a group of the Iranian population. METHODS: Totally, 149 patients with T2DM and 96 healthy individuals were recruited in this case-control study. The genotyping of the genetic variant was carried out using the polymerase chain reaction (PCR) followed by Sanger sequencing. RESULTS: No significant difference is observed between the CG and GG genotypes frequency of the PPARG variant (P = 0.17) in T2DM patient and the control groups. Furthermore, the frequency of the G allele was similar between case and control groups. The Pro12Ala variant may decrease the risk of diabetic retinopathy (DR) which was not statistically significant. Furthermore, the Pro12Ala variant caused a 27% increase in the risk of diabetes nephropathy (DN) among patients with T2DM but was not significant. CONCLUSIONS: Our findings showed that the PPARG variant could not impact on T2DM development and its complications.

A systematic review of miRNAs as biomarkers in osteoporosis disease.

BACKGROUND: Osteoporosis is often considered to be a disease of the elderly, which is characterized by two characteristics: low bone mineral density (BMD) and increased risk of fracture. MicroRNAs (miRNAs) have been reported to play a potential role in bone formation and resorption, bone remodeling, bone homeostasis regulation, and bone cell differentiation. Therefore, altered expression of different miRNAs may impact the pathology of bone diseases such as osteoporosis. A systematic review was conducted to extract all miRNA found to be significantly dys-regulated in the peripheral blood. METHODS: This review was carried out using a systematically search on PubMed, Scopus, Embase, Web of Science (WoS), and Cochrane databases from 1990 to 2018 to explore the diagnostic value of miRNAs as a biomarker in osteoporosis. RESULTS: A total of 31 studies were identified in the systematic review that indicated more than 30 kinds of up-regulated and down-regulated miRNAs in three categories; postmenopausal osteoporosis, postmenopausal osteoporosis with fracture risk, and other types of osteoporosis and fracture risk. CONCLUSION: The collective data presented in this review indicate that miRNAs could serve as biomarkers for the diagnosis (onset) and prognosis (progression of osteoporosis), while the clinical application of these findings has yet to be verified. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40200-021-00873-5.

Pilot study in pharmacogenomic management of empagliflozin in type 2 diabetes mellitus patients.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a metabolic disorder in which the patients with high blood sugar develop insufficient insulin secretion or insulin resistance. The solute carrier family, 5 member 2 (SLC5A2) gene is a member of sodium/glucose transporter family which can reduce heart and kidney problems. The current study aims to look into any association between rs11646054 variant in SLC5A2 gene and the anti-diabetic efficacy and safety of empagliflozin. METHODS: 14 T2DM who failed to respond to previous treatments, empagliflozin 10 mg was added for 6 months. Genotyping of the rs11646054 variant of SLC5A2 gene was performed by polymerase chain reaction (PCR) followed by Sanger sequencing. RESULTS: Although hemoglobin A1c (HbA1c) and low-density lipoprotein (LDL) were not significantly different, but the mean fasting blood sugar (FBS), 2-h post prandial (2hpp), albumin-to-creatinine ratio (ACR), and total cholesterol (TC) were significantly decreased after 6 months empagliflozin treatment. There was a significant difference in the mean final reductions in FBS level among genotypes. It's important to mention that those who were GG homozygotes had a tendency to have more decrements. CONCLUSIONS: The study results indicate that effects of variation in SLC5A2 (rs11646054) on the clinical efficacy of empagliflozin were negligible.