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2. The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the young

Author

Puckelwartz, Megan J., Pesce, Lorenzo L., Hernandez, Edgar J., Webster, Gregory, Dellefave-Castillo, Lisa M., Russell, Mark W., Geisler, Sarah S., Kearns, Samuel D., Karthik, Felix, Etheridge, Susan P., Monroe, Tanner O., Pottinger, Tess D., Kannankeril, Prince J., Shoemaker, M. Benjamin, Fountain, Darlene, Roden, Dan M., Faulkner, Meghan, MacLeod, Heather M., Burns, Kristin M., Yandell, Mark, Tristani-Firouzi, Martin, George, Jr., Alfred L., and McNally, Elizabeth M.

Published
2024
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4. Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations

Author

Lennon, Niall J., Kottyan, Leah C., Kachulis, Christopher, Abul-Husn, Noura S., Arias, Josh, Belbin, Gillian, Below, Jennifer E., Berndt, Sonja I., Chung, Wendy K., Cimino, James J., Clayton, Ellen Wright, Connolly, John J., Crosslin, David R., Dikilitas, Ozan, Velez Edwards, Digna R., Feng, QiPing, Fisher, Marissa, Freimuth, Robert R., Ge, Tian, Glessner, Joseph T., Gordon, Adam S., Patterson, Candace, Hakonarson, Hakon, Harden, Maegan, Harr, Margaret, Hirschhorn, Joel N., Hoggart, Clive, Hsu, Li, Irvin, Marguerite R., Jarvik, Gail P., Karlson, Elizabeth W., Khan, Atlas, Khera, Amit, Kiryluk, Krzysztof, Kullo, Iftikhar, Larkin, Katie, Limdi, Nita, Linder, Jodell E., Loos, Ruth J. F., Luo, Yuan, Malolepsza, Edyta, Manolio, Teri A., Martin, Lisa J., McCarthy, Li, McNally, Elizabeth M., Meigs, James B., Mersha, Tesfaye B., Mosley, Jonathan D., Musick, Anjene, Namjou, Bahram, Pai, Nihal, Pesce, Lorenzo L., Peters, Ulrike, Peterson, Josh F., Prows, Cynthia A., Puckelwartz, Megan J., Rehm, Heidi L., Roden, Dan M., Rosenthal, Elisabeth A., Rowley, Robb, Sawicki, Konrad Teodor, Schaid, Daniel J., Smit, Roelof A. J., Smith, Johanna L., Smoller, Jordan W., Thomas, Minta, Tiwari, Hemant, Toledo, Diana M., Vaitinadin, Nataraja Sarma, Veenstra, David, Walunas, Theresa L., Wang, Zhe, Wei, Wei-Qi, Weng, Chunhua, Wiesner, Georgia L., Yin, Xianyong, and Kenny, Eimear E.

Published
2024
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5. Susceptibility to innate immune activation in genetically mediated myocarditis

Author

Selgrade, Daniel F., Fullenkamp, Dominic E., Chychula, Ivana A., Li, Binjie, Dellefave-Castillo, Lisa, Dubash, Adi D., Ohiri, Joyce, Monroe, Tanner O., Blancard, Malorie, Tomar, Garima, Holgren, Cory, Burridge, Paul W., George, Alfred L., Jr., Demonbreun, Alexis R., Puckelwartz, Megan J., George, Sharon A., Efimov, Igor R., Green, Kathleen J., and McNally, Elizabeth M.

Subjects
Myocarditis -- Diagnosis -- Care and treatment, Disease susceptibility -- Analysis, Health care industry, Diagnosis, Care and treatment, Analysis
Abstract

Myocarditis is clinically characterized by chest pain, arrhythmias, and heart failure, and treatment is often supportive. Mutations in DSP, a gene encoding the desmosomal protein desmoplakin, have been increasingly implicated in myocarditis. To model DSP-associated myocarditis and assess the role of innate immunity, we generated engineered heart tissues (EHTs) using human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from patients with heterozygous DSP truncating variants (DSPtvs) and a gene-edited homozygous deletion cell line ([DSP.sup.-/-]). At baseline, [DSP.sup.-/-] EHTs displayed a transcriptomic signature of innate immune activation, which was mirrored by cytokine release. Importantly, [DSP.sup.- /-] EHTs were hypersensitive to Toll-like receptor (TLR) stimulation, demonstrating more contractile dysfunction compared with isogenic controls. Relative to [DSP.sup.-/-] EHTs, heterozygous DSPtv EHTs had less functional impairment. DSPtv EHTs displayed heightened sensitivity to TLR stimulation, and when subjected to strain, DSPtv EHTs developed functional deficits, indicating reduced contractile reserve compared with healthy controls. Colchicine or NF-[kappa]B inhibitors improved straininduced force deficits in DSPtv EHTs. Genomic correction of DSP p.R1951X using adenine base editing reduced inflammatory biomarker release from EHTs. Thus, EHTs replicate electrical and contractile phenotypes seen in human myocarditis, implicating cytokine release as a key part of the myogenic susceptibility to inflammation. The heightened innate immune activation and sensitivity are targets for clinical intervention., Introduction Myocarditis is a life-threatening heart condition characterized by inflammation, cellular infiltrate, chest pain, reduced heart function, and arrhythmias (1). Myocarditis affects as many as 10-20 per 100,000 people, with [...]

