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Funke, Birgit

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Funke

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Birgit

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Funke, Birgit
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Now showing 1 - 10 of 11
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    Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples
    (Nature Publishing Group, 2017) Walsh, Roddy; Thomson, Kate L.; Ware, James S.; Funke, Birgit; Woodley, Jessica; McGuire, Karen J.; Mazzarotto, Francesco; Blair, Edward; Seller, Anneke; Taylor, Jenny C.; Minikel, Eric; Exome Aggregation Consortium; MacArthur, Daniel; Farrall, Martin; Cook, Stuart A.; Watkins, Hugh
    Purpose: The accurate interpretation of variation in Mendelian disease genes has lagged behind data generation as sequencing has become increasingly accessible. Ongoing large sequencing efforts present huge interpretive challenges, but they also provide an invaluable opportunity to characterize the spectrum and importance of rare variation. Methods: We analyzed sequence data from 7,855 clinical cardiomyopathy cases and 60,706 Exome Aggregation Consortium (ExAC) reference samples to obtain a better understanding of genetic variation in a representative autosomal dominant disorder. Results: We found that in some genes previously reported as important causes of a given cardiomyopathy, rare variation is not clinically informative because there is an unacceptably high likelihood of false-positive interpretation. By contrast, in other genes, we find that diagnostic laboratories may be overly conservative when assessing variant pathogenicity. Conclusions: We outline improved analytical approaches that evaluate which genes and variant classes are interpretable and propose that these will increase the clinical utility of testing across a range of Mendelian diseases. Genet Med 19 2, 192–203.
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    An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge
    (BioMed Central, 2014) Brownstein, Catherine; Beggs, Alan; Homer, Nils; Merriman, Barry; Yu, Timothy W; Flannery, Katherine; DeChene, Elizabeth T; Towne, Meghan C; Savage, Sarah K; Price, Emily N; Holm, Ingrid; Luquette, Joe; Lyon, Elaine; Majzoub, Joseph; Neupert, Peter; McCallie Jr, David; Szolovits, Peter; Willard, Huntington F; Mendelsohn, Nancy J; Temme, Renee; Finkel, Richard S; Yum, Sabrina W; Medne, Livija; Sunyaev, Shamil; Adzhubey, Ivan; Cassa, Christopher; de Bakker, Paul IW; Duzkale, Hatice; Dworzyński, Piotr; Fairbrother, William; Francioli, Laurent; Funke, Birgit; Giovanni, Monica A; Handsaker, Robert; Lage, Kasper; Lebo, Matthew; Lek, Monkol; Leshchiner, Ignaty; MacArthur, Daniel; McLaughlin, Heather M; Murray, Michael F; Pers, Tune H; Polak, Paz P; Raychaudhuri, Soumya; Rehm, Heidi; Soemedi, Rachel; Stitziel, Nathan O; Vestecka, Sara; Supper, Jochen; Gugenmus, Claudia; Klocke, Bernward; Hahn, Alexander; Schubach, Max; Menzel, Mortiz; Biskup, Saskia; Freisinger, Peter; Deng, Mario; Braun, Martin; Perner, Sven; Smith, Richard JH; Andorf, Janeen L; Huang, Jian; Ryckman, Kelli; Sheffield, Val C; Stone, Edwin M; Bair, Thomas; Black-Ziegelbein, E Ann; Braun, Terry A; Darbro, Benjamin; DeLuca, Adam P; Kolbe, Diana L; Scheetz, Todd E; Shearer, Aiden E; Sompallae, Rama; Wang, Kai; Bassuk, Alexander G; Edens, Erik; Mathews, Katherine; Moore, Steven A; Shchelochkov, Oleg A; Trapane, Pamela; Bossler, Aaron; Campbell, Colleen A; Heusel, Jonathan W; Kwitek, Anne; Maga, Tara; Panzer, Karin; Wassink, Thomas; Van Daele, Douglas; Azaiez, Hela; Booth, Kevin; Meyer, Nic; Segal, Michael M; Williams, Marc