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BACKGROUND: Total serum IgE (tIgE) is an important intermediate phenotype of allergic disease. Whole genome genetic association studies across ancestries may identify important determinants of IgE. OBJECTIVE: By leveraging data from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) and the Atopic Dermatitis Research Network (ADRN), we aim to increase understanding of genetic variants affecting tIgE production across the ancestry and allergic disease spectrum (N=21,901). METHODS: We performed genome-wide association within strata of study, disease, and ancestry groups, and combined results via a meta-regression approach that models heterogeneity attributable to ancestry. We also tested for association between HLA alleles called from whole genome sequence data and tIgE, assessing replication of associations in HLA alleles called from genotype array data. For details, please see the Methods section in this article’s Online Repository at www.jacionline.org. RESULTS: We identified six loci at genome-wide significance (P

The folate-mediated one-carbon metabolism pathway is thought to play an important role in the etiology of non-syndromic oral clefts (NSOFC), although none of the genes in this pathway has shown significant signals in genome-wide association studies (GWAS). Recent evidence indicated that enhanced understanding could be gained by aggregating multiple SNPs effect simultaneously into polygenic risk score (PRS) to assess its association with disease risks. This study is aimed to assess the association between the genetic effect of folate-mediated one-carbon metabolism pathway and NSOFC risks using PRS based on a case-parent trio design. A total of 297 SNPs mapped from 18 genes in the folate-mediated one-carbon metabolism pathway were aggregated from a GWAS of 2458 case-parent trios recruited from an international consortium. We found a PRS based on the folate-mediated one-carbon metabolism pathway was significant among all NSOFC trios (OR = 1.95, 95% CI: 1.66-2.28, p = 2.39 × 10-16 ), as well as two major subtypes, non-syndromic cleft lip with or without cleft palate (NSCL/P) trios (OR = 1.71, 95% CI: 1.50-1.96, p = 7.66 × 10-15 ) and non-syndromic cleft palate only (NSCPO) trios (OR = 1.51, 95% CI: 1.36-1.68, p = 2.1 × 10-14 ). Similar results were also observed in further subgroup analyses stratified into Asian and European trios. The averaged PRS of the folate-mediated one-carbon metabolism pathway varied between the NSOFC case group and its comparison group (p

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI’s Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.

Novel or rare damaging mutations have been implicated in the developmental pathogenesis of nonsyndromic cleft lip with or without cleft palate (nsCL ± P). Thus, we investigated the human genome for high-impact mutations that could explain the risk of nsCL ± P in our cohorts.We conducted next-generation sequencing (NGS) analysis of 130 nsCL ± P case-parent African trios to identify pathogenic variants that contribute to the risk of clefting. We replicated this analysis using whole-exome sequence data from a Brazilian nsCL ± P cohort. Computational analyses were then used to predict the mechanism by which these variants could result in increased risks for nsCL ± P.We discovered damaging mutations within theThis is the first report on the contribution of

Summary Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380 ), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

PurposeOrofacial clefts (OFCs) are common birth defects including cleft lip (CL), cleft lip and palate (CLP), and cleft palate (CP). OFCs have heterogeneous etiologies, complicating clinical diagnostics as it is not always apparent if the cause is Mendelian, environmental, or multifactorial. Sequencing is not currently performed for isolated or sporadic OFCs, so we estimated the diagnostic yield for 418 genes in 841 cases and 294 controls.MethodsWe evaluated 418 genes using genome sequencing and curated variants to assess their pathogenicity using American College of Medical Genetics criteria.Results9.04% of cases and 1.02% of controls had ‘likely pathogenic’ (LP) variants (pCTNND1andIRF6, accounted for more than half of the yield (4.64% of cases). Most variants (61.8%) were ‘variants of uncertain significance’ (VUSs), occurring more frequently in cases (p=0.004), but no individual gene showed a significant excess of VUSs.ConclusionThese results underscore the etiological heterogeneity of OFCs and suggest sequencing could reduce the diagnostic gap in OFCs.

