C1QTNF8 Antibody

What is C1QTNF8/CTRP8 and what biological functions has it been associated with?

C1QTNF8, also known as CTRP8 or Complement C1q tumor necrosis factor-related protein 8, belongs to the C1q/TNF-related protein family. This protein has a calculated molecular weight of approximately 27,685 Da and contains characteristic structural domains common to the C1q/TNF family . C1QTNF8 shares structural similarities with other CTRP family members, featuring a globular C1q domain that mediates various protein-protein interactions in biological systems.

The protein contains distinct regions including:

• A signal peptide at the N-terminus

• A variable domain

• A collagen-like domain

• A C-terminal globular domain characteristic of the C1q/TNF family

Though its complete functional characterization remains ongoing, current research suggests roles in inflammation modulation, metabolic regulation, and potential involvement in tumor-related pathways. The protein has been detected in several human tissues, with expression patterns that suggest tissue-specific functions .

What applications are validated for C1QTNF8 antibodies according to manufacturer specifications?

Based on the available antibody validation data, C1QTNF8 antibodies have been validated for multiple research applications with varying levels of optimization:

*Validation varies by specific antibody product

Most commercially available C1QTNF8 antibodies are rabbit polyclonal antibodies generated against synthesized peptides derived from the C-terminal region of human CTRP8 . For optimal results, researchers should perform preliminary dilution series experiments to determine the optimal concentration for their specific experimental conditions and tissue/cell types .

What species reactivity is available for C1QTNF8 antibodies?

The search results indicate various species reactivity profiles for different C1QTNF8 antibody products:

*Antibody availability unclear from search results, but ELISA kits are available

When selecting an antibody for cross-species applications, researchers should carefully evaluate the sequence homology of the target epitope across species of interest and review validation data specific to their experimental model .

How can researchers validate the specificity of C1QTNF8 antibodies for their experimental systems?

Validating antibody specificity is critical for ensuring reliable experimental results. For C1QTNF8 antibodies, a comprehensive validation approach should include:

Positive and Negative Controls:

• Positive controls: Tissues or cell lines with known C1QTNF8 expression

• Negative controls:

  • Primary antibody omission

  • Tissues from C1QTNF8 knockout models (if available)

  • Use of blocking peptides that were used as immunogens

Blocking Peptide Verification:
Many commercial C1QTNF8 antibodies are raised against synthetic peptides from the C-terminal region of human CTRP8. Blocking peptides can be purchased separately and used for competitive inhibition assays to confirm specificity . Incubate the antibody with excess blocking peptide prior to application to validate binding specificity.

Multiple Detection Methods:
Researchers should verify target detection using at least two independent methods:

• Western blot to confirm expected molecular weight (~27.7 kDa)

• Immunohistochemistry/immunofluorescence to confirm expected cellular localization

• ELISA with recombinant proteins to confirm binding specificity

Knockout/Knockdown Verification:
When possible, use genetic approaches (siRNA, CRISPR) to create C1QTNF8-deficient samples and confirm loss of signal with the antibody.

What are the optimal experimental conditions for using C1QTNF8 antibodies in immunohistochemistry applications?

Based on the manufacturer recommendations and general best practices for IHC, the following protocol represents an optimized approach for C1QTNF8 detection:

Tissue Preparation:

• Fixation: 10% neutral buffered formalin (24-48 hours)

• Processing: Standard paraffin embedding

• Sectioning: 4-6 μm thickness

Antigen Retrieval:

• Heat-induced epitope retrieval (HIER) using citrate buffer (pH 6.0) or EDTA buffer (pH 9.0)

• Pressure cooker method: 125°C for 3 minutes or 95-100°C for 20 minutes

Staining Protocol:

• Deparaffinization and rehydration

• Antigen retrieval as above

• Peroxidase blocking: 3% H₂O₂ for 10 minutes

• Protein blocking: 5% normal serum for 30 minutes

• Primary antibody incubation: Anti-C1QTNF8 at 1:100-1:300 dilution overnight at 4°C

• Secondary antibody incubation: HRP-conjugated anti-rabbit IgG (30 minutes at room temperature)

• Visualization: DAB substrate

• Counterstaining: Hematoxylin

• Dehydration and mounting

Critical Controls:

• Negative control: Rabbit IgG isotype control at equivalent concentration

• Absorptive control: Pre-incubate primary antibody with blocking peptide

The specific dilution should be optimized for each tissue type and experimental condition through preliminary titration experiments .

