Lung Cancer in Ever- and Never-Smokers: Findings from Multi-Population GWAS Studies

BACKGROUND

Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer.

METHODS

We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer.

RESULTS

Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10-8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior.

CONCLUSIONS

We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies.

IMPACT

Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.

Gene-level association analysis of bivariate ordinal traits with functional regressions

In genetic studies, many phenotypes have multiple naturally ordered discrete values. The phenotypes can be correlated with each other. If multiple correlated ordinal traits are analyzed simultaneously, the power of analysis may increase significantly while the false positives can be controlled well. In this study, we propose bivariate functional ordinal linear regression (BFOLR) models using latent regressions with cumulative logit link or probit link to perform a gene-based analysis for bivariate ordinal traits and sequencing data. In the proposed BFOLR models, genetic variant data are viewed as stochastic functions of physical positions, and the genetic effects are treated as a function of physical positions. The BFOLR models take the correlation of the two ordinal traits into account via latent variables. The BFOLR models are built upon functional data analysis which can be revised to analyze the bivariate ordinal traits and high-dimension genetic data. The methods are flexible and can analyze three types of genetic data: (1) rare variants only, (2) common variants only, and (3) a combination of rare and common variants. Extensive simulation studies show that the likelihood ratio tests of the BFOLR models control type I errors well and have good power performance. The BFOLR models are applied to analyze Age-Related Eye Disease Study data, in which two genes, CFH and ARMS2, are found to strongly associate with eye drusen size, drusen area, age-related macular degeneration (AMD) categories, and AMD severity scale.

Transmission disequilibrium analysis of whole genome data in childhood-onset systemic lupus erythematosus

Childhood-onset systemic lupus erythematosus (cSLE) patients are unique, with hallmarks of Mendelian disorders (early-onset and severe disease) and thus are an ideal population for genetic investigation of SLE. In this study, we use the transmission disequilibrium test (TDT), a family-based genetic association analysis that employs robust methodology, to analyze whole genome sequencing data. We aim to identify novel genetic associations in an ancestrally diverse, international cSLE cohort. Forty-two cSLE patients and 84 unaffected parents from 3 countries underwent whole genome sequencing. First, we performed TDT with single nucleotide variant (SNV)-based (common variants) using PLINK 1.9, and gene-based (rare variants) analyses using Efficient and Parallelizable Association Container Toolbox (EPACTS) and rare variant TDT (rvTDT), which applies multiple gene-based burden tests adapted for TDT, including the burden of rare variants test. Applying the GWAS standard threshold (5.0 × 10-8) to common variants, our SNV-based analysis did not return any genome-wide significant SNVs. The rare variant gene-based TDT analysis identified many novel genes significantly enriched in cSLE patients, including HNRNPUL2, a DNA repair protein, and DNAH11, a ciliary movement protein, among others. Our approach identifies several novel SLE susceptibility genes in an ancestrally diverse childhood-onset lupus cohort.

A rare FGF5 candidate variant (rs112475347) for predisposition to nonsquamous, nonsmall-cell lung cancer

A unique approach with rare resources was used to identify candidate variants predisposing to familial nonsquamous nonsmall-cell lung cancers (NSNSCLC). We analyzed sequence data from NSNSCLC-affected cousin pairs belonging to high-risk lung cancer pedigrees identified in a genealogy of Utah linked to statewide cancer records to identify rare, shared candidate predisposition variants. Variants were tested for association with lung cancer risk in UK Biobank. Evidence for linkage with lung cancer was also reviewed in families from the Genetic Epidemiology of Lung Cancer Consortium. Protein prediction modeling compared the mutation with reference. We sequenced NSNSCLC-affected cousin pairs from eight high-risk lung cancer pedigrees and identified 66 rare candidate variants shared in the cousin pairs. One variant in the FGF5 gene also showed significant association with lung cancer in UKBiobank. This variant was observed in 3/163 additional sampled Utah lung cancer cases, 2 of whom were related in another independent pedigree. Modeling of the predicted protein predicted a second binding site for SO4 that may indicate binding differences. This unique study identified multiple candidate predisposition variants for NSNSCLC, including a rare variant in FGF5 that was significantly associated with lung cancer risk and that segregated with lung cancer in the two pedigrees in which it was observed. FGF5 is an oncogenic factor in several human cancers, and the mutation found here (W81C) changes the binding ability of heparan sulfate to FGF5, which might lead to its deregulation. These results support FGF5 as a potential NSNSCLC predisposition gene and present additional candidate predisposition variants.

Rare variant analyses across multiethnic cohorts identify novel genes for refractive error

Refractive error, measured here as mean spherical equivalent (SER), is a complex eye condition caused by both genetic and environmental factors. Individuals with strong positive or negative values of SER require spectacles or other approaches for vision correction. Common genetic risk factors have been identified by genome-wide association studies (GWAS), but a great part of the refractive error heritability is still missing. Some of this heritability may be explained by rare variants (minor allele frequency [MAF] ≤ 0.01.). We performed multiple gene-based association tests of mean Spherical Equivalent with rare variants in exome array data from the Consortium for Refractive Error and Myopia (CREAM). The dataset consisted of over 27,000 total subjects from five cohorts of Indo-European and Eastern Asian ethnicity. We identified 129 unique genes associated with refractive error, many of which were replicated in multiple cohorts. Our best novel candidates included the retina expressed PDCD6IP, the circadian rhythm gene PER3, and P4HTM, which affects eye morphology. Future work will include functional studies and validation. Identification of genes contributing to refractive error and future understanding of their function may lead to better treatment and prevention of refractive errors, which themselves are important risk factors for various blinding conditions.

