80 results on '"Posey J"'
Search Results
2. Loss of Vascular EC-SOD Is Protective Against PH in the Sugen Hypoxia Model of Pulmonary Hypertension Through Changes in Mitochondrial Respiration Mediated by p-AMPK
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Colon Hidalgo, D., primary, Burciaga, S., additional, Dee, N., additional, Elajaili, H.B., additional, Jordan, M., additional, Posey, J., additional, Jonscher, R., additional, Sparagna, G., additional, Sucharov, C., additional, Delaney, C., additional, and Nozik, E., additional
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- 2023
- Full Text
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3. Sleep deprivation affects reactivity to positive but not negative stimuli
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Pilcher, June J., Callan, Christina, and Posey, J. Laura
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- 2015
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4. Multiregion whole-exome sequencing of matched primary and metastatic tumors revealed genomic heterogeneity and suggested polyclonal seeding in colorectal cancer metastasis
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Wei, Q., Ye, Z., Zhong, X., Li, L., Wang, C., Myers, R. E., Palazzo, J. P., Fortuna, D., Yan, A., Waldman, S. A., Chen, X., Posey, J. A., Basu-Mallick, A., Jiang, B. H., Hou, L., Shu, J., Sun, Y., Xing, J., Li, B., and Yang, H.
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- 2017
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5. The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: a genotypic analysis
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Walker, TM, Miotto, P, Koser, CU, Fowler, PW, Knaggs, J, Iqbal, Z, Hunt, M, Chindelevitch, L, Farhat, MR, Cirillo, DM, Comas, I, Posey, J, Omar, SV, Peto, TEA, Suresh, A, Uplekar, S, Laurent, S, Colman, RE, Nathanson, C-M, Zignol, M, Walker, AS, Crook, DW, Ismail, N, Rodwell, TC, Walker, TM, Miotto, P, Koser, CU, Fowler, PW, Knaggs, J, Iqbal, Z, Hunt, M, Chindelevitch, L, Farhat, MR, Cirillo, DM, Comas, I, Posey, J, Omar, SV, Peto, TEA, Suresh, A, Uplekar, S, Laurent, S, Colman, RE, Nathanson, C-M, Zignol, M, Walker, AS, Crook, DW, Ismail, N, and Rodwell, TC
- Abstract
BACKGROUND: Molecular diagnostics are considered the most promising route to achieving rapid, universal drug susceptibility testing for Mycobacterium tuberculosiscomplex (MTBC). We aimed to generate a WHO endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction. METHODS: A candidate gene approach was used to identify mutations as associated with resistance, or consistent with susceptibility, for 13 WHO endorsed anti-tuberculosis drugs. 38,215 MTBC isolates with paired whole-genome sequencing and phenotypic drug susceptibility testing data were amassed from 45 countries. For each mutation, a contingency table of binary phenotypes and presence or absence of the mutation computed positive predictive value, and Fisher's exact tests generated odds ratios and Benjamini-Hochberg corrected p-values. Mutations were graded as Associated with Resistance if present in at least 5 isolates, if the odds ratio was >1 with a statistically significant corrected p-value, and if the lower bound of the 95% confidence interval on the positive predictive value for phenotypic resistance was >25%. A series of expert rules were applied for final confidence grading of each mutation. FINDINGS: 15,667 associations were computed for 13,211 unique mutations linked to one or more drugs. 1,149/15,667 (7·3%) mutations were classified as associated with phenotypic resistance and 107/15,667 (0·7%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was >80%. Specificity was over 95% for all drugs except ethionamide (91·4%), moxifloxacin (91·6%) and ethambutol (93·3%). Only two resistance mutations were classified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs. INTERPRETATION: This first WHO endorsed catalogue of molecular targets for MTBC drug susceptibility
- Published
- 2022
6. Loss of Vascular EC-SOD Is Associated with Worse RV Hypertrophy and Decreased Mitochondrial Content in a Model of Pulmonary Hypertension
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Colon Hidalgo, D., primary, Dee, N., additional, Elajaili, H., additional, Hernandez, L., additional, Jordan, M., additional, Posey, J., additional, Delaney, C., additional, and Nozik, E., additional
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- 2022
- Full Text
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7. Catalogue of mutations in Mycobacterium tuberculosis complex and their association with drug resistance
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Rodwell, T, Miotto, P, Köser, C, Walker, T, Fowler, PW, Knaggs, J, Iqbal, Z, Hunt, M, Chindelevitch, L, Farhat, M, Cirillo, D, Crook, D, Comas, I, Posey, J, Vally Omar, S, Peto, T, Walker, A, Suresh, A, Uplekar, S, Laurent, S, and Colman, R
- Abstract
Of the 10 million people estimated to have fallen ill with tuberculosis (TB) in 2019, nearly half million developed TB resistant to rifampicin (RIF), and over one million developed TB susceptible to RIF but resistant to isoniazid (INH). Drug resistance must be detected rapidly and accurately to initiate appropriate and effective treatment. The detection of RIF resistance has improved significantly in the past decade with the introduction of rapid diagnostic tools based on DNA detection. The introduction of these tests has dramatically increased the number of TB patients tested for RIF resistance, leading to a 129% increase of individuals started on second-line TB treatment between 2012 and 2019. The majority of patients with RIF-resistant TB can be detected by analysing the 81-base pair fragment of the rpoB gene region. However, the situation is not that clear for other anti-TB drugs due to the lack of knowledge of how phenotypic resistance is associated with mutations in the Mycobacterium tuberculosis (Mtb) genome. In response to this issue the WHO has developed a catalogue of Mtb mutations in the and their association with phenotypic drug resistance. The catalogue provides a reference standard for the interpretation of mutations conferring resistance to all first-line and a variety of second-line drugs. The report summarises the analysis of over 38,000 isolates with matched data on whole genome sequencing and phenotypic drug susceptibility testing from over 40 countries for 13 anti-TB medicines. It lists over 17,000 mutations, their frequency and association with or not with resistance and includes methods used, mutations identified and summaries of important findings for each drug. Tuberculosis laboratories around the world can use the catalogue as a support in the interpretation of genome sequencing results. The catalogue can also guide the development of new molecular drug susceptibility tests, including next-generation sequencing.
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- 2021
8. Alternative genomic diagnoses for individuals with a clinical diagnosis of Dubowitz syndrome
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Dyment, D. A. (David A.), O'Donnell-Luria, A. (Anne), Agrawal, P. B. (Pankaj B.), Coban Akdemir, Z. (Zeynep), Aleck, K. A. (Kyrieckos A.), Antaki, D. (Danny), Al Sharhan, H. (Hind), Au, P. B. (Ping-Yee B.), Aydin, H. (Hatip), Beggs, A. H. (Alan H.), Bilguvar, K. (Kaya), Boerwinkle, E. (Eric), Brand, H. (Harrison), Brownstein, C. A. (Catherine A.), Buyske, S. (Steve), Chodirker, B. (Bernard), Choi, J. (Jungmin), Chudley, A. E. (Albert E.), Clericuzio, C. L. (Carol L.), Cox, G. F. (Gerald F.), Curry, C. (Cynthia), De Boer, E. (Elke), De Vries, B. B. (Bert B. A.), Dunn, K. (Kathryn), Dutmer, C. M. (Cullen M.), England, E. M. (Eleina M.), Fahrner, J. A. (Jill A.), Geckinli, B. B. (Bilgen B.), Genetti, C. A. (Casie A.), Gezdirici, A. (Alper), Gibson, W. T. (William T.), Gleeson, J. G. (Joseph G.), Greenberg, C. R. (Cheryl R.), Hall, A. (April), Hamosh, A. (Ada), Hartley, T. (Taila), Jhangiani, S. N. (Shalini N.), Karaca, E. (Ender), Kernohan, K. (Kristin), Lauzon, J. L. (Julie L.), Lewis, M. E. (M. E. Suzanne), Lowry, R. B. (R. Brian), López-Giráldez, F. (Francesc), Matise, T. C. (Tara C.), McEvoy-Venneri, J. (Jennifer), McInnes, B. (Brenda), Mhanni, A. (Aziz), Garcia Minaur, S. (Sixto), Moilanen, J. (Jukka), Nguyen, A. (An), Nowaczyk, M. J. (Malgorzata J. M.), Posey, J. E. (Jennifer E.), Õunap, K. (Katrin), Pehlivan, D. (Davut), Pajusalu, S. (Sander), Penney, L. S. (Lynette S.), Poterba, T. (Timothy), Prontera, P. (Paolo), Rodovalho Doriqui, M. J. (Maria Juliana), Sawyer, S. L. (Sarah L.), Sobreira, N. (Nara), Stanley, V. (Valentina), Torun, D. (Deniz), Wargowski, D. (David), Witmer, P. D. (P. Dane), Wong, I. (Isaac), Xing, J. (Jinchuan), Zaki, M. S. (Maha S.), Zhang, Y. (Yeting), C. C. (Care4Rare Consortium), C. F. (Centers For Mendelian Genomics), Boycott, K. M. (Kym M.), Bamshad, M. J. (Michael J.), Nickerson, D. A. (Deborah A.), Blue, E. E. (Elizabeth E.), and Innes, A. M. (A. Micheil)
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genetic heterogeneity ,genome sequencing ,Dubowitz syndrome ,exome sequencing ,microarray - Abstract
Dubowitz syndrome (DubS) is considered a recognizable syndrome characterized by a distinctive facial appearance and deficits in growth and development. There have been over 200 individuals reported with Dubowitz or a “Dubowitz-like” condition, although no single gene has been implicated as responsible for its cause. We have performed exome (ES) or genome sequencing (GS) for 31 individuals clinically diagnosed with DubS. After genome-wide sequencing, rare variant filtering and computational and Mendelian genomic analyses, a presumptive molecular diagnosis was made in 13/27 (48%) families. The molecular diagnoses included biallelic variants in SKIV2L, SLC35C1, BRCA1, NSUN2; de novo variants in ARID1B, ARID1A, CREBBP, POGZ, TAF1, HDAC8, and copy-number variation at1p36.11(ARID1A), 8q22.2(VPS13B), Xp22, and Xq13(HDAC8). Variants of unknown significance in known disease genes, and also in genes of uncertain significance, were observed in 7/27 (26%) additional families. Only one gene, HDAC8, could explain the phenotype in more than one family (N = 2). All but two of the genomic diagnoses were for genes discovered, or for conditions recognized, since the introduction of next-generation sequencing. Overall, the DubS-like clinical phenotype is associated with extensive locus heterogeneity and the molecular diagnoses made are for emerging clinical conditions sharing characteristic features that overlap the DubS phenotype.
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- 2021
9. Exome sequencing reveals predominantly de novo variants in disorders with intellectual disability (ID) in the founder population of Finland
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Järvelä, I. (Irma), Määttä, T. (Tuomo), Acharya, A. (Anushree), Leppälä, J. (Juha), Jhangiani, S. N. (Shalini N.), Arvio, M. (Maria), Siren, A. (Auli), Kankuri-Tammilehto, M. (Minna), Kokkonen, H. (Hannaleena), Palomäki, M. (Maarit), Varilo, T. (Teppo), Fang, M. (Mary), Hadley, T. D. (Trevor D), Jolly, A. (Angad), Linnankivi, T. (Tarja), Paetau, R. (Ritva), Saarela, A. (Anni), Kälviäinen, R. (Reetta), Olme, J. (Jan), Nouel-Saied, L. M. (Liz M.), Cornejo-Sanchez, D. M. (Diana M.), Llaci, L. (Lorida), Lupski, J. R. (James R.), Posey, J. E. (Jennifer E.), Leal, S. M. (Suzanne M.), Schrauwen, I. (Isabelle), Järvelä, I. (Irma), Määttä, T. (Tuomo), Acharya, A. (Anushree), Leppälä, J. (Juha), Jhangiani, S. N. (Shalini N.), Arvio, M. (Maria), Siren, A. (Auli), Kankuri-Tammilehto, M. (Minna), Kokkonen, H. (Hannaleena), Palomäki, M. (Maarit), Varilo, T. (Teppo), Fang, M. (Mary), Hadley, T. D. (Trevor D), Jolly, A. (Angad), Linnankivi, T. (Tarja), Paetau, R. (Ritva), Saarela, A. (Anni), Kälviäinen, R. (Reetta), Olme, J. (Jan), Nouel-Saied, L. M. (Liz M.), Cornejo-Sanchez, D. M. (Diana M.), Llaci, L. (Lorida), Lupski, J. R. (James R.), Posey, J. E. (Jennifer E.), Leal, S. M. (Suzanne M.), and Schrauwen, I. (Isabelle)
- Abstract
The genetics of autosomal recessive intellectual disability (ARID) has mainly been studied in consanguineous families, however, founder populations may also be of interest to study intellectual disability (ID) and the contribution of ARID. Here, we used a genotype-driven approach to study the genetic landscape of ID in the founder population of Finland. A total of 39 families with syndromic and non-syndromic ID were analyzed using exome sequencing, which revealed a variant in a known ID gene in 27 families. Notably, 75% of these variants in known ID genes were de novo or suspected de novo (64% autosomal dominant; 11% X-linked) and 25% were inherited (14% autosomal recessive; 7% X-linked; and 4% autosomal dominant). A dual molecular diagnosis was suggested in two families (5%). Via additional analysis and molecular testing, we identified three cases with an abnormal molecular karyotype, including chr21q22.12q22.2 uniparental disomy with a mosaic interstitial 2.7 Mb deletion covering DYRK1A and KCNJ6. Overall, a pathogenic or likely pathogenic variant was identified in 64% (25/39) of the families. Last, we report an alternate inheritance model for 3 known ID genes (UBA7, DDX47, DHX58) and discuss potential candidate genes for ID, including SYPL1 and ERGIC3 with homozygous founder variants and de novo variants in POLR2F and DNAH3. In summary, similar to other European populations, de novo variants were the most common variants underlying ID in the studied Finnish population, with limited contribution of ARID to ID etiology, though mainly driven by founder and potential founder variation in the latter case.
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- 2021
10. The Presence of Circulating Tumor DNA in Ovarian Cancer Patients After Platinum-Based Chemotherapy
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Eakin, C., primary, Sun, K., additional, Shan, M., additional, Zhou, Y., additional, Feng, B., additional, Wang, S., additional, Posey, J., additional, Rubio, M., additional, Garg, K., additional, Thress, K.S., additional, Wang, J., additional, and Monk, B.J., additional
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- 2020
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11. Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase (vol 8, 15382, 2018)
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Ezewudo M, Borens A, Chiner-Oms Á, Miotto P, Chindelevitch L, Starks AM, Hanna D, Liwski R, Zignol M, Gilpin C, Niemann S, Kohl TA, Warren RM, Crook D, Gagneux S, Hoffner S, Rodrigues C, Comas I, Engelthaler DM, Alland D, Rigouts L, Lange C, Dheda K, Hasan R, McNerney R, Cirillo DM, Schito M, Rodwell TC, and Posey J
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- 2020
12. Multi-Label Random Forest Model for Tuberculosis Drug Resistance Classification and Mutation Ranking
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Kouchaki, S, Yang, Y, Lachapelle, A, Walker, T, Walker, SA, Hoosdally, S, Gibertoni Cruz, AL, Carter, J, Grazian, C, Earle, SG, Fowler, P, Iqbal, Z, Hunt, M, Knaggs, J, Smith, GE, Rathod, P, Jarrett, L, Matias, D, Cirillo, DM, Borroni, E, Battaglia, S, Ghodousi, A, Spitaler, A, Cabibbe, A, Tahseen, S, Nilgiriwala, K, Shah, S, Rodrigues, C, Kambli, P, Surve, U, Khot, R, Niemann, S, Merker, M, Hoffmann, H, Todt, K, Plesnik, S, Ismail, N, Omar, SV, Joseph, L, Thwaites, G, Thuong, TNT, Ngoc, NH, Srinivasan, V, Moore, D, Coronel, J, Solano, W, Gao, GF, He, G, Zhao, Y, Liu, C, Ma, A, Zhu, B, Laurenson, I, Claxton, P, Koch, A, Wilkinson, R, Lalvani, A, Posey, J, Gardy, J, Werngren, J, Paton, N, Jou, R, Wu, MH, Lin, WH, Ferrazoli, L, Siqueira de Oliveira, R, Arandjelovic, I, Chaiprasert, A, Comas, I, Roig, CR, Drobniewski, FA, Farhat, MR, Gao, Q, Hee, ROT, Sintchenko, V, Supply, P, van Soolingen, D, Peto, TEA, Crook, D, Clifton, D, Kouchaki, S, Yang, Y, Lachapelle, A, Walker, T, Walker, SA, Hoosdally, S, Gibertoni Cruz, AL, Carter, J, Grazian, C, Earle, SG, Fowler, P, Iqbal, Z, Hunt, M, Knaggs, J, Smith, GE, Rathod, P, Jarrett, L, Matias, D, Cirillo, DM, Borroni, E, Battaglia, S, Ghodousi, A, Spitaler, A, Cabibbe, A, Tahseen, S, Nilgiriwala, K, Shah, S, Rodrigues, C, Kambli, P, Surve, U, Khot, R, Niemann, S, Merker, M, Hoffmann, H, Todt, K, Plesnik, S, Ismail, N, Omar, SV, Joseph, L, Thwaites, G, Thuong, TNT, Ngoc, NH, Srinivasan, V, Moore, D, Coronel, J, Solano, W, Gao, GF, He, G, Zhao, Y, Liu, C, Ma, A, Zhu, B, Laurenson, I, Claxton, P, Koch, A, Wilkinson, R, Lalvani, A, Posey, J, Gardy, J, Werngren, J, Paton, N, Jou, R, Wu, MH, Lin, WH, Ferrazoli, L, Siqueira de Oliveira, R, Arandjelovic, I, Chaiprasert, A, Comas, I, Roig, CR, Drobniewski, FA, Farhat, MR, Gao, Q, Hee, ROT, Sintchenko, V, Supply, P, van Soolingen, D, Peto, TEA, Crook, D, and Clifton, D
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- 2020
13. GenomegaMap: within-species genome-wide d_N/d_S estimation from over 10,000 genomes
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Wilson, D, Crook, DW, Peto, TEA, Walker, AS, Hoosdally, SJ, Gibertoni Cruz, AL, Carter, J, Grazian, C, Earle, SG, Kouchaki, S, Lachapelle, A, Yang, Y, Clifton, DA, Fowler, PW, Iqbal, Z, Hunt, M, Knaggs, J, Smith, EG, Rathod, P, Jarrett, L, Matias, D, Cirillo, DM, Borroni, E, Battaglia, S, Ghodousi, A, Spitaleri, A, Cabibbe, A, Tahseen, S, Nilgiriwala, K, Shah, S, Rodrigues, C, Kambli, P, Surve, U, Khot, R, NIemann, S, Kohl, TA, Merker, M, Hoffman, H, Todt, K, Plesnik, S, Ismail, N, Omar, SV, Joseph, L, Thwaites, G, Thoung, TNT, Ngoc, NH, Srinivasan, V, Walker, TM, Moore, D, Coronel, J, Solano, W, Gao, GF, He, G, Zhao, Y, Liu, C, Ma, A, Zhu, B, Laurenson, I, Claxton, P, Koch, A, Wilkinson, R, Lalvani, A, Posey, J, Gardy, J, Werngren, J, Paton, N, Jou, R, Wu, MH, Lin, WH, Ferrazoli, L, Siqueira de Oliveira, R, Arandjelovic, I, Chaipresert, A, Comas, I, Roig, CJ, Drobniewski, FA, Farhat, MR, Gao, Q, Hee, ROT, Sintchenko, V, Wilson, D, Crook, DW, Peto, TEA, Walker, AS, Hoosdally, SJ, Gibertoni Cruz, AL, Carter, J, Grazian, C, Earle, SG, Kouchaki, S, Lachapelle, A, Yang, Y, Clifton, DA, Fowler, PW, Iqbal, Z, Hunt, M, Knaggs, J, Smith, EG, Rathod, P, Jarrett, L, Matias, D, Cirillo, DM, Borroni, E, Battaglia, S, Ghodousi, A, Spitaleri, A, Cabibbe, A, Tahseen, S, Nilgiriwala, K, Shah, S, Rodrigues, C, Kambli, P, Surve, U, Khot, R, NIemann, S, Kohl, TA, Merker, M, Hoffman, H, Todt, K, Plesnik, S, Ismail, N, Omar, SV, Joseph, L, Thwaites, G, Thoung, TNT, Ngoc, NH, Srinivasan, V, Walker, TM, Moore, D, Coronel, J, Solano, W, Gao, GF, He, G, Zhao, Y, Liu, C, Ma, A, Zhu, B, Laurenson, I, Claxton, P, Koch, A, Wilkinson, R, Lalvani, A, Posey, J, Gardy, J, Werngren, J, Paton, N, Jou, R, Wu, MH, Lin, WH, Ferrazoli, L, Siqueira de Oliveira, R, Arandjelovic, I, Chaipresert, A, Comas, I, Roig, CJ, Drobniewski, FA, Farhat, MR, Gao, Q, Hee, ROT, and Sintchenko, V
- Abstract
The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters such as dN/dS, but analysing very large datasets poses a major statistical challenge. Here I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: (i) it is fast no matter how large the sample size and (ii) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well-estimated even when genomegaMap’s simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in M. tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species.