S; Tromp, Gerard; White, Peter; Corsmeier, Donald; Fitzgerald-Butt, Sara; Herman, Gail; Lamb-Thrush, Devon; McBride, Kim L; Newsom, David; Pierson, Christopher R; Rakowsky, Alexander T; Maver, Aleš; Lovrečić, Luca; Palandačić, Anja; Peterlin, Borut; Torkamani, Ali; Wedell, Anna; Huss, Mikael; Alexeyenko, Andrey; Lindvall, Jessica M; Magnusson, Måns; Nilsson, Daniel; Stranneheim, Henrik; Taylan, Fulya; Gilissen, Christian; Hoischen, Alexander; van Bon, Bregje; Yntema, Helger; Nelen, Marcel; Zhang, Weidong; Sager, Jason; Zhang, Lu; Blair, Kathryn; Kural, Deniz; Cariaso, Michael; Lennon, Greg G; Javed, Asif; Agrawal, Saloni; Ng, Pauline C; Sandhu, Komal S; Krishna, Shuba; Veeramachaneni, Vamsi; Isakov, Ofer; Halperin, Eran; Friedman, Eitan; Shomron, Noam; Glusman, Gustavo; Roach, Jared C; Caballero, Juan; Cox, Hannah C; Mauldin, Denise; Ament, Seth A; Rowen, Lee; Richards, Daniel R; Lucas, F Anthony San; Gonzalez-Garay, Manuel L; Caskey, C Thomas; Bai, Yu; Huang, Ying; Fang, Fang; Zhang, Yan; Wang, Zhengyuan; Barrera, Jorge; Garcia-Lobo, Juan M; González-Lamuño, Domingo; Llorca, Javier; Rodriguez, Maria C; Varela, Ignacio; Reese, Martin G; De La Vega, Francisco M; Kiruluta, Edward; Cargill, Michele; Hart, Reece K; Sorenson, Jon M; Lyon, Gholson J; Stevenson, David A; Bray, Bruce E; Moore, Barry M; Eilbeck, Karen; Yandell, Mark; Zhao, Hongyu; Hou, Lin; Chen, Xiaowei; Yan, Xiting; Chen, Mengjie; Li, Cong; Yang, Can; Gunel, Murat; Li, Peining; Kong, Yong; Alexander, Austin C; Albertyn, Zayed I; Boycott, Kym M; Bulman, Dennis E; Gordon, Paul MK; Innes, A Micheil; Knoppers, Bartha M; Majewski, Jacek; Marshall, Christian R; Parboosingh, Jillian S; Sawyer, Sarah L; Samuels, Mark E; Schwartzentruber, Jeremy; Kohane, Isaac; Margulies, David
    Background: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. Results: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. Conclusions: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.
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    Compound heterozygosity of predicted loss-of-function DES variants in a family with recessive desminopathy
    (BioMed Central, 2013) McLaughlin, Heather M; Kelly, Melissa A; Hawley, Pamela P; Darras, Basil; Funke, Birgit; Picker, Jonathan
    Background: Variants in the desmin gene (DES) are associated with desminopathy; a myofibrillar myopathy mainly characterized by muscle weakness, conduction block, and dilated cardiomyopathy. To date, only ~50 disease-associated variants have been described, and the majority of these lead to dominant-negative effects. However, the complete genotypic spectrum of desminopathy is not well established. Case presentation: Next-generation sequencing was performed on 51 cardiac disease genes in a proband with profound skeletal myopathy, dilated cardiomyopathy, and respiratory dysfunction. Our analyses revealed compound heterozygous DES variants, both of which are predicted to lead to a loss-of-function. Consistent with recessive inheritance, each variant was identified in an unaffected parent. Conclusions: This case report serves to broaden the variant spectrum of desminopathies and provides insight into the molecular mechanisms of desminopathy, supporting distinct dominant-negative and loss-of-function etiologies.
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    The CHC22 Clathrin-GLUT4 Transport Pathway Contributes to Skeletal Muscle Regeneration
    (Public Library of Science, 2013) Hoshino, Sachiko; Sakamoto, Kazuho; Vassilopoulos, Stéphane; Camus, Stéphane M.; Griffin, Christine A.; Esk, Christopher; Torres, Jorge A.; Ohkoshi, Norio; Ishii, Akiko; Tamaoka, Akira; Funke, Birgit; Kucherlapati, Raju; Margeta, Marta; Rando, Thomas A.; Brodsky, Frances M.
