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4. Beyond the exome: What’s next in diagnostic testing for Mendelian conditions

Author

Abouhala, Siwaar, Albert, Jessica, Almalvez, Miguel, Alvarez, Raquel, Amin, Mutaz, Anderson, Peter, Aradhya, Swaroop, Ashley, Euan, Assimes, Themistocles, Auriga, Light, Austin-Tse, Christina, Bamshad, Mike, Barseghyan, Hayk, Baxter, Samantha, Behera, Sairam, Beheshti, Shaghayegh, Bejerano, Gill, Berger, Seth, Bernstein, Jon, Best, Sabrina, Blankenmeister, Benjamin, Blue, Elizabeth, Boerwinkle, Eric, Bonkowski, Emily, Bonner, Devon, Boone, Philip, Bornhorst, Miriam, Bozkurt-Yozgatli, Tugce, Brand, Harrison, Buckingham, Kati, Calame, Daniel, Casadei, Silvia, Chadwick, Lisa, Chavez, Clarisa, Chen, Ziwei, Chinn, Ivan, Chong, Jessica, Coban-Akdemir, Zeynep, Cohen, Andrea J., Conner, Sarah, Conomos, Matthew, Coveler, Karen, Cui, Ya Allen, Currin, Sara, Daber, Robert, Dardas, Zain, Davis, Colleen, Dawood, Moez, de Dios, Ivan, de Esch, Celine, Delaney, Meghan, Délot, Emmanuèle, DiTroia, Stephanie, Doddapaneni, Harsha, Du, Haowei, Duan, Ruizhi, Dugan-Perez, Shannon, Duong, Nhat, Duyzend, Michael, Eichler, Evan, Emami, Sara, Fatih, Jawid, Fraser, Jamie, Fusaro, Vincent, Galey, Miranda, Ganesh, Vijay, Garimella, Kiran, Gibbs, Richard, Gifford, Casey, Ginsburg, Amy, Goddard, Pagé, Gogarten, Stephanie, Gogate, Nikhita, Gordon, William, Gorzynski, John E., Greenleaf, William, Grochowski, Christopher, Groopman, Emily, Guarischi Sousa, Rodrigo, Gudmundsson, Sanna, Gulati, Ashima, Guo, Daniel, Hale, Walker, Hall, Stacey, Harvey, William, Hawley, Megan, Heavner, Ben, Herman, Isabella, Horike-Pyne, Martha, Hu, Jianhong, Huang, Yongqing, Hwang, James, Jarvik, Gail, Jensen, Tanner, Jhangiani, Shalini, Jimenez-Morales, David, Jin, Christopher, Saad, Ahmed K., Kahn-Kirby, Amanda, Kain, Jessica, Kaur, Parneet, Keehan, Laura, Knoblach, Susan, Ko, Arthur, Kohler, Jennefer, Kundaje, Anshul, Kundu, Soumya, Lancaster, Samuel M., Larsson, Katie, Lemire, Gabrielle, Lewis, Richard, Li, Wei, Li, Yidan, Liu, Pengfei, LoTempio, Jonathan, Lupski, James, Ma, Jialan, MacArthur, Daniel, Mahmoud, Medhat, Malani, Nirav, Mangilog, Brian, Marafi, Dana, Marmolejos, Sofia, Marten, Daniel, Martinez, Eva, Marvin, Colby, Marwaha, Shruti, Kumara Mastrorosa, Francesco, Matalon, Dena, May, Susanne, McGee, Sean, Meador, Lauren, Mefford, Heather, Rodrigo Mendez, Hector, Miller, Alexander, Miller, Danny E., Mitani, Tadahiro, Montgomery, Stephen, Moussa, Hala Mohamed, Moyses, Mariana, Munderloh, Chloe, Muzny, Donna, Nelson, Sarah, Neu, Matthew B., Nguyen, Jonathan, Nguyen, Thuy-mi P., Nussbaum, Robert, Nykamp, Keith, O'Callaghan, William, O'Heir, Emily, O'Leary, Melanie, Olsen, Jeren, Osei-Owusu, Ikeoluwa, O'Donnell-Luria, Anne, Padhi, Evin, Pais, Lynn, Pan, Miao, Panchal, Piyush, Patterson, Karynne, Payne, Sheryl, Pehlivan, Davut, Petrowski, Paul, Pham, Alicia, Pitsava, Georgia, Podesta, Astaria, Ponce, Sarah, Posey, Jennifer, Prosser, Jaime, Quertermous, Thomas, Rai, Archana, Ramani, Arun, Rehm, Heidi, Reuter, Chloe, Reuter, Jason, Richardson, Matthew, Rivera-Munoz, Andres, Rubio, Oriane, Sabo, Aniko, Salani, Monica, Samocha, Kaitlin, Sanchis-Juan, Alba, Savage, Sarah, Scott, Stuart, Scott, Evette, Sedlazeck, Fritz, Shah, Gulalai, Shojaie, Ali, Singh, Mugdha, Smith, Josh, Smith, Kevin, Snow, Hana, Snyder, Michael, Socarras, Kayla, Starita, Lea, Stark, Brigitte, Stenton, Sarah, Stergachis, Andrew, Stilp, Adrienne, Sundaram, Laksshman, Sutton, V. Reid, Tai, Jui-Cheng, Talkowski, Michael, Tise, Christina, Tong, Catherine, Tsao, Philip, Ungar, Rachel, VanNoy, Grace, Vilain, Eric, Voutos, Isabella, Walker, Kim, Weisburd, Ben, Weiss, Jeff, Wellington, Chris, Weng, Ziming, Westheimer, Emily, Wheeler, Marsha, Wheeler, Matthew, Wiel, Laurens, Wilson, Michael, Wojcik, Monica, Wong, Quenna, Wong, Issac, Xiao, Changrui, Yadav, Rachita, Yi, Qian, Yuan, Bo, Zhao, Jianhua, Zhen, Jimmy, Zhou, Harry, Wojcik, Monica H., Reuter, Chloe M., Duyzend, Michael H., Boone, Philip M., Groopman, Emily E., Délot, Emmanuèle C., Jain, Deepti, Starita, Lea M., Montgomery, Stephen B., Bamshad, Michael J., Chong, Jessica X., Wheeler, Matthew T., Berger, Seth I., and Sedlazeck, Fritz J.

