| Title: | Investigating the genetic architecture associated with skeletal body proportions |
| Lead Institution: | University of California, Davis |
| Principal investigator: | Professor Timothy Weaver |
Application 54084
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About
The primary goal of the proposed research is to investigate the genetic architecture associated with skeletal body proportions and identify genes associated with the length, breadth, and shape of skeletal features. For each individual included in our study, we will obtain a suite of skeletal measurements from DXA scans and perform a GWAS for these measurements using each individual's associated genetic data. After identifying relevant genes, we will be able to investigate how different components of skeletal body proportions are associated genetically, and how they relate to previously identified genes associated with composite measurements of height. Body proportions (e.g., how long an individual's limbs or limb segments are relative to their height) are an important component of height but are often overlooked in this regard. Previous studies have viewed height as a singular measurement, or a composite of sitting height and lower limb lengths, however, many more components actually comprise height. Because height is a composite of many different components but most studies utilize combined measurements, current knowledge of the genetic architecture underlying height has limited resolution. By better characterizing height and body proportions as a composite of skeletal elements, we will be able to identify the particular relationships between identified genes and the specific units that make up height. Any single gene may minutely affect many skeletal regions, or may have a large effect on one particular bone or region. Because height is influenced by many genes, we hope to identify the hierarchy of interactions between these genes and their correlations with genes associated with the different components of skeletal body proportions. This, in turn, may inform future research on the nature of other complex traits that may have a hierarchical genetic makeup, such as disease phenotypes. The results of the GWAS performed during this study will inform future medical research, risk prediction, and preventative care by identifying the extent to which the genotype affects skeletal traits, and the relationship between genotypic and environmental effects. Additionally, the collection of linear skeletal metrics will provide new data for future research; and refinements in automated methods for collecting linear skeletal measurements from DXA scans will facilitate similar studies.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 7889 | Developing an automated skeletal phenotyping pipeline to leverage biobank-level medical imaging databases | Chelsea C. Cataldo-Ramirez (+3) | 2023 | American Journal of Biological Anthropology |
Enabling scientific discoveries that improve human health