A genetic change was found from the great ape knuckle gait to the upright human gait

A new study by researchers at Columbia University and the University of Texas in the United States has found genetic changes which allowed the transition from movement with great ape knuckles to a human upright gait, as published in the journal ‘Science’.

Perhaps the greatest advance in primate evolution occurred about 6 million years ago, when our ancestors started walking on two legs. The gradual shift to bipedal locomotion is thought to have made primates more adaptable to diverse environments and free his hands to use tools, which in turn accelerates cognitive development. These changes paved the way for modern humans.

Using a combination of deep learning (a form of artificial intelligence) and genome association studies, researchers have created the first map of the genomic regions responsible for skeletal changes in primates they lead an upright gait. The map reveals that the genes underlying the anatomical transitions observed in the fossil record are robust influenced by natural selection and gave early humans an evolutionary advantage.

“On a more practical level, we have also identified genetic variants and skeletal traits associated with arthritis of the hip, knee and backleading cause of disability in adults in the United States,” said Tarjinder Singh, professor of computational genomics and statistics (in psychiatry) at Columbia University’s Vagelos College of Physicians and Surgeons and co-director of the study.

For example, a slight deviation from the mean hip width-to-height ratio is associated with an increased risk of hip osteoarthritis, while a slight deviation from the tibia-femur angle is associated with an increased risk of knee osteoarthritis. This data can help researchers design new way to prevent and treat this disease so debilitating.

The researchers applied deep learning to analyze more than 30,000 whole body X-rays from the UK Biobank. Deep learning, a technology modeled on the brain’s neural networks, trains computers to do things that come naturally to humans, such as driving a car or translating language. In this case, the technique is used to standardize the radiography, eliminate images with quality problems, and then accurately measure dozens of skeletal featuresa task that would take researchers months, if not years, to complete.

Next, they scanned the human genome to identify chromosomal regions associated with variations in 23 major skeletal measurements, such as shoulder width, torso length, and angle between tibia and femur. These scans, called genome-wide association studies, involve examining the genomes of large groups of people for genomic variants that occur more frequently in those with a particular disease or trait than in those without the disease or trait. This process unfolds 145 gene-related regions that regulate skeletal development. Only a handful of these loci are known from previous studies.

Many of the 145 areas coincide with “accelerated” regions of the human genome, which have evolved rapidly over thousands of years compared to the same region in great apes. Instead, several genes related to heart, immune system, metabolism, and other traits were found in the accelerated regions.

“What we’re seeing is the first existing genomic evidence selective pressure on genetic variants affecting skeletal proportionsenabling the transition from knuckle-based gait to bipedalism,” said Dr. Vagheesh M. Narasimhan, Associate Professor of Integrative Biology and Statistics and Information Sciences at the University of Texas and one of the paper’s directors.

This study also demonstrates the power of combining data from large-scale biobanks, machine learning and genomics to help us understand human health and disease.” Singh, who joined Columbia in 2022, is now applying this technique to understanding the causes of mental illness.

Stuart Martin

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