Volume : 13, Issue : 08, August – 2026

Title:

BIOMARKERS DISCOVERY IN TYPE 2 DIABETES MELLITUS: FROM OMICS TECHNOLOGIES TO CLINICAL PRACTICE

Authors :

Manisha, Soma Sekhar Pulamarasetti*, Omkar Rai, Karan Gupta, Shivlal Yadav

Abstract :

Background: Type 2 diabetes mellitus (T2DM) is caused by complex pathophysiological processes including progressive insulin resistance, pancreatic β-cell dysfunction, chronic systemic inflammation and altered interorgan metabolic communication1. The ability of common clinical markers such as fasting plasma glucose and glycated hemoglobin (HbA1c) to identify early subclinical alterations or discriminate between disease subphenotypes1 is limited.
Objective: To review current literature of multi-omic biomarker discovery in T2DM with focus on predictive discrimination, mechanistic contribution across omic layers, and translational, regulatory and clinical implementation barriers2.
Data Sources: Comprehensive synthesis of studies indexed in PubMed, MEDLINE, Scopus and Web of Science evaluating genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics and machine-learning-driven multi-omics integration2.
Review Methods: A state-of-the-art structured review of human prospective cohorts, case-cohort designs, clinical trial evaluations, assay standardization and regulatory qualification pathways2.
Key Findings: Among individual omic layers, plasma proteomics showed the highest discriminative performance for prediction of incident T2DM5. Targeted proteomic panels (e.g., 15 proteins) improve the C-index of established clinical models by 0.022–0.0235. Metabolomic signatures, including branched-chain amino acids (isoleucine, leucine, valine) and aromatic amino acids (phenylalanine, tyrosine), may reflect metabolic dysregulation >10 years prior to clinical onset4. Epigenetic methylation probes at TXNIP, ABCG1, and PDK4 capture cumulative metabolic memory 2 Integrating full multi-omic profiles yields modest predictive improvements (+0.006 to +0.05 C-index increment) over targeted proteomic-clinical models due to biological signal redundancy 5
Conclusion: Multi-omic biomarker profiling improves T2DM risk prediction and subphenotyping. For clinical translation, standardized analytical workflows, cross-population validation in diverse cohorts, cost-utility optimization, and formal regulatory qualification2 are required.
Keywords: Diabetes Mellitus, Type 2 Biomarkers Proteomics Metabolomics Precision Medicine Multi-omics

Cite This Article:

Please cite this article in press Soma Sekhar P et al., Biomarkers Discovery In Type 2 Diabetes Mellitus: From Omics Technologies To Clinical Practice. Indo Am. J. P. Sci, 2026; 13(08).

REFERENCES:

1. Multi-omics approaches for biomarker discovery and precision diagnosis of prediabetes, https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2025.1520436/full
2. Exploring the design of clinical research studies on the efficacy mechanisms in type 2 diabetes mellitus – PMC, https://pmc.ncbi.nlm.nih.gov/articles/PMC11449758/
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6. Multi-omic prediction of type 2 diabetes incidence. (a–d) C index of… – ResearchGate, https://www.researchgate.net/figure/Multi-omic-prediction-of-type-2-diabetes-incidence-a-d-C-index-of-the-prediction_fig2_375026793
7. Plasma multi-omics and machine learning reveal predictive biomarkers for type 2 diabetes and retinopathy in Qatar biobank cohort – Western Sydney University, https://researchers.westernsydney.edu.au/en/publications/plasma-multi-omics-and-machine-learning-reveal-predictive-biomark/
8. An FDA Perspective on the Regulatory Implications of Complex Signatures to Predict Response to Targeted Therapies | Clinical Cancer Research – AACR Journals, https://aacrjournals.org/clincancerres/article/23/6/1368/80400/An-FDA-Perspective-on-the-Regulatory-Implications
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Volume : 13, Issue : 08, August – 2026

Title:

EVALUATION OF ANTIHYPERLIPIDEMIC ACTIVITY OF SAPINDUS EMARGINATUS IN RATS

Authors :

Chinthala Jamima*, Dr.R.narasimha Rao, Dr.N. Raghunandhan

Abstract :

Obesity and hyperlipidemia have become major disorders predominantly causing prevailing cardiovascular diseases and ultimately death. The prolonged use of anti-obesity drugs and statins for reducing obesity and blood lipid levels is leading toward adverse effects of kidneys and muscles, specifically rhabdomyolysis. The objective of this study is to evaluate potential of seeds of Sapindus emarginatus against hyperlipidemia. In this model of Hyperlipidemia, 30 adult male wistar rats (200-250gms) were evenly divided into 5 groups in both groups. Group-1 and Group-2 served as untreated and model controls respectively, while Group-3, 4 and 5 were the treatments groups which were simultaneously treated with standard, 100 and 200 mg/kg extract respectively along with High Fat Diet. On last day, blood samples for biochemical parameters, were obtained under inhaled diether anaesthesia. The outcomes of this study were expressed as mean standard error and data were evaluated by using analysis of variance followed by multiple comparisons. Oral administration of 100 mg/ kg and 200mg/kg body weight of Methanolic extract residual fraction of Moringa oleifera. Leaves exhibited a significant reduction (P < 0.01) in serum lipid parameters such as triglycerides, total cholesterol, low density lipoprotein (LDL), very LDL and increase in high density lipoprotein in hyperlipidemic rats when compared with hyperlipidemic control in both models. Our results demonstrated that Methanolic extract fraction of Sesbania grandiflora. Possessed significant antihyperlipidemic activity.
Keywords: Sesbania grandiflora, Cholesterol, LDL, triglycerides and antihyperlipidemic activity.

Cite This Article:

Please cite this article in press Chinthala Jamimaet al., Evaluation of Antihyperlipidemic activity of Sapindus Emarginatus in rats,, Indo Am. J. P. Sci, 2026; 13(08).

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