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Anyimadu EA, Engelbart JM, Semprini J, Kahl A, Trentz C, Buatti JM, Casavant TL, Charlton ME, Canahuate G. Racial Disparities in Cancer Guideline-Concordant Treatment Using Surveillance, Epidemiology, and End Results Data for Patients With NSCLC. JTO Clin Res Rep 2025; 6:100747. [PMID: 39758596 PMCID: PMC11699381 DOI: 10.1016/j.jtocrr.2024.100747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 10/05/2024] [Accepted: 10/12/2024] [Indexed: 01/07/2025] Open
Abstract
Introduction Despite efforts to achieve health care equality, racial/ethnic disparities persist in lung cancer survival in the United States, with non-Hispanic Black patients experiencing higher mortality compared with non-Hispanic Whites. Previous research often focused on single treatments, overlooking the broad range of options available. We aimed to highlight disparities in survival and receipt of comprehensive lung cancer treatment by developing a guideline-concordant initial treatment (GCIT) indicator based on disease stage and recommended treatment. Methods Using data of the Surveillance, Epidemiology, and End Results on 377,370 patients with NSCLC, we derived a GCIT indicator based on National Comprehensive Cancer Network guidelines. Observed probabilities and logistic regression models adjusted for age, disease stage, and race were used to assess racial disparities in treatment and survival, with the Kaplan-Meier method evaluating survival rates. Racial/ethnic groups analyzed included non-Hispanic White, non-Hispanic Black, Asian/Pacific Islander, Hispanic, and American Indian/Alaska Native. Results Non-Hispanic Black patients had lower odds of receiving GCIT (OR = 0.80; 95% confidence interval [CI]: 0.78-0.82) and surviving 2 years after diagnosis (OR = 0.80; 95% CI: 0.78-0.82). Non-Hispanic Asians had the highest odds of receiving GCIT (OR = 1.02; 95% CI: 0.99-1.05). Patients receiving GCIT had improved survival, with early stage patients experiencing median survival of 67 to 102 months, compared with 11 to 17 months for those without GCIT. Conclusion Receiving GCIT considerably improves survival across all races, though disparities in receipt are observed. Interventions are needed to ensure equitable access to guideline-concordant care and reduce survival disparities for patients.
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Corrigan RA, Thiel AC, Lynn JR, Casavant TL, Ren P, Ponder JW, Schnieders MJ. A generalized Kirkwood implicit solvent for the polarizable AMOEBA protein model. J Chem Phys 2023; 159:054102. [PMID: 37526158 PMCID: PMC10396400 DOI: 10.1063/5.0158914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 07/17/2023] [Indexed: 08/02/2023] Open
Abstract
Computational simulation of biomolecules can provide important insights into protein design, protein-ligand binding interactions, and ab initio biomolecular folding, among other applications. Accurate treatment of the solvent environment is essential in such applications, but the use of explicit solvents can add considerable cost. Implicit treatment of solvent effects using a dielectric continuum model is an attractive alternative to explicit solvation since it is able to describe solvation effects without the inclusion of solvent degrees of freedom. Previously, we described the development and parameterization of implicit solvent models for small molecules. Here, we extend the parameterization of the generalized Kirkwood (GK) implicit solvent model for use with biomolecules described by the AMOEBA force field via the addition of corrections to the calculation of effective radii that account for interstitial spaces that arise within biomolecules. These include element-specific pairwise descreening scale factors, a short-range neck contribution to describe the solvent-excluded space between pairs of nearby atoms, and finally tanh-based rescaling of the overall descreening integral. We then apply the AMOEBA/GK implicit solvent to a set of ten proteins and achieve an average coordinate root mean square deviation for the experimental structures of 2.0 Å across 500 ns simulations. Overall, the continued development of implicit solvent models will help facilitate the simulation of biomolecules on mechanistically relevant timescales.
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Tollefson MR, Gogal RA, Weaver AM, Schaefer AM, Marini RJ, Azaiez H, Kolbe DL, Wang D, Weaver AE, Casavant TL, Braun TA, Smith RJH, Schnieders MJ. Assessing variants of uncertain significance implicated in hearing loss using a comprehensive deafness proteome. Hum Genet 2023; 142:819-834. [PMID: 37086329 PMCID: PMC10182131 DOI: 10.1007/s00439-023-02559-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 04/11/2023] [Indexed: 04/23/2023]
Abstract
Hearing loss is the leading sensory deficit, affecting ~ 5% of the population. It exhibits remarkable heterogeneity across 223 genes with 6328 pathogenic missense variants, making deafness-specific expertise a prerequisite for ascribing phenotypic consequences to genetic variants. Deafness-implicated variants are curated in the Deafness Variation Database (DVD) after classification by a genetic hearing loss expert panel and thorough informatics pipeline. However, seventy percent of the 128,167 missense variants in the DVD are "variants of uncertain significance" (VUS) due to insufficient evidence for classification. Here, we use the deep learning protein prediction algorithm, AlphaFold2, to curate structures for all DVD genes. We refine these structures with global optimization and the AMOEBA force field and use DDGun3D to predict folding free energy differences (∆∆GFold) for all DVD missense variants. We find that 5772 VUSs have a large, destabilizing ∆∆GFold that is consistent with pathogenic variants. When also filtered for CADD scores (> 25.7), we determine 3456 VUSs are likely pathogenic at a probability of 99.0%. Of the 224 genes in the DVD, 166 genes (74%) exhibit one or more missense variants predicted to cause a pathogenic change in protein folding stability. The VUSs prioritized here affect 119 patients (~ 3% of cases) sequenced by the OtoSCOPE targeted panel. Approximately half of these patients previously received an inconclusive report, and reclassification of these VUSs as pathogenic provides a new genetic diagnosis for six patients.
