Association analysis between the VDR gene variants and type 2 diabetes.

Background: Type 2 diabetes mellitus (T2DM) is recognized as a complex metabolic which has affected the lives of millions of people around the world. Vitamin D receptor (VDR) gene polymorphisms have been suggested to be a vital contributor to the development of T2DM. However, the association between VDR gene polymorphisms and T2DM remains controversial. We have investigated the association between two VDR gene polymorphisms (rs731236 and rs1544410) and T2DM in an Iranian population. Methods: A total of 148 T2DM patients and 100 normal controls were recruited in this study. We used polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis to perform genotyping. Results: The results of the present research revealed that the frequency of the rs731236 C allele was significantly higher in T2DM patients than in normal controls (p = 0.044). The CC genotype of rs731236 was connected with an increased risk of T2DM (OR = 2.85, 95% CI = 1.06-7.69, p = 0.039). However, no significant difference in the frequency of the rs1544410 C allele between T2DM patients and normal controls was observed (p = 0.918). Conclusion: Our findings were suggestive of the rs731236 polymorphism of the VDR as a risk factor for developing T2DM in the Iranian population, while rs1544410 polymorphism may not be associated with T2DM susceptibility. Further research is needed to approve these findings in other populations and to clarify the underlying mechanisms involved in such an association. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-023-01323-0.

Symptom Prediction and Mortality Risk Calculation for COVID-19 Using Machine Learning.

Background: Early prediction of symptoms and mortality risks for COVID-19 patients would improve healthcare outcomes, allow for the appropriate distribution of healthcare resources, reduce healthcare costs, aid in vaccine prioritization and self-isolation strategies, and thus reduce the prevalence of the disease. Such publicly accessible prediction models are lacking, however. Methods: Based on a comprehensive evaluation of existing machine learning (ML) methods, we created two models based solely on the age, gender, and medical histories of 23,749 hospital-confirmed COVID-19 patients from February to September 2020: a symptom prediction model (SPM) and a mortality prediction model (MPM). The SPM predicts 12 symptom groups for each patient: respiratory distress, consciousness disorders, chest pain, paresis or paralysis, cough, fever or chill, gastrointestinal symptoms, sore throat, headache, vertigo, loss of smell or taste, and muscular pain or fatigue. The MPM predicts the death of COVID-19-positive individuals. Results: The SPM yielded ROC-AUCs of 0.53-0.78 for symptoms. The most accurate prediction was for consciousness disorders at a sensitivity of 74% and a specificity of 70%. 2,440 deaths were observed in the study population. MPM had a ROC-AUC of 0.79 and could predict mortality with a sensitivity of 75% and a specificity of 70%. About 90% of deaths occurred in the top 21 percentile of risk groups. To allow patients and clinicians to use these models easily, we created a freely accessible online interface at www.aicovid.net. Conclusion: The ML models predict COVID-19-related symptoms and mortality using information that is readily available to patients as well as clinicians. Thus, both can rapidly estimate the severity of the disease, allowing shared and better healthcare decisions with regard to hospitalization, self-isolation strategy, and COVID-19 vaccine prioritization in the coming months.

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU.

Rationale: Given the expanding number of COVID-19 cases and the potential for new waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies. Objectives: Early prediction of mortality using machine learning based on typical laboratory results and clinical data registered on the day of ICU admission. Methods: We retrospectively studied 797 patients diagnosed with COVID-19 in Iran and the United Kingdom (U.K.). To find parameters with the highest predictive values, Kolmogorov-Smirnov and Pearson chi-squared tests were used. Several machine learning algorithms, including Random Forest (RF), logistic regression, gradient boosting classifier, support vector machine classifier, and artificial neural network algorithms were utilized to build classification models. The impact of each marker on the RF model predictions was studied by implementing the local interpretable model-agnostic explanation technique (LIME-SP). Results: Among 66 documented parameters, 15 factors with the highest predictive values were identified as follows: gender, age, blood urea nitrogen (BUN), creatinine, international normalized ratio (INR), albumin, mean corpuscular volume (MCV), white blood cell count, segmented neutrophil count, lymphocyte count, red cell distribution width (RDW), and mean cell hemoglobin (MCH) along with a history of neurological, cardiovascular, and respiratory disorders. Our RF model can predict patient outcomes with a sensitivity of 70% and a specificity of 75%. The performance of the models was confirmed by blindly testing the models in an external dataset. Conclusions: Using two independent patient datasets, we designed a machine-learning-based model that could predict the risk of mortality from severe COVID-19 with high accuracy. The most decisive variables in our model were increased levels of BUN, lowered albumin levels, increased creatinine, INR, and RDW, along with gender and age. Considering the importance of early triage decisions, this model can be a useful tool in COVID-19 ICU decision-making.

