@article {46685, title = {CD44, a predominant protein in methylglyoxal-induced secretome of muscle cells, is elevated in diabetic plasma}, journal = {ACS Omega}, volume = {5}, year = {2020}, month = {OCT }, pages = {25016-25028}, type = {Article}, abstract = {

Methylglyoxal (MG), a glycolytic intermediate and reactive dicarbonyl, is responsible for exacerbation of insulin resistance and diabetic complication. In this study, NIG-induced secretome of rat muscle cells was identified and relatively quantified by SWATH-MS. A total of 643 proteins were identified in MG induced{\textquoteright} secretome, of which 82 proteins were upregulated and 99 proteins were downregulated by more than 1.3-fold in SWATH analysis. Further, secretory proteins from the dassical secretory pathway and nonclassical secretory pathway were identified using SignalP and SecretomeP, respectively. A total of 180 proteins were identified with SignalP, and 113 proteins were identified with SecretomeP. The differentially expressed proteins were functionallyannotated by KEGG pathway analysis using Cytoscape soft ware with plugin clusterMaker. The differentially expressed proteins were{\textquoteright}sfound to he involved m various pathways like extracellular matrix (ECM) receptor interaction, leukocyte transendothelial migration, fluid shear tress and atherosclerosis, complement and coagulation cascades, and lysosomal pathway. Since the MG levels are high in diabetic conditions, the presence of MG-induced isecreted proteins was inspected {\textquoteleft}by profiling human plasma of healthy and diabetic subjects (n = 10 each). CD44, a predominant MG -induced secreted protein, was found to be elevated in the diabetic plasma and to have a role in the development of insulin resistance.

}, issn = {2470-1343}, doi = {10.1021/acsomega.0c01318}, author = {Bai, Shakuntala and Chaurasiya, Arvindkumar H. and Banarjee, Reema and Walke, Prachi B. and Rashid, Faraz and Unnikrishnan, Ambika G. and Kulkarni, Mahesh J.} } @article {47390, title = {Insights from a pan India Sero-epidemiological survey (Phenome-India Cohort) for SARS-CoV2}, journal = {eLife}, volume = {10}, year = {2021}, month = {APR }, pages = {e66537}, type = {Article}, abstract = {

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14\%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95\% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10\% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95\% confidence interval, p value: 2.23, 1.92-2.59, \<0.0001), use of public transport (1.79, 1.43-2.24, \<0.0001), not smoking (1.52, 1.16-1.99, 0.0257), non-vegetarian diet (1.67, 1.41-1.99, \<0.0001), and B blood group (1.36, 1.15-1.61, 0.001).