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Tollefson MR, Gogal RA, Weaver AM, Schaefer AM, Marini RJ, Azaiez H, Kolbe DL, Wang D, Weaver AE, Casavant TL, Braun TA, Smith RJH, Schnieders M. Assessing Variants of Uncertain Significance Implicated in Hearing Loss Using a Comprehensive Deafness Proteome. RESEARCH SQUARE 2023:rs.3.rs-2508462. [PMID: 36778238 PMCID: PMC9915777 DOI: 10.21203/rs.3.rs-2508462/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Hearing loss is the leading sensory deficit, affecting ~ 5% of the population. It exhibits remarkable heterogeneity across 223 genes with 6,328 pathogenic missense variants, making deafness-specific expertise a prerequisite for ascribing phenotypic consequences to genetic variants. Deafness-implicated variants are curated in the Deafness Variation Database (DVD) after classification by a genetic hearing loss expert panel and thorough informatics pipeline. However, seventy percent of the 128,167 missense variants in the DVD are "variants of uncertain significance" (VUS) due to insufficient evidence for classification. Here, we use the deep learning protein prediction algorithm, AlphaFold2, to curate structures for all DVD genes. We refine these structures with global optimization and the AMOEBA force field and use DDGun3D to predict folding free energy differences (∆∆G Fold ) for all DVD missense variants. We find that 5,772 VUSs have a large, destabilizing ∆∆G Fold that is consistent with pathogenic variants. When also filtered for CADD scores (> 25.7), we determine 3,456 VUSs are likely pathogenic at a probability of 99.0%. These VUSs affect 119 patients (~ 3% of cases) sequenced by the OtoSCOPE targeted panel. Approximately half of these patients previously received an inconclusive report, and reclassification of these VUSs as pathogenic provides a new genetic diagnosis for six patients.
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Thorpe RK, Walls WD, Corrigan R, Schaefer A, Wang K, Huygen P, Casavant TL, Smith RJH. AudioGene: refining the natural history of KCNQ4, GSDME, WFS1, and COCH-associated hearing loss. Hum Genet 2022; 141:877-887. [PMID: 35038006 PMCID: PMC9092196 DOI: 10.1007/s00439-021-02424-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 12/20/2021] [Indexed: 12/24/2022]
Abstract
Autosomal dominant non-syndromic hearing loss (ADNSHL) displays gene-specific progression of hearing loss, which is amenable to sequential audioprofiling. We sought to refine the natural history of ADNSHL by examining audiometric data in 5-year increments. 2175 audiograms were included from four genetic causes of ADNSHL-KCNQ4 (DFNA2), GSDME (DFNA5), WFS1 (DFNA6/14/38), and COCH (DFNA9). Annual threshold deterioration (ATD) was calculated for each gene: for the speech-frequency pure tone average, the ATD, respectively, was 0.72 dB/year, 0.94 dB/year, 0.53 dB/year, and 1.41 dB/year, with the largest drops occurring from ages 45-50 (0.89 dB/year; KCNQ4), 5-10 (1.42 dB/year; GSDME), 40-45 (0.83 dB/year; WFS1), and 50-55 (2.09 dB/year; COCH). 5-year interval analysis of audiograms reveals the gene specific natural history of KCNQ4, GSDME, WFS1 and COCH-related progressive hearing loss. Identifying ages at which hearing loss is most rapid informs clinical care and patient expectations. Natural history data are also essential to define outcomes of clinical trials that test novel therapies designed to correct or ameliorate these genetic forms of hearing loss.