Genome-wide interaction analysis identified low-frequency variants with sex disparity in lung cancer risk

Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10-8); rs79942605 (OR = 2.17, P = 2.81×10-8) and rs208908 (OR = 0.70, P = 4.54×10-8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.

Whole exome sequence analysis in 51 624 participants identifies novel genes and variants associated with refractive error and myopia

Refractive errors are associated with a range of pathological conditions, such as myopic maculopathy and glaucoma, and are highly heritable. Studies of missense and putative loss of function (pLOF) variants identified via whole exome sequencing (WES) offer the prospect of directly implicating potentially causative disease genes. We performed a genome-wide association study for refractive error in 51 624 unrelated adults, of European ancestry, aged 40-69 years from the UK and genotyped using WES. After testing 29 179 pLOF and 495 263 missense variants, 1 pLOF and 18 missense variants in 14 distinct genomic regions were taken forward for fine-mapping analysis. This yielded 19 putative causal variants of which 18 had a posterior inclusion probability >0.5. Of the 19 putative causal variants, 12 were novel discoveries. Specific variants were associated with a more myopic refractive error, while others were associated with a more hyperopic refractive error. Association with age of onset of spectacle wear (AOSW) was examined in an independent validation sample (38 100 early AOSW cases and 74 243 controls). Of 11 novel variants that could be tested, 8 (73%) showed evidence of association with AOSW status. This work identified COL4A4 and ATM as novel candidate genes associated with refractive error. In addition, novel putative causal variants were identified in the genes RASGEF1, ARMS2, BMP4, SIX6, GSDMA, GNGT2, ZNF652 and CRX. Despite these successes, the study also highlighted the limitations of community-based WES studies compared with high myopia case-control WES studies.

Complex N-Linked Glycosylation: A Potential Modifier of Niemann-Pick Disease, Type C1 Pathology

Complex asparagine-linked glycosylation plays key roles in cellular functions, including cellular signaling, protein stability, and immune response. Previously, we characterized the appearance of a complex asparagine-linked glycosylated form of lysosome-associated membrane protein 1 (LAMP1) in the cerebellum of Npc1^-/- mice. This LAMP1 form was found on activated microglia, and its appearance correlated both spatially and temporally with cerebellar Purkinje neuron loss. To test the importance of complex asparagine-linked glycosylation in NPC1 pathology, we generated NPC1 knock-out mice deficient in MGAT5, a key Golgi-resident glycosyl transferase involved in complex asparagine-linked glycosylation. Our results show that Mgat5^-/-:Npc1^-/- mice were smaller than Mgat5^+/+:Npc1^-/- mice, and exhibited earlier NPC1 disease onset and reduced lifespan. Western blot and lectin binding analyses of cerebellar extracts confirmed the reduction in complex asparagine-linked glycosylation, and the absence of the hyper-glycosylated LAMP1 previously observed. Western blot analysis of cerebellar extracts demonstrated reduced calbindin staining in Mgat5^-/-:Npc1^-/- mice compared to Mgat5^+/+:Npc1^-/- mutant mice, and immunofluorescent staining of cerebellar sections indicated decreased levels of Purkinje neurons and increased astrogliosis in Mgat5^-/-:Npc1^-/- mice. Our results suggest that reduced asparagine-linked glycosylation increases NPC1 disease severity in mice, and leads to the hypothesis that mutations in genes involved in asparagine-linked glycosylation may contribute to disease severity progression in individuals with NPC1. To examine this with respect to MGAT5, we analyzed 111 NPC1 patients for two MGAT5 SNPs associated with multiple sclerosis; however, we did not identify an association with NPC1 phenotypic severity.

Gene-level association analysis of ordinal traits with functional ordinal logistic regressions

In this paper, we develop functional ordinal logistic regression (FOLR) models to perform gene-based analysis of ordinal traits. In the proposed FOLR models, genetic variant data are viewed as stochastic functions of physical positions and the genetic effects are treated as a function of physical positions. The FOLR models are built upon functional data analysis which can be revised to analyze the ordinal traits and high dimension genetic data. The proposed methods are capable of dealing with dense genotype data which is usually encountered in analyzing the next-generation sequencing data. The methods are flexible and can analyze three types of genetic data: (1) rare variants only, (2) common variants only, and (3) a combination of rare and common variants. Simulation studies show that the likelihood ratio test statistics of the FOLR models control type I errors well and have good power performance. The proposed methods achieve the goals of analyzing ordinal traits directly, reducing high dimensionality of dense genetic variants, being computationally manageable, facilitating model convergence, properly controlling type I errors, and maintaining high power levels. The FOLR models are applied to analyze Age-Related Eye Disease Study data, in which two genes are found to strongly associate with four ordinal traits.

Association analyses of rare variants identify two genes associated with refractive error

PURPOSE

Genetic variants identified through population-based genome-wide studies are generally of high frequency, exerting their action in the central part of the refractive error spectrum. However, the power to identify associations with variants of lower minor allele frequency is greatly reduced, requiring considerable sample sizes. Here we aim to assess the impact of rare variants on genetic variation of refractive errors in a very large general population cohort.

METHODS

Genetic association analyses of non-cyclopaedic autorefraction calculated as mean spherical equivalent (SPHE) used whole-exome sequence genotypic information from 50,893 unrelated participants in the UK Biobank of European ancestry. Gene-based analyses tested for association with SPHE using an optimised SNP-set kernel association test (SKAT-O) restricted to rare variants (minor allele frequency < 1%) within protein-coding regions of the genome. All models were adjusted for age, sex and common lead variants within the same locus reported by previous genome-wide association studies. Potentially causal markers driving association at significant loci were elucidated using sensitivity analyses by sequentially dropping the most associated variants from gene-based analyses.

