Mapping genes for human face shape: exploration of univariate phenotyping strategies.

Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits. Author Summary: Advancements linking variation in the human genome to phenotypes have rapidly evolved in recent decades and have revealed that most human traits are influenced by genetic variants to at least some degree. While many traits, such as stature, are straightforward to acquire and investigate, the multivariate and multipartite nature of facial shape makes quantification more challenging. In this study, we compared the impact of different facial phenotyping approaches on gene mapping outcomes. Our findings suggest that the choice of facial phenotyping method has an impact on apparent trait heritability and the ability to detect genetic association signals. These results offer valuable insights into the importance of phenotyping in genetic investigations, especially when dealing with highly complex morphological traits.

DeepFace: Deep-learning-based framework to contextualize orofacial-cleft-related variants during human embryonic craniofacial development.

Orofacial clefts (OFCs) are among the most common human congenital birth defects. Previous multiethnic studies have identified dozens of associated loci for both cleft lip with or without cleft palate (CL/P) and cleft palate alone (CP). Although several nearby genes have been highlighted, the "casual" variants are largely unknown. Here, we developed DeepFace, a convolutional neural network model, to assess the functional impact of variants by SNP activity difference (SAD) scores. The DeepFace model is trained with 204 epigenomic assays from crucial human embryonic craniofacial developmental stages of post-conception week (pcw) 4 to pcw 10. The Pearson correlation coefficient between the predicted and actual values for 12 epigenetic features achieved a median range of 0.50-0.83. Specifically, our model revealed that SNPs significantly associated with OFCs tended to exhibit higher SAD scores across various variant categories compared to less related groups, indicating a context-specific impact of OFC-related SNPs. Notably, we identified six SNPs with a significant linear relationship to SAD scores throughout developmental progression, suggesting that these SNPs could play a temporal regulatory role. Furthermore, our cell-type specificity analysis pinpointed the trophoblast cell as having the highest enrichment of risk signals associated with OFCs. Overall, DeepFace can harness distal regulatory signals from extensive epigenomic assays, offering new perspectives for prioritizing OFC variants using contextualized functional genomic features. We expect DeepFace to be instrumental in accessing and predicting the regulatory roles of variants associated with OFCs, and the model can be extended to study other complex diseases or traits.

The bioelectric mechanisms of local calcium dynamics in cancer cell proliferation: an extension of the A549 in silico cell model.

Introduction: Advances in molecular targeting of ion channels may open up new avenues for therapeutic approaches in cancer based on the cells' bioelectric properties. In addition to in-vitro or in-vivo models, in silico models can provide deeper insight into the complex role of electrophysiology in cancer and reveal the impact of altered ion channel expression and the membrane potential on malignant processes. The A549 in silico model is the first computational cancer whole-cell ion current model that simulates the bioelectric mechanisms of the human non-small cell lung cancer cell line A549 during the different phases of the cell cycle. This work extends the existing model with a detailed mathematical description of the store-operated Ca2+ entry (SOCE) and the complex local intracellular calcium dynamics, which significantly affect the entire electrophysiological properties of the cell and regulate cell cycle progression. Methods: The initial model was extended by a multicompartmental approach, addressing the heterogenous calcium profile and dynamics in the ER-PM junction provoked by local calcium entry of store-operated calcium channels (SOCs) and uptake by SERCA pumps. Changes of cytosolic calcium levels due to diffusion from the ER-PM junction, release from the ER by RyR channels and IP3 receptors, as well as corresponding PM channels were simulated and the dynamics evaluated based on calcium imaging data. The model parameters were fitted to available data from two published experimental studies, showing the function of CRAC channels and indirectly of IP3R, RyR and PMCA via changes of the cytosolic calcium levels. Results: The proposed calcium description accurately reproduces the dynamics of calcium imaging data and simulates the SOCE mechanisms. In addition, simulations of the combined A549-SOCE model in distinct phases of the cell cycle demonstrate how Ca2+ - dynamics influence responding channels such as KCa, and consequently modulate the membrane potential accordingly. Discussion: Local calcium distribution and time evolution in microdomains of the cell significantly impact the overall electrophysiological properties and exert control over cell cycle progression. By providing a more profound description, the extended A549-SOCE model represents an important step on the route towards a valid model for oncological research and in silico supported development of novel therapeutic strategies.