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- 2020
14. Biallelic and monoallelic variants in PLXNA1 cause a syndromic disorder with neurodevelopmental and oculo-cerebral anomalies
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Dworschak, G. C., Punetha, J., Kalanithy, J. C., Mingardo, E., Erdem, H. B., Akdemir, Z. C., Karaca, E., Mitani, T., Marafi, D., Fatih, J. M., Jhangiani, S. N., Hunter, J. V., Dakal, T., Dhabhai, B., Dabbagh, O., Alsaif, H. S., Alkuraya, F. S., Maroofian, R., Houlden, H., Efthymiou, S., Dominik, N., Salpietro, V., Sultan, T., Haider, S., Bibi, F., Thiele, H., Hoefele, J., Riedhammer, K. M., Wagner, M., Guella, I., Demos, M., Keren, B., Buratti, J., Charles, P., Nava, C., Valkanas, E., Waddell, L. B., Jones, K. J., Oates, E. C., Cooper, S. T., MacArthur, D., Schnur, R. E., Hoganson, G. E., Burton, J. E., McEntagart, M., Pehlivan, D., Posey, J. E., Lupski, J. R., Reutter, H., Dworschak, G. C., Punetha, J., Kalanithy, J. C., Mingardo, E., Erdem, H. B., Akdemir, Z. C., Karaca, E., Mitani, T., Marafi, D., Fatih, J. M., Jhangiani, S. N., Hunter, J. V., Dakal, T., Dhabhai, B., Dabbagh, O., Alsaif, H. S., Alkuraya, F. S., Maroofian, R., Houlden, H., Efthymiou, S., Dominik, N., Salpietro, V., Sultan, T., Haider, S., Bibi, F., Thiele, H., Hoefele, J., Riedhammer, K. M., Wagner, M., Guella, I., Demos, M., Keren, B., Buratti, J., Charles, P., Nava, C., Valkanas, E., Waddell, L. B., Jones, K. J., Oates, E. C., Cooper, S. T., MacArthur, D., Schnur, R. E., Hoganson, G. E., Burton, J. E., McEntagart, M., Pehlivan, D., Posey, J. E., Lupski, J. R., and Reutter, H.
- Published
- 2020
15. DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis
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Yang, Y, Walker, TM, Walker, AS, Wilson, DJ, Peto, TEA, Crook, DW, Shamout, F, Zhu, T, Clifton, DA, Arandjelovic, I, Comas, I, Farhat, MR, Gao, Q, Sintchenko, V, Van Soolingen, D, Hoosdally, S, Cruz, ALG, Carter, J, Grazian, C, Earle, SG, Kouchaki, S, Fowler, PW, Iqbal, Z, Hunt, M, Smith, EG, Rathod, P, Jarrett, L, Matias, D, Cirillo, DM, Borroni, E, Battaglia, S, Ghodousi, A, Spitaleri, A, Cabibbe, A, Tahseen, S, Nilgiriwala, K, Shah, S, Rodrigues, C, Kambli, P, Surve, U, Khot, R, Niemann, S, Kohl, T, Merker, M, Hoffmann, H, Molodtsov, N, Plesnik, S, Ismail, N, Omar, SV, Thwaites, G, Thuong, NTT, Nhung, HN, Srinivasan, V, Moore, D, Coronel, J, Solano, W, Gao, GF, He, G, Zhao, Y, Ma, A, Liu, C, Zhu, B, Laurenson, I, Claxton, P, Koch, A, Wilkinson, R, Lalvani, A, Posey, J, Gardy, J, Werngren, J, Paton, N, Jou, R, Wu, M-H, Lin, W-H, Ferrazoli, L, De Oliveira, RS, and Wellcome Trust
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DRUG-RESISTANCE ,Technology ,Biochemistry & Molecular Biology ,Science & Technology ,INFORMATION ,MUTATIONS ,CRyPTIC Consortium ,Bioinformatics ,Statistics & Probability ,SUSCEPTIBILITY ,06 Biological Sciences ,GENE ,Biochemical Research Methods ,CLASSIFICATION ,DIMENSIONALITY REDUCTION ,Biotechnology & Applied Microbiology ,Physical Sciences ,Computer Science ,Computer Science, Interdisciplinary Applications ,Mathematical & Computational Biology ,08 Information and Computing Sciences ,Life Sciences & Biomedicine ,Mathematics ,01 Mathematical Sciences - Abstract
Motivation Resistance co-occurrence within first-line anti-tuberculosis (TB) drugs is a common phenomenon. Existing methods based on genetic data analysis of Mycobacterium tuberculosis (MTB) have been able to predict resistance of MTB to individual drugs, but have not considered the resistance co-occurrence and cannot capture latent structure of genomic data that corresponds to lineages. Results We used a large cohort of TB patients from 16 countries across six continents where whole-genome sequences for each isolate and associated phenotype to anti-TB drugs were obtained using drug susceptibility testing recommended by the World Health Organization. We then proposed an end-to-end multi-task model with deep denoising auto-encoder (DeepAMR) for multiple drug classification and developed DeepAMR_cluster, a clustering variant based on DeepAMR, for learning clusters in latent space of the data. The results showed that DeepAMR outperformed baseline model and four machine learning models with mean AUROC from 94.4% to 98.7% for predicting resistance to four first-line drugs [i.e. isoniazid (INH), ethambutol (EMB), rifampicin (RIF), pyrazinamide (PZA)], multi-drug resistant TB (MDR-TB) and pan-susceptible TB (PANS-TB: MTB that is susceptible to all four first-line anti-TB drugs). In the case of INH, EMB, PZA and MDR-TB, DeepAMR achieved its best mean sensitivity of 94.3%, 91.5%, 87.3% and 96.3%, respectively. While in the case of RIF and PANS-TB, it generated 94.2% and 92.2% sensitivity, which were lower than baseline model by 0.7% and 1.9%, respectively. t-SNE visualization shows that DeepAMR_cluster captures lineage-related clusters in the latent space. Availability and implementation The details of source code are provided at http://www.robots.ox.ac.uk/∼davidc/code.php.
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- 2019
16. GenomegaMap: within-species genome-widedN/dSestimation from over 10,000 genomes
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Wilson, DJ, Crook, DW, Peto, TEA, Walker, AS, Hoosdally, SJ, Gibertoni Cruz, AL, Carter, J, Grazian, C, Earle, SG, Kouchaki, S, Lachapelle, A, Yang, Y, Clifton, DA, Fowler, PW, Iqbal, Z, Hunt, M, Knaggs, J, Smith, EG, Rathod, P, Jarrett, L, Matias, D, Cirillo, DM, Borroni, E, Battaglia, S, Ghodousi, A, Spitaleri, A, Cabibbe, A, Tahseen, S, Nilgiriwala, K, Shah, S, Rodrigues, C, Kambli, P, Surve, U, Khot, R, Niemann, S, Kohl, TA, Merker, M, Hoffmann, H, Todt, K, Plesnik, S, Ismail, N, Omar, SV, Joseph, L, Thwaites, G, Thuong, TNT, Ngoc, NH, Srinivasan, V, Walker, TM, Moore, D, Coronel, J, Solano, W, Gao, GF, He, G, Zhao, Y, Liu, C, Ma, A, Zhu, B, Laurenson, I, Claxton, P, Koch, A, Wilkinson, R, Lalvani, A, Posey, J, Gardy, J, Werngren, J, Paton, N, Jou, R, Wu, M-H, Lin, W-H, Ferrazoli, L, De Oliveira, RS, Arandjelovic, I, Chaiprasert, A, Comas, I, Roig, CJ, Drobniewski, FA, Farhat, MR, Gao, Q, Hee, ROT, Sintchenko, V, Supply, P, Van Soolingen, D, University of Oxford, Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 (CIIL), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Centre National de la Recherche Scientifique (CNRS), D.J.W. is a Sir Henry Dale Fellow, jointly funded by the Wellcome Trust and the Royal Society (grant no. 101237/Z/13/B) and is a Big Data Institute Robertson Fellow. The CRyPTIC Consortium was supported by grants from the Bill and Melinda Gates Foundation (OPP1133541) and a Wellcome Trust/Newton Fund-MRC Collaborative Award (200205/Z/15/Z). F.A.D. was supported by the Imperial Biomedical Research Centre., Members of the CRyPTIC Consortium : Derrick W. Crook, Timothy E.A. Peto, A. Sarah Walker, Sarah J. Hoosdally, Ana L. Gibertoni Cruz, Joshua Carter, Clara Grazian, Sarah G. Earle, Samaneh Kouchaki, Alexander Lachapelle, Yang Yang, David A. Clifton, and Philip W. Fowler, University of Oxford, Zamin Iqbal, Martin Hunt, and Jeffrey Knaggs, European Bioinformatics Institute, E. Grace Smith, Priti Rathod, Lisa Jarrett, and Daniela Matias, Public Health England, Birmingham, Daniela M. Cirillo, Emanuele Borroni, Simone Battaglia, Arash Ghodousi, Andrea Spitaleri, and Andrea Cabibbe, Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Sabira Tahseen, National Tuberculosis Control Program Pakistan, Islamabad, Kayzad Nilgiriwala and Sanchi Shah, The Foundation for Medical Research, Mumbai, Camilla Rodrigues, Priti Kambli, Utkarsha Surve, and Rukhsar Khot, P.D. Hinduja National Hospital and Medical Research Centre, Mumbai, Stefan Niemann, Thomas A. Kohl, and Matthias Merker, Research Center Borstel, Harald Hoffmann, Katharina Todt, and Sara Plesnik, Institute of Microbiology & Laboratory Medicine, IML Red, Gauting, Nazir Ismail, Shaheed Vally Omar, and Lavania Joseph, National Institute for Communicable Diseases, Johannesburg, Guy Thwaites, Thuong Nguyen Thuy Thuong, Nhung Hoang Ngoc, Vijay Srinivasan, and Timothy M. Walker, Oxford University Clinical Research Unit, Ho Chi Minh City, David Moore, Jorge Coronel and Walter Solano, London School of Hygiene and Tropical Medicine and Universidad Peruana Cayetano Heredá, Lima, George F. Gao, Guangxue He, Yanlin Zhao, and Chunfa Liu, China CDC, Beijing, Aijing Ma, Shenzhen Third People’s Hospital, Shenzhen, Baoli Zhu, Institute of Microbiology, CAS, Beijing, Ian Laurenson and Pauline Claxton, Scottish Mycobacteria Reference Laboratory, Edinburgh, Anastasia Koch, Robert Wilkinson, University of Cape Town, Ajit Lalvani, Imperial College London, James Posey, CDC Atlanta, Jennifer Gardy, University of British Columbia, Jim Werngren, Public Health Agency of Sweden, Nicholas Paton, National University of Singapore, Ruwen Jou, Mei-Hua Wu, Wan-Hsuan Lin, CDC Taiwan, Lucilaine Ferrazoli, Rosangela Siqueira de Oliveira, Institute Adolfo Lutz, São Paulo. Authors contributing to the CRyPTIC Consortium are (in alphabetical order): Irena Arandjelovic (Institute of Microbiology and Immunology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia), Angkana Chaiprasert (Faculty of Medicine Siriraj Hospital, Mahidol University, Thailand), Iñaki Comas (Instituto de Biomedicina de Valencia [IBV-CSIC], Calle Jaime Roig, Valencia, Spain, FISABIO Public Health, Valencia, Spain, CIBER in Epidemiology and Public Health, Madrid, Spain), Francis A. Drobniewski (Imperial College, London, UK), Maha R. Farhat (Harvard Medical School, Boston, USA), Qian Gao (Shanghai Medical College, Fudan University, Shanghai, China), Rick Ong Twee Hee (Saw Swee Hock School of Public Health, National University of Singapore, Singapore), Vitali Sintchenko (Centre for Infectious Diseases and Microbiology—Public Health, University of Sydney, Sydney, Australia), Philip Supply (Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, U1019—UMR 8204—CIIL—Centre d’Infection et d’Immunité de Lille, F-59000 Lille, France), and Dick van Soolingen (National Institute for Public Health and the Environment [RIVM], Bilthoven, The Netherlands)., Supply, Philip, Consortium, CRyPTIC, University of Oxford [Oxford], Centre National de la Recherche Scientifique (CNRS)-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Royal Society (UK), Bill & Melinda Gates Foundation, Newton Fund, Comas, Iñaki [0000-0001-5504-9408], and Comas, Iñaki
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Natural selection ,[SDV]Life Sciences [q-bio] ,Population genetics ,adaptation ,Computational biology ,Biology ,AcademicSubjects/SCI01180 ,0601 Biochemistry and Cell Biology ,Genome ,Coalescent theory ,DEAD-box RNA Helicases ,Big data ,03 medical and health sciences ,0603 Evolutionary Biology ,big data ,Parent-dependent mutation ,Genetics ,dN/dS ,Adaptation ,Selection, Genetic ,Molecular Biology ,Allele frequency ,Ecology, Evolution, Behavior and Systematics ,Silent Mutation ,Selection (genetic algorithm) ,030304 developmental biology ,Evolutionary Biology ,0604 Genetics ,0303 health sciences ,Models, Genetic ,Phylogenetic tree ,030306 microbiology ,AcademicSubjects/SCI01130 ,natural selection ,Mycobacterium tuberculosis ,Recombination ,Resources ,recombination ,3. Good health ,[SDV] Life Sciences [q-bio] ,Genetic Techniques ,Mutation (genetic algorithm) ,parent-dependent mutation ,Genome, Bacterial - Abstract
11 págs, 4 figuras y fórmulas matemáticas. Material suplementario en: http://dx.doi.org/10.1093/molbev/msaa069, The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters, such as dN/dS, but analyzing very large data sets poses a major statistical challenge. Here, I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: 1) It is fast no matter how large the sample size and 2) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well estimated even when genomegaMap's simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in Mycobacterium tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species., D.J.W. is a Sir Henry Dale Fellow, jointly funded by the Wellcome Trust and the Royal Society (grant no. 101237/Z/13/B) and is a Big Data Institute Robertson Fellow. The CRyPTIC Consortium was supported by grants from the Bill and Melinda Gates Foundation (OPP1133541) and a Wellcome Trust/Newton Fund-MRC Collaborative Award (200205/Z/15/Z). F.A.D. was supported by the Imperial Biomedical Research Centre
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- 2019
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17. Analytical performance of the resolution-HRD plasma assay used to identify mCRPC patients with biallelic disruption of DNA repair genes for treatment with niraparib
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Pekker, I., primary, Lim, L., additional, Simon, J.S., additional, Gormley, M., additional, Li, Z., additional, Pollak, J., additional, Potts, K., additional, Watford, S., additional, Posey, J., additional, Chan, P., additional, Urtishak, K., additional, Garg, K., additional, Hosseini, A., additional, and Li, M., additional
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- 2019
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18. Application of machine learning techniques to tuberculosis drug resistance analysis
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Kouchaki, S, Yang, YY, Walker, TM, Walker, AS, Wilson, DJ, Peto, TEA, Crook, DW, Clifton, DA, Hoosdally, SJ, Gibertoni Cruz, AL, Carter, J, Grazian, C, Fowler, PW, Iqbal, Z, Hunt, M, Smith, EG, Rathod, P, Jarrett, L, Matias, D, Cirillo, DM, Borroni, E, Battaglia, S, Ghodousi, A, Spitaleri, A, Cabibbe, A, Tahseen, S, Nilgiriwala, K, Shah, S, Rodrigues, C, Kambli, P, Surve, U, Khot, R, Niemann, S, Kohl, T, Merker, M, Hoffmann, H, Molodtsov, N, Plesnik, S, Ismail, N, Omar, SV, Joseph, L, Marubini, E, Thwaites, G, Thuong, TNT, Ngoc, NH, Srinivasan, V, Moore, D, Coronel, J, Solano, W, Gao, GF, He, G, Zhao, Y, Ma, A, Liu, C, Zhu, B, Laurenson, I, Claxton, P, Wilkinson, RJ, Lalvani, A, Posey, J, Gardy, J, Werngren, J, Paton, N, Jou, R, Wu, MH, Lin, WH, Ferrazoli, L, De Oliveira, RS, Arandjelovic, I, Comas, I, Drobniewski, F, Gao, Q, Sintchenko, V, Supply, P, Van Soolingen, D, Kouchaki, S, Yang, YY, Walker, TM, Walker, AS, Wilson, DJ, Peto, TEA, Crook, DW, Clifton, DA, Hoosdally, SJ, Gibertoni Cruz, AL, Carter, J, Grazian, C, Fowler, PW, Iqbal, Z, Hunt, M, Smith, EG, Rathod, P, Jarrett, L, Matias, D, Cirillo, DM, Borroni, E, Battaglia, S, Ghodousi, A, Spitaleri, A, Cabibbe, A, Tahseen, S, Nilgiriwala, K, Shah, S, Rodrigues, C, Kambli, P, Surve, U, Khot, R, Niemann, S, Kohl, T, Merker, M, Hoffmann, H, Molodtsov, N, Plesnik, S, Ismail, N, Omar, SV, Joseph, L, Marubini, E, Thwaites, G, Thuong, TNT, Ngoc, NH, Srinivasan, V, Moore, D, Coronel, J, Solano, W, Gao, GF, He, G, Zhao, Y, Ma, A, Liu, C, Zhu, B, Laurenson, I, Claxton, P, Wilkinson, RJ, Lalvani, A, Posey, J, Gardy, J, Werngren, J, Paton, N, Jou, R, Wu, MH, Lin, WH, Ferrazoli, L, De Oliveira, RS, Arandjelovic, I, Comas, I, Drobniewski, F, Gao, Q, Sintchenko, V, Supply, P, and Van Soolingen, D
- Abstract
Motivation: Timely identification of Mycobacterium tuberculosis (MTB) resistance to existing drugs is vital to decrease mortality and prevent the amplification of existing antibiotic resistance. Machine learning methods have been widely applied for timely predicting resistance of MTB given a specific drug and identifying resistance markers. However, they have been not validated on a large cohort of MTB samples from multi-centers across the world in terms of resistance prediction and resistance marker identification. Several machine learning classifiers and linear dimension reduction techniques were developed and compared for a cohort of 13 402 isolates collected from 16 countries across 6 continents and tested 11 drugs. Results: Compared to conventional molecular diagnostic test, area under curve of the best machine learning classifier increased for all drugs especially by 23.11%, 15.22% and 10.14% for pyrazinamide, ciprofloxacin and ofloxacin, respectively (P < 0.01). Logistic regression and gradient tree boosting found to perform better than other techniques. Moreover, logistic regression/gradient tree boosting with a sparse principal component analysis/non-negative matrix factorization step compared with the classifier alone enhanced the best performance in terms of F1-score by 12.54%, 4.61%, 7.45% and 9.58% for amikacin, moxifloxacin, ofloxacin and capreomycin, respectively, as well increasing area under curve for amikacin and capreomycin. Results provided a comprehensive comparison of various techniques and confirmed the application of machine learning for better prediction of the large diverse tuberculosis data. Furthermore, mutation ranking showed the possibility of finding new resistance/susceptible markers.