How should researchers interpret and troubleshoot variable results when using C1QTNF8 antibodies?

When encountering variable or unexpected results with C1QTNF8 antibodies, a systematic troubleshooting approach should be followed:

For Weak or Absent Signal:

For High Background or Non-specific Staining:

For Inconsistent Results Across Experiments:

• Standardize all protocol conditions including:

  • Tissue fixation duration

  • Antigen retrieval parameters

  • Incubation times and temperatures

  • Reagent concentrations

• Create a standard positive control to include in all experiments

• Consider lot-to-lot variations in antibody performance and document lot numbers used

Remember that polyclonal antibodies, which are common for C1QTNF8 detection, can show greater variation than monoclonal antibodies .

How can researchers effectively use C1QTNF8 antibodies in multiplex immunofluorescence studies?

Multiplex immunofluorescence with C1QTNF8 antibodies requires careful planning to avoid cross-reactivity and optimize signal detection:

Protocol Optimization:

• Antibody Panel Design:

  • Select primary antibodies from different host species when possible

  • If using multiple rabbit antibodies, consider sequential detection with tyramide signal amplification (TSA)

  • When pairing with other antibodies, prioritize validated combinations

• C1QTNF8 Antibody Considerations:

  • Use at 1:50-1:150 dilution range for immunofluorescence

  • Select appropriate fluorophore based on expected expression level (brighter fluorophores for lower expression)

  • Consider signal amplification methods for weak signals

• Multiplex Protocol:

  • For sequential staining:

    • Complete first primary-secondary antibody cycle

    • Microwave treatment to strip antibodies (if using same species antibodies)

    • Proceed with next primary-secondary combination

  • For simultaneous staining:

    • Verify absence of cross-reactivity between antibodies

    • Use highly cross-adsorbed secondary antibodies

• Controls:

  • Single-stain controls for each antibody

  • Fluorescence minus one (FMO) controls

  • Isotype controls

• Image Acquisition and Analysis:

  • Use spectral unmixing for overlapping fluorophores

  • Employ automated quantification software for unbiased analysis

  • Include calibration standards for intensity normalization

This approach allows researchers to explore the relationship between C1QTNF8 and other proteins of interest in complex tissue contexts while minimizing technical artifacts.

What strategies maximize sensitivity when performing ELISA with C1QTNF8 antibodies?

ELISA represents one of the most well-validated applications for C1QTNF8 antibodies, with recommended dilutions reaching 1:10000 . To maximize sensitivity:

Sandwich ELISA Optimization:

• Antibody Selection:

  • Use a capture antibody targeting a different epitope than the detection antibody

  • Consider using a monoclonal antibody paired with a polyclonal for maximum epitope coverage

• Protocol Enhancements:

  • Coating buffer optimization: Compare carbonate buffer (pH 9.6) vs. PBS (pH 7.4)

  • Extended antibody incubation: 4°C overnight vs. room temperature

  • Blocking optimization: Compare BSA, casein, and commercial blockers

  • Sample diluent optimization: Include 0.1-0.5% detergent to reduce background

• Signal Amplification:

  • Avidin-biotin amplification system

  • Tyramide signal amplification

  • Poly-HRP detection systems

• Sensitivity Benchmarks:
  Commercial C1QTNF8 ELISA kits report sensitivity of 0.1 ng/mL with detection ranges of:

  • Human: Variable by kit

  • Mouse: 1.0-25 ng/mL

  • Rat: 2.5-50 ng/mL

• Sample Preparation:

  • Serum/plasma: 1:2 to 1:10 dilution depending on expression

  • Cell culture supernatants: Concentrate if necessary

  • Tissue homogenates: Optimize extraction buffers with protease inhibitors

By combining these approaches, researchers can achieve detection sensitivity in the pg/mL range while maintaining specificity.

How do researchers design validation studies for newly developed C1QTNF8 antibodies?