Genome-wide study of gene-by-sex interactions identifies risks for cleft palate.

Structural birth defects affect 3-4% of all live births and, depending on the type, tend to manifest in a sex-biased manner. Orofacial clefts (OFCs) are the most common craniofacial structural birth defects and are often divided into cleft lip with or without cleft palate (CL/P) and cleft palate only (CP). Previous studies have found sex-specific risks for CL/P, but these risks have yet to be evaluated in CP. CL/P is more common in males and CP is more frequently observed in females, so we hypothesized there would also be sex-specific differences for CP. Using a trio-based cohort, we performed sex-stratified genome-wide association studies (GWAS) based on proband sex followed by a genome-wide gene-by-sex (GxS) interaction testing. There were 13 loci significant for GxS interactions, with the top finding in LTBP1 (RR=3.37 [2.04 - 5.56], p=1.93x10 -6 ). LTBP1 plays a role in regulating TGF-B bioavailability, and knockdown in both mice and zebrafish lead to craniofacial anomalies. Further, there is evidence for differential expression of LTBP1 between males and females in both mice and humans. Therefore, we tested the association between the imputed genetically regulated gene expression of genes with significant GxS interactions and the CP phenotype. We found significant association for LTBP1 in cell cultured fibroblasts in female probands (p=0.0013) but not in males. Taken altogether, we show there are sex-specific risks for CP that are otherwise undetectable in a combined sex cohort, and LTBP1 is a candidate risk gene, particularly in females.

Connecting Transcriptomics with Computational Modeling to Reveal Developmental Adaptations in the Human Pediatric Myocardium.

Background: Nearly 1% or 1.3 million babies are born with congenital heart disease (CHD) globally each year - many of whom will require palliative or corrective heart surgery within the first few years of life. A detailed understanding of cardiac maturation can help to expand our knowledge on cardiac diseases that develop during gestation, identify age-appropriate cardiovascular drug therapies, and inform clinical care decisions related to surgical repair, myocardial preservation, or postoperative management. Yet, to date, our knowledge of the temporal changes that cardiomyocytes undergo during postnatal development is largely limited to animal models. Methods: Right atrial tissue samples were collected from n=117 neonatal, infant, and pediatric patients undergoing correct surgery due to (acyanotic) CHD. Patients were stratified into five age groups: neonate (0-30 days), infant (31-364 days), toddler to preschool (1-5 years), school age (6-11 years), and adolescent to young adults (12-32 years). We measured age-dependent adaptations in cardiac gene expression, and used computational modeling to simulate action potential and calcium transients. Results: Enrichment of differentially expressed genes (DEG) was explored, revealing age-dependent changes in several key biological processes (cell cycle, cell division, mitosis), cardiac ion channels, and calcium handling genes. Gene-associated changes in ionic currents exhibited both linear trends and sudden shifts across developmental stages, with changes in calcium handling ( I NCX ) and repolarization ( I K1 ) most strongly associated with an age-dependent decrease in the action potential plateau potential and increase in triangulation, respectively. We also note a shift in repolarization reserve, with lower I Kr expression in younger patients, a finding likely tied to the increased amplitude of I Ks triggered by elevated sympathetic activation in pediatric patients. Conclusion: This study provides valuable insights into age-dependent changes in human cardiac gene expression and electrophysiology among patients with CHD, shedding light on molecular mechanisms underlying cardiac development and function across different developmental stages.

Whole genome sequencing identifies associations for nonsyndromic sagittal craniosynostosis with the intergenic region of BMP2 and noncoding RNA gene LINC01428.