PPARG (Pro12Ala) genetic variant and risk of T2DM: a systematic review and meta-analysis.

Type 2 diabetes mellitus (T2DM) is a complex disease caused by the interaction between genetic and environmental factors. A growing number of evidence suggests that the peroxisome proliferator-activated receptor gamma (PPARG) gene plays a major role in T2DM development. Meta-analysis of genetic association studies is an efficient tool to gain a better understanding of multifactorial diseases and potentially to provide valuable insights into gene-disease interactions. The present study was focused on assessing the association between Pro12Ala variation in the PPARG and T2DM risk through a comprehensive meta-analysis. We searched PubMed, WoS, Embase, Scopus and ProQuest from 1990 to 2017. The fixed-effect or random-effect model was used to evaluate the pooled odds ratios (ORs) and 95% confidence intervals (CIs) depending on the heterogeneity among studies. The sources of heterogeneity and publication bias among the included studies were assessed using I2 statistics and Egger's tests. A total of 73 studies, involving 62,250 cases and 69,613 controls were included. The results showed that the minor allele (G) of the rs1801282 variant was associated with the decreased risk of T2DM under different genetic models. Moreover, the protective effect of minor allele was detected to be significantly more in some ethnicities including the European (18%), East Asian (20%), and South East Asian (18%). And the reduction of T2DM risk in Ala12 carriers was stronger in individuals from North Europe rather than Central and South Europe. Our findings indicated that the rs1801282 variant may contribute to decrease of T2DM susceptibility in different ancestries.

Activation and Inactivation of Nicotinic Receptnors in the Dorsal Hippocampal Region Restored Negative Effects of Total (TSD) and REM Sleep Deprivation (RSD) on Memory Acquisition, Locomotor Activity and Pain Perception.

Sleep deprivation (SD) is a common issue in today's society. Sleep is essential for proper cognitive functions, including learning and memory. Furthermore, sleep disorders can alter pain information processing. Meanwhile, hippocampal nicotinic receptors have a role in modulating pain and memory. The goal of this study is to investigate the effect of dorsal hippocampal (CA1) nicotinic receptors on behavioral changes induced by Total (TSD) and REM Sleep Deprivation (RSD). A modified water box and multi-platform apparatus were used to induce TSD and RSD, respectively. To investigate the interaction between nicotinic receptors and hippocampus-dependent memory, nicotinic receptor agonist (nicotine) or antagonist (mecamylamine) was injected into the CA1 region. The results showed, nicotine at the doses of 0.001 and 0.1 µg/rat and mecamylamine at the doses of 0.01 and 0.1 µg/rat decreased memory acquisition, while both at the doses of 0.01 and 0.1 µg/rat enhanced locomotor activity. Additionally, all doses used for both drugs did not alter pain perception. Also, 24 h TSD or RSD attenuated memory acquisition with no effect on locomotor activity and only TSD induced an analgesic effect. Intra-CA1 administration of subthreshold dose of nicotine (0.0001 µg/rat) and mecamylamine (0.001 µg/rat) did not alter memory acquisition, pain perception and locomotor activity in sham of TSD/RSD rats. Both drugs reversed all behavioral changes induced by TSD. Furthermore, both drugs reversed the effect of RSD on memory acquisition, while only mecamylamine reversed the effect of RSD on locomotor activity. In conclusion, CA1 nicotinic receptors play a significant role in TSD/RSD-induced behavioral changes.

Genetic Polymorphism of Mismatch Repair Genes and Susceptibility to Prostate Cancer.