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Corrigan RA, Qi G, Thiel AC, Lynn JR, Walker BD, Casavant TL, Lagardere L, Piquemal JP, Ponder JW, Ren P, Schnieders MJ. Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field. J Chem Theory Comput 2021; 17:2323-2341. [PMID: 33769814 DOI: 10.1021/acs.jctc.0c01286] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Computational protein design, ab initio protein/RNA folding, and protein-ligand screening can be too computationally demanding for explicit treatment of solvent. For these applications, implicit solvent offers a compelling alternative, which we describe here for the polarizable atomic multipole AMOEBA force field based on three treatments of continuum electrostatics: numerical solutions to the nonlinear and linearized versions of the Poisson-Boltzmann equation (PBE), the domain-decomposition conductor-like screening model (ddCOSMO) approximation to the PBE, and the analytic generalized Kirkwood (GK) approximation. The continuum electrostatics models are combined with a nonpolar estimator based on novel cavitation and dispersion terms. Electrostatic model parameters are numerically optimized using a least-squares style target function based on a library of 103 small-molecule solvation free energy differences. Mean signed errors for the adaptive Poisson-Boltzmann solver (APBS), ddCOSMO, and GK models are 0.05, 0.00, and 0.00 kcal/mol, respectively, while the mean unsigned errors are 0.70, 0.63, and 0.58 kcal/mol, respectively. Validation of the electrostatic response of the resulting implicit solvents, which are available in the Tinker (or Tinker-HP), OpenMM, and Force Field X software packages, is based on comparisons to explicit solvent simulations for a series of proteins and nucleic acids. Overall, the emergence of performative implicit solvent models for polarizable force fields opens the door to their use for folding and design applications.
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Walls WD, Moteki H, Thomas TR, Nishio SY, Yoshimura H, Iwasa Y, Frees KL, Nishimura CJ, Azaiez H, Booth KT, Marini RJ, Kolbe DL, Weaver AM, Schaefer AM, Wang K, Braun TA, Usami SI, Barr-Gillespie PG, Richardson GP, Smith RJ, Casavant TL. A comparative analysis of genetic hearing loss phenotypes in European/American and Japanese populations. Hum Genet 2020; 139:1315-1323. [PMID: 32382995 DOI: 10.1007/s00439-020-02174-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 04/29/2020] [Indexed: 01/04/2023]
Abstract
We present detailed comparative analyses to assess population-level differences in patterns of genetic deafness between European/American and Japanese cohorts with non-syndromic hearing loss. One thousand eighty-three audiometric test results (921 European/American and 162 Japanese) from members of 168 families (48 European/American and 120 Japanese) with non-syndromic hearing loss secondary to pathogenic variants in one of three genes (KCNQ4, TECTA, WFS1) were studied. Audioprofile characteristics, specific mutation types, and protein domains were considered in the comparative analyses. Our findings support differences in audioprofiles driven by both mutation type (non-truncating vs. truncating) and ethnic background. The former finding confirms data that ascribe a phenotypic consequence to different mutation types in KCNQ4; the latter finding suggests that there are ethnic-specific effects (genetic and/or environmental) that impact gene-specific audioprofiles for TECTA and WFS1. Identifying the drivers of ethnic differences will refine our understanding of phenotype-genotype relationships and the biology of hearing and deafness.
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Tollefson MR, Litman JM, Qi G, O'Connell CE, Wipfler MJ, Marini RJ, Bernabe HV, Tollefson WTA, Braun TA, Casavant TL, Smith RJH, Schnieders MJ. Structural Insights into Hearing Loss Genetics from Polarizable Protein Repacking. Biophys J 2019; 117:602-612. [PMID: 31327459 DOI: 10.1016/j.bpj.2019.06.030] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 06/10/2019] [Accepted: 06/25/2019] [Indexed: 12/21/2022] Open
Abstract
Hearing loss is associated with ∼8100 mutations in 152 genes, and within the coding regions of these genes are over 60,000 missense variants. The majority of these variants are classified as "variants of uncertain significance" to reflect our inability to ascribe a phenotypic effect to the observed amino acid change. A promising source of pathogenicity information is biophysical simulation, although input protein structures often contain defects because of limitations in experimental data and/or only distant homology to a template. Here, we combine the polarizable atomic multipole optimized energetics for biomolecular applications force field, many-body optimization theory, and graphical processing unit acceleration to repack all deafness-associated proteins and thereby improve average structure MolProbity score from 2.2 to 1.0. We then used these optimized wild-type models to create over 60,000 structures for missense variants in the Deafness Variation Database, which are being incorporated into the Deafness Variation Database to inform deafness pathogenicity prediction. Finally, this work demonstrates that advanced polarizable atomic multipole force fields are efficient enough to repack the entire human proteome.
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Rendleman MC, Buatti JM, Braun TA, Smith BJ, Nwakama C, Beichel RR, Brown B, Casavant TL. Machine learning with the TCGA-HNSC dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality. BMC Bioinformatics 2019; 20:339. [PMID: 31208324 PMCID: PMC6580485 DOI: 10.1186/s12859-019-2929-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2018] [Accepted: 06/04/2019] [Indexed: 12/15/2022] Open
Abstract
Background In the era of precision oncology and publicly available datasets, the amount of information available for each patient case has dramatically increased. From clinical variables and PET-CT radiomics measures to DNA-variant and RNA expression profiles, such a wide variety of data presents a multitude of challenges. Large clinical datasets are subject to sparsely and/or inconsistently populated fields. Corresponding sequencing profiles can suffer from the problem of high-dimensionality, where making useful inferences can be difficult without correspondingly large numbers of instances. In this paper we report a novel deployment of machine learning techniques to handle data sparsity and high dimensionality, while evaluating potential biomarkers in the form of unsupervised transformations of RNA data. We apply preprocessing, MICE imputation, and sparse principal component analysis (SPCA) to improve the usability of more than 500 patient cases from the TCGA-HNSC dataset for enhancing future oncological decision support for Head and Neck Squamous Cell Carcinoma (HNSCC). Results Imputation was shown to improve prognostic ability of sparse clinical treatment variables. SPCA transformation of RNA expression variables reduced runtime for RNA-based models, though changes to classifier performance were not significant. Gene ontology enrichment analysis of gene sets associated with individual sparse principal components (SPCs) are also reported, showing that both high- and low-importance SPCs were associated with cell death pathways, though the high-importance gene sets were found to be associated with a wider variety of cancer-related biological processes. Conclusions MICE imputation allowed us to impute missing values for clinically informative features, improving their overall importance for predicting two-year recurrence-free survival by incorporating variance from other clinical variables. Dimensionality reduction of RNA expression profiles via SPCA reduced both computation cost and model training/evaluation time without affecting classifier performance, allowing researchers to obtain experimental results much more quickly. SPCA simultaneously provided a convenient avenue for consideration of biological context via gene ontology enrichment analysis.
