For more than a century, scientists have sought to reconstruct human evolution using diverse lines of evidence, including fossils, genetic variation across populations, and ancient DNA. Building on these approaches, researchers are increasingly using large population biobanks to investigate how natural selection continues to shape the genomes of living populations.
In a new study, researchers analyzed genomic data from over 72,000 Han Taiwanese participants in the Taiwan Biobank by comparing allele frequencies across adult age groups. This analytic framework enabled them to identify genomic signatures of ongoing natural selection and uncover disease-associated genetic variants that may otherwise have gone undetected.
Published in The American Journal of Human Genetics, the study shows that large biobanks can function not only as tools for precision medicine but also as platforms for examining modern human evolution. The researchers suggest this framework could be used globally, providing new chances to identify medically relevant genetic variants in different populations.
"One of the most exciting aspects of this study was seeing how age-stratified allele-frequency trajectories could reveal ongoing natural selection in a contemporary population," said first author Jing-Lian Chen, formerly a master's student in Dr. Wen-Ya Ko's laboratory at National Yang Ming Chiao Tung University in Taiwan. "This approach complements existing methods and helps uncover disease-associated variants that might otherwise remain undetected."
"Biobanks are usually viewed as resources for studying disease," said corresponding author Dr. Wen-Ya Ko. " Our study demonstrates that these same resources can also help uncover how ongoing natural selection continues to shape disease-related genetic variation. This creates new opportunities to integrate evolutionary biology with precision medicine."
Finding rare disease variants that conventional studies often miss
The researchers examined 509,817 genome-wide variants in 72,635 Han Taiwanese individuals aged 24 to 70. Instead of targeting genes linked to specific diseases, they investigated whether certain inherited variants consistently increased or decreased in frequency across various adult age groups.
Their analysis revealed 168 variants that deviated from neutral expectations, with 159 displaying signs of ongoing purifying selection, an evolutionary process that gradually eliminates harmful genetic variants. Notably, about 90% of these variants were extremely rare, indicating that the approach can detect evolutionary signals that previous selection scans, which mainly focused on common variants, might miss.
Many of these rare variants were previously linked to inherited disorders. Seventy-one are classified as pathogenic or likely pathogenic in ClinVar, with many others associated with cancer, neurological conditions, cardiovascular problems, kidney disease, and other serious health issues. The identification of these medically relevant variants indicates that evolutionary analyses can be valuable in prioritizing mutations that cause disease for future research.
Unexpected evolutionary patterns in BRCA1 and DNA repair genes
One of the most notable discoveries was an unexpected evolutionary pattern involving BRCA1, a well-known cancer susceptibility gene. Researchers identified a rare BRCA1 haplotype carrying 16 protein-altering variants, of which 15 are already classified as pathogenic. This haplotype seems to be under purifying selection, gradually becoming less common in the population.
Interestingly, regions near BRCA1, as well as BRCA2 and MLH1, indicated evidence of positive selection. This suggests that different variants within the same DNA repair genes have experienced distinct forms of natural selection over evolutionary time. Rather than conflicting, these results highlight the complex interplay between genetic variants that increase disease risk and those that may have conferred advantages in past environments.
"Evolution rarely acts on genes in a straightforward manner," said Prof. Yoko Satta of SOKENDAI (The Graduate University for Advanced Studies), Japan. "A variant increasing disease risk now might have been beneficial in a different environmental context earlier. Understanding these evolutionary trade-offs enhances our interpretation of disease-related variants in current populations."
One gene, many health effects
The study also found evidence that natural selection might favor genes impacting multiple facets of human biology. Two genes, ATG9A and FADS2, demonstrated significant pleiotropy, where a single gene influences numerous seemingly unrelated traits. Variations in these genes were linked to blood cell characteristics, liver and kidney functions, lipid metabolism, diabetes-related traits, cardiovascular metrics, and bone density. This extensive biological influence may explain why these regions are recurrently influenced by natural selection; changing one gene can impact many physiological systems at once. This finding indicates that evolutionary research can help identify genes at central points of human biology, making them promising targets for future functional and clinical studies.
Red blood cells emerge as a shared evolutionary signature
Although the candidate variants are spread across the genome and occur in genes with diverse biological functions, many converge on a common physiological pattern. About 150 variants consistently associate with red blood cell traits, particularly increased mean corpuscular volume and reduced mean corpuscular hemoglobin concentration. The researchers propose that this pattern may be due to historical adaptation to infectious diseases like malaria, which was once widespread in Taiwan. While further research is necessary to confirm the exact mechanism, this discovery highlights how evolutionary pressures can shape similar physiological traits through genetic variation across multiple genes, rather than affecting single variants in isolation.
Toward more representative precision medicine
Beyond individual discoveries, the researchers see the greatest impact in showcasing a new analytical framework adaptable to other large-scale genomic datasets. Most existing genomic reference datasets are skewed toward populations of European ancestry. Applying this framework to one of the world's largest Han Taiwanese cohorts demonstrates how population-specific evolutionary histories can uncover medically significant variants that might otherwise go unnoticed. As more nations develop national biobanks, this approach could be expanded globally to better understand the ongoing influence of evolution on human health across diverse populations.
"Human evolution did not cease thousands of years ago," the scientists stated. "Living populations still bear its genetic imprints. Combining large biobanks with advanced genomic analysis offers a powerful new method to explore how evolution continues to shape health, disease, and human diversity."
