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Record W4389937002 · doi:10.1101/2023.12.18.23300119

Type 1 reaction leprosy patients display distinct immune-regulatory capacity before onset of symptoms

2023· preprint· en· W4389937002 on OpenAlexafffund
Wilian Correa-Macedo, Monica Dallmann-Sauer, Marianna Orlova, Jérémy Manry, Vinicius M. Fava, Nguyễn Thu Hương, Nguyen Ngoc Ba, Nguyen Van Thuc, Vu Hong Thai, Erwin Schurr

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldMedicine
TopicLeprosy Research and Treatment
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersMcGill University
KeywordsMycobacterium lepraeLeprosyImmune systemTranscriptomeBiologyImmunologyMacrophageIn vitroGeneticsGene expressionGene

Abstract

fetched live from OpenAlex

Abstract Leprosy is a chronic disease of the skin and peripheral nerves caused by Mycobacterium leprae . A major public health and clinical problem are leprosy reactions, which are inflammatory episodes that often contribute to nerve damage and disability. Type I reversal reactions (T1R) can occur after microbiological cure of leprosy and affect up to 50% of leprosy patients. Early intervention to prevent T1R and, hence, nerve damage, is a major focus of current leprosy control efforts. In a prospective study, we enrolled and collected samples from 32 leprosy patients before the onset of T1R. Whole blood aliquots were challenged with M. leprae sonicate or media and total RNA was extracted. After a three-year follow-up, the transcriptomic response was compared between cells from 22 patients who remained T1R-free and 10 patients who developed T1R during that period. Our analysis focused on differential transcript (i.e. isoform) expression and usage. Results showed that, at baseline, cells from T1R-destined and T1R-free subjects had no main difference in their transcripts expression and usage. However, the cells of T1R patients displayed a transcriptomic immune response to M. leprae antigens that was significantly different from the one of cells from leprosy patients who remained T1R-free. Transcripts with significantly higher upregulation in the T1R-destined group, compared to the cells from T1R-free patients, were enriched for pathways and GO terms involved in response to intracellular pathogens, apoptosis regulation and inflammatory processes. Similarly, transcript usage analysis pinpointed different transcript proportions in response to the in-vitro challenge of cells from T1R-destined patients. Hence, transcript usage in concert with transcript expression suggested a dysregulated inflammatory response including increased apoptosis regulation in the peripheral blood cells of T1R-destined patients before the onset of T1R symptoms. Combined, these results provided detailed insight into the pathogenesis of T1R. Author Summary The prevention and clinical management of type 1 reactions (T1R) remain an important unmet need to reduce nerve damage in leprosy patients. It is not known why 30-50% of leprosy patients will develop T1R. This knowledge gap underlies the need for a better mechanistic understanding of T1R that could lead to biomarker candidates to identify leprosy patients who are at high risk of developing T1R. Here, we used a prospective design in which leprosy patients were enrolled before the onset of T1R.Whole blood samples were obtained at enrollment, aliquots were left unstimulated or were stimulated M. leprae antigens and total RNA was extracted. Patients were followed for three years at which time 10 out of 32 participants had developed T1R. Subsequent transcript expression and usage analyses revealed that groups differed little in their isoform landscape at baseline. Following stimulation, transcriptomic response differences became pronounced. Transcripts with higher response in T1R group preferentially involved genes of intracellular defense and inflammatory pathways. Among these transcripts, non-coding ones had higher frequency in T1R. Our study provided new insights into the T1R pathogenesis by suggesting a role for non-coding transcripts into the immune dysregulations of T1R and providing additional candidate genes and their isoforms to be further investigated.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.034
GPT teacher head0.299
Teacher spread0.265 · 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 teacher head, not a consensus.

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

Citations2
Published2023
Admission routes2
Has abstractyes

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