Published
2024
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7. Beyond gene-disease validity: capturing structured data on inheritance, allelic requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions

Author

Josephs, Katherine S., Roberts, Angharad M., Theotokis, Pantazis, Walsh, Roddy, Ostrowski, Philip J., Edwards, Matthew, Fleming, Andrew, Thaxton, Courtney, Roberts, Jason D., Care, Melanie, Zareba, Wojciech, Adler, Arnon, Sturm, Amy C., Tadros, Rafik, Novelli, Valeria, Owens, Emma, Bronicki, Lucas, Jarinova, Olga, Callewaert, Bert, Peters, Stacey, Lumbers, Tom, Jordan, Elizabeth, Asatryan, Babken, Krishnan, Neesha, Hershberger, Ray E., Chahal, C. Anwar A., Landstrom, Andrew P., James, Cynthia, McNally, Elizabeth M., Judge, Daniel P., van Tintelen, Peter, Wilde, Arthur, Gollob, Michael, Ingles, Jodie, and Ware, James S.

Published
2023
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10. A Genomic Link From Heart Failure to Atrial Fibrillation Risk: FOG2 Modulates a TBX5/GATA4-Dependent Atrial Gene Regulatory Network

Author

Broman, Michael T., Nadadur, Rangarajan D., Perez-Cervantes, Carlos, Burnicka-Turek, Ozanna, Lazarevic, Sonja, Gams, Anna, Laforest, Brigitte, Steimle, Jeffrey D., Iddir, Sabrina, Wang, Zhezhen, Smith, Linsin, Mazurek, Stefan R., Olivey, Harold E., Zhou, Pingzhu, Gadek, Margaret, Shen, Kaitlyn M., Khan, Zoheb, Theisen, Joshua W.M., Yang, Xinan H., Ikegami, Kohta, Efimov, Igor R., Pu, William T., Weber, Christopher R., McNally, Elizabeth M., Svensson, Eric C., and Moskowitz, Ivan P.

Published
2024
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12. Improving the safety of systemic viral gene therapy

Author

McNally, Elizabeth M.

Subjects
Gene therapy -- Patient outcomes, Spinal muscular atrophy -- Diagnosis -- Care and treatment -- Genetic aspects, Immunosuppression -- Patient outcomes, Health care industry, Elevidys (Medication) -- Licensing, certification and accreditation
Abstract

Systemic treatment with adeno-associated virus (AAV) gene replacement therapy has seen gains with FDA approval for onasemnogene abeparvovec (trade name Zolgensma) in 2019 to treat spinal muscular atrophy (SMA) and [...]

Published
2024
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14. A Small-Molecule Approach to Restore a Slow-Oxidative Phenotype and Defective CaMKIIβ Signaling in Limb Girdle Muscular Dystrophy.

Author

Liu, Jian, Campagna, Jesus, John, Varghese, Damoiseaux, Robert, Mokhonova, Ekaterina, Becerra, Diana, Meng, Huan, McNally, Elizabeth M, Pyle, April D, Kramerova, Irina, and Spencer, Melissa J

Subjects
CaMK signaling, calcium calmodulin kinase, calpain, calpainopathy, exercise, fiber type, high-throughput screen, limb girdle muscular dystrophy, mitochondria, muscle
Abstract

Mutations in CAPN3 cause limb girdle muscular dystrophy R1 (LGMDR1, formerly LGMD2A) and lead to progressive and debilitating muscle wasting. Calpain 3 deficiency is associated with impaired CaMKIIβ signaling and blunted transcriptional programs that encode the slow-oxidative muscle phenotype. We conducted a high-throughput screen on a target of CaMKII (Myl2) to identify compounds to override this signaling defect; 4 were tested in vivo in the Capn3 knockout (C3KO) model of LGMDR1. The leading compound, AMBMP, showed good exposure and was able to reverse the LGMDR1 phenotype in vivo, including improved oxidative properties, increased slow fiber size, and enhanced exercise performance. AMBMP also activated CaMKIIβ signaling, but it did not alter other pathways known to be associated with muscle growth. Thus, AMBMP treatment activates CaMKII and metabolically reprograms skeletal muscle toward a slow muscle phenotype. These proof-of-concept studies lend support for an approach to the development of therapeutics for LGMDR1.