    Mobilization of the GLUT4 glucose transporter from intracellular storage vesicles provides a mechanism for insulin-responsive glucose import into skeletal muscle. In humans, clathrin isoform CHC22 participates in formation of the GLUT4 storage compartment in skeletal muscle and fat. CHC22 function is limited to retrograde endosomal sorting and is restricted in its tissue expression and species distribution compared to the conserved CHC17 isoform that mediates endocytosis and several other membrane traffic pathways. Previously, we noted that CHC22 was expressed at elevated levels in regenerating rat muscle. Here we investigate whether the GLUT4 pathway in which CHC22 participates could play a role in muscle regeneration in humans and we test this possibility using CHC22-transgenic mice, which do not normally express CHC22. We observed that GLUT4 expression is elevated in parallel with that of CHC22 in regenerating skeletal muscle fibers from patients with inflammatory and other myopathies. Regenerating human myofibers displayed concurrent increases in expression of VAMP2, another regulator of GLUT4 transport. Regenerating fibers from wild-type mouse skeletal muscle injected with cardiotoxin also showed increased levels of GLUT4 and VAMP2. We previously demonstrated that transgenic mice expressing CHC22 in their muscle over-sequester GLUT4 and VAMP2 and have defective GLUT4 trafficking leading to diabetic symptoms. In this study, we find that muscle regeneration rates in CHC22 mice were delayed compared to wild-type mice, and myoblasts isolated from these mice did not proliferate in response to glucose. Additionally, CHC22-expressing mouse muscle displayed a fiber type switch from oxidative to glycolytic, similar to that observed in type 2 diabetic patients. These observations implicate the pathway for GLUT4 transport in regeneration of both human and mouse skeletal muscle, and demonstrate a role for this pathway in maintenance of muscle fiber type. Extrapolating these findings, CHC22 and GLUT4 can be considered markers of muscle regeneration in humans.
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    VisCap: inference and visualization of germ-line copy-number variants from targeted clinical sequencing data
    (Nature Publishing Group, 2016) Pugh, Trevor J.; Amr, Sami; Bowser, Mark J.; Gowrisankar, Sivakumar; Hynes, Elizabeth; Mahanta, Lisa M.; Rehm, Heidi; Funke, Birgit; Lebo, Matthew
    Purpose: To develop and validate VisCap, a software program targeted to clinical laboratories for inference and visualization of germ-line copy-number variants (CNVs) from targeted next-generation sequencing data. Genet Med 18 7, 712–719. Methods: VisCap calculates the fraction of overall sequence coverage assigned to genomic intervals and computes log2 ratios of these values to the median of reference samples profiled using the same test configuration. Candidate CNVs are called when log2 ratios exceed user-defined thresholds. Genet Med 18 7, 712–719. Results: We optimized VisCap using 14 cases with known CNVs, followed by prospective analysis of 1,104 cases referred for diagnostic DNA sequencing. To verify calls in the prospective cohort, we used droplet digital polymerase chain reaction (PCR) to confirm 10/27 candidate CNVs and 72/72 copy-neutral genomic regions scored by VisCap. We also used a genome-wide bead array to confirm the absence of CNV calls across panels applied to 10 cases. To improve specificity, we instituted a visual scoring system that enabled experienced reviewers to differentiate true-positive from false-positive calls with minimal impact on laboratory workflow. Genet Med 18 7, 712–719. Conclusions: VisCap is a sensitive method for inferring CNVs from targeted sequence data from targeted gene panels. Visual scoring of data underlying CNV calls is a critical step to reduce false-positive calls for follow-up testing. Genet Med 18 7, 712–719.
