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To analyze pedigrees with quantitative trait (QT) and sequence data, we developed a rare variant (RV) quantitative nonparametric linkage (QNPL) method, which evaluates sharing of minor alleles. RV-QNPL has greater power than the traditional QNPL that tests for excess sharing of minor and major alleles. RV-QNPL is robust to population substructure and admixture, locus heterogeneity, and inclusion of nonpathogenic variants and can be readily applied outside of coding regions. When QNPL was used to analyze common variants, it often led to loci mapping to large intervals, e.g., >40 Mb. In contrast, when RVs are analyzed, regions are well defined, e.g., a gene. Using simulation studies, we demonstrate that RV-QNPL is substantially more powerful than applying traditional QNPL methods to analyze RVs. RV-QNPL was also applied to analyze age-at-onset (AAO) data for 107 late-onset Alzheimer’s disease (LOAD) pedigrees of Caribbean Hispanic and European ancestry with whole-genome sequence data. When AAO of AD was analyzed regardless of APOE ε4 status, suggestive linkage (LOD = 2.4) was observed with RVs in KNDC1 and nominally significant linkage (p

We previously demonstrated how sharing of rare variants (RVs) in distant affected relatives can be used to identify variants causing a complex and heterogeneous disease. This approach tested whether single RVs were shared by all sequenced affected family members. However, as with other study designs, joint analysis of several RVs (e.g., within genes) is sometimes required to obtain sufficient statistical power. Further, phenocopies can lead to false negatives for some causal RVs if complete sharing among affected is required. Here, we extend our methodology (Rare Variant Sharing, RVS) to address these issues. Specifically, we introduce gene-based analyses, a partial sharing test based on RV sharing probabilities for subsets of affected relatives and a haplotype-based RV definition. RVS also has the desirable feature of not requiring external estimates of variant frequency or control samples, provides functionality to assess and address violations of key assumptions, and is available as open source software for genome-wide analysis. Simulations including phenocopies, based on the families of an oral cleft study, revealed the partial and complete sharing versions of RVS achieved similar statistical power compared with alternative methods (RareIBD and the Gene-Based Segregation Test), and had superior power compared with the pedigree Variant Annotation, Analysis, and Search Tool (pVAAST) linkage statistic. In studies of multiplex cleft families, analysis of rare single nucleotide variants in the exome of 151 affected relatives from 54 families revealed no significant excess sharing in any one gene, but highlighted different patterns of sharing revealed by the complete and partial sharing tests.

Parametric or model-based linkage analysis assumes that models describing both the trait and marker loci are known without error. Nonparametric, model-free or weakly parametric linkage methods make fewer assumptions about the trait model. Keywords: power; type 1 error; heterogeneity; model-based; bias

Vitamin B12 deficiency is common in older individuals. Circulating vitamin B12 concentration can be used to diagnose deficiency, but this test has substantial false positive and false negative rates. We conducted genome-wide association studies (GWAS) in which we resolved total serum vitamin B12 into the fractions bound to transcobalamin and haptocorrin: two carrier proteins with very different biological properties. We replicated reported associations between total circulating vitamin B12 concentrations and a common null variant in FUT2. This allele determines the secretor phenotype in which blood group antigens are found in non-blood body fluids. Vitamin B12 bound to haptocorrin (holoHC) remained highly associated with FUT2 rs601338 (p.Trp154Ter). Transcobalamin bound vitamin B12 (holoTC) was not influenced by this variant. HoloTC is the bioactive the form of the vitamin and is taken up by all tissues. In contrast, holoHC is only taken up by the liver. Using holoHC from individuals with known FUT2 genotypes, we demonstrated that FUT2 rs601338 genotype influences the glycosylation of haptocorrin. We then developed an experimental model demonstrating that holoHC is transported into cultured hepatic cells (HepG2) via the asialoglycoprotein receptor (ASGR). Our data challenge current published hypotheses on the influence of genetic variation on this clinically important measure and are consistent with a model in which FUT2 rs601338 influences holoHC by altering haptocorrin glycosylation, whereas B12 bound to non-glycosylated transcobalamin (i.e. holoTC) is not affected. Our findings explain some of the observed disparity between use of total B12 or holoTC as first-line clinical tests of vitamin B12 status.

Purpose: The purpose of this study was to perform genetic linkage analysis and association analysis on exome genotyping from highly aggregated African American families with nonpathogenic myopia. African Americans are a particularly understudied population with respect to myopia. Methods: One hundred six African American families from the Philadelphia area with a family history of myopia were genotyped using an Illumina ExomePlus array and merged with previous microsatellite data. Myopia was initially measured in mean spherical equivalent (MSE) and converted to a binary phenotype where individuals were identified as affected, unaffected, or unknown. Parametric linkage analysis was performed on both individual variants (single-nucleotide polymorphisms [SNPs] and microsatellites) as well as gene-based markers. Family-based association analysis and transmission disequilibrium test (TDT) analysis modified for rare variants was also performed. Results: Genetic linkage analysis identified 2 genomewide significant variants at 7p15.2 and 7p14.2 (in the intergenic region between MIR148A and NFE2L3 and in the noncoding RNA LOC401324) and 2 genomewide significant genes (CRHR2 and AVL9) both at 7p14.3. No genomewide results were found in the association analyses. Conclusions: This study identified a significant linkage peak in African American families for myopia at 7p15.2 to 7p14.2, the first potential risk locus for myopia in African Americans. Interesting candidate genes are located in the region, including PDE1C, which is highly expressed in the eyes, and known to be involved in retinal development. Further identification of the causal variants at this linkage peak will help elucidate the genetics of myopia in this understudied population.

Item does not contain fulltext PURPOSE: The International Myopia Institute (IMI) Yearly Digest highlights new research considered to be of importance since the publication of the first series of IMI white papers. METHODS: A literature search was conducted for articles on myopia between 2019 and mid-2020 to inform definitions and classifications, experimental models, genetics, interventions, clinical trials, and clinical management. Conference abstracts from key meetings in the same period were also considered. RESULTS: One thousand articles on myopia have been published between 2019 and mid-2020. Key advances include the use of the definition of premyopia in studies currently under way to test interventions in myopia, new definitions in the field of pathologic myopia, the role of new pharmacologic treatments in experimental models such as intraocular pressure-lowering latanoprost, a large meta-analysis of refractive error identifying 336 new genetic loci, new clinical interventions such as the defocus incorporated multisegment spectacles and combination therapy with low-dose atropine and orthokeratology (OK), normative standards in refractive error, the ethical dilemma of a placebo control group when myopia control treatments are established, reporting the physical metric of myopia reduction versus a percentage reduction, comparison of the risk of pediatric OK wear with risk of vision impairment in myopia, the justification of preventing myopic and axial length increase versus quality of life, and future vision loss. CONCLUSIONS: Large amounts of research in myopia have been published since the IMI 2019 white papers were released. The yearly digest serves to highlight the latest research and advances in myopia.