Published
2020

15. Abstract 15706: Common- and Rare-Variant Genetic Architecture of Heart Failure Across the Allele Frequency Spectrum

Author

Lee, David S, Depaolo, John, Aragam, Krishna, Biddinger, Kiran, Conery, Mitchell, Dikilitas, Ozan, Khan, Atlas, Puckelwartz, Megan, Reza, Nosheen, Satterfield, Benjamin A, Arany, Zoltan, Cappola, Thomas P, Day, Sharlene, Joseph, Jacob, McNally, Elizabeth M, Owens, Anjali T, Voight, Benjamin F, Levin, Michael, and Damrauer, Scott M

Published
2023
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17. Returning integrated genomic risk and clinical recommendations: The eMERGE study

Author

Gordon, Adam, Sobowale, Agboade, Allworth, Aimee, Patel, Akshar, DiVietro, Alanna, Strong, Alanna, Sherafati, Alborz, Sherfati, Alborz, Bick, Alex, Miller, Alexandra, Chandel, Alka, Rosenthal, Alyssa, Khera, Amit, Kontorovich, Amy, Beck, Andrew, Beck, Andy, Espinoza, Angelica, Lewis, Anna, Prince, Anya, Khan, Atlas, Iverson, Ayuko, Khales, Bahram Namjou, Benoit, Barbara, Hernan, Becca, Kallman, Ben, Kerman, Ben, Shoemaker, Ben, Satterfield, Benjamin, Devine, Beth, Etheridge, Bethany, Goff, Blake, Freimuth, Bob, Grundmeier, Bob, Collier, Brenae, Mutai, Brenda, Harnett, Brett, Chang, Brian, Piening, Brian, Davis, Brittney, Korf, Bruce, Patterson, Candace, Demetriou, Carmen, Ta, Casey, Hammack, Catherine, Nelson, Catrina, Gascoigne, Caytie, Dorn, Chad, Moretz, Chad, Kachulis, Chris, Hoell, Christie, Cowles, Christine, Lange, Christoph, Weng, Chunhua, Prows, Cindy, Brokamp, Cole, Liu, Cong, Scherr, Courtney, Gonzalez, Crystal, Ramirez, Cynthia, Shimbo, Daichi, Roden, Dan, Schaid, Daniel, Kaufman, Dave, Crosslin, David, Kochan, David, Veenstra, David, Singh, Davinder, Karavite, Dean, Abrams, Debbie, Absher, Devin, Edwards, Digna Velez, Haverfield, Eden, Morales, Eduardo, Esplin, Edward, Malolepsza, Edyta, Alipour, Ehsan, Kenny, Eimear, Rosenthal, Elisabeth, Duvall, Eliza, McNally, Elizabeth, Bhoj, Elizabeth, Cohn, Elizabeth, Hibler, Elizabeth, Karlson, Elizabeth, Clayton, Ellen, Chesnut, Emily, DeFranco, Emily, Gallagher, Emily, Soper, Emily, Perez, Emma, Cash, Erin, Berner, Eta, Wang, Fei, Wehbe, Firas, Ricci, Francisco, Mentch, Frank, Shaibi, Gabriel, Jarvik, Gail, Hahn, George, Hripcsak, George, Wiesner, Georgia, Belbin, Gillian, Davogustto, Gio, Nadkarni, Girish, Qiu, Haijun, Hakonarson, Hakon, Bangash, Hana, Beasley, Hannah, Liu, Hao, Aungst, Heide, Tiwari, Hemant, Duckham, Hillary, Thomas, Hope, Kullo, Iftikhar, Holm, Ingrid, Allen, Isabelle, Ionita-Laza, Iuliana, Hellwege, Jacklyn, Petrzelka, Jacob, Odgis, Jacqueline, Narula, Jahnavi, Petrzelka, Jake, Patel, Jalpa, Cimino, James, Meigs, James, Snyder, James, Olson, Janet, Zahner, Janet, Pennington, Jeff, Pacheco, Jen, Pacheco, Jennifer Allen, Morse, Jennifer, Corsmo, Jeremy, Thayer, Jeritt, Cimino, Jim, Chen, Jingheng, Fournier, Jocelyn, Jackson, Jodell, Glessner, Joe, Pacyna, Joel, Smith, Johanna, Connolly, John, Lynch, John, Shelley, John, Mosley, Jonathan, Nestor, Jordan, Smoller, Jordan, Alsip, Jorge, Kannry, Joseph, Sutton, Joseph, Peterson, Josh, Smith, Joshua, Galasso, Julia, Smith, Julia, Wynn, Julia, Gundelach, Justin, Starren, Justin, Choi, Karmel, Mittendorf, Kate, Anderson, Katherine, Bonini, Katherine, Leppig, Kathleen, Muenzen, Kathleen, Larkin, Katie, Stuttgen, Kelsey, Wiley, Ken, Nguyen, Kenny, Dufendach, Kevin, Atkins, Kiley, Sawicki, Konrad, Norland, Kristjan, Kiryluk, Krzysztof, Beskow, Laura, Rasmussen-Torvik, Laura, Kottyan, Leah, Hsu, Li, Tian, Lifeng, Mahanta, Lisa, Martin, Lisa, Wang, Lisa, Gomez, Lizbeth, Thompson, Lorenzo, Orlando, Lori, Richter, Lucas, Rasmussen, Luke, Petukhova, Lynn, Seabolt, Lynn, O’Brien, Madison, Harden, Maegan, Fullerton, Malia, Harr, Margaret, Beasley, Mark, Guindo, Marta, Horike, Martha, Horike-Pyne, Martha, Abdalla, Marwah, Hamed, Marwan, Terry, Mary