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- 2019
19. EMERGENCE OF BEDAQUILINE RESISTANCE AFTER COMPLETION OF BEDAQUILINE-BASED DRUGRESISTANT TB TREATMENT: A CASE STUDY FROM SOUTH AFRICA
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De Vos, M., primary, Ley, S., additional, Derendinger, B., additional, Dippenaar, A., additional, Grobbelaar, M., additional, Reuter, A., additional, Daniels, J., additional, Burns, S., additional, Theron, G., additional, Posey, J., additional, Warren, R., additional, and Cox, H., additional
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- 2019
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20. WHOLE GENOME SEQUENCING SHEDS LIGHT ON THE TRANSMISSION DYNAMICS OF A MULTIDRUG RESISTANT MYCOBACTERIUM TUBERCULOSIS OUTBREAK OVER 23 YEARS IN A HIGH INCIDENCE SETTING
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Dippenaar, A., primary, Warren, R. M., additional, De Vos, M., additional, Heupink, T., additional, Van Rie, A., additional, Clarke, C., additional, Posey, J., additional, Sampson, S. L., additional, and Streicher, E. M., additional
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- 2019
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21. Detection of Apparent Cell-free M. tuberculosis DNA from Plasma
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Click, E. S., primary, Murithi, W., additional, Ouma, G. S., additional, McCarthy, K., additional, Willby, M., additional, Musau, S., additional, Alexander, H., additional, Pevzner, E., additional, Posey, J., additional, and Cain, K. P., additional
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- 2018
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22. 1412P - Analytical performance of the resolution-HRD plasma assay used to identify mCRPC patients with biallelic disruption of DNA repair genes for treatment with niraparib
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Pekker, I., Lim, L., Simon, J.S., Gormley, M., Li, Z., Pollak, J., Potts, K., Watford, S., Posey, J., Chan, P., Urtishak, K., Garg, K., Hosseini, A., and Li, M.
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- 2019
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23. Genetic Determinants of Drug Resistance in Mycobacterium tuberculosis and Their Diagnostic Value
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Farhat, M.R., Sultana, R., Iartchouk, O., Bozeman, S., Galagan, J., Sisk, P., Stolte, C., Nebenzahl-Guimaraes, H., Jacobson, K., Sloutsky, A., Kaur, D., Posey, J., Kreiswirth, B.N., Kurepina, N., Rigouts, L., Streicher, E.M., Victor, T.C., Warren, R.M., Soolingen, D. van, Murray, M., Farhat, M.R., Sultana, R., Iartchouk, O., Bozeman, S., Galagan, J., Sisk, P., Stolte, C., Nebenzahl-Guimaraes, H., Jacobson, K., Sloutsky, A., Kaur, D., Posey, J., Kreiswirth, B.N., Kurepina, N., Rigouts, L., Streicher, E.M., Victor, T.C., Warren, R.M., Soolingen, D. van, and Murray, M.
- Abstract
Item does not contain fulltext, RATIONALE: The development of molecular diagnostics that detect both the presence of Mycobacterium tuberculosis in clinical samples and drug resistance-conferring mutations promises to revolutionize patient care and interrupt transmission by ensuring early diagnosis. However, these tools require the identification of genetic determinants of resistance to the full range of antituberculosis drugs. OBJECTIVES: To determine the optimal molecular approach needed, we sought to create a comprehensive catalog of resistance mutations and assess their sensitivity and specificity in diagnosing drug resistance. METHODS: We developed and validated molecular inversion probes for DNA capture and deep sequencing of 28 drug-resistance loci in M. tuberculosis. We used the probes for targeted sequencing of a geographically diverse set of 1,397 clinical M. tuberculosis isolates with known drug resistance phenotypes. We identified a minimal set of mutations to predict resistance to first- and second-line antituberculosis drugs and validated our predictions in an independent dataset. We constructed and piloted a web-based database that provides public access to the sequence data and prediction tool. MEASUREMENTS AND MAIN RESULTS: The predicted resistance to rifampicin and isoniazid exceeded 90% sensitivity and specificity but was lower for other drugs. The number of mutations needed to diagnose resistance is large, and for the 13 drugs studied it was 238 across 18 genetic loci. CONCLUSIONS: These data suggest that a comprehensive M. tuberculosis drug resistance diagnostic will need to allow for a high dimension of mutation detection. They also support the hypothesis that currently unknown genetic determinants, potentially discoverable by whole-genome sequencing, encode resistance to second-line tuberculosis drugs.
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- 2016
24. Investigating Genetic Variants in Patients with Left Ventricular Assist Devices for Nonischemic Cardiomyopathy.
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Scott, C., Posey, J., Butac, A., Lamba, H., Oberton, S., Shafii, A., Liao, K., Loor, G., George, J., Simpson, L., Delgado, R., Civitello, A., and Nair, A.
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HEART assist devices , *GENETIC variation , *CARDIOMYOPATHIES , *GENETIC testing , *DILATED cardiomyopathy , *GENETIC mutation - Abstract
To investigate genetic mutations in patients with dilated nonischemic cardiomyopathy (NICM) and history of left ventricular assist device (LVAD) implant. 76 patients were included in this retrospective study. Clinical data was obtained to determine environmental exposures (i.e. infectious, chemotherapy, pregnancy, significant alcohol and drug use), family history, native heart function, and the attributed etiology of their cardiomyopathy as determined by each patient's cardiologist. Genetic testing was obtained using a third-party 168-gene cardiomyopathy panel. Variants were classified into five categories: pathogenic, likely pathogenic, variant of uncertain significance (VUS), likely benign, or benign. The VUS were investigated with population allele frequencies from Gnomad or Varsome databases and two modeling scores, Rare Exome Variant Ensemble Learner (Revel) and Combined Annotation Dependent Depletion (CADD), to investigate the likely pathogenicity. The patients were majority male (68%) and racially diverse, with 59% Black, 21% Hispanic, 17% White, and 3% Asian. Family history of heart failure was positive in 29% of the sample. The possible etiology of heart failure was 16% environmental, 8% familial, and 75% idiopathic or unknown. Regarding genetic testing results, 67 (88%) patients had variants identified; the remaining 9 patients (12%) had negative results. There were a total 170 variants for those 67 patients, with an average of 2.6 variants per patient. Of the 170 variants, 14 (8%) were pathogenic/likely pathogenic and 7 of these were titin (TTN) mutations. 151 (89%) of variants were VUS. Allele frequencies were not found for 17% of the VUS, and the remaining variants had total population and race-specific allele frequencies less than 1%. 83 (55%) of VUS were among the top 1% deleterious substitutions by CADD scores, and 27 (18%) of VUS had a Revel score > 0.5, on a scale of 0 to 1, suggesting more likely pathogenic variants. Patients with end-stage dilated NICM undergoing LVAD are likely to have genetic variants. The most frequent pathogenic variants were in TTN but most results are VUS. Due to the high frequency of VUS, augmenting genetic testing in this population may contribute to identification of additional pathogenic variants. [ABSTRACT FROM AUTHOR]
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- 2023
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25. Human genome meeting 2016
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Srivastava, A., Wang, Y., Huang, R., Skinner, C., Thompson, T., Pollard, L., Wood, T., Luo, F., Stevenson, R., Polimanti, R., Gelernter, J., Lin, X., Lim, I., Wu, Y., Teh, A., Chen, L., Aris, I., Soh, S., Tint, M., MacIsaac, J., Yap, F., Kwek, K., Saw, S., Kobor, M., Meaney, M., Godfrey, K., Chong, Y., Holbrook, J., Lee, Y., Gluckman, P., Karnani, N., Kapoor, A., Lee, D., Chakravarti, A., Maercker, C., Graf, F., Boutros, M., Stamoulis, G., Santoni, F., Makrythanasis, P., Letourneau, A., Guipponi, M., Panousis, N., Garieri, M., Ribaux, P., Falconnet, E., Borel, C., Antonarakis, S., Kumar, S., Curran, J., Blangero, J., Chatterjee, S., Kapoor, A., Akiyama, J., Auer, D., Berrios, C., Pennacchio, L., Chakravarti, A., Donti, T., Cappuccio, G., Miller, M., Atwal, P., Kennedy, A., Cardon, A., Bacino, C., Emrick, L., Hertecant, J., Baumer, F., Porter, B., Bainbridge, M., Bonnen, P., Graham, B., Sutton, R., Sun, Q., Elsea, S., Hu, Z., Wang, P., Zhu, Y., Zhao, J., Xiong, M., Bennett, David, Hidalgo-Miranda, A., Romero-Cordoba, S., Rodriguez-Cuevas, S., Rebollar-Vega, R., Tagliabue, E., Iorio, M., D’Ippolito, E., Baroni, S., Kaczkowski, B., Tanaka, Y., Kawaji, H., Sandelin, A., Andersson, R., Itoh, M., Lassmann, T., Hayashizaki, Y., Carninci, P., Forrest, A., Semple, C., Rosenthal, E., Shirts, B., Amendola, L., Gallego, C., Horike-Pyne, M., Burt, A., Robertson, P., Beyers, P., Nefcy, C., Veenstra, D., Hisama, F., Bennett, R., Dorschner, M., Nickerson, D., Smith, J., Patterson, K., Crosslin, D., Nassir, R., Zubair, N., Harrison, T., Peters, U., Jarvik, G., Menghi, F., Inaki, K., Woo, X., Kumar, P., Grzeda, K., Malhotra, A., Kim, H., Ucar, D., Shreckengast, P., Karuturi, K., Keck, J., Chuang, J., Liu, E., Ji, B., Tyler, A., Ananda, G., Carter, G., Nikbakht, H., Montagne, M., Zeinieh, M., Harutyunyan, A., Mcconechy, M., Jabado, N., Lavigne, P., Majewski, J., Goldstein, J., Overman, M., Varadhachary, G., Shroff, R., Wolff, R., Javle, M., Futreal, A., Fogelman, D., Bravo, L., Fajardo, W., Gomez, H., Castaneda, C., Rolfo, C., Pinto, J., Akdemir, K., Chin, L., Futreal, A., Patterson, S., Statz, C., Mockus, S., Nikolaev, S., Bonilla, X., Parmentier, L., King, B., Bezrukov, F., Kaya, G., Zoete, V., Seplyarskiy, V., Sharpe, H., McKee, T., Letourneau, A., Ribaux, P., Popadin, K., Basset-Seguin, N., Chaabene, R., Santoni, F., Andrianova, M., Guipponi, M., Garieri, M., Verdan, C., Grosdemange, K., Sumara, O., Eilers, M., Aifantis, I., Michielin, O., de Sauvage, F., Antonarakis, S., Likhitrattanapisal, S., Lincoln, S., Kurian, A., Desmond, A., Yang, S., Kobayashi, Y., Ford, J., Ellisen, L., Peters, T., Alvarez, K., Hollingsworth, E., Lopez-Terrada, D., Hastie, A., Dzakula, Z., Pang, A., Lam, E., Anantharaman, T., Saghbini, M., Cao, H., Gonzaga-Jauregui, C., Ma, L., King, A., Rosenzweig, E., Krishnan, U., Reid, J., Overton, J., Dewey, F., Chung, W., Small, K., DeLuca, A., Cremers, F., Lewis, R., Puech, V., Bakall, B., Silva-Garcia, R., Rohrschneider, K., Leys, M., Shaya, F., Stone, E., Sobreira, N., Schiettecatte, F., Ling, H., Pugh, E., Witmer, D., Hetrick, K., Zhang, P., Doheny, K., Valle, D., Hamosh, A., Jhangiani, S., Akdemir, Z., Bainbridge, M., Charng, W., Wiszniewski, W., Gambin, T., Karaca, E., Bayram, Y., Eldomery, M., Posey, J., Doddapaneni, H., Hu, J., Sutton, V., Muzny, D., Boerwinkle, E., Valle, D., Lupski, J., Gibbs, R., Shekar, S., Salerno, W., English, A., Mangubat, A., Bruestle, J., Thorogood, A., Knoppers, B., Takahashi, H., Nitta, K., Kozhuharova, A., Suzuki, A., Sharma, H., Cotella, D., Santoro, C., Zucchelli, S., Gustincich, S., Carninci, P., Mulvihill, J., Baynam, G., Gahl, W., Groft, S., Kosaki, K., Lasko, P., Melegh, B., Taruscio, D., Ghosh, R., Plon, S., Scherer, S., Qin, X., Sanghvi, R., Walker, K., Chiang, T., Muzny, D., Wang, L., Black, J., Boerwinkle, E., Weinshilboum, R., Gibbs, R., Karpinets, T., Calderone, T., Wani, K., Yu, X., Creasy, C., Haymaker, C., Forget, M., Nanda, V., Roszik, J., Wargo, J., Haydu, L., Song, X., Lazar, A., Gershenwald, J., Davies, M., Bernatchez, C., Zhang, J., Futreal, A., Woodman, S., Chesler, E., Reynolds, T., Bubier, J., Phillips, C., Langston, M., Baker, E., Xiong, M., Ma, L., Lin, N., Amos, C., Lin, N., Wang, P., Zhu, Y., Zhao, J., Calhoun, V., Xiong, M., Dobretsberger, O., Egger, M., Leimgruber, F., Sadedin, S., Oshlack, A., Antonio, V., Ono, N., Ahmed, Z., Bolisetty, M., Zeeshan, S., Anguiano, E., Ucar, D., Sarkar, A., Nandineni, M., Zeng, C., Shao, J., Cao, H., Hastie, A., Pang, A., Lam, E., Liang, T., Pham, K., Saghbini, M., Dzakula, Z., Chee-Wei, Y., Dongsheng, L., Lai-Ping, W., Lian, D., Hee, R., Yunus, Y., Aghakhanian, F., Mokhtar, S., Lok-Yung, C., Bhak, J., Phipps, M., Shuhua, X., Yik-Ying, T., Kumar, V., Boon-Peng, H., Campbell, I., Young, M., James, P., Rain, M., Mohammad, G., Kukreti, R., Pasha, Q., Akilzhanova, A., Guelly, C., Abilova, Z., Rakhimova, S., Akhmetova, A., Kairov, U., Trajanoski, S., Zhumadilov, Z., Bekbossynova, M., Schumacher, C., Sandhu, S., Harkins, T., Makarov, V., Doddapaneni, H., Glenn, R., Momin, Z., Dilrukshi, B., Chao, H., Meng, Q., Gudenkauf, B., Kshitij, R., Jayaseelan, J., Nessner, C., Lee, S., Blankenberg, K., Lewis, L., Hu, J., Han, Y., Dinh, H., Jireh, S., Walker, K., Boerwinkle, E., Muzny, D., Gibbs, R., Hu, J., Walker, K., Buhay, C., Liu, X., Wang, Q., Sanghvi, R., Doddapaneni, H., Ding, Y., Veeraraghavan, N., Yang, Y., Boerwinkle, E., Beaudet, A., Eng, C., Muzny, D., Gibbs, R., Worley, K., Liu, Y., Hughes, D., Murali, S., Harris, R., English, A., Qin, X., Hampton, O., Larsen, P., Beck, C., Han, Y., Wang, M., Doddapaneni, H., Kovar, C., Salerno, W., Yoder, A., Richards, S., Rogers, J., Lupski, J., Muzny, D., Gibbs, R., Meng, Q., Bainbridge, M., Wang, M., Doddapaneni, H., Han, Y., Muzny, D., Gibbs, R., Harris, R., Raveenedran, M., Xue, C., Dahdouli, M., Cox, L., Fan, G., Ferguson, B., Hovarth, J., Johnson, Z., Kanthaswamy, S., Kubisch, M., Platt, M., Smith, D., Vallender, E., Wiseman, R., Liu, X., Below, J., Muzny, D., Gibbs, R., Yu, F., Rogers, J., Lin, J., Zhang, Y., Ouyang, Z., Moore, A., Wang, Z., Hofmann, J., Purdue, M., Stolzenberg-Solomon, R., Weinstein, S., Albanes, D., Liu, C., Cheng, W., Lin, T., Lan, Q., Rothman, N., Berndt, S., Chen, E., Bahrami, H., Khoshzaban, A., Keshal, S., Bahrami, H., Khoshzaban, A., Keshal, S., Alharbi, K., Zhalbinova, M., Akilzhanova, A., Rakhimova, S., Bekbosynova, M., Myrzakhmetova, S., Matar, M., Mili, N., Molinari, R., Ma, Y., Guerrier, S., Elhawary, N., Tayeb, M., Bogari, N., Qotb, N., McClymont, S., Hook, P., Goff, L., McCallion, A., Kong, Y., Charette, J., Hicks, W., Naggert, J., Zhao, L., Nishina, P., Edrees, B., Athar, M., Al-Allaf, F., Taher, M., Khan, W., Bouazzaoui, A., Harbi, N., Safar, R., Al-Edressi, H., Anazi, A., Altayeb, N., Ahmed, M., Alansary, K., Abduljaleel, Z., Kratz, A., Beguin, P., Poulain, S., Kaneko, M., Takahiko, C., Matsunaga, A., Kato, S., Suzuki, A., Bertin, N., Lassmann, T., Vigot, R., Carninci, P., Plessy, C., Launey, T., Graur, D., Lee, D., Kapoor, A., Chakravarti, A., Friis-Nielsen, J., Izarzugaza, J., Brunak, S., Chakraborty, A., Basak, J., Mukhopadhyay, A., Soibam, B., Das, D., Biswas, N., Das, S., Sarkar, S., Maitra, A., Panda, C., Majumder, P., Morsy, H., Gaballah, A., Samir, M., Shamseya, M., Mahrous, H., Ghazal, A., Arafat, W., Hashish, M., Gruber, J., Jaeger, N., Snyder, M., Patel, K., Bowman, S., Davis, T., Kraushaar, D., Emerman, A., Russello, S., Henig, N., Hendrickson, C., Zhang, K., Rodriguez-Dorantes, M., Cruz-Hernandez, C., Garcia-Tobilla, C., Solorzano-Rosales, S., Jäger, N., Chen, J., Haile, R., Hitchins, M., Brooks, J., Snyder, M., Jiménez-Morales, S., Ramírez, M., Nuñez, J., Bekker, V., Leal, Y., Jiménez, E., Medina, A., Hidalgo, A., Mejía, J., Halytskiy, V., Naggert, J., Collin, G., DeMauro, K., Hanusek, R., Nishina, P., Belhassa, K., Belhassan, K., Bouguenouch, L., Samri, I., Sayel, H., moufid, FZ., El