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Introduction The sirtuin (Silent mating type information regulation 2 homolog)1(SIRT1) protein plays a vital role in many disorders such as diabetes, cancer, obesity, inflammation, and neurodegenerative and cardiovascular diseases. The objective of this in silico analysis of SIRT1's functional single nucleotide polymorphisms (SNPs) was to gain valuable insight into the harmful effects of non-synonymous SNPs (nsSNPs) on the protein. The objective of the study was to use bioinformatics methods to investigate the genetic variations and modifications that may have an impact on the SIRT1 gene's expression and function. Methods nsSNPs of SIRT1 protein were collected from the dbSNP site, from its three (3) different protein accession IDs. These were then fed to various bioinformatic tools such as SIFT, Provean, and I- Mutant to find the most deleterious ones. Functional and structural effects were examined using the HOPE server and I-Tasser. Gene interactions were predicted by STRING software. The SIFT, Provean, and I-Mutant tools detected the most deleterious three nsSNPs (rs769519031, rs778184510, and rs199983221). Results Out of 252 nsSNPs, SIFT analysis showed that 94 were deleterious, Provean listed 67 dangerous, and I-Mutant found 58 nsSNPs resulting in lowered stability of proteins. HOPE modelling of rs199983221 and rs769519031 suggested reduced hydrophobicity due to Ile 4Thr and Ile223Ser resulting in decreased hydrophobic interactions. In contrast, on modelling rs778184510, the mutant protein had a higher hydrophobicity than the wild type. Conclusions Our study reports that three nsSNPs (D357A, I223S, I4T) are the most damaging mutations of the SIRT1 gene. Mutations may result in altered protein structure and functions. Such altered protein may be the basis for various disorders. Our findings may be a crucial guide in establishing the pathogenesis of various disorders.

Background: Type 2 diabetes mellitus (DM) can develop many complications, including hypogonadism, the prevalence of which is largely unknown. Male hypogonadism is an endocrine disease characterized by low-serum testosterone levels and is closely related to the development of diabetes. Methods: This cross-sectional study was conducted on 200 male patients with type 2 (DM) for 2 years. Plasma glucose, lipid profile, serum insulin, and sex hormone levels were measured. Weight and height were measured, and body mass index (BMI) was calculated. Homeostatic model assessment-insulin resistance was measured. The percentage was used to document the prevalence of hypogonadism in type 2 diabetics. The correlations between the patients' metabolic index and sex hormone levels were analyzed using Pearson's correlation coefficient. Results: The prevalence of hypogonadism in male type 2 diabetics was 26%. Primary hypogonadism was present in 48.1% and secondary hypogonadism was present in 51.9% of male type 2 diabetics. The percentage of the study participants with hypogonadism increased with an increase in BMI. Total testosterone showed a negative correlation with BMI, which was statistically significant (r = −0.246 and P < 005). Fasting blood sugar and BMI correlated negatively with sex hormone-binding globulin and were statistically significant (r = −0.196 and P < 0.01), (r = −0.175 and P < 0.05). Conclusions: The prevalence of hypogonadism calls for implementing early, universal screening programs, irrespective of the symptoms of androgen deficiency, to detect those who have low-serum total testosterone levels at an early stage and supplement testosterone accordingly.

Background: Chronic kidney disease (CKD) is a major public health concern in recent years mainly due to its adverse clinical outcomes. It is most commonly attributed to diabetes mellitus (DM) and hypertension (HTN). Among the several novel biomarkers discovered to detect impaired renal function, serum cystatin C (SCysC) has gained importance. Objectives: The aim of the study was to compare SCysC and serum creatinine (SCr) in CKD subjects and apparently healthy controls. Methods: This case-control study comprising of 120 diagnosed cases of CKD and 40 controls was conducted at a tertiary care hospital. SCr and SCysC levels were estimated using modified Jaffe’s method and particle enhanced immunoturbidimetric method, respectively. Estimated glomerular filtration rate (eGFR) was calculated using CKD EPI formula. Comparison of SCr and SCysC between cases and controls was done using Mann Whitney U test. Pearson’s correlation test was used to study the correlation between variables. Statistical significance was considered at P

Introduction: Leptin is an adipokine hormone that regulates insulin sensitivity and lipid profile, which may contribute to complications like gestational diabetes.The goal of the study was to examine if there was a link between the leptin (LEP)/leptin receptor (LEPR) gene polymorphism and insulin resistance in pregnant women, and to determine the extent to which the leptin gene polymorphism could cause insulin resistance.. Methods: 208 pregnant women participated in this cross-sectional study of which 74 were insulin resistant cases and 134 were insulin sensitive controls. The study was carried out from December 2018 to December 2020 at a charitable hospital in Mangalore, Karnataka, India. Genotyping of leptin and its receptor gene were carried out using the Polymerase Chain Reaction- Restriction fragment Length Polymorphism (PCR-RFLP) method. Serum levels of leptin, insulin, and C peptide were assayed using Enzyme Linked Immuno Sorbent Assay (ELISA) and lipid profile by automated chemistry analyzer. Statistical analysis was carried out using SPSS 23. Results: Insignificant association was observed between leptin receptor gene polymorphisms and insulin resistance, and leptin gene and insulin resistant women. There was no significant difference in the serum leptin levels among the cases and control (61.62±29.23 and 59.88±22.25). However, fasting blood sugar, insulin, C peptide, Triglycerides (TG), and very low-density Lipoprotein (VLDL) levels were significantly higher in cases as compared to controls (p=0.0068, p