Published
2023
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5. Gustavson syndrome is caused by an in-frame deletion in RBMXassociated with potentially disturbed SH3 domain interactions

Author

Johansson, Josefin, Lidéus, Sarah, Frykholm, Carina, Gunnarsson, Cecilia, Mihalic, Filip, Gudmundsson, Sanna, Ekvall, Sara, Molin, Anna-Maja, Pham, Mai, Vihinen, Mauno, Lagerstedt-Robinson, Kristina, Nordgren, Ann, Jemth, Per, Ameur, Adam, Annerén, Göran, Wilbe, Maria, and Bondeson, Marie-Louise

Abstract

RNA binding motif protein X‐linked (RBMX) encodes the heterogeneous nuclear ribonucleoprotein G (hnRNP G) that regulates splicing, sister chromatid cohesion and genome stability. RBMXknock down experiments in various model organisms highlight the gene’s importance for brain development. Deletion of the RGG/RG motif in hnRNP G has previously been associated with Shashi syndrome, however involvement of other hnRNP G domains in intellectual disability remain unknown. In the current study, we present the underlying genetic and molecular cause of Gustavson syndrome. Gustavson syndrome was first reported in 1993 in a large Swedish five-generation family presented with profound X-linked intellectual disability and an early death. Extensive genomic analyses of the family revealed hemizygosity for a novel in-frame deletion in RBMXin affected individuals (NM_002139.4; c.484_486del, p.(Pro162del)). Carrier females were asymptomatic and presented with skewed X-chromosome inactivation, indicating silencing of the pathogenic allele. Affected individuals presented minor phenotypic overlap with Shashi syndrome, indicating a different disease-causing mechanism. Investigation of the variant effect in a neuronal cell line (SH-SY5Y) revealed differentially expressed genes enriched for transcription factors involved in RNA polymerase II transcription. Prediction tools and a fluorescence polarization assay imply a novel SH3-binding motif of hnRNP G, and potentially a reduced affinity to SH3 domains caused by the deletion. In conclusion, we present a novel in-frame deletion in RBMXsegregating with Gustavson syndrome, leading to disturbed RNA polymerase II transcription, and potentially reduced SH3 binding. The results indicate that disruption of different protein domains affects the severity of RBMX-associated intellectual disabilities.

