<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rochtus, Anne</style></author><author><style face="normal" font="default" size="100%">Olson, Heather E</style></author><author><style face="normal" font="default" size="100%">Smith, Lacey</style></author><author><style face="normal" font="default" size="100%">Keith, Louisa G</style></author><author><style face="normal" font="default" size="100%">El Achkar, Christelle</style></author><author><style face="normal" font="default" size="100%">Taylor, Alan</style></author><author><style face="normal" font="default" size="100%">Mahida, Sonal</style></author><author><style face="normal" font="default" size="100%">Park, Meredith</style></author><author><style face="normal" font="default" size="100%">Kelly, McKenna</style></author><author><style face="normal" font="default" size="100%">Shain, Catherine</style></author><author><style face="normal" font="default" size="100%">Rockowitz, Shira</style></author><author><style face="normal" font="default" size="100%">Rosen Sheidley, Beth</style></author><author><style face="normal" font="default" size="100%">Poduri, Annapurna</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetic diagnoses in epilepsy: The impact of dynamic exome analysis in a pediatric cohort.</style></title><secondary-title><style face="normal" font="default" size="100%">Epilepsia</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Epilepsia</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Age of Onset</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Child, Preschool</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosomes, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Epilepsy</style></keyword><keyword><style  face="normal" font="default" size="100%">Epilepsy, Generalized</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Testing</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Infant</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Microarray Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Exome Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Young Adult</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 02</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">61</style></volume><pages><style face="normal" font="default" size="100%">249-258</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;OBJECTIVE: &lt;/b&gt;We evaluated the yield of systematic analysis and/or reanalysis of whole exome sequencing (WES) data from a cohort of well-phenotyped pediatric patients with epilepsy and suspected but previously undetermined genetic etiology.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We identified and phenotyped 125 participants with pediatric epilepsy. Etiology was unexplained at the time of enrollment despite clinical testing, which included chromosomal microarray (57 patients), epilepsy gene panel (n = 48), both (n = 28), or WES (n = 8). Clinical epilepsy diagnoses included developmental and epileptic encephalopathy (DEE), febrile infection-related epilepsy syndrome, Rasmussen encephalitis, and other focal and generalized epilepsies. We analyzed WES data and compared the yield in participants with and without prior clinical genetic testing.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Overall, we identified pathogenic or likely pathogenic variants in 40% (50/125) of our study participants. Nine patients with DEE had genetic variants in recently published genes that had not been recognized as epilepsy-related at the time of clinical testing (FGF12, GABBR1, GABBR2, ITPA, KAT6A, PTPN23, RHOBTB2, SATB2), and eight patients had genetic variants in candidate epilepsy genes (CAMTA1, FAT3, GABRA6, HUWE1, PTCHD1). Ninety participants had concomitant or subsequent clinical genetic testing, which was ultimately explanatory for 26% (23/90). Of the 67 participants whose molecular diagnoses were &quot;unsolved&quot; through clinical genetic testing, we identified pathogenic or likely pathogenic variants in 17 (25%).&lt;/p&gt;&lt;p&gt;&lt;b&gt;SIGNIFICANCE: &lt;/b&gt;Our data argue for early consideration of WES with iterative reanalysis for patients with epilepsy, particularly those with DEE or epilepsy with intellectual disability. Rigorous analysis of WES data of well-phenotyped patients with epilepsy leads to a broader understanding of gene-specific phenotypic spectra as well as candidate disease gene identification. We illustrate the dynamic nature of genetic diagnosis over time, with analysis and in some cases reanalysis of exome data leading to the identification of disease-associated variants among participants with previously nondiagnostic results from a variety of clinical testing strategies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31957018?