Microbiome as a biomarker and therapeutic target in pancreatic cancer.

Studying the effects of the microbiome on the development of different types of cancer has recently received increasing research attention. In this context, the microbial content of organs of the gastrointestinal tract has been proposed to play a potential role in the development of pancreatic cancer (PC). Proposed mechanisms for the pathogenesis of PC include persistent inflammation caused by microbiota leading to an impairment of antitumor immune surveillance and altered cellular processes in the tumor microenvironment. The limited available diagnostic markers that can currently be used for screening suggest the importance of microbial composition as a non-invasive biomarker that can be used in clinical settings. Samples including saliva, stool, and blood can be analyzed by 16 s rRNA sequencing to determine the relative abundance of specific bacteria. Studies have shown the potentially beneficial effects of prebiotics, probiotics, antibiotics, fecal microbial transplantation, and bacteriophage therapy in altering microbial diversity, and subsequently improving treatment outcomes. In this review, we summarize the potential impact of the microbiome in the pathogenesis of PC, and the role these microorganisms might play as biomarkers in the diagnosis and determining the prognosis of patients. We also discuss novel treatment methods being used to minimize or prevent the progression of dysbiosis by modulating the microbial composition. Emerging evidence is supportive of applying these findings to improve current therapeutic strategies employed in the treatment of PC.

The associations of oxidative stress and inflammatory markers with obesity in Iranian population: MASHAD cohort study.

BACKGROUND: Low-grade inflammation and stress oxidative condition play a role in the pathogenesis of obesity, and the serum levels of these markers, such as pro-oxidant-antioxidant balance (PAB), high-sensitivity C-reactive protein (hs-CRP), and uric acid may indicate obesity progression. In this study, we aimed to investigate the relationship between obesity with PAB, hs-CRP, and uric acid in the Iranian population. METHODS: This study was derived from the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study. A total of 7985 subjects aged 35 to 65 years were divided into three groups according to body mass index (BMI) as: normal, overweight and obese groups. Anthropometric indices and biochemical parameters such as PAB, superoxide dismutase type 1 (SOD1), hs-CRP, and uric acid were measured in all the participants. We evaluated the association of obesity with inflammatory factors by using multivariate regression analysis. Also, those participants with hypertension, an endocrine disorder, history of cardiovascular diseases and diabetes mellitus were excluded from the study. RESULTS: There was a positive significant correlation between BMI and serum PAB, hs-CRP and uric acid (p < 0.001). While no statistically significant relation was observed between BMI and SOD1 (p = 0.85). Multivariate regression analysis showed that the risk of overweight and obesity increased 1.02 and 1.03-fold according to increase 10 units of PAB raise in comparison to reference group (normal weight) [(odds ratio (OR): 1.02, 95% CI (1.01-1.03)] and [OR: 1.03, 95% CI (1.01-1.04)], respectively). In addition, hs-CRP serum concentration was significantly associated with a high risk of obesity [(OR: 1.02; 95% CI (1.01-1.03)]. While the high levels of serum uric acid were associated with increased odds of overweight and obesity risk [OR: 1.4; CI (1.39-1.58) and OR: 1.76; CI (1.63-1.89), respectively]. CONCLUSIONS: Generally, we showed a significant association between BMI and serum PAB, hs-CRP values and uric acid levels, suggesting the role of these factors as risk stratification factors for obesity.

Association of T-wave electrocardiogram changes and type 2 diabetes: a cross-sectional sub-analysis of the MASHAD cohort population using the Minnesota coding system.