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Monson ET, de Klerk K, Gaynor SC, Wagner AH, Breen ME, Parsons M, Casavant TL, Zandi PP, Potash JB, Willour VL. Whole-gene sequencing investigation of SAT1 in attempted suicide. Am J Med Genet B Neuropsychiatr Genet 2016; 171:888-95. [PMID: 27229768 PMCID: PMC5814250 DOI: 10.1002/ajmg.b.32462] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Accepted: 05/11/2016] [Indexed: 11/10/2022]
Abstract
Suicidal behavior imposes a tremendous cost, with current US estimates reporting approximately 1.3 million suicide attempts and more than 40,000 suicide deaths each year. Several recent research efforts have identified an association between suicidal behavior and the expression level of the spermidine/spermine N1-acetyltransferase 1 (SAT1) gene. To date, several SAT1 genetic variants have been inconsistently associated with altered gene expression and/or directly with suicidal behavior. To clarify the role SAT1 genetic variation plays in suicidal behavior risk, we present a whole-gene sequencing effort of SAT1 in 476 bipolar disorder subjects with a history of suicide attempt and 473 subjects with bipolar disorder but no suicide attempts. Agilent SureSelect target enrichment was used to sequence all exons, introns, promoter regions, and putative regulatory regions identified from the ENCODE project within 10 kb of SAT1. Individual variant, haplotype, and collapsing variant tests were performed. Our results identified no variant or assessed region of SAT1 that showed a significant association with attempted suicide, nor did any assessment show evidence for replication of previously reported associations. Overall, no evidence for SAT1 sequence variation contributing to the risk for attempted suicide could be identified. It is possible that past associations of SAT1 expression with suicidal behavior arise from variation not captured in this study, or that causal variants in the region are too rare to be detected within our sample. Larger sample sizes and broader sequencing efforts will likely be required to identify the source of SAT1 expression level associations with suicidal behavior. © 2016 Wiley Periodicals, Inc.
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Taylor KR, Booth KT, Azaiez H, Sloan CM, Kolbe DL, Glanz EN, Shearer AE, DeLuca AP, Anand VN, Hildebrand MS, Simpson AC, Eppsteiner RW, Scheetz TE, Braun TA, Huygen PLM, Smith RJH, Casavant TL. Audioprofile Surfaces: The 21st Century Audiogram. Ann Otol Rhinol Laryngol 2015; 125:361-8. [PMID: 26530094 DOI: 10.1177/0003489415614863] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
OBJECTIVE To present audiometric data in 3 dimensions by considering age as an addition dimension. METHODS Audioprofile surfaces (APSs) were fitted to a set of audiograms by plotting each measurement of an audiogram as an independent point in 3 dimensions with the x, y, and z axes representing frequency, hearing loss in dB, and age, respectively. RESULTS Using the Java-based APS viewer as a standalone application, APSs were pre-computed for 34 loci. By selecting APSs for the appropriate genetic locus, a clinician can compare this APS-generated average surface to a specific patient's audiogram. CONCLUSION Audioprofile surfaces provide an easily interpreted visual representation of a person's hearing acuity relative to others with the same genetic cause of hearing loss. Audioprofile surfaces will support the generation and testing of sophisticated hypotheses to further refine our understanding of the biology of hearing.
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Ephraim SS, Anand N, DeLuca AP, Taylor KR, Kolbe DL, Simpson AC, Azaiez H, Sloan CM, Shearer AE, Hallier AR, Casavant TL, Scheetz TE, Smith RJH, Braun TA. Cordova: web-based management of genetic variation data. Bioinformatics 2014; 30:3438-9. [PMID: 25123904 DOI: 10.1093/bioinformatics/btu539] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
UNLABELLED Cordova is an out-of-the-box solution for building and maintaining an online database of genetic variations integrated with pathogenicity prediction results from popular algorithms. Our primary motivation for developing this system is to aid researchers and clinician-scientists in determining the clinical significance of genetic variations. To achieve this goal, Cordova provides an interface to review and manually or computationally curate genetic variation data as well as share it for clinical diagnostics and the advancement of research. AVAILABILITY AND IMPLEMENTATION Cordova is open source under the MIT license and is freely available for download at https://github.com/clcg/cordova.
