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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.

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.

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 502682 participants, 117279 (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 51841 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..

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 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.

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.

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

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.

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.

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.

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.

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.

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Prostate cancer has a strong familial component but uncovering the molecular basis for inherited susceptibility for this disease has been challenging. Recently, a rare, recurrent mutation (G84E) in HOXB13 was reported to be associated with prostate cancer risk. Confirmation and characterization of this finding is necessary to potentially translate this information to the clinic. To examine this finding in a large international sample of prostate cancer families, we genotyped this mutation and 14 other SNPs in or flanking HOXB13 in 2,443 prostate cancer families recruited by the International Consortium for Prostate Cancer Genetics (ICPCG). At least one mutation carrier was found in 112 prostate cancer families (4.6 %), all of European descent. Within carrier families, the G84E mutation was more common in men with a diagnosis of prostate cancer (194 of 382, 51 %) than those without (42 of 137, 30 %), P = 9.9 × 10−8 [odds ratio 4.42 (95 % confidence interval 2.56–7.64)]. A family-based association test found G84E to be significantly over-transmitted from parents to affected offspring (P = 6.5 × 10−6). Analysis of markers flanking the G84E mutation indicates that it resides in the same haplotype in 95 % of carriers, consistent with a founder effect. Clinical characteristics of cancers in mutation carriers included features of high-risk disease. These findings demonstrate that the HOXB13 G84E mutation is present in ~5 % of prostate cancer families, predominantly of European descent, and confirm its association with prostate cancer risk. While future studies are needed to more fully define the clinical utility of this observation, this allele and others like it could form the basis for early, targeted screening of men at elevated risk for this common, clinically heterogeneous cancer. Electronic supplementary material The online version of this article (doi:10.1007/s00439-012-1229-4) contains supplementary material, which is available to authorized users.

Author version made available in accordance with the publisher's policy., Refractive error is the most common eye disorder worldwide and is a prominent cause of blindness. Myopia affects over 30% of Western populations and up to 80% of Asians. The CREAM consortium conducted genome-wide meta-analyses, including 37,382 individuals from 27 studies of European ancestry and 8,376 from 5 Asian cohorts. We identified 16 new loci for refractive error in individuals of European ancestry, of which 8 were shared with Asians. Combined analysis identified 8 additional associated loci. The new loci include candidate genes with functions in neurotransmission (GRIA4), ion transport (KCNQ5), retinoic acid metabolism (RDH5), extracellular matrix remodeling (LAMA2 and BMP2) and eye development (SIX6 and PRSS56). We also confirmed previously reported associations with GJD2 and RASGRF1. Risk score analysis using associated SNPs showed a tenfold increased risk of myopia for individuals carrying the highest genetic load. Our results, based on a large meta-analysis across independent multiancestry studies, considerably advance understanding of the mechanisms involved in refractive error and myopia., Australian National Health and Medical Research Council.

We report here the identification of a gene associated with the hyperparathyroidism-jaw tumor (HPT-JT) syndrome. A single locus associated with HPT-JT (HRPT2) was previously mapped to chromosomal region 1q25-q32. We refined this region to a critical interval of 12 cM by genotyping in 26 affected kindreds. Using a positional candidate approach, we identified thirteen different heterozygous, germline, inactivating mutations in a single gene in fourteen families with HPT-JT. The proposed role of HRPT2 as a tumor suppressor was supported by mutation screening in 48 parathyroid adenomas with cystic features, which identified three somatic inactivating mutations, all located in exon 1. None of these mutations were detected in normal controls, and all were predicted to cause deficient or impaired protein function. HRPT2 is a ubiquitously expressed, evolutionarily conserved gene encoding a predicted protein of 531 amino acids, for which we propose the name parafibromin. Our findings suggest that HRPT2 is a tumor-suppressor gene, the inactivation of which is directly involved in predisposition to HPT-JT and in development of some sporadic parathyroid tumors.