Beth, Maradik, Mary, Wyatt, Matt, Davis, Matthew, Lebo, Matthew, Smith, Maureen, Rosario, Maya del, Sabatello, Maya, Behr, Meckenzie, Roy-Puckelwartz, Meg, Habrat, Mel, Myers, Melanie, Yetisgen, Meliha, Iris, Merve, DaSilva, Michael, Preuss, Michael, McGowan, Michelle, Shi, Mingjian, Perera, Minoli, Thomas, Minta, Elkind, Mitch, Abbass, Mohammad, Saadatagah, Mohammad, Hess, Molly, Maradik, Molly, Vaitinadin, Nataraja “RJ”, Vaitinadin, Nataraja, Muthu, Naveen, Netherly, Neil, Lennon, Niall, Shang, Ning, Limdi, Nita, Forrest, Noah, Romero, Noheli, Robinson, Nora, Abul-Husn, Noura, Elsekaily, Omar, Dikilitas, Ozan, Kovatch, Patricia, Davis, Patrick, Appelbaum, Paul, Francaviglia, Paul, O’Reilly, Paul, Chandler, Paulette, Caraballo, Pedro, Tarczy-Hornoch, Peter, Shum, Pierre, Marathe, Priya, Murali, Priyanka, Feng, Qiping, Wells, Quinn, Atchley, Rachel, Narla, Radhika, Barton, Rene, Sterling, Rene, Chisholm, Rex, Green, Richard, Sharp, Richard, Peters, Riki, Kukafka, Rita, Rowley, Robb, Freimuth, Robert, Green, Robert, Winter, Robert, Mueller, Roger, Loos, Ruth, Irvin, Ryan, Suckiel, Sabrina, Hussain, Sajjad, Sharba, Samer, Aronson, Sandy, Jones, Sarah, Knerr, Sarah, Nigbur, Scott, Weiss, Scott, Mooney, Sean, Terek, Shannon, Aufox, Sharon, Nirenberg, Sharon, Murphy, Shawn, O’Byrne, Sheila, Wang (Sam) Choi, Shing, Aguilar, Sienna, Bland, S.T., Rodrigues, Stefanie, Ledbetter, Stephanie, Rutledge, Stephanie, Booth, Stuart James, Xian, Su, Trinidad, Susan Brown, Bakken, Suzanne, Schmidlen, Tara, Rakhra-Burris, Tejinder, Manolio, Teri, Mersha, Tesfaye, Walunas, Theresa, Chandereng, Thevaa, May, Thomas, Ge, Tian, Edwards, Todd, Kaszemacher, Tom, Hernandez, Valentina, Willis, Valerie, Desai, Vemi, Desai, Vimi, Lorenzi, Virginia, Gainer, Vivian, Wei, Wei-Qi, Chung, Wendy, Su, Wu-Chen, Chang, Xiao, Zhao, Yiqing, Luo, Yuan, Shen, Yufeng, Linder, Jodell E., Bland, Sarah T., Caraballo, Pedro J., Chisholm, Rex L., Clayton, Ellen Wright, Crosslin, David R., Esplin, Edward D., Forman, Sophie, Freimuth, Robert R., Gordon, Adam S., Harden, Maegan V., Holm, Ingrid A., Jarvik, Gail P., Karlson, Elizabeth W., Labrecque, Sofia, Lennon, Niall J., Limdi, Nita A., Mittendorf, Kathleen F., Murphy, Shawn N., Prows, Cynthia A., Rasmussen, Luke V., Sawicki, Konrad Teodor, Velez Edwards, Digna R., Abul-Husn, Noura S., Below, Jennifer E., Berner, Eta S., Booth, James, Chung, Wendy K., Cimino, James J., Fullerton, Stephanie M., Guiducci, Candace, Habrat, Melissa L., Hain, Heather, Hoell, Christin, Irvin, Marguerite R., Kachulis, Christopher, Kenny, Eimear E., Kullo, Iftikhar J., Manolio, Teri A., McNally, Elizabeth M., Mooney, Sean D., Namjou, Bahram, Perez, Emma F., Puckelwartz, Megan J., Roden, Dan M., Rosenthal, Elisabeth A., Saadatagah, Seyedmohammad, Schaid, Dan J., Schultz, Baergen, Shaibi, Gabriel Q., Sharp, Richard R., Shirts, Brian, Smith, Maureen E., Smoller, Jordan W., Suckiel, Sabrina A., Tiwari, Hemant K., Trinidad, Susan B., Wells, Quinn S., Wiesner, Georgia L., and Peterson, Josh F.