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Shearer AE, Black-Ziegelbein EA, Hildebrand MS, Eppsteiner RW, Ravi H, Joshi S, Guiffre AC, Sloan CM, Happe S, Howard SD, Novak B, Deluca AP, Taylor KR, Scheetz TE, Braun TA, Casavant TL, Kimberling WJ, Leproust EM, Smith RJH. Advancing genetic testing for deafness with genomic technology. J Med Genet 2013; 50:627-34. [PMID: 23804846 DOI: 10.1136/jmedgenet-2013-101749] [Citation(s) in RCA: 91] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BACKGROUND Non-syndromic hearing loss (NSHL) is the most common sensory impairment in humans. Until recently its extreme genetic heterogeneity precluded comprehensive genetic testing. Using a platform that couples targeted genomic enrichment (TGE) and massively parallel sequencing (MPS) to sequence all exons of all genes implicated in NSHL, we tested 100 persons with presumed genetic NSHL and in so doing established sequencing requirements for maximum sensitivity and defined MPS quality score metrics that obviate Sanger validation of variants. METHODS We examined DNA from 100 sequentially collected probands with presumed genetic NSHL without exclusions due to inheritance, previous genetic testing, or type of hearing loss. We performed TGE using post-capture multiplexing in variable pool sizes followed by Illumina sequencing. We developed a local Galaxy installation on a high performance computing cluster for bioinformatics analysis. RESULTS To obtain maximum variant sensitivity with this platform 3.2-6.3 million total mapped sequencing reads per sample were required. Quality score analysis showed that Sanger validation was not required for 95% of variants. Our overall diagnostic rate was 42%, but this varied by clinical features from 0% for persons with asymmetric hearing loss to 56% for persons with bilateral autosomal recessive NSHL. CONCLUSIONS These findings will direct the use of TGE and MPS strategies for genetic diagnosis for NSHL. Our diagnostic rate highlights the need for further research on genetic deafness focused on novel gene identification and an improved understanding of the role of non-exonic mutations. The unsolved families we have identified provide a valuable resource to address these areas.
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Wagner AH, Taylor KR, DeLuca AP, Casavant TL, Mullins RF, Stone EM, Scheetz TE, Braun TA. Prioritization of retinal disease genes: an integrative approach. Hum Mutat 2013; 34:853-9. [PMID: 23508994 DOI: 10.1002/humu.22317] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2012] [Accepted: 03/07/2013] [Indexed: 02/03/2023]
Abstract
The discovery of novel disease-associated variations in genes is often a daunting task in highly heterogeneous disease classes. We seek a generalizable algorithm that integrates multiple publicly available genomic data sources in a machine-learning model for the prioritization of candidates identified in patients with retinal disease. To approach this problem, we generate a set of feature vectors from publicly available microarray, RNA-seq, and ChIP-seq datasets of biological relevance to retinal disease, to observe patterns in gene expression specificity among tissues of the body and the eye, in addition to photoreceptor-specific signals by the CRX transcription factor. Using these features, we describe a novel algorithm, positive and unlabeled learning for prioritization (PULP). This article compares several popular supervised learning techniques as the regression function for PULP. The results demonstrate a highly significant enrichment for previously characterized disease genes using a logistic regression method. Finally, a comparison of PULP with the popular gene prioritization tool ENDEAVOUR shows superior prioritization of retinal disease genes from previous studies. The java source code, compiled binary, assembled feature vectors, and instructions are available online at https://github.com/ahwagner/PULP.
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Nannapaneni K, Ben-Shahar Y, Keen HL, Welsh MJ, Casavant TL, Scheetz TE. Computational identification of operon-like transcriptional loci in eukaryotes. Comput Biol Med 2013; 43:738-43. [PMID: 23668349 DOI: 10.1016/j.compbiomed.2013.03.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2011] [Revised: 12/12/2012] [Accepted: 03/15/2013] [Indexed: 01/20/2023]
Abstract
Operons are primarily a bacterial phenomenon, not commonly observed in eukaryotes. However, new research indicates that operons are found in higher organisms as well. There are instances of operons found in C. elegans, Drosophila melanogaster and other eukaryotic species. We developed a prototype using positional, structural and gene expression information to identify candidate operons. We focused our efforts on "trans-spliced" operons in which the pre-mRNA is trans-spliced into individual transcripts and subsequently translated, as widely observed in C. elegans and some instances in Drosophila. We identify several candidate operons in Drosophila melanogaster of which two have been subsequently molecularly validated.