Bouchikhi, I., Trhanint, S., Hamdaoui, H., Elotmani, I., Khtiri, I., Kettani, O., Quibibo, L., Ahagoud, M., Abbassi, M., Ouldim, K., Marusin, A., Kornetov, A., Swarovskaya, M., Vagaiceva, K., Stepanov, V., De La Paz, E., Sy, R., Nevado, J., Reganit, P., Santos, L., Magno, J., Punzalan, F., Ona, D., Llanes, E., Santos-Cortes, R., Tiongco, R., Aherrera, J., Abrahan, L., Pagauitan-Alan, P., Morelli, K., Domire, J., Pyne, N., Harper, S., Burgess, R., Zhalbinova, M., Akilzhanova, A., Rakhimova, S., Bekbosynova, M., Myrzakhmetova, S., Gari, M., Dallol, A., Alsehli, H., Gari, A., Gari, M., Abuzenadah, A., Thomas, M., Sukhai, M., Garg, S., Misyura, M., Zhang, T., Schuh, A., Stockley, T., Kamel-Reid, S., Sherry, S., Xiao, C., Slotta, D., Rodarmer, K., Feolo, M., Kimelman, M., Godynskiy, G., O’Sullivan, C., Yaschenko, E., Xiao, C., Yaschenko, E., Sherry, S., Rangel-Escareño, C., Rueda-Zarate, H., Tayubi, I., Mohammed, R., Ahmed, I., Ahmed, T., Seth, S., Amin, S., Song, X., Mao, X., Sun, H., Verhaak, R., Futreal, A., Zhang, J., Whiite, S., Chiang, T., English, A., Farek, J., Kahn, Z., Salerno, W., Veeraraghavan, N., Boerwinkle, E., Gibbs, R., Kasukawa, T., Lizio, M., Harshbarger, J., Hisashi, S., Severin, J., Imad, A., Sahin, S., Freeman, T., Baillie, K., Sandelin, A., Carninci, P., Forrest, A., Kawaji, H., Salerno, W., English, A., Shekar, S., Mangubat, A., Bruestle, J., Boerwinkle, E., Gibbs, R., Salem, A., Ali, M., Ibrahim, A., Ibrahim, M., Barrera, H., Garza, L., Torres, J., Barajas, V., Ulloa-Aguirre, A., Kershenobich, D., Mortaji, Shahroj, Guizar, Pedro, Loera, Eliezer, Moreno, Karen, De León, Adriana, Monsiváis, Daniela, Gómez, Jackeline, Cardiel, Raquel, Fernandez-Lopez, J., Bonifaz-Peña, V., Rangel-Escareño, C., Hidalgo-Miranda, A., Contreras, A., Polfus, L., Wang, X., Philip, V., Carter, G., Abuzenadah, A., Gari, M., Turki, R., Dallol, A., Uyar, A., Kaygun, A., Zaman, S., Marquez, E., George, J., Ucar, D., Hendrickson, C., Emerman, A., Kraushaar, D., Bowman, S., Henig, N., Davis, T., Russello, S., Patel, K., Starr, D., Baird, M., Kirkpatrick, B., Sheets, K., Nitsche, R., Prieto-Lafuente, L., Landrum, M., Lee, J., Rubinstein, W., Maglott, D., Thavanati, P., de Dios, A., Hernandez, R., Aldrate, M., Mejia, M., Kanala, K., Abduljaleel, Z., Khan, W., Al-Allaf, F., Athar, M., Taher, M., Shahzad, N., Bouazzaoui, A., Huber, E., Dan, A., Al-Allaf, F., Herr, W., Sprotte, G., Köstler, J., Hiergeist, A., Gessner, A., Andreesen, R., Holler, E., Al-Allaf, F., Alashwal, A., Abduljaleel, Z., Taher, M., Bouazzaoui, A., Abalkhail, H., Al-Allaf, A., Bamardadh, R., Athar, M., Filiptsova, O., Kobets, M., Kobets, Y., Burlaka, I., Timoshyna, I., Filiptsova, O., Kobets, M., Kobets, Y., Burlaka, I., Timoshyna, I., Filiptsova, O., Kobets, M., Kobets, Y., Burlaka, I., Timoshyna, I., Al-allaf, F., Mohiuddin, M., Zainularifeen, A., Mohammed, A., Abalkhail, H., Owaidah, T., and Bouazzaoui, A.
- Abstract
O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s disease Z. Hu, P. Wang, Y. Zhu, J. Zhao, M. Xiong, David A Bennett O11 A microRNA signature identifies subtypes of triple-negative breast cancer and reveals MIR-342-3P as regulator of a lactate metabolic pathway A. Hidalgo-Miranda, S. Romero-Cordoba, S. Rodriguez-Cuevas, R. Rebollar-Vega, E. Tagliabue, M. Iorio, E. D’Ippolito, S. Baroni O12 Transcriptome analysis identifies genes, enhancer RNAs and repetitive elements that are recurrently deregulated across multiple cancer types B. Kaczkowski, Y. Tanaka, H. Kawaji, A. Sandelin, R. Andersson, M. Itoh, T. Lassmann, the FANTOM5 consortium, Y. Hayashizaki, P. Carninci, A. R. R. Forrest O13 Elevated mutation and widespread loss of constraint at regulatory and architectural binding sites across 11 tumour types C. A. Semple O14 Exome sequencing provides evidence of pathogenicity for genes implicated in colorectal cancer E. A. Rosenthal, B. Shirts, L. Amendola, C. Gallego, M. Horike-Pyne, A. Burt, P. Robertson, P. Beyers, C. Nefcy, D. Veenstra, F. Hisama, R. Bennett, M. Dorschner, D. Nickerson, J. Smith, K. Patterson, D. Crosslin, R. Nassir, N. Zubair, T. Harrison, U. Peters, G. Jarvik, NHLBI GO Exome Sequencing Project O15 The tandem duplicator phenotype as a distinct genomic configuration in cancer F. Menghi, K. Inaki, X. Woo, P. Kumar, K. Grzeda, A. Malhotra, H. Kim, D. Ucar, P. Shreckengast, K. Karuturi, J. Keck, J. Chuang, E. T. Liu O16 Modeling genetic interactions associated with molecular subtypes of breast cancer B. Ji, A. Tyler, G. Ananda, G. Carter O17 Recurrent somatic mutation in the MYC associated factor X in brain tumors H. Nikbakht, M. Montagne, M. Zeinieh, A. Harutyunyan, M. Mcconechy, N. Jabado, P. Lavigne, J. Majewski O18 Predictive biomarkers to metastatic pancreatic cancer treatment J. B. Goldstein, M. Overman, G. Varadhachary, R. Shroff, R. Wolff, M. Javle, A. Futreal, D. Fogelman O19 DDIT4 gene expression as a prognostic marker in several malignant tumors L. Bravo, W. Fajardo, H. Gomez, C. Castaneda, C. Rolfo, J. A. Pinto O20 Spatial organization of the genome and genomic alterations in human cancers K. C. Akdemir, L. Chin, A. Futreal, ICGC PCAWG Structural Alterations Group O21 Landscape of targeted therapies in solid tumors S. Patterson, C. Statz, S. Mockus O22 Genomic analysis reveals novel drivers and progression pathways in skin basal cell carcinoma S. N. Nikolaev, X. I. Bonilla, L. Parmentier, B. King, F. Bezrukov, G. Kaya, V. Zoete, V. Seplyarskiy, H. Sharpe, T. McKee, A. Letourneau, P. Ribaux, K. Popadin, N. Basset-Seguin, R. Ben Chaabene, F. Santoni, M. Andrianova, M. Guipponi, M. Garieri, C. Verdan, K. Grosdemange, O. Sumara, M. Eilers, I. Aifantis, O. Michielin, F. de Sauvage, S. Antonarakis O23 Identification of differential biomarkers of hepatocellular carcinoma and cholangiocarcinoma via transcriptome microarray meta-analysis S. Likhitrattanapisal O24 Clinical validity and actionability of multigene tests for hereditary cancers in a large multi-center study S. Lincoln, A. Kurian, A. Desmond, S. Yang, Y. Kobayashi, J. Ford, L. Ellisen O25 Correlation with tumor ploidy status is essential for correct determination of genome-wide copy number changes by SNP array T. L. Peters, K. R. Alvarez, E. F. Hollingsworth, D. H. Lopez-Terrada O26 Nanochannel based next-generation mapping for interrogation of clinically relevant structural variation A. Hastie, Z. Dzakula, A. W. Pang, E. T. Lam, T. Anantharaman, M. Saghbini, H. Cao, BioNano Genomics O27 Mutation spectrum in a pulmonary arterial hypertension (PAH) cohort and identification of associated truncating mutations in TBX4 C. Gonzaga-Jauregui, L. Ma, A. King, E. Berman Rosenzweig, U. Krishnan, J. G. Reid, J. D. Overton, F. Dewey, W. K. Chung O28 NORTH CAROLINA macular dystrophy (MCDR1): mutations found affecting PRDM13 K. Small, A. DeLuca, F. Cremers, R. A. Lewis, V. Puech, B. Bakall, R. Silva-Garcia, K. Rohrschneider, M. Leys, F. S. Shaya, E. Stone O29 PhenoDB and genematcher, solving unsolved whole exome sequencing data N. L. Sobreira, F. Schiettecatte, H. Ling, E. Pugh, D. Witmer, K. Hetrick, P. Zhang, K. Doheny, D. Valle, A. Hamosh O30 Baylor-Johns Hopkins Center for Mendelian genomics: a four year review S. N. Jhangiani, Z. Coban Akdemir, M. N. Bainbridge, W. Charng, W. Wiszniewski, T. Gambin, E. Karaca, Y. Bayram, M. K. Eldomery, J. Posey, H. Doddapaneni, J. Hu, V. R. Sutton, D. M. Muzny, E. A. Boerwinkle, D. Valle, J. R. Lupski, R. A. Gibbs O31 Using read overlap assembly to accurately identify structural genetic differences in an ashkenazi jewish trio S. Shekar, W. Salerno, A. English, A. Mangubat, J. Bruestle O32 Legal interoperability: a sine qua non for international data sharing A. Thorogood, B. M. Knoppers, Global Alliance for Genomics and Health - Regulatory and Ethics Working Group O33 High throughput screening platform of competent sineups: that can enhance translation activities of therapeutic target H. Takahashi, K. R. Nitta, A. Kozhuharova, A. M. Suzuki, H. Sharma, D. Cotella, C. Santoro, S. Zucchelli, S. Gustincich, P. Carninci O34 The undiagnosed diseases network international (UDNI): clinical and laboratory research to meet patient needs J. J. Mulvihill, G. Baynam, W. Gahl, S. C. Groft, K. Kosaki, P. Lasko, B. Melegh, D. Taruscio O36 Performance of computational algorithms in pathogenicity predictions for activating variants in oncogenes versus loss of function mutations in tumor suppressor genes R. Ghosh, S. Plon O37 Identification and electronic health record incorporation of clinically actionable pharmacogenomic variants using prospective targeted sequencing S. Scherer, X. Qin, R. Sanghvi, K. Walker, T. Chiang, D. Muzny, L. Wang, J. Black, E. Boerwinkle, R. Weinshilboum, R. Gibbs O38 Melanoma reprogramming state correlates with response to CTLA-4 blockade in metastatic melanoma T. Karpinets, T. Calderone, K. Wani, X. Yu, C. Creasy, C. Haymaker, M. Forget, V. Nanda, J. Roszik, J. Wargo, L. Haydu, X. Song, A. Lazar, J. Gershenwald, M. Davies, C. Bernatchez, J. Zhang, A. Futreal, S. Woodman O39 Data-driven refinement of complex disease classification from integration of heterogeneous functional genomics data in GeneWeaver E. J. Chesler, T. Reynolds, J. A. Bubier, C. Phillips, M. A. Langston, E. J. Baker O40 A general statistic framework for genome-based disease risk prediction M. Xiong, L. Ma, N. Lin, C. Amos O41 Integrative large-scale causal network analysis of imaging and genomic data and its application in schizophrenia studies N. Lin, P. Wang, Y. Zhu, J. Zhao, V. Calhoun, M. Xiong O42 Big data and NGS data analysis: the cloud to the rescue O. Dobretsberger, M. Egger, F. Leimgruber O43 Cpipe: a convergent clinical exome pipeline specialised for targeted sequencing S. Sadedin, A. Oshlack, Melbourne Genomics Health Alliance O44 A Bayesian classification of biomedical images using feature extraction from deep neural networks implemented on lung cancer data V. A. A. Antonio, N. Ono, Clark Kendrick C. Go O45 MAV-SEQ: an interactive platform for the Management, Analysis, and Visualization of sequence data Z. Ahmed, M. Bolisetty, S. Zeeshan, E. Anguiano, D. Ucar O47 Allele specific enhancer in EPAS1 intronic regions may contribute to high altitude adaptation of Tibetans C. Zeng, J. Shao O48 Nanochannel based next-generation mapping for structural variation detection and comparison in trios and populations H. Cao, A. Hastie, A. W. Pang, E. T. Lam, T. Liang, K. Pham, M. Saghbini, Z. Dzakula O49 Archaic introgression in indigenous populations of Malaysia revealed by whole genome sequencing Y. Chee-Wei, L. Dongsheng, W. Lai-Ping, D. Lian, R. O. Twee Hee, Y. Yunus, F. Aghakhanian, S. S. Mokhtar, C. V. Lok-Yung, J. Bhak, M. Phipps, X. Shuhua, T. Yik-Ying, V. Kumar, H. Boon-Peng O50 Breast and ovarian cancer prevention: is it time for population-based mutation screening of high risk genes? I. Campbell, M.-A. Young, P. James, Lifepool O53 Comprehensive coverage from low DNA input using novel NGS library preparation methods for WGS and WGBS C. Schumacher, S. Sandhu, T. Harkins, V. Makarov O54 Methods for large scale construction of robust PCR-free libraries for sequencing on Illumina HiSeqX platform H. DoddapaneniR. Glenn, Z. Momin, B. Dilrukshi, H. Chao, Q. Meng, B. Gudenkauf, R. Kshitij, J. Jayaseelan, C. Nessner, S. Lee, K. Blankenberg, L. Lewis, J. Hu, Y. Han, H. Dinh, S. Jireh, K. Walker, E. Boerwinkle, D. Muzny, R. Gibbs O55 Rapid capture methods for clinical sequencing J. Hu, K. Walker, C. Buhay, X. Liu, Q. Wang, R. Sanghvi, H. Doddapaneni, Y. Ding, N. Veeraraghavan, Y. Yang, E. Boerwinkle, A. L. Beaudet, C. M. Eng, D. M. Muzny, R. A. Gibbs O56 A diploid personal human genome model for better genomes from diverse sequence data K. C. C. Worley, Y. Liu, D. S. T. Hughes, S. C. Murali, R. A. Harris, A. C. English, X. Qin, O. A. Hampton, P. Larsen, C. Beck, Y. Han, M. Wang, H. Doddapaneni, C. L. Kovar, W. J. Salerno, A. Yoder, S. Richards, J. Rogers, J. R. Lupski, D. M. Muzny, R. A. Gibbs O57 Development of PacBio long range capture for detection of pathogenic structural variants Q. Meng, M. Bainbridge, M. Wang, H. Doddapaneni, Y. Han, D. Muzny, R. Gibbs O58 Rhesus macaques exhibit more non-synonymous variation but greater impact of purifying selection than humans R. A. Harris, M. Raveenedran, C. Xue, M. Dahdouli, L. Cox, G. Fan, B. Ferguson, J. Hovarth, Z. Johnson, S. Kanthaswamy, M. Kubisch, M. Platt, D. Smith, E. Vallender, R. Wiseman, X. Liu, J. Below, D. Muzny, R. Gibbs, F. Yu, J. Rogers O59 Assessing RNA structure disruption induced by single-nucleotide variation J. Lin, Y. Zhang, Z. Ouyang P1 A meta-analysis of genome-wide association studies of mitochondrial dna copy number A. Moore, Z. Wang, J. Hofmann, M. Purdue, R. Stolzenberg-Solomon, S. Weinstein, D. Albanes, C.-S. Liu, W.-L. Cheng, T.-T. Lin, Q. Lan, N. Rothman, S. Berndt P2 Missense polymorphic genetic combinations underlying down syndrome susceptibility E. S. Chen P4 The evaluation of alteration of ELAM-1 expression in the endometriosis patients H. Bahrami, A. Khoshzaban, S. Heidari Keshal P5 Obesity and the incidence of apolipoprotein E polymorphisms in an assorted population from Saudi Arabia population K. K. R. Alharbi P6 Genome-associated personalized antithrombotical therapy for patients with high risk of thrombosis and bleeding M. Zhalbinova, A. Akilzhanova, S. Rakhimova, M. Bekbosynova, S. Myrzakhmetova P7 Frequency of Xmn1 polymorphism among sickle cell carrier cases in UAE population M. Matar P8 Differentiating inflammatory bowel diseases by using genomic data: dimension of the problem and network organization N. Mili, R. Molinari, Y. Ma, S. Guerrier P9 Vulnerability of genetic variants to the risk of autism among Saudi children N. Elhawary, M. Tayeb, N. Bogari, N. Qotb P10 Chromatin profiles from ex vivo purified dopaminergic neurons establish a promising model to support studies of neurological function and dysfunction S. A. McClymont, P. W. Hook, L. A. Goff, A. McCallion P11 Utilization of a sensitized chemical mutagenesis screen to identify genetic modifiers of retinal dysplasia in homozygous Nr2e3rd7mice Y. Kong, J. R. Charette, W. L. Hicks, J. K. Naggert, L. Zhao, P. M. Nishina P12 Ion torrent next generation sequencing of recessive polycystic kidney disease in Saudi patients B. M. Edrees, M. Athar, F. A. Al-Allaf, M. M. Taher, W. Khan, A. Bouazzaoui, N. A. Harbi, R. Safar, H. Al-Edressi, A. Anazi, N. Altayeb, M. A. Ahmed, K. Alansary, Z. Abduljaleel P13 Digital expression profiling of Purkinje neurons and dendrites in different subcellular compartments A. Kratz, P. Beguin, S. Poulain, M. Kaneko, C. Takahiko, A. Matsunaga, S. Kato, A. M. Suzuki, N. Bertin, T. Lassmann, R. Vigot, P. Carninci, C. Plessy, T. Launey P14 The evolution of imperfection and imperfection of evolution: the functional and functionless fractions of the human genome D. Graur P16 Species-independent identification of known and novel recurrent genomic entities in multiple cancer patients J. Friis-Nielsen, J. M. Izarzugaza, S. Brunak P18 Discovery of active gene modules which are densely conserved across multiple cancer types reveal their prognostic power and mutually exclusive mutation patterns B. S. Soibam P19 Whole exome sequencing of dysplastic leukoplakia tissue indicates sequential accumulation of somatic mutations from oral precancer to cancer D. Das, N. Biswas, S. Das, S. Sarkar, A. Maitra, C. Panda, P. Majumder P21 Epigenetic mechanisms of carcinogensis by hereditary breast cancer genes J. J. Gruber, N. Jaeger, M. Snyder P22 RNA direct: a novel RNA enrichment strategy applied to transcripts associated with solid tumors K. Patel, S. Bowman, T. Davis, D. Kraushaar, A. Emerman, S. Russello, N. Henig, C. Hendrickson