Sanjay Shete

University of Texas MD Anderson Cancer Center, Houston, Texas, United States

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Publications (170)874.08 Total impact

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    ABSTRACT: Background Addictions to alcohol and tobacco, known risk factors for cancer, are complex heritable disorders. Addictive behaviors have a bidirectional relationship with pain. We hypothesize that the associations between alcohol, smoking, and opioid addiction observed in cancer patients have a genetic basis. Therefore, using bioinformatics tools, we explored the underlying genetic basis and identified new candidate genes and common biological pathways for smoking, alcohol, and opioid addiction. Results Literature search showed 56 genes associated with alcohol, smoking and opioid addiction. Using Core Analysis function in Ingenuity Pathway Analysis software, we found that ERK1/2 was strongly interconnected across all three addiction networks. Genes involved in immune signaling pathways were shown across all three networks. Connect function from IPA My Pathway toolbox showed that DRD2 is the gene common to both the list of genetic variations associated with all three addiction phenotypes and the components of the brain neuronal signaling network involved in substance addiction. The top canonical pathways associated with the 56 genes were: 1) calcium signaling, 2) GPCR signaling, 3) cAMP-mediated signaling, 4) GABA receptor signaling, and 5) G-alpha i signaling. Conlusions Cancer patients are often prescribed opioids for cancer pain thus increasing their risk for opioid abuse and addiction. Our findings provide candidate genes and biological pathways underlying addiction phenotypes, which may be future targets for treatment of addiction. Further study of the variations of the candidate genes could allow physicians to make more informed decisions when treating cancer pain with opioid analgesics. Electronic supplementary material The online version of this article (doi:10.1186/s12918-015-0167-x) contains supplementary material, which is available to authorized users.
    BMC Systems Biology 06/2015; 9(1). DOI:10.1186/s12918-015-0167-x · 2.85 Impact Factor
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    ABSTRACT: http://onlinelibrary.wiley.com/enhanced/doi/10.1002/bdra.23385/ Birth defects are a major cause of morbidity and mortality worldwide. There has been much progress in understanding the genetic basis of familial and syndromic forms of birth defects. However, the etiology of nonsydromic birth defects is not well-understood. Although there is still much work to be done, we have many of the tools needed to accomplish the task. Advances in next-generation sequencing have introduced a sea of possibilities, from disease-gene discovery to clinical screening and diagnosis. These advances have been fruitful in identifying a host of candidate disease genes, spanning the spectrum of birth defects. With the advent of CRISPR-Cas9 gene editing, researchers now have a precise tool for characterizing this genetic variation in model systems. Work in model organisms has also illustrated the importance of epigenetics in human development and birth defects etiology. Here we review past and current knowledge in birth defects genetics. We describe genotyping and sequencing methods for the detection and analysis of rare and common variants. We remark on the utility of model organisms and explore epigenetics in the context of structural malformation. We conclude by highlighting approaches that may provide insight into the complex genetics of birth defects.
    Birth Defects Research Part A Clinical and Molecular Teratology 05/2015; DOI:10.1002/bdra.23385 · 2.21 Impact Factor
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    ABSTRACT: Background and Objectives To assess tobacco use among lesbian, gay, bisexual, and transgender (LGBT) individuals from the 2014 Houston Pride Parade and Festival in Houston, Texas (TX).Methods Cross-sectional study using convenience sample of LGBT individuals (n = 99) examining tobacco use, sexual orientation, and other socio-demographic factors through survey participation.ResultsFindings showed a high prevalence of tobacco and electronic cigarettes use. White LGBT individuals had greater odds of using any type of tobacco product.Discussion and Conclusions Despite a high smoking prevalence among the surveyed LGBT individuals, this study sample did not identify tobacco use as a health issue.Scientific SignificanceSupports the need for further investigation on tobacco-related disparities among LGBT individuals in Houston, TX.
