Complement dysregulation and Alzheimer's disease in Down syndrome
Bibliographic record
Abstract
INTRODUCTION: Down syndrome (DS) is associated with immune dysregulation and a high risk of early onset Alzheimer's disease (AD). Complement is a key part of innate immunity and driver of pathological inflammation, including neuroinflammation in AD. Complement dysregulation has been reported in DS; however, the pattern of dysregulation and its relationship to AD risk is unclear. METHODS: Plasma levels of 14 complement biomarkers were measured in 71 adults with DS and 46 controls to identify DS-associated dysregulation; impact of apolipoprotein E (APOE) ε4 genotype, single nucleotide polymorphisms (SNPs) in CLU and CR1, and dementia on complement biomarkers was assessed. RESULTS: Plasma levels of complement activation products (TCC, iC3b), proteins (C1q, C3, C9), and regulators (C1 inhibitor, factor H, FHR4, clusterin) were significantly elevated in DS versus controls while FI and sCR1 were significantly lower. In DS with AD (n = 13), C3 and FI were significantly decreased compared to non-AD DS (n = 58). Neither APOE genotype nor CLU SNPs impacted complement levels, while rs6656401 in CR1 significantly impacted plasma sCR1 levels. CONCLUSIONS: Complement is dysregulated in DS, likely reflecting the generalized immune dysregulation state; measurement may help identify inflammatory events in individuals with DS. Complement biomarkers differed in DS with and without AD and may aid diagnosis and/or prediction. HIGHLIGHTS: Complement is significantly dysregulated in plasma of people with DS who show changes in levels of multiple complement proteins compared to controls. People with DS and dementia show evidence of additional complement dysregulation with significantly lower levels of C3 and factor I compared to those without dementia. rs6656401 in CR1 was associated with significantly elevated sCR1 plasma levels in DS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".