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Satterstrom, F Kyle</style></author><author><style face="normal" font="default" size="100%">Kosmicki, Jack A</style></author><author><style face="normal" font="default" size="100%">Wang, Jiebiao</style></author><author><style face="normal" font="default" size="100%">Breen, Michael S</style></author><author><style face="normal" font="default" size="100%">De Rubeis, Silvia</style></author><author><style face="normal" font="default" size="100%">An, Joon-Yong</style></author><author><style face="normal" font="default" size="100%">Peng, Minshi</style></author><author><style face="normal" font="default" size="100%">Collins, Ryan</style></author><author><style face="normal" font="default" size="100%">Grove, Jakob</style></author><author><style face="normal" font="default" size="100%">Klei, Lambertus</style></author><author><style face="normal" font="default" size="100%">Stevens, Christine</style></author><author><style face="normal" font="default" size="100%">Reichert, Jennifer</style></author><author><style face="normal" font="default" size="100%">Mulhern, Maureen S</style></author><author><style face="normal" font="default" size="100%">Artomov, Mykyta</style></author><author><style face="normal" font="default" size="100%">Gerges, Sherif</style></author><author><style face="normal" font="default" size="100%">Sheppard, Brooke</style></author><author><style face="normal" font="default" size="100%">Xu, Xinyi</style></author><author><style face="normal" font="default" size="100%">Bhaduri, Aparna</style></author><author><style face="normal" font="default" size="100%">Norman, Utku</style></author><author><style face="normal" font="default" size="100%">Brand, Harrison</style></author><author><style face="normal" font="default" size="100%">Schwartz, Grace</style></author><author><style face="normal" font="default" size="100%">Nguyen, Rachel</style></author><author><style face="normal" font="default" size="100%">Guerrero, Elizabeth E</style></author><author><style face="normal" font="default" size="100%">Dias, Caroline</style></author><author><style face="normal" font="default" size="100%">Betancur, Catalina</style></author><author><style face="normal" font="default" size="100%">Cook, Edwin H</style></author><author><style face="normal" font="default" size="100%">Gallagher, Louise</style></author><author><style face="normal" font="default" size="100%">Gill, Michael</style></author><author><style face="normal" font="default" size="100%">Sutcliffe, James S</style></author><author><style face="normal" font="default" size="100%">Thurm, Audrey</style></author><author><style face="normal" font="default" size="100%">Zwick, Michael E</style></author><author><style face="normal" font="default" size="100%">Børglum, Anders D</style></author><author><style face="normal" font="default" size="100%">State, Matthew W</style></author><author><style face="normal" font="default" size="100%">Cicek, A Ercument</style></author><author><style face="normal" font="default" size="100%">Talkowski, Michael E</style></author><author><style face="normal" font="default" size="100%">Cutler, David J</style></author><author><style face="normal" font="default" size="100%">Devlin, Bernie</style></author><author><style face="normal" font="default" size="100%">Sanders, Stephan J</style></author><author><style face="normal" font="default" size="100%">Roeder, Kathryn</style></author><author><style face="normal" font="default" size="100%">Daly, Mark J</style></author><author><style face="normal" font="default" size="100%">Buxbaum, Joseph D</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">Autism Sequencing Consortium</style></author><author><style face="normal" font="default" size="100%">iPSYCH-Broad Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cell</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Autistic Disorder</style></keyword><keyword><style  face="normal" font="default" size="100%">Case-Control Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Lineage</style></keyword><keyword><style  face="normal" font="default" size="100%">Cerebral Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Developmental</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Frequency</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation, Missense</style></keyword><keyword><style  face="normal" font="default" size="100%">Neurobiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Neurons</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Sex Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Single-Cell Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Exome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 02 06</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">180</style></volume><pages><style face="normal" font="default" size="100%">568-584.e23</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31981491?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sanghvi, Rashesh V</style></author><author><style face="normal" font="default" size="100%">Buhay, Christian J</style></author><author><style face="normal" font="default" size="100%">Powell, Bradford C</style></author><author><style face="normal" font="default" size="100%">Tsai, Ellen A</style></author><author><style face="normal" font="default" size="100%">Dorschner, Michael O</style></author><author><style face="normal" font="default" size="100%">Hong, Celine S</style></author><author><style face="normal" font="default" size="100%">Lebo, Matthew S</style></author><author><style face="normal" font="default" size="100%">Sasson, Ariella</style></author><author><style face="normal" font="default" size="100%">Hanna, David S</style></author><author><style face="normal" font="default" size="100%">McGee, Sean</style></author><author><style face="normal" font="default" size="100%">Bowling, Kevin M</style></author><author><style face="normal" font="default" size="100%">Cooper, Gregory M</style></author><author><style face="normal" font="default" size="100%">Gray, David E</style></author><author><style face="normal" font="default" size="100%">Lonigro, Robert J</style></author><author><style face="normal" font="default" size="100%">Dunford, Andrew</style></author><author><style