Human leukocyte antigen (HLA) mismatching, particularly with HLA-DQ, significantly impacts the development of donor-specific antibodies (DSA) and transplant outcomes. HLA-DQ antibodies are highly immunogenic and detrimental, necessitating advanced high-resolution HLA typing to improve mismatch assessment and clinical risk evaluation. Traditional serological or low-resolution typing often misclassifies mismatches, leading to inaccuracies in assessing immunogenicity and predicting outcomes. Emerging molecular mismatch algorithms refine immunogenicity assessments by analyzing amino acid differences and structural interactions. These tools show promise for personalizing transplant protocols but have limitations, such as variability in predicting individual patient outcomes. Immunogenicity of mismatches also depends on evolutionary divergence and specific amino acid differences, with studies revealing that certain evolutionary lineages and polymorphisms influence T-cell alloreactivity and DSA development. Complexities in HLA-DQ protein expression, including combinatorial diversity of heterodimers and inter-isotypic heterodimers, further complicate risk evaluation. Expression levels, influenced by tissue specificity and inflammatory stimuli, and alternative splicing of HLA-DQ transcripts add additional layers of variability. Future clinical applications, enabled by high-resolution HLA typing, may include refined graft selection, improved DSA monitoring, and individualized therapy. However, understanding the precise mechanisms of HLA-DQ immunogenicity remains a priority for advancing transplantation science and enhancing patient outcomes.