Risk of chronic obstructive pulmonary disease (COPD) is determined by both cigarette smoking and genetic susceptibility, but little is known about gene-by-smoking interactions. We performed a genome-wide association analysis of 179,689 controls and 21,077 COPD cases from UK Biobank subjects of European ancestry recruited from 2006 to 2010, considering genetic main effects and gene-by-smoking interaction effects simultaneously (2-degrees-of-freedom (df) test) as well as interaction effects alone (1-df interaction test). We sought to replicate significant results in COPDGene (United States, 2008–2010) and SpiroMeta Consortium (multiple countries, 1947–2015) data. We considered 2 smoking variables: 1) ever/never and 2) current/noncurrent. In the 1-df test, we identified 1 genome-wide significant locus on 15q25.1 (cholinergic receptor nicotinic β4 subunit, or CHRNB4) for ever- and current smoking and identified PI*Z allele (rs28929474) of serpin family A member 1 (SERPINA1) for ever-smoking and 3q26.2 (MDS1 and EVI1 complex locus, or MECOM) for current smoking in an analysis of previously reported COPD loci. In the 2-df test, most of the significant signals were also significant for genetic marginal effects, aside from 16q22.1 (sphingomyelin phosphodiesterase 3, or SMPD3) and 19q13.2 (Egl-9 family hypoxia inducible factor 2, or EGLN2). The significant effects at 15q25.1 and 19q13.2 loci, both previously described in prior genome-wide association studies of COPD or smoking, were replicated in COPDGene and SpiroMeta. We identified interaction effects at previously reported COPD loci; however, we failed to identify novel susceptibility loci.

Purpose Medication patterns include all medications in an individual's clinical profile. We aimed to identify chronic co-morbidity treatment patterns through medication use among COPDGene participants and determine whether these patterns were associated with mortality, acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and quality of life. Materials and methods Participants analyzed here completed Phase 1 (P1) and/or Phase 2 (P2) of COPDGene. Latent class analysis (LCA) was used to identify medication patterns and assign individuals into unobserved LCA classes. Mortality, AECOPD, and the St. George's Respiratory Questionnaire (SGRQ) health status were compared in different LCA classes through survival analysis, logistic regression, and Kruskal-Wallis test, respectively. Results LCA identified 8 medication patterns from 32 classes of chronic comorbid medications. A total of 8110 out of 10,127 participants with complete covariate information were included. Survival analysis adjusted for covariates showed, compared to a low medication use class, mortality was highest in participants with hypertension+diabetes+statin+antiplatelet medication group. Participants in hypertension+SSRI+statin medication group had the highest odds of AECOPD and the highest SGRQ score at both P1 and P2. Conclusion Medication pattern can serve as a good indicator of an individual's comorbidities profile and improves models predicting clinical outcomes.

The case–control study design is one of the main tools for detecting associations between genetic markers and diseases. It is well known that population substructure can lead to spurious association between disease status and a genetic marker if the prevalence of disease and the marker allele frequency vary across subpopulations. In this paper, we propose a novel statistical method to estimate the association in case–control studies with unmeasured population substructure. The proposed method takes two steps. First, the information on genomic markers and disease status is used to infer the population substructure; second, the association between the disease and the test marker adjusting for the population substructure is modeled and estimated parametrically through polytomous logistic regression. The performance of the proposed method, relative to the existing methods, on bias, coverage probability and computational time, is assessed through simulations. The method is applied to an end-stage renal disease study in African Americans population.

