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.

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.

Platelet distribution widths and white blood cell are associated with cardiovascular diseases: data mining approaches.

OBJECTIVE: To investigate the association between cardiovascular diseases (CVDs) and haematologic factors in a cohort of Iranian adults. METHOD: For a total population of 9,704 aged 35 to 65, a prospective study was designed. Haematologic factors and demographic characteristics (such as gender, age, and smoking status) were completed for all participants. The association between haematologic factors and CVDs was assessed through logistic regression (LR) analysis, decision tree (DT), and bootstrap forest (BF). RESULTS: Almost all of the included factors were significantly associated with CVD (p<.001). Among the included factors, were: age, white blood cell (WBC), and platelet distribution width (PDW) had the strongest correlation with the development of CVD. For unit OR interpretation, WBC has been represented as the most remarkable risk factor for CVD (OR: 1.22 (CI 95% (1.18, 1.27))). Also, age is associated with an increase in the odds of CVD + occurrence (OR: 1.12 (CI 95% (1.11, 1.13))). Moreover, males are times more likely to develop CVD than females (OR: 1.39 (CI 95% (1.22, 1.58))). In DT model, age is the best classifier factor in CVD development, followed by WBC and PDW. Furthermore, based on the BF algorithm, the most crucial factors correlated with CVD are age, WBC, PDW, sex, and smoking status. CONCLUSION: The obtained result from LR, DT, and BF models confirmed that age, WBC, and PDW are the most crucial factors for the development of CVD.

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.