Published
2024
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6. Advanced variant classification framework reduces the false positive rate of predicted loss of function (pLoF) variants in population sequencing data

Author

Singer-Berk, Moriel, primary, Gudmundsson, Sanna, additional, Baxter, Samantha, additional, Seaby, Eleanor G, additional, Wood, Jordan C, additional, Son, Rachel G, additional, Watts, Nicholas A, additional, Karczewski, Konrad, additional, Harrison, Steven, additional, MacArthur, Daniel G, additional, Rehm, Heidi L, additional, and O'Donnell-Luria, Anne, additional

Published
2023
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8. P559: Improved classification framework demonstrates many population predicted loss of function (pLoF) variants in genomic sequencing do not result in LoF*

Author

Singer-Berk, Moriel, primary, Gudmundsson, Sanna, additional, Baxter, Samantha, additional, Seaby, Eleanor, additional, England, Eleina, additional, Wood, Jordan, additional, Son, Rachel, additional, Watts, Nicholas, additional, Karczewski, Konrad, additional, Harrison, Steven, additional, MacArthur, Daniel, additional, Rehm, Heidi, additional, and O'Donnell-Luria, Anne, additional

Published
2023
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9. Variant interpretation using population databases: Lessons from gnomAD

Author

Gudmundsson, Sanna, Singer-Berk, Moriel, Watts, Nicholas A., Phu, William, Goodrich, Julia K., Solomonson, Matthew, Consortium, Genome Aggregation Database, Rehm, Heidi L., MacArthur, Daniel G., and ODonnell-Luria, Anne

Subjects
Genomics (q-bio.GN), education.field_of_study, Database, Interpretation (philosophy), Population, Variation (game tree), Biology, computer.software_genre, Genome, Article, Identification (information), Rare Diseases, Gene Frequency, FOS: Biological sciences, Databases, Genetic, Genetics, Humans, Quantitative Biology - Genomics, Reference population, Human genome, education, computer, Allele frequency, Software, Genetics (clinical)
Abstract

Reference population databases are an essential tool in variant and gene interpretation. Their use guides the identification of pathogenic variants amidst the sea of benign variation present in every human genome, and supports the discovery of new disease-gene relationships. The Genome Aggregation Database (gnomAD) is currently the largest and most widely used publicly available collection of population variation from harmonized sequencing data. The data is available through the online gnomAD browser (https://gnomad.broadinstitute.org/) that enables rapid and intuitive variant analysis. This review provides guidance on the content of the gnomAD browser, and its usage for variant and gene interpretation. We introduce key features including allele frequency, per-base expression levels, constraint scores, and variant co-occurrence, alongside guidance on how to use these in analysis, with a focus on the interpretation of candidate variants and novel genes in rare disease., Version 3: Includes updates to mirror the latest features and layouts available on the gnomAD browser and general improvements to text and figures (clarifications, typos, additional references etc.) as well as the addition of Table S1, S2, Figure S1, S2 and S5