}, issn = {2050-084X}, doi = {10.7554/eLife.66537}, author = {Naushin, Salwa and Sardana, Viren and Ujjainiya, Rajat and Bhatheja, Nitin and Kutum, Rintu and Bhaskar, Akash Kumar and Pradhan, Shalini and Prakash, Satyartha and Khan, Raju and Rawat, Birendra Singh and Tallapaka, Karthik Bharadwaj and Anumalla, Mahesh and Chandak, Giriraj Ratan and Lahiri, Amit and Kar, Susanta and Mulay, Shrikant Ramesh and Mugale, Madhav Nilakanth and Srivastava, Mrigank and Khan, Shaziya and Srivastava, Anjali and Tomar, Bhawana and Veerapandian, Murugan and Venkatachalam, Ganesh and Vijayakumar, Selvamani Raja and Agarwal, Ajay and Gupta, Dinesh and Halami, Prakash M. and Peddha, Muthukumar Serva and Sundaram, Gopinath M. and Veeranna, Ravindra P. and Pal, Anirban and Agarwal, Vinay Kumar and Maurya, Anil Ku and Singh, Ranvijay Kumar and Raman, Ashok Kumar and Anandasadagopan, Suresh Kumar and Karuppanan, Parimala and Venkatesan, Subramanian and Sardana, Harish Kumar and Kothari, Anamika and Jain, Rishabh and Thakur, Anupama and Parihar, Devendra Singh and Saifi, Anas and Kaur, Jasleen and Kumar, Virendra and Mishra, Avinash and Gogeri, Iranna and Rayasam, Geethavani and Singh, Praveen and Chakraborty, Rahul and Chaturvedi, Gaura and Karunakar, Pinreddy and Yadav, Rohit and Singhmar, Sunanda and Singh, Dayanidhi and Sarkar, Sharmistha and Bhattacharya, Purbasha and Acharya, Sundaram and Singh, Vandana and Verma, Shweta and Soni, Drishti and Seth, Surabhi and Vashisht, Sakshi and Thakran, Sarita and Fatima, Firdaus and Singh, Akash Pratap and Sharma, Akanksha and Sharma, Babita and Subramanian, Manikandan and Padwad, Yogendra S. and Hallan, Vipin and Patial, Vikram and Singh, Damanpreet and Tripude, Narendra Vijay and Chakrabarti, Partha and Maity, Sujay Krishna and Ganguly, Dipyaman and Sarkar, Jit and Ramakrishna, Sistla and Kumar, Balthu Narender and Kumar, Kiran A. and Gandhi, Sumit G. and Jamwal, Piyush Singh and Chouhan, Rekha and Jamwal, Vijay Lakshmi and Kapoor, Nitika and Ghosh, Debashish and Thakkar, Ghanshyam and Subudhi, Umakanta and Sen, Pradip and Chaudhury, Saumya Ray and Kumar, Rashmi and Gupta, Pawan and Tuli, Amit and Sharma, Deepak and Ringe, Rajesh P. and Amarnarayan, D. and Kulkarni, Mahesh and Shanmugam, Dhansekaran and Dharne, Mahesh S. and Dastager, Sayed G. and Joshi, Rakesh and Patil, Amita P. and Mahajan, Sachin N. and Khan, Abujunaid Habib and Wagh, Vasudev and Yadav, Rakesh Kumar and Khilari, Ajinkya and Bhadange, Mayuri and Chaurasiya, Arvindkumar H. and Kulsange, Shabda E. and Khairnar, Krishna and Paranjape, Shilpa and Kalita, Jatin and Sastry, Narahari G. and Phukan, Tridip and Manna, Prasenjit and Romi, Wahengbam and Bharali, Pankaj and Ozah, Dibyajyoti and Sahu, Ravi Kumar and Babu, Elapavalooru Vssk and Sukumaran, Rajeev and Nair, Aiswarya R. and Valappil, Prajeesh Kooloth and Puthiyamadam, Anoop and Velayudhanpillai, Adarsh and Chodankar, Kalpana and Damare, Samir and Madhavi, Yennapu and Aggarwal, Ved Varun and Dahiya, Sumit and Agrawal, Anurag and Dash, Debasis and Sengupta, Shantanu} } @article {47095, title = {Molecular investigation of glycated insulin-induced insulin resistance via insulin signaling and AGE-RAGE axis}, journal = {Biochimica ET Biophysica Acta-Molecular Basis of Disease}, volume = {1867}, year = {2021}, month = {FEB }, pages = {166029}, type = {Article}, abstract = {

Hyperglycemic condition in diabetes promotes glycation of various plasma proteins including insulin. Glycation of insulin has been reported to reduce its biological activity. Reduced biological activity of glycated insulin could be either due to reduced affinity for the insulin receptor and impaired insulin signaling, or it can act as a ligand for the receptor for advanced glycation end products (RAGE) and activates oxidative stress and pro-inflammatory pathways leading to insulin resistance. This study investigates the effect of glycated insulin on both insulin and RAGE signaling. Glycated insulin treatment to Chinese hamster ovary (CHO-IR-GLUT4) cells stably expressing insulin receptor (IR) and glucose transporter fused with a green fluorescent protein (GLUT4-GFP) resulted in the impairment of insulin signaling, as the phosphorylation of IR and AKT significantly reduced, which affected GLUT4 translocation and glucose uptake. Moreover, it also activated RAGE signaling as observed by increased expression of NADPH oxidase accompanied by an increase in reactive oxygen species (ROS). Immunofluorescence study indicated the translocation of NF-kappa B to the nucleus upon treatment of glycated insulin. This was associated with increased RAGE expression, Caspase 3, and cell death. Downregulation of RAGE with the losartan treatment restored the impaired insulin signaling and glucose uptake. Additionally, in silico study demonstrated that glycated insulin has reduced binding affinity to insulin receptor and increased binding affinity to RAGE. Overall, this study demonstrates the role of glycated insulin in exacerbating insulin resistance by impairing insulin signaling as well as stimulating AGE-RAGE signaling.