P23 RNA sequencing identifies gene mutations for neuroblastoma K. Zhang P24 Participation of SFRP1 in the modulation of TMPRSS2-ERG fusion gene in prostate cancer cell lines M. Rodriguez-Dorantes, C. D. Cruz-Hernandez, C. D. P. Garcia-Tobilla, S. Solorzano-Rosales P25 Targeted Methylation Sequencing of Prostate Cancer N. Jäger, J. Chen, R. Haile, M. Hitchins, J. D. Brooks, M. Snyder P26 Mutant TPMT alleles in children with acute lymphoblastic leukemia from México City and Yucatán, Mexico S. Jiménez-Morales, M. Ramírez, J. Nuñez, V. Bekker, Y. Leal, E. Jiménez, A. Medina, A. Hidalgo, J. Mejía P28 Genetic modifiers of Alström syndrome J. Naggert, G. B. Collin, K. DeMauro, R. Hanusek, P. M. Nishina P31 Association of genomic variants with the occurrence of angiotensin-converting-enzyme inhibitor (ACEI)-induced coughing among Filipinos E. M. Cutiongco De La Paz, R. Sy, J. Nevado, P. Reganit, L. Santos, J. D. Magno, F. E. Punzalan , D. Ona , E. Llanes, R. L. Santos-Cortes , R. Tiongco, J. Aherrera, L. Abrahan, P. Pagauitan-Alan; Philippine Cardiogenomics Study Group P32 The use of “humanized” mouse models to validate disease association of a de novo GARS variant and to test a novel gene therapy strategy for Charcot-Marie-Tooth disease type 2D K. H. Morelli, J. S. Domire, N. Pyne, S. Harper, R. Burgess P34 Molecular regulation of chondrogenic human induced pluripotent stem cells M. A. Gari, A. Dallol, H. Alsehli, A. Gari, M. Gari, A. Abuzenadah P35 Molecular profiling of hematologic malignancies: implementation of a variant assessment algorithm for next generation sequencing data analysis and clinical reporting M. Thomas, M. Sukhai, S. Garg, M. Misyura, T. Zhang, A. Schuh, T. Stockley, S. Kamel-Reid P36 Accessing genomic evidence for clinical variants at NCBI S. Sherry, C. Xiao, D. Slotta, K. Rodarmer, M. Feolo, M. Kimelman, G. Godynskiy, C. O’Sullivan, E. Yaschenko P37 NGS-SWIFT: a cloud-based variant analysis framework using control-accessed sequencing data from DBGAP/SRA C. Xiao, E. Yaschenko, S. Sherry P38 Computational assessment of drug induced hepatotoxicity through gene expression profiling C. Rangel-Escareño, H. Rueda-Zarate P40 Flowr: robust and efficient pipelines using a simple language-agnostic approach;ultraseq; fast modular pipeline for somatic variation calling using flowr S. Seth, S. Amin, X. Song, X. Mao, H. Sun, R. G. Verhaak, A. Futreal, J. Zhang P41 Applying “Big data” technologies to the rapid analysis of heterogenous large cohort data S. J. Whiite, T. Chiang, A. English, J. Farek, Z. Kahn, W. Salerno, N. Veeraraghavan, E. Boerwinkle, R. Gibbs P42 FANTOM5 web resource for the large-scale genome-wide transcription start site activity profiles of wide-range of mammalian cells T. Kasukawa, M. Lizio, J. Harshbarger, S. Hisashi, J. Severin, A. Imad, S. Sahin, T. C. Freeman, K. Baillie, A. Sandelin, P. Carninci, A. R. R. Forrest, H. Kawaji, The FANTOM Consortium P43 Rapid and scalable typing of structural variants for disease cohorts W. Salerno, A. English, S. N. Shekar, A. Mangubat, J. Bruestle, E. Boerwinkle, R. A. Gibbs P44 Polymorphism of glutathione S-transferases and sulphotransferases genes in an Arab population A. H. Salem, M. Ali, A. Ibrahim, M. Ibrahim P46 Genetic divergence of CYP3A5*3 pharmacogenomic marker for native and admixed Mexican populations J. C. Fernandez-Lopez, V. Bonifaz-Peña, C. Rangel-Escareño, A. Hidalgo-Miranda, A. V. Contreras P47 Whole exome sequence meta-analysis of 13 white blood cell, red blood cell, and platelet traits L. Polfus, CHARGE and NHLBI Exome Sequence Project Working Groups P48 Association of adipoq gene with type 2 diabetes and related phenotypes in african american men and women: The jackson heart study S. Davis, R. Xu, S. Gebeab, P Riestra, A Gaye, R. Khan, J. Wilson, A. Bidulescu P49 Common variants in casr gene are associated with serum calcium levels in koreans S. H. Jung, N. Vinayagamoorthy, S. H. Yim, Y. J. Chung P50 Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with multiple exponential functions Y. Zhou, S. Xu P51 A Bayesian framework for generalized linear mixed models in genome-wide association studies X. Wang, V. Philip, G. Carter P52 Targeted sequencing approach for the identification of the genetic causes of hereditary hearing impairment A. A. Abuzenadah, M. Gari, R. Turki, A. Dallol P53 Identification of enhancer sequences by ATAC-seq open chromatin profiling A. Uyar, A. Kaygun, S. Zaman, E. Marquez, J. George, D. Ucar P54 Direct enrichment for the rapid preparation of targeted NGS libraries C. L. Hendrickson, A. Emerman, D. Kraushaar, S. Bowman, N. Henig, T. Davis, S. Russello, K. Patel P56 Performance of the Agilent D5000 and High Sensitivity D5000 ScreenTape assays for the Agilent 4200 Tapestation System R. Nitsche, L. Prieto-Lafuente P57 ClinVar: a multi-source archive for variant interpretation M. Landrum, J. Lee, W. Rubinstein, D. Maglott P59 Association of functional variants and protein physical interactions of human MUTY homolog linked with familial adenomatous polyposis and colorectal cancer syndrome Z. Abduljaleel, W. Khan, F. A. Al-Allaf, M. Athar , M. M. Taher, N. Shahzad P60 Modification of the microbiom constitution in the gut using chicken IgY antibodies resulted in a reduction of acute graft-versus-host disease after experimental bone marrow transplantation A. Bouazzaoui, E. Huber, A. Dan, F. A. Al-Allaf, W. Herr, G. Sprotte, J. Köstler, A. Hiergeist, A. Gessner, R. Andreesen, E. Holler P61 Compound heterozygous mutation in the LDLRgene in Saudi patients suffering severe hypercholesterolemia F. Al-Allaf, A. Alashwal, Z. Abduljaleel, M. Taher, A. Bouazzaoui, H. Abalkhail, A. Al-Allaf, R. Bamardadh, M. Athar
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- 2016
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26. Therapeutic liver repopulation by transient acetaminophen selection of gene-modified hepatocytes
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Luigi Naldini, Sean Nygaard, Jeffrey Posey, Alexander Mack Peters, Markus Grompe, Alessio Cantore, Amita Tiyaboonchai, Anne Vonada, Shelley R. Winn, Cary O. Harding, Vonada, A., Tiyaboonchai, A., Nygaard, S., Posey, J., Peters, A. M., Winn, S. R., Cantore, A., Naldini, L., Harding, C. O., and Grompe, M.
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biology ,business.industry ,Transgene ,Genetic enhancement ,Cytochrome P450 ,General Medicine ,Genetic Therapy ,Reductase ,Pharmacology ,Article ,Acetaminophen ,Small hairpin RNA ,Mice ,Liver ,In vivo ,biology.protein ,Hepatocytes ,Medicine ,Animals ,Transgenes ,business ,Gene ,medicine.drug - Abstract
Gene therapy by integrating vectors is promising for monogenic liver diseases, especially in children where episomal vectors remain transient. However, reaching the therapeutic threshold with genome-integrating vectors is challenging. Therefore, we developed a method to expand hepatocytes bearing therapeutic transgenes. The common fever medicine acetaminophen becomes hepatotoxic via cytochrome p450 metabolism. Lentiviral vectors with transgenes linked in cis to a Cypor shRNA were administered to neonatal mice. Hepatocytes lacking the essential cofactor of Cyp enzymes, NADPH-cytochrome p450 reductase (Cypor), were selected in vivo by acetaminophen administration, replacing up to 50% of the hepatic mass. Acetaminophen treatment of the mice resulted in over 30-fold expansion of transgene-bearing hepatocytes and achieved therapeutic thresholds in hemophilia B and phenylketonuria. We conclude that therapeutically modified hepatocytes can be selected safely and efficiently in preclinical models with a transient regimen of moderately hepatotoxic acetaminophen.
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- 2021
27. Paralog Studies Augment Gene Discovery: DDX and DHX Genes
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Ekkehard Wilichowski, Richard A. Gibbs, Fernando Kok, Gholson J. Lyon, Gerarda Cappuccio, René Santer, Ignatia B. Van den Veyver, Friedhelm Hildebrandt, Christopher M. Grochowski, Janson White, Nicola Brunetti-Pierri, Dilek Aktas, Ender Karaca, Joao Paulo Kitajima, Reid J. Robison, Sevcan Tug Bozdogan, V. Reid Sutton, Kai Wang, Davor Lessel, Michael J. Bamshad, Shalini N. Jhangiani, Michael O. Dorschner, Ian A. Glass, Donna M. Muzny, Mehmet Alikasifoglu, Robert Kleyner, Margaret Yoon, Jessika Johannsen, Hadas Ityel, James R. Lupski, Tatjana Bierhals, Hatip Aydin, Lucia Ortega, Hilde Van Esch, Bibiana K Y Wong, Ingrid S. Paine, Adriano Magli, Mir Reza Bekheirnia, Ariel Brautbar, Maja Hempel, Wai Lan Yeung, Zeynep Coban Akdemir, Saskia B. Wortmann, Taylor Marmorale, Jennifer E. Posey, Yavuz Bayram, Fabíola Paoli Monteiro, Michele Pinelli, Sarah Rosenheck, Erasmo Barbante Casella, Joannie Hui, Paine, I., Posey, J. E., Grochowski, C. M., Jhangiani, S. N., Rosenheck, S., Kleyner, R., Marmorale, T., Yoon, M., Wang, K., Robison, R., Cappuccio, G., Pinelli, M., Magli, A., Coban Akdemir, Z., Hui, J., Yeung, W. L., Wong, B. K. Y., ORTEGA DE LUNA, Ernesto, Bekheirnia, M. R., Bierhals, T., Hempel, M., Johannsen, J., Santer, R., Aktas, D., Alikasifoglu, M., Bozdogan, S., Aydin, H., Karaca, E., Bayram, Y., Ityel, H., Dorschner, M., White, J. J., Wilichowski, E., Wortmann, S. B., Casella, E. B., Kitajima, J. P., Kok, F., Monteiro, F., Muzny, D. M., Bamshad, M., Gibbs, R. A., Sutton, V. R., Van Esch, H., Brunetti-Pierri, N., Hildebrandt, F., Brautbar, A., Van den Veyver, I. B., Glass, I., Lessel, D., Lyon, G. J., Lupski, J. R., and Çukurova Üniversitesi
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0301 basic medicine ,Male ,Identification ,Mutation, Missense ,Common-Cause ,Paralogous Gene ,Biology ,Article ,DEAD-box RNA Helicases ,03 medical and health sciences ,0302 clinical medicine ,Intellectual Disability ,Exome Sequencing ,Genetics ,human paralog ,Nmd ,Missense mutation ,Humans ,Gene ,Genetics (clinical) ,Exome sequencing ,Genetic Association Studies ,Protein ,Mutants ,Variants ,Infant, Newborn ,Helicase ,Infant ,developmental delay ,DExD/H-box RNA helicase family ,human paralogs ,intellectual disability ,Phenotype ,RNA Helicase A ,De-Novo ,3. Good health ,Neoplasm Proteins ,Pedigree ,030104 developmental biology ,Neurodevelopmental Disorders ,biology.protein ,Developmental Delay ,Dexd/h-box Rna Helicase Family ,Human Paralogs ,Female ,DDX3X ,Mutations ,030217 neurology & neurosurgery ,RNA Helicases - Abstract
Members of a paralogous gene family in which variation in one gene is known to cause disease are eight times more likely to also be associated with human disease. Recent studies have elucidated DHX30 and DDX3X as genes for which pathogenic variant alleles are involved in neurodevelopmental disorders. We hypothesized that variants in paralogous genes encoding members of the DExD/H-box RNA helicase superfamily might also underlie developmental delay and/or intellectual disability (DD and/or ID) disease phenotypes. Here we describe 15 unrelated individuals who have DD and/or ID, central nervous system (CNS) dysfunction, vertebral anomalies, and dysmorphic features and were found to have probably damaging variants in DExD/H-box RNA helicase genes. In addition, these individuals exhibit a variety of other tissue and organ system involvement including ocular, outer ear, hearing, cardiac, and kidney tissues. Five individuals with homozygous (one), compound-heterozygous (two), or de novo (two) missense variants in DHX37 were identified by exome sequencing. We identified ten total individuals with missense variants in three other DDX/DHX paralogs: DHX16 (four individuals), DDX54 (three individuals), and DHX34 (three individuals). Most identified variants are rare, predicted to be damaging, and occur at conserved amino acid residues. Taken together, these 15 individuals implicate the DExD/H-box helicases in both dominantly and recessively inherited neurodevelopmental phenotypes and highlight the potential for more than one disease mechanism underlying these disorders. National Human Genome Research Institute (NHGRI)United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Human Genome Research Institute (NHGRI) [UM1 HG006542, UM1 HG006493]; National Heart, Lung, and Blood Institute (NHLBI)United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI); University of Washington Center for Mendelian Genomics [R01 NS058529, R35 NS105078]; National Institute of Neurological Disorders and Stroke (NINDS)United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Neurological Disorders & Stroke (NINDS); NHGRIUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Human Genome Research Institute (NHGRI) [K08 HG008986]; Telethon Undiagnosed Diseases Program [GSP15001]; Telethon FoundationFondazione Telethon; Aicardi Syndrome Foundation [2T32NS043124-16]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA; National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK) [DK088767]; Werner Otto Stiftung [K12 DK083014]; German Research Foundation (DFG)German Research Foundation (DFG) [LE 4223/1]; Common Fund of the Office of the Director of the National Institutes of Health; National Cancer Institute, NHGRI; NHLBIUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI); National Institute on Drug AbuseUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute on Drug Abuse (NIDA)European Commission; National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH); NINDSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Neurological Disorders & Stroke (NINDS); NATIONAL HUMAN GENOME RESEARCH INSTITUTEUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Human Genome Research Institute (NHGRI) [K08HG008986, UM1HG006542] Funding Source: NIH RePORTER; NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCESUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of General Medical Sciences (NIGMS) [T32GM008307] Funding Source: NIH RePORTER; NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKEUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Neurological Disorders & Stroke (NINDS) [R35NS105078] Funding Source: NIH RePORTER This work was supported in part by grants UM1 HG006542 (J.R.L) and UM1 HG006493 (M.B.) from the National Human Genome Research Institute (NHGRI) and the National Heart, Lung, and Blood Institute (NHLBI) to the Baylor Hopkins Center for Mendelian Genomics and the University of Washington Center for Mendelian Genomics, R01 NS058529 and R35 NS105078(J.R.L.) from the National Institute of Neurological Disorders and Stroke (NINDS), U54-HG003273 (R.A.G.) from NHGRI, and Telethon Undiagnosed Diseases Program (TUDP) GSP15001 (N.B.-P.) from the Telethon Foundation, and also by the Aicardi Syndrome Foundation. I.P. was supported by 2T32NS043124-16 through the National Institutes of Health. J.E.P. was supported by NHGRI K08 HG008986. F.H. was supported by the National Institutes of Health (DK088767). M.R.B. was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) K12 DK083014. D.L was supported by the Werner Otto Stiftung and the German Research Foundation (DFG; LE 4223/1). The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by the National Cancer Institute, NHGRI, NHLBI, the National Institute on Drug Abuse, the National Institute of Mental Health, and NINDS. The data used for the analyses described in this manuscript were obtained from the GTEx Portal on 10/29/18. The authors would like to thank Hans-Jurgen Kreienkamp for the help in identifying helicase core motifs and the Genome Aggregation Database (gnomAD) and the groups that provided exome and genome variant data to this resource. A full list of contributing groups can be found at https://gnomad.broadinstitute.org/about.