RESULTS

We found strong statistical evidence for association of SPHE with the SIX6 (p-value = 2.15 x 10-10, or Bonferroni-Corrected p = 4.41x10-06) and the CRX gene (p-value = 6.65 x 10-08, or Bonferroni-Corrected p = 0.001). The SIX6 gene codes for a transcription factor believed to be critical to the eye, retina and optic disc development and morphology, while CRX regulates photoreceptor specification and expression of over 700 genes in the retina. These novel associations suggest an important role of genes involved in eye morphogenesis in refractive error.

CONCLUSION

The results of our study support previous research highlighting the importance of rare variants to the genetic risk of refractive error. We explain some of the origins of the genetic signals seen in GWAS but also report for the first time a completely novel association with the CRX gene.

What makes a good prediction? Feature importance and beginning to open the black box of machine learning in genetics

Genetic data have become increasingly complex within the past decade, leading researchers to pursue increasingly complex questions, such as those involving epistatic interactions and protein prediction. Traditional methods are ill-suited to answer these questions, but machine learning (ML) techniques offer an alternative solution. ML algorithms are commonly used in genetics to predict or classify subjects, but some methods evaluate which features (variables) are responsible for creating a good prediction; this is called feature importance. This is critical in genetics, as researchers are often interested in which features (e.g., SNP genotype or environmental exposure) are responsible for a good prediction. This allows for the deeper analysis beyond simple prediction, including the determination of risk factors associated with a given phenotype. Feature importance further permits the researcher to peer inside the black box of many ML algorithms to see how they work and which features are critical in informing a good prediction. This review focuses on ML methods that provide feature importance metrics for the analysis of genetic data. Five major categories of ML algorithms: k nearest neighbors, artificial neural networks, deep learning, support vector machines, and random forests are described. The review ends with a discussion of how to choose the best machine for a data set. This review will be particularly useful for genetic researchers looking to use ML methods to answer questions beyond basic prediction and classification.

Myopia in African Americans Is Significantly Linked to Chromosome 7p15.2-14.2

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.

Evaluation of Shared Genetic Susceptibility to High and Low Myopia and Hyperopia

Importance

Uncertainty currently exists about whether the same genetic variants are associated with susceptibility to low myopia (LM) and high myopia (HM) and to myopia and hyperopia. Addressing this question is fundamental to understanding the genetics of refractive error and has clinical relevance for genotype-based prediction of children at risk for HM and for identification of new therapeutic targets.

Objective

To assess whether a common set of genetic variants are associated with susceptibility to HM, LM, and hyperopia.

Design, Setting, and Participants

This genetic association study assessed unrelated UK Biobank participants 40 to 69 years of age of European and Asian ancestry. Participants 40 to 69 years of age living in the United Kingdom were recruited from January 1, 2006, to October 31, 2010. Of the total sample of 502 682 participants, 117 279 (23.3%) underwent an ophthalmic assessment. Data analysis was performed from December 12, 2019, to June 23, 2020.

Exposures

Four refractive error groups were defined: HM, -6.00 diopters (D) or less; LM, -3.00 to -1.00 D; hyperopia, +2.00 D or greater; and emmetropia, 0.00 to +1.00 D. Four genome-wide association study (GWAS) analyses were performed in participants of European ancestry: (1) HM vs emmetropia, (2) LM vs emmetropia, (3) hyperopia vs emmetropia, and (4) LM vs hyperopia. Polygenic risk scores were generated from GWAS summary statistics, yielding 4 sets of polygenic risk scores. Performance was assessed in independent replication samples of European and Asian ancestry.

Main Outcomes and Measures

Odds ratios (ORs) of polygenic risk scores in replication samples.

Results

A total of 51 841 unrelated individuals of European ancestry and 2165 unrelated individuals of Asian ancestry were assigned to a specific refractive error group and included in our analyses. Polygenic risk scores derived from all 4 GWAS analyses were predictive of all categories of refractive error in both European and Asian replication samples. For example, the polygenic risk score derived from the HM vs emmetropia GWAS was predictive in the European sample of HM vs emmetropia (OR, 1.58; 95% CI, 1.41-1.77; P = 1.54 × 10-15) as well as LM vs emmetropia (OR, 1.15; 95% CI, 1.07-1.23; P = 8.14 × 10-5), hyperopia vs emmetropia (OR, 0.83; 95% CI, 0.77-0.89; P = 4.18 × 10-7), and LM vs hyperopia (OR, 1.45; 95% CI, 1.33-1.59; P = 1.43 × 10-16).

Conclusions and Relevance

Genetic risk variants were shared across HM, LM, and hyperopia and across European and Asian samples. Individuals with HM inherited a higher number of variants from among the same set of myopia-predisposing alleles and not different risk alleles compared with individuals with LM. These findings suggest that treatment interventions targeting common genetic risk variants associated with refractive error could be effective against both LM and HM.

IMI 2021 Yearly Digest

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.