BACKGROUND: Type 2 Diabetes Mellitus (T2DM) has become a major health concern with an increasing prevalence and is now one of the leading attributable causes of death globally. T2DM and cardiovascular disease are strongly associated and T2DM is an important independent risk factor for ischemic heart disease. T-wave abnormalities (TWA) on electrocardiogram (ECG) can indicate several pathologies including ischemia. In this study, we aimed to investigate the association between T2DM and T-wave changes using the Minnesota coding system. METHODS: A cross-sectional study was conducted on the MASHAD cohort study population. All participants of the cohort population were enrolled in the study. 12-lead ECG and Minnesota coding system (codes 5-1 to 5-4) were utilized for T-wave observation and interpretation. Regression models were used for the final evaluation with a level of significance being considered at p < 0.05. RESULTS: A total of 9035 participants aged 35-65 years old were included in the study, of whom 1273 were diabetic. The prevalence of code 5-2, 5-3, major and minor TWA were significantly higher in diabetics (p < 0.05). However, following adjustment for age, gender, and hypertension, the presence of TWAs was not significantly associated with T2DM (p > 0.05). Hypertension, age, and body mass index were significantly associated with T2DM (p < 0.05). CONCLUSIONS: Although some T-wave abnormalities were more frequent in diabetics, they were not statistically associated with the presence of T2DM in our study.

Anxiety, a significant risk factor for coronary artery disease: what is the best index.

BACKGROUND: Coronary artery disease (CAD) is known as the leading cause of disability and death globally. Anxiety disorders are also recognized as common types of mental disorders that substantially impact global health. Iran ranks among the countries with a high incidence of CAD and anxiety disorders. Therefore, the present study aims to determine the potential association and epidemiological aspects of anxiety and CAD within the population of Mashhad, the second most popoulos city in Iran. METHODS: The present study is based on extracted data from the Mashhad stroke and heart atherosclerotic disorder (MASHAD) study which is a 10-year prospective cohort study intended to assess the effects of various CAD risk factors among Mashhad city residents. Anxiety scores were assessed at the baseline using Beck Anxiety Inventory and individuals were classified based on the BAI 4-factor structure model which included autonomic, cognitive, panic, and neuromotor components. Accordingly, the association between baseline anxiety scores and the BAI four-factor model with the risk of CAD events was analyzed using SPSS software version 21. RESULTS: Based on the results, 60.4% of the sample were female, and 5.6% were classified as having severe forms of anxiety. Moreover, severe anxiety was more prevalent in females. Results showed a 1.7% risk of CAD (p-value < 0.001) over 10 years with one unit increase in anxiety score. Based on the 4-factor model structure, we found that only panic disorder could significantly increase the risk of CAD by 1.1% over the 10-year follow-up (p-value < 0.001). CONCLUSION: Anxiety symptoms, particularly panic disorder, are independently and significantly associated with an increased overall risk of developing CAD over a 10-year period. Therefore, further studies are warranted to investigate the mechanisms through which anxiety may cause CAD, as well as possible interventions to mitigate these processes.

The association between lifelines diet score (LLDS) with depression and quality of life in Iranian adolescent girls.

BACKGROUND: It has been proposed that a greater degree of adherence to a healthy dietary pattern is associated with a lower risk of depression and a poor quality of life (QoL). The Lifelines diet score (LLDS) is a new, evidence-base scoring system to define the quality of diet. We designed a cross-sectional study to investigate the association between LLDS with depression and QoL in Iranian adolescent girls. METHODS: A total of 733 female adolescents were recruited from Mashhad and Sabzevar cities, Iran. Depression and QoL were assessed utilizing the Beck Depression Inventory (BDI) and SF-12v2 questionnaires, respectively. The LLDS was defined by dividing intakes of 12 food groups with negative or positive health effects into quintiles ranging 12 to 60 points. To explore the association between LLDS with QoL and depression, logistic regression was used in crude and adjusted models. RESULTS: The prevalence of depression and poor QoL was 24% and 49%, respectively. After adjusting for confounding factors, adolescent girls in the highest quartile of LLDS compared with the participants in the lowest quartile had a 42% lower probability of reporting depressive symptoms (OR: 0.58; 95% CI: 0.35-0.97, P = 0.03). In addition, the participants in the highest quartile of LLDS had lower odds of poor QoL compared with the subjects in the lowest quartile (OR: 0.65; 95% CI: 0.42-0.92, P = 0.04). CONCLUSIONS: There is an inverse relationship between LLDS with risk of depression and poor QoL. Prospective and interventional investigations are needed to reach a clear vision.