Published
2021

10. Centers for Mendelian Genomics: A decade of facilitating gene discovery

Author

Baxter, Samantha M., primary, Posey, Jennifer E., additional, Lake, Nicole J., additional, Sobreira, Nara, additional, Chong, Jessica X., additional, Buyske, Steven, additional, Blue, Elizabeth E., additional, Chadwick, Lisa H., additional, Coban-Akdemir, Zeynep H., additional, Doheny, Kimberly F., additional, Davis, Colleen P., additional, Lek, Monkol, additional, Wellington, Christopher, additional, Jhangiani, Shalini N., additional, Gerstein, Mark, additional, Gibbs, Richard A., additional, Lifton, Richard P., additional, MacArthur, Daniel G., additional, Matise, Tara C., additional, Lupski, James R., additional, Valle, David, additional, Bamshad, Michael J., additional, Hamosh, Ada, additional, Mane, Shrikant, additional, Nickerson, Deborah A., additional, Rehm, Heidi L., additional, O’Donnell-Luria, Anne, additional, Adams, Marcia, additional, Aguet, François, additional, Akay, Gulsen, additional, Anderson, Peter, additional, Antonescu, Corina, additional, Arachchi, Harindra M., additional, Atik, Mehmed M., additional, Austin-Tse, Christina A., additional, Babb, Larry, additional, Bacus, Tamara J., additional, Bahrambeigi, Vahid, additional, Balasubramanian, Suganthi, additional, Bayram, Yavuz, additional, Beaudet, Arthur L., additional, Beck, Christine R., additional, Belmont, John W., additional, Below, Jennifer E., additional, Bilguvar, Kaya, additional, Boehm, Corinne D., additional, Boerwinkle, Eric, additional, Boone, Philip M., additional, Bowne, Sara J., additional, Brand, Harrison, additional, Buckingham, Kati J., additional, Byrne, Alicia B., additional, Calame, Daniel, additional, Campbell, Ian M., additional, Cao, Xiaolong, additional, Carvalho, Claudia, additional, Chander, Varuna, additional, Chang, Jaime, additional, Chao, Katherine R., additional, Chinn, Ivan K., additional, Clarke, Declan, additional, Collins, Ryan L., additional, Cummings, Beryl, additional, Dardas, Zain, additional, Dawood, Moez, additional, Delano, Kayla, additional, DiTroia, Stephanie P., additional, Doddapaneni, Harshavardhan, additional, Du, Haowei, additional, Du, Renqian, additional, Duan, Ruizhi, additional, Eldomery, Mohammad, additional, Eng, Christine M., additional, England, Eleina, additional, Evangelista, Emily, additional, Everett, Selin, additional, Fatih, Jawid, additional, Felsenfeld, Adam, additional, Francioli, Laurent C., additional, Frazar, Christian D., additional, Fu, Jack, additional, Gamarra, Emmanuel, additional, Gambin, Tomasz, additional, Gan, Weiniu, additional, Gandhi, Mira, additional, Ganesh, Vijay S., additional, Garimella, Kiran V., additional, Gauthier, Laura D., additional, Giroux, Danielle, additional, Gonzaga-Jauregui, Claudia, additional, Goodrich, Julia K., additional, Gordon, William W., additional, Griffith, Sean, additional, Grochowski, Christopher M., additional, Gu, Shen, additional, Gudmundsson, Sanna, additional, Hall, Stacey J., additional, Hansen, Adam, additional, Harel, Tamar, additional, Harmanci, Arif O., additional, Herman, Isabella, additional, Hetrick, Kurt, additional, Hijazi, Hadia, additional, Horike-Pyne, Martha, additional, Hsu, Elvin, additional, Hu, Jianhong, additional, Huang, Yongqing, additional, Hurless, Jameson R., additional, Jahl, Steve, additional, Jarvik, Gail P., additional, Jiang, Yunyun, additional, Johanson, Eric, additional, Jolly, Angad, additional, Karaca, Ender, additional, Khayat, Michael, additional, Knight, James, additional, Kolar, J. Thomas, additional, Kumar, Sushant, additional, Lalani, Seema, additional, Laricchia, Kristen M., additional, Larkin, Kathryn E., additional, Leal, Suzanne M., additional, Lemire, Gabrielle, additional, Lewis, Richard A., additional, Li, He, additional, Ling, Hua, additional, Lipson, Rachel B., additional, Liu, Pengfei, additional, Lovgren, Alysia Kern, additional, López-Giráldez, Francesc, additional, MacMillan, Melissa P., additional, Mangilog, Brian E., additional, Mano, Stacy, additional, Marafi, Dana, additional, Marosy, Beth, additional, Marshall, Jamie L., additional, Martin, Renan, additional, Marvin, Colby T., additional, Mawhinney, Michelle, additional, McGee, Sean, additional, McGoldrick, Daniel J., additional, Mehaffey, Michelle, additional, Mekonnen, Betselote, additional, Meng, Xiaolu, additional, Mitani, Tadahiro, additional, Miyake, Christina Y., additional, Mohr, David, additional, Morris, Shaine, additional, Mullen, Thomas E., additional, Murdock, David R., additional, Murugan, Mullai, additional, Muzny, Donna M., additional, Myers, Ben, additional, Neira, Juanita, additional, Nguyen, Kevin K., additional, Nielsen, Patrick M., additional, Nudelman, Natalie, additional, O’Heir, Emily, additional, O’Leary, Melanie C., additional, Ongaco, Chrissie, additional, Orange, Jordan, additional, Osei-Owusu, Ikeoluwa A., additional, Paine, Ingrid S., additional, Pais, Lynn S., additional, Paschall, Justin, additional, Patterson, Karynne, additional, Pehlivan, Davut, additional, Pelle, Benjamin, additional, Penney, Samantha, additional, Perez de Acha Chavez, Jorge, additional, Pierce-Hoffman, Emma, additional, Poli, Cecilia M., additional, Punetha, Jaya, additional, Radhakrishnan, Aparna, additional, Richardson, Matthew A., additional, Rodrigues, Eliete, additional, Roote, Gwendolin T., additional, Rosenfeld, Jill A., additional, Ryke, Erica L., additional, Sabo, Aniko, additional, Sanchez, Alice, additional, Schrauwen, Isabelle, additional, Scott, Daryl A., additional, Sedlazeck, Fritz, additional, Serrano, Jillian, additional, Shaw, Chad A., additional, Shelford, Tameka, additional, Shively, Kathryn M., additional, Singer-Berk, Moriel, additional, Smith, Joshua D., additional, Snow, Hana, additional, Snyder, Grace, additional, Solomonson, Matthew, additional, Son, Rachel G., additional, Song, Xiaofei, additional, Stankiewicz, Pawel, additional, Stephan, Taylorlyn, additional, Sutton, V. Reid, additional, Sveden, Abigail, additional, Sánchez, Diana Cornejo, additional, Tackett, Monica, additional, Talkowski, Michael, additional, Threlkeld, Machiko S., additional, Tiao, Grace, additional, Udler, Miriam S., additional, Vail, Laura, additional, Valivullah, Zaheer, additional, Valkanas, Elise, additional, VanNoy, Grace E., additional, Wang, Qingbo S., additional, Wang, Gao, additional, Wang, Lu, additional, Wangler, Michael F., additional, Watts, Nicholas A., additional, Weisburd, Ben, additional, Weiss, Jeffrey M., additional, Wheeler, Marsha M., additional, White, Janson J., additional, Williamson, Clara E., additional, Wilson, Michael W., additional, Wiszniewski, Wojciech, additional, Withers, Marjorie A., additional, Witmer, Dane, additional, Witzgall, Lauren, additional, Wohler, Elizabeth, additional, Wojcik, Monica H., additional, Wong, Isaac, additional, Wood, Jordan C., additional, Wu, Nan, additional, Xing, Jinchuan, additional, Yang, Yaping, additional, Yi, Qian, additional, Yuan, Bo, additional, Zeiger, Jordan E., additional, Zhang, Chaofan, additional, Zhang, Peng, additional, Zhang, Yan, additional, Zhang, Xiaohong, additional, Zhang, Yeting, additional, Zhang, Shifa, additional, Zoghbi, Huda, additional, and van den Veyver, Igna, additional