Craniosynostosis (CS) is a major birth defect resulting from premature fusion of cranial sutures. Nonsyndromic CS occurs more frequently than syndromic CS, with sagittal nonsyndromic craniosynostosis (sNCS) presenting as the most common CS phenotype. Previous genome-wide association and targeted sequencing analyses of sNCS have identified multiple associated loci, with the strongest association on chromosome 20. Herein, we report the first whole-genome sequencing study of sNCS using 63 proband-parent trios. Sequencing data for these trios were analyzed using the transmission disequilibrium test (TDT) and rare variant TDT (rvTDT) to identify high-risk rare gene variants. Sequencing data were also examined for copy number variants (CNVs) and de novo variants. TDT analysis identified a highly significant locus at 20p12.3, localized to the intergenic region between BMP2 and the noncoding RNA gene LINC01428. Three variants (rs6054763, rs6054764, rs932517) were identified as potential causal variants due to their probability of being transcription factor binding sites, deleterious combined annotation dependent depletion scores, and high minor allele enrichment in probands. Morphometric analysis of cranial vault shape in an unaffected cohort validated the effect of these three single nucleotide variants (SNVs) on dolichocephaly. No genome-wide significant rare variants, de novo loci, or CNVs were identified. Future efforts to identify risk variants for sNCS should include sequencing of larger and more diverse population samples and increased omics analyses, such as RNA-seq and ATAC-seq.

A common cis-regulatory variant impacts normal-range and disease-associated human facial shape through regulation of PKDCC during chondrogenesis.

Genome-wide association studies (GWAS) identified thousands of genetic variants linked to phenotypic traits and disease risk. However, mechanistic understanding of how GWAS variants influence complex morphological traits and can, in certain cases, simultaneously confer normal-range phenotypic variation and disease predisposition, is still largely lacking. Here, we focus on rs6740960, a single nucleotide polymorphism (SNP) at the 2p21 locus, which in GWAS studies has been associated both with normal-range variation in jaw shape and with an increased risk of non-syndromic orofacial clefting. Using in vitro derived embryonic cell types relevant for human facial morphogenesis, we show that this SNP resides in an enhancer that regulates chondrocytic expression of PKDCC - a gene encoding a tyrosine kinase involved in chondrogenesis and skeletal development. In agreement, we demonstrate that the rs6740960 SNP is sufficient to confer chondrocyte-specific differences in PKDCC expression. By deploying dense landmark morphometric analysis of skull elements in mice, we show that changes in Pkdcc dosage are associated with quantitative changes in the maxilla, mandible, and palatine bone shape that are concordant with the facial phenotypes and disease predisposition seen in humans. We further demonstrate that the frequency of the rs6740960 variant strongly deviated among different human populations, and that the activity of its cognate enhancer diverged in hominids. Our study provides a mechanistic explanation of how a common SNP can mediate normal-range and disease-associated morphological variation, with implications for the evolution of human facial features.

Cardiac-Specific Deletion of Scn8a Mitigates Dravet Syndrome-Associated Sudden Death in Adults.

