In a recent article published in Science, researchers evaluate imaging information from the United Kingdom biobank subjects and characterized skeletal proportions (SPs) to assess the genetic root of these traits and their connections to each other.
Study: The genetic architecture and evolution of the human skeletal form. Image Credit: JuliusKielaitis / Shutterstock.com
How is skeletal evolution studied?
Morphological alterations that contribute to human skeletal structure have been extensively studied in paleoanthropology. Aside from standing height, it has been difficult to examine the genetic mechanisms responsible for specific and differential individual bone growth and their evolution due to the small sample numbers.
It is crucial to understand the genetic foundation of skeletal structure for several reasons, including discovering genetic risk elements for skeletal illnesses and gaining knowledge about the evolution of the human body.
One method for investigating skeletal form involves acquiring a map of the genomic areas impacting skeletal morphology and development. Comparative genomics and animal models have primarily been used previously to explore this approach; however, these methods generally have poor throughput.
Examining the genetic causes of variations in human skeletal features is an alternative approach.
About the study
In the present study, researchers analyze 31,221 full-body dual-energy X-ray absorptiometry (DXA) images from the U.K. Biobank. Deep learning models were applied to these images, from which an extensive collection of SPs linked with numerous independent genome-wide loci were extracted.
Genome-wide association studies (GWAS) were conducted using deep learning models, which involved comparing the genetic profiles of individuals with diverse SPs to determine genetic variants associated with SPs.
Over 10,000 people from various populations were included in the dataset, thereby enabling a more thorough examination of the genetic foundations of skeletal structure. While accounting for height, the team examined the extracted image-derived phenotypes (IDPs) comprising all long-bone lengths, as well as shoulder and hip widths.
Numerous quality control measures were employed to ensure the consistency and accuracy of the imaging information. Additional assessments on distinct datasets were performed to confirm their findings, which were followed by functional analyses to analyze the biological processes responsible for the discovered genetic variants.
Women have significantly greater body proportions than men, including hip-width to height, humerus to height, and torso length to height. Age also causes small changes in body proportions.
Torso length to leg proportion declines with height, thus suggesting that leg length increases more rapidly than torso length as height increases. Total limb length increases lower to upper limb ratios, whereas height increases the ratio of the tibia to the femur.
The traits analyzed in GWAS were highly heritable, with single-nucleotide polymorphism (SNP) heritability varying from 23% to 53% for linkage disequilibrium Score regression (LDSC) and 17-50% for genome-wide complex trait analysis-restricted maximum-likelihood (GCTA-REML). Although test statistic inflation was observed, this result was more likely due to polygenicity than confounding factors.
While analyzing SPs, 223 loci were associated with several features, including forearm length and hip width. Moreover, 145 of these loci were independently relevant for all traits, with 37 loci particularly relevant for SPs after accounting for height.
Genetic correlations between skeletal measures, including limb proportions, showed positive correlations with each other, whereas body-width proportions and limb-length proportions were uncorrelated. Additionally, genomic structural equation modeling (SEM) identified five key factors governing SPs, with limb traits loading on the general skeletal factor and arm traits loading on a separate factor. Torso length and body width traits were independent of limb proportions because they depended on trait-specific factors.
Skeletal and anthropometric traits like hip width displayed sexual dimorphism, with the genetic association between men and women close to one, except for tibiofemoral angle (TFA). Skeletal features had more sex-specific genetic impacts in males than females, thus differentiating the degree of sex-specific impacts in the U.K. Biobank.
Gene set enrichment assessments using functional mapping and annotation (FUMA) discovered 195 enriched gene sets linked to skeletal features, including skeletal system development, chondrocyte differentiation, connective tissue, and cartilage development. In 701 autosomal genes associated with musculoskeletal illnesses, common alleles related to skeletal growth anomalies were enriched. GWAS catalog shares 45 loci with protein-coding genes and anthropometric characteristics, thus leading to aberrant mouse skeletal phenotypes.
Hip width, femur length, torso length, tibia length, and thigh fat area were linked to an augmented risk of knee and hip osteoarthritis, internal derangement of the knee, and back pain. The length of skeletal elements associated with overall height was primarily associated with an increased risk of pain and arthritis in specific body areas.
Human accelerated regions (HARs) were significantly enriched for genes associated with schizophrenia, hair pigmentation, and leg or arm length. Nevertheless, there was no enrichment for HARs in cancer, cardiovascular illness, autoimmune disorders, or overall height.
A meta-analysis of SP traits revealed enrichment in fetal human-gained promoters and enhancers, thus indicating that early stages of human and ape development involve differing gene expression patterns.
The current study identified several factors associated with the heritability of SPs, genetic overlap between skeletal traits, and discovery of genetic variants related to specific SPs.
Overall, this study highlights the potential of deep learning models for evaluating large-scale imaging datasets and complex traits. These findings provide new insights into the genetic foundation of skeletal structure and evolution of the human body.
- Kun, E., Javan, E. M., Smith, O., et al. (2023). The genetic architecture and evolution of the human skeletal form. Science 381. doi:10.1126/science.adf8009 https://www.science.org/doi/10.1126/science.adf8009
Posted in: Molecular & Structural Biology | Medical Science News | Medical Research News
Tags: Arthritis, Autosomal, Back Pain, Bone, Cancer, Cartilage, Deep Learning, Evolution, Gene, Gene Expression, Genes, Genetic, Genome, Genomic, Genomics, Hair, Imaging, Knee, Morphology, Musculoskeletal, Nucleotide, Osteoarthritis, Pain, Protein, Schizophrenia, X-Ray
Shanet Susan Alex
Shanet Susan Alex, a medical writer, based in Kerala, India, is a Doctor of Pharmacy graduate from Kerala University of Health Sciences. Her academic background is in clinical pharmacy and research, and she is passionate about medical writing. Shanet has published papers in the International Journal of Medical Science and Current Research (IJMSCR), the International Journal of Pharmacy (IJP), and the International Journal of Medical Science and Applied Research (IJMSAR). Apart from work, she enjoys listening to music and watching movies.