Developing comprehensive validation protocols for new C1QTNF8 antibodies ensures reliability and reproducibility:

Validation Framework:

• Epitope Characterization:

  • Determine exact epitope sequence through epitope mapping

  • Assess epitope conservation across species

  • Evaluate potential cross-reactivity with other CTRP family members

• Specificity Assessment:

  • Western blot against recombinant C1QTNF8 and cell/tissue lysates

  • Competitive binding assays with purified protein

  • Immunoprecipitation followed by mass spectrometry

  • Testing in knockout/knockdown models

• Application-Specific Validation:

  Application	Validation Criteria	Acceptance Metrics
  Western Blot	Single band at expected MW	Single band at ~27.7 kDa
  IHC	Specific staining pattern	Concordant with mRNA expression
  IF	Subcellular localization	Appropriate distribution
  ELISA	Standard curve linearity	R² > 0.98, CV < 10%

• Reproducibility Assessment:

  • Intra-assay variation: CV < 10%

  • Inter-assay variation: CV < 15%

  • Lot-to-lot consistency testing

• Documentation:

  • Detailed protocols for each validated application

  • Recommended positive controls

  • Optimal working concentrations

  • Images demonstrating specific staining patterns

This validation framework provides confidence in antibody performance across multiple experimental contexts and ensures data reliability.

What is the significance of C1QTNF8/CTRP8 in current cancer research?

While the search results don't provide specific information on C1QTNF8's role in cancer, we can infer from related C1q/TNF family members that this protein may have significance in cancer biology. Based on structural similarities to other family members:

C1QTNF8 may be involved in:

• Tumor microenvironment modulation

• Cancer cell signaling pathways

• Inflammatory processes related to tumor progression

Researchers investigating C1QTNF8 in cancer contexts should:

• Assess expression patterns across cancer types and stages

• Investigate correlation with clinical outcomes

• Explore functional mechanisms through knockdown/overexpression studies

• Identify potential interacting partners in cancer cells

As research on C1QTNF8 is evolving, antibody-based detection methods provide valuable tools for characterizing its expression and localization in cancer tissues and cells.

How can researchers effectively use C1QTNF8 antibodies in flow cytometry applications?

While flow cytometry applications weren't specifically mentioned in the search results for C1QTNF8 antibodies, researchers can adapt standard protocols:

Protocol Development:

• Sample Preparation:

  • Cell suspension: 1×10⁶ cells per sample

  • Fixation: 4% paraformaldehyde for 15 minutes

  • Permeabilization: 0.1% Triton X-100 (if intracellular target)

• Staining Protocol:

  • Blocking: 5% normal serum, 30 minutes

  • Primary antibody: Anti-C1QTNF8 at 1:50-1:200 dilution, 1 hour

  • Washing: 3× with PBS + 0.1% BSA

  • Secondary antibody: Fluorophore-conjugated anti-rabbit IgG, 30 minutes in dark

  • Final washing: 3× with PBS + 0.1% BSA

• Controls:

  • Unstained cells

  • Secondary antibody only

  • Isotype control

  • Positive control (cell line with known expression)

• Optimization Steps:

  • Titrate antibody to determine optimal concentration

  • Test multiple fixation and permeabilization conditions

  • Compare direct conjugation vs. secondary detection

• Analysis Considerations:

  • Gate on viable cells first

  • Analyze shift in fluorescence intensity compared to controls

  • Consider dual staining with lineage markers

This approach allows researchers to quantify C1QTNF8 expression at the single-cell level and identify specific cell populations expressing the protein.

What methodological approaches help resolve discrepancies in C1QTNF8 detection between different assay platforms?

When researchers encounter discrepancies in C1QTNF8 detection across different techniques, methodological reconciliation approaches include:

Systematic Discrepancy Analysis:

• Epitope Accessibility Assessment:
  Different methods expose different protein epitopes:

  • Western blot: Denatured protein exposes linear epitopes

  • IHC/IF: Partially preserved structure with some epitope masking

  • ELISA: Depending on format, may detect native or denatured protein

• Cross-Platform Validation Strategy:

  Primary Method	Validation Method	Resolution Approach
  Western Blot	IHC negative	Try reduced antigen retrieval; protein may be denatured in WB
  IHC positive	WB negative	Try native gel conditions; epitope may require folded structure
  ELISA positive	WB/IHC negative	Verify specificity with blocking peptide; check cross-reactivity

• Protein Variant Consideration:

  • Alternative splicing producing different protein isoforms

  • Post-translational modifications affecting epitope recognition

  • Sample preparation differences affecting protein conformation

• Antibody Characteristics:

  • Batch-to-batch variation in polyclonal antibodies

  • Different epitope targets between antibodies

  • Varying affinities across applications

• Reconciliation Experiments:

  • Immunoprecipitation followed by mass spectrometry

  • Multiple antibody validation with different epitope targets

  • Genetic manipulation (overexpression/knockdown) with multiple detection methods

This systematic approach helps resolve apparent contradictions between methods and provides a more complete understanding of C1QTNF8 biology.