    American Journal on Addictions 05/2015; DOI:10.1111/ajad.12244 · 1.74 Impact Factor
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    Rajesh Talluri, Sanjay Shete
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    ABSTRACT: Epistasis helps to explain how multiple single-nucleotide polymorphisms (SNPs) interact to cause disease. A variety of tools have been developed to detect epistasis. In this article, we explore the strengths and weaknesses of an information theory approach for detecting epistasis and compare it to the logistic regression approach through simulations. We consider several scenarios to simulate the involvement of SNPs in an epistasis network with respect to linkage disequilibrium patterns among them and the presence or absence of main and interaction effects. We conclude that the information theory approach more efficiently detects interaction effects when main effects are absent, whereas, in general, the logistic regression approach is appropriate in all scenarios but results in higher false positives. We compute epistasis networks for SNPs in the FSD1L gene using a two-phase head and neck cancer genome-wide association study involving 2,185 cases and 4,507 controls to demonstrate the practical application of the methods.
    Cancer informatics 02/2015; 14(Suppl 2):17-23. DOI:10.4137/CIN.S17289
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    ABSTRACT: Glioma is a rare, but highly fatal, cancer that accounts for the majority of malignant primary brain tumors. Inherited predisposition to glioma has been consistently observed within non-syndromic families. Our previous studies, which involved non-parametric and parametric linkage analyses, both yielded significant linkage peaks on chromosome 17q. Here, we use data from next generation and Sanger sequencing to identify familial glioma candidate genes and variants on chromosome 17q for further investigation. We applied a filtering schema to narrow the original list of 4830 annotated variants down to 21 very rare (<0.1% frequency), non-synonymous variants. Our findings implicate the MYO19 and KIF18B genes and rare variants in SPAG9 and RUNDC1 as candidates worthy of further investigation. Burden testing and functional studies are planned.
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    ABSTRACT: Gliomas are the most common brain tumor, with several histological subtypes of various malignancy grade. The genetic contribution to familial glioma is not well understood. Using whole exome sequencing of 90 individuals from 55 families, we identified two families with mutations in POT1 (p.G95C, p.E450X), a member of the telomere shelterin complex, shared by both affected individuals in each family and predicted to impact DNA binding and TPP1 binding, respectively. Validation in a separate cohort of 264 individuals from 246 families identified an additional mutation in POT1 (p.D617Efs), also predicted to disrupt TPP1 binding. All families with POT1 mutations had affected members with oligodendroglioma, a specific subtype of glioma more sensitive to irradiation. These findings are important for understanding the origin of glioma and could have importance for the future diagnostics and treatment of glioma. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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    ABSTRACT: 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.
    BMC Medical Genetics 01/2015; 16(1):43. DOI:10.1186/s12881-015-0188-8 · 2.45 Impact Factor
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    ABSTRACT: The underlying ethos of dbGaP is that access to these data by secondary data analysts facilitates advancement of science. NIH has required that genome-wide association study data be deposited in the Database of Genotypes and Phenotypes (dbGaP) since 2003. In 2013, a proposed updated policy extended this requirement to next-generation sequencing data. However, recent literature and anecdotal reports suggest lingering logistical and ethical concerns about subject identifiability, informed consent, publication embargo enforcement, and difficulty in accessing dbGaP data. We surveyed the International Genetic Epidemiology Society (IGES) membership about their experiences. One hundred and seventy five (175) individuals completed the survey, a response rate of 27%. Of respondents who received data from dbGaP (43%), only 32% perceived the application process as easy but most (75%) received data within five months. Remaining challenges include difficulty in identifying an institutional signing official and an overlong application process. Only 24% of respondents had contributed data to dbGaP. Of these, 31% reported local IRB restrictions on data release; an additional 15% had to reconsent study participants before depositing data. The majority of respondents (56%) disagreed that the publication embargo period was sufficient. In response, we recommend longer embargo periods and use of varied data-sharing models rather than a one-size-fits-all approach.