BACKGROUND: Sudden unexpected death in epilepsy (SUDEP) is a fatal complication experienced by otherwise healthy epilepsy patients. Dravet syndrome (DS) is an inherited epileptic disorder resulting from loss of function of the voltage-gated sodium channel, NaV 1.1, and is associated with particularly high SUDEP risk. Evidence is mounting that NaVs abundant in the brain also occur in the heart, suggesting that the very molecular mechanisms underlying epilepsy could also precipitate cardiac arrhythmias and sudden death. Despite marked reduction of NaV 1.1 functional expression in DS, pathogenic late sodium current (INa,L) is paradoxically increased in DS hearts. However, the mechanisms by which DS directly impacts the heart to promote sudden death remain unclear. OBJECTIVES: In this study, the authors sought to provide evidence implicating remodeling of Na+ - and Ca2+ -handling machinery, including NaV 1.6 and Na+/Ca2+exchanger (NCX) within transverse (T)-tubules in DS-associated arrhythmias. METHODS: The authors undertook scanning ion conductance microscopy (SICM)-guided patch clamp, super-resolution microscopy, confocal Ca2+ imaging, and in vivo electrocardiography studies in Scn1a haploinsufficient murine model of DS. RESULTS: DS promotes INa,L in T-tubular nanodomains, but not in other subcellular regions. Consistent with increased NaV activity in these regions, super-resolution microscopy revealed increased NaV 1.6 density near Ca2+release channels, the ryanodine receptors (RyR2) and NCX in DS relative to WT hearts. The resulting INa,L in these regions promoted aberrant Ca2+ release, leading to ventricular arrhythmias in vivo. Cardiac-specific deletion of NaV 1.6 protects adult DS mice from increased T-tubular late NaV activity and the resulting arrhythmias, as well as sudden death. CONCLUSIONS: These data demonstrate that NaV 1.6 undergoes remodeling within T-tubules of adult DS hearts serving as a substrate for Ca2+ -mediated cardiac arrhythmias and may be a druggable target for the prevention of SUDEP in adult DS subjects.

Indirect Correlative Light and Electron Microscopy (iCLEM): A Novel Pipeline for Multiscale Quantification of Structure From Molecules to Organs.

Correlative light and electron microscopy (CLEM) methods are powerful methods that combine molecular organization (from light microscopy) with ultrastructure (from electron microscopy). However, CLEM methods pose high cost/difficulty barriers to entry and have very low experimental throughput. Therefore, we have developed an indirect correlative light and electron microscopy (iCLEM) pipeline to sidestep the rate-limiting steps of CLEM (i.e., preparing and imaging the same samples on multiple microscopes) and correlate multiscale structural data gleaned from separate samples imaged using different modalities by exploiting biological structures identifiable by both light and electron microscopy as intrinsic fiducials. We demonstrate here an application of iCLEM, where we utilized gap junctions and mechanical junctions between muscle cells in the heart as intrinsic fiducials to correlate ultrastructural measurements from transmission electron microscopy (TEM), and focused ion beam scanning electron microscopy (FIB-SEM) with molecular organization from confocal microscopy and single molecule localization microscopy (SMLM). We further demonstrate how iCLEM can be integrated with computational modeling to discover structure-function relationships. Thus, we present iCLEM as a novel approach that complements existing CLEM methods and provides a generalizable framework that can be applied to any set of imaging modalities, provided suitable intrinsic fiducials can be identified.

netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity.

Introduction: Multi-view data offer advantages over single-view data for characterizing individuals, which is crucial in precision medicine toward personalized prevention, diagnosis, or treatment follow-up. Methods: Here, we develop a network-guided multi-view clustering framework named netMUG to identify actionable subgroups of individuals. This pipeline first adopts sparse multiple canonical correlation analysis to select multi-view features possibly informed by extraneous data, which are then used to construct individual-specific networks (ISNs). Finally, the individual subtypes are automatically derived by hierarchical clustering on these network representations. Results: We applied netMUG to a dataset containing genomic data and facial images to obtain BMI-informed multi-view strata and showed how it could be used for a refined obesity characterization. Benchmark analysis of netMUG on synthetic data with known strata of individuals indicated its superior performance compared with both baseline and benchmark methods for multi-view clustering. The clustering derived from netMUG achieved an adjusted Rand index of 1 with respect to the synthesized true labels. In addition, the real-data analysis revealed subgroups strongly linked to BMI and genetic and facial determinants of these subgroups. Discussion: netMUG provides a powerful strategy, exploiting individual-specific networks to identify meaningful and actionable strata. Moreover, the implementation is easy to generalize to accommodate heterogeneous data sources or highlight data structures.