Prostate cancer (PrCa) is the most common male cancer in developed countries and the second most common cause of cancer death after lung cancer. We recently reported a genome-wide linkage scan in 69 Finnish hereditary PrCa (HPC) families, which replicated the HPC9 locus on 17q21-q22 and identified a locus on 2q37. The aim of this study was to identify and to detect other loci linked to HPC. Here we used ordered subset analysis (OSA), conditioned on nonparametric linkage to these loci to detect other loci linked to HPC in subsets of families, but not the overall sample. We analyzed the families based on their evidence for linkage to chromosome 2, chromosome 17 and a maximum score using the strongest evidence of linkage from either of the two loci. Significant linkage to a 5-cM linkage interval with a peak OSA nonparametric allele-sharing LOD score of 4.876 on Xq26.3-q27 (ΔLOD=3.193, empirical P=0.009) was observed in a subset of 41 families weakly linked to 2q37, overlapping the HPCX1 locus. Two peaks that were novel to the analysis combining linkage evidence from both primary loci were identified; 18q12.1-q12.2 (OSA LOD=2.541, ΔLOD=1.651, P=0.03) and 22q11.1-q11.21 (OSA LOD=2.395, ΔLOD=2.36, P=0.006), which is close to HPC6. Using OSA allows us to find additional loci linked to HPC in subsets of families, and underlines the complex genetic heterogeneity of HPC even in highly aggregated families.

Deficiency of prolyl 3-hydroxylase 1, encoded by LEPRE1, causes recessive osteogenesis imperfecta (OI). We previously identified a LEPRE1 mutation exclusively in African Americans and contemporary West Africans. We hypothesized that this allele originated in West Africa and was introduced to the Americas with the Atlantic slave trade. We aimed to determine the frequency of carriers for this mutation among African Americans and West Africans, and the mutation origin and age.Genomic DNA was screened for the mutation using PCR and restriction digestion, and a custom TaqMan genomic single-nucleotide polymorphism assay. The mutation age was estimated using microsatellites and short tandem repeats spanning 4.2 Mb surrounding LEPRE1 in probands and carriers.Approximately 0.4% (95% confidence interval: 0.22-0.68%) of Mid-Atlantic African Americans carry this mutation, estimating recessive OI in 1/260,000 births in this population. In Nigeria and Ghana, 1.48% (95% confidence interval: 0.95-2.30%) of unrelated individuals are heterozygous carriers, predicting that 1/18,260 births will be affected with recessive OI, equal to the incidence of de novo dominant OI. The mutation was not detected in Africans from surrounding countries. All carriers shared a haplotype of 63-770 Kb, consistent with a single founder for this mutation. Using linkage disequilibrium analysis, the mutation was estimated to have originated between 650 and 900 years before present (1100-1350 CE).We identified a West African founder mutation for recessive OI in LEPRE1. Nearly 1.5% of Ghanians and Nigerians are carriers. The estimated age of this allele is consistent with introduction to North America via the Atlantic slave trade (1501-1867 CE).

Genome-wide linkage studies have been used to localize rare and highly penetrant prostate cancer (PRCA) susceptibility genes. Linkage studies performed in different ethnic backgrounds and populations have been somewhat disparate, resulting in multiple, often irreproducible signals because of genetic heterogeneity and high sporadic background of the disease. Our first genome-wide linkage study and subsequent fine-mapping study of Finnish hereditary prostate cancer (HPC) families gave evidence of linkage to one region. Here, we conducted subsequent scans with microsatellites and SNPs in a total of 69 Finnish HPC families. GENEHUNTER-PLUS was used for parametric and non-parametric analyses. Our microsatellite genome-wide linkage study provided evidence of linkage to 17q12-q23, with a heterogeneity LOD (HLOD) score of 3.14 in a total of 54 of the 69 families. Genome-wide SNP analysis of 59 of the 69 families gave a highest HLOD score of 3.40 at 2q37.3 under a dominant high penetrance model. Analyzing all 69 families by combining microsatellite and SNP maps also yielded HLOD scores of > 3.3 in two regions (2q37.3 and 17q12-q21.3). These significant linkage peaks on chromosome 2 and 17 confirm previous linkage evidence of a locus on 17q from other populations and provide a basis for continued research into genetic factors involved in PRCA. Fine-mapping analysis of these regions is ongoing and candidate genes at linked loci are currently under analysis.