PURPOSE: Mismatch repair (MMR) is one of the DNA repair systems that correct mispaired bases during DNA replication errors. Polymorphisms in genes can increase susceptibility to the development of prostate cancer (PCa). In this study, we investigated mutL homolog 1 (MLH1) -93G>A (rs1800734) and mutS homolog 3 (MSH3) (rs26279) polymorphisms with the risk of PCa. MATERIALS AND METHODS: In this study of Iranian population, 175 histopathologically confirmed (PCa) patients and 230 benign prostate hyperplasia (BPH) as the controls were recruited. The genotypes of MLH1 and MSH3 were determined by polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP) method. RESULTS: There was no significant difference of MLH1 (P = 0.4) and MSH3 (P?=?0.5) genotype distributions among PCa cases and controls. And also patients with PCa were not significant differences compared to those without in stage of cancer, grade of tumor, perineural invasion, and vascular invasion. CONCLUSION: Our results did not show adequate evidence for any significant association of MLH1 and MSH3 polymorphisms and PCa .

Gut microbiota: a perspective of precision medicine in endocrine disorders.

Gut microbiota composition is unique in every individual, it impacts on organ functions that produce hormones. Gut microbiota composition balance is directly related to our general health status. This continual interaction between gut microbiota and endocrine organs sometimes can be considered as the etiology of diseases such as type 2 diabetes mellitus (T2DM), obesity, osteoporosis, polycystic ovary syndrome (PCOS), and thyroid diseases. Microbiota is introduced for a total collection of microbial organisms in our bodies and microbiome referred for their genome and their collective functions. Near 100 trillion microorganisms live in our body and almost all of them occupy the human gut gastrointestinal tract. Precision medicine can play a crucial role in health maintenance by affecting gut microbiota composition in every individual. It can also develop special treatments specifically for every individual. In this review, we addressed any correlation between gut microbiota and endocrine disorders including T2DM, obesity, PCOS, thyroid disorders and osteoporosis.

The role of 5-HT4 serotonin receptors in the CA1 hippocampal region on memory acquisition impairment induced by total (TSD) and REM sleep deprivation (RSD).

Sleep is a circadian rhythm that is modulated by endogenous circadian clock located in the suprachiasmatic nucleus (SCN). Sleep modulates memory acquisition and promotes memory consolidation. Studies have shown that sleep deprivation (SD) impairs different types of memory including passive avoidance. Furthermore, the hippocampus plays a significant role in modulating passive avoidance memory. On the other hand, 5-HT4 receptors are expressed in the hippocampus and involved in learning and memory processes. In this study, we aimed to investigate the role of CA1 hippocampal 5-HT4 receptors in memory acquisition impairment induced by total sleep deprivation (TSD: 24 h) and REM sleep deprivation (RSD: 24 h). The water box apparatus was used to induce TSD, while multi-platform apparatus was applied to induce RSD. Passive avoidance memory test was also used to evaluate memory acquisition. The results showed that, intra-CA1 pre-training injection of RS67333 (5-HT4 agonist) and RS23597 (5-HT4 antagonist) at the doses of 0.01 and 0.1 µg/rat decreased memory acquisition, but did not alter pain perception and locomotor activity. Furthermore, TSD and RSD decreased memory acquisition; however, only TSD decreased locomotor activity and induced analgesic effect. The sub-threshold doses of RS67333 and RS23597, 0.001 and 0.0001 µg/rat, respectively, reversed the effect of TSD on memory acquisition and locomotor activity. In addition, only RS23597 reversed TSD-induced analgesia. In RSD condition, the subthreshold dose of RS23597 improved RSD-induced memory acquisition deficit. In conclusion, CA1 hippocampal 5-HT4 receptors play an important role in TSD/RSD-induced cognitive alterations.

Association between matrix metaloproteinases 2-1306C/T polymorphism and the risk of coronary artery disease in Iranian population.