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Wagner AH, Anand VN, Wang WH, Chatterton JE, Sun D, Shepard AR, Jacobson N, Pang IH, Deluca AP, Casavant TL, Scheetz TE, Mullins RF, Braun TA, Clark AF. Exon-level expression profiling of ocular tissues. Exp Eye Res 2013; 111:105-11. [PMID: 23500522 DOI: 10.1016/j.exer.2013.03.004] [Citation(s) in RCA: 84] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2012] [Revised: 02/06/2013] [Accepted: 03/05/2013] [Indexed: 11/25/2022]
Abstract
The normal gene expression profiles of the tissues in the eye are a valuable resource for considering genes likely to be involved with disease processes. We profiled gene expression in ten ocular tissues from human donor eyes using Affymetrix Human Exon 1.0 ST arrays. Ten different tissues were obtained from six different individuals and RNA was pooled. The tissues included: retina, optic nerve head (ONH), optic nerve (ON), ciliary body (CB), trabecular meshwork (TM), sclera, lens, cornea, choroid/retinal pigment epithelium (RPE) and iris. Expression values were compared with publically available Expressed Sequence Tag (EST) and RNA-sequencing resources. Known tissue-specific genes were examined and they demonstrated correspondence of expression with the representative ocular tissues. The estimated gene and exon level abundances are available online at the Ocular Tissue Database.
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Scheetz TE, Fingert JH, Wang K, Kuehn MH, Knudtson KL, Alward WLM, Boldt HC, Russell SR, Folk JC, Casavant TL, Braun TA, Clark AF, Stone EM, Sheffield VC. A genome-wide association study for primary open angle glaucoma and macular degeneration reveals novel Loci. PLoS One 2013; 8:e58657. [PMID: 23536807 PMCID: PMC3594156 DOI: 10.1371/journal.pone.0058657] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2012] [Accepted: 02/07/2013] [Indexed: 11/22/2022] Open
Abstract
Glaucoma and age-related macular degeneration (AMD) are the two leading causes of visual loss in the United States. We utilized a novel study design to perform a genome-wide association for both primary open angle glaucoma (POAG) and AMD. This study design utilized a two-stage process for hypothesis generation and validation, in which each disease cohort was utilized as a control for the other. A total of 400 POAG patients and 400 AMD patients were ascertained and genotyped at 500,000 loci. This study identified a novel association of complement component 7 (C7) to POAG. Additionally, an association of central corneal thickness, a known risk factor for POAG, was found to be associated with ribophorin II (RPN2). Linked monogenic loci for POAG and AMD were also evaluated for evidence of association, none of which were found to be significantly associated. However, several yielded putative associations requiring validation. Our data suggest that POAG is more genetically complex than AMD, with no common risk alleles of large effect.
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Taylor KR, Deluca AP, Shearer AE, Hildebrand MS, Black-Ziegelbein EA, Anand VN, Sloan CM, Eppsteiner RW, Scheetz TE, Huygen PLM, Smith RJH, Braun TA, Casavant TL. AudioGene: predicting hearing loss genotypes from phenotypes to guide genetic screening. Hum Mutat 2013; 34:539-45. [PMID: 23280582 DOI: 10.1002/humu.22268] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2012] [Accepted: 12/18/2012] [Indexed: 12/31/2022]
Abstract
Autosomal dominant nonsyndromic hearing loss (ADNSHL) is a common and often progressive sensory deficit. ADNSHL displays a high degree of genetic heterogeneity and varying rates of progression. Accurate, comprehensive, and cost-effective genetic testing facilitates genetic counseling and provides valuable prognostic information to affected individuals. In this article, we describe the algorithm underlying AudioGene, a software system employing machine-learning techniques that utilizes phenotypic information derived from audiograms to predict the genetic cause of hearing loss in persons segregating ADNSHL. Our data show that AudioGene has an accuracy of 68% in predicting the causative gene within its top three predictions, as compared with 44% for a majority classifier. We also show that AudioGene remains effective for audiograms with high levels of clinical measurement noise. We identify audiometric outliers for each genetic locus and hypothesize that outliers may reflect modifying genetic effects. As personalized genomic medicine becomes more common, AudioGene will be increasingly useful as a phenotypic filter to assess pathogenicity of variants identified by massively parallel sequencing.
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Levy MA, Freymann JB, Kirby JS, Fedorov A, Fennessy FM, Eschrich SA, Berglund AE, Fenstermacher DA, Tan Y, Guo X, Casavant TL, Brown BJ, Braun TA, Dekker A, Roelofs E, Mountz JM, Boada F, Laymon C, Oborski M, Rubin DL. Informatics methods to enable sharing of quantitative imaging research data. Magn Reson Imaging 2012; 30:1249-56. [PMID: 22770688 PMCID: PMC3466343 DOI: 10.1016/j.mri.2012.04.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2012] [Revised: 04/16/2012] [Accepted: 04/18/2012] [Indexed: 10/28/2022]
Abstract
INTRODUCTION The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community. METHODS We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN. RESULTS There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network. CONCLUSIONS As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers.
