Identification of a possible proteomic biomarker in Parkinson's disease: discovery and replication in blood, brain and cerebrospinal fluid.

Biomarkers to aid diagnosis and delineate the progression of Parkinson's disease are vital for targeting treatment in the early phases of the disease. Here, we aim to discover a multi-protein panel representative of Parkinson's and make mechanistic inferences from protein expression profiles within the broader objective of finding novel biomarkers. We used aptamer-based technology (SomaLogic®) to measure proteins in 1599 serum samples, 85 cerebrospinal fluid samples and 37 brain tissue samples collected from two observational longitudinal cohorts (the Oxford Parkinson's Disease Centre and Tracking Parkinson's) and the Parkinson's Disease Brain Bank, respectively. Random forest machine learning was performed to discover new proteins related to disease status and generate multi-protein expression signatures with potential novel biomarkers. Differential regulation analysis and pathway analysis were performed to identify functional and mechanistic disease associations. The most consistent diagnostic classifier signature was tested across modalities [cerebrospinal fluid (area under curve) = 0.74, P = 0.0009; brain area under curve = 0.75, P = 0.006; serum area under curve = 0.66, P = 0.0002]. Focusing on serum samples and using only those with severe disease compared with controls increased the area under curve to 0.72 (P = 1.0 × 10-4). In the validation data set, we showed that the same classifiers were significantly related to disease status (P < 0.001). Differential expression analysis and weighted gene correlation network analysis highlighted key proteins and pathways with known relationships to Parkinson's. Proteins from the complement and coagulation cascades suggest a disease relationship to immune response. The combined analytical approaches in a relatively large number of samples, across tissue types, with replication and validation, provide mechanistic insights into the disease as well as nominate a protein signature classifier that deserves further biomarker evaluation.

Neurodevelopmental dimensional assessment of young children at high genomic risk of neuropsychiatric conditions.

Background: Individuals with 22q11.2 deletion are at considerably increased risk of neurodevelopmental and psychiatric conditions. There have been very few studies investigating how this risk manifests in early childhood and what factors may underlie developmental variability. Insights into this can elucidate transdiagnostic markers of risk that may underlie later development of neuropsychiatric outcomes. Methods: Thirty two children with 22q11.2 Deletion Syndrome (22q11.2DS) (mean age = 4.1 [SD = 1.2] years) and 12 sibling controls (mean age = 4.1 [SD = 1.5] years) underwent in-depth dimensional phenotyping across several developmental domains selected as being potential early indicators of neurodevelopmental and psychiatric liability. Comparisons were conducted of the dimensional developmental phenotype of 22q11.2DS and sibling controls. For autistic traits, both parents and children were phenotyped using the Social Responsiveness Scale. Results: Young children with 22q11.2DS exhibited large impairments (Hedge's g ≥ 0.8) across a range of developmental domains relative to sibling controls, as well as high rates of transdiagnostic neurodevelopmental and psychiatric traits. Cluster analysis revealed a subgroup of children with 22q11.2DS (n = 16; 53%) in whom neurodevelopmental and psychiatric liability was particularly increased and who differed from other children with 22q11.2DS and non-carrier siblings. Exploratory analyses revealed that early motor and sleep impairments indexed liability for neurodevelopmental and psychiatric outcomes. Maternal autism trait scores were predictive of autism traits in children with 22q11.2DS (intraclass correlation coefficients = 0.47, p = 0.046, n = 31). Conclusions: Although psychiatric conditions typically emerge later in adolescence and adulthood in 22q11.2DS, our exploratory study was able to identify a range of early risk indicators. Furthermore, findings indicate the presence of a subgroup who appeared to have increased neurodevelopmental and psychiatric liability. Our findings highlight the scope for future studies of early risk mechanisms and early intervention within this high genetic risk patient group.

Collecting genetic samples and linked mental health data from adolescents in schools: protocol coproduction and a mixed-methods pilot of feasibility and acceptability.

OBJECTIVES: To coproduce a school-based protocol and examine acceptability and feasibility of collecting saliva samples for genetic studies from secondary/high school students for the purpose of mental health research. DESIGN: Protocol coproduction and mixed-methods feasibility pilot. SETTING: Secondary schools in Wales, UK. PARTICIPANTS: Students aged 11-13 years. PRIMARY AND SECONDARY OUTCOME MEASURES: Coproduced research protocol including an interactive science workshop delivered in schools; school, parental and student recruitment rates; adherence to protocol and adverse events; ability to extract and genotype saliva samples; student enjoyment of the science workshop and qualitative analysis of teacher focus groups on acceptability and feasibility. RESULTS: Five secondary schools participated in the coproduction phase, and three of these took part in the research study (eligible sample n=868 students). Four further schools were subsequently approached, but none participated. Parental opt-in consent was received from 98 parents (11.3% eligible sample), three parents (0.3%) actively refused and responses were not received for 767 (88.4%) parents. We obtained saliva samples plus consent for data linkage for 79 students. Only one sample was of insufficient quality to be genotyped. The science workshop received positive feedback from students. Feedback from teachers showed that undertaking research like this in schools is viewed as acceptable in principle, potentially feasible, but that there are important procedural barriers to be overcome. Key recommendations include establishing close working relationships between the research team and school classroom staff, together with improved methods for communicating with and engaging parents. CONCLUSIONS: There are major challenges to undertaking large-scale genetic mental health research in secondary schools. Such research may be acceptable in principle, and in practice DNA collected from saliva in classrooms is of sufficient quality. However, key challenges that must be overcome include ensuring representative recruitment of schools and sufficient parental engagement where opt-in parental consent is required.