}, keywords = {AGE, Diabetes, Glycation, Hyperglycemia, insulin, RAGE}, issn = {0925-4439}, doi = {10.1016/j.bbadis.2020.166029}, author = {Walke, Prachi B. and Bansode, Sneha B. and More, Nikita P. and Chaurasiya, Arvindkumar H. and Joshi, Rakesh S. and Kulkarni, Mahesh J.} } @article {48748, title = {Elevated level of glycated KQTALVELVK peptide of albumin is associated with the risk of diabetic nephropathy}, journal = {ACS Omega}, volume = {8}, year = {2023}, month = {JUN }, pages = {20654-20660}, type = {Article}, abstract = {

Diabetic nephropathyis a leading cause of end-stagerenal disease.Hence, early detection of diabetic nephropathy is essential to mitigatethe disease burden. Microalbuminuria, the currently used diagnosticmarker of diabetic nephropathy, is not efficient in detecting it atan early stage. Therefore, we explored the utility of glycated humanserum albumin (HSA) peptides for risk prediction of diabetic nephropathy.Three glycation-sensitive HSA peptides, namely, FKDLG-EENFK,KQTAL-VELVK, and KVPQVST-PTLVEVSR, with deoxyfructosyllysine(DFL) modification were quantified by targeted mass spectrometry (MS)in a study population comprising healthy and type II diabetes subjectswith and without nephropathy. Mass spectrometry, receiver operatingcharacteristic (ROC) curve, and correlation analysis revealed thatthe DFL-modified KQTALVELVK peptide was better than other glycatedHSA peptides and HbA(1c) for identifying diabetic nephropathy.DFL-modified KQTALVELVK could be a potential marker for risk predictionof diabetic nephropathy.

}, issn = {2470-1343}, doi = {10.1021/acsomega.3c01219}, author = {Chaurasiya, Arvindkumar H. and Jaiswal, Meera R. and Bayatigeri, Santhakumari and Kahar, Shweta and Tiwari, Shalbha and Unnikrishnan, Ambika G. and Kulkarni, Mahesh J.} } @article {48781, title = {Nanopore sequencing of RAGE gene polymorphisms and their association with type 2 diabetes}, journal = {ACS Omega}, volume = {8}, year = {2023}, month = {JUL}, pages = {25727-25738}, type = {Article}, abstract = {

The receptor foradvanced glycation end products (RAGE)is a transmembraneprotein that interacts with its ligands, advanced glycation end products(AGEs). AGEs are elevated in diabetes and diabetic complications,leading to increased oxidative stress and activation of pro-inflammatorypathways facilitated by AGE-RAGE signaling. Polymorphisms inthe RAGE gene can potentially affect AGE-RAGEinteraction and its downstream signaling, which plays a crucial rolein the progression of diabetes and its complications. In this study,we used nanopore sequencing for genotyping of RAGE polymorphism and identified a maximum number of 33 polymorphisms,including two previously unreported novel mutations in a cohort ofhealthy, type 2 diabetics without nephropathy and type 2 diabeticswith nephropathy in order to identify associations. Two novel RAGE polymorphisms in the intron 8 and 3 \& PRIME;UTR regionat genomic locations 32181834 and 32181132, respectively, were detectedwith a low frequency. For four previously reported polymorphisms,cross-validation by PCR-RFLP showed 99.75\% concordance with nanoporesequencing. Analysis of genotype distribution and allele frequenciesrevealed that five single nucleotide polymorphisms, i.e., rs1800625,rs3131300, rs3134940, rs2070600, and rs9391855, were associated withan increased risk for type 2 diabetes.

}, issn = {2470-1343}, doi = {10.1021/acsomega.3c00297}, author = {Chaurasiya, Arvindkumar H. and Khilari, Ajinkya A. and Kazi, Rubina and Jaiswal, Meera R. and Bhoite, Gouri M. and Padwal, Meghana K. and Momin, Abdulrahaman A. and Shanmugam, Dhanasekaran and Kulkarni, Mahesh J.} }