The association between hyperuricemia and insulin resistance surrogates, dietary- and lifestyle insulin resistance indices in an Iranian population: MASHAD cohort study.

BACKGROUND: Previous studies have reported insulin resistance (IR) to be associated with hyperuricemia. In this study, we aimed to assess the possible associations between the empirical dietary index for IR (EDIR), the empirical lifestyle index for IR (ELIR), and non-insulin-based surrogates (triglyceride-glucose (TyG) index, triglyceride-to-high-density-lipoprotein-cholesterol (TG/HDL-C) ratio, metabolic score for insulin resistance (METS-IR) and TyG with body mass index (TyG-BMI)) and hyperuricemia in an Iranian population. METHODS: In this cross-sectional study, 6457 participants aged 35-65 years were recruited as part of the MASHAD cohort study. EDIR and ELIR were calculated using dietary intakes, body mass index, and physical activity information. Insulin resistance surrogates including TyG, TyG-BMI, TG/HDL-C, and METS-IR were calculated for all participants. Hyperuricemia was defined as serum uric acid ≥ 7 mg/dl in men or ≥ 6 mg/dl in women. Multivariable logistic regression models were applied to determine the association between indexes of IR and hyperuricemia. RESULTS: The mean ELIR and IR surrogates (TyG, TyG-BMI, TG/ HDL, and METS-IR) were significantly higher in subjects with hyperuricemia compared to non-hyperuricemic subjects (p < 0.001). After adjusting for confounding variables, the association between hyperuricemia and EDIR was not significant, but ELIR had a significant association in all models (p < 0.001). All four IR surrogates (TyG, TyG-BMI, TG/ HDL, and METS-IR) showed a significant association with hyperuricemia (p < 0.001). CONCLUSION: There was a significant association between indexes of insulin resistance: TyG, TyG-BMI, TG/HDL-c, METS-IR, and ELIR with hyperuricemia, in a population sample from northeastern Iran.

Micronutrients intake and genetic variants associated with premature ovarian insufficiency; MASHAD cohort study.

BACKGROUND AND AIM: premature ovarian insufficiency (POI) is defined as the menopause before 40 years of age, and its prevalence is reported to be two-fold higher in Iranian women than the average for woman globally. POI is associated with several cardio/cerebrovascular complications as well as an increased overall mortality. Genetic factors, and serum levels of minerals and vitamin D, have been reported to be related to the prevalence of POI. We have investigated the association between some POI -related genotypes with the serum levels of some important micronutrients. METHODS: One hundred and seventeen women with POI and 183 controls without any renal, hepatic, and thyroid abnormalities were recruited as part of the MASHAD study. Demographic and anthropometric features were recorded and blood samples were collected and processed. DNA was extracted from the buffy coat of blood samples from all participants and 8 POI-related single nucleotide polymorphisms (SNPs) were determined using ASO-PCR or Tetra ARMS-PCR. Serum minerals and vitamin D concentrations were measured using routine methods. RESULTS: In women with POI, serum copper, phosphate, and calcium were significantly different for those with rs244715, rs16991615, and rs4806660 genotypes, respectively. In our control population, significant differences were also found in serum copper concentrations between different genotypes of rs4806660, rs7246479, rs1046089, and rs2303369. After adjusting for all confounding factors, the women with POI carrying TC genotype (rs4806660) had a lower risk to have serum copper levels < 80 (µg/dL) than those carrying a TT genotype. Furthermore, women with POI carrying GG genotype (rs244715) had a 6-fold higher risk to have serum copper levels > 155 than those carrying AA genotype. CONCLUSION: The C and G alleles of the rs4806660 and rs244715 polymorphisms respectively are independently associated with serum copper in women with POI. Further studies are necessary to investigate the association of serum copper and other micronutrients in women and other POI -related polymorphisms.

Predicting the 10-year incidence of dyslipidemia based on novel anthropometric indices, using data mining.

