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Start Over Author "Parfenov, Michael" Journal nature genetics
3 results on '"Parfenov, Michael"'

1. Genomic analyses implicate noncoding de novo variants in congenital heart disease

Author

Richter, Felix, Morton, Sarah U, Kim, Seong Won, Kitaygorodsky, Alexander, Wasson, Lauren K, Chen, Kathleen M, Zhou, Jian, Qi, Hongjian, Patel, Nihir, DePalma, Steven R, Parfenov, Michael, Homsy, Jason, Gorham, Joshua M, Manheimer, Kathryn B, Velinder, Matthew, Farrell, Andrew, Marth, Gabor, Schadt, Eric E, Kaltman, Jonathan R, Newburger, Jane W, Giardini, Alessandro, Goldmuntz, Elizabeth, Brueckner, Martina, Kim, Richard, Porter, George A, Bernstein, Daniel, Chung, Wendy K, Srivastava, Deepak, Tristani-Firouzi, Martin, Troyanskaya, Olga G, Dickel, Diane E, Shen, Yufeng, Seidman, Jonathan G, Seidman, Christine E, and Gelb, Bruce D

Subjects
Biological Sciences, Genetics, Congenital Structural Anomalies, Heart Disease, Pediatric, Human Genome, Cardiovascular, Aetiology, 2.1 Biological and endogenous factors, Adolescent, Adult, Animals, Female, Genetic Predisposition to Disease, Genetic Variation, Genomics, Heart, Heart Defects, Congenital, Humans, Male, Mice, Middle Aged, Open Reading Frames, RNA, Untranslated, RNA-Binding Proteins, Transcription, Genetic, Young Adult, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

A genetic etiology is identified for one-third of patients with congenital heart disease (CHD), with 8% of cases attributable to coding de novo variants (DNVs). To assess the contribution of noncoding DNVs to CHD, we compared genome sequences from 749 CHD probands and their parents with those from 1,611 unaffected trios. Neural network prediction of noncoding DNV transcriptional impact identified a burden of DNVs in individuals with CHD (n = 2,238 DNVs) compared to controls (n = 4,177; P = 8.7 × 10-4). Independent analyses of enhancers showed an excess of DNVs in associated genes (27 genes versus 3.7 expected, P = 1 × 10-5). We observed significant overlap between these transcription-based approaches (odds ratio (OR) = 2.5, 95% confidence interval (CI) 1.1-5.0, P = 5.4 × 10-3). CHD DNVs altered transcription levels in 5 of 31 enhancers assayed. Finally, we observed a DNV burden in RNA-binding-protein regulatory sites (OR = 1.13, 95% CI 1.1-1.2, P = 8.8 × 10-5). Our findings demonstrate an enrichment of potentially disruptive regulatory noncoding DNVs in a fraction of CHD at least as high as that observed for damaging coding DNVs.

Published
2020

2. The Cancer Genome Atlas Pan-Cancer analysis project

Author

Chang, Kyle, Creighton, Chad J, Davis, Caleb, Donehower, Lawrence, Drummond, Jennifer, Wheeler, David, Ally, Adrian, Balasundaram, Miruna, Birol, Inanc, Butterfield, Yaron SN, Chu, Andy, Chuah, Eric, Chun, Hye-Jung E, Dhalla, Noreen, Guin, Ranabir, Hirst, Martin, Hirst, Carrie, Holt, Robert A, Jones, Steven JM, Lee, Darlene, Li, Haiyan I, Marra, Marco A, Mayo, Michael, Moore, Richard A, Mungall, Andrew J, Robertson, A Gordon, Schein, Jacqueline E, Sipahimalani, Payal, Tam, Angela, Thiessen, Nina, Varhol, Richard J, Beroukhim, Rameen, Bhatt, Ami S, Brooks, Angela N, Cherniack, Andrew D, Freeman, Samuel S, Gabriel, Stacey B, Helman, Elena, Jung, Joonil, Meyerson, Matthew, Ojesina, Akinyemi I, Pedamallu, Chandra Sekhar, Saksena, Gordon, Schumacher, Steven E, Tabak, Barbara, Zack, Travis, Lander, Eric S, Bristow, Christopher A, Hadjipanayis, Angela, Haseley, Psalm, Kucherlapati, Raju, Lee, Semin, Lee, Eunjung, Luquette, Lovelace J, Mahadeshwar, Harshad S, Pantazi, Angeliki, Parfenov, Michael, Park, Peter J, Protopopov, Alexei, Ren, Xiaojia, Santoso, Netty, Seidman, Jonathan, Seth, Sahil, Song, Xingzhi, Tang, Jiabin, Xi, Ruibin, Xu, Andrew W, Yang, Lixing, Zeng, Dong, Auman, J Todd, Balu, Saianand, Buda, Elizabeth, Fan, Cheng, Hoadley, Katherine A, Jones, Corbin D, Meng, Shaowu, Mieczkowski, Piotr A, Parker, Joel S, Perou, Charles M, Roach, Jeffrey, Shi, Yan, Silva, Grace O, Tan, Donghui, Veluvolu, Umadevi, Waring, Scot, Wilkerson, Matthew D, Wu, Junyuan, Zhao, Wei, Bodenheimer, Tom, Hayes, D Neil, Hoyle, Alan P, Jeffreys, Stuart R, Mose, Lisle E, Simons, Janae V, Soloway, Mathew G, Baylin, Stephen B, Berman, Benjamin P, Bootwalla, Moiz S, Danilova, Ludmila, and Herman, James G