Genetic Variation and Recurrent Haplotypes on Chromosome 6q23-25 Risk Locus in Familial Lung Cancer

Although lung cancer is known to be caused by environmental factors, it has also been shown to have genetic components, and the genetic etiology of lung cancer remains understudied. We previously identified a lung cancer risk locus on 6q23-25 using microsatellite data in families with a history of lung cancer. To further elucidate that signal, we performed targeted sequencing on nine of our most strongly linked families. Two-point linkage analysis of the sequencing data revealed that the signal was heterogeneous and that different families likely had different risk variants. Three specific haplotypes were shared by some of the families: 6q25.3-26 in families 42 and 44, 6q25.2-25.3 in families 47 and 59, and 6q24.2-25.1 in families 30, 33, and 35. Region-based logarithm of the odds scores and expression data identified the likely candidate genes for each haplotype overlap: ARID1B at 6q25.3, MAP3K4 at 6q26, and UTRN (6q24.1) and PHACTR2 (6q24.2). Further annotation was used to zero in on potential risk variants in those genes. All four genes are good candidate genes for lung cancer risk, having been linked to either lung cancer specifically or other cancers. However, this is the first time any of these genes has been implicated in germline risk. Functional analysis of these four genes is planned for future work. SIGNIFICANCE: This study identifies four genes associated with lung cancer risk, which could help guide future lung cancer prevention and treatment approaches.

Increased Burden of Rare Sequence Variants in GnRH-Associated Genes in Women With Hypothalamic Amenorrhea

CONTEXT

Functional hypothalamic amenorrhea (HA) is a common, acquired form of hypogonadotropic hypogonadism that occurs in the setting of energy deficits and/or stress. Variability in individual susceptibility to these stressors, HA heritability, and previous identification of several rare sequence variants (RSVs) in genes associated with the rare disorder, isolated hypogonadotropic hypogonadism (IHH), in individuals with HA suggest a possible genetic contribution to HA susceptibility.

OBJECTIVE

We sought to determine whether the burden of RSVs in IHH-related genes is greater in women with HA than controls.

DESIGN

We compared patients with HA to control women.

SETTING

The study was conducted at secondary referral centers.

PATIENTS AND OTHER PARTICIPANTS

Women with HA (n = 106) and control women (ClinSeq study; n = 468).

INTERVENTIONS

We performed exome sequencing in all patients and controls.

MAIN OUTCOME MEASURE(S)

The frequency of RSVs in 53 IHH-associated genes was determined using rare variant burden and association tests.

RESULTS

RSVs were overrepresented in women with HA compared with controls (P = .007). Seventy-eight heterozygous RSVs in 33 genes were identified in 58 women with HA (36.8% of alleles) compared to 255 RSVs in 41 genes among 200 control women (27.2%).

CONCLUSIONS

Women with HA are enriched for RSVs in genes that cause IHH, suggesting that variation in genes associated with gonadotropin-releasing hormone neuronal ontogeny and function may be a major determinant of individual susceptibility to developing HA in the face of diet, exercise, and/or stress.

Gene-based analysis of bi-variate survival traits via functional regressions with applications to eye diseases

Genetic studies of two related survival outcomes of a pleiotropic gene are commonly encountered but statistical models to analyze them are rarely developed. To analyze sequencing data, we propose mixed effect Cox proportional hazard models by functional regressions to perform gene-based joint association analysis of two survival traits motivated by our ongoing real studies. These models extend fixed effect Cox models of univariate survival traits by incorporating variations and correlation of multivariate survival traits into the models. The associations between genetic variants and two survival traits are tested by likelihood ratio test statistics. Extensive simulation studies suggest that type I error rates are well controlled and power performances are stable. The proposed models are applied to analyze bivariate survival traits of left and right eyes in the age-related macular degeneration progression.

Abstract 37: Highly aggregated lung cancer families reveal a heterogeneous cause for a previous linkage signal on 6q

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.

Abstract 2300: 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

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.

Two-stage Study of Familial Prostate Cancer by Whole-exome Sequencing and Custom Capture Identifies 10 Novel Genes Associated with the Risk of Prostate Cancer

BACKGROUND

Family history of prostate cancer (PCa) is a well-known risk factor, and both common and rare genetic variants are associated with the disease.

OBJECTIVE

To detect new genetic variants associated with PCa, capitalizing on the role of family history and more aggressive PCa.

DESIGN, SETTING, AND PARTICIPANTS

A two-stage design was used. In stage one, whole-exome sequencing was used to identify potential risk alleles among affected men with a strong family history of disease or with more aggressive disease (491 cases and 429 controls). Aggressive disease was based on a sum of scores for Gleason score, node status, metastasis, tumor stage, prostate-specific antigen at diagnosis, systemic recurrence, and time to PCa death. Genes identified in stage one were screened in stage two using a custom-capture design in an independent set of 2917 cases and 1899 controls.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Frequencies of genetic variants (singly or jointly in a gene) were compared between cases and controls.

RESULTS AND LIMITATIONS

Eleven genes previously reported to be associated with PCa were detected (ATM, BRCA2, HOXB13, FAM111A, EMSY, HNF1B, KLK3, MSMB, PCAT1, PRSS3, and TERT), as well as an additional 10 novel genes (PABPC1, QK1, FAM114A1, MUC6, MYCBP2, RAPGEF4, RNASEH2B, ULK4, XPO7, and THAP3). Of these 10 novel genes, all but PABPC1 and ULK4 were primarily associated with the risk of aggressive PCa.

CONCLUSIONS

Our approach demonstrates the advantage of gene sequencing in the search for genetic variants associated with PCa and the benefits of sampling patients with a strong family history of disease or an aggressive form of disease.

PATIENT SUMMARY

Multiple genes are associated with prostate cancer (PCa) among men with a strong family history of this disease or among men with an aggressive form of PCa.