BACKGROUND: The aim was to establish a 10-year dyslipidemia incidence model, investigating novel anthropometric indices using exploratory regression and data mining. METHODS: This data mining study was conducted on people who were diagnosed with dyslipidemia in phase 2 (n = 1097) of the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study, who were compared with healthy people in this phase (n = 679). The association of dyslipidemia with several novel anthropometric indices including Conicity Index (C-Index), Body Roundness Index (BRI), Visceral Adiposity Index (VAI), Lipid Accumulation Product (LAP), Abdominal Volume Index (AVI), Weight-Adjusted-Waist Index (WWI), A Body Shape Index (ABSI), Body Mass Index (BMI), Body Adiposity Index (BAI) and Body Surface Area (BSA) was evaluated. Logistic Regression (LR) and Decision Tree (DT) analysis were utilized to evaluate the association. The accuracy, sensitivity, and specificity of DT were assessed through the performance of a Receiver Operating Characteristic (ROC) curve using R software. RESULTS: A total of 1776 subjects without dyslipidemia during phase 1 were followed up in phase 2 and enrolled into the current study. The AUC of models A and B were 0.69 and 0.63 among subjects with dyslipidemia, respectively. VAI has been identified as a significant predictor of dyslipidemias (OR: 2.81, (95% CI: 2.07, 3.81)) in all models. Moreover, the DT showed that VAI followed by BMI and LAP were the most critical variables in predicting dyslipidemia incidence. CONCLUSIONS: Based on the results, model A had an acceptable performance for predicting 10 years of dyslipidemia incidence. Furthermore, the VAI, BMI, and LAP were the principal anthropometric factors for predicting dyslipidemia incidence by LR and DT models.

Factors associated with prolonged QTc interval in Iranian population: MASHAD cohort study.

AIM: QTc interval prolongation is a growing global issue which can cause torsades de pointes, a potentially fatal arrhythmia. We aimed to identify risk factors for prolonged QT interval in men and women. METHODS: The Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort study collected electrocardiogram interval data. QT was corrected for heart rate using the Bazett's formula. Ordinal logistic regression with crude (univariable) and adjusted (multivariate) association analyses in the form of odds ratio and corresponding 95% confidence interval (CI) were used to identify the factors associated with QTc prolongation. RESULTS: A total of 8878 individuals including 5318 females and 3560 males, aged 35 to 65 years, were included in this cross-sectional study. Participants with QTc prolongation were more likely to be older and have hypercholesterolemia, hypertension (HTN), and Type 2 diabetes mellitus (T2DM), but to have lower levels of physical activity (P < 0.05). Age (OR = 1.68, 95%CI = 1.18-2.39), hypercholesterolemia (OR = 1.77, 95%CI = 1.24-2.51), HTN (OR = 1.36, 95%CI = 1.06-1.73), T2DM (OR = 1.59, 95%CI = 1.19-2.13), severe anxiety (OR = 1.80, 95%CI = 1.05-3.11) and mild depression (OR = 1.38, 95%CI = 1.01-1.88) were independent risk factors for prolonged QTc interval in men. For women, only HTN (OR = 1.29, 95%CI = 1.02-1.63) and T2DM (OR = 1.50, 95%CI = 1.14-1.97) were independent risk factors. CONCLUSIONS: Older age, Hypercholesterolemia, HTN, T2DM, severe anxiety and mild depression in men, and HTN and T2DM in women were associated with high risk of prolonged QTc interval. Healthcare practitioners should be aware of the risk factors of QTc interval prolongation and should exercise caution in the management of certain patients.

Age-specific reference intervals for routine biochemical parameters in healthy neonates, infants, and young children in Iran.