Polysubstance use among pregnant women has increased because of the opioid epidemic and the increasing legalization of cannabis along with persistent tobacco and alcohol consumption. Previous research on prenatal substance use and the child's risk of attention-deficit/hyperactivity disorder (ADHD) has mostly focused on single-substance exposures; simultaneous examination of multiple substance use and assessment of their synergistic health consequences is needed.To assess the consequences of the use of specific substances during pregnancy, investigate whether the interaction of multiple prenatal substance exposures is associated with increases in the risk of childhood ADHD, and estimate the aggregate burden of polysubstance exposure during gestation.This cohort study analyzed data from the Boston Birth Cohort from 1998 to 2019. The sample of the present study comprised a multiethnic urban cohort of mother-child pairs who were predominantly low income. A total of 3138 children who were enrolled shortly after birth at Boston Medical Center were included and followed up from age 6 months to 21 years.Substance use during pregnancy was identified based on self-reported tobacco smoking, alcohol consumption, and use of cannabis, cocaine, or opioids in any trimester of pregnancy. Diagnostic codes for neonatal opioid withdrawal syndrome or neonatal abstinence syndrome from the International Classification of Diseases, Ninth Revision, and the International Classification of Diseases, Tenth Revision, were also used to identify opioid exposure during gestation.ADHD diagnosis in the child's electronic medical record.Among 3138 children (1583 boys [50.4%]; median age, 12 years [IQR, 9-14 years]; median follow-up, 10 years [IQR, 7-12 years]) in the final analytic sample, 486 (15.5%) had an ADHD diagnosis and 2652 (84.5%) were neurotypical. The median postnatal follow-up duration was 12 years (IQR, 9-14 years). Among mothers, 46 women (1.5%) self-identified as Asian (non-Pacific Islander), 701 (22.3%) as Hispanic, 1838 (58.6%) as non-Hispanic Black, 227 (7.2%) as non-Hispanic White, and 326 (10.4%) as other races and/or ethnicities (including American Indian or Indigenous, Cape Verdean, Pacific Islander, multiracial, other, or unknown). A total of 759 women (24.2%) reported the use of at least 1 substance during pregnancy, with tobacco being the most frequently reported (580 women [18.5%]). Cox proportional hazards models revealed that opioid exposure (60 children) had the highest adjusted hazard ratio (HR) for ADHD (2.19; 95% CI, 1.10-4.37). After including main statistical effects of all individual substances in an elastic net regression model, the HR of opioids was reduced to 1.60, and evidence of a statistical interaction between opioids and both cannabis and alcohol was found, producing 1.42 and 1.15 times higher risk of ADHD, respectively. The interaction between opioids and smoking was also associated with a higher risk of ADHD (HR, 1.17).The findings of this study suggest that it is important to consider prenatal concurrent exposure to multiple substances and their possible interactions when counseling women regarding substance use during pregnancy, the future risk of ADHD for their children, and strategies for cessation and treatment programs.

Genetic association studies of child health outcomes often employ family-based study designs. One of the most popular family-based designs is the case-parent trio design that considers the smallest possible nuclear family consisting of two parents and their affected child. This trio design is particularly advantageous for studying relatively rare disorders because it is less prone to type 1 error inflation due to population stratification compared to population-based study designs (e.g., case-control studies). However, obtaining genetic data from both parents is difficult, from a practical perspective, and many large studies predominantly measure genetic variants in mother-child dyads. While some statistical methods for analyzing parent-child dyad data (most commonly involving mother-child pairs) exist, it is not clear if they provide the same advantage as trio methods in protecting against population stratification, or if a specific dyad design (e.g., case-mother dyads vs. case-mother/control-mother dyads) is more advantageous. In this article, we review existing statistical methods for analyzing genome-wide marker data on dyads and perform extensive simulation experiments to benchmark their type I errors and statistical power under different scenarios. We extend our evaluation to existing methods for analyzing a combination of case-parent trios and dyads together. We apply these methods on genotyped and imputed data from multiethnic mother-child pairs only, case-parent trios only or combinations of both dyads and trios from the Gene, Environment Association Studies consortium (GENEVA), where each family was ascertained through a child affected by nonsyndromic cleft lip with or without cleft palate. Results from the GENEVA study corroborate the findings from our simulation experiments. Finally, we provide recommendations for using statistical genetic association methods for dyads.

PURPOSE: The growing size of public variant repositories prompted us to test the accuracy of pathogenicity prediction of DNA variants using population data alone. METHODS: Under the a priori assumption that the ratio of the prevalence of variants in healthy population vs that in affected populations form 2 distinct distributions (pathogenic and benign), we used a Bayesian method to assign probability to a variant belonging to either distribution. RESULTS: The approach, termed Bayesian prevalence ratio (BayPR), accurately parsed 300 of 313 expertly curated CFTR variants: 284 of 296 pathogenic/likely pathogenic variants in 1 distribution and 16 of 17 benign/likely benign variants in another. BayPR produced an area under the receiver operating characteristic curve of 0.99 for 103 functionally confirmed missense CFTR variants, which is equal to or exceeds 10 commonly used algorithms (area under the receiver operating characteristic curve range 0.54–0.99). Application of BayPR to expertly curated variants in 8 genes associated with 7 Mendelian conditions led to the assignment of a disease-causing probability of ≥80% to 1350 of 1374 (98.3%) pathogenic/likely pathogenic variants and of ≤20% to 22 of 23 (95.7%) benign/likely benign variants. CONCLUSION: Irrespective of the variant type or functional effect, the BayPR approach provides probabilities of pathogenicity for DNA variants responsible for Mendelian disorders using only the variant counts in affected and unaffected population samples.