    International Journal of Environmental Research and Public Health 08/2014; 11(8):8383-8398. DOI:10.3390/ijerph110808383 · 1.99 Impact Factor
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    ABSTRACT: Background: Smoking experimentation in Mexican American youth is problematic. In light of the research showing that preventing smoking experimentation is a valid strategy for smoking prevention, there is a need to identify Mexican American youth at high risk for experimentation. Methods: A prospective population-based cohort of 1179 adolescents of Mexican descent was followed for 5 years starting in 2005-06. Participants completed a baseline interview at a home visit followed by three telephone interviews at intervals of approximately 6 months and additional interviews at two home visits in 2008-09 and 2010-11. The primary end point of interest in this study was smoking experimentation. Information regarding social, cultural, and behavioral factors (e.g., acculturation, susceptibility to experimentation, home characteristics, household influences) was collected at baseline using validated questionnaires. Results: Age, sex, cognitive susceptibility, household smoking behavior, peer influence, neighborhood influence, acculturation, work characteristics, positive outcome expectations, family cohesion, degree of tension, ability to concentrate, and school discipline were found to be associated with smoking experimentation. In a validation dataset, the proposed risk prediction model had an AUC of 0.719 (95% confidence interval, 0.637 to 0.801) for predicting absolute risk for smoking experimentation within 1 year. Conclusions: The proposed risk prediction model is able to quantify the risk of smoking experimentation in Mexican American adolescents. Impact: Accurately identifying Mexican American adolescents who are at higher risk for smoking experimentation who can be intervened will substantially reduce the incidence of smoking and thereby subsequent health risks.
    Cancer Epidemiology Biomarkers & Prevention 07/2014; 23(10). DOI:10.1158/1055-9965.EPI-14-0467 · 4.32 Impact Factor
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    ABSTRACT: Survival outcomes in patients with squamous cell carcinoma of the head and neck (HNSCC) vary by extent of disease, behavioral, and socioeconomic factors. We assessed the extent to which pre-treatment pain influences survival in 2340 newly diagnosed patients with HNSCC, adjusting for disease stage, symptoms, pain medications, comorbidities, smoking, alcohol consumption, age, sex, and race/ethnicity. Patients rated their pain at presentation to the cancer center (0= 'no pain' and 10= 'pain as bad as you can imagine'). Survival time was calculated from the date of diagnosis to the date of death of any cause or last follow-up. Five year overall survival was calculated for all the variables assessed in the study. Severe pain (>7) was most prevalent among those with oral cancer (20.4%; pharynx=18.8%; larynx=16.1%) and significantly varied by tumor stage, fatigue severity, smoking status, comorbid lung disease, and race (all p<0.05) across cancer diagnoses. Overall 5 year survival varied by pain for oral (severe pain=31% versus non-severe=52%; p<0.001) and pharyngeal cancer (severe pain=33%, versus non-severe=53%; p<0.001). Multivariable analyses showed that pain persisted as an independent prognostic factor for survival. Pain reported prior to treatment should be considered in understanding survival outcomes in HNSCC patients.
    Journal of Pain 07/2014; 15(10). DOI:10.1016/j.jpain.2014.07.003 · 4.22 Impact Factor
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    ABSTRACT: Genome-wide association studies (GWAS) have mapped risk alleles for at least ten distinct cancers to a small region of 63,000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (ASSET) across six distinct cancers in 34,248 cases and 45,036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single nucleotide polymorphisms (SNPs): five in the TERT gene (region 1: rs7726159, P=2.10x10-39; region 3: rs2853677, P=3.30x10-36 and PConditional=2.36x10-8; region 4: rs2736098, P=3.87x10-12 and PConditional=5.19x10-6, region 5: rs13172201, P=0.041 and PConditional=2.04x10-6; and region 6: rs10069690, P=7.49x10-15 and PConditional=5.35x10-7) and one in the neighboring CLPTM1L gene (region 2: rs451360; P=1.90x10-18 and PConditional=7.06x10-16). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele specific effects on DNA methylation were seen for a subset of risk loci indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.
    Human Molecular Genetics 07/2014; DOI:10.1093/hmg/ddu363 · 6.68 Impact Factor
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    Jian Wang, Robert Yu, Sanjay Shete
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    ABSTRACT: X-chromosome inactivation (XCI) is the process in which one of the two copies of the X-chromosome in females is randomly inactivated to achieve the dosage compensation of X-linked genes between males and females. That is, 50% of the cells have one allele inactive and the other 50% of the cells have the other allele inactive. However, studies have shown that skewed or nonrandom XCI is a biological plausibility wherein more than 75% of cells have the same allele inactive. Also, some of the X-chromosome genes escape XCI, i.e., both alleles are active in all cells. Current statistical tests for X-chromosome association studies can either account for random XCI (e.g., Clayton's approach) or escape from XCI (e.g., PLINK software). Because the true XCI process is unknown and differs across different regions on the X-chromosome, we proposed a unified approach of maximizing likelihood ratio over all biological possibilities: random XCI, skewed XCI, and escape from XCI. A permutation-based procedure was developed to assess the significance of the approach. We conducted simulation studies to compare the performance of the proposed approach with Clayton's approach and PLINK regression. The results showed that the proposed approach has higher powers in the scenarios where XCI is skewed while losing some power in scenarios where XCI is random or XCI is escaped, with well-controlled type I errors. We also applied the approach to the X-chromosomal genetic association study of head and neck cancer.