Age and sex need to be considered in the establishment of reference intervals (RIs), especially in early life when there are dynamic physiological changes. Since data for important biomarkers in healthy neonates and infants are limited, particularly in Iranian populations, we have determined age-specific RIs for 7 laboratory biochemical parameters. This cross-sectional study comprised a total of 344 paediatric participants (males: 158, females: 186) between the ages of 3 days and 30 months (mean age: 12.91 ± 7.15 months). Serum levels of creatinine, urea, uric acid, calcium, phosphate, vitamin D and high-sensitivity C-reactive protein (hs-CRP) were measured using an Alpha classic-AT plus auto-analyser. We determined age-specific RIs using CLSI Ep28-A3 and C28-A3 guidelines. No sex partitioning was required for any of the biomarkers. Age partitioning was required for kidney function tests and phosphate. The serum concentration of urea and creatinine increased with age, while phosphate and uric acid decreased with age. Age partitioning was not required for serum calcium, vitamin D, and hs-CRP, which remained relatively constant throughout the age range. Age-specific RIs for 7 routine biochemical markers were determined to address critical gaps in RIs in early life to help improve clinical interpretation of blood test results in young children, including neonates. Established age partitions demonstrate the biochemical changes that take place during child growth and development. These novel data will ultimately better disease management in the Iranian paediatric population and can be of value to clinical and hospital laboratories with similar populations.

Association between biochemical and hematologic factors with COVID-19 using data mining methods.

BACKGROUND AND AIM: Coronavirus disease (COVID-19) is an infectious disease that can spread very rapidly with important public health impacts. The prediction of the important factors related to the patient's infectious diseases is helpful to health care workers. The aim of this research was to select the critical feature of the relationship between demographic, biochemical, and hematological characteristics, in patients with and without COVID-19 infection. METHOD: A total of 13,170 participants in the age range of 35-65 years were recruited. Decision Tree (DT), Logistic Regression (LR), and Bootstrap Forest (BF) techniques were fitted into data. Three models were considered in this study, in model I, the biochemical features, in model II, the hematological features, and in model II, both biochemical and homological features were studied. RESULTS: In Model I, the BF, DT, and LR algorithms identified creatine phosphokinase (CPK), blood urea nitrogen (BUN), fasting blood glucose (FBG), total bilirubin, body mass index (BMI), sex, and age, as important predictors for COVID-19. In Model II, our BF, DT, and LR algorithms identified BMI, sex, mean platelet volume (MPV), and age as important predictors. In Model III, our BF, DT, and LR algorithms identified CPK, BMI, MPV, BUN, FBG, sex, creatinine (Cr), age, and total bilirubin as important predictors. CONCLUSION: The proposed BF, DT, and LR models appear to be able to predict and classify infected and non-infected people based on CPK, BUN, BMI, MPV, FBG, Sex, Cr, and Age which had a high association with COVID-19.

Association of dietary and blood inflammatory indicators with depression, anxiety, and stress in adults with vitamin D deficiency.

BACKGROUND: There is growing evidence that vitamin D may be related to mental health. The aim of the current study was to investigate the association of dietary and blood inflammatory factors with mental health disorders in subjects with vitamin D deficiency, shedding further light on the complex interplay of these conditions. METHOD: In this cross-sectional study, 306 subjects completed the validated Depression, Anxiety, and Stress Scale questionnaire to evaluate their depression, anxiety, and stress scores. Dietary inflammatory index (DII) and healthy eating index (HEI) were calculated using a validated 65-item food frequency questionnaire. Blood samples were taken and vitamin D, cytokine, and hs-CRP levels were measured using enzyme-linked immunosorbent assay kits. Platelet to lymphocyte ratio (PLR) and neutrophil to lymphocyte ratio (NLR) were calculated using standard laboratory methods. RESULTS: The subjects were divided into two groups based on their vitamin D levels: a vitamin D < 20 µg/dl group (N = 257) and a vitamin D ≥ 20  µg/dl group (N = 49). Between group analysis revealed that only DII (p = 0.015), platelet (p = 0.04), and hs-CRP (p = 0.015) were significantly different. In adults with vitamin D levels below 20 µg/dl, NLR and DII were significantly higher in subjects with anxiety (p < 0.05), and this relationship remained significant only for NLR after adjusting for age and sex. Additionally, PLR and HEI were significantly different in depressed compared to non-depressed subjects, and this association remained significant only for HEI after adjusting for age and sex. CONCLUSION: In subjects with vitamin D deficiency, increased levels of PLR, NLR, and DII were associated with depression and anxiety, while HEI was negatively associated with depression. These associations were not found in subjects with vitamin D levels ≥20 µg/dl.