Introduction: Osteoporosis is a global health problem, asymptomatic and noticed only after a fracture. Ten years after the cessation of ovarian function due to hormonal imbalance, women show an accelerated phase of reduction in bone mass known as primary osteoporosis. Determination of Bone Mineral Density (BMD) and Dual Energy X-Ray Absorptiometry (DEXA) are the gold standard diagnostic approaches for osteoporosis. However, they are costly; hence Bone Turnover Markers (BTMs) have been suggested to detect the risk of osteoporotic fractures. Aim: To assess the potential of BTMs as a diagnostic tool for primary osteoporosis in order to reduce the associated morbidity and mortality. Materials and Methods: This study was conducted on 105 women who were divided into Group I with 35 pre-menopausal women, Group II with 35 post-menopausal women without fractures and Group III with 35 post-menopausal women with wrist, spine or hip fractures. Serum osteocalcin (OC), calcium, phosphate, alkaline phosphatase, total protein, albumin and 24 hour urinary hydroxyproline were estimated. Statistical analysis was done using Statistical Package for the Social Sciences (SPSS) Version 16.0. ANOVA test was done to compare variables among the groups. Tukey’s test was applied for intergroup comparison. Student’s t-test was used to compare two groups and correlation studies were done using Pearson’s correlation. Statistical significance was considered as p

Introduction: Sialic acid levels are increased in type-2 diabetes mellitus and its estimation helps in predicting the occurrence of microvascular complication such as diabetic nephropathy. The present study compared the levels of sialic acid, glycated haemoglobin, serum creatinine and urine microalbumin: in type-2 diabetics without any complications; in type-2 diabetics with nephropathy; and in age and sex matched healthy individual (controls). Results: The study observed an increased level of sialic acid in type-2 diabetics without any complications and type-2 diabetics with nephropathy. Serum sialic acid levels in type-2 diabetics without any complications was 64.44 ± 3.93 mg/dl, in type-2 diabetics with nephropathy was 73.88 ± 4.41 mg/dl, and in controls it was 53.16 ± 3.40 mg/dl. Urine sialic acid levels in type-2 diabetics without any complications was 6.62 ± 0.70 mg/ dl, in type-2 diabetics with nephropathy was 8.46 ± 0.97 mg/ dl, and in controls it was 4.44 ± 0.62 mg/dl. Correlation of sialic acid levels with glycated haemoglobin and urine microalbumin was statistically significant but with serum creatinine was not statistically significant. Conclusion: Sialic acid is an important component of vascular cell membrane. Their increased levels indicate extensive vascular damage in type-2 DM. Therefore, estimation of sialic acid levels help in early prediction and prevention of microvascular complications occurring due to diabetics, thereby decreasing the mortality and morbidity in them.

Introduction: Diabetic patients have higher prevalence of thyroid disorders than the general population which may have an influence on diabetic management. The present study compared the levels of thyroid hormones, serum creatinine, glycated haemoglobin and urine microalbumin between type 2 diabetics without any complications, type 2 diabetics with nephropathy and age and sex matched normal controls. Result: The mean serum T3 level in type 2 diabetics without any complications was 91.27 ± 14.56 ng/dl , in type 2 diabetics with nephropathy was 88.5320 ± 30.87 ng/dl and in controls was 134.98 ± 28.55 ng/dl. The mean serum T4 level in type 2 diabetics without any complications was 7.73 ± 1.42 µg/dl, in type 2 diabetics with nephropathy was 7.25 ± 2.72 µg/dl and in controls was 8.61 ± 1.73 µg/dl. The mean serum TSH level in type 2 diabetics without any complications was 3.99 ± 1.87 µIU/ ml, in type 2 diabetics with nephropathy was 4.27 ± 1.62 µIU/ml and in controls was 2.07 ± 1.09 µIU/ml. Correlations between T3, T4, TSH with serum creatinine, glycated haemoglobin were not statistically significant in type 2 diabetes without any complications and diabetic nephropathy. We found a statistically significant correlation between T3 and urine microalbumin in patients with diabetic nephropathy. Conclusion: Failure to recognize the presence of abnormal thyroid hormone levels may be a primary cause of poor management of diabetes mellitus type 2. Therefore there is a need for the routine assay of thyroid hormones in type 2 diabetics and diabetic nephropathy in order to improve the quality of life and reduce the morbidity.

