Metadata matters: enhancing TBI proteomics

Meta-analysis is a cornerstone of scientific research, enabling the synthesis of data across multiple studies to derive comprehensive conclusions and gain insights into connections between the different studies. However, the utility of meta-analyses is significantly compromised by the lack of comprehensive metadata. This study explores the importance of detailed metadata in proteomics meta-analyses, with a focus on understanding the proteomic alterations in Traumatic Brain Injury (TBI).

TBI is a complex condition involving a wide range of pathological processes and diverse proteomic changes. Despite being a leading cause of morbidity and mortality worldwide, its underlying molecular mechanisms remain poorly understood. To address this, a meta-analysis of publicly available proteomic TBI datasets was designed. We conducted a systematic review of proteomics TBI studies, assessing the quality and completeness of their metadata. Our analysis revealed significant deficiencies in metadata reporting, including the absence of and inconsistencies in study designs, sample characteristics, and data processing methods that were uploaded to the PRIDE repository. These gaps hinder accurate meta-analyses, leading to reduced reproducibility of findings.

By addressing these deficiencies and adhering to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles, the proteomics community can significantly improve the transparency, reproducibility, and overall quality of meta-analyses. Despite the lack of comprehensive metadata, our study identified key TBI proteins present in the datasets at an identification level. Enhanced metadata practices would allow us to analyze the datasets at a quantification level, thereby advancing our understanding of TBI and facilitating the translation of proteomic discoveries into clinical applications.

In conclusion, prioritizing meticulous metadata collection and reporting (like enforcing the SDRF or MIAPE initiatives) is essential for unlocking deeper insights, identifying reliable biomarkers, and developing more effective diagnostic and therapeutic strategies. This study exemplifies the transformative potential of data integration and bioinformatics in translating raw proteomic data into actionable biological knowledge, with significant implications for advancing TBI research and ultimately improving patient outcomes.

Keywords: Meta-analysis, Metadata, Traumatic Brain Injury, Data Integration, Bioinformatics, Reproducibility