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Purpose: The Discovery of underlying intermediates associated with the development of dyslipidemia results in a better understanding of pathophysiology of dyslipidemia and their modification will be a promising preventive and therapeutic strategy for the management of dyslipidemia., Methods: The entire dataset was selected from the Surveillance of Risk Factors of Noncommunicable Diseases (NCDs) in 30 provinces of Iran (STEPs 2016 Country report in Iran) that included 1200 subjects and was stratified into four binary classes with normal and abnormal cases based on their levels of triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and non-HDL-C.Plasma concentrations of 20 amino acids and 30 acylcarnitines in each class of dyslipidemia were evaluated using Tandem mass spectrometry. Then, these attributes, along with baseline characteristics data, were used to check whether machine learning (ML) algorithms could classify cases and controls., Results: Our ML framework accurately predicts TG binary classes. Among the models tested, the SVM model stood out, performing slightly better with an AUC of 0.81 and a standard deviation of test accuracy at 0.04. Consequently, it was chosen as the optimal model for TG classification. Moreover, the findings showed that alanine, phenylalanine, methionine, C3, C14:2, and C16 had great power in differentiating patients with high TG from normal TG controls. Conclusions: The comprehensive output of this work, along with sex-specific attributes, will improve our understanding of the underlying intermediates involved in dyslipidemia., Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-024-01384-9., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s), under exclusive licence to Tehran University of Medical Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Objective: Polycystic ovary syndrome (PCOS) is a common multifactorial endocrine disorder affecting women of reproductive age. ACE enzyme is involved in the physiopathology of the ovarian system, and there are inconsistencies between studies regarding the association between ACE gene variants and PCOS. The objective of this study is to evaluate the association between ACE I/D gene polymorphisms and PCOS, as well as its clinical manifestations, in Iranian women with PCOS., Design: This study included 140 patients with PCOS and 153 controls without the disease. Samples were collected from Yas Hospital Complex in Tehran-Iran during 2018 to 2022. Genomic DNA was obtained from whole blood samples using salt extraction, and genotyping was carried out using polymerase chain reaction (PCR)., Results: Variants of DD, ID, and II were observed in 31.4, 44.3, and 24.3% of PCOS, and 38.6, 44.1, and 17.2% of control group, respectively. The frequency of ACE gene variants did not differ between PCOS patients and control group. A significant difference was observed between the frequency of elevated LH to FSH ratio > 2 and ACE gene polymorphisms in patients with PCOS (OR: 0.32 (0.12-0.88), P value 0.024) with lower frequency observed in D allele carriers., Conclusion: This study indicate that although ACE I/D variants frequency in PCOS women is similar to non-PCOS women, it may be involved in the pathogenesis of the disease through mechanisms regulating steroidogenesis in the ovary and suggests that ACE might be related to exacerbated clinical manifestations of PCOS which requires further investigations., Competing Interests: Conflict of interestThe authors declare no conflict of interest., (© The Author(s), under exclusive licence to Tehran University of Medical Sciences 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Background: The risk of depression among patients with diabetes is higher than the general population. The exact mechanisms linking these two diseases are mostly unknown. Energy metabolism disorders seem to be a shared pathway. One of the key genes playing important roles in energy metabolism-related pathways is the APOE gene. We aimed to investigate the association of the APOE gene variants with depression among Iranian patients with type 2 diabetes (T2DM)., Methods: Three APOE gene alleles and genotypes frequencies (E2, E3, E4) were determined in 244 patients with T2DM (114 with depression and 130 without depression) using the high-resolution melting (HRM) method on the genomic DNA extracted from the patient's peripheral blood., Results: Apoe4 allele frequency was significantly higher in T2DM patients without depression compared with those with depression (11.9 vs. 2.2%, p-value < 0.0001 and p-value = 0.001, respectively). Conversely, the wild allele apoe3 frequency was significantly higher in T2DM patients with depression (86% vs., 69%, p-value < 0.0001). Apoe4 carrier status was associated with decreased risk of depression in patients with T2DM [OR: 0.19 (0.07-0.53)]., Conclusion: Our results showed that the apoe4 allele and apoe4 carrier status significantly reduced the risk of depression among patients with T2DM. Further studies are needed to unravel the complex role of the APOE gene in depression among patients with diabetes., Competing Interests: Conflict of interestNone., (© The Author(s), under exclusive