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- 2019
28. Nbeal2 Knockout Mice Are Not Protected Against Hypoxia-Induced Pulmonary Vascular Remodeling and Pulmonary Hypertension.
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Posey J, Jordan M, Lewis CV, Sul C, Dobrinskikh E, Swindle D, Denorme F, Irwin D, Di Paola J, Stenmark K, Nozik E, and Delaney C
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Inflammation drives the initiation and progression of pulmonary hypertension (PH). Platelets, increasingly recognized as immune cells, are activated and increased in the lungs of patients with PH. Platelet activation leads to the release of α-granule chemokines, many of which are implicated in PH. We hypothesized that hypoxia-induced secretion of platelet α-granule stored proteins and PH would be prevented in Nbeal2 -/-, α-granule deficient mice. WT and Nbeal2 -/- mice were maintained in normoxia or exposed to 10% hypobaric hypoxia for 3, 14, 21, or 35 days. We observed macrothrombocytopenia, increased circulating neutrophils and monocytes, and increased lung interstitial macrophages in Nbeal2 -/- mice at baseline. Hypoxia-induced platelet activation was attenuated, and hypoxia-induced increase in lung PF4 and platelets was delayed in Nbeal2 -/- mice compared to WT mice. Finally, although pulmonary vascular remodeling (PVR) and PH were attenuated at day 21, Nbeal2 -/- mice were not protected against hypoxia-induced PVR and PH at day 35. While this mutation also impacted circulating monocytes, neutrophils, and lung IMs, all of which are critical in the development of experimental PH, we gained further support for the role of platelets and α-granule proteins, such as PF4, in PH progression and pathogenesis and made several observations that expand our understanding of α-granule deficient mice in chronic hypoxia., (Copyright © 2024 American Society of Hematology.)
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- 2024
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29. Increased Circulating Extracellular Superoxide Dismutase Attenuates Platelet-Neutrophil Interactions.
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Sul C, Lewis CV, Posey J, Jordan M, Colon Hidalgo D, Porfilio T, Elajaili H, McCormack G, Burciaga S, Delaney C, and Nozik ES
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Acute respiratory distress syndrome (ARDS) is a serious illness accounting for 10% of ICU admissions and high mortality of 31-45% with a paucity of pharmacologic treatment options. Dysregulated inflammation and oxidative stress are hallmark features of ARDS. We previously showed that transgenic mice expressing a naturally occurring polymorphism of the antioxidant enzyme extracellular superoxide dismutase (EC-SOD), are protected against Staphylococcus aureus (S. aureus) pneumonia, acute lung injury, and pulmonary neutrophilia. In this mouse strain, an R213G amino acid substitution leads to lower tissue binding affinity and elevated alveolar and plasma EC-SOD levels, though the redox-regulated mechanisms responsible for protection against S. aureus are not yet elucidated. Neutrophils are recruited to the areas of injury and inflammation, in part by activated platelets, which contain multiple redox-sensitive targets. Thus, we hypothesize that increased circulating EC-SOD due to the EC-SOD R213G variant protects against S. aureus pneumonia by reducing platelet activation and subsequent neutrophil recruitment to the lung. We demonstrate that, compared to WT mice with S. aureus pneumonia, platelet activation, formation of platelet-neutrophil aggregates (PNAs), and influx of neutrophils and PNAs into the lung are decreased in the infected R213G mice. Furthermore, pre-treatment with a MnTE-2-PyP SOD mimetic protects against S. aureus-induced platelet activation, pulmonary neutrophilia, and acute lung injury. Our data highlight the redox regulation of platelet activation as a driver of S. aureus -induced acute lung injury.
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- 2024
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30. Genomic Balancing Act: Deciphering DNA rearrangements in the Complex Chromosomal Aberration involving 5p15.2, 2q31.1 and 18q21.32.
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Lupski J, Dardas Z, Marafi D, Duan R, Fatih J, El-Rashidy O, Grochowski C, Carvalho C, Jhangiani S, Bi W, Du H, Gibbs R, Posey J, Calame D, and Zaki M
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Despite extensive research into the genetic underpinnings of neurodevelopmental disorders (NDD), many clinical cases remain unresolved. We studied a female proband with a NDD, mildly dysmorphic facial features, and brain stem hypoplasia on neuroimaging. Comprehensive genomic analyses revealed a terminal 5p loss and terminal 18q gain in the proband while a diploid copy number for chromosomes 5 and 18 in both parents. Genomic investigations in the proband identified an unbalanced translocation t(5;18) with additional genetic material from chromosome 2 (2q31.3) inserted at the breakpoint, pointing to a complex chromosomal rearrangement (CCR) involving 5p15.2, 2q31.3, and 18q21.32. Breakpoint junction analyses enabled by long read genome sequencing unveiled the presence of four distinct junctions in the father, who is carrier of a balanced CCR. The proband inherited from the father both the abnormal chromosome 5 resulting in segmental aneusomies of chr5 (loss) and chr18 (gain) and a der(2) homologue. Evidences suggest a chromoplexy mechanism for this CCR derivation, involving double-strand breaks (DSBs) repaired by non-homologous end joining (NHEJ) or alternative end joining (alt-EJ). The complexity of the CCR and the segregation of homologues elucidate the genetic model for this family. This study demonstrates the importance of combining multiple genomic technologies to uncover genetic causes of complex neurodevelopmental syndrome and to better understand genetic disease mechanisms., Competing Interests: Additional Declarations: J.R.L. has stock ownership in 23andMe, is a paid consultant for Genome International, and is a co-inventor on multiple U.S. and European patents related to molecular diagnostics for inherited neuropathies, genomic disorders, eye diseases, and bacterial genomic fingerprinting. The Department of Molecular and Human Genetics at Baylor College of Medicine derives revenue from the chromosomal microarray analysis and clinical genomic sequencing (both ES and GS) offered in the Baylor Genetics Laboratory (http://bmgl.com). J.R.L. serves on the Scientific Advisory Board of BG.
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- 2024
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31. Multicenter retrospective evaluation of magnetic resonance imaging in pediatric and congenital heart disease patients with cardiac implantable electronic devices.
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Gakenheimer-Smith L, Ou Z, Kuang J, Moore JP, Burrows A, Kovach J, Dechert B, Beach CM, Ayers M, Tan RB, Mostafavifar M, Mah DY, Conner TM, Turpin S, Avasarala K, Shah MJ, Webster G, Posey J, Etheridge SP, Binka E, Niu M, Asaki SY, Lambert LM, and Pilcher TA
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- Adolescent, Child, Humans, Magnetic Resonance Imaging methods, Retrospective Studies, Infant, Child, Preschool, Young Adult, Adult, Defibrillators, Implantable, Heart Defects, Congenital diagnosis, Heart Defects, Congenital therapy, Pacemaker, Artificial
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Background: Guidelines addressing magnetic resonance imaging (MRI) in patients with cardiac implantable electronic devices (CIEDs) provide algorithms for imaging pediatric and congenital heart disease (CHD) patients. Guideline acceptance varies by institution. Guidelines also do not support routine MRI scans in patients with epicardial or abandoned leads, common in pediatric and CHD patients., Objective: The purpose of this study was to determine the incidence of MRI-related complications in pediatric and CHD patients with CIEDs, including epicardial and/or abandoned leads., Methods: A multicenter retrospective review included patients with CIEDs who underwent any MRI between 2007 and 2022 at congenital cardiac centers. The primary outcome was any patient adverse event or clinically significant CIED change after MRI, defined as pacing lead capture threshold increase >0.5 V with output change, P- or R- wave amplitude decrease >50% with sensitivity change, or impedance change >50%., Results: Across 14 institutions, 314 patients (median age 18.8 [1.3; 31.4] years) underwent 389 MRIs. There were 288 pacemakers (74%) and 87 implantable cardioverter-defibrillators (22%); 52% contained epicardial leads, and 14 (4%) were abandoned leads only. Symptoms or CIED changes occurred in 4.9% of MRI scans (6.1% of patients). On 9 occasions (2%), warmth or pain occurred. Pacing capture threshold or lead impedance changes occurred in 1.4% and 2.0% of CIEDs post-MRI and at follow-up., Conclusion: Our data provide evidence that MRIs can be performed in pediatric and CHD patients with CIEDs, including non-MRI-conditional CIEDs and epicardial and/or abandoned leads, with rare minor symptoms or CIED changes but no other complications., (Copyright © 2023 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)
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- 2023
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32. Feasibility of a Text Messaging-Integrated and Chatbot-Interfaced Self-Management Program for Symptom Control in Patients With Gastrointestinal Cancer Undergoing Chemotherapy: Pilot Mixed Methods Study.
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Gomaa S, Posey J, Bashir B, Basu Mallick A, Vanderklok E, Schnoll M, Zhan T, and Wen KY
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Background: Outpatient chemotherapy often leaves patients to grapple with a range of complex side effects at home. Leveraging tailored evidence-based content to monitor and manage these symptoms remains an untapped potential among patients with gastrointestinal (GI) cancer., Objective: This study aims to bridge the gap in outpatient chemotherapy care by integrating a cutting-edge text messaging system with a chatbot interface. This approach seeks to enable real-time monitoring and proactive management of side effects in patients with GI cancer undergoing intravenous chemotherapy., Methods: Real-Time Chemotherapy-Associated Side Effects Monitoring Supportive System (RT-CAMSS) was developed iteratively, incorporating patient-centered inputs and evidence-based information. It synthesizes chemotherapy knowledge, self-care symptom management skills, emotional support, and healthy lifestyle recommendations. In a single-arm 2-month pilot study, patients with GI cancer undergoing chemotherapy received tailored intervention messages thrice a week and a weekly Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events-based symptom assessment via a chatbot interface. Baseline and postintervention patient surveys and interviews were conducted., Results: Out of 45 eligible patients, 34 were enrolled (76% consent rate). The mean age was 61 (SD 12) years, with 19 (56%) being females and 21 (62%) non-Hispanic White. The most common cancer type was pancreatic (n=18, 53%), followed by colon (n=12, 35%) and stomach (n=4, 12%). In total, 27 (79% retention rate) participants completed the postintervention follow-up. In total, 20 patients texted back at least once to seek additional information, with the keyword "chemo" or "support" texted the most. Among those who used the chatbot system checker, fatigue emerged as the most frequently reported symptom (n=15), followed by neuropathy (n=7). Adjusted for multiple comparisons, patients engaging with the platform exhibited significantly improved Patient Activation Measure (3.70, 95% CI -6.919 to -0.499; P=.02). Postintervention interviews and satisfaction surveys revealed that participants found the intervention was user-friendly and were provided with valuable information., Conclusions: Capitalizing on mobile technology communication holds tremendous scalability for enhancing health care services. This study presents initial evidence of the engagement and acceptability of RT-CAMSS, warranting further evaluation in a controlled clinical trial setting., (©Sameh Gomaa, James Posey, Babar Bashir, Atrayee Basu Mallick, Eleanor Vanderklok, Max Schnoll, Tingting Zhan, Kuang-Yi Wen. Originally published in JMIR Formative Research (https://formative.jmir.org), 10.11.2023.)
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- 2023
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33. Repurposing the FDA-approved anthelmintic pyrvinium pamoate for pancreatic cancer treatment: study protocol for a phase I clinical trial in early-stage pancreatic ductal adenocarcinoma.
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Ponzini FM, Schultz CW, Leiby BE, Cannaday S, Yeo T, Posey J, Bowne WB, Yeo C, Brody JR, Lavu H, and Nevler A
- Subjects
- Humans, Drug Repositioning, Clinical Trials, Phase I as Topic, Pancreatic Neoplasms drug therapy, Pancreatic Neoplasms surgery, Carcinoma, Pancreatic Ductal drug therapy, Carcinoma, Pancreatic Ductal surgery, Adenocarcinoma surgery, Anthelmintics therapeutic use
- Abstract
Background: Recent reports of the utilisation of pyrvinium pamoate (PP), an FDA-approved anti-helminth, have shown that it inhibits pancreatic ductal adenocarcinoma (PDAC) cell growth and proliferation in-vitro and in-vivo in preclinical models. Here, we report about an ongoing phase I open-label, single-arm, dose escalation clinical trial to determine the safety and tolerability of PP in PDAC surgical candidates., Methods and Analysis: In a 3+3 dose design, PP is initiated 3 days prior to surgery. The first three patients will be treated with the initial dose of PP at 5 mg/kg orally for 3 days prior to surgery. Dose doubling will be continued to a reach a maximum of 20 mg/kg orally for 3 days, if the previous two dosages (5 mg/kg and 10 mg/kg) were tolerated. Dose-limiting toxicity grade≥3 is used as the primary endpoint. The pharmacokinetic and pharmacodynamic (PK/PD) profile of PP and bioavailability in humans will be used as the secondary objective. Each participant will be monitored weekly for a total of 30 days from the final dose of PP for any side effects. The purpose of this clinical trial is to examine whether PP is safe and tolerable in patients with pancreatic cancer, as well as assess the drug's PK/PD profile in plasma and fatty tissue. Potential implications include the utilisation of PP in a synergistic manner with chemotherapeutics for the treatment of pancreatic cancer., Ethics and Dissemination: This study was approved by the Thomas Jefferson Institutional Review Board. The protocol number for this study is 20F.041 (Version 3.1 as of 27 October 2021). The data collected and analysed from this study will be used to present at local and national conferences, as well as, written into peer-reviewed manuscript publications., Trial Registration Number: ClinicalTrials.gov: NCT05055323., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
- Published
- 2023
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34. Genomic characterization of early-stage hepatocellular carcinoma patients with Hepatitis B using circulating tumor DNA.
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Lin D, Luo R, Ye Z, Wei Q, Bae H, Juon HS, Hann HW, Posey J, and Wang C
- Subjects
- Humans, Hepatitis B virus genetics, Genomics, ROC Curve, Biomarkers, Tumor, Carcinoma, Hepatocellular genetics, Carcinoma, Hepatocellular diagnosis, Liver Neoplasms genetics, Liver Neoplasms diagnosis, Circulating Tumor DNA genetics, Hepatitis B complications
- Abstract
Background: Hepatocellular carcinoma (HCC) is a leading cause of mortality, with Hepatitis B virus (HBV) infection as a dominant etiology worldwide. Effective early detection strategies may facilitate curative therapies and improve survival. We investigated genomic aberrations in circulating tumor DNA (ctDNA) as potential diagnostic markers of HCC in HBV-infected patients., Methods: We identified early stage (BCLC 0-A) HCC cases (n = 21) and patients without HCC (n = 14) from a cohort of Asian patients with HBV, undergoing surveillance between 2013 and 2017. Circulating cell-free DNA was isolated from blood samples, and assayed by next-generation sequencing of 23 genes implicated in HCC pathogenesis. Somatic mutations were identified using a computational pipeline. Using area under the curve (AUC) in receiver operating characteristic (ROC) analysis, we evaluated gene alterations and clinical factors in an exploratory early HCC detection model., Results: Mutant ARID1A, CTNNB1, TP53 genes were increased in HCC cases vs. non-HCC patients (85.7% vs 42.9%, P = 0.011; 42.9% vs 0%, P = 0.005; 100% vs 71.4%, P = 0.019, respectively). Using these three genes, AUC for discriminating HCC from non-HCC patients was 0.844 (95% confidence interval [CI]: 0.7317-0.9553). When combining these genes with clinical factors in an exploratory early HCC detection model, AUC increased from 0.7415 (using clinical factors alone) to 0.9354 (P = 0.041)., Conclusion: Genomic aberrations in ctDNA were more prevalent in HBV-infected HCC patients compared with patients without HCC. Combining these alterations with clinical factors may identify HCC in HBV-infected patients at an early stage. These findings warrant validation in future studies., Competing Interests: Declaration of Competing Interest The authors have no conflict of interest to disclose., (Copyright © 2023. Published by Elsevier Masson SAS.)
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- 2023
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35. Incidence and recovery of post-surgical heart block in children following cardiac surgery.