Background Nonsyndromic oral clefts are craniofacial malformations, which include cleft lip with or without cleft palate. The etiology for oral clefts is complex with both genetic and environmental factors contributing to risk. Previous genome-wide association (GWAS) studies have identified multiple loci with small effects; however, many causal variants remain elusive. Methods In this study, we address this by specifically looking for rare, potentially damaging variants in family-based data. We analyzed both whole exome sequence (WES) data and whole genome sequence (WGS) data in multiplex cleft families to identify variants shared by affected individuals. Results Here we present the results from these analyses. Our most interesting finding was from a single Syrian family, which showed enrichment of nonsynonymous and potentially damaging rare variants in two genes: CASP9 and FAT4. Conclusion Neither of these candidate genes has previously been associated with oral clefts and, if confirmed as contributing to disease risk, may indicate novel biological pathways in the genetic etiology for oral clefts.

The structure of the cornea is vital to its transparency, and dystrophies that disrupt corneal organization are highly heritable. To understand the genetic aetiology of Fuchs endothelial corneal dystrophy (FECD), the most prevalent corneal disorder requiring transplantation, we conducted a genome-wide association study (GWAS) on 1,404 FECD cases and 2,564 controls of European ancestry, followed by replication and meta-analysis, for a total of 2,075 cases and 3,342 controls. We identify three novel loci meeting genome-wide significance (P, Fuchs endothelial corneal dystrophy (FECD) is one of the most common reasons for corneal transplantation, and is known to cluster in families. Here, the authors discover new genetic loci associated with FECD with sex-specific effects and implications for disease mechanism.

Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results.

Background Previous studies using different cardiac phenotypes, technologies and designs suggest a burden of large, rare or de novo copy number variants (CNVs) in subjects with congenital heart defects. We sought to identify disease-related CNVs, candidate genes, and functional pathways in a large number of cases with conotruncal and related defects that carried no known genetic syndrome. Methods Cases and control samples were divided into two cohorts and genotyped to assess each subject's CNV content. Analyses were performed to ascertain differences in overall CNV prevalence and to identify enrichment of specific genes and functional pathways in conotruncal cases relative to healthy controls. Results Only findings present in both cohorts are presented. From 973 total conotruncal cases, a burden of rare CNVs was detected in both cohorts. Candidate genes from rare CNVs found in both cohorts were identified based on their association with cardiac development or disease, and/or their reported disruption in published studies. Functional and pathway analyses revealed significant enrichment of terms involved in either heart or early embryonic development. Conclusion Our study tested one of the largest cohorts specifically with cardiac conotruncal and related defects. These results confirm and extend previous findings that CNVs contribute to disease risk for congenital heart defects in general and conotruncal defects in particular. As disease heterogeneity renders identification of single recurrent genes or loci difficult, functional pathway and gene regulation network analyses appear to be more informative. Birth Defects Research, 2017. © 2017 Wiley Periodicals, Inc.

In this paper, extensive simulations are performed to compare two statistical methods to analyze multiple correlated quantitative phenotypes: (1) approximate F-distributed tests of multivariate functional linear models (MFLM) and additive models of multivariate analysis of variance (MANOVA), and (2) Gene Association with Multiple Traits (GAMuT) for association testing of high-dimensional genotype data. It is shown that approximate F-distributed tests of MFLM and MANOVA have higher power and are more appropriate for major gene association analysis (i.e., scenarios in which some genetic variants have relatively large effects on the phenotypes); GAMuT has higher power and is more appropriate for analyzing polygenic effects (i.e., effects from a large number of genetic variants each of which contributes a small amount to the phenotypes). MFLM and MANOVA are very flexible and can be used to perform association analysis for: (i) rare variants, (ii) common variants, and (iii) a combination of rare and common variants. Although GAMuT was designed to analyze rare variants, it can be applied to analyze a combination of rare and common variants and it performs well when (1) the number of genetic variants is large and (2) each variant contributes a small amount to the phenotypes (i.e., polygenes). MFLM and MANOVA are fixed effect models which perform well for major gene association analysis. GAMuT can be viewed as an extension of sequence kernel association tests (SKAT). Both GAMuT and SKAT are more appropriate for analyzing polygenic effects and they perform well not only in the rare variant case, but also in the case of a combination of rare and common variants. Data analyses of European cohorts and the Trinity Students Study are presented to compare the performance of the two methods.

By sequencing the exomes of distantly related individuals in multiplex families, rare mutational and structural changes to coding DNA can be characterized and their relationship to disease risk can be assessed. Recently, several rare single nucleotide variants (SNVs) were associated with an increased risk of nonsyndromic oral cleft, highlighting the importance of rare sequence variants in oral clefts and illustrating the strength of family-based study designs. However, the extent to which rare deletions in coding regions of the genome occur and contribute to risk of nonsyndromic clefts is not well understood. To identify putative structural variants underlying risk, we developed a pipeline for rare hemizygous deletions in families from whole exome sequencing and statistical inference based on rare variant sharing. Among 56 multiplex families with 115 individuals, we identified 53 regions with one or more rare hemizygous deletions. We found 45 of the 53 regions contained rare deletions occurring in only one family member. Members of the same family shared a rare deletion in only eight regions. We also devised a scalable global test for enrichment of shared rare deletions.

Supplemental Data Supplemental Data include one figure and five tables and can be found with this article online at http://dx.doi.org/10.1016/j.ajhg.2016.08.016. Supplemental Data Document S1. Figure S1 and Tables S1–S5 Download Document S2. Article plus Supplemental Data Download Web Resources ClinVar, https://www.ncbi.nlm.nih.gov/clinvar/ dbNSFP, https://sites.google.com/site/jpopgen/dbNSFP Human Gene Mutation Database, http://www.hgmd.cf.ac.uk/ REVEL, https://sites.google.com/site/revelgenomics/ SwissVar, http://swissvar.expasy.org/ The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p < 10−12) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies

The posterior fossa of the cranium contains the cerebellum and brainstem. Processes that reduce the volume of the posterior fossa squeeze the cerebellum and brainstem caudally, resulting in Chiari I malformation (CM1). CM1 causes neck pain, balance issues, decreased motor skills and headaches in those affected. We have posterior fossa measurements and whole exome sequence data on individuals from 7 extended families from Russia that have a family history of CM1. We performed parametric linkage analyses using an autosomal dominant inheritance model with a disease allele frequency of 0.01 and a penetrance of 0.8 for carriers and 0.0 for non-carriers. Variant-based two-point linkage analysis and gene-based linkage analysis was performed. Our results found a genome-wide significant signal on chromosome 1q43-44 (max HLOD = 3.3) in the variant-based analysis and 12q23 (max HLOD = 4.2) in the gene-based analysis. In both cases, the signal was driven by a single (different) family that contained a long, linked haplotype across the region in question. Using functional annotation, we were able to identify several rare nonsynonymous variants that were enriched in each family. The best candidate genes were rs765865412:G>A in MYBPC1 for the 12q haplotype and rs61749963:A>G in COX20 for the 1q haplotype. Good candidate variants in the 1q haplotype were also identified in CEP170 and AKT. Further laboratory work is planned to verify the causality of these genes.

The importance to integrate survival analysis into genetics and genomics is widely recognized, but only a small number of statisticians have produced relevant work toward this research direction. For unrelated population data, functional regression models have been developed to test for association between a quantitative/dichotomous/survival trait and genetic variants in a gene region. In major gene association analysis, these models have higher power than sequence kernel association tests (SKAT). In this paper, we extend this approach to analyze censored traits for family data or related samples using functional regression based mixed effect Cox models (FamCoxME). The FamCoxME model the effect of major gene as fixed mean via functional data analysis techniques, the local gene or polygene variations or both as random, and the correlation of pedigree members by kinship coefficients or genetic relationship matrix (GRM) or both. The association between the censored trait and the major gene is tested by likelihood ratio tests (FamCoxME FR LRT). Simulation results indicate that the LRT control the type I error rates accurately/conservatively and have good power levels when both local gene or polygene variations are modeled. The proposed methods were applied to analyze a breast cancer data set from the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA). The FamCoxME provides a new tool for gene-based analysis of family-based studies or related samples.