    Genetic Epidemiology 07/2014; DOI:10.1002/gepi.21814 · 2.95 Impact Factor
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    ABSTRACT: IntroductionThe genetic heritability for sensation-seeking tendencies ranges from 40 to 60%. Sensation-seeking behaviors typically manifest during adolescence and are associated with alcohol and cigarette experimentation in adolescents. Social disinhibition is an aspect of sensation-seeking that is closely tied to cigarette and alcohol experimentation.Methods We examined the contribution of candidate genes to social disinhibition among 1132 Mexican origin youth in Houston, Texas, adjusting for established demographic and psychosocial risk factors. Saliva samples were obtained at baseline in 2005–06, and social disinhibition and other psychosocial data were obtained in 2008–09. Participants were genotyped for 672 functional and tagging SNPs potentially related to sensation-seeking, risk-taking, smoking, and alcohol use.ResultsSix SNPs were significantly associated with social disinhibition scores, after controlling for false discovery and adjusting for population stratification and relevant demographic/psychosocial characteristics. Minor alleles for three of the SNPs (rs1998220 on OPRM1; rs9534511 on HTR2A; and rs4938056 on HTR3B) were associated with increased risk of social disinhibition, while minor alleles for the other three SNPs (rs1003921 on KCNC1; rs16116 downstream of NPY; and rs16870286 on LINC00518) exhibited a protective effect. Age, linguistic acculturation, thrill and adventure-seeking, and drug and alcohol-seeking were all significantly positively associated with increased risk of social disinhibition in a multivariable model (P < 0.001).Conclusions These results add to our knowledge of genetic risk factors for social disinhibition. Additional research is needed to verify whether these SNPs are associated with social disinhibition among youth of different ethnicities and nationalities, and to elucidate whether and how these SNPs functionally contribute to social disinhibition.
    07/2014; 4(4). DOI:10.1002/brb3.236
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    Rajesh Talluri, Jian Wang, Sanjay Shete
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    ABSTRACT: Several methods have been proposed to account for multiple comparisons in genetic association studies. However, investigators typically test each of the SNPs using multiple genetic models. Association testing using the Cochran-Armitage test for trend assuming an additive, dominant, or recessive genetic model, is commonly performed. Thus, each SNP is tested three times. Some investigators report the smallest p-value obtained from the three tests corresponding to the three genetic models, but such an approach inherently leads to inflated type 1 errors. Because of the small number of tests (three) and high correlation (functional dependence) among these tests, the procedures available for accounting for multiple tests are either too conservative or fail to meet the underlying assumptions (e.g., asymptotic multivariate normality or independence among the tests).
    BMC Genetics 06/2014; 15(1):75. DOI:10.1186/1471-2156-15-75 · 2.36 Impact Factor
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    Jian Wang, Robert Yu, Sanjay Shete
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    ABSTRACT: Identifying genetic variants associated with complex diseases is an important task in genetic research. Although association studies based on unrelated individuals (ie, case-control genome-wide association studies) have successfully identified common single-nucleotide polymorphisms for many complex diseases, these studies are not so likely to identify rare genetic variants. In contrast, family-based association studies are particularly useful for identifying rare-variant associations. Recently, there has been some interest in employing multilevel models in family-based genetic association studies. However, the performance of such models in these studies, especially for longitudinal family-based sequence data, has not been fully investigated. Therefore, in this study, we investigated the performance of the multilevel model in the family-based genetic association analysis and compared it with the conventional family-based association test, by examining the powers and type I error rates of the 2 approaches using 3 data sets from the Genetic Analysis Workshop 18 simulated data: genome-wide association single-nucleotide polymorphism data, sequence data, and rare-variants-only data. Compared with the univariate family-based association test, the multilevel model had slightly higher power to identify most of the causal genetic variants using the genome-wide association single-nucleotide polymorphism data and sequence data. However, both approaches had low power to identify most of the causal single-nucleotide polymorphisms, especially those among the relatively rare genetic variants. Therefore, we suggest a unified method that combines both approaches and incorporates collapsing strategy, which may be more powerful than either approach alone for studying genetic associations using family-based data.