Published
2022
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11. Loss of Nexilin function leads to a recessive lethal fetal cardiomyopathy characterized by cardiomegaly and endocardial fibroelastosis

Author

Johansson, Josefin, primary, Frykholm, Carina, additional, Ericson, Katharina, additional, Kazamia, Kalliopi, additional, Lindberg, Amanda, additional, Mulaiese, Nancy, additional, Falck, Geir, additional, Gustafsson, Per‐Erik, additional, Lidéus, Sarah, additional, Gudmundsson, Sanna, additional, Ameur, Adam, additional, Bondeson, Marie‐Louise, additional, and Wilbe, Maria, additional

Published
2022
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12. Variant interpretation using population databases: Lessons from gnomAD.

Author

Gudmundsson, Sanna, Singer‐Berk, Moriel, Watts, Nicholas A., Phu, William, Goodrich, Julia K., Solomonson, Matthew, Rehm, Heidi L., MacArthur, Daniel G., and O'Donnell‐Luria, Anne

Abstract

Reference population databases are an essential tool in variant and gene interpretation. Their use guides the identification of pathogenic variants amidst the sea of benign variation present in every human genome, and supports the discovery of new disease–gene relationships. The Genome Aggregation Database (gnomAD) is currently the largest and most widely used publicly available collection of population variation from harmonized sequencing data. The data is available through the online gnomAD browser (https://gnomad.broadinstitute.org/) that enables rapid and intuitive variant analysis. This review provides guidance on the content of the gnomAD browser, and its usage for variant and gene interpretation. We introduce key features including allele frequency, per‐base expression levels, constraint scores, and variant co‐occurrence, alongside guidance on how to use these in analysis, with a focus on the interpretation of candidate variants and novel genes in rare disease. [ABSTRACT FROM AUTHOR]

Published
2022
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13. Considerations for reporting variants in novel candidate genes identified during clinical genomic testing