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    Next generation sequencing‐based copy number analysis reveals low prevalence of deletions and duplications in 46 genes associated with genetic cardiomyopathies
    (John Wiley and Sons Inc., 2015) Ceyhan‐Birsoy, Ozge; Pugh, Trevor J.; Bowser, Mark J.; Hynes, Elizabeth; Frisella, Ashley L.; Mahanta, Lisa M.; Lebo, Matt S.; Amr, Sami; Funke, Birgit
    Abstract Background: Diagnostic testing for genetic cardiomyopathies has undergone dramatic changes in the last decade with next generation sequencing (NGS) expanding the number of genes that can be interrogated simultaneously. Exon resolution copy number analysis is increasingly incorporated into routine diagnostic testing via cytogenomic arrays and more recently via NGS. While NGS is an attractive option for laboratories that have no access to array platforms, its higher false positive rate requires weighing the added cost incurred by orthogonal confirmation against the magnitude of the increase in diagnostic yield. Although copy number variants (CNVs) have been reported in various cardiomyopathy genes, their contribution has not been systematically studied. Methods: We performed single exon resolution NGS‐based deletion/duplication analysis for up to 46 cardiomyopathy genes in >1400 individuals with cardiomyopathies including HCM, DCM, ARVC, RCM, and LVNC. Results and Conclusion Clinically significant deletions and duplications were identified in only 9 of 1425 (0.63%) individuals. The majority of those (6/9) represented intragenic events. We conclude that the added benefit of exon level deletion/duplication analysis is low for currently known cardiomyopathy genes and may not outweigh the increased cost and complexity of incorporating it into routine diagnostic testing for these disorders.
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    The Changing Landscape of Molecular Diagnostic Testing: Implications for Academic Medical Centers
    (MDPI, 2016) Rehm, Heidi; Hynes, Elizabeth; Funke, Birgit
    Over the last decade, the field of molecular diagnostics has undergone tremendous transformation, catalyzed by the clinical implementation of next generation sequencing (NGS). As technical capabilities are enhanced and current limitations are addressed, NGS is increasingly capable of detecting most variant types and will therefore continue to consolidate and simplify diagnostic testing. It is likely that genome sequencing will eventually serve as a universal first line test for disorders with a suspected genetic origin. Academic Medical Centers (AMCs), which have been at the forefront of this paradigm shift are now presented with challenges to keep up with increasing technical, bioinformatic and interpretive complexity of NGS-based tests in a highly competitive market. Additional complexity may arise from altered regulatory oversight, also triggered by the unprecedented scope of NGS-based testing, which requires new approaches. However, these challenges are balanced by unique opportunities, particularly at the interface between clinical and research operations, where AMCs can capitalize on access to cutting edge research environments and establish collaborations to facilitate rapid diagnostic innovation. This article reviews present and future challenges and opportunities for AMC associated molecular diagnostic laboratories from the perspective of the Partners HealthCare Laboratory for Molecular Medicine (LMM).
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    COMT Genetic Variation Confers Risk for Psychotic and Affective Disorders: A Case Control Study
    (BioMed Central, 2005) Funke, Birgit; Malhotra, Anil K; Finn, Christine; Plocik, Alex M; Lake, Stephen L; Lencz, Todd; DeRosse, Pamela; Kane, John M.; Kucherlapati, Raju
    Background: Variation in the COMT gene has been implicated in a number of psychiatric disorders, including psychotic, affective and anxiety disorders. The majority of these studies have focused on the functional Val108/158Met polymorphism and yielded conflicting results, with limited studies examining the relationship between other polymorphisms, or haplotypes, and psychiatric illness. We hypothesized that COMT variation may confer a general risk for psychiatric disorders and have genotyped four COMT variants (Val158Met, rs737865, rs165599, and a SNP in the P2 promoter [-278A/G; rs2097603]) in 394 Caucasian cases and 467 controls. Cases included patients with schizophrenia (n = 196), schizoaffective disorder (n = 62), bipolar disorder (n = 82), major depression (n = 30), and patients diagnosed with either psychotic disorder NOS or depressive disorder NOS (n = 24). Results: SNP rs2097603, the Val/Met variant and SNP rs165599 were significantly associated (p = 0.004; p = 0.05; p = 0.035) with a broad "all affected" diagnosis. Haplotype analysis revealed a potentially protective G-A-A-A haplotype haplotype (-278A/G; rs737865; Val108/158Met; rs165599), which was significantly underrepresented in this group (p = 0.0033) and contained the opposite alleles of the risk haplotype previously described by Shifman et al. Analysis of diagnostic subgroups within the "all affecteds group" showed an association of COMT in patients with psychotic disorders as well as in cases with affective illness although the associated variants differed. The protective haplotype remained significantly underrepresented in most of these subgroups. Conclusion: Our results support the view that COMT variation provides a weak general predisposition to neuropsychiatric disease including psychotic and affective disorders.