    BMC proceedings 06/2014; 8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo):S30. DOI:10.1186/1753-6561-8-S1-S30
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    ABSTRACT: 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.
    BMC proceedings 06/2014; 8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo):S13. DOI:10.1186/1753-6561-8-S1-S13
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    Rajesh Talluri, Sanjay Shete
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    ABSTRACT: Graphical models are increasingly used in genetic analyses to take into account the complex relationships between genetic and nongenetic factors influencing the phenotypes. We propose a model for determining the network structure of quantitative traits while accounting for the correlated nature of the family-based samples using the kinship coefficient. The Gaussian graphical model of age, systolic blood pressure, diastolic blood pressure, hypertension, blood pressure medication use, and smoking status was derived for three time points using real data. We also explored binary sparse graphical models of single-nucleotide polymorphisms (SNPs), covariates, and quantitative traits for exploratory analysis of the data. We validated the applicability of this method by producing a network graph using 20 causal variants, 21 noncausal variants, and 6 binary and quantitative phenotypes using the simulated data. To improve the model's ability to identify associations between the causal variants and the phenotypes, we intend to conduct follow-up studies investigating how to use the relationships between SNPs and between SNPs and phenotypes when analyzing genome wide association data with multiple phenotypes.
    BMC proceedings 06/2014; 8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo):S99. DOI:10.1186/1753-6561-8-S1-S99
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    ABSTRACT: The aim was to determine the proportions and correlates of essential hypertension among children in a tertiary pediatric hypertension clinic.
    American Journal of Hypertension 05/2014; DOI:10.1093/ajh/hpu083 · 3.40 Impact Factor
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    ABSTRACT: 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.
    Neuro-Oncology 04/2014; 16(10). DOI:10.1093/neuonc/nou052 · 5.29 Impact Factor
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    ABSTRACT: Birth defects are a leading cause of infant morbidity and mortality worldwide. The vast majority of birth defects are nonsyndromic, and although their etiologies remain mostly unknown, evidence supports the hypothesis that they result from the complex interaction of genetic, epigenetic, environmental, and lifestyle factors. Since our last review published in 2002 describing the basic tools of genetic epidemiology used to study nonsyndromic structural birth defects, many new approaches have become available and have been used with varying success. Through rapid advances in genomic technologies, investigators are now able to investigate large portions of the genome at a fraction of previous costs. With next-generation sequencing, research has progressed from assessing a small percentage of single-nucleotide polymorphisms to assessing the entire human protein-coding repertoire (exome)-an approach that is starting to uncover rare but informative mutations associated with nonsyndromic birth defects. Herein, we report on the current state of the genetic epidemiology of birth defects and comment on future challenges and opportunities. We consider issues of study design, and we discuss common variant approaches, including candidate gene studies and genome-wide association studies. We also discuss the complexities embedded in exploring interactions between genes and the environment. We complete our review by describing new and promising next-generation sequencing technologies and examining how the study of epigenetic mechanisms could become the key to unraveling the complex etiologies of nonsyndromic structural birth defects.
    02/2014; 168(4). DOI:10.1001/jamapediatrics.2013.4858

Publication Stats

6k Citations
874.08 Total Impact Points

Institutions

  • 2002–2015
    • University of Texas MD Anderson Cancer Center
      • • Department of Biostatistics
      • • Department of Epidemiology
      Houston, Texas, United States
  • 2012
    • Harvard Medical School
      • Department of Medicine
      Boston, Massachusetts, United States
  • 2010
    • Baylor College of Medicine
      • Department of Pediatrics
      Houston, Texas, United States
  • 2008
    • University of Texas Health Science Center at Houston
      • Department of Internal Medicine
      Houston, TX, United States
  • 2007–2008
    • University of Houston
      Houston, Texas, United States
    • Umeå University
      Umeå, Västerbotten, Sweden
  • 2005
    • The Ohio State University
      Columbus, Ohio, United States
    • Brigham and Women's Hospital
      Boston, Massachusetts, United States
  • 2000–2003
    • Case Western Reserve University
      • Rammelkamp Center for Education and Research
      Cleveland, Ohio, United States