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Hearing Disorders: HELP
Articles by Swati Joshi
Based on 3 articles published since 2010
(Why 3 articles?)

Between 2010 and 2020, Swati Joshi wrote the following 3 articles about Hearing Disorders.
+ Citations + Abstracts
1 Article Utilizing ethnic-specific differences in minor allele frequency to recategorize reported pathogenic deafness variants. 2014

Shearer, A Eliot / Eppsteiner, Robert W / Booth, Kevin T / Ephraim, Sean S / Gurrola, José / Simpson, Allen / Black-Ziegelbein, E Ann / Joshi, Swati / Ravi, Harini / Giuffre, Angelica C / Happe, Scott / Hildebrand, Michael S / Azaiez, Hela / Bayazit, Yildirim A / Erdal, Mehmet Emin / Lopez-Escamez, Jose A / Gazquez, Irene / Tamayo, Marta L / Gelvez, Nancy Y / Leal, Greizy Lopez / Jalas, Chaim / Ekstein, Josef / Yang, Tao / Usami, Shin-ichi / Kahrizi, Kimia / Bazazzadegan, Niloofar / Najmabadi, Hossein / Scheetz, Todd E / Braun, Terry A / Casavant, Thomas L / LeProust, Emily M / Smith, Richard J H. ·Molecular Otolaryngology & Renal Research Labs, Department of Otolaryngology-Head and Neck Surgery, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA. · Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA. · Agilent Technologies, Cedar Creek, TX 78612, USA. · Epilepsy Research Centre, Department of Medicine, University of Melbourne, Heidelberg, VIC 3084, Australia. · Department of Otolaryngology, Faculty of Medicine, Medipol University, Istanbul 34083, Turkey. · Department of Medical Biology and Genetics, University of Mersin, Mersin 33160, Turkey. · Otology and Neurotology Group CTS495, Center for Genomic and Oncological Research (GENyO), Granada 18012, Spain. · Instituto de Genética Humana, Pontificia Universidad Javeriana, Bogotá 11001000, Colombia. · Bonei Olam, Center for Rare Jewish Genetic Disorders, Brooklyn, NY 11204, USA. · Dor Yeshorim, The Committee for Prevention of Jewish Genetic Diseases, Brooklyn, NY 11211, USA. · Department of Otorhinolaryngology-Head and Neck Surgery, Xinhua Hospital, and the Ear Institute, Shanghai Jiaotong University School of Medicine, Shanghai 20025, China. · Department of Otorhinolaryngology, School of Medicine, Shinshu University, Matsumoto, Nagano 390-8621, Japan. · Genetics Research Centre, University of Social Welfare and Rehabilitation Sciences, Tehran 1985713834, Iran. · Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA; Center for Bioinformatics and Computational Biology, University of Iowa, Iowa City, IA 52242, USA; Department of Ophthalmology and Visual Sciences, University of Iowa, Iowa City, IA 52242, USA. · Molecular Otolaryngology & Renal Research Labs, Department of Otolaryngology-Head and Neck Surgery, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Interdepartmental PhD Program in Genetics, University of Iowa, Iowa City, IA 52242, USA; Department of Molecular Physiology & Biophysics, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA. Electronic address: richard-smith@uiowa.edu. ·Am J Hum Genet · Pubmed #25262649.