Higher global diet quality score is related to lower prevalence of depression and poor quality of life among adolescent girls.

BACKGROUND: Adolescence is a key time for the development of depression symptoms and the diet quality may be associated with mental health conditions. The present study examined the association between depression and quality of life (QoL) and the global diet quality score (GDQS) as a simple and standardized metric diet quality in Iranian adolescents. METHODS: This cross-sectional study was conducted on 733 adolescent girls recruited using a random cluster sampling method. A 147-item food frequency questionnaire (FFQ) was used for dietary intake assessment. The GDQS is gained by summing points of all the 25 food groups, ranged from 0 to 49. Depression symptoms were assessed using a Persian version of the Beck Depression Inventory (BDI). For assessment of health-related QoL, the Short Form 12 Survey-version 2 (SF-12v2) questionnaire was employed. Multivariable logistic regression examined the association of depression and QoL with GDQS in crude and adjusted models. RESULTS: Adolescent girls in the highest tertile of GDQS score compared with the lowest tertile had a 41% lower odds of depressive symptoms (OR: 0.59; 95% CI: 0.39-0.90, P = 0.01). The participants in the third tertile of GDQS score had lower odds of poor QoL compared with the first tertile (OR: 0.56; 95% CI: 0.37-0.85, P < 0.01). These associations remained significant (both P = 0.01) after adjustment for age, energy intake, body mass index (BMI), physical activity, and menstruation (depressive symptoms: OR: 0.59; 95% CI: 0.38-0.92; QoL: OR: 0.59; 95% CI: 0.38-0.91, P = 0.01). CONCLUSION: We found that adolescent girls with a higher score of the GDQS had lower odds of depression and poor QoL Prospective and interventional investigations are needed to reach a clear vision.

Dietary acid load, depression, and anxiety: results of a population-based study.

BACKGROUND: Dietary acid load seems to be associated with psychological disorders through several mechanisms, and may barricade their treatment and recovery. The aim of current study was to evaluate the relationship between dietary acid load, using potential renal acid load (PRAL) and dietary acid load (DAL) scores, with the severity of depression and anxiety among Iranian adults. METHODS: A total of 6531 participants aged 35-65 years were recruited in this cross-sectional study. A validated food frequency questionnaire (FFQ) was used to assess dietary intakes of participants. DAL was estimated using PRAL and DAL scores. Depression and anxiety were screened using Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI). RESULTS: In the fully adjusted model, women with the highest DAL or PRAL had higher odds of more severe depression compared to those in the lowest category (OR = 1.20; 95% CI = 1.03-1.42 and OR = 1.20; 95% CI = 1.03-1.39, respectively). No significant association was observed between DAL and PRAL and depression severity in men and in the population as a whole. Regarding the association between PRAL and anxiety severity, there was no significant association when separated by sex. However, in the fully adjusted model for the whole population, participants in the highest tertile of PRAL had 13% greater odds of more severe anxiety than the lowest tertile (OR: 1.13, 95% CI: 1.01-1.13). No significant association was observed between DAL and anxiety severity in women, men or in the whole population. CONCLUSION: Women, but not men, with higher dietary acid load had significantly higher odds of having more severe depression. A significant positive association was also observed between dietary acid load and anxiety in the whole population.

A large population-based study on the prevalence of electrocardiographic abnormalities: A result of Mashhad stroke and heart atherosclerotic disorder cohort study.

