Variance-components and regression-based methods are frequently used to map quantitative trait loci. The normality of the trait values is usually assumed and violation of this assumption can have a detrimental effect on the power and type I error of such analyses. Various transformations can be used, but appropriate transformations usually require careful analysis of individual traits, which is not feasible for data sets with a large number of traits like those in Problem 1 of Genetic Analysis Workshop 15 (GAW15). A semiparametric variance-components method can estimate the transformation along with the model parameters, but existing methods are computationally intensive. In this paper, we propose the use of empirical normal quantile transformation to normalize the scaled rank of trait values using an inverse normal transformation. Despite its simplicity and potential loss of information, this transformation is shown, by extensive simulations, to have good control of power and type I error, even when compared with the semiparametric method. To investigate the impact of such a transformation on real data sets, we apply variance-components and variance-regression methods to the expression data of GAW15 and compare the results before and after transformation.

Although familial susceptibility to glioma is known, the genetic basis for this susceptibility remains unidentified in the majority of glioma-specific families. An alternative approach to identifying such genes is to examine cancer pedigrees, which include glioma as one of several cancer phenotypes, to determine whether common chromosomal modifications might account for the familial aggregation of glioma and other cancers. Germline rearrangements in 146 glioma families (from the Gliogene Consortium; http://www.gliogene.org/) were examined using multiplex ligation-dependent probe amplification. These families all had at least 2 verified glioma cases and a third reported or verified glioma case in the same family or 2 glioma cases in the family with at least one family member affected with melanoma, colon, or breast cancer.The genomic areas covering TP53, CDKN2A, MLH1, and MSH2 were selected because these genes have been previously reported to be associated with cancer pedigrees known to include glioma. We detected a single structural rearrangement, a deletion of exons 1-6 in MSH2, in the proband of one family with 3 cases with glioma and one relative with colon cancer. Large deletions and duplications are rare events in familial glioma cases, even in families with a strong family history of cancers that may be involved in known cancer syndromes.

Increasing rates of human papillomavirus (HPV)–driven oropharyngeal cancer (OPC) have largely offset declines in tobacco-associated head and neck squamous cell carcinoma (HNSCC) at non-OPC sites. Host immunity is an important modulator of HPV infection, persistence, and clearance, and also of immune evasion in both virally- and nonvirally-driven cancers. However, the association between collective known cancer-related immune gene variants and HNSCC susceptibility has not been fully characterized. Here, we conducted a genetic association study in the multiethnic Veterans Affairs Million Veteran Program cohort, evaluating 16,050 variants in 1,576 immune genes in 4,012 HNSCC cases (OPC = 1,823; non-OPC = 2,189) and 16,048 matched controls. Significant polymorphisms were further examined in a non-Hispanic white (NHW) validation cohort (OPC = 1,206; non-OPC = 955; controls = 4,507). For overall HNSCC susceptibility in NHWs, we discovered and validated a novel 9q31.1 SMC2 association and replicated the known 6p21.32 HLA-DQ-DR association. Six loci/genes for overall HNSCC susceptibility were selectively enriched in African-Americans (6p21.32 HLA-G, 9q21.33 GAS1, 11q12.2 CD6, 11q23.2 NCAM1/CD56, 17p13.1 CD68, 18q22.2 SOCS6); all 6 genes function in antigen-presenting regulation and T-cell activation. Two additional loci (10q26 DMBT1, 15q22.2 TPM1) were uncovered for non-OPC susceptibility, and three loci (11q24 CRTAM, 16q21 CDH5, 18q12.1 CDH2) were identified for HPV-positive OPC susceptibility. This study underscores the role of immune gene variants in modulating susceptibility for both HPV-driven and non-HPV-driven HNSCC. Additional large studies, particularly in racially diverse populations, are needed to further validate the associations and to help elucidate other potential immune factors and mechanisms that may underlie HNSCC risk. Significance: Several inherited variations in immune system genes are significantly associated with susceptibility to head and neck cancer, which could help improve personalized cancer risk estimates.

