Hypothesis-Driven Proteomic Data-Analysis of Plasma from Subjects in the At-Risk Mental State
Strong evidence now supports an association between systemic abnormalities and schizophrenia pathology. Furthermore, the clinical outcome in schizophrenia is significantly improved by early identification and treatment. These factors are driving the search for blood-based biomarkers for the disorder. Promising biomarker findings are hampered however by a relative lack of studies in prodromal psychosis, such as the at-risk mental state (ARMS). Poor replication of findings, particularly across highthroughput mass-spectrometry studies, is also problematic. A technique which has begun to emerge prominently in recent years, Data-Independent Analysis (DIA), has the ability to overcome limitations in reproducibility associated with more traditional Data-Dependent Acquisition (DDA) methods due to its more comprehensive sampling nature. Participants were recruited from the UK Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Here, DIA coupled to cutting-edge bioinformatics is used to 1) identify and 2) validate candidate biomarkers for the transition from ARMS to psychotic disorder (age 11 ARMS subjects who transitioned to psychotic disorder at age 18; n=19 versus those who did not transition; n=17). Biomarker candidates were derived from the top pathway implicated in the literature on drug-free schizophrenia, the acute-phase response, for identification (53 proteins; target list 1) and from the results of DDA conducted on the same samples, for validation (19 proteins; target list 2). Four acute-phase proteins (SERPING1, ITIH3, AGT, and APOA1) were found to be differentially expressed in ARMS subjects who transitioned to psychosis, in comparison to those who did not. Three DDA derived biomarker candidates were similarly validated (F5, APOE and ITIH3). Here the potential of this particular DIA workflow as a high-throughput tool for biomarker identification and validation in schizophrenia is demonstrated. The identification of a small biomarker panel consisting of proteins converging on the acute-phase response and coagulation pathway provides an insight into the development of psychotic disorders and an opportunity for future biomarker studies in prodromal patients to build on the current findings.
Health Research Board
First SupervisorProfessor David Cotter
Second SupervisorDr Jane English
Third SupervisorDr Melanie Föcking
Fourth SupervisorDr Gerard Cagney
CommentsA thesis submitted for the degree of Master of Science from the Royal College of Surgeons in Ireland in 2016.
Published CitationSabherwal S. Hypothesis-Driven Proteomic Data-Analysis of Plasma from Subjects in the At-Risk Mental State [MSc Thesis]. Dublin: Royal College of Surgeons in Ireland; 2016.
- Master of Science (MSc): Research