Gene-Based Association Testing of Dichotomous Traits With Generalized Functional Linear Mixed Models Using Extended Pedigrees: Applications to Age-Related Macular Degeneration

Genetics plays a role in age-related macular degeneration (AMD), a common cause of blindness in the elderly. There is a need for powerful methods for carrying out region-based association tests between a dichotomous trait like AMD and genetic variants on family data. Here, we apply our new generalized functional linear mixed models (GFLMM) developed to test for gene-based association in a set of AMD families. Using common and rare variants, we observe significant association with two known AMD genes: CFH and ARMS2. Using rare variants, we find suggestive signals in four genes: ASAH1, CLEC6A, TMEM63C, and SGSM1. Intriguingly, ASAH1 is down-regulated in AMD aqueous humor, and ASAH1 deficiency leads to retinal inflammation and increased vulnerability to oxidative stress. These findings were made possible by our GFLMM which model the effect of a major gene as a fixed mean, the polygenic contributions as a random variation, and the correlation of pedigree members by kinship coefficients. Simulations indicate that the GFLMM likelihood ratio tests (LRTs) accurately control the Type I error rates. The LRTs have similar or higher power than existing retrospective kernel and burden statistics. Our GFLMM-based statistics provide a new tool for conducting family-based genetic studies of complex diseases. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

Abstract C050: Deleterious coding variants in African American Hereditary Prostate Cancer Study (AAHPC) families

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 &gt;10, Quality Score &gt;10, and Quality Score: Read Depth Ratio &gt; 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.

Whole Exome Sequencing of Highly Aggregated Lung Cancer Families Reveals Linked Loci for Increased Cancer Risk on Chromosomes 12q, 7p, and 4q

BACKGROUND

Lung cancer kills more people than any other cancer in the United States. In addition to environmental factors, lung cancer has genetic risk factors as well, though the genetic etiology is still not well understood. We have performed whole exome sequencing on 262 individuals from 28 extended families with a family history of lung cancer.

METHODS

Parametric genetic linkage analysis was performed on these samples using two distinct analyses-the lung cancer only (LCO) analysis, where only patients with lung cancer were coded as affected, and the all aggregated cancers (AAC) analysis, where other cancers seen in the pedigree were coded as affected.

RESULTS

The AAC analysis yielded a genome-wide significant result at rs61943670 in POLR3B at 12q23.3. POLR3B has been implicated somatically in lung cancer, but this germline finding is novel and is a significant expression quantitative trait locus in lung tissue. Interesting genome-wide suggestive haplotypes were also found within individual families, particularly near SSPO at 7p36.1 in one family and a large linked haplotype spanning 4q21.3-28.3 in a different family. The 4q haplotype contains potential causal rare variants in DSPP at 4q22.1 and PTPN13 at 4q21.3.

CONCLUSIONS

Regions on 12q, 7p, and 4q are linked to increased cancer risk in highly aggregated lung cancer families, 12q across families and 7p and 4q within a single family. POLR3B, SSPO, DSPP, and PTPN13 are currently the best candidate genes.

IMPACT

Functional work on these genes is planned for future studies and if confirmed would lead to potential biomarkers for risk in cancer.

Gene-based association analysis of survival traits via functional regression-based mixed effect cox models for related samples

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 study direction. For unrelated population data, functional regression (FR) 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. In this paper, we extend this approach to analyze censored traits for family data or related samples using FR based mixed effect Cox models (FamCoxME). The FamCoxME model 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 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.

Abstract 4176: Familial lung cancer exhibits multiple novel linked haplotypes within pedigrees

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.

Abstract 4240: Rare candidate variants shared among affected family members in the African American Hereditary Prostate Cancer Study families

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 &gt;10, Quality Score &gt;10, and Quality Score: Read Depth Ratio &gt; 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.

Abstract LB-053: Familial studies identify variants in the E2A transcription factor as putative risk factors for lung cancer

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.

Analysis of the CDKN2A Gene in FAMMM Syndrome Families Reveals Early Age of Onset for Additional Syndromic Cancers

Familial atypical multiple mole melanoma (FAMMM) syndrome is a hereditary cancer syndrome that results from mutations in several genes, including the CDKN2A gene. In addition to melanoma, certain other malignancies such as pancreatic cancer are known to occur more frequently in family members who carry the mutation. However, as these families have been followed over time, additional cancers have been observed in both carriers and noncarriers. We sought to determine whether these additional cancers occur at higher frequencies in carriers than noncarriers. We performed survival analyses using 10 FAMMM syndrome families (N = 1,085 individuals) as well as a mixed effects Cox regression, with age at last visit to the clinic or age at cancer diagnosis as our time variable. This analysis was done separately for the known FAMMM-related cancers and "other" cancer groups. The survival curves showed a significant age effect with carriers having a younger age at cancer onset than noncarriers for FAMMM-related cancers (as expected) as well as for newly associated cancers. The Cox regression reflected what was seen in the survival curves, with all models being highly significant (P = 7.15E-20 and P = 5.00E-13 for the FAMMM-related and other cancers, respectively). These analyses support the hypothesis that CDKN2A mutation carriers in FAMMM syndrome families have increased risk for early onset of several cancer types beyond the known cancers. Therefore, these individuals should be screened for additional cancers, and mutation screening should be extended to more than first-degree relatives of an index carrier patient. SIGNIFICANCE: This study shows that carriers of mutations in the CDKN2A gene in FAMMM syndrome are at increased risk for early onset of several cancer types beyond the known cancers.