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Eppsteiner RW, Shearer AE, Hildebrand MS, Deluca AP, Ji H, Dunn CC, Black-Ziegelbein EA, Casavant TL, Braun TA, Scheetz TE, Scherer SE, Hansen MR, Gantz BJ, Smith RJH. Prediction of cochlear implant performance by genetic mutation: the spiral ganglion hypothesis. Hear Res 2012; 292:51-8. [PMID: 22975204 DOI: 10.1016/j.heares.2012.08.007] [Citation(s) in RCA: 95] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2012] [Revised: 08/16/2012] [Accepted: 08/20/2012] [Indexed: 11/29/2022]
Abstract
BACKGROUND Up to 7% of patients with severe-to-profound deafness do not benefit from cochlear implantation. Given the high surgical implantation and clinical management cost of cochlear implantation (>$1 million lifetime cost), prospective identification of the worst performers would reduce unnecessary procedures and healthcare costs. Because cochlear implants bypass the membranous labyrinth but rely on the spiral ganglion for functionality, we hypothesize that cochlear implant (CI) performance is dictated in part by the anatomic location of the cochlear pathology that underlies the hearing loss. As a corollary, we hypothesize that because genetic testing can identify sites of cochlear pathology, it may be useful in predicting CI performance. METHODS 29 adult CI recipients with idiopathic adult-onset severe-to-profound hearing loss were studied. DNA samples were subjected to solution-based sequence capture and massively parallel sequencing using the OtoSCOPE(®) platform. The cohort was divided into three CI performance groups (good, intermediate, poor) and genetic causes of deafness were correlated with audiometric data to determine whether there was a gene-specific impact on CI performance. RESULTS The genetic cause of deafness was determined in 3/29 (10%) individuals. The two poor performers segregated mutations in TMPRSS3, a gene expressed in the spiral ganglion, while the good performer segregated mutations in LOXHD1, a gene expressed in the membranous labyrinth. Comprehensive literature review identified other good performers with mutations in membranous labyrinth-expressed genes; poor performance was associated with spiral ganglion-expressed genes. CONCLUSIONS Our data support the underlying hypothesis that mutations in genes preferentially expressed in the spiral ganglion portend poor CI performance while mutations in genes expressed in the membranous labyrinth portend good CI performance. Although the low mutation rate in known deafness genes in this cohort likely relates to the ascertainment characteristics (postlingual hearing loss in adult CI recipients), these data suggest that genetic testing should be implemented as part of the CI evaluation to test this association prospectively.
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Eppsteiner RW, Shearer AE, Hildebrand MS, Taylor KR, Deluca AP, Scherer S, Huygen P, Scheetz TE, Braun TA, Casavant TL, Smith RJH. Using the phenome and genome to improve genetic diagnosis for deafness. Otolaryngol Head Neck Surg 2012; 147:975-7. [PMID: 22785243 DOI: 10.1177/0194599812454271] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
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Morcuende JA, Stevens JW, Scheetz TE, de Fatima Bonaldoc M, Casavant TL, Otero JE, Soares MB. Swarm rat chondrosarcoma cells as an in vivo model: lung colonization and effects of tissue environment on tumor growth. THE IOWA ORTHOPAEDIC JOURNAL 2012; 32:46-53. [PMID: 23576921 PMCID: PMC3565414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Swarm rat chondrosarcoma cells have been used extensively for biochemical studies of extra-cellular matrix metabolism in cartilage. However, these cells also possess tumor-like behavior in vivo and are useful in investigation of chondrosarcoma biology. the current study was designed to develop a metastatic model using swarm rat chondrosarcoma cells, and to assess the effect of tissue-environment on tumor behavior in vivo. Tumors were implanted subcutaneously or into bone, and animals were assessed radiographically and microscopically for tumor growth and metastasis. The subcutaneous tumor grew to an average mass of 35 g, while tumor implanted into bone grew 75 mg. Transplantation of the cells into the bone led to extensive bone remodeling with invasion of the medullary cavity and destruction of the bone cortex. Light microscopy demonstrated no significant differences in the number of mitoses, cellular atypia or extracellular matrix staining between the two sites of tumor implantation. Interestingly, lung colonization was observed in none of the animals in the subcutaneous tumor injection group, while tumors colonized the lungs in 95% of the rats with tumor injected into bone. Analysis of cDNA libraries from subcutaneous and bone-transplanted tumors demonstrated a complex and diverse array of expressed transcripts, and there were significant differences in gene expression between tumors at different sites. The results of this study suggest swarm rat chondrosarcoma is a model that resembles human chondrosarcoma mimicking its ability to infiltrate and remodel local bone and to colonize the lungs. Furthermore, the interaction between host-tissue and tumor cells plays a major role in the tumor behavior in this model. Identifying these interactions will lead to further understanding of chondrosarcoma and contribute to therapeutic targets in the future.