Author

Chong, Jessica X., Berger, Seth I., Baxter, Samantha, Smith, Erica, Xiao, Changrui, Calame, Daniel G., Hawley, Megan H., Rivera-Munoz, E. Andres, DiTroia, Stephanie, Abouhala, Siwaar, Albert, Jessica, Almalvez, Miguel, Alvarez, Raquel, Amin, Mutaz, Anderson, Peter, Aradhya, Swaroop, Ashley, Euan, Assimes, Themistocles, Auriga, Light, Austin-Tse, Christina, Bamshad, Mike, Barseghyan, Hayk, Baxter, Samantha, Behera, Sairam, Beheshti, Shaghayegh, Bejerano, Gill, Berger, Seth, Bernstein, Jon, Best, Sabrina, Blankenmeister, Benjamin, Blue, Elizabeth, Boerwinkle, Eric, Bonkowski, Emily, Bonner, Devon, Boone, Philip, Bornhorst, Miriam, Brand, Harrison, Buckingham, Kati, Calame, Daniel, Carter, Jennefer, Casadei, Silvia, Chadwick, Lisa, Chavez, Clarisa, Chen, Ziwei, Chinn, Ivan, Chong, Jessica, Coban-Akdemir, Zeynep, Cohen, Andrea J., Conner, Sarah, Conomos, Matthew, Coveler, Karen, Cui, Ya Allen, Currin, Sara, Daber, Robert, Dardas, Zain, Davis, Colleen, Dawood, Moez, de Dios, Ivan, de Esch, Celine, Delaney, Meghan, Delot, Emmanuele, DiTroia, Stephanie, Doddapaneni, Harsha, Du, Haowei, Duan, Ruizhi, Dugan-Perez, Shannon, Duong, Nhat, Duyzend, Michael, Eichler, Evan, Emami, Sara, Fraser, Jamie, Fusaro, Vincent, Galey, Miranda, Ganesh, Vijay, Garcia, Brandon, Garimella, Kiran, Gibbs, Richard, Gifford, Casey, Ginsburg, Amy, Goddard, Page, Gogarten, Stephanie, Gogate, Nikhita, Gordon, William, Gorzynski, John E., Greenleaf, William, Grochowski, Christopher, Groopman, Emily, Sousa, Rodrigo Guarischi, Gudmundsson, Sanna, Gulati, Ashima, Hall, Stacey, Harvey, William, Hawley, Megan, Heavner, Ben, Horike-Pyne, Martha, Hu, Jianhong, Huang, Yongqing, Hwang, James, Jarvik, Gail, Jensen, Tanner, Jhangiani, Shalini, Jimenez-Morales, David, Jin, Christopher, Saad, Ahmed K., Kahn-Kirby, Amanda, Kain, Jessica, Kaur, Parneet, Keehan, Laura, Knoblach, Susan, Ko, Arthur, Kundaje, Anshul, Kundu, Soumya, Lancaster, Samuel M., Larsson, Katie, Lee, Arthur, Lemire, Gabrielle, Lewis, Richard, Li, Wei, Li, Yidan, Liu, Pengfei, LoTempio, Jonathan, Lupski, James (Jim), Ma, Jialan, MacArthur, Daniel, Mahmoud, Medhat, Malani, Nirav, Mangilog, Brian, Marafi, Dana, Marmolejos, Sofia, Marten, Daniel, Martinez, Eva, Marvin, Colby, Marwaha, Shruti, Mastrorosa, Francesco Kumara, Matalon, Dena, May, Susanne, McGee, Sean, Meador, Lauren, Mefford, Heather, Mendez, Hector Rodrigo, Miller, Alexander, Miller, Danny E., Mitani, Tadahiro, Montgomery, Stephen, Moyses, Mariana, Munderloh, Chloe, Muzny, Donna, Nelson, Sarah, Nguyen, Thuy-mi P., Nguyen, Jonathan, Nussbaum, Robert, Nykamp, Keith, O'Callaghan, William, O'Heir, Emily, O'Leary, Melanie, Olsen, Jeren, Osei-Owusu, Ikeoluwa, O'Donnell-Luria, Anne, Padhi, Evin, Pais, Lynn, Pan, Miao, Panchal, Piyush, Patterson, Karynne, Payne, Sheryl, Pehlivan, Davut, Petrowski, Paul, Pham, Alicia, Pitsava, Georgia, Podesta, Astaria Sara, Ponce, Sarah, Porter, Elizabeth, Posey, Jennifer, Prosser, Jaime, Quertermous, Thomas, Rai, Archana, Ramani, Arun, Rehm, Heidi, Reuter, Chloe, Reuter, Jason, Richardson, Matthew, Rivera-Munoz, Andres, Rubio, Oriane, Sabo, Aniko, Salani, Monica, Samocha, Kaitlin, Sanchis-Juan, Alba, Savage, Sarah, Scott, Evette, Scott, Stuart, Sedlazeck, Fritz, Shah, Gulalai, Shojaie, Ali, Singh, Mugdha, Smith, Kevin, Smith, Josh, Snow, Hana, Snyder, Michael, Socarras, Kayla, Starita, Lea, Stark, Brigitte, Stenton, Sarah, Stergachis, Andrew, Stilp, Adrienne, Sutton, V. Reid, Tai, Jui-Cheng, Talkowski, Michael (Mike), Tise, Christina, Tong, Catherine (Cat), Tsao, Philip, Ungar, Rachel, VanNoy, Grace, Vilain, Eric, Voutos, Isabella, Walker, Kim, Wei, Chia-Lin, Weisburd, Ben, Weiss, Jeff, Wellington, Chris, Weng, Ziming, Westheimer, Emily, Wheeler, Marsha, Wheeler, Matthew, Wiel, Laurens, Wilson, Michael, Wojcik, Monica, Wong, Quenna, Xiao, Changrui, Yadav, Rachita, Yi, Qian, Yuan, Bo, Zhao, Jianhua, Zhen, Jimmy, Zhou, Harry, Bamshad, Michael J., and Rehm, Heidi L.