face="normal" font="default" size="100%">Brennan, Christine A</style></author><author><style face="normal" font="default" size="100%">Cibulskis, Carrie</style></author><author><style face="normal" font="default" size="100%">Walker, Kimberly</style></author><author><style face="normal" font="default" size="100%">Carneiro, Mauricio O</style></author><author><style face="normal" font="default" size="100%">Sailsbery, Joshua</style></author><author><style face="normal" font="default" size="100%">Hindorff, Lucia A</style></author><author><style face="normal" font="default" size="100%">Robinson, Dan R</style></author><author><style face="normal" font="default" size="100%">Santani, Avni</style></author><author><style face="normal" font="default" size="100%">Sarmady, Mahdi</style></author><author><style face="normal" font="default" size="100%">Rehm, Heidi L</style></author><author><style face="normal" font="default" size="100%">Biesecker, Leslie G</style></author><author><style face="normal" font="default" size="100%">Nickerson, Deborah A</style></author><author><style face="normal" font="default" size="100%">Hutter, Carolyn M</style></author><author><style face="normal" font="default" size="100%">Garraway, Levi</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna M</style></author><author><style face="normal" font="default" size="100%">Wagle, Nikhil</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">NHGRI Clinical Sequencing Exploratory Research (CSER) Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterizing reduced coverage regions through comparison of exome and genome sequencing data across 10 centers.</style></title><secondary-title><style face="normal" font="default" size="100%">Genet Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genet. Med.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Base Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosome Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Exome Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 08</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">855-866</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;PURPOSE: &lt;/b&gt;As massively parallel sequencing is increasingly being used for clinical decision making, it has become critical to understand parameters that affect sequencing quality and to establish methods for measuring and reporting clinical sequencing standards. In this report, we propose a definition for reduced coverage regions and describe a set of standards for variant calling in clinical sequencing applications.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;To enable sequencing centers to assess the regions of poor sequencing quality in their own data, we optimized and used a tool (ExCID) to identify reduced coverage loci within genes or regions of particular interest. We used this framework to examine sequencing data from 500 patients generated in 10 projects at sequencing centers in the National Human Genome Research Institute/National Cancer Institute Clinical Sequencing Exploratory Research Consortium.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;This approach identified reduced coverage regions in clinically relevant genes, including known clinically relevant loci that were uniquely missed at individual centers, in multiple centers, and in all centers.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSION: &lt;/b&gt;This report provides a process road map for clinical sequencing centers looking to perform similar analyses on their data.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/29144510?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sabo, Aniko</style></author><author><style face="normal" font="default" size="100%">Mishra, Pamela</style></author><author><style face="normal" font="default" size="100%">Dugan-Perez, Shannon</style></author><author><style face="normal" font="default" size="100%">Voruganti, V Saroja</style></author><author><style face="normal" font="default" size="100%">Kent, Jack W</style></author><author><style face="normal" font="default" size="100%">Kalra, Divya</style></author><author><style face="normal" font="default" size="100%">Cole, Shelley A</style></author><author><style face="normal" font="default" size="100%">Comuzzie, Anthony G</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna M</style></author><author><style face="normal" font="default" size="100%">Gibbs, Richard A</style></author><author><style face="normal" font="default" size="100%">Butte, Nancy F</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exome sequencing reveals novel genetic loci influencing obesity-related traits in Hispanic children.</style></title><secondary-title><style face="normal" font="default" size="100%">Obesity (Silver Spring)</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Obesity (Silver Spring)</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">ATPases Associated with Diverse Cellular Activities</style></keyword><keyword><style  face="normal" font="default" size="100%">Body Mass Index</style></keyword><keyword><style  face="normal" font="default" size="100%">Body Weight</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Child, Preschool</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Hispanic or Latino</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Membrane Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Pediatric Obesity</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Waist Circumference</style></keyword><keyword><style  face="normal" font="default" size="100%">Young Adult</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Jul</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">25</style></volume><pages><style face="normal" font="default" size="100%">1270-1276</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;OBJECTIVE: &lt;/b&gt;To perform whole exome sequencing in 928 Hispanic children and identify variants and genes associated with childhood obesity.