Weinberg Lab

Research Mission

The Weinberg Lab focuses primarily on understanding the biological factors that influence human craniofacial form and variation. These forms includes both normal-range variation (i.e., our typical facial features) as well as craniofacial dysmorphology. The lab uses a combination of 3D imaging and morphometrics to investigate the genetic architecture of human craniofacial traits in populations around the world. Research from the Weinberg Lab has been featured by numerous news outlets including The Scientist, Nature, Forbes, Popular Science, Pittsburgh Post-Gazette, NPR, and National Geographic. 

Revealing the Genetic Architecture of the Human Face

We have led numerous large-scale genome-wide studies of normal-range facial features, resulting in the discovery of novel genetic associations. We have applied both traditional and novel 3D facial phenotyping approaches resulting in the identification of several hundred GWAS loci in multiple human populations.  Importantly, this work revealscritical insights into the gene networks that build the face and those involved in dysmorphology. For example, our discovered loci show strong evidence of involvement in the epigenetic regulation of cranial neural crest cells during embryogenesis. 

• Shaffer JR, Orlova E, Lee MK, Leslie EJ, Raffensperger ZD, Heike CL, Cunningham ML, Hecht JT, Kau CH, Nidey NL, Moreno LM, Wehby GL, Murray JC, Laurie CA, Laurie CC, Cole J, Ferrara T, Santorico S, Klein O, Mio W, Feingold E, Hallgrimsson B, Spritz RA, Marazita ML, Weinberg SM. Genome-wide association study reveals multiple loci influencing normal human facial morphology. PLoS Genetics. 2016;12(8):e1006149. PMC4999139.
• Claes P, Roosenboom J, White JD, Swigut T, Sero D, Li J, Lee MK, Zaidi A, Mattern BC, Liebowitz C, Pearson L, González T, Leslie EJ, Carlson JC, Orlova E, Suetens P, Vandermeulen D, Feingold E, Marazita ML, Shaffer JR, Wysocka J, Shriver MD, Weinberg SM. Genome-wide mapping of global-to-local genetic effects on human facial shape. Nature Genetics. 2018;50(3):414-423. PMC5937280.
• White JD, Indencleef K, Naqvi S, Eller RJ, Hoskens H, Roosenboom J, Lee MK, Li J, Mohammed J, Richmond S, Quillen EE, Norton HL, Feingold E, Swigut T, Marazita ML, Peeters H, Hens G, Shaffer JR, Wysocka J, Walsh S, Weinberg SM, Shriver MD, Claes P. Insights into the genetic architecture of the human face. Nature Genetics. 2021;53(1):45-53. PMC7796995.
• Naqvi S, Hoskens H, Wilke F, Weinberg SM, Shaffer JR, Walsh S, Shriver MD, Wysocka J, Claes P. Decoding the human face: challenges and progress in understanding the genetics of craniofacial morphology. Annual Review of Genomics and Human Genetics. 2022;23:383-412. PMC9482780.

Relevant Funding: R01-DE027023 (NIDCR) ; U01-DE020078 (NIDCR) 

Learn more about this project here: https://theconversation.com/we-scanned-the-dna-of-8-000-people-to-see-how-facial-features-are-controlled-by-genes-151539  

The 3D Facial Norms Database: A Repository for the Craniofacial Research Community

In 2009, as part of NIDCR’s newly funded FaceBase Consortium, we created the world’s first interactive web-based normative repository containing 3D surface images, measurements and genome-wide markers from a large number of healthy subjects. The 3D Facial Norms (3DFN) database currently consists of 2,454 male and female subjects ranging in age from 3 to 40 years, recruited at four US centers. Through the FaceBase Consortium website, members of the research and clinical community can search and interact with the 3DFN repository and access summary statistics on a wide variety of anthropometric measurements. The 3DFN repository has been used in studies of comparative facial dysmorphology, craniofacial growth and development, imaging and morphometrics methods development, and large-scale genomic studies of human facial morphology. 

