Relationship between Insulin Sensitivity and Lipid Status of Hyperglycemic and Normoglycemic Subjects

Abstract

Type 2 diabetes mellitus (T2DM) is primarily due to a decreased response to insulin in the tissues of the body, which is defined as the insulin resistance (IR). Excess weight, obesity and morbid obesity are all risk factors for developing T2DM. The usual characteristics of South Asians include low muscle mass, a high body fat percentage, abdominal obesity, insulin resistance, and hyperinsulinemia. Type 2 diabetes is among the most serious consequences of being overweight or obese. The risk factors for cardiovascular illnesses in obese people are insulin resistance (IR) and abnormal lipid profiles. To investigate the relationship among IR, obesity and lipid profile, this study was conducted on a total of 1500 Bangladeshi people at the time of their general health checkup in the North East Medical College Hospital. The Ethical Committee of North East Medical College Hospital approved this study. All the T2DM patients were defined according to the 1999 World Health Organization (WHO) criteria and randomly recruited from the outpatient department. The controls had a fasting plasma glucose concentration <5.1 mmol/L and HbA1C <6%, with no history of oral hypoglycemic or lipid lowering agents. We collected the medical history and demographic information of all the individuals. Total study population was grouped according to age, gender, insulin, glycemic status and obesity. However, 728 patients were excluded due to other endocrine diseases. The remaining 772 patients were categorized as having IR > 2 and IR< 2 based on the homeostatic model assessment-estimated insulin resistance (HOMA-IR) index. Statistical analysis was used to examine and link the anthropometric and biochemical profiles with the IR>2 and IR<2 groups. In comparison to the IR<2 group, the total cholesterol (TC), triglyceride (TG), low density lipoprotein (LDL), and serum insulin levels were considerably higher in all the IR>2 group. Obesity and dyslipidemia were found to be common IR components. According to a generalized linear model, IR was significantly impacted by TC:LDL and TG:HDL. In comparison to age groups I (20–40 years old) and III (61-80 years old), participants in the age group II (41–60 years old) showed considerably higher lipid profiles. These findings provide credence to the idea that lipoprotein ratios may serve as biomarkers for measuring IR. During this study period, novel corona virus affected different people in different regions worldwide. The COVID-19 patients with DM more likely exhibited severe inflammatory response. In an effort to comprehend the connection between COVID-19 and diabetes mellitus and to assess the most affordable treatment option for the general population, the medical data of all suspected patients from 1 May 2020 to 15 August 2020 in the Medical College and Hospital aforementioned were included in the study. A total of 250 suspected COVID-19 patients were considered for this study. Among them, 211 patients were reviewed for laboratory data availability. Most of these patients had mild v symptoms and a good prognosis. All of the 211 patients were subjected to test for COVID-19 confirmation by qRT-PCR. Among them, 98 patients were confirmed COVID-19 positive. Several blood biomarkers in T2DM and non-diabetic (NDM) COVID-19 positive patients were analyzed to rapidly predict COVID-19 progression and severity. In the serum of COVID-19 patients, substantial amounts of ferritin, C-reactive protein (CRP), D-dimer, ALT, and troponin I. In comparison to COVID-19 positive patients without diabetes, the COVID- 19 patients with T2DM had increased levels of HbA1C, serum ferritin, and CRP. Data in the present study support the notion that ferritin and HbA1c levels for DM patients, and ferritin, D-dimer, ALT for NDM patients could be biomarkers for progression and severity assessment of COVID-19. However, CRP and Troponin-I could be biomarkers only for poor prognosis of COVID-19. Insulin receptor is a big warehouse of diseases such as T2DM. Any change or mutation in insulin receptor (INSR) may change disease pathogenesis. Single nucleotide polymorphisms (SNPs) may fall within coding sequences of genes (Non- synonymous), non-coding regions of genes (synonymous), or in the intergenic regions between genes. Non-synonymous SNPs (nsSNPs) may have deleterious effect due to substitution of single amino acids in the protein sequence. The harmful nsSNPs in the INSR gene was analyzed based on various computational approaches. The computational analysis indicated that 13 of these mutations nsSNPs decreased protein stability and may have led to function loss. Two nsSNPs such as I448T and W1220L positions (rs1051691 and rs52800171, respectively) were predicted as "Highly Destabilizing”. Their inclusion in the INSR raises the risk of diseases caused by the INSR and altered transcriptional and cell cycle control. In order to search SNPs in the INSR in Bangladeshi subjects, genomic DNA were isolated from healthy individuals and T2DM patient for sequences analysis. Polymerase chain reaction was carried out with primers from different exons of the INSR. Sequence analysis showed that Bangladeshi diabetic patients included in the present study had two mutations in exon 11 of the INSR. However, no mutation was observed in the healthy individuals. The 3D model analysis using bioinformatics tools revealed that the both mutations in the exon 11 may cause conformational change in the INSR. These alterations in the INSR could either slow or speed up the disease's course.