Introduction The sirtuin (Silent mating type information regulation 2 homolog)1(SIRT1) protein plays a vital role in many disorders such as diabetes, cancer, obesity, inflammation, and neurodegenerative and cardiovascular diseases. The objective of this in silico analysis of SIRT1's functional single nucleotide polymorphisms (SNPs) was to gain valuable insight into the harmful effects of non-synonymous SNPs (nsSNPs) on the protein. The objective of the study was to use bioinformatics methods to investigate the genetic variations and modifications that may have an impact on the SIRT1 gene's expression and function. Methods nsSNPs of SIRT1 protein were collected from the dbSNP site, from its three (3) different protein accession IDs. These were then fed to various bioinformatic tools such as SIFT, Provean, and I- Mutant to find the most deleterious ones. Functional and structural effects were examined using the HOPE server and I-Tasser. Gene interactions were predicted by STRING software. The SIFT, Provean, and I-Mutant tools detected the most deleterious three nsSNPs (rs769519031, rs778184510, and rs199983221). Results Out of 252 nsSNPs, SIFT analysis showed that 94 were deleterious, Provean listed 67 dangerous, and I-Mutant found 58 nsSNPs resulting in lowered stability of proteins. HOPE modelling of rs199983221 and rs769519031 suggested reduced hydrophobicity due to Ile 4Thr and Ile223Ser resulting in decreased hydrophobic interactions. In contrast, on modelling rs778184510, the mutant protein had a higher hydrophobicity than the wild type. Conclusions Our study reports that three nsSNPs (D357A, I223S, I4T) are the most damaging mutations of the SIRT1 gene. Mutations may result in altered protein structure and functions. Such altered protein may be the basis for various disorders. Our findings may be a crucial guide in establishing the pathogenesis of various disorders.

Introduction: The sirtuin (Silent mating type information regulation 2 homolog)1(SIRT1) protein plays a vital role in many disorders such as diabetes, cancer, obesity, inflammation, and neurodegenerative and cardiovascular diseases. The objective of this in silico analysis of SIRT1's functional single nucleotide polymorphisms (SNPs) was to gain valuable insight into the harmful effects of non-synonymous SNPs (nsSNPs) on the protein. The objective of the study was to use bioinformatics methods to investigate the genetic variations and modifications that may have an impact on the SIRT1 gene's expression and function. Methods: nsSNPs of SIRT1 protein were collected from the dbSNP site, from its three (3) different protein accession IDs. These were then fed to various bioinformatic tools such as SIFT, Provean, and I- Mutant to find the most deleterious ones. Functional and structural effects were examined using the HOPE server and I-Tasser. Gene interactions were predicted by STRING software. The SIFT, Provean, and I-Mutant tools detected the most deleterious three nsSNPs (rs769519031, rs778184510, and rs199983221). Results: Out of 252 nsSNPs, SIFT analysis showed that 94 were deleterious, Provean listed 76 dangerous, and I-Mutant found 66 nsSNPs resulting in lowered stability of proteins. HOPE modelling of rs199983221 and rs769519031 suggested reduced hydrophobicity due to Ile 4Thr and Ile223Ser resulting in decreased hydrophobic interactions. In contrast, on modelling rs778184510, the mutant protein had a higher hydrophobicity than the wild type. Conclusions: Our study reports that three nsSNPs (D357A, I223S, I4T) are the most damaging mutations of the SIRT1 gene. Mutations may result in altered protein structure and functions. Such altered protein may be the basis for various disorders. Our findings may be a crucial guide in establishing the pathogenesis of various disorders.

Introduction: Leptin, along with its receptor, are linked with mechanisms affecting a diverse array of pregnancy-specific pathologies that include gestational diabetes and intrauterine growth restriction. The goal of the study was to examine if there was a link between the leptin (LEP)/leptin receptor (LEPR) gene polymorphism and insulin resistance in pregnant women, and to determine the extent to which the leptin gene polymorphism could cause insulin resistance.. Methods: 208 pregnant women participated in this cross-sectional study of which 74 were insulin resistant cases and 134 were insulin sensitive controls. The study was carried out from December 2018 to December 2020 at a charitable hospital in Mangalore, Karnataka, India. Genotyping of leptin and its receptor gene were carried out using the Polymerase Chain Reaction- Restriction fragment Length Polymorphism (PCR-RFLP) method. Serum levels of leptin, insulin, and C peptide were assayed using Enzyme Linked Immuno Sorbent Assay (ELISA). Statistical analysis was carried out using SPSS 23. Results: Insignificant association was observed between leptin receptor gene polymorphisms and insulin resistance, and leptin gene and insulin resistant women. There was no significant difference in the serum leptin levels among the cases and control (61.62±29.23 and 59.88±22.25). However, fasting blood sugar, insulin, C peptide, Triglycerides (TG), and very low-density Lipoprotein (VLDL) levels were significantly higher in cases as compared to controls (p=0.0068, p Conclusion: No significant association was found between leptin and leptin receptor gene polymorphisms with insulin resistance in pregnancy. However, genotyping of these genes may be useful in predicting insulin resistance and gestational diabetes in pregnancy.