Rare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single-marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden-type approaches attempt to identify aggregation of RVs across case-control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large-scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway-level RV analysis results from a prostate cancer (PC) risk case-control sequencing study. Finally, we discuss potential extensions and future directions of this work.

Methylmalonic acid (MMA) is a by-product of propionic acid metabolism through the vitamin B12 (cobalamin)-dependent enzyme methylmalonyl CoA mutase. Elevated MMA concentrations are a hallmark of several inborn errors of metabolism and indicators of cobalamin deficiency in older persons. In a genome-wide analysis of 2,210 healthy young Irish adults (median age 22 years) we identified a strong association of plasma MMA with SNPs in 3-hydroxyisobutyryl-CoA hydrolase (HIBCH, p = 8.42 × 10(-89)) and acyl-CoA synthetase family member 3 (ACSF3, p = 3.48 × 10(-19)). These loci accounted for 12% of the variance in MMA concentration. The most strongly associated SNP (HIBCH rs291466; c:2TC) causes a missense change of the initiator methionine codon (minor-allele frequency = 0.43) to threonine. Surprisingly, the resulting variant, p.Met1?, is associated with increased expression of HIBCH mRNA and encoded protein. These homozygotes had, on average, 46% higher MMA concentrations than methionine-encoding homozygotes in young adults with generally low MMA concentrations (0.17 [0.14-0.21] μmol/L; median [25(th)-75(th) quartile]). The association between MMA levels and HIBCH rs291466 was highly significant in a replication cohort of 1,481 older individuals (median age 79 years) with elevated plasma MMA concentrations (0.34 [0.24-0.51] μmol/L; p = 4.0 × 10(-26)). In a longitudinal study of 185 pregnant women and their newborns, the association of this SNP remained significant across the gestational trimesters and in newborns. HIBCH is unique to valine catabolism. Studies evaluating flux through the valine catabolic pathway in humans should account for these variants. Furthermore, this SNP could help resolve equivocal clinical tests where plasma MMA values have been used to diagnose cobalamin deficiency.

Niemann-Pick disease type C (NPC) is a recessive, neurodegenerative, lysosomal storage disease caused by mutations in either NPC1 or NPC2. The diagnosis is difficult and frequently delayed. Ascertainment is likely incomplete because of both these factors and because the full phenotypic spectrum may not have been fully delineated. Given the recent development of a blood-based diagnostic test and the development of potential therapies, understanding the incidence of NPC and defining at-risk patient populations are important.We evaluated data from four large, massively parallel exome sequencing data sets. Variant sequences were identified and classified as pathogenic or nonpathogenic based on a combination of literature review and bioinformatic analysis. This methodology provided an unbiased approach to determining the allele frequency.Our data suggest an incidence rate for NPC1 and NPC2 of 1/92,104 and 1/2,858,998, respectively. Evaluation of common NPC1 variants, however, suggests that there may be a late-onset NPC1 phenotype with a markedly higher incidence, on the order of 1/19,000-1/36,000.We determined a combined incidence of classical NPC of 1/89,229, or 1.12 affected patients per 100,000 conceptions, but predict incomplete ascertainment of a late-onset phenotype of NPC1. This finding strongly supports the need for increased screening of potential patients.

Objective: One of four American cancer patients dies of lung cancer. Environmental factors such as tobacco smoking are known to affect lung cancer risk. However, there is a genetic factor to lung cancer risk as well. Here, we perform parametric linkage analysis on family-based genotype data in an effort to find genetic loci linked to the disease. Methods: 197 individuals from families with a high-risk history of lung cancer were recruited and genotyped using an Illumina array. Parametric linkage analyses were performed using an affected-only phenotype model with an autosomal dominant inheritance using a disease allele frequency of 0.01. Three types of analyses were performed: single variant two-point, collapsed haplotype pattern variant two-point, and multipoint analysis. Results: Five novel genome-wide significant loci were identified at 18p11.23, 2p22.2, 14q13.1, 16p13, and 20q13.11. The families most informative for linkage were also determined. Conclusions: The 5 novel signals are good candidate regions, containing genes that have been implicated as having somatic changes in lung cancer or other cancers (though not in germ line cells). Targeted sequencing on the significant loci is planned to determine the causal variants at these loci.

Introduction The association between smoking-induced chronic obstructive pulmonary disease (COPD) and lung cancer (LC) is well documented. Recent genome-wide association studies (GWAS) have identified 28 susceptibility loci for LC, 10 for COPD, 32 for smoking behavior, and 63 for pulmonary function, totaling 107 nonoverlapping loci. Given that common variants have been found to be associated with LC in genome-wide association studies, exome sequencing of these high-priority regions has great potential to identify novel rare causal variants. Methods To search for disease-causing rare germline mutations, we used a variation of the extreme phenotype approach to select 48 patients with sporadic LC who reported histories of heavy smoking—37 of whom also exhibited carefully documented severe COPD (in whom smoking is considered the overwhelming determinant)—and 54 unique familial LC cases from families with at least three first-degree relatives with LC (who are likely enriched for genomic effects). Results By focusing on exome profiles of the 107 target loci, we identified two key rare mutations. A heterozygous p.Arg696Cys variant in the coiled-coil domain containing 147 ( CCDC147 ) gene at 10q25.1 was identified in one sporadic and two familial cases. The minor allele frequency (MAF) of this variant in the 1000 Genomes database is 0.0026. The p.Val26Met variant in the dopamine β-hydroxylase ( DBH ) gene at 9q34.2 was identified in two sporadic cases; the minor allele frequency of this mutation is 0.0034 according to the 1000 Genomes database. We also observed three suggestive rare mutations on 15q25.1: iron-responsive element binding protein neuronal 2 ( IREB2 ); cholinergic receptor, nicotinic, alpha 5 (neuronal) ( CHRNA5 ); and cholinergic receptor, nicotinic, beta 4 ( CHRNB4 ). Conclusions Our results demonstrated highly disruptive risk-conferring CCDC147 and DBH mutations.

Myopia is the largest cause of uncorrected visual impairments globally and its recent dramatic increase in the population has made it a major public health problem. In observational studies, educational attainment has been consistently reported to be correlated to myopia. Nonetheless, correlation does not imply causation. Observational studies do not tell us if education causes myopia or if instead there are confounding factors underlying the association. In this work, we use a two-step least squares instrumental-variable (IV) approach to estimate the causal effect of education on refractive error, specifically myopia. We used the results from the educational attainment GWAS from the Social Science Genetic Association Consortium to define a polygenic risk score (PGRS) in three cohorts of late middle age and elderly Caucasian individuals (N = 5,649). In a meta-analysis of the three cohorts, using the PGRS as an IV, we estimated that each z-score increase in education (approximately 2 years of education) results in a reduction of 0.92 ± 0.29 diopters (P = 1.04 × 10(-3) ). Our estimate of the effect of education on myopia was higher (P = 0.01) than the observed estimate (0.25 ± 0.03 diopters reduction per education z-score [∼2 years] increase). This suggests that observational studies may actually underestimate the true effect. Our Mendelian Randomization (MR) analysis provides new evidence for a causal role of educational attainment on refractive error.

