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.

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 novel de novo TP63 mutation in whole-exome sequencing of a Syrian family with Oral cleft and ectrodactyly.

BACKGROUND: Oral clefts and ectrodactyly are common, heterogeneous birth defects. We performed whole-exome sequencing (WES) analysis in a Syrian family. The proband presented with both orofacial clefting and ectrodactyly but not ectodermal dysplasia as typically seen in ectrodactyly, ectodermal dysplasia, and cleft lip/palate syndrome-3. A paternal uncle with only an oral cleft was deceased and unavailable for analysis. METHODS: Variant annotation, Mendelian inconsistencies, and novel variants in known cleft genes were examined. Candidate variants were validated using Sanger sequencing, and pathogenicity assessed by knocking out the tp63 gene in zebrafish to evaluate its role during zebrafish development. RESULTS: Twenty-eight candidate de novo events were identified, one of which is in a known oral cleft and ectrodactyly gene, TP63 (c.956G > T, p.Arg319Leu), and confirmed by Sanger sequencing. CONCLUSION: TP63 mutations are associated with multiple autosomal dominant orofacial clefting and limb malformation disorders. The p.Arg319Leu mutation seen in this patient is de novo but also novel. Two known mutations in the same codon (c.956G > A, p.(Arg319His; rs121908839, c.955C > T), p.Arg319Cys) cause ectrodactyly, providing evidence that mutating this codon is deleterious. While this TP63 mutation is the best candidate for the patient's clinical presentation, whether it is responsible for the entire phenotype is unclear. Generation and characterization of tp63 knockout zebrafish showed necrosis and rupture of the head at 3 days post-fertilization (dpf). The embryonic phenotype could not be rescued by injection of zebrafish or human messenger RNA (mRNA). Further functional analysis is needed to determine what proportion of the phenotype is due to this mutation.

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.

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.

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.

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.

Genome-wide linkage search for cancer susceptibility loci in a cohort of non BRCA1/2 families in Sri Lanka.

OBJECTIVE: Although linkage studies have been utilized for the identification of variants associated with cancer in the world, little is known about their role in non BRCA1/2 individuals in the Sri Lankans. Hence we performed linkage analysis to identify susceptibility loci related to the inherited risk of cancer in a cohort of Sri Lankans affected with hereditary breast cancer. The Illumina global screening array having 654,027 single nucleotide polymorphism markers was performed in four families, in which at least three individuals within third degree relatives were affected by breast cancer. Two-point parametric linkage analysis was conducted assuming disease allele frequency of 1%. Penetrance was set at 90% for carriers with a 10% phenocopy rate. RESULTS: Thirty-one variants exhibited genome-wide suggestive HLODs. The top overall HLOD score was at rs1856277, an intronic variant in MYO16 on chromosome 13. The two most informative families also suggested several candidate linked loci in genes, including ERAP1, RPRM, WWOX, CDH1, EXOC1, HUS1B, STIM1 and TUSC1. This study provides the first step in identifying germline variants that may be involved in risk of cancer in cancer-aggregated non-BRCA1/2 families from the understudied Sri Lankan population. Several candidate linked regions showed suggestive evidence of linkage to cancer risk.

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.

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.

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.

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.

Sterol and lipid analyses identifies hypolipidemia and apolipoprotein disorders in autism associated with adaptive functioning deficits.

An improved understanding of sterol and lipid abnormalities in individuals with autism spectrum disorder (ASD) could lead to personalized treatment approaches. Toward this end, in blood, we identified reduced synthesis of cholesterol in families with ≥2 children with ASD participating with the Autism Genetic Resource Exchange (AGRE), as well as reduced amounts of high-density lipoprotein cholesterol (HDL), apolipoprotein A1 (ApoA1) and apolipoprotein B (ApoB), with 19.9% of the subjects presenting with apolipoprotein patterns similar to hypolipidemic clinical syndromes and 30% with either or both ApoA1 and ApoB less than the fifth centile. Subjects with levels less than the fifth centile of HDL or ApoA1 or ApoA1 + ApoB had lower adaptive functioning than other individuals with ASD, and hypocholesterolemic subjects had apolipoprotein deficits significantly divergent from either typically developing individuals participating in National Institutes of Health or the National Health and Nutrition Examination Survey III.

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.

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.

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.

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.

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.