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Single-nucleotide variants (SNVs) were identified from Illumina whole exome sequencing data using integrated read mapping, variant calling, and an annotation pipeline (Mercury). Association analyses of 74 obesity-related traits and exonic variants were performed using SeqMeta software. Rare autosomal variants were analyzed using gene-based association analyses, and common autosomal variants were analyzed at the SNV level.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;(1) Rare exonic variants in 10 genes and 16 common SNVs in 11 genes that were associated with obesity traits in a cohort of Hispanic children were identified, (2) novel rare variants in peroxisome biogenesis factor 1 (PEX1) associated with several obesity traits (weight, weight z score, BMI, BMI z score, waist circumference, fat mass, trunk fat mass) were discovered, and (3) previously reported SNVs associated with childhood obesity were replicated.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Convergence of whole exome sequencing, a family-based design, and extensive phenotyping discovered novel rare and common variants associated with childhood obesity. Linking PEX1 to obesity phenotypes poses a novel mechanism of peroxisomal biogenesis and metabolism underlying the development of childhood obesity.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28508493?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Posey, Jennifer E</style></author><author><style face="normal" font="default" size="100%">Harel, Tamar</style></author><author><style face="normal" font="default" size="100%">Liu, Pengfei</style></author><author><style face="normal" font="default" size="100%">Rosenfeld, Jill A</style></author><author><style face="normal" font="default" size="100%">James, Regis A</style></author><author><style face="normal" font="default" size="100%">Coban Akdemir, Zeynep H</style></author><author><style face="normal" font="default" size="100%">Walkiewicz, Magdalena</style></author><author><style face="normal" font="default" size="100%">Bi, Weimin</style></author><author><style face="normal" font="default" size="100%">Xiao, Rui</style></author><author><style face="normal" font="default" size="100%">Ding, Yan</style></author><author><style face="normal" font="default" size="100%">Xia, Fan</style></author><author><style face="normal" font="default" size="100%">Beaudet, Arthur L</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna M</style></author><author><style face="normal" font="default" size="100%">Gibbs, Richard A</style></author><author><style face="normal" font="default" size="100%">Boerwinkle, Eric</style></author><author><style face="normal" font="default" size="100%">Eng, Christine M</style></author><author><style face="normal" font="default" size="100%">Sutton, V Reid</style></author><author><style face="normal" font="default" size="100%">Shaw, Chad A</style></author><author><style face="normal" font="default" size="100%">Plon, Sharon E</style></author><author><style face="normal" font="default" size="100%">Yang, Yaping</style></author><author><style face="normal" font="default" size="100%">Lupski, James R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Resolution of Disease Phenotypes Resulting from Multilocus Genomic Variation.</style></title><secondary-title><style face="normal" font="default" size="100%">N Engl J Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">N Engl J Med</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Diseases, Inborn</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotyping Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Retrospective Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Jan 05</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">376</style></volume><pages><style face="normal" font="default" size="100%">21-31</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Whole-exome sequencing can provide insight into the relationship between observed clinical phenotypes and underlying genotypes.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We conducted a retrospective analysis of data from a series of 7374 consecutive unrelated patients who had been referred to a clinical diagnostic laboratory for whole-exome sequencing; our goal was to determine the frequency and clinical characteristics of patients for whom more than one molecular diagnosis was reported. The phenotypic similarity between molecularly diagnosed pairs of diseases was calculated with the use of terms from the Human Phenotype Ontology.