BACKGROUND: Coronary Artery Disease (CAD) represents the most important cause of sudden cardiac death. Interaction between genetic and environmental factors, individual susceptibility of the development of CAD is one of the MMP2 genes. Genetic variants' dysfunction of the MMP2 gene associated with the risk of CAD. The aim of the present study is to assess possible association between risk of Coronary Artery Disease and MMP2-1306C/T polymorphism. METHODS: This case-control study contains a total number of 344 subjects, including 215 patients with CAD and 129 of controls. Genomic DNA was isolated from whole blood and genotyping was performed by the Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR- RFLP) method. RESULTS: This study reveals the result that about 3.5% of CAD patients had TT genotype while 30.4% of them had CT genotype. Corresponding figures for subjects without CAD were zero and 52.6% respectively. These differences were statistically significant (P=0.002). Frequencies of T allele among patients with and without CAD were 18.71% and 26.28% respectively (p=0.04). The odds ratio between T allele and CAD was 0.64 (p=0.055). we couldn't trace significant differences among alleles in Gensini score, Gesnsini score's median among patients carried out TT, CT and CC genotypes were 4, 2 and 2 respectively (p=0.3). CONCLUSIONS: Result of this study provides some evidences that the MMP2-1306 polymorphism can be associated with coronary artery disease. Further longitudinal studies including more sample sizes are required to confirm this protective effect.

Genetic Polymorphism of MMP2 Gene and Susceptibility to Prostate Cancer.

BACKGROUND AND AIMS: The polymorphic genetic variants of matrix metalloproteinase (MMPs) can play critical roles in development and progression of cancer. The purpose of this study was to investigate if any association exists between MMP2 -1306/T and risk of prostate cancer (PCa). METHODS: This case-control study comprised a total number of 241 subjects, including 102 patients with PCa and 139 controls with benign prostatic hyperplasia (BPH). MMP2 genotypes were detected by RFLP. RESULTS: There is no significant difference between different genotypes of MMP2 polymorphism and risk of developing PCa (p = 0.08). Although these genotypes increased the risk of developing PCa 79% (CT vs. CC) and 54% (TT vs. CC), none had a significant effect (p = 0.09 and p = 1 respectively). There were no significant differences in genotype frequencies between patients with low and high degrees of PCa (p = 0.4). Therefore, this polymorphism cannot be considered as a protective factor for PCa metastasis. It seems that MMP2 polymorphism has no protective effect on the grading of the tumor (p = 0.8). Our results indicated that MMP2 polymorphism had no role in the vascular invasion of PCa. CONCLUSION: We found no association between MMP2 polymorphism and cancer risk, overall or by grade, stage or age of diagnosis. Finally, there was no association between the different genotypes and PSA plasma levels among cases or controls. Further evaluations with larger samples from our population may illuminate the effects of polymorphisms on PCa risk and thus help early diagnosis, follow-up and prognostic determinations for PCa patients.

Association of polymorphisms at LDLR locus with coronary artery disease independently from lipid profile.

Coronary artery disease (CAD) is the leading cause of mortality in many parts of the world. Genome-wide association studies (GWAS) have identified several genetic variants associated with CAD in Low-density lipoprotein receptor (LDLR) locus. This study was evaluated the possible association of genetic markers at LDLR locus with CAD irrespective to lipid profile and as well as the association of these SNPs with severity of CAD in Iranian population. Sequencing of 2 exons in LDLR gene (Exon 2, 12) and part of intron 30 of SMARCA4 gene include rs1122608, was performed in 170 Iranian patients angiographically confirmed CAD and 104 healthy controls by direct sequencing. Sullivan's scoring system was used for determining the severity of CAD in cases. Our results showed that homozygote genotypes of rs1122608 (P<0.0001), rs4300767 (P<0.005) and rs10417578 (p<0.007) SNPs have strong protective effects on the CAD. In addition, we found that rs1122608 (GT or TT) was at higher risk of three vessel involvement compared to single vessels affecting (P=0.01).

Biased homozygous haplotypes across the human caveolin 1 upstream purine complex in Parkinson's disease.

The alpha-synuclein-caveolin 1 axis is suggested to be of role in the pathogenesis of Parkinson's disease in cell line models. The objective of this study was to analyze the homozygous haplotype compartment of the human caveolin 1 gene upstream purine complex in patients afflicted with Parkinson's disease. This complex was screened in patients with Parkinson's disease (n = 141) and compared with a group of controls (n = 760) using polymerase chain reaction and sequencing. The expression activity of the homozygous haplotypes was then examined using luciferase Dual-Glo system in human neuronal cell line, LAN-5. Six haplotypes were found to be homozygous in the patients, and not in the control pool (Fisher exact p < 1 × 10(-6)). Three of those haplotypes were specific to Parkinson's disease (Fisher exact p < 0.002), and the remaining three overlapped with homozygous haplotypes in Alzheimer's disease and multiple sclerosis (Fisher exact p < 0.002). The disease haplotypes contained motif lengths that were nonexistent in the control homozygous haplotype pool and significantly increased gene expression (p < 9 × 10(-6)). We conclude that skew in the caveolin 1 purine complex homozygous haplotype compartment and an additive effect of those haplotypes may be linked with Parkinson's disease.

