Do Unaffected Parents of Children with Orofacial Clefts have Decreased Facial Integration Compared to Controls?
Authors: Ruiz Jaime , Branham Nicholas , Nguyen Lisa , Ehrlich Daniel E. , Moskal Russell J. , Lee Myoung Keun , Marazita Mary L. , Weinberg Seth M. , Miller Steven F. 
Published: June 2021

Orofacial clefts are the most common congenital craniofacial anomaly affecting humans. Non‐syndromic clefts may result from decreased integration of the palate during fetal facial growth. This study will investigate whether this pattern is detectable in individuals who do not have a cleft, but do have a child with an orofacial cleft (and therefore carry genetic risk factors for clefting). In order to examine this, we hypothesize that 1) facial shape differences exist between unaffected parents of children with clefts (cases) compared to adults with no history of clefting (controls), and 2) cases will have lower facial integration values compared to controls.

For this study, 3D facial scans were obtained from the University of Pittsburgh Center for Craniofacial and Dental Genetics (CCDG). 34 landmarks were placed on n=230 case faces of unaffected parents from the Pitt Orofacial Cleft Study and n=490 control faces from the Pitt 3D Facial Norms Study. Landmarks were aligned using Generalized Procrustes Analysis (GPA) and geometric morphometrics were used for quantifying facial phenotypes. Facial shape differences as a function of age were removed prior to all analyses using linear regression. Canonical Variate Analysis (CVA) was employed to examine shape differences in three different subsets of facial landmarks: a midfacial nose and mouth dataset, a lower facial mouth and jaw dataset and a third dataset consisting of the nose and jaw. Two Block Partial Least Squares analysis (2B PLS) was used to measure the strength of integration by comparing RV coefficients between the case and control populations.

Results from the CVA identify significant differences in facial morphology, including jaw width, chin projection, nasal height and mouth width, between cases and controls across all datasets (nose/mouth midfacial set p<0.001, mouth/jaw lower facial set p<0.001, and nose/jaw dataset p=0.028). 2B PLS results, however, showed overall equivalent or higher integration levels in case faces compared to the controls. When comparing levels of integration within the midface (nose and mouth dataset), case samples demonstrate significant (p<0.001) overall higher integration levels (RV=0.352) compared to control samples (RV=0.301). This pattern is also seen within the nose and jaw dataset, with cases (RV=0.614) showing increased integration compared to controls (RV=0.554). Interestingly, integration levels within the lower facial mouth and jaw dataset were nearly identical in both case samples (RV=0.444) and controls (RV=0.447).

While facial shape differences exist between unaffected cleft relatives and controls with no family history of clefting, integration values were actually higher in case samples compared to control samples. This indicates that integration in facial soft tissue structures may not serve as a good indicator of cleft risk. Future studies will examine skeletal structures (such as the maxilla and mandible) to test if differences in integration are quantifiable in the facial skeleton only.

Support or Funding Information

NIDCR: R01‐DE016148, U01‐DE020078

This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.