Published
2023
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20. Spp1 (osteopontin) promotes TGFβ processing in fibroblasts of dystrophin deficient muscles through matrix metalloproteinases

Author

Kramerova, Irina, Kumagai-Cresse, Chino, Ermolova, Natalia, Mokhonova, Ekaterina, Marinov, Masha, Capote, Joana, Becerra, Diana, Quattrocelli, Mattia, Crosbie, Rachelle H, Welch, Ellen, McNally, Elizabeth M, and Spencer, Melissa J

Subjects
Biological Sciences, Genetics, Intellectual and Developmental Disabilities (IDD), Pediatric, Rare Diseases, Brain Disorders, Muscular Dystrophy, Duchenne/ Becker Muscular Dystrophy, 2.1 Biological and endogenous factors, Aetiology, Musculoskeletal, Animals, Collagen Type I, Disease Models, Animal, Dystrophin, Extracellular Matrix, Female, Fibroblasts, Fibrosis, Male, Matrix Metalloproteinase 9, Mice, Mice, Inbred mdx, Mice, Knockout, Muscle, Skeletal, Muscular Dystrophy, Duchenne, Osteopontin, Primary Cell Culture, Regeneration, Signal Transduction, Transforming Growth Factor beta, Medical and Health Sciences, Genetics & Heredity
Abstract

Duchenne muscular dystrophy (DMD) is caused by mutations in the gene encoding dystrophin. Prior work has shown that DMD progression can vary, depending on the genetic makeup of the patient. Several modifier alleles have been identified including LTBP4 and SPP1. We previously showed that Spp1 exacerbates the DMD phenotype in the mdx mouse model by promoting fibrosis and by skewing macrophage polarization. Here, we studied the mechanisms involved in Spp1's promotion of fibrosis by using both isolated fibroblasts and genetically modified mice. We found that Spp1 upregulates collagen expression in mdx fibroblasts by enhancing TGFβ signaling. Spp1's effects on TGFβ signaling are through induction of MMP9 expression. MMP9 is a protease that can release active TGFβ ligand from its latent complex. In support for activation of this pathway in our model, we showed that treatment of mdx fibroblasts with MMP9 inhibitor led to accumulation of the TGFβ latent complex, decreased levels of active TGFβ and reduced collagen expression. Correspondingly, we found reduced active TGFβ in Spp1-/-mdxB10 and Mmp9-/-mdxB10 muscles in vivo. Taken together with previous observations of reduced fibrosis in both models, these data suggest that Spp1 acts upstream of TGFβ to promote fibrosis in mdx muscles. We found that in the context of constitutively upregulated TGFβ signaling (such as in the mdxD2 model), ablation of Spp1 has very little effect on fibrosis. Finally, we performed proof-of-concept studies showing that postnatal pharmacological inhibition of Spp1 reduces fibrosis and improves muscle function in mdx mice.

Published
2019

21. 2022 HRS expert consensus statement on evaluation and management of arrhythmic risk in neuromuscular disorders

Author

Groh, William J., Bhakta, Deepak, Tomaselli, Gordon F., Aleong, Ryan G., Teixeira, Ricardo Alkmim, Amato, Anthony, Asirvatham, Samuel J., Cha, Yong-Mei, Corrado, Domenico, Duboc, Denis, Goldberger, Zachary D., Horie, Minoru, Hornyak, Joseph E., Jefferies, John Lynn, Kääb, Stefan, Kalman, Jonathan M., Kertesz, Naomi J., Lakdawala, Neal K., Lambiase, Pier D., Lubitz, Steven A., McMillan, Hugh J., McNally, Elizabeth M., Milone, Margherita, Namboodiri, Narayanan, Nazarian, Saman, Patton, Kristen K., Russo, Vincenzo, Sacher, Frederic, Santangeli, Pasquale, Shen, Win-Kuang, Sobral Filho, Dario C., Stambler, Bruce S., Stöllberger, Claudia, Wahbi, Karim, Wehrens, Xander H.T., Weiner, Menachem Mendel, Wheeler, Matthew T., and Zeppenfeld, Katja

Published
2022
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25. Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure

Author

Levin, Michael G., Tsao, Noah L., Singhal, Pankhuri, Liu, Chang, Vy, Ha My T., Paranjpe, Ishan, Backman, Joshua D., Bellomo, Tiffany R., Bone, William P., Biddinger, Kiran J., Hui, Qin, Dikilitas, Ozan, Satterfield, Benjamin A., Yang, Yifan, Morley, Michael P., Bradford, Yuki, Burke, Megan, Reza, Nosheen, Charest, Brian, Judy, Renae L., Puckelwartz, Megan J., Hakonarson, Hakon, Khan, Atlas, Kottyan, Leah C., Kullo, Iftikhar, Luo, Yuan, McNally, Elizabeth M., Rasmussen-Torvik, Laura J., Day, Sharlene M., Do, Ron, Phillips, Lawrence S., Ellinor, Patrick T., Nadkarni, Girish N., Ritchie, Marylyn D., Arany, Zoltan, Cappola, Thomas P., Margulies, Kenneth B., Aragam, Krishna G., Haggerty, Christopher M., Joseph, Jacob, Sun, Yan V., Voight, Benjamin F., and Damrauer, Scott M.