BACKGROUND: Twelve-lead electrocardiogram (ECG) is a common and inexpensive tool for the diagnostic workup of patients with suspected cardiovascular disease, both in clinical and epidemiological settings. The present study was designed to evaluate ECG abnormalities in Mashhad population. METHODS: ECGs were taken as part of MASHAD cohort study (phase1) and were coded according to the Minnesota coding criteria. Data were analyzed using SPSS. RESULTS: Total 9035 ECGs were available for final analysis including 3615 (40.0%) male and 5420 (60.0%) female. Among ECG abnormalities precordial Q wave, major T-wave abnormalities, inferior Q wave, sinus bradycardia, and left axis deviation were the most prevalent abnormalities. The frequency of precordial and inferior Q wave, inferior QS pattern, major and minor ST abnormalities, major and minor T abnormalities, Wolff-Parkinson-White and Brugada pattern, sinus bradycardia, sinus tachycardia, left axis deviation, ST elevation, and tall T wave were significantly different between two genders. Moreover, the frequency of Q wave in precordial and aVL leads, QS pattern in precordial and inferior leads, major and minor T-wave abnormalities, Wolff-Parkinson-White, atrial fibrillation, sinus bradycardia, left axis deviation, and ST elevation were significantly different in different age groups. A comparison of the heart rate, P-wave duration, and QRS duration between men and women indicated that there was a significant difference. CONCLUSIONS: Our finding indicated that the prevalence ECG abnormalities are different between men and women and also it varied in different age groups.

Use of data mining approaches to explore the association between type 2 diabetes mellitus with SARS-CoV-2.

BACKGROUND AND OBJECTIVE: Corona virus causes respiratory tract infections in mammals. The latest type of Severe Acute Respiratory Syndrome Corona-viruses 2 (SARS-CoV-2), Corona virus spread in humans in December 2019 in Wuhan, China. The purpose of this study was to investigate the relationship between type 2 diabetes mellitus (T2DM), and their biochemical and hematological factors with the level of infection with COVID-19 to improve the treatment and management of the disease. MATERIAL AND METHOD: This study was conducted on a population of 13,170 including 5780 subjects with SARS-COV-2 and 7390 subjects without SARS-COV-2, in the age range of 35-65 years. Also, the associations between biochemical factors, hematological factors, physical activity level (PAL), age, sex, and smoking status were investigated with the COVID-19 infection. RESULT: Data mining techniques such as logistic regression (LR) and decision tree (DT) algorithms were used to analyze the data. The results using the LR model showed that in biochemical factors (Model I) creatine phosphokinase (CPK) (OR: 1.006 CI 95% (1.006,1.007)), blood urea nitrogen (BUN) (OR: 1.039 CI 95% (1.033, 1.047)) and in hematological factors (Model II) mean platelet volume (MVP) (OR: 1.546 CI 95% (1.470, 1.628)) were significant factors associated with COVID-19 infection. Using the DT model, CPK, BUN, and MPV were the most important variables. Also, after adjustment for confounding factors, subjects with T2DM had higher risk for COVID-19 infection. CONCLUSION: There was a significant association between CPK, BUN, MPV and T2DM with COVID-19 infection and T2DM appears to be important in the development of COVID-19 infection.

Data mining approaches for type 2 diabetes mellitus prediction using anthropometric measurements.

BACKGROUND: The aim of this study was to evaluate the anthropometric measurements most associated with type 2 diabetes mellitus (T2DM) using machine learning approaches. METHODS: A prospective study was designed for a total population of 9354 (43% men and 57% women) aged 35-65. Anthropometric measurements include weight, height, demispan, Hip Circumference (HC), Mid-arm Circumference (MAC), Waist Circumference (WC), Body Roundness Index (BRI), Body Adiposity Index (BAI), A Body Shape Index (ABSI), Body Mass Index (BMI), Waist-to-height Ratio (WHtR), and Waist-to-hip Ratio (WHR) were completed for all participants. The association was assessed using logistic regression (LR) and decision tree (DT) analysis. Receiver operating characteristic (ROC) curve was performed to evaluate the DT's accuracy, sensitivity, and specificity using R software. RESULTS: Traditionally, 1461 women and 875 men with T2DM (T2DM group). According to the LR, in males, WC and BIA (p-value < 0.001) and in females, demispan and WC (p-value < 0.001) had the highest correlation with T2DM development risk. The DT indicated that WC has the most crucial effect on T2DM development risk, followed by HC, and BAI. CONCLUSIONS: Our results showed that in both men and women, WC was the most important anthropometric factor to predict T2DM.

Age-specific reference intervals for liver function tests in healthy neonates, infants, and young children in Iran.