Genome-wide scans of myopia in Pennsylvania Amish families reveal significant linkage to 12q15, 8q21.3 and 5p15.33

Myopia is one of the most common ocular disorders in the world, yet the genetic etiology of the disease remains poorly understood. Specialized founder populations, such as the Pennsylvania Amish, provide the opportunity to utilize exclusive genomic architecture, like unique haplotypes, to better understand the genetic causes of myopia. We perform genetic linkage analysis on Pennsylvania Amish families that have a strong familial history of myopia to map any potential causal variants and genes for the disease. 293 individuals from 25 extended families were genotyped on the Illumina ExomePlus array and merged with previous microsatellite data. We coded myopia affection as a binary phenotype; myopia was defined as having a mean spherical equivalent (MSE) of less than or equal to - 1 D (diopters). Two-point and multipoint parametric linkage analyses were performed under an autosomal dominant model. When allowing for locus heterogeneity, we identified two novel genome-wide significantly linked variants at 12q15 (heterogeneity LOD, HLOD = 3.77) in PTPRB and at 8q21.3 (HLOD = 3.35) in CNGB3. We identified further three genome-wide significant variants within a single family. These three variants were located in exons of SLC6A18 at 5p15.33 (LODs ranged from 3.51 to 3.37). Multipoint analysis confirmed the significant signal at 5p15.33 with six genome-wide significant variants (LODs ranged from 3.6 to 3.3). Further suggestive evidence of linkage was observed in several other regions of the genome. All three novel linked regions contain strong candidate genes, especially CNGB3 on 8q21.3, which has been shown to affect photoreceptors and cause complete color blindness. Whole genome sequencing on these regions is planned to conclusively elucidate the causal variants.

Linear mixed models for association analysis of quantitative traits with next-generation sequencing data

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.

Inferring disease risk genes from sequencing data in multiplex pedigrees through sharing of rare variants

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.

Exome genotyping and linkage analysis identifies two novel linked regions and replicates two others for myopia in Ashkenazi Jewish families

BACKGROUND

Myopia is one of most common eye diseases in the world and affects 1 in 4 Americans. It is a complex disease caused by both environmental and genetics effects; the genetics effects are still not well understood. In this study, we performed genetic linkage analyses on Ashkenazi Jewish families with a strong familial history of myopia to elucidate any potential causal genes.

METHODS

Sixty-four extended Ashkenazi Jewish families were previously collected from New Jersey. Genotypes from the Illumina ExomePlus array were merged with prior microsatellite linkage data from these families. Additional custom markers were added for candidate regions reported in literature for myopia or refractive error. Myopia was defined as mean spherical equivalent (MSE) of -1D or worse and parametric two-point linkage analyses (using TwoPointLods) and multi-point linkage analyses (using SimWalk2) were performed as well as collapsed haplotype pattern (CHP) analysis in SEQLinkage and association analyses performed with FBAT and rv-TDT.

RESULTS

Strongest evidence of linkage was on 1p36(two-point LOD = 4.47) a region previously linked to refractive error (MYP14) but not myopia. Another genome-wide significant locus was found on 8q24.22 with a maximum two-point LOD score of 3.75. CHP analysis also detected the signal on 1p36, localized to the LINC00339 gene with a maximum HLOD of 3.47, as well as genome-wide significant signals on 7q36.1 and 11p15, which overlaps with the MYP7 locus.

CONCLUSIONS

We identified 2 novel linkage peaks for myopia on chromosomes 7 and 8 in these Ashkenazi Jewish families and replicated 2 more loci on chromosomes 1 and 11, one previously reported in refractive error but not myopia in these families and the other locus previously reported in the literature. Strong candidate genes have been identified within these linkage peaks in our families. Targeted sequencing in these regions will be necessary to definitively identify causal variants under these linkage peaks.

The 677C→T variant of MTHFR is the major genetic modifier of biomarkers of folate status in a young, healthy Irish population

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.

ComPaSS-GWAS: A method to reduce type I error in genome-wide association studies when replication data are not available

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.

Genome-wide association study of familial lung cancer

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.

A genome-wide association study identifies a susceptibility locus for biliary atresia on 2p16.1 within the gene EFEMP1

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.

Abstract 3276: Whole exome sequencing identifies significantly linked regions on multiple chromosomes in families with a history of lung cancer

Lung cancer is the deadliest cancer in the United States, contributing approximately 25% of all cancer deaths. Lung cancer risk is well-documented to increase in response to environmental factors, particularly tobacco smoking. As one might expect for a complex trait, there is also a significant genetic risk component in lung cancer, though it is not very well studied. We obtained whole exome sequencing (WES) genotype data from Washington University on 204 subjects from 25 extended families. These individuals were recruited from families with a history of lung cancer and previous analyses showed these 25 families be informative. The purpose of this study is to identify potential risk variants for lung cancer by performing genetic linkage analysis. Quality control was performed on the sequence data, filtering on parameters such as depth (less than 10), genotype quality (less than 10), missingness, and Mendelian inconsistencies. Identity-by-descent (IBD) values were also calculated to verify correct familial relationships. Quality control procedures left approximately 500,000 SNVs and indels for analysis.

We performed two-point parametric linkage analysis assuming an autosomal dominant mode of inheritance with a disease allele frequency of 1%, a 10% penetrance for carriers and a 1% penetrance for non-carriers. Two discrete sets of linkage analyses were performed. One was a variant-based analysis, which evaluated linkage between the phenotype and individual SNVs or indels. The second was gene-based analysis, which created a multi-allelic pseudomarker corresponding to a gene from haplotypes of rare variants (minor allele frequency &lt;= 0.01) located within that particular gene. Two-point linkage analysis was then performed on the pseudomarkers.