Introduction: Mutations within the BRCA1 gene have been linked to up to an 80% lifetime risk of breast cancer as well as increased risk for ovarian, pancreatic and melanoma cancers. In this study we examined families with known germline mutations in BRCA1 after long-term follow-up to determine whether carriers experience higher rates of other cancers that have not yet been associated with germline mutations in the BRCA1 gene. Methods: We studied 127 Hereditary Breast and Ovarian Cancer (HBOC) syndrome families (N = 23,078 individuals who have been followed at Creighton University) in which a causal mutation in the BRCA1 gene was identified. We performed survival analysis and a mixed effects cox regression with age at follow-up or cancer event as our time variable and presence or absence of BRCA1-related or other cancers (separate analyses) as our indicator variable. Results: The survival curves showed a significant age effect with carriers having a younger age at cancer onset for BRCA1-related (as expected) as well as other cancers than that of non-carriers. The cox regression models were also highly significant (P = 1.77E-37 and P = 1.04E-07 for the BRCA1-related and other cancers, respectively). Of the cancers with enough samples to do stratified analyses, uterine, skin, lymphoma and colon cancers occurred at higher rates and at earlier ages in mutation carriers. Conclusions: These analyses support the hypothesis that the BRCA1 mutations carriers of HBOC syndrome have increased risk for early onset of several additional cancer types, especially cancers that arise in estrogen-influenced tissues. Citation Format: Candace Middlebrooks, Kenzhane Pantin, Mark Stacey, Carrie Snyder, Murray J. Casey, Trudy Shaw, Joan E. Bailey-Wilson, Henry T. Lynch. Deleterious germline mutations in the BRCA1 gene are associated with increased risk for cancers of the female reproductive system other than breast and ovarian as well as other cancers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2300.

More Americans die every year of lung cancer than any other cancer. While the environmental risks for lung cancer are well understood, the genetic risk factors for this disease are not, even though it has been shown that lung cancer risk aggregates in families. Segregation analyses have confirmed the likelihood of rare, highly penetrant variants affecting lung cancer. Family studies offer a unique opportunity to identify such rare risk variants. We have previously identified a genome-wide significant risk locus for lung cancer using multipoint linkage analysis in highly aggregated lung cancer families. In this study, we performed targeted sequencing on this 6q23-6q27 region on 75 individuals from the 9 most strongly linked families. Parametric two-point linkage analysis using an autosomal dominant model with 10% penetrance for carriers and a 1% phenocopy rate and disease allele frequency of 1% was performed for each family. While we did not find any genome-wide significant results in any of the individual families, we did observe several interesting potential rare risk variants. First, we observed that the significant signal previously observed on 6q is recapitulated in these data but the location of the peak LOD is highly heterogeneous across families and it is likely that each family has a different risk gene. While most of the highest LOD scores were in noncoding variants, we did observe exonic variants with the highest LOD scores in two families (44 and 42). Both variants were rare, with a minor allele frequency (MAF) of approximately 1% and were in LPA and GPR126 respectively. Both these genes have been implicated somatically in lung cancer, however this is the first time that they have been implicated in the germline. While the other families have their highest LOD scores in noncoding variants, some of these genes are also good potential candidate genes including PARK2 (family 30), GRM1 (family 47), and PDE10A (family 102). All three genes have been implicated in lung cancer in some capacity, and this is the first time that GRM1 and PDE10A have been implicated as germline mutations. Again, all these variants are rare (MAF ⇐ 0.01) in the general population, which makes sense for a potential highly penetrant risk variant. In this study, we have elucidated that a previously identified risk locus on 6q25 is heterogeneous in the nine most strongly linked families, with different families appearing to be carrying different risk variants. Many of the top variants in each family are rare variants that are in good potential causal genes that have been identified for the first time here as germline risk variants for lung cancer. Further functional annotation is underway for these variants and some additional linkage analyses using other penetrance matrices may also be performed. Citation Format: Anthony M. Musolf, Claire L. Simpson, Bilal A. Moiz, Mariza de Andrade, Diptasri Mandal, Colette Gaba, Ping Yang, Ming You, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Joan E. Bailey-Wilson. Highly aggregated lung cancer families reveal a heterogeneous cause for a previous linkage signal on 6q [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 37.

Purpose: Prostate cancer is the most common cancer in males, with a ~1.5-2-fold higher incidence in African American men when compared with whites. Epidemiologic evidence supports a large heritable contribution to prostate cancer, with over 100 susceptibility loci identified to date that can explain ~33% of the familial risk. A portion of the undefined risk may be due to rare susceptibility variants. The African American Hereditary Prostate Cancer (AAHPC) Study, established in 1997, enrolled 77 African American families from seven clinical sites across the United States. The aim of this study is to identify rare, predictive, deleterious variants through exome sequencing of 99 cases from families selected from the AAHPC families and three 1000 Genome controls. Methods: To explore the contribution of rare variation in coding regions to prostate cancer risk, we sequenced the exomes of 99 AAHPC cases at a mean coverage of 30x. Post-variant calling quality control (QC) was implemented using Golden Helix SVS 8 software with filters set for removal of variants with Read Depth >10, Quality Score >10, and Quality Score: Read Depth Ratio > 0.5. Mendelian inconsistency was checked using PLINK. Prioritization of all candidate genes/variants was evaluated using online databases 1000 Genome and bioinformatics tool ANNOVAR for non-reference allele frequency and predictions of functional impact. Conclusions: Through exome sequencing of 99 AAHPC cases and three 1000 Genome controls, we identified 37 nonsynonymous single-nucleotide variants that are considered damaging by at least one predictive scoring tool in our candidate genes. Interesting candidate variants were found in known cancer susceptibility loci BRCA2, MSR1, PCNT, STAT3, WRN and ZFHX3. Future results are pending additional QC and analyses to determine which variants are shared by related individuals within each family compared to those not seen in the controls. Citation Format: Deyana D. Lewis, Shukmei Wong, Angela S. Baker, Joan E. Bailey-Wilson, John D. Carpten, Cheryl D. Cropp. Deleterious coding variants in African American Hereditary Prostate Cancer Study (AAHPC) families [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr C050.

Familial atypical multiple mole melanoma (FAMMM) syndrome is a hereditary cancer syndrome that results from mutations in several genes, including the

Results from association studies are traditionally corroborated by replicating the findings in an independent data set. Although replication studies may be comparable for the main trait or phenotype of interest, it is unlikely that secondary phenotypes will be comparable across studies, making replication problematic. Alternatively, there may simply not be a replication sample available because of the nature or frequency of the phenotype. In these situations, an approach based on complementary pairs stability selection for genome-wide association study (ComPaSS-GWAS), is proposed as an ad-hoc alternative to replication. In this method, the sample is randomly split into two conditionally independent halves multiple times (resamples) and a GWAS is performed on each half in each resample. Similar in spirit to testing for association with independent discovery and replication samples, a marker is corroborated if its p-value is significant in both halves of the resample. Simulation experiments were performed for both nongenetic and genetic models. The type I error rate and power of ComPaSS-GWAS were determined and compared to the statistical properties of a traditional GWAS. Simulation results show that the type I error rate decreased as the number of resamples increased with only a small reduction in power and that these results were comparable with those from a traditional GWAS. Blood levels of vitamin pyridoxal 5'-phosphate from the Trinity Student Study (TSS) were used to validate this approach. The results from the validation study were compared to, and were consistent with, those obtained from previously published independent replication data and functional studies.