Abstract

Since the first novel gene discovery for a Mendelian condition was made via exome sequencing (ES), the rapid increase in the number of genes known to underlie Mendelian conditions coupled with the adoption of exome (and more recently, genome) sequencing by diagnostic testing labs has changed the landscape of genomic testing for rare disease. Specifically, many individuals suspected to have a Mendelian condition are now routinely offered clinical ES. This commonly results in a precise genetic diagnosis but frequently overlooks the identification of novel candidate genes. Such candidates are also less likely to be identified in the absence of large-scale gene discovery research programs. Accordingly, clinical laboratories have both the opportunity, and some might argue a responsibility, to contribute to novel gene discovery which should in turn increase the diagnostic yield for many conditions. However, clinical diagnostic laboratories must necessarily balance priorities for throughput, turnaround time, cost efficiency, clinician preferences, and regulatory constraints, and often do not have the infrastructure or resources to effectively participate in either clinical translational or basic genome science research efforts. For these and other reasons, many laboratories have historically refrained from broadly sharing potentially pathogenic variants in novel genes via networks like Matchmaker Exchange, much less reporting such results to ordering providers. Efforts to report such results are further complicated by a lack of guidelines for clinical reporting and interpretation of variants in novel candidate genes. Nevertheless, there are myriad benefits for many stakeholders, including patients/families, clinicians, researchers, if clinical laboratories systematically and routinely identify, share, and report novel candidate genes. To facilitate this change in practice, we developed criteria for triaging, sharing, and reporting novel candidate genes that are most likely to be promptly validated as underlying a Mendelian condition and translated to use in clinical settings.

Published
2024
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14. Addendum: The mutational constraint spectrum quantified from variation in 141,456 humans.

Author

Gudmundsson, Sanna, Karczewski, Konrad J., Francioli, Laurent C., Tiao, Grace, Cummings, Beryl B., Alföldi, Jessica, Wang, Qingbo, Collins, Ryan L., Laricchia, Kristen M., Ganna, Andrea, Birnbaum, Daniel P., Gauthier, Laura D., Brand, Harrison, Solomonson, Matthew, Watts, Nicholas A., Rhodes, Daniel, Singer-Berk, Moriel, England, Eleina M., Seaby, Eleanor G., and Kosmicki, Jack A.

Published
2021
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15. Exploring penetrance of clinically relevant variants in over 800,000 humans from the Genome Aggregation Database.