Syndrome-informed phenotyping identifies a polygenic background for achondroplasia-like facial variation in the general population.

Human craniofacial shape is highly variable yet highly heritable with genetic variants interacting through multiple layers of development. Here, we hypothesize that Mendelian phenotypes represent the extremes of a phenotypic spectrum and, using achondroplasia as an example, we introduce a syndrome-informed phenotyping approach to identify genomic loci associated with achondroplasia-like facial variation in the normal population. We compared three-dimensional facial scans from 43 individuals with achondroplasia and 8246 controls to calculate achondroplasia-like facial scores. Multivariate GWAS of the control scores revealed a polygenic basis for normal facial variation along an achondroplasia-specific shape axis, identifying genes primarily involved in skeletal development. Jointly modeling these genes in two independent control samples showed craniofacial effects approximating the characteristic achondroplasia phenotype. These findings suggest that both complex and Mendelian genetic variation act on the same developmentally determined axes of facial variation, providing new insights into the genetic intersection of complex traits and Mendelian disorders.

Joint multi-ancestry and admixed GWAS reveals the complex genetics behind human cranial vault shape.

The cranial vault in humans is highly variable, clinically relevant, and heritable, yet its genetic architecture remains poorly understood. Here, we conduct a joint multi-ancestry and admixed multivariate genome-wide association study on 3D cranial vault shape extracted from magnetic resonance images of 6772 children from the ABCD study cohort yielding 30 genome-wide significant loci. Follow-up analyses indicate that these loci overlap with genomic risk loci for sagittal craniosynostosis, show elevated activity cranial neural crest cells, are enriched for processes related to skeletal development, and are shared with the face and brain. We present supporting evidence of regional localization for several of the identified genes based on expression patterns in the cranial vault bones of E15.5 mice. Overall, our study provides a comprehensive overview of the genetics underlying normal-range cranial vault shape and its relevance for understanding modern human craniofacial diversity and the etiology of congenital malformations.

Sex Differences in Velopharyngeal Anatomy of 9- and 10-Year-Old Children.

OBJECTIVE: Understanding the normal anatomy of velopharyngeal (VP) mechanism and the emergence of sexual dimorphism provides valuable insights into differences of VP anatomy among males and females. The purpose of this study is to examine sex differences in VP anatomy in a large data set of 3,248 9- and 10-year-old children. METHOD: Static three-dimensional magnetic resonance imaging was used to compare five VP characteristics including velar length, velar thickness, effective velar length, levator veli palatini muscle length, and pharyngeal depth between age-matched males (n = 1,670) and females (n = 1,578). Additionally, these dimensions were used to determine the VP ratio and effective VP ratio. RESULTS: Males showed significantly larger dimensions for all VP distances and significantly lower ratios of velar length and effective velar length to pharyngeal depth (p < .05). The magnitude of these effect sizes was small to medium, with Cohen's d values ranging from 0.12 to 0.63. Additionally, the VP ratio and effective VP ratio are lower among males compared to females (p < .05). CONCLUSIONS: Results suggest the presence of sexual dimorphism in the VP mechanism among 9- and 10-year-old children. These findings emphasize the necessity of using different normative data for males and females when making comparisons to patients with cleft palate.

Rare variant modifier analysis identifies variants in SEC24D associated with orofacial cleft subtypes.