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;A molecular diagnosis was rendered for 2076 of 7374 patients (28.2%); among these patients, 101 (4.9%) had diagnoses that involved two or more disease loci. We also analyzed parental samples, when available, and found that de novo variants accounted for 67.8% (61 of 90) of pathogenic variants in autosomal dominant disease genes and 51.7% (15 of 29) of pathogenic variants in X-linked disease genes; both variants were de novo in 44.7% (17 of 38) of patients with two monoallelic variants. Causal copy-number variants were found in 12 patients (11.9%) with multiple diagnoses. Phenotypic similarity scores were significantly lower among patients in whom the phenotype resulted from two distinct mendelian disorders that affected different organ systems (50 patients) than among patients with disorders that had overlapping phenotypic features (30 patients) (median score, 0.21 vs. 0.36; P=1.77×10).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;In our study, we found multiple molecular diagnoses in 4.9% of cases in which whole-exome sequencing was informative. Our results show that structured clinical ontologies can be used to determine the degree of overlap between two mendelian diseases in the same patient; the diseases can be distinct or overlapping. Distinct disease phenotypes affect different organ systems, whereas overlapping disease phenotypes are more likely to be caused by two genes encoding proteins that interact within the same pathway. (Funded by the National Institutes of Health and the Ting Tsung and Wei Fong Chao Foundation.).&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/27959697?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Turner, Tychele N</style></author><author><style face="normal" font="default" size="100%">Hormozdiari, Fereydoun</style></author><author><style face="normal" font="default" size="100%">Duyzend, Michael H</style></author><author><style face="normal" font="default" size="100%">McClymont, Sarah A</style></author><author><style face="normal" font="default" size="100%">Hook, Paul W</style></author><author><style face="normal" font="default" size="100%">Iossifov, Ivan</style></author><author><style face="normal" font="default" size="100%">Raja, Archana</style></author><author><style face="normal" font="default" size="100%">Baker, Carl</style></author><author><style face="normal" font="default" size="100%">Hoekzema, Kendra</style></author><author><style face="normal" font="default" size="100%">Stessman, Holly A</style></author><author><style face="normal" font="default" size="100%">Zody, Michael C</style></author><author><style face="normal" font="default" size="100%">Nelson, Bradley J</style></author><author><style face="normal" font="default" size="100%">Huddleston, John</style></author><author><style face="normal" font="default" size="100%">Sandstrom, Richard</style></author><author><style face="normal" font="default" size="100%">Smith, Joshua D</style></author><author><style face="normal" font="default" size="100%">Hanna, David</style></author><author><style face="normal" font="default" size="100%">Swanson, James M</style></author><author><style face="normal" font="default" size="100%">Faustman, Elaine M</style></author><author><style face="normal" font="default" size="100%">Bamshad, Michael J</style></author><author><style face="normal" font="default" size="100%">Stamatoyannopoulos, John</style></author><author><style face="normal" font="default" size="100%">Nickerson, Deborah A</style></author><author><style face="normal" font="default" size="100%">McCallion, Andrew S</style></author><author><style face="normal" font="default" size="100%">Darnell, Robert</style></author><author><style face="normal" font="default" size="100%">Eichler, Evan E</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome Sequencing of Autism-Affected Families Reveals Disruption of Putative Noncoding Regulatory DNA.</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Hum Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am J Hum Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Autistic Disorder</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Pedigree</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Jan 07</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">98</style></volume><pages><style face="normal" font="default" size="100%">58-74</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We performed whole-genome sequencing (WGS) of 208 genomes from 53 families affected by simplex autism. For the majority of these families, no copy-number variant (CNV) or candidate de novo gene-disruptive single-nucleotide variant (SNV) had been detected by microarray or whole-exome sequencing (WES). We integrated multiple CNV and SNV analyses and extensive experimental validation to identify additional candidate mutations in eight families. We report that compared to control individuals, probands showed a significant (p = 0.03) enrichment of de novo and private disruptive mutations within fetal CNS DNase I hypersensitive sites (i.e., putative regulatory regions). This effect was only observed within 50 kb of genes that have been previously associated with autism risk, including genes where dosage sensitivity has already been established by recurrent disruptive de novo protein-coding mutations (ARID1B, SCN2A, NR3C2, PRKCA, and DSCAM). In addition, we provide evidence of gene-disruptive CNVs (in DISC1, WNT7A, RBFOX1, and MBD5), as well as smaller de novo CNVs and exon-specific SNVs missed by exome sequencing in neurodevelopmental genes (e.g., CANX, SAE1, and PIK3CA). Our results suggest that the detection of smaller, often multiple CNVs affecting putative regulatory elements might help explain additional risk of simplex autism.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/26749308?dopt=Abstract</style></custom1></record></records></xml>