The single-cell "atlases" that are increasingly used to map the human body and as training data for artificial intelligence models may not represent the world's populations fairly, according to a study led by researchers at the Icahn School of Medicine at Mount Sinai. The analysis found that people of European ancestry were consistently overrepresented, while Asian and Latino individuals were underrepresented, and a large share of samples lacked any record of ancestry. The findings were published July 20 in Cell Genomics.
Single-cell technologies allow scientists to profile biology one cell at a time, revealing rare cell types and disease-related changes that older, bulk methods miss. Large international efforts have used these tools to build reference maps—expansive datasets meant to serve as universal references for research and medicine. But the researchers say the demographic makeup of these resources had not been systematically examined, raising the question of whether the maps reflect all of humanity or only part of it.
How the team measured bias
The team reviewed more than 13,500 samples from three major single-cell resources: the Human Cell Atlas, the Human Tumor Atlas Network and the PsychAD Consortium. They curated the reported ancestry, race, ethnicity and sex of the sampled individuals, then compared each dataset with global population data, U.S. cancer incidence data and disease-specific reference data, examining patterns across tissues, cancer types and brain disease categories.
