Browsing by Author "Nickerson, Deborah A."

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    CYP2C8, CYP2C9, and CYP2C19 Characterization Using Next-Generation Sequencing and Haplotype Analysis: A GeT-RM Collaborative Project
    (Elsevier, 2022) Gaedigk, Andrea; Boone, Erin C.; Scherer, Steven E.; Lee, Seung-Been; Numanagić, Ibrahim; Sahinalp, Cenk; Smith, Joshua D.; McGee, Sean; Radhakrishnan, Aparna; Qin, Xiang; Wang, Wendy Y.; Farrow, Emily G.; Gonzaludo, Nina; Halpern, Aaron L.; Nickerson, Deborah A.; Miller, Neil A.; Pratt, Victoria M.; Kalman, Lisa V.; Medical and Molecular Genetics, School of Medicine
    Pharmacogenetic tests typically target selected sequence variants to identify haplotypes that are often defined by star (∗) allele nomenclature. Due to their design, these targeted genotyping assays are unable to detect novel variants that may change the function of the gene product and thereby affect phenotype prediction and patient care. In the current study, 137 DNA samples that were previously characterized by the Genetic Testing Reference Material (GeT-RM) program using a variety of targeted genotyping methods were recharacterized using targeted and whole genome sequencing analysis. Sequence data were analyzed using three genotype calling tools to identify star allele diplotypes for CYP2C8, CYP2C9, and CYP2C19. The genotype calls from next-generation sequencing (NGS) correlated well to those previously reported, except when novel alleles were present in a sample. Six novel alleles and 38 novel suballeles were identified in the three genes due to identification of variants not covered by targeted genotyping assays. In addition, several ambiguous genotype calls from a previous study were resolved using the NGS and/or long-read NGS data. Diplotype calls were mostly consistent between the calling algorithms, although several discrepancies were noted. This study highlights the utility of NGS for pharmacogenetic testing and demonstrates that there are many novel alleles that are yet to be discovered, even in highly characterized genes such as CYP2C9 and CYP2C19.
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    Functional Dysregulation of CDC42 Causes Diverse Developmental Phenotypes
    (Elsevier, 2018-02-01) Martinelli, Simone; Krumbach, Oliver H.F.; Pantaleoni, Francesca; Coppola, Simona; Amin, Ehsan; Pannone, Luca; Nouri, Kazem; Farina, Luciapia; Dvorsky, Radovan; Lepri, Francesca; Bucholzer, Marcel; Konopatzki, Raphael; Walsh, Laurence; Payne, Katelyn; Pierpont, Mary Ella; Vergano, Samantha Schrier; Langley, Katherine G.; Larsen, Douglas; Farwell, Kelly D.; Tang, Sha; Mroske, Cameron; Gallotta, Ivan; Schiavi, Elia Di; della Monica, Matteo; Lugli, Licia; Rossi, Cesare; Seri, Marco; Cocchi, Guido; Henderson, Lindsay; Baskin, Berivan; Alders, Mariëlle; Mendoza-Londono, Roberto; Dupuis, Lucie; Nickerson, Deborah A.; Chong, Jessica X.; Meeks, Naomi; Brown, Kathleen; Causey, Tahnee; Cho, Megan T.; Demuth, Stephanie; Digilio, Maria Cristina; Gelb, Bruce D.; Bamshad, Michael J.; Zenker, Martin; Ahmadian, Mohammad Reza; Hennekam, Raoul C.; Tartaglia, Marco; Mirzaa, Ghayda M.; Neurology, School of Medicine
    Exome sequencing has markedly enhanced the discovery of genes implicated in Mendelian disorders, particularly for individuals in whom a known clinical entity could not be assigned. This has led to the recognition that phenotypic heterogeneity resulting from allelic mutations occurs more commonly than previously appreciated. Here, we report that missense variants in CDC42, a gene encoding a small GTPase functioning as an intracellular signaling node, underlie a clinically heterogeneous group of phenotypes characterized by variable growth dysregulation, facial dysmorphism, and neurodevelopmental, immunological, and hematological anomalies, including a phenotype resembling Noonan syndrome, a developmental disorder caused by dysregulated RAS signaling. In silico, in vitro, and in vivo analyses demonstrate that mutations variably perturb CDC42 function by altering the switch between the active and inactive states of the GTPase and/or affecting CDC42 interaction with effectors, and differentially disturb cellular and developmental processes. These findings reveal the remarkably variable impact that dominantly acting CDC42 mutations have on cell function and development, creating challenges in syndrome definition, and exemplify the importance of functional profiling for syndrome recognition and delineation.