Genomic imprinting is a mechanism in which the expression of a gene copy depends upon the sex of the parent from which it was inherited. This mechanism is now well recognized in humans, and the deregulation of imprinted genes has been implicated in a number of diseases. In this study, we performed a genome-wide joint linkage and imprinting scan using two data sets provided by Genetic Analysis Workshop 15 (GAW15). The first data set was high-risk rheumatoid arthritis families collected by the North American Rheumatoid Arthritis Consortium. We used both model-based and model-free methods of joint linkage and imprinting analyses. Although a genome scan of rheumatoid arthritis families using GENEHUNTER-MODSCORE suggested regions that might be imprinted, further analyses using variance-components method failed to obtain significant signals of imprinting. The second data set was Problem 1 of GAW15, which included single-nucleotide polymorphism genotypes and gene expression data for Centre d'Etude du Polymorphisme Humain pedigrees. A previous genome-wide linkage scan identified loci that may be regulators of gene expression: our genome-wide joint linkage and imprinting scan using a variance-components approach found significant signals for linkage. Our linkage scan results suggest that imprinted genes are unlikely to be involved in susceptibility to rheumatoid arthritis. However, for expression level of TGFBR3 gene, we found a point-wise p-value of 0.03 for imprinting, but increase in the LOD score did not meet the required threshold to reliably identify imprinting as the correct mode of inheritance in genome-wide linkage scans.

Despite well-established negative health consequences of smokeless tobacco use (STU), the number and variety of alternative non-combustible tobacco products on the market have increased tremendously over the last 10 years, as has the market share of these products relative to cigarettes. While STU among non-Hispanic white youth has decreased over the last 10 years, the prevalence has remained constant among Hispanic youth. Here we examine demographic, psychosocial, and genetic risk associated with STU among Mexican heritage youth. Participants (50.5 % girls) reported on psychosocial risk factors in 2008–09 (n = 1,087, mean age = 14.3 years), and smokeless tobacco use in 2010–11 (mean age = 16.7 years). Participants provided a saliva sample that was genotyped for genes in the dopamine, serotonin and opioid pathways. Overall 62 (5.7 %) participants reported lifetime STU. We identified five single nucleotide polymorphisms that increased the risk for lifetime use. Specifically, rs2023902 on SERGEF (OR = 1.93; 95 % CI: 1.05-3.53), rs16941667 on ALDH2 (OR = 3.14; 95 % CI: 1.65-5.94), and rs17721739 on TPH1 (OR = 1.71; 95 % CI: 1.00-2.91) in the dopamine pathway, rs514912 on TRH-DE (OR = 1.84; 95 % CI: 1.25-2.71) in the serotonin pathway, and rs42451417 on the serotonin transporter gene, SLC6A4 (OR = 3.53; 95 % CI: 1.56-7.97). After controlling for genetic risk, being male (OR = 1.86; 95 % CI: 1.02-3.41), obesity status (OR = 2.22; 95 % CI: 1.21-4.09), and both higher levels of anxiety (OR = 1.04; 95 % CI: 1.01-1.08) and social disinhibition (OR = 1.26; 95 % CI: 1.07-1.48) were associated with increased use. High subjective social status (OR = 0.78; 95 % CI: 0.64-0.93) was protective against use, while higher parental education (OR = 2.01; 95 % CI: 1.03-3.93) was associated with increased use. These data suggest that use of genetic risk, along with psychosocial, demographic, and behavioral risk factors may increase our ability to identify youth at increased risk for STU, which in turn may improve our ability to effectively target prevention messages to Mexican heritage youth.

We are now well into the sequencing era of genetic analysis, and methods to investigate rare variants associated with disease remain in high demand. Currently, the more common rare variant analysis methods are burden tests and variance component tests. This report introduces a burden test known as the modified replication based sum statistic and evaluates its performance, and the performance of other common burden and variance component tests under the setting of a small sample size (103 total cases and controls) using the Genetic Analysis Workshop 18 simulated data with complete knowledge of the simulation model. Specifically we look at the variable threshold sum statistic, replication-based sum statistics, the C-alpha, and sequence kernel association test. Using minor allele frequency thresholds of less than 0.05, we find that the modified replication based sum statistic is competitive with all methods and that using 103 individuals leads to all methods being vastly underpowered. Much larger sample sizes are needed to confidently find truly associated genes.