licence to Tehran University of Medical Sciences 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Aim: This paper presented the methodology and main findings of a population-based survey to determine diabetes care status among type 2 diabetic subjects in Iran. The current study assessed treatment goal achievements in type 2 diabetics, diabetes care service utilization, prevalence of diabetes complications, and psychological effects of diabetes in a representative sample of Iranian population in urban and rural areas., Materials and Methods: This nationwide study was conducted between 2018 and 2020 as the observational survey entitled "Diabetes Care (DiaCare)". We studied a representative sample of participants with type 2 diabetes, aged 35-75 years, living in urban and rural areas in all thirty- one provinces of Iran. Data were collected by an interviewer in a form of a questionnaire that includes demographic and socioeconomic status, family and drug history, lifestyle, and self-reported psychological status according to a Patient's Health Questionnaire (PHQ). Management goal achievements, diabetes care service utilization, diabetes complications and psychological effects of diabetes were also assessed. Physical measurements were measured based on standard protocol. Fasting blood glucose (FBG), HbA1c, lipid profile, and also urine albumin to creatinine ratio were obtained from all participants of the study., Results: Overall, 13,334 people with type 2 diabetes in 31 provinces of Iran completed the survey (response rate: 99.6%). In total 13,321 participants, 6683(50.17%) women and 6638(49.83%) men were included in our analysis. Thirteen recruited patients refused after the consenting process and did not respond. The mean age (SD) of total participants was 54.86 ± 9.44 years and 71.50% were from the urban areas. 13.66% of diabetic patients had achieved the triple target of management [controlled HbA1c, blood pressure, and Low-Density Lipoprotein-Cholesterol (LDL-C)] in the whole country. While 28.74% of people had controlled HbA1c and 33.40% of them had controlled FBG. Diabetic subjects living in rural areas had less controlled HbA1c (23.93 vs. 29.48), controlled FBG (29.50 vs. 34.20) and controlled triple targets (10.45 vs. 14.32) than those living in urban areas. Diabetic neuropathy and diabetic foot were more common in women than men, while end-stage of renal disease (ESRD) was more common in men than women., Conclusions: This population-based study provided representative information about diabetes care in Iran. The high prevalence of diabetes and low proportion of diabetes control in Iran implies that it is necessary to identify factors associated with poor treatment goal achievements. Besides, general improvements in management and care of diabetes are mandatory., Competing Interests: Conflict of interestAuthors declare that they have no conflict of interest., (© The Author(s), under exclusive licence to Tehran University of Medical Sciences 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Purpose: This study aimed to evaluate the performance of valid risk assessment models developed for osteoporosis/ fracture screening to identify women in need of bone density measurement in a population of Iranian elderly women., Methods: This study was performed using the data of Bushehr Elderly Health (BEH) program, a population-based cohort study of elderly population aged ≥ 60 years. Seven osteoporosis risk assessment tools, including Osteoporosis Risk Assessment Instrument (ORAI), Malaysian Osteoporosis Screening Tool (MOST), Osteoporosis Prescreening Risk Assessment (OPERA), Osteoporosis Prescreening Model for Iranian Postmenopausal women (OPMIP), Osteoporosis Index of Risk (OSIRIS), and Osteoporosis Self-Assessment Tool for Asians (OSTA), as well as Fracture Risk Assessment Tool (FRAX) were included in the study. By using osteoporosis definition based on BMD results, the performance measurement criteria of diagnostic tests such as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Youden index for each model were calculated and the models were compared., Results: A total of 1237 female participants with the mean age of 69.1 ± 6.3 years were included. Overall, 733 (59%) participants had osteoporosis, and about 80% had no history of fracture. The sensitivity of the seven models ranged from 16.7% (OSIRIS) to 100% (ORAI and MOST) at their recommended cut-off points. Moreover,their specificity ranged from 0.0% (ORAI and MOST) to 78.9% (OSTA). The FRAX and OPERA had the optimal performance with the Youden index of 0.237 and 0.226, respectively. Moreover, after combining these models, the sensitivity of them increased to 85.4%., Conclusion: We found that the FRAX (model with 11 simple variables) and OPERA (model with 5 simple variables) had the best performance. By combining the models, the performance of each was improved. Further studies are needed to adopt the model and to find the best cut-off point in the Iranian postmenopausal women., Competing Interests: Competing interestsThe authors declare no competing interest., (© The Author(s), under exclusive licence to Tehran University of Medical Sciences 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)