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    Mutations in PIEZO2 cause Gordon syndrome, Marden-Walker syndrome, and distal arthrogryposis type 5
    (Elsevier, 2014-05-01) McMillin, Margaret J.; Beck, Anita E.; Chong, Jessica X.; Shively, Kathryn M.; Buckingham, Kati J.; Gildersleeve, Heidi I.S.; Aracena, Mariana I.; Aylsworth, Arthur S.; Bitoun, Pierre; Carey, John C.; Clericuzio, Carol L.; Crow, Yanick J.; Curry, Cynthia J.; Devriendt, Koenraad; Everman, David B.; Fryer, Alan; Gibson, Kate; Uzielli, Maria Luisa Giovannucci; Graham, John M. Jr.; Hall, Judith G.; Hecht, Jacqueline T.; Heidenreich, Randall A.; Hurst, Jane A.; Irani, Sarosh; Krapels, Ingrid P.C.; Leroy, Jules G.; Mowat, David; Plant, Gordon T.; Robertson, Stephen P.; Schorry, Elizabeth K.; Scott, Richard H.; Seaver, Laurie H.; Sherr, Elliott; Splitt, Miranda; Stewart, Helen; Stumpel, Constance; Temel, Sehime G.; Weaver, David D.; Whiteford, Margo; Williams, Marc S.; Tabor, Holly K.; Smith, Joshua D.; Shendure, Jay; Nickerson, Deborah A.; Bamshad, Michael J.; Medical & Molecular Genetics, School of Medicine
    Gordon syndrome (GS), or distal arthrogryposis type 3, is a rare, autosomal-dominant disorder characterized by cleft palate and congenital contractures of the hands and feet. Exome sequencing of five GS-affected families identified mutations in piezo-type mechanosensitive ion channel component 2 (PIEZO2) in each family. Sanger sequencing revealed PIEZO2 mutations in five of seven additional families studied (for a total of 10/12 [83%] individuals), and nine families had an identical c.8057G>A (p.Arg2686His) mutation. The phenotype of GS overlaps with distal arthrogryposis type 5 (DA5) and Marden-Walker syndrome (MWS). Using molecular inversion probes for targeted sequencing to screen PIEZO2, we found mutations in 24/29 (82%) DA5-affected families and one of two MWS-affected families. The presence of cleft palate was significantly associated with c.8057G>A (Fisher’s exact test, adjusted p value < 0.0001). Collectively, although GS, DA5, and MWS have traditionally been considered separate disorders, our findings indicate that they are etiologically related and perhaps represent variable expressivity of the same condition.
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    Pharmacogenetic allele nomenclature: International workgroup recommendations for test result reporting
    (Wiley, 2016-02) Kalman, Lisa V.; Agúndez, José A.G.; Appell, Malin Lindqvist; Bell, Gillian C.; Boukouvala, Sotiria; Bruckner, Carsten; Bruford, Elspeth; Bruckner, Carsten; Caudle, Kelly; Coulthard, Sally; Daly, Ann K.; Del Tredici, Johan T.; Drozda, Katarzyna; Everts, Robin; Flockhart, David; Freimuth, Robert; Gaedigk, Andrea; Hachad, Houda; Hartshorne, Toinette; Ingelman-Sundberg, Magnus; Klein, Teri E.; Lauschke, Volker M.; Maglott, Donna R.; McLeod, Howard L.; McMillin, Gwendolyn A.; Meyer, Urs A.; Müller, Daniel J.; Nickerson, Deborah A.; Oetting, William S.; Pacanowski, Michael; Pratt, Victoria M.; Relling, Mary V.; Roberts, Ali; Rubinstein, Wendy S.; Sangkuhl, Katrin; Schwab, Matthias; Scott, Stuart A.; Sim, Sarah C.; Thirumaran, Ranjit K.; Toji, Lorraine H.; Tyndale, Rachel; van Schaik, Ron HN; Whirl-Carrillo, Michelle; Yeo, Kiang-Teck J.; Zanger, Ulrich M.; Department of Medical & Molecular Genetics, IU School of Medicine
    This manuscript provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward.
