Abstract WP133: Sex Differences In The Human Intracerebral Hemorrhage Peripheral Blood Transcriptome Implicate Differential Immune And Inflammatory Responses
Bibliographic record
Abstract
Sex differences in immune and inflammatory pathways have been shown in health and disease. However, little research has been done on sex differences following human Intracerebral Hemorrhage (ICH). We sought to unveil transcriptome differences in blood between Male (M) and Female (F) ICH responses. We evaluated 33 ICH patients and 33 vascular risk factor matched controls (VRFC), 9F and 24M each. Peripheral blood expression of 21,175 genes was analyzed at the co-expression network level with WGCNA - separate F (F-ICH and F-VRFC) and M (M-ICH and M-VRFC) networks generated; and per gene level (ANCOVA: Age, Time, and Sex*Dx (Diagnosis)). Five F (F-6, F-20, F-21, F-19, F-5) and 2 M (M-32, M-26) WGCNA modules were significant to Dx (p < 0.05) (Fig 1A). 105 genes were significant for the direct comparison (F-ICH vs M-ICH p < 0.05, |FC| > 1.2; Sex*Dx FDR < 0.2), which separated Sex*Dx groups (Fig 1B). 1,425 genes were differentially expressed in F-ICH (F-ICH vs F-VRFC p < 0.05, |FC| > 1.2; Sex*Dx FDR < 0.2) and 421 in M-ICH (M-ICH vs M-VRFC p < 0.05, |FC| > 1.2; Sex*Dx FDR < 0.2) (Fig 1C). F-ICH response was enriched in Monocyte and T Cell Specific genes and M-ICH in B Cell and Erythroblast specific genes; both were enriched in Neutrophil specific genes (Fig 1A). Overall, F modules and gene lists were significantly enriched in 236 GO terms (FDR < 0.1) and M modules in 55; 20 were common (Fig 1D). The ICH response unique to F-ICH included Inflammatory Response, T Cell Activation, Autophagy, Apoptotic Process, and RNA Splicing. M-ICH unique included B Cell Receptor Signaling, Immunoglobulin Receptor Binding, Antigen Binding, Complement Activation, and Receptor Mediated Endocytosis. Common responses included Innate Immune Response, Blood Coagulation, and Fc-ã Receptor Signaling Involved in Phagocytosis (Fig 1E). We found sex differences in ICH transcriptome responses in human peripheral blood. These implicate specific cell types in each sex that could represent novel sex-specific treatment targets.
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 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 | 0.000 | 0.001 |
| 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) | 0.006 | 0.001 |
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".