BACKGROUND: The reference intervals (RIs) for liver function tests (LFTs) were determined in Iranian children for the first time. METHODS: A total of 344 healthy pediatrics aged 3 days to 30 months old were recruited. Serum levels of ALT, AST, ALP, direct bilirubin, and total bilirubin were measured. RIs were determined using CLSI Ep28-A3 guidelines. RESULTS: All analytes demonstrated age-specific differences except AST. ALT and ALP demonstrated significantly elevated levels in infants 0 to <5 months relative to the remainder of the age range. Direct and total bilirubin demonstrated markedly elevated levels in early life with mean of 0.28 mg/dL and 1.64 mg/dL observed for direct and total bilirubin, respectively, decreasing by ~50% in the adjacent partition. CONCLUSION: These novel data will help improve the clinical interpretation of biochemical test results in young Iranian neonates and children and can be of value to clinical laboratories with similar populations.

Association of Genotypes of ANGPTL3 with Vitamin D and Calcium Concentration in Cardiovascular Disease.

One of the leading causes of mortality worldwide is cardiovascular disease, which is influenced by some variables, including calcium and vitamin D. This study aimed to assess the relationship between Angiopoietin-Like 3 (ANGPTL3) gene polymorphisms with vitamin D and calcium levels in cardiovascular disease (CVD) patients. In this research, 1002 people participated. Participants' anthropometric parameters, and FBG, calcium, and vitamin D were assessed. Blood samples were used to extract DNA. Taqman®-based polymerase chain reaction (PCR) was used to conduct genetic analysis for the rs10789117 and rs17458195. Statistical analysis was applied to determine differences across subgroups and the relationship between polymorphisms and disease. Age, body mass index (BMI), fasting Blood Sugar (FBG), phenylalanine ammonia-lyase (PAL), and smoking history were significantly correlated with CVD. Vitamin D was statistically associated with rs10789117 and rs17458195 in non-CVD individuals. In the moderate group, individuals with the C allele in rs10789117 showed a tenfold increase in vitamin D deficiency compared to those with the A allele. However, in rs11207997, individuals with the T allele had 5 to 6 times higher vitamin D deficiency than those with the C allele in all groups. This research demonstrates the relationship between some ANGPTL3 gene polymorphisms and complement levels in CVD patients. It may be concluded that individuals carrying these variants would likely benefit from using vitamin D and calcium supplements to avoid CVD.

Assessment of the Performances of Adaptive Neuro-Fuzzy Inference System and Two Statistical Methods for Diagnosing Coronary Artery Disease.

Background: The accurate diagnosis of cardiac disease is vital in managing patients' health. Data mining and machine learning techniques play an important role in the diagnosis of heart disease. We aimed to examine the diagnostic performances of an adaptive neuro-fuzzy inference system (ANFIS) for predicting coronary artery disease and compare this with two statistical methods: flexible discriminant analysis (FDA) and logistic regression (LR). Methods: The data of this study is the result of descriptive-analytical research from the study of Mashhad. We used ANFIS, LR, and FDA to predict coronary artery disease. A total of 7385 subjects were recruited as part of the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) cohort study. The data set contained demographic, serum biochemical parameters, anthropometric, and many other variables. To evaluate the ability of trained ANFIS, LR, and FDA models to diagnose coronary artery disease, we used the Hold-Out method.For analyzing data, we used SPSS v25, R 4.0.4, and MATLAB 2018 software. Results: The accuracy, sensitivity, specificity, Mean squared error (MSE) , and area under the roc curve (AUC) for ANFIS were 83.4%, 80%, 86%, 0.166 and 83.4%. The corresponding values based on the LR method were 72.4%, 74%, 70% , 0.175 and 81.5% and for the FDA method, these measurements were 77.7%, 74%, 81%, 0.223, and 77.6%, respectively. Conclusion: There was a significant difference between the accuracy of these three methods. The present findings showed that ANFIS was the most accurate method for diagnosing coronary artery disease compared with LR and FDA methods. Thus, it could be a helpful tool to aid medical decision-making for the diagnosis of coronary artery disease.