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    Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program
    (Springer Nature, 2021) Taliun, Daniel; Harris, Daniel N.; Kessler, Michael D.; Carlson, Jedidiah; Szpiech, Zachary A.; Torres, Raul; Gagliano Taliun, Sarah A.; Corvelo, André; Gogarten, Stephanie M.; Kang, Hyun Min; Pitsillides, Achilleas N.; LeFaive, Jonathon; Lee, Seung-Been; Tian, Xiaowen; Browning, Brian L.; Das, Sayantan; Emde, Anne-Katrin; Clarke, Wayne E.; Loesch, Douglas P.; Shetty, Amol C.; Blackwell, Thomas W.; Smith, Albert V.; Wong, Quenna; Liu, Xiaoming; Conomos, Matthew P.; Bobo, Dean M.; Aguet, François; Albert, Christine; Alonso, Alvaro; Ardlie, Kristin G.; Arking, Dan E.; Aslibekyan, Stella; Auer, Paul L.; Barnard, John; Barr, R. Graham; Barwick, Lucas; Becker, Lewis C.; Beer, Rebecca L.; Benjamin, Emelia J.; Bielak, Lawrence F.; Blangero, John; Boehnke, Michael; Bowden, Donald W.; Brody, Jennifer A.; Burchard, Esteban G.; Cade, Brian E.; Casella, James F.; Chalazan, Brandon; Chasman, Daniel I.; Chen, Yii-Der Ida; Cho, Michael H.; Choi, Seung Hoan; Chung, Mina K.; Clish, Clary B.; Correa, Adolfo; Curran, Joanne E.; Custer, Brian; Darbar, Dawood; Daya, Michelle; de Andrade, Mariza; DeMeo, Dawn L.; Dutcher, Susan K.; Ellinor, Patrick T.; Emery, Leslie S.; Eng, Celeste; Fatkin, Diane; Fingerlin, Tasha; Forer, Lukas; Fornage, Myriam; Franceschini, Nora; Fuchsberger, Christian; Fullerton, Stephanie M.; Germer, Soren; Gladwin, Mark T.; Gottlieb, Daniel J.; Guo, Xiuqing; Hall, Michael E.; He, Jiang; Heard-Costa, Nancy L.; Heckbert, Susan R.; Irvin, Marguerite R.; Johnsen, Jill M.; Johnson, Andrew D.; Kaplan, Robert; Kardia, Sharon L. R.; Kelly, Tanika; Kelly, Shannon; Kenny, Eimear E.; Kiel, Douglas P.; Klemmer, Robert; Konkle, Barbara A.; Kooperberg, Charles; Köttgen, Anna; Lange, Leslie A.; Lasky-Su, Jessica; Levy, Daniel; Lin, Xihong; Lin, Keng-Han; Liu, Chunyu; Loos, Ruth J. F.; Garman, Lori; Gerszten, Robert; Lubitz, Steven A.; Lunetta, Kathryn L.; Mak, Angel C. Y.; Manichaikul, Ani; Manning, Alisa K.; Mathias, Rasika A.; McManus, David D.; McGarvey, Stephen T.; Meigs, James B.; Meyers, Deborah A.; Mikulla, Julie L.; Minear, Mollie A.; Mitchell, Braxton D.; Mohanty, Sanghamitra; Montasser, May E.; Montgomery, Courtney; Morrison, Alanna C.; Murabito, Joanne M.; Natale, Andrea; Natarajan, Pradeep; Nelson, Sarah C.; North, Kari E.; O'Connell, Jeffrey R.; Palmer, Nicholette D.; Pankratz, Nathan; Peloso, Gina M.; Peyser, Patricia A.; Pleiness, Jacob; Post, Wendy S.; Psaty, Bruce M.; Rao, D. C.; Redline, Susan; Reiner, Alexander P.; Roden, Dan; Rotter, Jerome I.; Ruczinski, Ingo; Sarnowski, Chloé; Schoenherr, Sebastian; Schwartz, David A.; Seo, Jeong-Sun; Seshadri, Sudha; Sheehan, Vivien A.; Sheu, Wayne H.; Shoemaker, M. Benjamin; Smith, Nicholas L.; Smith, Jennifer A.; Sotoodehnia, Nona; Stilp, Adrienne M.; Tang, Weihong; Taylor, Kent D.; Telen, Marilyn; Thornton, Timothy A.; Tracy, Russell P.; Van Den Berg, David J.; Vasan, Ramachandran S.; Viaud-Martinez, Karine A.; Vrieze, Scott; Weeks, Daniel E.; Weir, Bruce S.; Weiss, Scott T.; Weng, Lu-Chen; Willer, Cristen J.; Zhang, Yingze; Zhao, Xutong; Arnett, Donna K.; Ashley-Koch, Allison E.; Barnes, Kathleen C.; Boerwinkle, Eric; Gabriel, Stacey; Gibbs, Richard; Rice, Kenneth M.; Rich, Stephen S.; Silverman, Edwin K.; Qasba, Pankaj; Gan, Weiniu; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; Papanicolaou, George J.; Nickerson, Deborah A.; Browning, Sharon R.; Zody, Michael C.; Zöllner, Sebastian; Wilson, James G.; Cupples, L. Adrienne; Laurie, Cathy C.; Jaquish, Cashell E.; Hernandez, Ryan D.; O'Connor, Timothy D.; Abecasis, Gonçalo R.; Epidemiology, Richard M. Fairbanks School of Public Health
    The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.