A method for improving the efficiency of DNA extraction from clotted blood samples

Funding information: This study was supported by a grant from the Research Council of the Mashhad University of Medical Sciences (Grant No: 931680). The authors would like to thank Dr. Hossein Eshghi at Department of Chemistry, Faculty of Science, the Ferdowsi University of Mashhad for his assistance in the experiment and Mohammad Sadegh Khorami who contributed to this study. We are also particularly grateful to the Research Council of the Mashhad University of Medical Sciences (MUMS) for the financial support of this studyPeer reviewedPublisher PD

Hookah smoking is strongly associated with diabetes mellitus, metabolic syndrome and obesity: a population-based study

Objectives The adverse effects of cigarette smoking have been widely studied before, whilst the effects of hookah smoking has received less attention, although it is a common habit in the Middle East. Here we have investigated the effects of cigarette and hookah smoking on biochemical characteristics in a representative population sample derived from the Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort study, from Northeastern Iran. Study design A total of 9840 subjects from the MASHAD population study were allocated to five groups; non-smokers (6742), ex-smokers (976), cigarette smokers (864), hookah smokers (1067), concomitant cigarette and hookah smokers (41). Methods Baseline characteristics were recorded in a questionnaire. Biochemical characteristics were measured by routine methods. Data were analyzed using SPSS software and p < 0.05 was considered significant. Results After adjustment for age and sex; the presence of CVD, obesity, metabolic syndrome, DM and dyslipidemia were significantly (p < 0.001) related to smoking status. After multivariate analysis, HDL (p < 0.001), WBC (p < 0.001), MCV (p < 0.05), PLT (p < 0.01) and RDW (p < 0.001), and the presence of CVD (p < 0.01), obesity (p < 0.001), metabolic syndrome (p < 0.05) and DM (p < 0.01) remained significant between cigarette smokers and non-smokers. Between hookah smokers and non-smokers; uric acid (p < 0.001), PLT (p < 0.05) and RDW (p < 0.05), and the presence of obesity (p < 0.01), metabolic syndrome (p < 0.001), diabetes (p < 0.01) and dyslipidemia (p < 0.01) remained significant after logistic regression. Conclusion There was a positive association between hookah smoking and metabolic syndrome, diabetes, obesity and dyslipidemia which was not established in cigarette smoking

Association of Paraoxonase-1 Genotype and Phenotype with Angiogram Positive Coronary Artery Disease

Funding Information: This study was supported by Mashhad and Isfahan University of Medical Sciences. The authors would like to thank technicians of Sina, Sadi, Ghaem catheterization laboratory and technicians of Isfahan Alzahra genetics laboratory.Peer reviewedPublisher PD

Association between diabetes mellitus and rs2868371; a polymorphism of HSPB1

Introduction: Diabetes (DM) is a type of metabolic disorder that its types are generated by collectingof genetic and environmental risk agents. Here, the association between HSPB1 polymorphism as a genetic risk factor and DM was investigated. Methods: Total 690 participants from MASHAD cohort study population were recruited into the study.Anti-HSP27-level was assessed followed by genotyping using Taqman®-probes-based assay. Anthropometric, demographic and hematological/biochemical characteristics were evaluated. Kaplan-Meier curves were utilized, while logistic regression models were used to assess the association of the genetic variant with clinical characteristics of population. Results: Finds was shown there are meaningful differences among groups of age, height, waist circumference, systolic blood pressure, FBG,TG, HDL-C, and hs-CRP, and was no big -significant difference between theexists in different HSP27 SNP in the two studied groups (with and without DM), also was no remarkable relation between genetic forms of HSPB1and T2DM. This investigation was the first research that analyzed the relationship between the genetic type of the HSPB1 gene (rs2868371) and Type 2 diabetes (DM2). In our population, the CC genotype (68.1%) had a higher prevalence versus GC (26.6%) and GG (5.3%) genotypes and the data shown that no genetic difference of HSPB1 gene polymorphism (rs2868371) was related with DM2. Conclusion: HSPB1 polymorphism, rs2868371, was not associated with type 2 diabetes mellitus

Utilizing the sublingual form of squalene in COVID-19 patients: a randomized clinical trial

Abstract In this study, the efficacy of sublingual squalene in decreasing the mortality rate among patients with COVID-19 was investigated. Squalene was extracted from pumpkin seed oil with a novel method. Then, the microemulsion form of squalene was prepared for sublingual usage. In the clinical study, among 850 admitted patients, 602 eligible COVID-19 patients were divided in two groups of control (N = 301) and cases (N = 301) between Nov 2021 and Jan 2022. Groups were statistically the same in terms of age, sex, BMI, lymphocyte count on 1st admission day, hypertension, chronic kidney disease, chronic respiratory disease, immunosuppressive disease, and required standard treatments. The treatment group received five drops of sublingual squalene every 4 h for 5 days plus standard treatment, while the control group received only standard treatment. Patients were followed up for 30 days after discharge from the hospital. The sublingual form of squalene in the microemulsion form was associated with a significant decrease in the mortality rate (p < 0.001), in which 285 (94.7%) cases were alive after one month while 245 (81.4%) controls were alive after 1 month of discharge from the hospital. In addition, squalene appears to be effective in preventing re-hospitalization due to COVID-19 (p < 0.001), with 141 of controls (46.8%) versus 58 cases (19.3%). This study suggests sublingual squalene in the microemulsion as an effective drug for reducing mortality and re-hospitalization rates in COVID-19 patients. Trial Registration Number: IRCT20200927048848N3