Author

Gudmundsson S, Singer-Berk M, Stenton SL, Goodrich JK, Wilson MW, Einson J, Watts NA, Lappalainen T, Rehm HL, MacArthur DG, and O'Donnell-Luria A

Abstract

Incomplete penetrance, or absence of disease phenotype in an individual with a disease-associated variant, is a major challenge in variant interpretation. Studying individuals with apparent incomplete penetrance can shed light on underlying drivers of altered phenotype penetrance. Here, we investigate clinically relevant variants from ClinVar in 807,162 individuals from the Genome Aggregation Database (gnomAD), demonstrating improved representation in gnomAD version 4. We then conduct a comprehensive case-by-case assessment of 734 predicted loss of function variants (pLoF) in 77 genes associated with severe, early-onset, highly penetrant haploinsufficient disease. We identified explanations for the presumed lack of disease manifestation in 701 of the variants (95%). Individuals with unexplained lack of disease manifestation in this set of disorders rarely occur, underscoring the need and power of deep case-by-case assessment presented here to minimize false assignments of disease risk, particularly in unaffected individuals with higher rates of secondary properties that result in rescue., Competing Interests: COMPETING INTERESTS A.O-D.L. is on the scientific advisory board for Congenica, receives research funding in the form of reagents from Pacific Biosciences, and is a paid advisor to Addition Therapeutics and former advisor to Tome Biosciences and Ono Pharma USA. D.G.M. is a paid adviser to GlaxoSmithKline, Insitro, and Overtone Therapeutics, and receives research funding from Microsoft Corporation. H.L.R. receives research funding from Microsoft. T.L. is an advisor and has equity in Variant Bio.

Published
2024
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16. Gustavson syndrome is caused by an in-frame deletion in RBMX associated with potentially disturbed SH3 domain interactions.

Author

Johansson J, Lidéus S, Frykholm C, Gunnarsson C, Mihalic F, Gudmundsson S, Ekvall S, Molin AM, Pham M, Vihinen M, Lagerstedt-Robinson K, Nordgren A, Jemth P, Ameur A, Annerén G, Wilbe M, and Bondeson ML

Subjects
Female, Humans, Heterogeneous-Nuclear Ribonucleoproteins genetics, Heterogeneous-Nuclear Ribonucleoproteins chemistry, Heterogeneous-Nuclear Ribonucleoproteins metabolism, RNA Polymerase II, src Homology Domains, RNA-Binding Proteins genetics, Intellectual Disability genetics, Neuroblastoma, Deafness, Optic Atrophy, Seizures, Mental Retardation, X-Linked
Abstract

RNA binding motif protein X-linked (RBMX) encodes the heterogeneous nuclear ribonucleoprotein G (hnRNP G) that regulates splicing, sister chromatid cohesion and genome stability. RBMX knock down experiments in various model organisms highlight the gene's importance for brain development. Deletion of the RGG/RG motif in hnRNP G has previously been associated with Shashi syndrome, however involvement of other hnRNP G domains in intellectual disability remain unknown. In the current study, we present the underlying genetic and molecular cause of Gustavson syndrome. Gustavson syndrome was first reported in 1993 in a large Swedish five-generation family presented with profound X-linked intellectual disability and an early death. Extensive genomic analyses of the family revealed hemizygosity for a novel in-frame deletion in RBMX in affected individuals (NM_002139.4; c.484_486del, p.(Pro162del)). Carrier females were asymptomatic and presented with skewed X-chromosome inactivation, indicating silencing of the pathogenic allele. Affected individuals presented minor phenotypic overlap with Shashi syndrome, indicating a different disease-causing mechanism. Investigation of the variant effect in a neuronal cell line (SH-SY5Y) revealed differentially expressed genes enriched for transcription factors involved in RNA polymerase II transcription. Prediction tools and a fluorescence polarization assay imply a novel SH3-binding motif of hnRNP G, and potentially a reduced affinity to SH3 domains caused by the deletion. In conclusion, we present a novel in-frame deletion in RBMX segregating with Gustavson syndrome, leading to disturbed RNA polymerase II transcription, and potentially reduced SH3 binding. The results indicate that disruption of different protein domains affects the severity of RBMX-associated intellectual disabilities., (© 2023. The Author(s).)

Published
2024
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17. Advanced variant classification framework reduces the false positive rate of predicted loss of function (pLoF) variants in population sequencing data.

Author

Singer-Berk M, Gudmundsson S, Baxter S, Seaby EG, England E, Wood JC, Son RG, Watts NA, Karczewski KJ, Harrison SM, MacArthur DG, Rehm HL, and O'Donnell-Luria A

Abstract

Predicted loss of function (pLoF) variants are highly deleterious and play an important role in disease biology, but many of these variants may not actually result in loss-of-function. Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines's PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 autosomal recessive disease-genes from the Genome Aggregation Database (gnomAD, v2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in low per-base expression (pext) score regions, or the presence of cryptic splice rescues. Variants predicted to be potential artifacts or to evade LoF were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of LoF evading variants assessed, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines, and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

Published
2023
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