• Hochheiser H, Aronow BJ, Artinger K, Beaty TH, Brinkley JF, Chai Y, Clouthier D, Cunningham ML, Dixon M, Donahue LR, Fraser SE, Hallgrimsson B, Iwata J, Klein O, Marazita ML, Murray JC, Murray S, de Villena FP, Postlethwait J, Potter S, Shapiro L, Spritz R, Visel A, Weinberg SM, Trainor PA. The FaceBase Consortium: A comprehensive program to facilitate craniofacial research. Developmental Biology. 2011; 355(2):175-182. PMC3440302.
• Kesterke MJ, Raffensperger ZD, Heike CL, Cunningham ML, Hecht JT, CH Kau, Nidey NL, Moreno LM, Wehby GL, Marazita ML, Weinberg SM. Using the 3D Facial Norms Database to investigate craniofacial sexual dimorphism in healthy children, adolescents, and adults. Biology of Sex Differences. 2016;7:24. PMC4841054.
• Weinberg SM, Raffensperger ZD, Kesterke MJ, Heike CL, Cunningham ML, Hecht JT, Kau CH, Murray JC, Wehby GL, Moreno LM, Marazita ML. The 3D Facial Norms Database: Part 1. A web-based craniofacial anthropometric and image repository for the clinical and research community. Cleft Palate Craniofacial Journal. 2016;53(6). PMC4841760.
• Matthews HS, Mahdi S, Penington AJ, Marazita ML, Shaffer JR, Walsh S, Shriver MD, Claes P, Weinberg SM.  Using data-driven phenotyping to investigate the impact of sex on 3D human facial surface morphology. Journal of Anatomy. 2023;243(2):274-283. PMC10335371.

Relevant Funding: U01-DE020078 (NIDCR) 

The “Rich Phenotyping” Paradigm in Orofacial Clefting

Since 1999, we have been heavily invested in fundamentally reshaping how clefts of the lip and palate are conceptualized in etiologic studies.  Genetic studies of clefting have traditionally used phenotypic definitions that only capture overt manifestations of the trait. The “rich phenotyping” concept starts with the premise that this traditional approach ignores a large amount of relevant phenotypic information in families. We hypothesized that expanding the definition of “affected” to include certain subtle subclinical manifestations of clefting (e.g., upper lip muscle defects, dental abnormalities, subtle speech alterations) will improve our power to detect genetic signals and offer a way to potentially mitigate etiological heterogeneity. Working with a team of US and international collaborators, we have applied rigorous and detailed phenotyping protocols to both cleft affected individuals and their immediate and extended relatives. We have shown that many subclinical cleft phenotypes are present at higher rates in these ostensibly “unaffected” relatives compared to controls.  

• Weinberg SM, Brandon CA, McHenry TH, Neiswanger K, Deleyiannis FWB, de Salamanca JE, Castilla EE, Czeizel AE, Vieira AR, Marazita ML. Rethinking isolated cleft palate: evidence of occult lip defects in a subset of cases. American Journal of Medical Genetics Part A. 2008;146A(13):1670-1675.
• Suzuki S, Marazita ML, Cooper ME, Miwa N, Hing A, Jugessur A, Natsume N, Shimozato K, Shi M, Ohbayashi N, Suzuki Y, Niimi T, Minami K, Yamamoto M, Altannamar TJ, Erkhembaatar T, Furukawa H, Daack-Hirsch S, L’Heureux J, Brandon CA, Weinberg SM, Neiswanger K, Deleyiannis FWB, de Salamanca JE, Vieira A, Lidral AC, Martin JF, Murray JC. Mutations in BMP4 are associated with subepithelial, microform, and overt cleft lip. American Journal of Human Genetics. 2009;84(3):406-411. PMC2667991.
• Howe BJ, Cooper ME, Wehby GL, Resick J, Nidey N, Valencia-Ramirez LC, Lopez-Palacio AM, Rivera D, Vieira AR, Weinberg SM, Marazita ML, Moreno Uribe LM. Dental decay phenotype in nonsyndromic orofacial clefting. Journal of Dental Research. 2017;96(10):1106-1114. PMC5582684.