Association of Three Novel Inflammatory Markers: Lymphocyte to HDL‐C Ratio, High‐Sensitivity C‐Reactive Protein to HDL‐C Ratio and High‐Sensitivity C‐Reactive Protein to Lymphocyte Ratio With Metabolic Syndrome

ABSTRACT Objective We aimed to compare the association of three novel inflammatory indicators with metabolic syndrome (MetS) among Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort participants. Methods According to the International Diabetes Federation (IDF) criteria, the cohort participants were divided into the MetS(+) and MetS(−) groups. The lymphocyte to high‐density lipoprotein cholesterol (HDL‐C) ratio (LHR), high‐sensitivity C‐reactive protein (hs‐CRP) to HDL‐C ratio (HCHR) and hs‐CRP to lymphocyte ratio (HCLR) were calculated and were compared between the groups. Binary logistic regression (LR) analysis was performed to find the association of the indices with the presence of MetS among men and women. Receiver‐operating characteristic (ROC) curve analysis was used to establish cut‐off values in predicting MetS for men and women. p‐Values <0.05 were considered as statistically significant. Results Among a total of 8890 participants (5500 MetS(−) and 3390 MetS(+)), LHR, HCHR and HCLR were significantly higher in the MetS(+) group than in MetS(−) group (p < 0.001). In LR analysis, after adjusting for multiple cofounders, LHR remained an independent factor for the presence of MetS among men (OR: 1.254; 95% CI: 1.202–1.308; p < 0.001) and women (OR: 1.393; 95% CI: 1.340–1.448; p < 0.001). HCHR also remained an independent factor for the presence of MetS only in women (OR: 1.058; 95% CI: 1.043–1.073; p < 0.001). ROC curve analysis showed that LHR had the higher AUC for predicting MetS in both men (AUC: 0.627; 95% CI: 0.611–0.643; p < 0.001) and women (AUC: 0.683; 95% CI: 0.670, 0.696; p < 0.001). Conclusion This suggests that among both genders, the LHR as an inexpensive and easy‐to‐access marker has a better diagnostic performance and could be a promising alternative to the traditional expensive inflammatory markers such as hs‐CRP for the evaluation of inflammation in patients with MetS

Association between a genetic variant in scavenger receptor class B type 1 and its role on codon usage bias with increased risk of developing coronary artery disease

Objective: Coronary artery disease (CAD) as an important cause of morbidity and mortality globally. The scavenger receptor class B type 1 (SCARB1) plays an essential role in the reverse cholesterol transport. We have explored the association between a genetic variant, rs5888, in the SCARB1 gene with CAD and serum HDL-C levels. Methods: Patients were categorized into two groups' angiogram positive (>50% coronary stenosis) and angiogram negative (<50% coronary stenosis). Genotyping was carried out using polymerase chain reaction amplification refractory mutation system. The association between the SNP rs5888 and serum HDL-C was analyzed using a logistic regression model. Results: The results showed that the subjects carrying a T allele was associated with a decreased serum HDL-C levels compared to the C allele in total population (p < 0.001). The risk of angiogram positivity in subjects carrying a T allele was 3.1-fold higher than for the control group (p < 0.001). Conclusion: CVD patients carrying the T allele of rs5888 variant in the SCARB1 gene was associated with decreased serum level of HDL

Prediction of type 2 diabetes mellitus using hematological factors based on machine learning approaches: a cohort study analysis

Abstract Type 2 Diabetes Mellitus (T2DM) is a significant public health problem globally. The diagnosis and management of diabetes are critical to reduce the diabetes complications including cardiovascular disease and cancer. This study was designed to assess the potential association between T2DM and routinely measured hematological parameters. This study was a subsample of 9000 adults aged 35–65 years recruited as part of Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort study. Machine learning techniques including logistic regression (LR), decision tree (DT) and bootstrap forest (BF) algorithms were applied to analyze data. All data analyses were performed using SPSS version 22 and SAS JMP Pro version 13 at a significant level of 0.05. Based on the performance indices, the BF model gave high accuracy, precision, specificity, and AUC. Previous studies suggested the positive relationship of triglyceride-glucose (TyG) index with T2DM, so we considered the association of TyG index with hematological factors. We found this association was aligned with their results regarding T2DM, except MCHC. The most effective factors in the BF model were age and WBC (white blood cell). The BF model represented a better performance to predict T2DM. Our model provides valuable information to predict T2DM like age and WBC