RATIONALE: Multiple studies have demonstrated an increased risk of chronic obstructive pulmonary disease (COPD) in heterozygous carriers of the AAT (alpha-1 antitrypsin) Z allele. However, it is not known if MZ subjects with COPD are phenotypically different from noncarriers (MM genotype) with COPD. OBJECTIVES: To assess if MZ subjects with COPD have different clinical features compared with MM subjects with COPD. METHODS: Genotypes of SERPINA1 were ascertained by using whole-genome sequencing data in three independent studies. We compared outcomes between MM subjects with COPD and MZ subjects with COPD in each study and combined the results in a meta-analysis. We performed longitudinal and survival analyses to compare outcomes in MM and MZ subjects with COPD over time. MEASUREMENTS AND MAIN RESULTS: We included 290 MZ subjects with COPD and 6,184 MM subjects with COPD across the three studies. MZ subjects had a lower FEV(1)% predicted and greater quantitative emphysema on chest computed tomography scans compared with MM subjects. In a meta-analysis, the FEV(1) was 3.9% lower (95% confidence interval [CI], −6.55% to −1.26%) and emphysema (the percentage of lung attenuation areas

The majority (85%) of nonsyndromic cleft lip with or without cleft palate (nsCL/P) cases occur sporadically, suggesting a role for de novo mutations (DNMs) in the etiology of nsCL/P. To identify high impact DNMs that contribute to the risk of nsCL/P, we conducted whole genome sequencing (WGS) analyses in 130 African case-parent trios (affected probands and unaffected parents). We identified 162 high confidence protein-altering DNMs that contribute to the risk of nsCL/P. These include novel loss-of-function DNMs in the ACTL6A, ARHGAP10, MINK1, TMEM5 and TTN genes; as well as missense variants in ACAN, DHRS3, DLX6, EPHB2, FKBP10, KMT2D, RECQL4, SEMA3C, SEMA4D, SHH, TP63, and TULP4. Experimental evidence showed that ACAN, DHRS3, DLX6, EPHB2, FKBP10, KMT2D, MINK1, RECQL4, SEMA3C, SEMA4D, SHH, TP63, and TTN genes contribute to facial development and mutations in these genes could contribute to CL/P. Association studies have identified TULP4 as a potential cleft candidate gene, while ARHGAP10 interacts with CTNNB1 to control WNT signaling. DLX6, EPHB2, SEMA3C and SEMA4D harbor novel damaging DNMs that may affect their role in neural crest migration and palatal development. This discovery of pathogenic DNMs also confirms the power of WGS analysis of trios in the discovery of potential pathogenic variants.

Genetic association studies of child health outcomes often employ family-based designs. One of the most popular family-based designs is the case-parent trio design that considers the smallest possible nuclear family consisting of two parents and their affected child. This trio design is particularly advantageous for studying relatively rare disorders because it is less prone to type 1 error inflation due to population stratification compared to population-based study designs (e.g., case-control studies). However, obtaining genetic data from both parents is difficult, from a practical perspective, and many large studies predominantly measure genetic variants in mother-child dyads. While some statistical methods for analyzing parent-child dyad data (most commonly involving mother-child pairs) exist, it is not clear if they provide the same advantage as trio methods in protecting against population stratification, or if a specific dyad design (e.g., case-mother dyads vs. case-mother/control-mother dyads) is more advantageous. In this article, we review existing statistical methods for analyzing genome-wide data on dyads and perform extensive simulation experiments to benchmark their type I errors and statistical power under different scenarios. We extend our evaluation to existing methods for analyzing a combination of case-parent trios and dyads together. We apply these methods on genotyped and imputed data from multi-ethnic mother-child pairs only, case-parent trios only or combinations of both dyads and trios from the Gene, Environment Association Studies consortium (GENEVA), where each family was ascertained through a child affected by nonsyndromic cleft lip with or without cleft palate. Results from the GENEVA study corroborate the findings from our simulation experiments. Finally, we provide recommendations for using statistical genetic association methods for dyads.