Endothelial nitric oxide synthase Glu298Asp polymorphism as a risk factor for prostate cancer.

BACKGROUND: The endothelial form of nitric oxide synthases (eNOS) seems to have an important role in vascular development, maintenance of the vascular tone and tumor growth in human prostate cancer (PC). The purpose of this study was to investigate the association between grade and stage of disease, age of diagnosis, vascular or perineural invasion, pre-diagnostic plasma prostate-specific antigen (PSA) levels, prostate cancer risk and Glu298Asp polymorphism of the eNOS gene.
 METHODS: Ninety-five prostate cancer patients and 111 benign prostate hyperplasia subjects were included. The Glu298Asp polymorphism of the eNOS gene was determined by polymerase chain reaction and restriction fragment length polymorphism 
 RESULTS: The odds ratio (OR) between the GT and GG polymorphism was 0.76, indicating that the presence of the GT polymorphism decreased the risk of prostate cancer of more than 20% compared to the GG polymorphism. This difference, however, was not statistically significant. The GT polymorphism had an inverse association with cancer grade compared to the reference group (OR=0.47, p value=0.2).
 CONCLUSIONS: These results suggest that prostate cancer development is not associated with the Glu298Asp polymorphism of the endothelial nitric oxide synthase gene in our population. Further studies in larger samples are needed to confirm our results and characterize the molecular mechanisms by which eNOS is involved in the susceptibility to prostate cancer.

Association of G/A polymorphism, rs266882, in AREI region of the prostate-specific antigen gene with prostate cancer risk and clinicopathological features.

PURPOSE: To determine the association of prostate-specific antigen (PSA) 158A/G polymorphism with clinicopathologic characteristics of the disease and prostate cancer (PCa) risk. MATERIALS AND METHODS: Two hundred and six subjects, including 95 patients with PCa and 111 subjects with benign prostatic hyperplasia (BPH), were recruited in this study. Genotyping was performed by Polymerase Chain Reaction-Restriction Fragment Length Polymorphism method. RESULTS: Presence of GG genotype significantly increased the risk of PCa more than 2-fold compared to AG genotype (adjusted odds ratio = 2.4; P = .03). The percentages of G alleles of polymorphisms in patients with PCa were more than that in ones with BPH (odds ratio = 1.2; P = .7). CONCLUSION: The GG genotype of PSA 158A/G polymorphism is a predisposing factor for PCa. But no association was observed between alleles and grade, stage, or age of diagnosis. Similarly, the rs266882 polymorphism was not associated with PSA plasma levels.

Association of angiotensin I converting enzyme polymorphism as genetic risk factor in benign prostatic hyperplasia and prostate cancer.

INTRODUCTION: Angiotensin I converting enzyme (ACE) gene insertion/deletion (I/D) polymorphism is one of the genetic factors found to be related with prostate cancer (PC). We investigated the association between grade and stage of disease, age of diagnosis, vascular or perineural invasion, prediagnostic plasma prostate specific antigen (PSA) levels, and PC risk with I/D polymorphism of the ACE gene. MATERIALS AND METHODS: We recruited 206 subjects in this study, including 95 patients with PC and 111 patients with benign prostatic hyperplasia. RESULTS: The odds ratio between II and DD polymorphisms (reference) was 1.38. It means that the presence of the II polymorphism increased the risk of cancer more than 38% compared with DD polymorphism although still it was not statistically significant. The mean of total PSA in the patients with the II genotype was 20 ng/L more than that in those who had DD polymorphism. The odds ratio (OR) between the D allele and PC development was 1.16, indicating that this allele increased the risk of cancer about 16%. CONCLUSION: We found no association between the ACE polymorphism and cancer risk, overall or by grade, stage, or age of diagnosis. The difference in results for ACE polymorphisms between studies may be minimized by using larger study groups.