To identify genetic variation associated with lung cancer risk, we performed a genome-wide association analysis of 685 lung cancer cases that had a family history of two or more first or second degree relatives compared with 744 controls without lung cancer that were genotyped on an Illumina Human OmniExpressExome-8v1 array. To ensure robust results, we further evaluated these findings using data from six additional studies that were assembled through the Transdisciplinary Research on Cancer of the Lung Consortium comprising 1993 familial cases and 33 690 controls. We performed a meta-analysis after imputation of all variants using the 1000 Genomes Project Phase 1 (version 3 release date September 2013). Analyses were conducted for 9 327 222 SNPs integrating data from the two sources. A novel variant on chromosome 4p15.31 near the LCORL gene and an imputed rare variant intergenic between CDKN2A and IFNA8 on chromosome 9p21.3 were identified at a genome-wide level of significance for squamous cell carcinomas. Additionally, associations of CHRNA3 and CHRNA5 on chromosome 15q25.1 in sporadic lung cancer were confirmed at a genome-wide level of significance in familial lung cancer. Previously identified variants in or near CHRNA2, BRCA2, CYP2A6 for overall lung cancer, TERT, SECISPB2L and RTEL1 for adenocarcinoma and RAD52 and MHC for squamous carcinoma were significantly associated with lung cancer.

We develop linear mixed models (LMMs) and functional linear mixed models (FLMMs) for gene-based tests of association between a quantitative trait and genetic variants on pedigrees. The effects of a major gene are modeled as a fixed effect, the contributions of polygenes are modeled as a random effect, and the correlations of pedigree members are modeled via inbreeding/kinship coefficients. F -statistics and χ 2 likelihood ratio test (LRT) statistics based on the LMMs and FLMMs are constructed to test for association. We show empirically that the F -distributed statistics provide a good control of the type I error rate. The F -test statistics of the LMMs have similar or higher power than the FLMMs, kernel-based famSKAT (family-based sequence kernel association test), and burden test famBT (family-based burden test). The F -statistics of the FLMMs perform well when analyzing a combination of rare and common variants. For small samples, the LRT statistics of the FLMMs control the type I error rate well at the nominal levels α = 0.01 and 0.05 . For moderate/large samples, the LRT statistics of the FLMMs control the type I error rates well. The LRT statistics of the LMMs can lead to inflated type I error rates. The proposed models are useful in whole genome and whole exome association studies of complex traits.

BACKGROUND: Genetic polymorphisms can explain some of the population- and individual-based variations in nutritional status biomarkers. OBJECTIVE: We sought to screen the entire human genome for common genetic polymorphisms that influence folate-status biomarkers in healthy individuals. DESIGN: We carried out candidate gene analyses and genome-wide association scans in 2232 young, healthy Irish subjects to evaluate which common genetic polymorphisms influence red blood cell folate, serum folate, and plasma total homocysteine. RESULTS: The 5,10-methylenetetrahydrofolate reductase (MTHFR) 677C→T (rs1801133) variant was the major genetic modifier of all 3 folate-related biomarkers in this Irish population and reached genome-wide significance for red blood cell folate (P = 1.37 × 10(−17)), serum folate (P = 2.82 × 10(−11)), and plasma total homocysteine (P = 1.26 × 10(−19)) concentrations. A second polymorphism in the MTHFR gene (rs3753584, P = 1.09 × 10(−11)) was the only additional MTHFR variant to exhibit any significant independent effect on red blood cell folate. Other MTHFR variants, including the 1298A→C variant (rs1801131), appeared to reach genome-wide significance, but these variants shared linkage disequilibrium with MTHFR 677C→T and were not significant when analyzed in MTHFR 677CC homozygotes. No additional non-MTHFR modifiers of red blood cell or plasma folate were detected. Two additional genome-wide significant modifiers of plasma homocysteine were found in the region of the dipeptidase 1 (DPEP1) gene on chromosome 16 and the Twist neighbor B (TWISTNB) gene on chromosome 7. CONCLUSIONS: The MTHFR 677C→T variant is the predominant genetic modifier of folate status biomarkers in this healthy Irish population. It is not necessary to determine MTHFR 677C→T genotype to evaluate folate status because its effect is reflected in concentrations of standard folate biomarkers. The MTHFR 1298A→C variant had no independent effect on folate status biomarkers. To our knowledge, this is the first genome-wide association study report on red blood cell folate and the first report of an association between homocysteine and TWISTNB.

We previously demonstrated how sharing of rare variants (RVs) in distant affected relatives can be used to identify variants causing a complex and heterogeneous disease. This approach tested whether single RVs were shared by all sequenced affected family members. However, as with other study designs, joint analysis of several RVs (e.g., within genes) is sometimes required to obtain sufficient statistical power. Further, phenocopies can lead to false negatives for some causal RVs if complete sharing among affected is required. Here, we extend our methodology (Rare Variant Sharing, RVS) to address these issues. Specifically, we introduce gene-based analyses, a partial sharing test based on RV sharing probabilities for subsets of affected relatives and a haplotype-based RV definition. RVS also has the desirable feature of not requiring external estimates of variant frequency or control samples, provides functionality to assess and address violations of key assumptions, and is available as open source software for genome-wide analysis. Simulations including phenocopies, based on the families of an oral cleft study, revealed the partial and complete sharing versions of RVS achieved similar statistical power compared with alternative methods (RareIBD and the Gene-Based Segregation Test), and had superior power compared with the pedigree Variant Annotation, Analysis, and Search Tool (pVAAST) linkage statistic. In studies of multiplex cleft families, analysis of rare single nucleotide variants in the exome of 151 affected relatives from 54 families revealed no significant excess sharing in any one gene, but highlighted different patterns of sharing revealed by the complete and partial sharing tests.

Biliary atresia (BA) is a rare pediatric cholangiopathy characterized by fibrosclerosing obliteration of the extrahepatic bile ducts, leading to cholestasis, fibrosis, cirrhosis, and eventual liver failure. The etiology of BA remains unknown, although environmental, inflammatory, infectious, and genetic risk factors have been proposed. We performed a genome-wide association study (GWAS) in a European-American cohort of 343 isolated BA patients and 1716 controls to identify genetic loci associated with BA. A second GWAS was performed in an independent European-American cohort of 156 patients with BA and other extrahepatic anomalies and 212 controls to confirm the identified candidate BA-associated SNPs. Meta-analysis revealed three genome-wide significant BA-associated SNPs on 2p16.1 (rs10865291, rs6761893, and rs727878; P < 5 ×10−8), located within the fifth intron of the EFEMP1 gene, which encodes a secreted extracellular protein implicated in extracellular matrix remodeling, cell proliferation, and organogenesis. RNA expression analysis showed an increase in EFEMP1 transcripts from human liver specimens isolated from patients with either BA or other cholestatic diseases when compared to normal control liver samples. Immunohistochemistry demonstrated that EFEMP1 is expressed in cholangiocytes and vascular smooth muscle cells in liver specimens from patients with BA and other cholestatic diseases, but it is absent from cholangiocytes in normal control liver samples. Efemp1 transcripts had higher expression in cholangiocytes and portal fibroblasts as compared with other cell types in normal rat liver. The identification of a novel BA-associated locus, and implication of EFEMP1 as a new BA candidate susceptibility gene, could provide new insights to understanding the mechanisms underlying this severe pediatric disorder., Author summary The etiology of biliary atresia (BA) is unknown and likely complex. Environmental, infectious, and genetic risk factors have all been proposed, and the leading hypothesis in the field is that a combination of these factors is responsible for disease manifestation. To identify susceptibility loci for BA, we performed a genome wide association study on two groups of BA patients (one composed of patients with isolated BA (n = 343) and one of patients with BA and other extrahepatic anomalies (n = 156)) and genetically matched controls. We detected a set of SNPs within the EFEMP1 gene associated with BA in both cohorts. We further showed by immunohistochemistry that EFEMP1 protein was expressed in cholangiocytes and vascular smooth muscle cells in BA livers, and that EFEMP1 RNA expression levels were elevated in both BA and other cholestatic disease livers. These findings suggest that EFEMP1 should be considered as a new candidate susceptibility gene for BA.