How are C1QTNF8 antibodies being utilized in studies of metabolic disorders?

Based on the structural similarity of C1QTNF8 to other C1q/TNF family members that are known adipokines, researchers might investigate its potential role in metabolic regulation:

Research Applications:

• Tissue Expression Analysis:

  • Comparing C1QTNF8 expression in adipose tissue between lean and obese subjects

  • Evaluating expression changes during adipocyte differentiation

  • Examining regulation under different metabolic conditions

• Functional Studies:

  • Investigating effects on glucose metabolism in cell culture models

  • Assessing impact on insulin signaling pathways

  • Exploring potential anti-inflammatory properties in adipose tissue

• Clinical Correlations:

  • Measuring circulating C1QTNF8 levels in patients with metabolic syndrome

  • Correlating expression with clinical parameters like BMI, insulin resistance, and lipid profiles

  • Evaluating changes with therapeutic interventions

These approaches could provide insights into whether C1QTNF8, like other family members, plays a role in metabolic homeostasis and could represent a potential biomarker or therapeutic target.

What considerations are important when using C1QTNF8 antibodies for tissue microarray analysis?

When applying C1QTNF8 antibodies to tissue microarray (TMA) analysis, researchers should consider:

TMA-Specific Protocol Adaptations:

• Pre-Analytical Variables:

  • Core size: Recommend 1.0-1.5 mm cores for adequate representation

  • Core number: Minimum 2-3 cores per case to account for heterogeneity

  • Control tissues: Include positive, negative, and gradient controls on each TMA

• Staining Optimization:

  • Perform initial titration on whole sections before TMA application

  • Consider automated staining platforms for consistency across multiple TMAs

  • Adjust primary antibody concentration (typically 1:50-1:200 range)

  • Standardize antigen retrieval conditions

• Scoring and Analysis:

  • Develop clear scoring criteria for C1QTNF8 expression

  • Consider digital image analysis for objective quantification

  • Evaluate both staining intensity and percentage of positive cells

  • Account for potential heterogeneity across cores

• Quality Control:

  • Include replicate cores to assess reproducibility

  • Analyze inter-observer and intra-observer variation

  • Document lot numbers and detailed protocols

• Data Integration:

  • Correlate with other molecular markers

  • Integrate with clinical data for meaningful associations

  • Consider multivariate analysis to identify independent associations

This approach ensures reliable and reproducible assessment of C1QTNF8 expression across large sample sets, facilitating biomarker discovery and validation.

How can researchers address non-specific binding issues with C1QTNF8 antibodies?

Non-specific binding represents a common challenge when working with antibodies, including those targeting C1QTNF8:

Comprehensive Troubleshooting Strategy:

• Background Reduction Protocol:

  Issue	Intervention	Implementation
  High background in IHC/IF	Enhanced blocking	Extend blocking to 60 minutes; use 5-10% serum plus 1% BSA
  Non-specific bands in WB	Stringent washing	Increase TBST concentration to 0.1-0.2% Tween-20; longer washes
  Cross-reactivity	Antibody pre-absorption	Pre-incubate with tissues/lysates from non-target species

• Application-Specific Solutions:

  For Western Blot:

  • Increase membrane blocking time to 2 hours

  • Use casein-based blockers instead of milk for problematic antibodies

  • Increase antibody dilution (1:1000-1:5000)

  • Add 0.1-0.5% nonfat dry milk to antibody diluent

  For IHC/IF:

  • Include avidin/biotin blocking for biotin-based detection systems

  • Add 0.1-0.3 M NaCl to antibody diluent to reduce ionic interactions

  • Use protein-free blockers if endogenous immunoglobulins are an issue

  • Consider enzymatic pre-treatment with neuraminidase if glycosylation is causing issues

• Validation Controls:

  • Peptide competition assays to confirm specificity

  • Isotype control at equivalent concentration

  • Secondary antibody only controls

  • Gradient of primary antibody concentrations

By implementing these strategies, researchers can significantly improve signal-to-noise ratio and ensure specific detection of C1QTNF8.