As one of the most common structural birth defects, orofacial clefts (OFCs) have been studied for decades, and recent studies have demonstrated that there are genetic differences between the different phenotypic presentations of OFCs. However, the contribution of rare genetic variation genome-wide to different subtypes of OFCs has been understudied, with most studies focusing on common genetic variation or rare variation within targeted regions of the genome. Therefore, we used whole-genome sequencing data from the Gabriella Miller Kids First Pediatric Research Program to conduct a gene-based burden analysis to test for genetic modifiers of cleft lip (CL) vs cleft lip and palate (CLP). We found that there was a significantly increased burden of rare variants in SEC24D in CL cases compared to CLP cases (p = 6.86 [Formula: see text] 10-7). Of the 15 variants within SEC24D, 53.3% were synonymous, but overlapped a known craniofacial enhancer. We then tested whether these variants could alter predicted transcription factor binding sites (TFBS), and found that the rare alleles destroyed binding sites for 9 transcription factors (TFs), including Pax1 (p = 0.0009), and created binding sites for 23 TFs, including Pax6 (p = 6.12 [Formula: see text] 10-5) and Pax9 (p = 0.0001), which are known to be involved in normal craniofacial development, suggesting a potential mechanism by which these synonymous variants could have a functional impact. Overall, this study indicates that rare genetic variation may contribute to the phenotypic heterogeneity of OFCs and suggests that regulatory variation may also contribute and warrant further investigation in future studies of genetic variants controlling risk to OFC.

Trio-based GWAS identifies novel associations and subtype-specific risk factors for cleft palate.

Cleft palate (CP) is one of the most common craniofacial birth defects; however, there are relatively few established genetic risk factors associated with its occurrence despite high heritability. Historically, CP has been studied as a single phenotype, although it manifests across a spectrum of defects involving the hard and/or soft palate. We performed a genome-wide association study using transmission disequilibrium tests of 435 case-parent trios to evaluate broad risks for any cleft palate (ACP) (n = 435), and subtype-specific risks for any cleft soft palate (CSP), (n = 259) and any cleft hard palate (CHP) (n = 125). We identified a single genome-wide significant locus at 9q33.3 (lead SNP rs7035976, p = 4.24 × 10-8) associated with CHP. One gene at this locus, angiopoietin-like 2 (ANGPTL2), plays a role in osteoblast differentiation. It is expressed both in craniofacial tissue of human embryos and developing mouse palatal shelves. We found 19 additional loci reaching suggestive significance (p < 5 × 10-6), of which only one overlapped between groups (chromosome 17q24.2, ACP and CSP). Odds ratios for the 20 loci were most similar across all 3 groups for SNPs associated with the ACP group, but more distinct when comparing SNPs associated with either subtype. We also found nominal evidence of replication (p < 0.05) for 22 SNPs previously associated with orofacial clefts. Our study to evaluate CP risks in the context of its subtypes and we provide newly reported associations affecting the broad risk for CP as well as evidence of subtype-specific risks.

Data-driven trait heritability-based extraction of human facial phenotypes.

A genome-wide association study (GWAS) of a complex, multi-dimensional morphological trait, such as the human face, typically relies on predefined and simplified phenotypic measurements, such as inter-landmark distances and angles. These measures are predominantly designed by human experts based on perceived biological or clinical knowledge. To avoid use handcrafted phenotypes (i.e., a priori expert-identified phenotypes), alternative automatically extracted phenotypic descriptors, such as features derived from dimension reduction techniques (e.g., principal component analysis), are employed. While the features generated by such computational algorithms capture the geometric variations of the biological shape, they are not necessarily genetically relevant. Therefore, genetically informed data-driven phenotyping is desirable. Here, we propose an approach where phenotyping is done through a data-driven optimization of trait heritability, defined as the degree of variation in a phenotypic trait in a population that is due to genetic variation. The resulting phenotyping process consists of two steps: 1) constructing a feature space that models shape variations using dimension reduction techniques, and 2) searching for directions in the feature space exhibiting high trait heritability using a genetic search algorithm (i.e., heuristic inspired by natural selection). We show that the phenotypes resulting from the proposed trait heritability-optimized training differ from those of principal components in the following aspects: 1) higher trait heritability, 2) higher SNP heritability, and 3) identification of the same number of independent genetic loci with a smaller number of effective traits. Our results demonstrate that data-driven trait heritability-based optimization enables the automatic extraction of genetically relevant phenotypes, as shown by their increased power in genome-wide association scans.