Subjects
Biological Sciences, Genetics, Cancer, Human Genome, Rare Diseases, Good Health and Well Being, Gene Expression Profiling, Genome, Humans, Neoplasms, Cancer Genome Atlas Research Network, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.

Published
2013

3. Genomic analyses implicate noncoding de novo variants in congenital heart disease

Author

Richter, Felix, Morton, Sarah U, Kim, Seong Won, Kitaygorodsky, Alexander, Wasson, Lauren K, Chen, Kathleen M, Zhou, Jian, Qi, Hongjian, Patel, Nihir, DePalma, Steven R, Parfenov, Michael, Homsy, Jason, Gorham, Joshua M, Manheimer, Kathryn B, Velinder, Matthew, Farrell, Andrew, Marth, Gabor, Schadt, Eric E, Kaltman, Jonathan R, Newburger, Jane W, Giardini, Alessandro, Goldmuntz, Elizabeth, Brueckner, Martina, Kim, Richard, Porter, George A, Bernstein, Daniel, Chung, Wendy K, Srivastava, Deepak, Tristani-Firouzi, Martin, Troyanskaya, Olga G, Dickel, Diane E, Shen, Yufeng, Seidman, Jonathan G, Seidman, Christine E, and Gelb, Bruce D

Subjects
Adult, Heart Defects, Congenital, Male, RNA, Untranslated, Adolescent, Transcription, Genetic, Cardiovascular, Medical and Health Sciences, Congenital, Mice, Open Reading Frames, Young Adult, Genetic, Genetics, 2.1 Biological and endogenous factors, Animals, Humans, Genetic Predisposition to Disease, Aetiology, Heart Defects, Pediatric, Human Genome, Untranslated, Genetic Variation, RNA-Binding Proteins, Heart, Genomics, Biological Sciences, Middle Aged, Heart Disease, Congenital Structural Anomalies, RNA, Female, Transcription, Developmental Biology
Abstract

A genetic etiology is identified for one-third of patients with congenital heart disease (CHD), with 8% of cases attributable to coding de novo variants (DNVs). To assess the contribution of noncoding DNVs to CHD, we compared genome sequences from 749 CHD probands and their parents with those from 1,611 unaffected trios. Neural network prediction of noncoding DNV transcriptional impact identified a burden of DNVs in individuals with CHD (n = 2,238 DNVs) compared to controls (n = 4,177; P = 8.7 × 10-4). Independent analyses of enhancers showed an excess of DNVs in associated genes (27 genes versus 3.7 expected, P = 1 × 10-5). We observed significant overlap between these transcription-based approaches (odds ratio (OR) = 2.5, 95% confidence interval (CI) 1.1-5.0, P = 5.4 × 10-3). CHD DNVs altered transcription levels in 5 of 31 enhancers assayed. Finally, we observed a DNV burden in RNA-binding-protein regulatory sites (OR = 1.13, 95% CI 1.1-1.2, P = 8.8 × 10-5). Our findings demonstrate an enrichment of potentially disruptive regulatory noncoding DNVs in a fraction of CHD at least as high as that observed for damaging coding DNVs.

Published
2019

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