Lynch syndrome is the hereditary disorder that most frequently predisposes to colorectal cancer as well as predisposing to a number of extracolonic cancers, most prominently endometrial cancer. It is caused by germline mutations in the mismatch repair genes. Both its phenotype and genotype show marked heterogeneity. This review gives a historical overview of the syndrome, its heterogeneity, its genomic landscape, and its implications for complex diagnosis, genetic counseling and putative implications for immunotherapy.

Background Vitamin B-6 interconversion enzymes are important for supplying pyridoxal 5'-phosphate (PLP), the co-enzyme form, to tissues. Variants in the genes for these enzymes [tissue nonspecific alkaline phosphatase (ALPL), pyridoxamine 5'-phosphate oxidase, pyridoxal kinase, and pyridoxal phosphatase] could affect enzyme function and vitamin B-6 status. Objectives We tested whether single-nucleotide polymorphisms (SNPs) in these genes influence vitamin B-6 status markers [plasma PLP, pyridoxal (PL), and 4-pyridoxic acid (PA)], and explored potential functional effects of the SNPs. Methods Study subjects were young, healthy adults from Ireland (n = 2345). We measured plasma PLP, PL, and PA with liquid chromatography-tandem mass spectrometry and genotyped 66 tag SNPs in the 4 genes. We tested for associations with single SNPs in candidate genes and also performed genome-wide association study (GWAS) and gene-based analyses. Results Seventeen SNPs in ALPL were associated with altered plasma PLP in candidate gene analyses (P Conclusions In healthy adults, common variants in ALPL influence plasma PLP concentration, the most frequently used biomarker for vitamin B-6 status. Whether these associations are indicative of functional changes in vitamin B-6 status requires more investigation.

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks’s Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case.

Genome-wide association studies (GWAS) for nonsyndromic cleft lip with or without cleft palate (CL/P) have identified multiple genes as important in the etiology of this common birth defect. We performed a candidate gene/pathway analysis explicitly considering gene-gene (G × G) interaction to further explore the etiology of CL/P. Animal models have shown the WNT signaling pathway plays an important role in mid-facial development, and various genes in this pathway have been associated with nonsyndromic CL/P in previous studies. We propose a combined approach to search for possible G × G interactions using machine learning and regression-based methods to test for interactions between genes in the WNT family, and between these genes and other genes identified by GWAS in case-parent trios. Using this combined approach of regression-based and machine learning methods in CL/P case-parent trios, we found robust evidence of G × G interaction between markers in WNT5B and MAFB (empiric P-values = 0.0076 among Asian trios and P-values = 0.018 among European trios). Additional evidence for epistatic interaction between markers in WNT5A, IRF6, and C1orf107 was seen among Asian trios, and markers in the 8q24 region and WNT5B among European trios.

PARK2, a gene associated with Parkinson disease, is a tumor suppressor in human malignancies. Here, we show that c.823C>T (p.Arg275Trp), a germline mutation in PARK2, is present in a family with eight cases of lung cancer. The resulting amino acid change, p.Arg275Trp, is located in the highly conserved RING finger 1 domain of PARK2, which encodes an E3 ubiquitin ligase. Upon further analysis, the c.823C>T mutation was detected in three additional families affected by lung cancer. The effect size for PARK2 c.823C>T (odds ratio = 5.24) in white individuals was larger than those reported for variants from lung cancer genome-wide association studies. These data implicate this PARK2 germline mutation as a genetic susceptibility factor for lung cancer. Our results provide a rationale for further investigations of this specific mutation and gene for evaluation of the possibility of developing targeted therapies against lung cancer in individuals with PARK2 variants by compensating for the loss-of-function effect caused by the associated variation.

Purpose To determine genetic linkage between myopia and Han Chinese patients with a family history of the disease. Methods One hundred seventy-six Han Chinese patients from 34 extended families were given eye examinations, and mean spherical equivalent (MSE) in diopters (D) was calculated by adding the spherical component of the refraction to one-half the cylindrical component and taking the average of both eyes. The MSE was converted to a binary phenotype, where all patients with an MSE of -1.00 D or less were coded as affected. Unaffected individuals had an MSE greater than 0.00 D (ages 21 years and up), +1.50 (ages 11–20), or +2.00 D (ages 6–10 years). Individuals between the given upper threshold and −1.00 were coded as unknown. Patients were genotyped on an exome chip. Three types of linkage analyses were performed: single-variant two-point, multipoint, and collapsed haplotype pattern (CHP) variant two-point. Results The CHP variant two-point results identified a significant peak (heterogeneity logarithm of the odds [HLOD] = 3.73) at 10q26.13 in TACC2. The single-variant two-point and multipoint analyses showed highly suggestive linkage to the same region. The single-variant two-point results identified 25 suggestive variants at HTRA1, also at 10q26.13. Conclusions We report a significant genetic linkage between myopia and Han Chinese patients at 10q26.13. 10q26.13 contains several good candidate genes, such as TACC2 and the known age-related macular degeneration gene HTRA1. Targeted sequencing of the region is planned to identify the causal variant(s).

Purpose Myopia is a common visual disorder caused by eye overgrowth, resulting in blurry vision. It affects one in four Americans, and its prevalence is increasing. The genetic mechanisms that underpin myopia are not completely understood. Here, we use genotype data and linkage analyses to identify high-risk genetic loci that are significantly linked to myopia. Methods Individuals from 56 Caucasian families with a history of myopia were genotyped on an exome-based array, and the single nucleotide polymorphism (SNP) data were merged with microsatellite genotype data. Refractive error measures on the samples were converted into binary phenotypes consisting of affected, unaffected, or unknown myopia status. Parametric linkage analyses assuming an autosomal dominant model with 90% penetrance and 10% phenocopy rate were performed. Results Single variant two-point analyses yielded three significantly linked SNPs at 11p14.1 and 11p11.2; a further 45 SNPs at 11p were found to be suggestive. No other chromosome had any significant SNPs or more than seven suggestive linkages. Two of the significant SNPs were located in BBOX1-AS1 and one in the intergenic region between ORA47 and TRIM49B. Collapsed haplotype pattern two-point analysis and multipoint analyses also yielded multiple suggestively linked genes at 11p. Multipoint analysis also identified suggestive evidence of linkage on 20q13. Conclusions We identified three genome-wide significant linked variants on 11p for myopia in Caucasians. Although the novel specific signals still need to be replicated, 11p is a promising region that has been identified by other linkage studies with a number of potentially interesting candidate genes. We hope that the identification of these regions on 11p as potential causal regions for myopia will lead to more focus on these regions and maybe possible replication of our specific linkage peaks in other studies. We further plan targeted sequencing on 11p for our most highly linked families to more clearly understand the source of the linkage in this region.

