ArticleBlood advances2025
Molecular inflammatory expression profiles associated with the frequency of pain in individuals with sickle cell disease.
Article in Blood advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Beyond Pain: A Pilot Study of Neurodegenerative and Mitochondrial Pathway Alterations in Sickle Cell Disease Using Platelet Proteomics.Medical sciences (Basel, Switzerland) · 2026Article
- Dyslipidemia is a metabolic hallmark of acute pain in sickle cell disease.medRxiv : the preprint server for health sciences · 2026Article
- Article
- Machine learning identifies PPARG as a diagnostic biomarker for sepsis linked to CD14/NF-κB signaling: integrated transcriptomics and experimental validation.Frontiers in cellular and infection microbiology · 2026Article
- Biomarker signatures for sickle cell pain.Blood advances · 2025Article
Corrections and comments
- Commented on by
Authors and funding
8 authors.
Funding
Abstract
abstractPain is the most common complication of sickle cell disease (SCD). The underlying biology of SCD pain is not well understood, which is a barrier to novel, effective analgesic and preventive therapies. A wide variability in the phenotypic expression of pain exists among individuals with SCD, despite the inheritance of a similar defective hemoglobin gene. This interindividual pain variability further complicates the ability to understand the biology and effectively treat pain. We sought to discover a biological signature comprising differentially expressed genes unique to SCD that could differentiate between individuals with varied pain frequency. We conducted plasma-induced transcription analysis from 149 individuals with SCD and 60 Black individuals without SCD from multiple sites. We discovered 3028 differentially expressed genes that underwent weighted gene coexpression network analysis to distinguish gene modules significantly associated with pain frequency. We identified 524 genes, significantly associated with pain frequency (≥|0.3| and P < .05), that were further analyzed using the "database for annotation, visualization, and integrated discovery" (DAVID) tool to delineate the biological pathways associated with these genes. The highest ranked Gene Ontology process from DAVID was inflammatory response (P = 1.67E-12) and many related pathways were enriched (eg, response to lipopolysaccharide, and chemokine and cytokine signaling). The top 10 hub genes identified within our biological signature were TNF, CCL2, ITGAM, ITGAX, ICAM1, CCR5, CXCL2, IFNG, CCR1, and CXCL3. Future work should focus on further validating this signature and investigating the potential targets uncovered for their mechanistic and potentially therapeutic role in SCD pain.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.