High-Altitude Acclimatization Data: Physiological and Transcriptomic Dynamics Over 23 Days

Chinese Han individuals were studied during a 23-day exposure at 4,104 meters. The dataset likely contains physiological measurements and RNA-seq data from 113 participants, with a subset of 48 used for transcriptomic analysis. Author Ling Chen published the data on figshare under a CC-BY-4.0 license, last updated in March 2026.

Use Cases

• Modeling physiological trends (SpO2, hemoglobin) over time based on the duration of acclimatization at high altitude (DAHA).
• Identifying gene expression patterns associated with prolonged high-altitude exposure based on the described decreasing and 'mountain-shaped' patterns.
• Predicting AMS susceptibility based on the five identified hub genes (BCL2L1, DCAF12, CDC34, PINK1, UBB).
• Pathway enrichment analysis based on the 10 overlapping pathways identified in the eAMS+ group.

Strengths

• Includes data from 113 participants, providing a substantial sample size for physiological analysis.
• Integrates temporal data over a 23-day period, allowing for analysis of acclimatization dynamics.
• Combines physiological parameters (SpO2, hemoglobin, hematocrit, RDW-SD) with transcriptomic data from RNA-seq.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the primary data tables is unknown, which may limit suitability assessment.
• The primary data file is a 16.9 MB DOCX, which may require extraction or conversion for analysis.

Provenance

Source

figshare

Collection Method

Cross-sectional study with linear regression, time series, and enrichment analysis applied.

Time Range

Study conducted over a 23-day period.

Freshness

Last updated 2026-03-17 13:05:10; freshness should be verified.

Geography

Data collected from individuals at 4,104 m; participants were Chinese Han.