BACKGROUND African American men (AA) exhibit a disproportionate share of prostate cancer (PRCA) incidence, morbidity, and mortality. Several genetic association studies have implicated select 8q24 loci in PRCA risk in AA. The objective of this investigation is to evaluate the association between previously reported 8q24 risk alleles and PRCA in African-Barbadian (AB) men known to have high rates of PRCA. METHODS Ten previously reported candidate tag SNPs were genotyped and/or imputed in the 8q24 region in 532 AB men with PRCA and 513 AB controls from the Prostate Cancer in a Black Population (PCBP) study. RESULTS Rs2124036 was significant in AB men, (OR = 2.7, 95% CI (1.3–5.3), P = 0.005, Empirical (max (T), corrected for multiple testing) P = 0.03) for the homozygous C/C genotype. Only a single SNP from this region remained statistically significant in our analysis of our AB population. These results may indicate the presence of a founder effect or due to the chosen SNPs not tagging an ancestral haplotype bearing the 8q24 risk allele(s) in this population or could reflect inadequate power to detect an association. We conducted a meta-analysis including our AB population along with two additional African Caribbean populations from Tobago and Jamaica for SNPs rs16901979 and rs1447295. Meta-analysis results were most significant for rs16901979 A allele (Z score 2.73; P = 0.006) with a summary OR = 1.31 (95% CI: 1.09–1.58). CONCLUSIONS Additional studies are needed to provide deeper genotype coverage to further interrogate the 8q24 region to understand its contribution to PRCA in this population. Prostate 74: 1579–1588, 2014. © 2014 Wiley Periodicals, Inc.

A dozen genes/regions have been confirmed as genetic risk factors for oral clefts in human association and linkage studies, and animal models argue even more genes may be involved. Genomic sequencing studies should identify specific causal variants and may reveal additional genes as influencing risk to oral clefts, which have a complex and heterogeneous etiology. We conducted a whole exome sequencing (WES) study to search for potentially causal variants using affected relatives drawn from multiplex cleft families. Two or three affected second, third, and higher degree relatives from 55 multiplex families were sequenced. We examined rare single nucleotide variants (SNVs) shared by affected relatives in 348 recognized candidate genes. Exact probabilities that affected relatives would share these rare variants were calculated, given pedigree structures, and corrected for the number of variants tested. Five novel and potentially damaging SNVs shared by affected distant relatives were found and confirmed by Sanger sequencing. One damaging SNV in CDH1, shared by three affected second cousins from a single family, attained statistical significance (P = 0.02 after correcting for multiple tests). Family-based designs such as the one used in this WES study offer important advantages for identifying genes likely to be causing complex and heterogeneous disorders.

Data from massively parallel sequencing or 'Next Generation Sequencing' of the human exome has reached a critical mass in both public and private databases, in that these collections now allow researchers to critically evaluate population genetics in a manner that was not feasible a decade ago. The ability to determine pathogenic allele frequencies by evaluation of the full coding sequences and not merely a single nucleotide polymorphism (SNP) or series of SNPs will lead to more accurate estimations of incidence. For demonstrative purposes, we analyzed the causative gene for the disorder Smith-Lemli-Opitz Syndrome (SLOS), the 7-dehydrocholesterol reductase (DHCR7) gene and determined both the carrier frequency for DHCR7 mutations, and predicted an expected incidence of the disorder. Estimations of the incidence of SLOS have ranged widely from 1:10,000 to 1:70,000 while the carrier frequency has been reported as high as 1 in 30. Using four exome data sets with a total of 17,836 chromosomes, we ascertained a carrier frequency of pathogenic DHRC7 mutations of 1.01%, and predict a SLOS disease incidence of 1/39,215 conceptions. This approach highlights yet another valuable aspect of the exome sequencing databases, to inform clinical and health policy decisions related to genetic counseling, prenatal testing and newborn screening.

Elevated intraocular pressure (IOP) is an important risk factor in developing glaucoma, and variability in IOP might herald glaucomatous development or progression. We report the results of a genome-wide association study meta-analysis of 18 population cohorts from the International Glaucoma Genetics Consortium (IGGC), comprising 35,296 multi-ancestry participants for IOP. We confirm genetic association of known loci for IOP and primary open-angle glaucoma (POAG) and identify four new IOP-associated loci located on chromosome 3q25.31 within the FNDC3B gene (P = 4.19 x 10(-8) for rs6445055), two on chromosome 9 (P = 2.80 x 10(-11) for rs2472493 near ABCA1 and P = 6.39 x 10(-11) for rs8176693 within ABO) and one on chromosome 11p11.2 (best P = 1.04 x 10(-11) for rs747782). Separate meta-analyses of 4 independent POAG cohorts, totaling 4,284 cases and 95,560 controls, showed that 3 of these loci for IOP were also associated with POAG.

Lung cancer (LC) kills more people in the United States each year than any other cancer. While it is well known that a variety of environmental factors (particularly tobacco smoke) strongly increase the risk of LC, there are multiple associated genetic variants with small contributions to risk. High aggregation of LC within rare individual families suggest that there are high-risk genetic variants as well. However, these genetic risk factors for LC are under studied due to the rapid fatality of LC. We studied 28 highly aggregated extended high-risk familial lung cancer (HRFLC) families collected from eight different sites across the US. Whole exome sequencing was performed on 290 individuals from these families to identify potential risk variants for HRFLC using genetic linkage analysis. Quality control was performed on the sequence data, filtering on parameters such as read depth, genotype quality, missingness, and Mendelian inconsistencies. Identity-by-descent (IBD) values were also calculated to verify correct familial relationships. Quality control procedures left approximately 400,000 SNVs and indels for analysis.Parametric two-point linkage analysis was performed assuming an autosomal dominant mode of inheritance. Disease allele frequency was set to 1% with a penetrance of 80% for carriers and 1% phenocopy rate. While we did not identify any genome-wide significant variants across the 28 families, multiple suggestive variants were identified. The largest cluster of suggestive variants was located at 14q32 in the CATSPERB gene. Given the likely locus heterogeneity in LC (combined with the lack of power in some families), it is not surprising that none of the variants were significant across the families; looking at the individual family results proved more informative. Long haplotypes linked to LC risk were identified in multiple families. These long runs of positive linkages, which have little to no negative linkage evidence across them, are characteristic of true linkage signals in these types of analysis. Two of the most interesting linked regions were at 7p36.1 and 4q21.23-28.23. The 7p signal (observed in a single family) was genome-wide suggestive and located within the SSPO gene. SSPO has been implicated in breast and skin cancer (melanoma); it is a novel lung cancer signal. The 4q linkage (again observed in a single family) covers a large chunk of 4q and contains multiple potential candidate genes, however, the best candidate gene is PTPN13, a gene implicated in lung cancer but never in familial lung cancer. We are currently evaluating the individual family results of several other pedigrees and plan to perform additional analyses to confirm these linkages. Citation Format: Anthony Musolf, Haiming Sun, Bilal A. Moiz, Claudio W. Pikielny, Mariza de Andrade, Diptasri Mandal, Colette Gaba, Ping Yang, Yafang Li, Ming You, Richard K. Wilson, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Ramaswamy Govindan, Joan E. Bailey-Wilson. Familial lung cancer exhibits multiple novel linked haplotypes within pedigrees [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4176.

