Thalassemia (thal) is the most inherited single-gene disorder globally. In the past, β-thalassemia (β-thal) was classified phenotypically as major, intermedia and minor or trait. Recently, a new classification was developed based on blood transfusion requirements, i.e., transfusion-dependent thalassaemia (TDT) and non-transfusiondependent thalassaemia (NTDT). However, this classification essentially represents the patient's need for transfusion, and a TDT patient can shift to NTDT based on the intermittent clinical evaluation. The management of thalassaemia syndromes has seen essential improvements; however, still several challenges to control the incidence worldwide. In resource constrained countries, the lack of adequate prevention programmes and effective management is still inappropriate. Curative treatment like haemopoietic stem cell transplantation (HSCT) is not affordable for most patients, and this procedure is also not without risks. Gene therapy is another curative treatment, but it is still experimental. So, currently, supportive treatments such as regular blood transfusions and iron chelation therapy are the best options available for these patients. Limitations of available current treatment modalities are the driving force to investigate the novel diagnostic and therapeutic options for better clinical management of these patients. This study aimed to investigate the differentially expressed proteins (novel proteins) in serum from TDT to understand the pathophysiology of TDT and determine their role in TDT severity by performing quantitative serum proteomics profiling. Understanding the inter-relationships of proteins affected by the disease process, such as oxidative stress in TDT patients, can explore the mechanisms involved in pathophysiology associated with the disease. Twenty differentially expressed proteins can propose the mechanism behind continuous oxidative stress, which leads to damage to several cytosolic and membrane erythroid proteins. The preliminary studies using the immunome array approach identified 23 signature biomarkers. To explore the biological relevance of the shortlisted biomarkers, all 23 biomarkers were subjected to an Open Target Platform. Four (4) out of the 23 biomarkers were related to thalassemia subtypes, which suggests that there might be a potential association between autoantibody with disease stratification, or perhaps if tested in a larger cohort to disease severity. Interestingly, 19 of the 23 identified markers are novel and not known previously for their association with thalassemia. Autoantibodies to these 23 proteins were present in the serum of TDT patients compared to non-thalassemia controls. Therefore, evaluating autoantibody signatures from differentially reactive antigens associated with TDT could help us understand the disease's pathophysiology. Most of the identified biomarkers such as hematopoietic lineage cell-specific protein (HCLS1), Epidermal growth factor receptor substrate 15 (EPS15), drebrin like (DBNL), zinc finger HIT-type containing 3 (ZNHIT3), twinfilin actin-binding protein 2 (TWF2), Tropomyosin 1 (TPM1) are associated with cell growth regulation and apoptosis. Upregulated autoantibodies may cause red blood cells to be susceptible to apoptosis with these proteins, which may increase disease severity and the need for a transfusion. The differentially expressed proteins which are associated with thalassaemia mainly are haematopoietic lineage cell-specific protein (HCLS1), Tropomyosin 1(TPM1) and Epidermal growth factor receptor substrate 15 (EPS15). The results from the main study for the differential serum proteins using the proteomics approach identified 51 differentially expressed proteins in cases comparing controls. However, only 13 showed significant differential expression (p <0.05) that was statistically significant. Among these 13 proteins, all 13 had a fold change greater than 1. Protein-protein interactions (PPI) were analysed using STRING, online software. The PPI enrichment clusters show a local clustering coefficient of 0.803. A cluster was generated using Kmeans clustering. Proteins in this cluster include Alpha-1Bglycoprotein (A1BG), Angiotensinogen (AGT), Alpha-2-HS-glycoprotein (AHSG), Apolipoprotein A-IV (APOA4), Vitamin D-binding protein (GC), Hemopexin (HPX), Alpha-1-acid glycoprotein 1 (ORM1) Alpha-1-acid glycoprotein 2 (ORM2), Alpha-2- macroglobulin (A2M), Apolipoprotein A-I (APOA1) and Ceruloplasmin (CP). In the Reactome pathway analysis, proteins were mostly involved in haemostasis (platelet signalling, activation, and aggregation). In KEGG pathway analysis, the proteins were involved mainly in two pathways (i) fat digestion and absorption and (ii) vitamin digestion & absorption. ELISA validated the LCMS/MS results. In conclusion, in this study, we report that we elucidated the possible biological processes modulated by oxidative stress using the differentially expressed novel proteins and the associated pathways using comprehensive molecular and biocomputational analysis. Interestingly, most of the differentially expressed proteins in this study have not been yet reported in previous studies to be modulated by oxidative stress in TDT patients. This could pave the way for a more comprehensive approach to uncovering novel information and putative pathways.