Published
2022
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27. From Calculation to Communication: Using Risk Score Calculators to Inform Clinical Decision Making and Facilitate Patient Engagement.

Author

Fakhari, Hoda, Scherr, Courtney L., Moe, Sydney, Hoell, Christin, Smith, Maureen E., Rasmussen-Torvik, Laura J., Chisholm, Rex L., and McNally, Elizabeth M.

Abstract

Background: Risk score calculators are a widely developed tool to support clinicians in identifying and managing risk for certain diseases. However, little is known about physicians' applied experiences with risk score calculators and the role of risk score estimates in clinical decision making and patient communication. Methods: Physicians providing care in outpatient community-based clinical settings (N = 20) were recruited to participate in semi-structured individual interviews to assess their use of risk score calculators in practice. Two study team members conducted an inductive thematic analysis using a consensus-based coding approach. Results: Participants referenced at least 20 risk score calculators, the most common being the Atherosclerotic Cardiovascular Disease Risk Calculator. Ecological factors related to the clinical system (e.g., time), patient (e.g., receptivity), and physician (e.g., experience) influenced conditions and patterns of risk score calculator use. For example, compared with attending physicians, residents tended to use a greater variety of risk score calculators and with higher frequency. Risk score estimates were generally used in clinical decision making to improve or validate clinical judgment and in patient communication to serve as a motivational tool. Conclusions: The degree to which risk score estimates influenced physician decision making and whether and how these scores were communicated to patients varied, reflecting a nuanced role of risk score calculator use in clinical practice. The theory of planned behavior can help explain how attitudes, beliefs, and norms shape the use of risk score estimates in clinical decision making and patient communication. Additional research is needed to evaluate best practices in the use of risk score calculators and risk score estimates. Highlights: The risk score calculators and estimates that participants referenced in this study represented a range of conditions (e.g., heart disease, anxiety), levels of model complexity (e.g., probability calculations, scales of severity), and output formats (e.g., point estimates, risk intervals). Risk score calculators that are easily accessed, have simple inputs, and are trusted by physicians appear more likely to be used. Risk score estimates were generally used in clinical decision making to improve or validate clinical judgment and in patient communication to serve as a motivational tool. Risk score estimates helped participants manage the uncertainty and complexity of various clinical situations, yet consideration of the limitations of these estimates was relatively minimal. Developers of risk score calculators should consider the patient- (e.g., response to risk score estimates) and physician- (e.g., training status) related characteristics that influence risk score calculator use in addition to that of the clinical system. [ABSTRACT FROM AUTHOR]

Published
2024
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28. Distribution of MRI-derived T2 values as a biomarker for in vivo rapid screening of phenotype severity in mdx mice.

Author

Waters, Emily A., Haney, Chad R., Vaught, Lauren A, McNally, Elizabeth M., and Demonbreun, Alexis R.

Subjects
DUCHENNE muscular dystrophy, MAGNETIC resonance imaging, PATHOLOGY, MUSCLE diseases, IMAGE processing
Abstract

Background: The pathology in Duchenne muscular dystrophy (DMD) is characterized by degenerating muscle fibers, inflammation, fibro-fatty infiltrate, and edema, and these pathological processes replace normal healthy muscle tissue. The mdx mouse model is one of the most commonly used preclinical models to study DMD. Mounting evidence has emerged illustrating that muscle disease progression varies considerably in mdx mice, with inter-animal differences as well as intra-muscular differences in pathology in individual mdx mice. This variation is important to consider when conducting assessments of drug efficacy and in longitudinal studies. We developed a magnetic resonance imaging (MRI) segmentation and analysis pipeline to rapidly and non-invasively measure the severity of muscle disease in mdx mice. Methods: Wildtype and mdx mice were imaged with MRI and T2 maps were obtained axially across the hindlimbs. A neural network was trained to rapidly and semi-automatically segment the muscle tissue, and the distribution of resulting T2 values was analyzed. Interdecile range and Pearson Skew were identified as biomarkers to quickly and accurately estimate muscle disease severity in mice. Results: The semiautomated segmentation tool reduced image processing time approximately tenfold. Measures of Pearson skew and interdecile range based on that segmentation were repeatable and reflected muscle disease severity in healthy wildtype and diseased mdx mice based on both qualitative observation of images and correlation with Evans blue dye uptake. Conclusion: Use of this rapid, non-invasive, semi-automated MR image segmentation and analysis pipeline has the potential to transform preclinical studies, allowing for pre-screening of dystrophic mice prior to study enrollment to ensure more uniform muscle disease pathology across treatment groups, improving study outcomes. [ABSTRACT FROM AUTHOR]

Published
2024
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29. Genetic testing in early-onset atrial fibrillation.

