Lab Activity 2: Analyzing NASA Astronaut Immune Health Data

Objective

Students will analyze real NASA data on astronaut immune function, identify trends, and draw evidence-based conclusions about spaceflight effects on immunity.

Time Required

60-90 minutes

Materials

• Computer with Excel or Google Sheets
• NASA OSDR database access
• Graphing calculator (optional)
• Lab notebooks
• Statistical analysis handouts

Background

NASA monitors astronaut health before, during, and after spaceflight. Immune system markers include:
- White blood cell counts (WBC)
- T cell subpopulations (CD4+, CD8+)
- Natural Killer (NK) cell activity
- Immunoglobulin levels (IgG, IgA, IgM)
- Cytokine concentrations

Pre-Lab Questions

1. Why monitor immune function in astronauts?
2. What changes would you predict during spaceflight?
3. How long might changes persist after return to Earth?

Procedure

Part 1: Data Collection (20 minutes)

Access NASA OSDR:
1. Navigate to https://osdr.nasa.gov/
2. Search for "immune function" or "astronaut health"
3. Select datasets from ISS missions
4. Download CSV files for:
- Complete Blood Count (CBC) data
- Flow cytometry results
- Cytokine measurements

Organize Data:
- Pre-flight baseline (L-180 to L-60 days)
- Early flight (Day 15-30)
- Mid-flight (Day 60-120)
- Late flight (Day 150+)
- Post-flight recovery (R+0 to R+180)

Part 2: Data Analysis (30 minutes)

Statistical Analysis:
1. Calculate means and standard deviations
2. Determine percent change from baseline
3. Identify significant trends

Create Graphs:
1. Line graph: WBC counts over mission duration
2. Bar graph: T cell populations (pre, during, post flight)
3. Box plot: NK cell activity distribution
4. Scatter plot: Cytokine levels vs. mission day

Part 3: Pattern Recognition (20 minutes)

Identify Trends:
- Which immune parameters change most?
- When do changes appear?
- Do changes return to baseline post-flight?
- Are there individual variations?

Compare Missions:
- Short vs. long duration
- Different mission years
- Various crew members

Data Tables

Table 1: Mean Immune Parameters

Table 2: Statistical Analysis

Analysis Questions

1. Which immune cell type showed the greatest change during spaceflight?

2. At what point during the mission were immune changes most pronounced?

3. Did immune parameters return to pre-flight levels after landing? How long did recovery take?

4. What biological mechanisms might explain the observed changes?

5. How might these immune changes affect astronaut health and safety?

6. What countermeasures would you recommend based on this data?

Real NASA Findings to Compare

Expected Results:
- 10-20% decrease in T cell proliferation
- 30-40% reduction in NK cell activity
- Cytokine dysregulation (varies by type)
- Most changes resolve within 30-60 days post-flight
- Individual variation is significant

Advanced Analysis

For Advanced Students:
1. Perform t-tests or ANOVA
2. Calculate correlation coefficients
3. Create heat maps of multiple parameters
4. Build predictive models

Research Questions:
- Does mission duration correlate with immune suppression?
- Are certain crew members more susceptible?
- Do countermeasures (exercise, nutrition) help?

Lab Report

Requirements

• Abstract (150 words)
• Introduction (NASA immune research background)
• Methods (data sources and analysis approach)
• Results (graphs, tables, statistical findings)
• Discussion (interpret findings, compare to literature)
• Conclusions (implications for space exploration)
• References (NASA studies, scientific papers)

Grading (100 points)

• Data collection and organization (15 points)
• Graphs (25 points)
• Statistical analysis (20 points)
• Analysis questions (20 points)
• Discussion (15 points)
• Overall quality (5 points)

Extensions

Connection to Other Lessons:
- Lesson 1: Space immunology foundations
- Lesson 5: Innovation opportunities for countermeasures

Career Applications:
- Data scientist
- Biostatistician
- NASA flight surgeon
- Research analyst

Resources

Data Sources

• NASA Open Science Data Repository (OSDR)
• NASA Human Research Program
• ISS Medical Monitoring database

Analysis Tools

• Excel/Google Sheets
• GraphPad Prism
• R statistical software
• Python (pandas, matplotlib)

References

• Crucian, B., et al. (2018). "Immune System Dysregulation During Spaceflight"
• Mehta, S. K., et al. (2017). "Multiple latent virus reactivation in astronauts"

Part of the Space Medicine Antibody Drug Development Curriculum
NGSS: HS-LS1-2, Math Standards: Data Analysis