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Study into genetics offers hope for bone conditions

  • November 18, 2023
  • 3 min read
Study into genetics offers hope for bone conditions

Six million years ago, our ancestors began to walk on two legs. This shift to being bipedal is believed to have made primates more adapted to a diverse range of habitats and freed their hands, allowing them to make and use tools, which further accelerated cognitive development. This set the stage for the evolution of modern humans.

The genetic changes that made this possible have been uncovered in a new study by researchers from Columbia University and the University of Texas. The findings were published in the journal Science. The study was co-led by Vagheesh M. Narasimhan, PhD, assistant professor of integrative biology and of statistics and data sciences at the University of Texas at Austin.

The researchers used a combination of deep learning (a type of artificial intelligence) and genome-wide association studies to build the first map of the ‘genomic regions’ responsible for skeletal changes. The map revealed that the genes that underlie the anatomical changes seen in the fossil record were strongly acted on by natural selection, giving early humans an evolutionary advantage.

“On a more practical level, we’ve also identified genetic variants and skeletal features that are associated with hip, knee, and back arthritis, the leading causes of adult disability in the United States,” says Tarjinder Singh, PhD, assistant professor of computational and statistical genomics (in psychiatry) at the Columbia University Vagelos College of Physicians and Surgeons and a co-leader of the study.

One example is slight deviations from the average hip width-to-height ratio, which is linked with an increased risk of hip osteoarthritis, and slight deviations in the tibia-femur angle were linked with an increase in the risk of knee osteoarthritis. These findings could help researchers develop new ways to prevent and treat these conditions.

The researchers applied deep learning to analyse over 30,000 full-body X-rays from the UK Biobank. Deep learning is a technology modelled after the brain’s neural networks. It trains computers to do what comes naturally to humans such as driving a car or translating languages. In this case it was used to examine X-rays, remove any images with quality issues, and precisely measure dozens of skeletal features. These tasks would take researchers months or even years to finish. This was followed by a scan of the genome to identify any regions associated with the variations in the skeletal measurements.

“What we’re seeing is the first genomic evidence that there was selective pressure on genetic variants that affect skeletal proportions, enabling a transition from knuckle-based walking to bipedalism,” says Narasimhan.

The study also highlights the power of combining large-scale biobank data, along with machine learning and genomics to help understand human health and disease. This technique is now being applied to understand the causes of mental illness.

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