Author

Kany, Shinwan, Jurgens, Sean J, Rämö, Joel T, Christophersen, Ingrid E, Rienstra, Michiel, Chung, Mina K, Olesen, Morten S, Ackerman, Michael J, McNally, Elizabeth M, Semsarian, Christopher, Schnabel, Renate B, Wilde, Arthur A M, Benjamin, Emelia J, Rehm, Heidi L, Kirchhof, Paulus, Bezzina, Connie R, Roden, Dan M, Shoemaker, M Benjamin, and Ellinor, Patrick T

Subjects
GENETIC testing, ATRIAL fibrillation, PATIENT education, MEDICAL screening, CARDIOMYOPATHIES
Abstract

Atrial fibrillation (AF) is a globally prevalent cardiac arrhythmia with significant genetic underpinnings, as highlighted by recent large-scale genetic studies. A prominent clinical and genetic overlap exists between AF, heritable ventricular cardiomyopathies, and arrhythmia syndromes, underlining the potential of AF as an early indicator of severe ventricular disease in younger individuals. Indeed, several recent studies have demonstrated meaningful yields of rare pathogenic variants among early-onset AF patients (∼4%–11%), most notably for cardiomyopathy genes in which rare variants are considered clinically actionable. Genetic testing thus presents a promising opportunity to identify monogenetic defects linked to AF and inherited cardiac conditions, such as cardiomyopathy, and may contribute to prognosis and management in early-onset AF patients. A first step towards recognizing this monogenic contribution was taken with the Class IIb recommendation for genetic testing in AF patients aged 45 years or younger by the 2023 American College of Cardiology/American Heart Association guidelines for AF. By identifying pathogenic genetic variants known to underlie inherited cardiomyopathies and arrhythmia syndromes, a personalized care pathway can be developed, encompassing more tailored screening, cascade testing, and potentially genotype-informed prognosis and preventive measures. However, this can only be ensured by frameworks that are developed and supported by all stakeholders. Ambiguity in test results such as variants of uncertain significance remain a major challenge and as many as ∼60% of people with early-onset AF might carry such variants. Patient education (including pretest counselling), training of genetic teams, selection of high-confidence genes, and careful reporting are strategies to mitigate this. Further challenges to implementation include financial barriers, insurability issues, workforce limitations, and the need for standardized definitions in a fast-moving field. Moreover, the prevailing genetic evidence largely rests on European descent populations, underscoring the need for diverse research cohorts and international collaboration. Embracing these challenges and the potential of genetic testing may improve AF care. However, further research—mechanistic, translational, and clinical—is urgently needed. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Removing uncertainty from variants of unknown significance

Author

McNally, Elizabeth M.

Subjects
Health care industry
Abstract

Interpretation of genetic testing results is complicated by the high degree of genetic variation present in every individual genome. Most inherited single-gene disorders are caused by rare gene variants, but [...]

Published
2023
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33. Prelamin A causes aberrant myonuclear arrangement and results in muscle fiber weakness.

Author

Levy, Yotam, Ross, Jacob A, Niglas, Marili, Snetkov, Vladimir A, Lynham, Steven, Liao, Chen-Yu, Puckelwartz, Megan J, Hsu, Yueh-Mei, McNally, Elizabeth M, Alsheimer, Manfred, Harridge, Stephen Dr, Young, Stephen G, Fong, Loren G, Español, Yaiza, Lopez-Otin, Carlos, Kennedy, Brian K, Lowe, Dawn A, and Ochala, Julien

Subjects
Cells, Cultured, Cell Membrane, Cell Nucleus, Animals, Mice, Knockout, Humans, Mice, Disease Models, Animal, Aging, Premature, Myosins, Lamin Type A, Cell Membrane Permeability, Muscle Strength, Muscle Fibers, Skeletal, Primary Cell Culture, Aging, Genetic diseases, Muscle Biology, Neuromuscular disease, Premature, Cells, Cultured, Disease Models, Animal, Knockout, Muscle Fibers, Skeletal
Abstract

Physiological and premature aging are frequently associated with an accumulation of prelamin A, a precursor of lamin A, in the nuclear envelope of various cell types. Here, we aimed to underpin the hitherto unknown mechanisms by which prelamin A alters myonuclear organization and muscle fiber function. By experimentally studying membrane-permeabilized myofibers from various transgenic mouse lines, our results indicate that, in the presence of prelamin A, the abundance of nuclei and myosin content is markedly reduced within muscle fibers. This leads to a concept by which the remaining myonuclei are very distant from each other and are pushed to function beyond their maximum cytoplasmic capacity, ultimately inducing muscle fiber weakness.