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Madani R, Aronoff E, Posey J, Basu M, Zinyandu T, Chai P, Whitehill R, Maher KO, and Beshish AG
- Subjects
- Humans, Child, Retrospective Studies, Incidence, Atrioventricular Node surgery, Treatment Outcome, Atrioventricular Block epidemiology, Atrioventricular Block etiology, Atrioventricular Block therapy, Cardiac Surgical Procedures adverse effects, Pacemaker, Artificial adverse effects, Univentricular Heart complications
- Abstract
Background: A subset of patients who develop post-surgical heart block have recovery of atrioventricular node function. Factors predicting recovery are not understood. We investigated our centre's incidence of post-surgical heart block and examine factors associated with recovery of atrioventricular node function., Methods: We conducted a single-centre retrospective study of patients 0 - 21 years who underwent cardiac surgery between January 2010 and December 2019 and experienced post-operative heart block. Data including patient and clinical characteristics and operative variables were collected and analysed., Results: Of 6333 surgical hospitalisations, 128 (2%) patients developed post-operative heart block. Of the 128 patients, 90 (70%) had return of atrioventricular node function, and 38 (30%) had pacemaker placement. Of the 38 patients who underwent pacemaker placement, 6 (15.8%) had recovery of atrioventricular node function noted on long-term follow-up. Median time from onset of heart block to late atrioventricular node recovery was 13 days (Interquartile range: 5 - 117). Patients with single-ventricle physiology (p = 0.04), greater weight (p = 0.03), and shorter cardiopulmonary bypass time (p = 0.015) were more likely to have recovery. The use of post-operative steroids was similar between all groups (p = 0.445). Infectious or wound complications were similar between pacemaker groups (p = 1)., Conclusions: Two per cent of patients who underwent congenital cardiac surgery developed post-operative heart block, and 0.6% underwent pacemaker placement. Early recovery of atrioventricular node was associated with greater weight at the time of surgery, single-ventricle physiology, and shorter cardiopulmonary bypass time. Late recovery of atrioventricular node conduction following pacemaker placement occurred in 15.8% of patients.
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- 2023
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36. Zoster-Associated Prothrombotic Plasma Exosomes and Increased Stroke Risk.
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Bubak AN, Coughlan C, Posey J, Saviola AJ, Niemeyer CS, Lewis SWR, Lopez SB, Solano A, Tyring SK, Delaney C, Neeves KB, Mahalingam R, Hansen KC, and Nagel MA
- Subjects
- Humans, Exosomes, Herpesvirus 3, Human physiology, Risk Assessment, Male, Female, Plasma cytology, Thrombosis virology, Herpes Zoster epidemiology, Stroke epidemiology
- Abstract
Herpes zoster (HZ; shingles) caused by varicella zoster virus reactivation increases stroke risk for up to 1 year after HZ. The underlying mechanisms are unclear, however, the development of stroke distant from the site of zoster (eg, thoracic, lumbar, sacral) that can occur months after resolution of rash points to a long-lasting, virus-induced soluble factor (or factors) that can trigger thrombosis and/or vasculitis. Herein, we investigated the content and contributions of circulating plasma exosomes from HZ and non-HZ patient samples. Compared with non-HZ exosomes, HZ exosomes (1) contained proteins conferring a prothrombotic state to recipient cells and (2) activated platelets leading to the formation of platelet-leukocyte aggregates. Exosomes 3 months after HZ yielded similar results and also triggered cerebrovascular cells to secrete the proinflammatory cytokines, interleukin 6 and 8. These results can potentially change clinical practice through addition of antiplatelet agents for HZ and initiatives to increase HZ vaccine uptake to decrease stroke risk., Competing Interests: Potential conflicts of interest. All authors: No reported conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
- Published
- 2023
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37. Bi-allelic TTI1 variants cause an autosomal-recessive neurodevelopmental disorder with microcephaly.
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Serey-Gaut M, Cortes M, Makrythanasis P, Suri M, Taylor AMR, Sullivan JA, Asleh AN, Mitra J, Dar MA, McNamara A, Shashi V, Dugan S, Song X, Rosenfeld JA, Cabrol C, Iwaszkiewicz J, Zoete V, Pehlivan D, Akdemir ZC, Roeder ER, Littlejohn RO, Dibra HK, Byrd PJ, Stewart GS, Geckinli BB, Posey J, Westman R, Jungbluth C, Eason J, Sachdev R, Evans CA, Lemire G, VanNoy GE, O'Donnell-Luria A, Mau-Them FT, Juven A, Piard J, Nixon CY, Zhu Y, Ha T, Buckley MF, Thauvin C, Essien Umanah GK, Van Maldergem L, Lupski JR, Roscioli T, Dawson VL, Dawson TM, and Antonarakis SE
- Subjects
- Humans, Intracellular Signaling Peptides and Proteins, HEK293 Cells, TOR Serine-Threonine Kinases, Microcephaly, Neurodevelopmental Disorders, Movement Disorders
- Abstract
Telomere maintenance 2 (TELO2), Tel2 interacting protein 2 (TTI2), and Tel2 interacting protein 1 (TTI1) are the three components of the conserved Triple T (TTT) complex that modulates activity of phosphatidylinositol 3-kinase-related protein kinases (PIKKs), including mTOR, ATM, and ATR, by regulating the assembly of mTOR complex 1 (mTORC1). The TTT complex is essential for the expression, maturation, and stability of ATM and ATR in response to DNA damage. TELO2- and TTI2-related bi-allelic autosomal-recessive (AR) encephalopathies have been described in individuals with moderate to severe intellectual disability (ID), short stature, postnatal microcephaly, and a movement disorder (in the case of variants within TELO2). We present clinical, genomic, and functional data from 11 individuals in 9 unrelated families with bi-allelic variants in TTI1. All present with ID, and most with microcephaly, short stature, and a movement disorder. Functional studies performed in HEK293T cell lines and fibroblasts and lymphoblastoid cells derived from 4 unrelated individuals showed impairment of the TTT complex and of mTOR pathway activity which is improved by treatment with Rapamycin. Our data delineate a TTI1-related neurodevelopmental disorder and expand the group of disorders related to the TTT complex., Competing Interests: Declaration of interests S.E.A. is a co-founder and CEO of Medigenome, Swiss Institute of Genomic Medicine, and serves in the Scientific Advisory Board of the “Imagine” Institute in Paris. The Department of Medical and Human Genetics at Baylor College of Medicine receives revenue from clinical genetic testing conducted at Baylor Genetics Laboratories. J.R.L. has stock ownership in 23andMe; is a paid consultant for Regeneron Genetics Center; and is a co-inventor on multiple United States and European patents related to molecular diagnostics for inherited neuropathies, eye diseases, genomic disorders, and bacterial genomic fingerprinting, and serves on the Scientific Advisory Board of Baylor Genomics., (Copyright © 2023 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)
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- 2023
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38. Self-cleaving guide RNAs enable pharmacological selection of precise gene editing events in vivo.
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Tiyaboonchai A, Vonada A, Posey J, Pelz C, Wakefield L, and Grompe M
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- Humans, Gene Editing, Homologous Recombination, Transgenes, RNA, Guide, CRISPR-Cas Systems genetics, RNA, Catalytic genetics
- Abstract
Expression of guide RNAs in the CRISPR/Cas9 system typically requires the use of RNA polymerase III promoters, which are not cell-type specific. Flanking the gRNA with self-cleaving ribozyme motifs to create a self-cleaving gRNA overcomes this limitation. Here, we use self-cleaving gRNAs to create drug-selectable gene editing events in specific hepatocyte loci. A recombinant Adeno Associated Virus vector targeting the Albumin locus with a promoterless self-cleaving gRNA to create drug resistance is linked in cis with the therapeutic transgene. Gene expression of both are dependent on homologous recombination into the target locus. In vivo drug selection for the precisely edited hepatocytes allows >30-fold expansion of gene-edited cells and results in therapeutic levels of a human Factor 9 transgene. Importantly, self-cleaving gRNA expression is also achieved after targeting weak hepatocyte genes. We conclude that self-cleaving gRNAs are a powerful system to enable cell-type specific in vivo drug resistance for therapeutic gene editing applications., (© 2022. The Author(s).)
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- 2022
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39. Development of a Beta Cell-Specific Expression Control Element for Recombinant Adeno-Associated Virus.
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Chai S, Kim Y, Galivo F, Dorrell C, Wakefield L, Posey J, Ackermann AM, Kaestner KH, Hebrok M, and Grompe M
- Subjects
- Genetic Vectors genetics, Humans, Insulin metabolism, Transgenes, Dependovirus genetics, Dependovirus metabolism, MicroRNAs metabolism
- Abstract
Diabetes mellitus, caused by loss or dysfunction of the insulin-producing beta cells of the pancreas, is a promising target for recombinant adeno-associated virus (rAAV)-mediated gene therapy. To target potential therapeutic payloads specifically to beta cells, a cell type-specific expression control element is needed. In this study, we tested a series of rAAV vectors designed to express transgenes specifically in human beta cells using the islet-tropic rAAV-KP1 capsid. A small promoter, consisting of only 84 bp of the insulin core promoter was not beta cell-specific in AAV, but highly active in multiple cell types, including tissues outside the pancreas. A larger 363 bp fragment of the insulin promoter (INS) also lacked beta cell specificity. However, beta cell-specific expression was achieved by combining two regulatory elements, a promoter consisting of two copies of INS (INS × 2) and microRNA (miRNA) recognition elements (MREs). The INS × 2 promoter alone showed some beta cell preference, but not tight specificity. To reduce unspecific transgene expression in alpha cells, negative regulation by miRNAs was applied. MREs that are recognized by miRNAs abundant in alpha cells effectively downregulated the transgene expression in these cells. The INS2 × -MRE expression vector was highly specific to human beta cells and stem cell-derived beta cells.
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- 2022
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40. The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: A genotypic analysis.
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Walker TM, Miotto P, Köser CU, Fowler PW, Knaggs J, Iqbal Z, Hunt M, Chindelevitch L, Farhat M, Cirillo DM, Comas I, Posey J, Omar SV, Peto TE, Suresh A, Uplekar S, Laurent S, Colman RE, Nathanson CM, Zignol M, Walker AS, Crook DW, Ismail N, and Rodwell TC
- Subjects
- Antitubercular Agents pharmacology, Drug Resistance, Microbial Sensitivity Tests, Mutation, World Health Organization, Ethambutol, Mycobacterium tuberculosis genetics
- Abstract
Background: Molecular diagnostics are considered the most promising route to achieving rapid, universal drug susceptibility testing for Mycobacterium tuberculosis complex (MTBC). We aimed to generate a WHO endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction., Methods: A candidate gene approach was used to identify mutations as associated with resistance, or consistent with susceptibility, for 13 WHO endorsed anti-tuberculosis drugs. 38,215 MTBC isolates with paired whole-genome sequencing and phenotypic drug susceptibility testing data were amassed from 45 countries. For each mutation, a contingency table of binary phenotypes and presence or absence of the mutation computed positive predictive value, and Fisher's exact tests generated odds ratios and Benjamini-Hochberg corrected p-values. Mutations were graded as Associated with Resistance if present in at least 5 isolates, if the odds ratio was >1 with a statistically significant corrected p-value, and if the lower bound of the 95% confidence interval on the positive predictive value for phenotypic resistance was >25%. A series of expert rules were applied for final confidence grading of each mutation., Findings: 15,667 associations were computed for 13,211 unique mutations linked to one or more drugs. 1,149/15,667 (7·3%) mutations were classified as associated with phenotypic resistance and 107/15,667 (0·7%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was >80%. Specificity was over 95% for all drugs except ethionamide (91·4%), moxifloxacin (91·6%) and ethambutol (93·3%). Only two resistance mutations were classified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs., Interpretation: This first WHO endorsed catalogue of molecular targets for MTBC drug susceptibility testing provides a global standard for resistance interpretation. Its existence should encourage the implementation of molecular diagnostics by National Tuberculosis Programmes., Funding: UNITAID, Wellcome, MRC, BMGF., Competing Interests: Conflicts of interest C.U.K. is a consultant Becton Dickinson, the Foundation for Innovative New Diagnostics and the TB Alliance. C.U.K. is collaborating with Janssen, PZA Innovation and Thermo Fisher Scientific. C.U.K. worked as a consultant for QuantuMDx, the Stop TB Partnership, the World Health Organization (WHO) Global TB Programme and the WHO Regional Office for Europe. C.U.K. gave a paid educational talk for Oxford Immunotec. Hain Lifescience covered C.U.K.’s and accommodation to present at a meeting. C.U.K. is an unpaid advisor to BioVersys and GenoScreen. E.R. is employed by Public Health England and holds an honorary contract with Imperial College London. I.F.L. is Director of the Scottish Mycobacteria Reference Laboratory. S.N. receives funding from German Center for Infection Research, Excellenz Cluster Precision Medicine in Chronic Inflammation, Leibniz Science Campus Evolutionary Medicine of the LUNG (EvoLUNG)tion EXC 2167. P.S. is a consultant at Genoscreen. T.R. is funded by NIH and DoD and receives salary support from the non-profit organization FIND. T.R. is a co-founder, board member and shareholder of Verus Diagnostics Inc, a company that was founded with the intent of developing diagnostic assays. Verus Diagnostics was not involved in any way with data collection, analysis or publication of the results. T.R. has not received any financial support from Verus Diagnostics. UCSD Conflict of Interest office has reviewed and approved T.R.’s role in Verus Diagnostics Inc. T.R. is a co-inventor of a provisional patent for a TB diagnostic assay (provisional patent #: 63/048.989). T.R. is a co-inventor on a patent associated with the processing of TB sequencing data (European Patent Application No. 14840432.0 & USSN 14/912,918). T.R. has agreed to “donate all present and future interest in and rights to royalties from this patent” to UCSD to ensure that he does not receive any financial benefits from this patent. S.S. is working and holding ESOPs at HaystackAnalytics Pvt. Ltd. (Product: Using whole genome sequencing for drug susceptibility testing for Mycobacterium tuberculosis). G.F.G. is listed as an inventor on patent applications for RBD-dimer-based CoV vaccines. The patents for RBD-dimers as protein subunit vaccines for SARS-CoV-2 have been licensed to Anhui Zhifei Longcom Biopharmaceutical Co. Ltd, China. No other authors declare a conflict of interest. I.C. is a consultant for the Foundation for Innovative New Diagnostics. DAC reports funding from GlaxoSmithKline and consultancy fees from Biobeats, Oxford University Innovation, Sensyne Health.C.C. reports funding from FIND to his institution (Pathology Queensland, Queensland Department of Health) for his laboratory to perform molecular analytic studies (limits of detection) for new molecular platforms manufactured by Cepheid and Bioneer.
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- 2022
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41. Mutation of Mycobacterium tuberculosis and Implications for Using Whole-Genome Sequencing for Investigating Recent Tuberculosis Transmission.
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Nelson KN, Talarico S, Poonja S, McDaniel CJ, Cilnis M, Chang AH, Raz K, Noboa WS, Cowan L, Shaw T, Posey J, and Silk BJ
- Subjects
- Humans, Mutation, Polymorphism, Single Nucleotide, Whole Genome Sequencing methods, Mycobacterium tuberculosis genetics, Tuberculosis diagnosis, Tuberculosis epidemiology, Tuberculosis microbiology
- Abstract
Tuberculosis (TB) control programs use whole-genome sequencing (WGS) of Mycobacterium tuberculosis ( Mtb ) for detecting and investigating TB case clusters. Existence of few genomic differences between Mtb isolates might indicate TB cases are the result of recent transmission. However, the variable and sometimes long duration of latent infection, combined with uncertainty in the Mtb mutation rate during latency, can complicate interpretation of WGS results. To estimate the association between infection duration and single nucleotide polymorphism (SNP) accumulation in the Mtb genome, we first analyzed pairwise SNP differences among TB cases from Los Angeles County, California, with strong epidemiologic links. We found that SNP distance alone was insufficient for concluding that cases are linked through recent transmission. Second, we describe a well-characterized cluster of TB cases in California to illustrate the role of genomic data in conclusions regarding recent transmission. Longer presumed latent periods were inconsistently associated with larger SNP differences. Our analyses suggest that WGS alone cannot be used to definitively determine that a case is attributable to recent transmission. Methods for integrating clinical, epidemiologic, and genomic data can guide conclusions regarding the likelihood of recent transmission, providing local public health practitioners with better tools for monitoring and investigating TB transmission., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict ofinterest., (Copyright © 2022 Nelson, Talarico, Poonja, McDaniel, Cilnis, Chang, Raz, Noboa, Cowan, Shaw, Posey and Silk.)
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- 2022
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42. AAV integration in human hepatocytes.
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Dalwadi DA, Calabria A, Tiyaboonchai A, Posey J, Naugler WE, Montini E, and Grompe M
- Subjects
- Animals, Cells, Cultured, Chromosomes genetics, Dependovirus genetics, Disease Models, Animal, Genetic Therapy, Genetic Vectors administration & dosage, Hepatocytes cytology, Hepatocytes metabolism, Humans, Mice, Transduction, Genetic, Virus Integration, Dependovirus physiology, Hepatocytes transplantation, Liver Regeneration
- Abstract
Recombinant adeno-associated viral (rAAV) vectors are considered promising tools for gene therapy directed at the liver. Whereas rAAV is thought to be an episomal vector, its single-stranded DNA genome is prone to intra- and inter-molecular recombination leading to rearrangements and integration into the host cell genome. Here, we ascertained the integration frequency of rAAV in human hepatocytes transduced either ex vivo or in vivo and subsequently expanded in a mouse model of xenogeneic liver regeneration. Chromosomal rAAV integration events and vector integrity were determined using the capture-PacBio sequencing approach, a long-read next-generation sequencing method that has not previously been used for this purpose. Chromosomal integrations were found at a surprisingly high frequency of 1%-3% both in vitro and in vivo. Importantly, most of the inserted rAAV sequences were heavily rearranged and were accompanied by deletions of the host genomic sequence at the integration site., Competing Interests: Declaration of interests M.G. has a financial interest in Yecuris Corp. (Tigard, Oregon), a company that has commercialized the humanized mouse liver model used in this work. MG also is a consultant for LogicBio Therapeutics. Other authors declare no competing interests., (Copyright © 2021 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.)
- Published
- 2021
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43. Optimising pyrazinamide for the treatment of tuberculosis.