What are the most effective sample preparation methods for detecting C1QTNF8 in complex biological specimens?

Optimal sample preparation is crucial for reliable C1QTNF8 detection across different biological specimens:

Tissue-Specific Extraction Protocols:

• For Protein Extraction (Western Blot/ELISA):

  Sample Type	Extraction Buffer	Optimization Steps
  Cell Culture	RIPA buffer + PI*	Gentle lysis (avoid excessive sonication)
  Tissue Samples	Tissue PE buffer + PI*	Flash-freeze in liquid N₂; cryopulverization
  Plasma/Serum	Direct use or dilute	Pre-clear lipids for lipemic samples

  *PI = Protease Inhibitors (complete cocktail)

  Critical Parameters:

  • Maintain samples at 4°C throughout processing

  • Include phosphatase inhibitors if studying phosphorylation status

  • Centrifuge at 14,000×g for 15 minutes to remove debris

  • Determine protein concentration before analysis

• For Histological Preparation:

  Parameter	Recommendation	Rationale
  Fixation	10% NBF, 24-48h	Preserves structure while maintaining epitopes
  Processing	Short dehydration	Prevents excessive protein crosslinking
  Sectioning	4 μm sections	Optimal for antibody penetration
  Antigen Retrieval	Test both HIER methods	Citrate (pH 6.0) vs. EDTA (pH 9.0)

• For Cell Preparation (Flow Cytometry/IF):

  • Gentle dissociation: Non-enzymatic methods preferred

  • Fixation: 2-4% PFA, 10-15 minutes at room temperature

  • Permeabilization: Titrate detergent (0.05-0.3% Triton X-100)

  • Storage: Analyze immediately or store at 4°C (short-term only)

• Quality Control Indicators:

  • Positive control samples with known expression

  • Housekeeping protein detection for extract quality

  • Morphological assessment for tissue samples

These optimized preparation methods provide the foundation for reliable C1QTNF8 detection across various experimental platforms.

How should researchers standardize quantitative analysis of C1QTNF8 expression in immunohistochemistry?

Standardized quantification of C1QTNF8 expression in immunohistochemistry ensures reproducibility and meaningful comparisons across studies:

Comprehensive Scoring System:

• Intensity Scoring:

  • 0: No staining

  • 1: Weak staining

  • 2: Moderate staining

  • 3: Strong staining

• Distribution Scoring:

  • 0: <5% positive cells

  • 1: 5-25% positive cells

  • 2: 26-50% positive cells

  • 3: 51-75% positive cells

  • 4: >75% positive cells

• Combined Scoring Approaches:

  • H-score: Intensity × percentage (range 0-300)

  • Quick score: Intensity + distribution (range 0-7)

  • IRS score: Intensity × distribution category (range 0-12)

• Digital Analysis Implementation:

  • Tissue segmentation to identify regions of interest

  • Color deconvolution to isolate DAB staining

  • Threshold determination for positive pixel counting

  • Automated cell counting with intensity measurement

• Standardization Measures:

  • Include calibration slides in each batch

  • Use reference images for manual scoring

  • Calculate inter-observer and intra-observer concordance

  • Report detailed scoring methodology in publications

• Statistical Analysis Approaches:

  • Consider continuous vs. categorical treatment of scores

  • Determine appropriate cutoffs through ROC analysis

  • Account for potential confounding variables

  • Apply appropriate tests based on data distribution

This standardized approach enables reliable quantification of C1QTNF8 expression patterns and facilitates meaningful comparisons between studies.

What statistical approaches are recommended for analyzing C1QTNF8 ELISA data in complex experimental designs?