Relevant Funding: R01-DE016148 (NIDCR) 

Facial Shape and Orofacial Cleft Risk

Influenced largely by the multifactorial threshold model of inheritance, numerous researchers have investigated the hypothesis that embryonic face shape itself may be a risk factor for clefting. In mouse models, strains at-risk for spontaneous clefting have been shown to exhibit distinctive embryonic and post-natal facial features.  In humans, the focus was on unaffected relatives (parents and siblings) of cleft-affected individuals. Since the mid-1960s, there have been over 40 studies comparing the facial features of genetically at-risk relatives to controls; virtually all have used cephalometry or traditional anthropometry. In 2008 and 2009, we led the first studies in humans to investigate the face shape hypothesis using 3D imaging and statistical shape analysis. This analysis and overcame many inherent limitations in prior approaches to help clarify four decades of contradictory findings. Researchers have subsequently used findings from these studies to identify genes associated with quantitative facial traits.   

• Weinberg SM, Naidoo S, Bardi KM, Brandon CA, Neiswanger K, Resick JM, Martin RA, Marazita ML. Face shape of unaffected parents with cleft affected offspring: combining three-dimensional surface imaging and geometric morphometrics. Orthodontics and Craniofacial Research. 2009;12(4):271-281. PMC2765674.
• Roosenboom J, Indencleef K, Hens G, Peeters H, Christensen K, Marazita ML, Claes P, Leslie EJ, Weinberg SM. Testing the face shape hypothesis in twins discordant for nonsyndromic orofacial clefting. American Journal of Medical Genetics Part A. 2017;173(11):2886-2892. PMC5725745.
• Howe LJ, Lee MK, Sharp GC, Smith GD, St Pourcain B, Shaffer JR, Ludwig KU, Mangold E, Marazita ML, Feingold E, Zhurov A, Stergiakouli E, Sandy J, Richmond S, Weinberg SM, Hemani G, Lewis SJ. Investigating the shared genetics of non-syndromic cleft lip/palate and facial morphology. PLoS Genetics. 2018;14(8):e1007501. PMC6089455.
• Indencleef K, Hoskens H, Lee MK, White JD, Liu C, Eller RJ, Naqvi S, Wehby GL, Moreno Uribe LM, Hecht JT, Long RE, Christensen K, Deleyiannis FW, Walsh S, Shriver MD, Richmond S, Wysocka J, Peeters H, Shaffer JR, Marazita ML, Hens G, Weinberg SM, Claes P. The intersection of the genetic architectures of orofacial clefts and normal facial variation. Frontiers in Genetics. 2021;12:626403. PMC7937973.
• Weinberg SM. What’s shape got to do with it? Examining the relationship between facial shape and orofacial clefting. Frontiers in Genetics. 2022;13:891502. PMC9111168.Relevant Funding: R01-DE016148 (NIDCR) 

Digital 3D Stereophotogrammetry in Craniofacial Research

Digital 3D stereophotogrammetry emerged as a viable surface imaging modality for craniofacial research in the early 2000s, as “turn key” systems became cost effective and commercially available. Prior to the advent of these systems, a variety of other surface imaging technologies existed, but were too slow, too expensive or too cumbersome for routine craniofacial research and clinical applications. In 2004, we led the first comprehensive study to test and validate a digital 3D stereophotogrammetry system for craniofacial anthropometric applications. We enhanced this work with the first published study comparing two different 3D camera systems. These studies helped establish digital 3D stereophotogrammetry as the dominant facial surface imaging technology used today. 
 

• Weinberg SM, Naidoo S, Govier DP, Martin RA, Kane AA, Marazita ML. Anthropometric precision and accuracy of digital three-dimensional photogrammetry: comparing the Genex and 3dMD imaging systems to one another and to direct anthropometry. Journal of Craniofacial Surgery. 2006;17(3):477-483.
• Heike CL, Upson K, Stuhaug E, Weinberg SM. 3D digital stereophotogrammetry: A practical guide to facial image acquisition. Head & Face Medicine. 2010;6:18. PMC2920242.
• Camison L, Bykowski M, Lee WW, Carlson JC, Roosenboom J, Goldstein JA, Losee JE, Weinberg SM. Validation of the Vectra H1 portable 3D photogrammetry system for facial imaging. International Journal of Oral & Maxillofacial Surgery. 2018;47(3):403-410. PMC5803347.

Publications

• Seth M Weinberg – Search Results – PubMed (nih.gov)