European scientists, led by biologist Tomàs Marquès, sequenced over 800 non-human primate genomes from 233 species and compared them to the genomes of 141,456 humans.
The research published in Science magazine unveiled a remarkable finding: the identification of approximately four million genetic mutations in the human genome, some of which may be linked to various pathologies.
Scientists Revealing Genetic Mutations
The study emphasized the significance of comparing human genetic information with that of primates as a means to unravel the origins of human diseases. Marquès, the lead biologist, affirmed the value of studying primates, stating, “Our results demonstrate that by investigating primates, we can enhance our understanding of humans.”
Scientists compared genetic samples from endangered species like the Sahafary’s jumping lemur from Madagascar with those from chimpanzees, gorillas, orangutans, and other primates that are closely related to humans.
The gathered data played a crucial role in developing the PrimateAI-3D deep learning artificial intelligence algorithm, a genetic-focused system similar to ChatGPT, aimed at identifying mutations associated with diseases. Remarkably, the algorithm successfully identified 73% of the established connections between genetic variations and pathologies, encompassing complex conditions like cancer and diabetes.
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Future Explorations in Primate Genomics
The biologist emphasized the algorithm’s ability to recognize not only common mutations contributing to these diseases but also rare, infrequent mutations that exert a significant impact. Notably, the algorithm’s training with primate data played a pivotal role in achieving these outcomes.
Marquès offered an explanation regarding the specific causes of these diseases, stating, “The cause does not solely reside in a single gene mutation but rather stems from a combination of numerous factors.”
There is a prevailing belief that certain diseases can emerge when mutations with a mild effect synergistically contribute to polygenic conditions such as diabetes, heart disease, or cancer.
The algorithm now serves as a valuable tool to precisely determine the origin of such diseases.
The development of this algorithm represents a groundbreaking advancement in science, addressing the limitations of human and clinical genetics in detecting disease-causing mutations. Currently, the genetic causes of numerous serious diseases remain unknown. The study’s authors concluded that this research will open up extensive avenues for future exploration in primate genomics.
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