While the variant-based analysis did not identify any genome-wide significant results, several were identified by the gene-based analysis. The highest HLOD scores were both greater than the genome-wide significance level of HLOD = 3.3 and were located on two regions of chromosome 1q: 1q42.13-43 and 1q21.2-21.1. In both regions, the significant HLOD scores clustered around known cancer genes. At the 1q42.13-43 region, signals centered on the cancer-implicated genes OBSCN and RYR2 (also a known mesothelioma gene), while at 1q21.2-21.1 the signals centered on five genes in the neuroblastoma breakpoint family (NBPF) genes, a cluster of recently duplicated genes. NBPF genes have previously been implicated in a variety of different cancers including lung cancer. We are currently performing additional analyses to corroborate the significant results, as well as examining the individual families to determine which families are driving the significant signals.

Citation Format: Anthony M. Musolf, Haiming Sun, Bilal A. Moiz, Diptasri Mandal, Mariza de Andrade, Colette Gaba, Ping Yang, Yafang Li, Ming You, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Joan E. Bailey-Wilson. Whole exome sequencing identifies significantly linked regions on multiple chromosomes in families with a history of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3276.

Genome-wide association meta-analysis highlights light-induced signaling as a driver for refractive error

Refractive errors, including myopia, are the most frequent eye disorders worldwide and an increasingly common cause of blindness. This genome-wide association meta-analysis in 160,420 participants and replication in 95,505 participants increased the number of established independent signals from 37 to 161 and showed high genetic correlation between Europeans and Asians (>0.78). Expression experiments and comprehensive in silico analyses identified retinal cell physiology and light processing as prominent mechanisms, and also identified functional contributions to refractive-error development in all cell types of the neurosensory retina, retinal pigment epithelium, vascular endothelium and extracellular matrix. Newly identified genes implicate novel mechanisms such as rod-and-cone bipolar synaptic neurotransmission, anterior-segment morphology and angiogenesis. Thirty-one loci resided in or near regions transcribing small RNAs, thus suggesting a role for post-transcriptional regulation. Our results support the notion that refractive errors are caused by a light-dependent retina-to-sclera signaling cascade and delineate potential pathobiological molecular drivers.

A genome-wide association study of corneal astigmatism: The CREAM Consortium

Purpose

To identify genes and genetic markers associated with corneal astigmatism.

Methods

A meta-analysis of genome-wide association studies (GWASs) of corneal astigmatism undertaken for 14 European ancestry (n=22,250) and 8 Asian ancestry (n=9,120) cohorts was performed by the Consortium for Refractive Error and Myopia. Cases were defined as having >0.75 diopters of corneal astigmatism. Subsequent gene-based and gene-set analyses of the meta-analyzed results of European ancestry cohorts were performed using VEGAS2 and MAGMA software. Additionally, estimates of single nucleotide polymorphism (SNP)-based heritability for corneal and refractive astigmatism and the spherical equivalent were calculated for Europeans using LD score regression.

Results

The meta-analysis of all cohorts identified a genome-wide significant locus near the platelet-derived growth factor receptor alpha (PDGFRA) gene: top SNP: rs7673984, odds ratio=1.12 (95% CI:1.08-1.16), p=5.55×10^-9. No other genome-wide significant loci were identified in the combined analysis or European/Asian ancestry-specific analyses. Gene-based analysis identified three novel candidate genes for corneal astigmatism in Europeans-claudin-7 (CLDN7), acid phosphatase 2, lysosomal (ACP2), and TNF alpha-induced protein 8 like 3 (TNFAIP8L3).

Conclusions

In addition to replicating a previously identified genome-wide significant locus for corneal astigmatism near the PDGFRA gene, gene-based analysis identified three novel candidate genes, CLDN7, ACP2, and TNFAIP8L3, that warrant further investigation to understand their role in the pathogenesis of corneal astigmatism. The much lower number of genetic variants and genes demonstrating an association with corneal astigmatism compared to published spherical equivalent GWAS analyses suggest a greater influence of rare genetic variants, non-additive genetic effects, or environmental factors in the development of astigmatism.

Myopia in Chinese families shows linkage to 10q26.13

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).

The FUT2 secretor variant p.Trp154Ter influences serum vitamin B12 concentration via holo-haptocorrin, but not holo-transcobalamin, and is associated with haptocorrin glycosylation

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.

Parametric Linkage Analysis Identifies Five Novel Genome-Wide Significant Loci for Familial Lung Cancer

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.

Abstract 4268: Familial lung cancer is significantly linked to cancer-associated genes on five chromosomes