Chronic obstructive pulmonary disease (COPD) is a common and progressive disease that is influenced by both genetic and environmental factors. For many years, knowledge of the genetic basis of COPD was limited to Mendelian syndromes, such as alpha-1 antitrypsin deficiency and cutis laxa, caused by rare genetic variants. Over the past decade, the proliferation of genome-wide association studies, the accessibility of whole-genome sequencing, and the development of novel methods for analyzing genetic variation data have led to a substantial increase in the understanding of genetic variants that play a role in COPD susceptibility and COPD-related phenotypes. COPDGene (Genetic Epidemiology of COPD), a multicenter, longitudinal study of over 10,000 current and former cigarette smokers, has been pivotal to these breakthroughs in understanding the genetic basis of COPD. To date, over 20 genetic loci have been convincingly associated with COPD affection status, with additional loci demonstrating association with COPD-related phenotypes such as emphysema, chronic bronchitis, and hypoxemia. In this review, we discuss the contributions of the COPDGene study to the discovery of these genetic associations as well as the ongoing genetic investigations of COPD subtypes, protein biomarkers, and post–genome-wide association study analysis.

Objectives Dental utilization is an important determinant of oral health and well‐being. The aim of this study was to evaluate potential associations between a variety of biopsychosocial factors and dental utilization in north‐central Appalachia, USA, a region where oral health disparities are profound. Methods This study used household‐based data from the Center for Oral Health Research in Appalachia (COHRA1) study in north‐central Appalachia, including 449 families with 868 adults. The generalized estimating equation (GEE) approach was used to determine the best‐fitting predictor model for dental utilization among adult family members. Results On average across West Virginia and Pennsylvania, having dental insurance was associated with greater dental utilization over a 3‐year time period (OR = 2.20, 95% CI = 1.54, 3.14). When stratified by state, the association held for only West Virginia (OR = 2.41, 95% CI = 1.54, 3.79) and was nonsignificant for Pennsylvania residents (OR = 1.50, 95% CI = 0.80, 2.79). Individuals from Pennsylvania were more likely to utilize dental care and participants from West Virginia less so (2.31, 95% CI = 1.57, 3.40). Females from Pennsylvania were more likely than males to regularly seek dental care (OR = 1.44, 95% CI = 1.00, 2.05), and a higher income was associated with greater frequency of regular dental visits (OR = 1.21, 95% CI = 1.09, 1.34) in West Virginia. Individuals from Pennsylvania who scored higher on the Physiological Arousal subscale of the Dental Fear Survey were more likely to attend routine care visits (OR = 1.18, 95% CI = 1.03, 1.35). Across both states, more fatalistic beliefs related to oral health care also predicted less routine care (OR = 0.87, 95% CI = 0.81, 0.94), and more investment in or more positive attitudes towards one's oral health also was associated with higher utilization (OR = 1.18, 95% CI = 1.13, 1.23). Conclusions Overall, the findings of this study suggest state residency, sex, insurance, income, fatalistic beliefs, health values, and aspects of dental care‐related anxiety and fear predicted dental care utilization in north‐central Appalachia. These findings reinforce the need to address insurance and other economic factors affecting utilization and to consider how individual‐level fatalistic beliefs and oral health values may affect utilization of routine oral health care.

Novel or rare damaging mutations have been implicated in the developmental pathogenesis of nonsyndromic cleft lip with or without cleft palate (nsCL ± P). Thus, we investigated the human genome for high-impact mutations that could explain the risk of nsCL ± P in our cohorts. We conducted next-generation sequencing (NGS) analysis of 130 nsCL ± P case-parent African trios to identify pathogenic variants that contribute to the risk of clefting. We replicated this analysis using whole-exome sequence data from a Brazilian nsCL ± P cohort. Computational analyses were then used to predict the mechanism by which these variants could result in increased risks for nsCL ± P. We discovered damaging mutations within the AFDN gene, a cell adhesion molecule (CAMs) that was previously shown to contribute to cleft palate in mice. These mutations include p.Met1164Ile, p.Thr453Asn, p.Pro1638Ala, p.Arg669Gln, p.Ala1717Val, and p.Arg1596His. We also discovered a novel splicing p.Leu1588Leu mutation in this protein. Computational analysis suggests that these amino acid changes affect the interactions with other cleft-associated genes including nectins (PVRL1, PVRL2, PVRL3, and PVRL4) CDH1, CTNNA1, and CTNND1. This is the first report on the contribution of AFDN to the risk for nsCL ± P in humans. AFDN encodes AFADIN, an important CAM that forms calcium-independent complexes with nectins 1 and 4 (encoded by the genes PVRL1 and PVRL4). This discovery shows the power of NGS analysis of multiethnic cleft samples in combination with a computational approach in the understanding of the pathogenesis of nsCL ± P.