Parkinson’s disease risk factors are expressed at brain barriers
Bibliographic record
Abstract
Abstract Parkinson’s disease (PD) is characterized by the selective loss of dopaminergic neurons in the substantia nigra pars compacta , but whether its etiology is cell autonomous remains unclear. Increasing evidence implicates the blood-central nervous system (CNS) barriers in disease development, highlighting the importance of identifying genetic risk factors linked to cells forming the cerebrovasculature to advance this emerging area of research. The objective of this study is to identify PD genetic risk factors associated with blood-brain (BBB) and blood-cerebrospinal fluid (BCSFB) barriers, and to validate protein localization in human tissue and experimental models. To do so, we integrated genome-wide association studies and single nuclei RNA-sequencing datasets from the human postmortem substantia nigra (SN), midbrain, or cortical samples from control and PD donors. An in-depth bioinformatics analysis identified genes enriched in cell types that form the multicellular architecture of brain barriers, including CAVIN2 , ANXA1 , ANO2 , and LRP1B . We further validated whether corresponding proteins were present in cell types associated with the blood-CNS barriers in human and mouse post-mortem tissues, as well as in iPSC-differentiated cells and choroid plexus organoids. Results showed that quantifying the proportion of endothelial cells expressing PD-related genes was under-evaluated at the transcript level compared to immunofluorescence analyses. In addition, we observed that CAVIN2 and ANXA1 proteins were more abundant at the vasculature of the substantia nigra vs. cortex, and CAVIN2 protein levels were reduced in PD vs. control human postmortem tissues. In contrast, the investigation of mouse postmortem samples demonstrated that the CAVIN2 protein is only present in a subset of mouse blood vessels, compared to nearly all vessels in human tissue. Similarly, mouse ANXA1 protein localizes to dopaminergic neurons of the substantia nigra and not at the vasculature, as seen in human tissue. The primary outcome of this study is the identification of PD-relevant risk genes specifically expressed at brain barriers and enriched in PD-relevant brain regions. The secondary outcome is the demonstration of poor transcript-protein correlation in – at least – a subset of PD risk factors, and a low interspecies conservation of protein localization for the selected candidates. In conclusion, the BBB and BCSFB may represent understudied contributors to PD, endothelial-specific proteins appear differentially regulated compared to transcripts, and experimental models require comprehensive validation to ensure relevance to the human condition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".