# Investigating the genetic basis of human skeletal facial morphology > **NIH NIH R15** · INDIANA UNIVERSITY INDIANAPOLIS · 2022 · $468,255 ## Abstract PROJECT SUMMARY/ABSTRACT The human face consists of unique structures that form our identity. We have strong evidence that human craniofacial variation has a high genetic component, influenced by ancestry and sex. The effort to improve our understanding of ‘normal-range’ facial variation has been of great interest in the last decade as it has particular implications for understanding the etiology of malformations in the face related to disease. Recently, an advancement in phenotyping towards the use of quasi-landmarks applied to 3D facial scans has enriched our knowledge with new genetic links tied to the human face. However, these and other genetic signals may potentially be clouded by not knowing facial skeletal information underneath the skin. A complete examination of human facial structure would be to inspect both the outer soft tissue structure and the inner hard tissue bone concurrently, including the depth of tissue in their connection. From our ever-expanding list of craniofacial candidate variants/genes, it is more important than ever to accurately classify their specific contribution to the face’s development through accurate landmark placement, and correction of competing structures within the facial construct. By doing this, we effectively provide a more precise classification of the facial link, whether it is directed towards tissue or bone variation. This more explicit definition will allow a more efficient examination of how these variants work in tandem for downstream gene expression and functional analyses work. This insight would also pave the way for more accurate personalized therapeutic interventions for craniofacial treatment and surgery, not to mention a more complete face visual for diagnostics. The current proposal has two aims designed to significantly advance our current understanding of normal-range human craniofacial variation: (1) We will enhance current mesh landmarking procedures by building a dense (thousands) map of vertices across the human skeletal bone, effectively generating a craniofacial skeletal mask using quasi-landmarks, which has not yet been made available in the field. This template will allow efficient normalized landmarking of craniofacial bone using MeshMonk registration; (2) Utilizing a new collection of Cone Beam Computed Tomography facial scans (n=750), allows us to connect both soft tissue with hard tissue landmarks ensuring one is a covariate against the other facial structure being examined and perform association testing with a list of over 350 facial candidate variants/genes. This more precise method of phenotype:genotype association has not yet been characterized in such a manner, correcting bone from soft tissue and vice versa. For the first time, we shall also generate Facial Soft Tissue Thickness (FSTT) at quasi-landmarks by utilizing the information gleaned from these two structural entities and their connection in space. This project aims to confirm, with genetic association, a more ... ## Key facts - **NIH application ID:** 10438980 - **Project number:** 1R15DE031929-01 - **Recipient organization:** INDIANA UNIVERSITY INDIANAPOLIS - **Principal Investigator:** Susan Walsh - **Activity code:** R15 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $468,255 - **Award type:** 1 - **Project period:** 2022-08-01 → 2026-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10438980 ## Citation > US National Institutes of Health, RePORTER application 10438980, Investigating the genetic basis of human skeletal facial morphology (1R15DE031929-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10438980. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*