Genetics Analysis Workshop 17 provided common and rare genetic variants from exome sequencing data and simulated binary and quantitative traits in 200 replicates. We provide a brief review of the machine learning and regression-based methods used in the analyses of these data. Several regression and machine learning methods were used to address different problems inherent in the analyses of these data, which are high-dimension, low-sample-size data typical of many genetic association studies. Unsupervised methods, such as cluster analysis, were used for data segmentation and, subset selection. Supervised learning methods, which include regression-based methods (e.g., generalized linear models, logic regression, and regularized regression) and tree-based methods (e.g., decision trees and random forests), were used for variable selection (selecting genetic and clinical features most associated or predictive of outcome) and prediction (developing models using common and rare genetic variants to accurately predict outcome), with the outcome being case-control status or quantitative trait value. We include a discussion of cross-validation for model selection and assessment, and a description of available software resources for these methods.

Background: Genetic factors play important roles in lung cancer susceptibility. In this study, we replicated the association of 5p15.33 and 6p21.33 with familial lung cancer. Taking into account the previously identified genetic susceptibility variants on 6q23-25/RGS17 and 15q24-25.1, we further determined the cumulative association of these four genetic regions and the population attributable risk percent of familial lung cancer they account for. Methods: One hundred ninety-four case patients and 219 cancer-free control subjects from the Genetic Epidemiology of Lung Cancer Consortium were used for the association analysis. Each familial case was chosen from one high-risk lung cancer family that has three or more affected members. Single nucleotide polymorphisms (SNP) on chromosomal regions 5p15.33, 6p21.33, 6q23-25/RGS17, and 15q24-25.1 were assessed for their associations with familial lung cancer. The cumulative association of the four chromosomal regions with familial lung cancer was evaluated with the use of a linear logistic model. Population attributable risk percent was calculated for each SNP using risk ratio. Results: SNP rs31489 showed the strongest evidence of familial lung cancer association on 5p15.33 (P = 2 × 10−4; odds ratio, 0.57; 95% confidence interval, 0.42-0.77), whereas rs3117582 showed a weak association on 6p21.33 (P = 0.09; odds ratio, 1.47; 95% confidence interval, 0.94-2.31). Analysis of a combination of SNPs from the four regions provided a stronger cumulative association with familial lung cancer (P = 6.70 × 10−6) than any individual SNPs. The risk of lung cancer was increased to 3- to 11-fold among those subjects who had at least one copy of risk allele at each region compared with subjects without any of the risk factors. These four genetic regions contribute to a total of 34.6% of familial lung cancer in smokers. Conclusions: The SNPs in four chromosomal regions have a cumulative and significant association with familial lung cancer and account for about one-third of the population attributable risk for familial lung cancer. Cancer Epidemiol Biomarkers Prev; 19(2); 517–24

Recent genome-wide association studies have linked the chromosome 15q24-25.1 locus to nicotine addiction and lung cancer susceptibility. To refine the 15q24-25.1 locus, we performed a haplotype-based association analysis of 194 familial lung cases and 219 cancer-free controls from the Genetic Epidemiology of Lung Cancer Consortium (GELCC) collection, and used proliferation and apoptosis analyses to determine which gene(s) in the 15q24-25.1 locus mediates effects on lung cancer cell growth in vitro. We identified two distinct subregions, hapL (P = 3.20 × 10−6) and hapN (P = 1.51 × 10−6), which were significantly associated with familial lung cancer. hapL encompasses IREB2, LOC123688, and PSMA4, and hapN encompasses the three nicotinic acetylcholine receptor subunit genes CHRNA5, CHRNA3, and CHRNB4. Examination of the genes around hapL revealed that PSMA4 plays a role in promoting cancer cell proliferation. PSMA4 mRNA levels were increased in lung tumors compared with normal lung tissues. Down-regulation of PSMA4 expression decreased proteasome activity and induced apoptosis. Proteasome dysfunction leads to many diseases including cancer, and drugs that inhibit proteasome activity show promise as a form of cancer treatment. Genes around hapN were also investigated, but did not show any direct effect on lung cancer cell proliferation. We concluded that PSMA4 is a strong candidate mediator of lung cancer cell growth, and may directly affect lung cancer susceptibility through its modulation of cell proliferation and apoptosis. [Cancer Res 2009;69(19):7844–50]