Lung cancer (LC) is the leading cancer killer of Americans; an estimated 158,000 people will die in the U.S. from LC in 2016. While it is well-known that LC risk is affected by the environment, particularly tobacco smoking, there is a substantial genetic risk to LC also. We examined genotype data from Illumina HumanCore-12v1-0 array (297,000 SNPs) on 175 individuals in 25 extended families with a strong history of LC recruited by the Genetic Epidemiology of Lung Cancer Consortium. The purpose of this study is to determine which families are segregating a high-penetrance genetic risk haplotype so that the most informative families can be selected for DNA sequencing studies. Quality control was performed to remove SNPs and individuals with greater than 1% missingness as well as monomorphic SNPs. SNPs with Mendelian errors in more than one family were dropped. Identity-by-descent values were calculated to confirm correct familial relationships; 1 individual was dropped. After quality control we were left with approximately 245,000 SNPs for analysis. We performed three types of parametric linkage analyses using an autosomal dominant model with 40% penetrance in carriers and 1% penetrance in non-carriers. A disease allele frequency of 0.01 was used. Standard single variant two-point analysis between the disease and each marker was performed using TwoPointLods. Multipoint linkage analysis was performed using SimWalk2. We also performed regional-based linkage analyses using SEQLinkage and MERLIN. SEQLinkage builds a multiallelic regional marker (similar to a microsatellite) that corresponds to a gene or a portion of a gene. Two-point linkage analyses were then performed on the regional markers using MERLIN. We identified five loci that were genome-wide significant (HLOD score ≥ 3.3) from the regional-based linkage analyses on 18p11.23 (HLOD = 4.1), 2p22.2 (3.9), 14q13.1 (3.7), 16p13.1 (3.4), and 20q13.11 (3.4). It is particularly exciting that the scores centered on prospective cancer genes. Our highest score was centered on PTPRM, a protein tyrosine phosphatase on chromosome 18 that has been implicated as a LC oncogene. The signal on 20q13 also centered on another protein tyrosine phosphatase (PTPRT) that has been shown to be mutated in LC cells. The source of the signal on 16p13 was RNA binding protein RBFOX1, which has been shown to be deleted in LC cell lines and the source of the signal on 2p22 was LRP1B, a LDL receptor-related protein that is often inactivated in LC cells. The source of the final signal on 14q13 was NPAS3, a transcription factor that is a tumor suppressor in brain tumors. It should be noted that all previous evidence linking these genes to cancer was based on somatic mutations; this is the first time any of these genes has been shown to be significantly linked to germline disease risk in a family-based study. We plan to perform targeted sequencing on the linked regions to elucidate the exact causal variant.

Citation Format: Joan E. Bailey-Wilson, Anthony M. Musolf, Claire L. Simpson, Mariza de Andrade, Diptasri Mandal, Colette G. Gaba, Ping Yang, Ming You, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos. Familial lung cancer is significantly linked to cancer-associated genes on five chromosomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4268. doi:10.1158/1538-7445.AM2017-4268

Abstract 4290: A study in locus heterogeneity: Targeted sequencing analysis of 6q reveals multiple significant loci as the source of a previous linkage peak in familial lung cancer

Lung cancer is the leading cancer-related cause of death in the United States. We had previously performed multipoint linkage analysis on families with a strong family history of lung cancer and found significant linkage to the 6q25 region. In order to find the source of that linkage signal, we performed targeted sequencing 6q23-6q27 on 75 individuals from the 9 most highly linked families. We performed two types of parametric linkage analysis, using an autosomal dominant mode of inheritance with 10% penetrance for carriers and a 1% phenocopy rate using a disease allele frequency of 1%. The first type was a two-point analysis using an Elston-Stewart algorithm. This approach did not lead to any genome-wide significant results but demonstrated significant heterogeneity throughout the nine families.In an effort to recover the power from the original multipoint analysis, we performed a regional linkage analysis using SEQLinkage and MERLIN. SEQLinkage built regional haplotypes that corresponded to a gene or an intergenic region - the regions were based on a customized map of our design. The regional markers were multiallelic which allowed for greater information content and were similar to the microsatellites that were used in the original multipoint analysis. The regional markers were then analyzed in a two-point linkage analysis via MERLIN. This allowed us to identify two genome-wide significant signals at PACRG-AS1 at 6q26 (HLOD = 3.4) and SAMD5 at 6q24 (3.3). The PACRG-AS1 is novel, though it is associated with the known lung cancer gene PARK2. SAMD5 may be involved in lung cancer cell proliferation. The heterogeneity of the two signals was particularly interesting. The PACRG-AS1 was driven primarily by two families. The SAMD5 marker was not being strongly driven by any of the families and appears to be a small cumulative effect across the nine families. In addition, several families have large, but non-significant LOD scores at other loci across the region. This further reinforces the locus heterogeneity within the region, and it is likely that our two significant signals here are not the only variants affecting the phenotype. We further attempted to localize the signals by running SEQLinkage using a custom map where genes are broken into exons and introns. Though this resulted in no significant markers, the highest signal was located in the intronic region of SAMD5 (HLOD = 3) and several other suggestive signals were localized to intronic regions of good candidate genes like SASH1 and ARID1B. Examination of predicted effects of the candidate regulatory variants using eQTL databases is ongoing. This is a region full of promising candidates, and it is likely that the two significant signals found here are just part of many that could be affecting lung cancer risk. We plan to do further analysis within the individual families to elucidate any more genes affecting this signal.

Citation Format: Anthony M. Musolf, Claire L. Simpson, Bilal A. Moiz, Candace Middlebrooks, Mariza de Andrade, Diptasri Mandal, Colette Gaba, Ping Yang, Yafang Li, Ming You, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Joan E. Bailey-Wilson. A study in locus heterogeneity: Targeted sequencing analysis of 6q reveals multiple significant loci as the source of a previous linkage peak in familial lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4290. doi:10.1158/1538-7445.AM2017-4290

Caucasian Families Exhibit Significant Linkage of Myopia to Chromosome 11p

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.

Genome-wide association study identifies three novel loci in Fuchs endothelial corneal dystrophy

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<5 × 10-8): KANK4 rs79742895, LAMC1 rs3768617 and LINC00970/ATP1B1 rs1200114. We also observe an overwhelming effect of the established TCF4 locus. Interestingly, we detect differential sex-specific association at LAMC1, with greater risk in women, and TCF4, with greater risk in men. Combining GWAS results with biological evidence we expand the knowledge of common FECD loci from one to four, and provide a deeper understanding of the underlying pathogenic basis of FECD.

gsSKAT: Rapid gene set analysis and multiple testing correction for rare-variant association studies using weighted linear kernels

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.

Rare copy number variants in patients with congenital conotruncal heart defects

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 109:271-295, 2017. © 2017 Wiley Periodicals, Inc.