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Hildebrand MS, Morín M, Meyer NC, Mayo F, Modamio-Hoybjor S, Mencía A, Olavarrieta L, Morales-Angulo C, Nishimura CJ, Workman H, DeLuca AP, del Castillo I, Taylor KR, Tompkins B, Goodman CW, Schrauwen I, Wesemael MV, Lachlan K, Shearer AE, Braun TA, Huygen PLM, Kremer H, Van Camp G, Moreno F, Casavant TL, Smith RJH, Moreno-Pelayo MA. DFNA8/12 caused by TECTA mutations is the most identified subtype of nonsyndromic autosomal dominant hearing loss. Hum Mutat 2011; 32:825-34. [PMID: 21520338 DOI: 10.1002/humu.21512] [Citation(s) in RCA: 65] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2011] [Accepted: 03/31/2011] [Indexed: 12/13/2022]
Abstract
The prevalence of DFNA8/DFNA12 (DFNA8/12), a type of autosomal dominant nonsyndromic hearing loss (ADNSHL), is unknown as comprehensive population-based genetic screening has not been conducted. We therefore completed unbiased screening for TECTA mutations in a Spanish cohort of 372 probands from ADNSHL families. Three additional families (Spanish, Belgian, and English) known to be linked to DFNA8/12 were also included in the screening. In an additional cohort of 835 American ADNSHL families, we preselected 73 probands for TECTA screening based on audiometric data. In aggregate, we identified 23 TECTA mutations in this process. Remarkably, 20 of these mutations are novel, more than doubling the number of reported TECTA ADNSHL mutations from 13 to 33. Mutations lie in all domains of the α-tectorin protein, including those for the first time identified in the entactin domain, as well as the vWFD1, vWFD2, and vWFD3 repeats, and the D1-D2 and TIL2 connectors. Although the majority are private mutations, four of them-p.Cys1036Tyr, p.Cys1837Gly, p.Thr1866Met, and p.Arg1890Cys-were observed in more than one unrelated family. For two of these mutations founder effects were also confirmed. Our data validate previously observed genotype-phenotype correlations in DFNA8/12 and introduce new correlations. Specifically, mutations in the N-terminal region of α-tectorin (entactin domain, vWFD1, and vWFD2) lead to mid-frequency NSHL, a phenotype previously associated only with mutations in the ZP domain. Collectively, our results indicate that DFNA8/12 hearing loss is a frequent type of ADNSHL.
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Bayouth JE, Casavant TL, Graham MM, Sonka M, Muruganandham M, Buatti JM. Image-based biomarkers in clinical practice. Semin Radiat Oncol 2011; 21:157-66. [PMID: 21356483 PMCID: PMC4270476 DOI: 10.1016/j.semradonc.2010.11.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The growth of functional and metabolically informative imaging is eclipsing anatomic imaging alone in clinical practice. The recognition that magnetic resonance (MR) and positron emission tomography (PET)-based treatment planning and response assessment are essential components of clinical practice and furthermore offer the potential of quantitative analysis being important. Extracting the greatest benefit from these imaging techniques will require refining the best combinations of multimodality imaging through well-designed clinical trials that use robust image-analysis tools and require substantial computer based infrastructure. Through these changes and enhancements, image-based biomarkers will enhance clinical decision making and accelerate the progress that is made through clinical trial research.
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Hamm CA, Stevens JW, Xie H, Vanin EF, Morcuende JA, Abdulkawy H, Seftor EA, Sredni ST, Bischof JM, Wang D, Malchenko S, Bonaldo MDF, Casavant TL, Hendrix MJC, Soares MB. Microenvironment alters epigenetic and gene expression profiles in Swarm rat chondrosarcoma tumors. BMC Cancer 2010; 10:471. [PMID: 20809981 PMCID: PMC2944175 DOI: 10.1186/1471-2407-10-471] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2010] [Accepted: 09/01/2010] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Chondrosarcomas are malignant cartilage tumors that do not respond to traditional chemotherapy or radiation. The 5-year survival rate of histologic grade III chondrosarcoma is less than 30%. An animal model of chondrosarcoma has been established--namely, the Swarm Rat Chondrosarcoma (SRC)--and shown to resemble the human disease. Previous studies with this model revealed that tumor microenvironment could significantly influence chondrosarcoma malignancy. METHODS To examine the effect of the microenvironment, SRC tumors were initiated at different transplantation sites. Pyrosequencing assays were utilized to assess the DNA methylation of the tumors, and SAGE libraries were constructed and sequenced to determine the gene expression profiles of the tumors. Based on the gene expression analysis, subsequent functional assays were designed to determine the relevancy of the specific genes in the development and progression of the SRC. RESULTS The site of transplantation had a significant impact on the epigenetic and gene expression profiles of SRC tumors. Our analyses revealed that SRC tumors were hypomethylated compared to control tissue, and that tumors at each transplantation site had a unique expression profile. Subsequent functional analysis of differentially expressed genes, albeit preliminary, provided some insight into the role that thymosin-β4, c-fos, and CTGF may play in chondrosarcoma development and progression. CONCLUSION This report describes the first global molecular characterization of the SRC model, and it demonstrates that the tumor microenvironment can induce epigenetic alterations and changes in gene expression in the SRC tumors. We documented changes in gene expression that accompany changes in tumor phenotype, and these gene expression changes provide insight into the pathways that may play a role in the development and progression of chondrosarcoma. Furthermore, specific functional analysis indicates that thymosin-β4 may have a role in chondrosarcoma metastasis.
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