ABSTRACT: Ethnic-specific differences in minor allele frequency impact variant categorization for genetic screening of nonsyndromic hearing loss (NSHL) and other genetic disorders. We sought to evaluate all previously reported pathogenic NSHL variants in the context of a large number of controls from ethnically distinct populations sequenced with orthogonal massively parallel sequencing methods. We used HGMD, ClinVar, and dbSNP to generate a comprehensive list of reported pathogenic NSHL variants and re-evaluated these variants in the context of 8,595 individuals from 12 populations and 6 ethnically distinct major human evolutionary phylogenetic groups from three sources (Exome Variant Server, 1000 Genomes project, and a control set of individuals created for this study, the OtoDB). Of the 2,197 reported pathogenic deafness variants, 325 (14.8%) were present in at least one of the 8,595 controls, indicating a minor allele frequency (MAF) > 0.00006. MAFs ranged as high as 0.72, a level incompatible with pathogenicity for a fully penetrant disease like NSHL. Based on these data, we established MAF thresholds of 0.005 for autosomal-recessive variants (excluding specific variants in GJB2) and 0.0005 for autosomal-dominant variants. Using these thresholds, we recategorized 93 (4.2%) of reported pathogenic variants as benign. Our data show that evaluation of reported pathogenic deafness variants using variant MAFs from multiple distinct ethnicities and sequenced by orthogonal methods provides a powerful filter for determining pathogenicity. The proposed MAF thresholds will facilitate clinical interpretation of variants identified in genetic testing for NSHL. All data are publicly available to facilitate interpretation of genetic variants causing deafness.

2 Article Advancing genetic testing for deafness with genomic technology. 2013

Shearer, A Eliot / Black-Ziegelbein, E Ann / Hildebrand, Michael S / Eppsteiner, Robert W / Ravi, Harini / Joshi, Swati / Guiffre, Angelica C / Sloan, Christina M / Happe, Scott / Howard, Susanna D / Novak, Barbara / Deluca, Adam P / Taylor, Kyle R / Scheetz, Todd E / Braun, Terry A / Casavant, Thomas L / Kimberling, William J / Leproust, Emily M / Smith, Richard J H. ·Department of Otolaryngology-Head and Neck Surgery, Molecular Otolaryngology & Renal Research Labs, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA. ·J Med Genet · Pubmed #23804846.

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.

3 Article Pre-capture multiplexing improves efficiency and cost-effectiveness of targeted genomic enrichment. 2012

Shearer, A Eliot / Hildebrand, Michael S / Ravi, Harini / Joshi, Swati / Guiffre, Angelica C / Novak, Barbara / Happe, Scott / LeProust, Emily M / Smith, Richard J H. ·Department of Otolaryngology - Head & Neck Surgery, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA. ·BMC Genomics · Pubmed #23148716.

ABSTRACT: BACKGROUND: Targeted genomic enrichment (TGE) is a widely used method for isolating and enriching specific genomic regions prior to massively parallel sequencing. To make effective use of sequencer output, barcoding and sample pooling (multiplexing) after TGE and prior to sequencing (post-capture multiplexing) has become routine. While previous reports have indicated that multiplexing prior to capture (pre-capture multiplexing) is feasible, no thorough examination of the effect of this method has been completed on a large number of samples. Here we compare standard post-capture TGE to two levels of pre-capture multiplexing: 12 or 16 samples per pool. We evaluated these methods using standard TGE metrics and determined the ability to identify several classes of genetic mutations in three sets of 96 samples, including 48 controls. Our overall goal was to maximize cost reduction and minimize experimental time while maintaining a high percentage of reads on target and a high depth of coverage at thresholds required for variant detection. RESULTS: We adapted the standard post-capture TGE method for pre-capture TGE with several protocol modifications, including redesign of blocking oligonucleotides and optimization of enzymatic and amplification steps. Pre-capture multiplexing reduced costs for TGE by at least 38% and significantly reduced hands-on time during the TGE protocol. We found that pre-capture multiplexing reduced capture efficiency by 23 or 31% for pre-capture pools of 12 and 16, respectively. However efficiency losses at this step can be compensated by reducing the number of simultaneously sequenced samples. Pre-capture multiplexing and post-capture TGE performed similarly with respect to variant detection of positive control mutations. In addition, we detected no instances of sample switching due to aberrant barcode identification. CONCLUSIONS: Pre-capture multiplexing improves efficiency of TGE experiments with respect to hands-on time and reagent use compared to standard post-capture TGE. A decrease in capture efficiency is observed when using pre-capture multiplexing; however, it does not negatively impact variant detection and can be accommodated by the experimental design.