Analyzing C1QTNF8 ELISA data requires careful statistical consideration, particularly in complex experimental designs:

Statistical Analysis Framework:

• Data Preprocessing:

  • Outlier identification: Grubbs test or 3× IQR method

  • Normality testing: Shapiro-Wilk or Kolmogorov-Smirnov test

  • Transformation if needed: Log or Box-Cox transformation

  • Standard curve fitting: 4PL or 5PL models for accuracy

• Descriptive Statistics:

  • Report means with appropriate error (SD for data description, SEM for precision of mean)

  • Include median and IQR for non-normally distributed data

  • Calculate coefficient of variation (CV%) for replicates

• Statistical Tests by Design:

  Experimental Design	Recommended Tests	Post-Hoc Analysis
  Two groups	t-test or Mann-Whitney	N/A
  Multiple groups	ANOVA or Kruskal-Wallis	Tukey's or Dunn's
  Repeated measures	RM-ANOVA or Friedman	Bonferroni-corrected comparisons
  Nested designs	Mixed-effects models	Model-specific contrasts

• Correlation Analysis:

  • Pearson (parametric) or Spearman (non-parametric) correlation

  • Multiple regression for controlling confounding variables

  • Partial correlation to assess relationships while controlling for covariates

• Advanced Analysis:

  • ROC curve analysis for diagnostic potential

  • Survival analysis if paired with outcome data

  • Machine learning approaches for complex pattern recognition

• Reporting Guidelines:

  • Include precise p-values (not just p<0.05)

  • Report effect sizes and confidence intervals

  • Clearly state statistical tests and software used

  • Address multiple testing corrections when applicable

What emerging technologies might enhance C1QTNF8 antibody-based research in the coming years?

Several cutting-edge technologies are poised to transform antibody-based research for targets like C1QTNF8:

Innovative Methodological Approaches:

• Single-Cell Protein Analysis:

  • Mass cytometry (CyTOF) for high-parameter protein detection

  • Microfluidic antibody capture for single-cell secretome analysis

  • Spatial proteomics with multiplexed antibody staining

• Advanced Imaging Technologies:

  • Super-resolution microscopy for nanoscale localization

  • Expansion microscopy for physical sample magnification

  • Volumetric tissue imaging with clearing techniques

  • Multiplexed ion beam imaging (MIBI) for 40+ marker detection

• Antibody Engineering Advances:

  • Nanobodies and single-domain antibodies for improved penetration

  • Recombinant antibodies with standardized production

  • Site-specific conjugation for oriented immobilization

  • Bispecific antibodies for co-detection of interacting partners

• Automated/AI-Enhanced Analysis:

  • Deep learning for image analysis and pattern recognition

  • Automated tissue segmentation and classification

  • Unsupervised clustering of complex expression patterns

  • Predictive modeling of protein-protein interactions

• Integration with Multi-Omics:

  • Spatial transcriptomics paired with protein detection

  • Antibody-based proximity labeling for interactome analysis

  • Integrated single-cell RNA-seq and protein analysis

These emerging technologies will enable researchers to study C1QTNF8 with unprecedented resolution, sensitivity, and contextual understanding, potentially revealing new functions and associations.

How can researchers design longitudinal studies to evaluate C1QTNF8 expression changes in disease progression?

Longitudinal studies of C1QTNF8 expression can provide valuable insights into its role in disease progression:

Longitudinal Study Design Framework:

• Cohort Selection and Sampling Strategy:

  • Define clear inclusion/exclusion criteria

  • Power analysis to determine sample size requirements

  • Stratification based on relevant clinical parameters

  • Sampling frequency determination based on disease trajectory

• Specimen Collection Protocol:

  • Standardized collection timing (time of day, fasting status)

  • Consistent processing and storage (-80°C, avoid freeze-thaw)

  • Parallel collection of complementary biospecimens

  • Detailed clinical data capture at each timepoint

• Analysis Approach:

  Parameter	Methodology	Analysis Considerations
  Circulating levels	ELISA/multiplex assays	Account for diurnal variation
  Tissue expression	Serial biopsies with IHC	Standardize scoring across timepoints
  Cellular source	Flow cytometry	Track specific cell populations
  Functional changes	Ex vivo functional assays	Account for technical variations

• Statistical Considerations:

  • Mixed-effects modeling for repeated measures

  • Time-to-event analysis for clinical outcomes

  • Adjusting for time-varying confounders

  • Handling missing data (LOCF, multiple imputation)

• Integration with Clinical Trajectories:

  • Correlation with disease activity scores

  • Identification of expression patterns preceding clinical changes

  • Evaluation as potential predictive biomarker

  • Assessment of response to therapeutic interventions

This comprehensive approach to longitudinal study design enables researchers to characterize dynamic changes in C1QTNF8 expression throughout disease progression, potentially identifying critical windows for therapeutic intervention or predictive biomarker applications.