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Record W4388594227 · doi:10.1101/2023.11.10.23298334

Elevated Plasma Complement Factors in <i>CRB1</i> -associated Inherited Retinal Dystrophies

2023· preprint· en· W4388594227 on OpenAlexaff
Lude Moekotte, Joke de Boer, Sanne Hiddingh, Aafke de Ligt, Xuan‐Thanh‐An Nguyen, Carel B. Hoyng, Chris F. Inglehearn, Martin McKibbin, Tina M. Lamey, Jennifer A. Thompson, Fred K. Chen, Terri L. McLaren, Alaa AlTalbishi, Daan M. Panneman, Erica G. M. Boonen, Sandro Banfi, Béatrice Bocquet, Isabelle Meunier, Robert K. Koenekoop, Monika Ołdak, Carlo Rivolta, Lisa Roberts, Raj Ramesar, R. Strupaite-Sileikiene, Susanne Kohl, G. Jane Farrar, Marion van Vugt, Jessica van Setten, Susanne Roosing, L. Ingeborgh van den Born, Camiel J.F. Boon, Maria M. van Genderen, Jonas J. W. Kuiper

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsMcGill University Health Centre
FundersEuropean CommissionSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsComplement factor IBiologyFactor HGenotypeComplement systemComplement component 3CohortComplement factor BSerpinInternal medicineAlleleImmunologyGeneticsMedicineGeneAntibodyAlternative complement pathway

Abstract

fetched live from OpenAlex

Abstract Objective To determine the profile of inflammation-related proteins and complement system factors in serum of CRB1 -associated inherited retinal dystrophies ( CRB1 -IRDs). Design A case-control study. Subjects, Participants, and/or Controls A cohort of 30 Dutch CRB1 -IRD patients and 29 Dutch healthy controls (HC) (Cohort I), and a second cohort of 123 CRB1 -IRD patients from 14 countries and 1292 controls (Cohort II) were used in this study. Methods Quantitative 370-plex targeted proteomics in blood plasma and genotyping of the single nucleotide variant (SNV) rs7535263 in the CFH gene. Main Outcome Measures Plasma concentrations of inflammation-related proteins and the genotype of the SNV rs7535263. Results CRB1 -IRD patients showed increased plasma levels of complement system and coagulation cascade proteins compared to healthy controls. Complement Factor I [CFI], Serpin Family D1 [SERPIND1], and Complement Factor H [CFH] were significantly elevated (q<0.05, adjusted for age and sex), which correlated (Pearson’s correlation coefficient >0.6) with higher levels of plasma Complement Component 3 [C3] (q = 0.064). The most enriched pathway in patients was the “Complement cascade” (R-HSA-166658, Padj = P = 3.03 × 10 -15 ). An analysis of the genotype of CFH variant rs7535263, which is in close physical proximity to the CRB1 gene and is associated with other retinal conditions by influencing plasma complement levels, revealed significantly skewed allele distribution specifically in Dutch patients (A allele of rs7535263, odds ratio (OR) [95%CI = 2.85 [1.35-6.02], P = 6.19 × 10 -3 ), but not in a global case-control cohort ( P = 0.12). However, CRB1 missense variants that are common in patients display strong linkage disequilibrium (LD) with rs7535263 in CFH in the UK Biobank (D’ = 0.97 for p.(Cys948Tyr); D’ = 1.0 for p.(Arg764Cys)), indicating that genetic linkage may influence plasma complement factor levels in CRB1 -IRD patients. After accounting for the CFH genotype in the proteomic analyses, we also detected significantly elevated plasma levels of Complement Factor H Related 2 [CFHR2] in CRB1 -IRD patients (q = 0.04). Conclusions CRB1 -IRDs are characterized by changes in plasma levels of complement factors and proteins of the innate immune system, which is influenced by common functional variants in the CFH-CFHR locus. This indicates that innate immunity is implicated in CRB1 -IRDs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.065
GPT teacher head0.317
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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