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    Adaptation and validation of the ACMG/AMP variant classification framework for MYH7-associated inherited cardiomyopathies: recommendations by ClinGen’s Inherited Cardiomyopathy Expert Panel
    (Nature Publishing Group, 2018) Kelly, Melissa A; Caleshu, Colleen; Morales, Ana; Buchan, Jillian; Wolf, Zena; Harrison, Steven M; Cook, Stuart; Dillon, Mitchell W; Garcia, John; Haverfield, Eden; Jongbloed, Jan D H; Macaya, Daniela; Manrai, Arjun; Orland, Kate; Richard, Gabriele; Spoonamore, Katherine; Thomas, Matthew; Thomson, Kate; Vincent, Lisa M; Walsh, Roddy; Watkins, Hugh; Whiffin, Nicola; Ingles, Jodie; van Tintelen, J Peter; Semsarian, Christopher; Ware, James S; Hershberger, Ray; Funke, Birgit
    Purpose Integrating genomic sequencing in clinical care requires standardization of variant interpretation practices. The Clinical Genome Resource has established expert panels to adapt the American College of Medical Genetics and Genomics/Association for Molecular Pathology classification framework for specific genes and diseases. The Cardiomyopathy Expert Panel selected MYH7, a key contributor to inherited cardiomyopathies, as a pilot gene to develop a broadly applicable approach. Methods: Expert revisions were tested with 60 variants using a structured double review by pairs of clinical and diagnostic laboratory experts. Final consensus rules were established via iterative discussions. Results: Adjustments represented disease-/gene-informed specifications (12) or strength adjustments of existing rules (5). Nine rules were deemed not applicable. Key specifications included quantitative frameworks for minor allele frequency thresholds, the use of segregation data, and a semiquantitative approach to counting multiple independent variant occurrences where fully controlled case-control studies are lacking. Initial inter-expert classification concordance was 93%. Internal data from participating diagnostic laboratories changed the classification of 20% of the variants (n = 12), highlighting the critical importance of data sharing. Conclusion: These adapted rules provide increased specificity for use in MYH7-associated disorders in combination with expert review and clinical judgment and serve as a stepping stone for genes and disorders with similar genetic and clinical characteristics.
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    Using high-resolution variant frequencies to empower clinical genome interpretation
    (Nature Publishing Group, 2017) Whiffin, Nicola; Minikel, Eric; Walsh, Roddy; O’Donnell-Luria, Anne H; Karczewski, Konrad; Ing, Alexander Y; Barton, Paul J R; Funke, Birgit; Cook, Stuart A; MacArthur, Daniel; Ware, James S
    Purpose Whole-exome and whole-genome sequencing have transformed the discovery of genetic variants that cause human Mendelian disease, but discriminating pathogenic from benign variants remains a daunting challenge. Rarity is recognized as a necessary, although not sufficient, criterion for pathogenicity, but frequency cutoffs used in Mendelian analysis are often arbitrary and overly lenient. Recent very large reference datasets, such as the Exome Aggregation Consortium (ExAC), provide an unprecedented opportunity to obtain robust frequency estimates even for very rare variants. Methods: We present a statistical framework for the frequency-based filtering of candidate disease-causing variants, accounting for disease prevalence, genetic and allelic heterogeneity, inheritance mode, penetrance, and sampling variance in reference datasets. Results: Using the example of cardiomyopathy, we show that our approach reduces by two-thirds the number of candidate variants under consideration in the average exome, without removing true pathogenic variants (false-positive rate<0.001). Conclusion: We outline a statistically robust framework for assessing whether a variant is “too common” to be causative for a Mendelian disorder of interest. We present precomputed allele frequency cutoffs for all variants in the ExAC dataset.