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Zhang N, Savic RM, Boeree MJ, Peloquin CA, Weiner M, Heinrich N, Bliven-Sizemore E, Phillips PPJ, Hoelscher M, Whitworth W, Morlock G, Posey J, Stout JE, Mac Kenzie W, Aarnoutse R, and Dooley KE
- Subjects
- Antitubercular Agents therapeutic use, Humans, Isoniazid, Pyrazinamide, Rifampin, Antibiotics, Antitubercular, Tuberculosis drug therapy
- Abstract
Pyrazinamide is a potent sterilising agent that shortens the treatment duration needed to cure tuberculosis. It is synergistic with novel and existing drugs for tuberculosis. The dose of pyrazinamide that optimises efficacy while remaining safe is uncertain, as is its potential role in shortening treatment duration further.Pharmacokinetic data, sputum culture, and safety laboratory results were compiled from Tuberculosis Trials Consortium (TBTC) studies 27 and 28 and Pan-African Consortium for the Evaluation of Antituberculosis Antibiotics (PanACEA) multi-arm multi-stage tuberculosis (MAMS-TB), multi-centre phase 2 trials in which participants received rifampicin (range 10-35 mg·kg
-1 ), pyrazinamide (range 20-30 mg·kg-1 ), plus two companion drugs. Pyrazinamide pharmacokinetic-pharmacodynamic (PK-PD) and pharmacokinetic-toxicity analyses were performed.In TBTC studies (n=77), higher pyrazinamide maximum concentration (Cmax ) was associated with shorter time to culture conversion (TTCC) and higher probability of 2-month culture conversion (p-value<0.001). Parametric survival analyses showed that relationships varied geographically, with steeper PK-PD relationships seen among non-African than African participants. In PanACEA MAMS-TB (n=363), TTCC decreased as pyrazinamide Cmax increased and varied by rifampicin area under the curve (p-value<0.01). Modelling and simulation suggested that very high doses of pyrazinamide (>4500 mg) or increasing both pyrazinamide and rifampicin would be required to reach targets associated with treatment shortening. Combining all trials, liver toxicity was rare (3.9% with grade 3 or higher liver function tests (LFT)), and no relationship was seen between pyrazinamide Cmax and LFT levels.Pyrazinamide's microbiological efficacy increases with increasing drug concentrations. Optimising pyrazinamide alone, though, is unlikely to be sufficient to allow tuberculosis treatment shortening; rather, rifampicin dose would need to be increased in parallel., Competing Interests: Conflict of interest: N. Zhang has nothing to disclose. Conflict of interest: R.M. Savic has nothing to disclose. Conflict of interest: M.J. Boeree has nothing to disclose. Conflict of interest: C.A. Peloquin has nothing to disclose. Conflict of interest: M. Weiner has nothing to disclose. Conflict of interest: N. Heinrich reports grants from EDCTP (EU), during the conduct of the study; personal fees for lectures from AstraZeneca, outside the submitted work. Conflict of interest: E. Bliven-Sizemore has nothing to disclose. Conflict of interest: P.P.J. Phillips reports grants from EDCTP, during the conduct of the study. Conflict of interest: M. Hoelscher has nothing to disclose. Conflict of interest: W. Whitworth has nothing to disclose. Conflict of interest: G. Morlock has nothing to disclose. Conflict of interest: J. Posey has nothing to disclose. Conflict of interest: J.E. Stout has nothing to disclose. Conflict of interest: W. Mac Kenzie has nothing to disclose. Conflict of interest: R. Aarnoutse has nothing to disclose. Conflict of interest: K.E. Dooley has nothing to disclose., (The content of this work is not subject to copyright. Design and branding are copyright ©ERS 2021. For commercial reproduction rights and permissions contact permissions@ersnet.org.)- Published
- 2021
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44. Logically Inferred Tuberculosis Transmission (LITT): A Data Integration Algorithm to Rank Potential Source Cases.
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Winglee K, McDaniel CJ, Linde L, Kammerer S, Cilnis M, Raz KM, Noboa W, Knorr J, Cowan L, Reynolds S, Posey J, Sullivan Meissner J, Poonja S, Shaw T, Talarico S, and Silk BJ
- Subjects
- Algorithms, Humans, Molecular Epidemiology, Whole Genome Sequencing, Mycobacterium tuberculosis genetics, Tuberculosis epidemiology
- Abstract
Understanding tuberculosis (TB) transmission chains can help public health staff target their resources to prevent further transmission, but currently there are few tools to automate this process. We have developed the Logically Inferred Tuberculosis Transmission (LITT) algorithm to systematize the integration and analysis of whole-genome sequencing, clinical, and epidemiological data. Based on the work typically performed by hand during a cluster investigation, LITT identifies and ranks potential source cases for each case in a TB cluster. We evaluated LITT using a diverse dataset of 534 cases in 56 clusters (size range: 2-69 cases), which were investigated locally in three different U.S. jurisdictions. Investigators and LITT agreed on the most likely source case for 145 (80%) of 181 cases. By reviewing discrepancies, we found that many of the remaining differences resulted from errors in the dataset used for the LITT algorithm. In addition, we developed a graphical user interface, user's manual, and training resources to improve LITT accessibility for frontline staff. While LITT cannot replace thorough field investigation, the algorithm can help investigators systematically analyze and interpret complex data over the course of a TB cluster investigation. Code available at: https://github.com/CDCgov/TB_molecular_epidemiology/tree/1.0; https://zenodo.org/badge/latestdoi/166261171., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Winglee, McDaniel, Linde, Kammerer, Cilnis, Raz, Noboa, Knorr, Cowan, Reynolds, Posey, Sullivan Meissner, Poonja, Shaw, Talarico and Silk.)
- Published
- 2021
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45. Therapeutic liver repopulation by transient acetaminophen selection of gene-modified hepatocytes.
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Vonada A, Tiyaboonchai A, Nygaard S, Posey J, Peters AM, Winn SR, Cantore A, Naldini L, Harding CO, and Grompe M
- Subjects
- Animals, Genetic Therapy, Liver, Mice, Transgenes, Acetaminophen, Hepatocytes
- Abstract
Gene therapy by integrating vectors is promising for monogenic liver diseases, especially in children where episomal vectors remain transient. However, reaching the therapeutic threshold with genome-integrating vectors is challenging. Therefore, we developed a method to expand hepatocytes bearing therapeutic transgenes. The common fever medicine acetaminophen becomes hepatotoxic via cytochrome p450 metabolism. Lentiviral vectors with transgenes linked in cis to a Cypor shRNA were administered to neonatal mice. Hepatocytes lacking the essential cofactor of Cyp enzymes, NADPH-cytochrome p450 reductase (Cypor), were selected in vivo by acetaminophen administration, replacing up to 50% of the hepatic mass. Acetaminophen treatment of the mice resulted in over 30-fold expansion of transgene-bearing hepatocytes and achieved therapeutic thresholds in hemophilia B and phenylketonuria. We conclude that therapeutically modified hepatocytes can be selected safely and efficiently in preclinical models with a transient regimen of moderately hepatotoxic acetaminophen., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)
- Published
- 2021
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46. Multi-agent neoadjuvant chemotherapy improves survival in early-stage pancreatic cancer: A National Cancer Database analysis.
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Deng A, Wang C, Cohen SJ, Winter JM, Posey J, Yeo C, and Basu Mallick A
- Subjects
- Adenocarcinoma mortality, Adenocarcinoma pathology, Aged, Antineoplastic Combined Chemotherapy Protocols adverse effects, Chemotherapy, Adjuvant, Databases, Factual, Female, Humans, Male, Middle Aged, Neoplasm Staging, Pancreatectomy, Pancreatic Neoplasms mortality, Pancreatic Neoplasms pathology, Retrospective Studies, Risk Assessment, Risk Factors, Time Factors, Treatment Outcome, United States, Adenocarcinoma drug therapy, Antineoplastic Combined Chemotherapy Protocols therapeutic use, Neoadjuvant Therapy adverse effects, Neoadjuvant Therapy mortality, Pancreatic Neoplasms drug therapy
- Abstract
Purpose: To compare overall survival (OS) in patients who underwent surgery for early-stage pancreatic adenocarcinoma (rPca) based on sequence (NAT, neoadjuvant therapy and/or AT, adjuvant therapy) and type (SA, single-agent or MA, multi-agent) of chemotherapy received., Methods: Using the National Cancer Database, patients with clinical stage I/II rPca diagnosed between 2010 and 2014 were identified and five comparison matches (1: NAT vs. upfront resection (UR); 2: multi-agent neoadjuvant (MA NAT) vs. single-agent adjuvant therapy (SA AT), single-agent neoadjuvant therapy (SA NAT), multi-agent adjuvant therapy (MA AT); 3: MA NAT vs. MA AT; 4: NAT + AT vs NAT; 5: NAT + AT vs AT) were constructed using minimum distance matching strategy. Median OS (mOS) was analysed using Kaplan-Meier method, log-rank test and Cox proportional hazard model., Results: A total of 18,470 patients with stage I/II rPca were eligible for analysis. NAT showed a 5 month (mo.) improved OS compared with UR (3271 patients/group, 28.1 vs 23.2 mo. P < 0.0001 hazard ratio [HR]: 0.79). MA-NAT was shown to be superior to other chemotherapy approaches SA AT, SA NAT, and MA AT (1349 patients/group: 30 vs. 25.9 mo., P = 0.0001 [HR: 0.82]). MA NAT showed a survival advantage over MA-AT (1349 patients/group, 30 vs 26.1 mo., P = 0.0008 [HR: 0.86]). The combination of NAT and AT showed a better outcome when compared with NAT alone (1128 patients/group, 31.6 vs 27.4 mo., P = 0.0011 [HR: 0.81]) or AT alone (1128 patients/group, 31.6 vs. 25.2 mo., P < 0.0001 [HR: 0.76])., Conclusions: In patients with stage I/II rPca, MA NAT showed improved mOS compared to UR and all other chemotherapy sequences except both NAT plus AT. These findings support the use of MA NAT in stage I/II rPca patients and warrant prospective trials evaluating MA NAT and post-resection maintenance therapies., Competing Interests: Conflict of interest statement None., (Copyright © 2021 Elsevier Ltd. All rights reserved.)
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- 2021
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47. Racial Disparities in Rates of Surgery for Esophageal Cancer: a Study from the National Cancer Database.
- Author
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Savitch SL, Grenda TR, Scott W, Cowan SW, Posey J 3rd, Mitchell EP, Cohen SJ, Yeo CJ, and Evans NR 3rd
- Subjects
- Black or African American, Databases, Factual, Humans, United States epidemiology, White People, Esophageal Neoplasms surgery, Healthcare Disparities
- Abstract
Background: Treatment guidelines for stage I-III esophageal cancer indicate that management should include surgery in appropriate patients. Variations in utilization of surgery may contribute to racial differences observed in survival. We sought to identify factors associated with racial disparities in surgical resection of esophageal cancer and evaluate associated survival differences., Methods: Patients diagnosed with stage I-III esophageal cancer from 2004 to 2015 were identified using the National Cancer Database. Matched patient cohorts were created to reduce confounding. Multivariate logistic regression was used to identify factors associated with receipt of surgery. Multi-level modeling was performed to control for random effects of individual hospitals on surgical utilization., Results: A total of 60,041 patients were included (4402 black; 55,639 white). After 1:1 matching, there were 5858 patients evenly distributed across race. For all stages, significantly fewer black than white patients received surgery. Black race independently conferred lower likelihood of receiving surgery in single-level multivariable analysis (OR (95% CI); stage I, 0.67 (0.48-0.94); stage II, 0.76 (0.60-0.96); stage III, 0.62 (0.50-0.76)) and after controlling for hospital random effects. Hospital-level random effects accounted for one third of the unexplained variance in receipt of surgery. Risk-adjusted 1-, 3-, and 5-year mortality was higher for patients who did not undergo surgery., Conclusion: Black patients with esophageal cancer are at higher risk of mortality compared to white patients. This increased risk may be influenced by decreased likelihood of receiving surgical intervention for resectable disease, in part because of between-hospital differences. Improving access to surgical care may improve disparities in esophageal cancer survival.
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- 2021
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48. Platelet activation contributes to hypoxia-induced inflammation.
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Delaney C, Davizon-Castillo P, Allawzi A, Posey J, Gandjeva A, Neeves K, Tuder RM, Di Paola J, Stenmark KR, and Nozik ES
- Subjects
- Animals, Blood Platelets pathology, Chemokine CCL5 immunology, Disease Models, Animal, Female, Granulocyte-Macrophage Colony-Stimulating Factor immunology, Hypoxia pathology, Inflammation immunology, Inflammation pathology, Lung pathology, Male, Mice, Platelet Factor 4 immunology, Pneumonia pathology, Thrombocytopenia chemically induced, Thrombocytopenia immunology, Thrombocytopenia pathology, Blood Platelets immunology, Hypoxia immunology, Lung immunology, Platelet Activation immunology, Pneumonia immunology
- Abstract
Inflammation is central to the pathogenesis of pulmonary vascular remodeling and pulmonary hypertension (PH). Inflammation precedes remodeling in preclinical models, thus supporting the concept that changes in immunity drive remodeling in PH. Platelets are recognized as mediators of inflammation, but whether platelets contribute to hypoxia-driven inflammation has not been studied. We utilized a murine hypoxia model to test the hypothesis that platelets drive hypoxia-induced inflammation. We evaluated male and female 9-wk-old normoxic and hypoxic mice and in selected experiments included hypoxic thrombocytopenic mice. Thrombocytopenic mice were generated with an anti-GP1bα rat IgG antibody. We also performed immunostaining of lung sections from failed donor controls and patients with idiopathic pulmonary arterial hypertension. We found that platelets are increased in the lungs of hypoxic mice and hypoxia induces platelet activation. Platelet depletion prevents hypoxia-driven increases in the proinflammatory chemokines CXCL4 and CCL5 and attenuates hypoxia-induced increase in plasma CSF-2. Pulmonary interstitial macrophages are increased in the lungs of hypoxic mice; this increase is prevented in thrombocytopenic mice. To determine the potential relevance to human disease, lung sections from donors and patients with advanced idiopathic pulmonary arterial hypertension (iPAH) were immunostained for the platelet-specific protein CD41. We observed iPAH lungs had a two-fold increase in CD41, compared with controls. Our data provide evidence that the platelet count is increased in the lungs and activated in mice with hypoxia-induced inflammation and provides rationale for the further study of the potential contribution of platelets to inflammatory mediated vascular remodeling and PH.
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- 2021
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49. Liver Injury Increases the Incidence of HCC following AAV Gene Therapy in Mice.
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Dalwadi DA, Torrens L, Abril-Fornaguera J, Pinyol R, Willoughby C, Posey J, Llovet JM, Lanciault C, Russell DW, Grompe M, and Naugler WE
- Subjects
- Animals, Carcinoma, Hepatocellular diagnosis, Disease Models, Animal, Genetic Therapy methods, Incidence, Liver Diseases pathology, Liver Neoplasms diagnosis, Mice, Carcinoma, Hepatocellular etiology, Dependovirus genetics, Genetic Therapy adverse effects, Genetic Vectors genetics, Liver Diseases complications, Liver Diseases etiology, Liver Neoplasms etiology
- Abstract
Adeno-associated virus (AAV) integrates into host genomes at low frequency, but when integration occurs in oncogenic hotspots it can cause hepatocellular carcinoma (HCC). Given the possibility of recombinant AAV (rAAV) integration leading to HCC, common causes of liver inflammation like non-alcoholic fatty liver disease (NAFLD) may increase the risk of rAAV-induced HCC. A rAAV targeting the oncogenic mouse Rian locus was used, and as expected led to HCC in all mice infected as neonates, likely due to growth-related hepatocyte proliferation in young mice. Mice infected with rAAV as adults did not develop HCC unless they were fed a diet leading to NAFLD, with increased inflammation and hepatocyte proliferation. Female mice were less susceptible to rAAV-induced HCC, and male mice with NAFLD treated with estrogen exhibited less inflammation and immune exhaustion associated with oncogenesis compared to those without estrogen. Adult NAFLD mice infected with a non-targeted control rAAV also developed HCC, though only half as frequently as those exposed to the Rian targeted rAAV. This study shows that adult mice exposed to rAAV gene therapy in the context of chronic liver disease developed HCC at high frequency, and thus warrants further study in humans given the high prevalence of NAFLD in the population., (Copyright © 2020 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.)
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- 2021
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50. A step towards personalizing next line therapy for resected pancreatic and related cancer patients: A single institution's experience.
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Lowder CY, Dhir T, Goetz AB, Thomsett HL, Bender J, Tatarian T, Madhavan S, Petricoin EF 3rd, Blais E, Lavu H, Winter JM, Posey J 3rd, Brody JR, Pishvaian MJ, and Yeo CJ
- Subjects
- Aged, Carcinoma, Pancreatic Ductal therapy, Chemotherapy, Adjuvant, DNA Copy Number Variations, Feasibility Studies, Female, Genomics, Humans, Male, Middle Aged, Molecular Targeted Therapy, Mutation, Pancreatectomy, Pancreatic Neoplasms therapy, Poly(ADP-ribose) Polymerase Inhibitors therapeutic use, Protein Kinase Inhibitors therapeutic use, Proteomics, Registries, Carcinoma, Pancreatic Ductal genetics, Pancreatic Neoplasms genetics, Precision Medicine methods
- Abstract
Background: There is a lack of precision medicine in pancreatic ductal adenocarcinoma (PDA) and related cancers, and outcomes for patients with this diagnosis remain poor despite decades of research investigating this disease. Therefore, it is necessary to explore novel therapeutic options for these patients who may benefit from personalized therapies., Objective: Molecular profiling of hepatopancreaticobiliary malignancies at our institution, including but not limited to PDA, was initiated to assess the feasibility of incorporating molecular profiling results into patient oncological therapy planning., Methods: All eligible patients from Thomas Jefferson University (TJU) with hepatopancreaticobiliary tumors including PDA, who agreed to molecular testing profiling, were prospectively enrolled in a registry study from December 2014 to September 2017 and their tumor samples were tested to identify molecular markers that can be used to guide therapy options in the future. Next generation sequencing (NGS) and protein expression in tumor samples were tested at CLIA-certified laboratories. Prospective clinicopathologic data were extracted from medical records and compiled in a de-identified fashion., Results: Seventy eight (78) patients were enrolled in the study, which included 65/78 patients with PDA (local and metastatic) and out of that subset, 52/65 patients had surgically resected PDA. Therapy recommendations were generated based on molecular and clinicopathologic data for all enrolled patients. NGS uncovered actionable alterations in 25/52 surgically resected PDAs (48%) which could be used to guide therapy options in the future. High expression of three proteins, TS (p = 0.005), ERCC1 (p = 0.001), and PD-1 (p = 0.04), was associated with reduced recurrence-free survival (RFS), while TP53 mutations were correlated with longer RFS (p = 0.01)., Conclusions: The goal of this study was to implement a stepwise strategy to identify and profile resected PDAs at our institution. Consistent with previous studies, approximately half of patients with resected PDA harbor actionable mutations with possible targeted therapeutic implications. Ongoing studies will determine the clinical value of identifying these mutations in patients with resected PDA., Competing Interests: Declaration of competing interest Joseph Bender, PhD, Talar Tatarian, MD, Subha Madhavan, PhD, Emanuel F Petricoin 3rd, PhD, Michael J Pishvaian, MD, PhD, and Jonathan R Brody, PhD have affiliations with Perthera, Inc., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)
- Published
- 2020
- Full Text
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