Purpose: Prostate cancer is the most common cancer in males, but also exhibits a ∼1.5-2-fold higher incidence in African American men compared with whites. Epidemiologic evidence supports a large heritable contribution to prostate cancer, with over 100 susceptibility loci identified to date that can explain ∼33 % of the familial risk. A portion of the undefined risk may be due to rare susceptibility variants. The African American Hereditary Prostate Cancer (AAHPC) Study, established in 1997, enrolled 77 AA families from seven clinical sites across the United States (Ann Epidemiol, 2000). The aim of this study is to identify rare, predictive, deleterious variants through exome sequencing of 99 cases from 26 families selected from the AAHPC families (2 to 3 affected men sequenced per family) and three female 1000 Genome controls. Methods: To explore the contribution of rare variation in coding regions of 38 known cancer-causing genes to prostate cancer risk (PCa), we sequenced the exomes of 99 AAHPC cases at a mean coverage of 30x. Post-variant calling quality control (QC) was implemented using Golden Helix SVS 8 software with filters set for removal of variants with Read Depth >10, Quality Score >10, and Quality Score: Read Depth Ratio > 0.5. Mendelian inconsistency was checked using PLINK. Prioritization of all candidate genes/variants were evaluated using online databases including 1000 Genomes and ANNOVAR for non-reference allele frequency and predictions of functional impact. Conclusions. Through exome sequencing of 99 AAHPC cases and 3 female 1000 Genome controls, we identified 37 non-synonymous single nucleotide variants that are considered damaging by at least one predictive scoring tool in our 38 candidate genes. However, most of these variants were common and thus unlikely to be causal. We observed three rare variants that were considered damaging by three predictive scoring tools in two known PCa genes, PCNT and ZFHX3. These 3 variants were each observed in a single different family (in 1 of 3 affected individuals). Interesting rare candidate variants (MAF ≤ 0.01) rs190517526 & rs114692729 were found in known cancer susceptibility loci (CD82 and EZH2). The CD82 variant was observed in all 3 sequenced affecteds in one family and the EZH2 variant was observed in 2 of 3 sequenced affecteds in a different family. These predicted damaging variants in these four genes represent potentially novel causal candidates for some of the 26 AAHPC families sequenced here. Future work will carefully analyze the remainder of the genome in the other 21 sequenced families including planned sequencing of additional family members. Citation Format: Deyana D. Lewis, Shukmei Wong, Angela S. Baker, Isaac Powell, John D. Carpten, Joan E. Bailey-Wilson, Cheryl Cropp. Rare candidate variants shared among affected family members in the African American Hereditary Prostate Cancer Study families [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4240.

Lung cancer (LC) is the primary cause of cancer-related deaths in the United States. Whereas smoking and other environmental factors strongly increase LC risk, multiple genetic variants also contribute to risk in smokers. Furthermore, among smokers, some families have been identified with an abnormally high prevalence of LC, suggesting that unknown genetic factors can greatly increase LC risk in smokers. The typically short survival after LC diagnosis impedes collection of detailed genotypic information on any single large family pedigree, impairing the identification of putative high-risk factors. Therefore, the Genetic Epidemiology of LC Consortium has collected epidemiological and genetic data from a number of families with high numbers of LC cases from eight different sites across the US. In this study, we have obtained whole exome sequences (WES) from 290 members of 28 families, including 66 LC cases. We used a gene-based approach to allow for the possibility that different families may contain different variants of the same gene. Variants were filtered for i) allele frequency, ii) functional effect using combined annotation-dependent depletion (CADD), and, iii) affecting a gene with either a known or suspected role in cancer. We further selected variants based on their segregation in family pedigrees in a pattern consistent with a large effect on LC risk. Candidate LC risk genes were then identified as those represented in at least two families by the same or different variants. We further culled the list of genes by requiring the presence of at least one rare, functional variant enriched in the WES of 1060 cases relative to 899 controls from the Transdisciplinary Research on Cancer of the Lung consortium. This analysis narrowed our results to two genes, one being E2A, a member of the E family of bHLH transcription factors. Whereas loss-of-function mutations in E2A drive lymphoid cancers, the E2A protein also participates in an oncogenic heterodimer with TWIST1 that promotes the epithelial-mesenchymal transition and is implicated in multiple cancer types. Furthermore, the E2A/TWIST1 heterodimer is the primary TWIST1-containing complex implicated in oncogenesis, and silencing of E2A in KRAS-mutant non-small cell lung cancer (NSCLC) cell lines results in oncogene-stimulated senescence and apoptosis. Our data identified three distinct E2A variants present in all 10 sequenced LC cases in the 5 families in which those variants are found. Finally, two of these E2A variants are located only 57 nucleotides from each other, immediately adjacent to sequences encoding a transcription activation domain, suggesting that both variants alter the same specific protein function. These data identify E2A variants as likely high risk factors for LC in smokers and validate our general approach for identifying genetic factors with a large impact on LC risk. Citation Format: Claudio W. Pikielny, Anthony M. Musolf, Mariza de Andrade, Diptasri Mandal, Colette Gaba, Ping Yang, yafang Li, Ming You, Richard Wilson, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Ambrose I. Granizo-Mackenzie, Yanhong Liu, Ramaswamy Govindan, James McKay, Rayjean Hung, John K. Field, David C. Christiani, Joan E. Bailey-Wilson, Christopher I. Amos. Familial studies identify variants in the E2A transcription factor as putative risk factors for lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-053.

Previous GWAS studies have reported significant associations between various common SNPs and prostate cancer risk using cases unselected for family history. How these variants influence risk in familial prostate cancer is not well studied. Here, we analyzed 25 previously reported SNPs across 14 loci from prior prostate cancer GWAS. The International Consortium for Prostate Cancer Genetics (ICPCG) previously validated some of these using a family-based association method (FBAT). However, this approach suffered reduced power due to the conditional statistics implemented in FBAT. Here, we use a case-control design with an empirical analysis strategy to analyze the ICPCG resource for association between these 25 SNPs and familial prostate cancer risk. Fourteen sites contributed 12,506 samples (9,560 prostate cancer cases, 3,368 with aggressive disease, and 2,946 controls from 2,283 pedigrees). We performed association analysis with Genie software which accounts for relationships. We analyzed all familial prostate cancer cases and the subset of aggressive cases. For the familial prostate cancer phenotype, 20 of the 25 SNPs were at least nominally associated with prostate cancer and 16 remained significant after multiple testing correction (p a parts per thousand currency sign 1E (-3)) occurring on chromosomal bands 6q25, 7p15, 8q24, 10q11, 11q13, 17q12, 17q24, and Xp11. For aggressive disease, 16 of the SNPs had at least nominal evidence and 8 were statistically significant including 2p15. The results indicate that the majority of common, low-risk alleles identified in GWAS studies for all prostate cancer also contribute risk for familial prostate cancer, and that some may contribute risk to aggressive disease.