Published
2018

37. Genetic modifiers of muscular dystrophy act on sarcolemmal resealing and recovery from injury.

Author

Quattrocelli, Mattia, Capote, Joanna, Ohiri, Joyce C, Warner, James L, Vo, Andy H, Earley, Judy U, Hadhazy, Michele, Demonbreun, Alexis R, Spencer, Melissa J, and McNally, Elizabeth M

Subjects
Muscle, Skeletal, Sarcolemma, Animals, Mice, Inbred DBA, Mice, Knockout, Mice, Muscular Dystrophy, Animal, Annexin A1, Annexin A6, Receptors, Transforming Growth Factor beta, Recovery of Function, Gene Expression Regulation, Female, Male, Latent TGF-beta Binding Proteins, Osteopontin, Genes, Modifier, Genes, Modifier, Inbred DBA, Knockout, Muscle, Skeletal, Muscular Dystrophy, Animal, Receptors, Transforming Growth Factor beta, Genetics, Developmental Biology
Abstract

Genetic disruption of the dystrophin complex produces muscular dystrophy characterized by a fragile muscle plasma membrane leading to excessive muscle degeneration. Two genetic modifiers of Duchenne Muscular Dystrophy implicate the transforming growth factor β (TGFβ) pathway, osteopontin encoded by the SPP1 gene and latent TGFβ binding protein 4 (LTBP4). We now evaluated the functional effect of these modifiers in the context of muscle injury and repair to elucidate their mechanisms of action. We found that excess osteopontin exacerbated sarcolemmal injury, and correspondingly, that loss of osteopontin reduced injury extent both in isolated myofibers and in muscle in vivo. We found that ablation of osteopontin was associated with reduced expression of TGFβ and TGFβ-associated pathways. We identified that increased TGFβ resulted in reduced expression of Anxa1 and Anxa6, genes encoding key components of the muscle sarcolemma resealing process. Genetic manipulation of Ltbp4 in dystrophic muscle also directly modulated sarcolemmal resealing, and Ltbp4 alleles acted in concert with Anxa6, a distinct modifier of muscular dystrophy. These data provide a model in which a feed forward loop of TGFβ and osteopontin directly impacts the capacity of muscle to recover from injury, and identifies an intersection of genetic modifiers on muscular dystrophy.

Published
2017

41. The super-healing MRL strain promotes muscle growth in muscular dystrophy through a regenerative extracellular matrix

Author

O'Brien, Joseph G., primary, Willis, Alexander B., additional, Long, Ashlee M., additional, Kwon, Jason M., additional, Lee, GaHyun, additional, Li, Frank W., additional, Page, Patrick G.T., additional, Vo, Andy H., additional, Hadhazy, Michele, additional, Spencer, Melissa J., additional, Crosbie, Rachelle H., additional, Demonbreun, Alexis R., additional, and McNally, Elizabeth M., additional

Published
2024
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42. Identification of Clinical Drivers of Left Atrial Enlargement Through Genomics of Left Atrial Size

Author

Agrawal, Vineet, primary, Manouchehri, Ali, additional, Vaitinadin, Nataraja S., additional, Shi, Mingjian, additional, Bagheri, Minoo, additional, Gupta, Deepak K., additional, Kullo, Iftikhar J., additional, Luo, Yuan, additional, McNally, Elizabeth M., additional, Puckelwartz, Megan J., additional, Ferguson, Jane F., additional, Wells, Quinn S., additional, and Mosley, Jonathan D., additional

Published
2023
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43. Myosin-binding protein H-like regulates myosin-binding protein distribution and function in atrial cardiomyocytes

Author

Barefield, David Y., primary, Tonino, Paola, additional, Woulfe, Kathleen C., additional, Rahmanseresht, Sheema, additional, O’Leary, Thomas S., additional, Burnham, Hope V., additional, Wasserstrom, J. Andrew, additional, Kirk, Jonathan A., additional, Previs, Michael J., additional, Granzier, Henk L., additional, and McNally, Elizabeth M., additional

Published
2023
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44. Physiological stress improves stem cell modeling of dystrophic cardiomyopathy

Author

Fullenkamp, Dominic E., primary, Willis, Alexander B., additional, Curtin, Jodi L., additional, Amaral, Ansel P., additional, Dittloff, Kyle T., additional, Harris, Sloane I., additional, Chychula, Ivana A., additional, Holgren, Cory W., additional, Burridge, Paul W., additional, Russell, Brenda, additional, Demonbreun, Alexis R., additional, and McNally, Elizabeth M., additional

Published
2023
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45. Hypertrophic Cardiomyopathy Secondary to RAF1 Cysteine-Rich Domain Variants

Author

Fullenkamp, Dominic E., primary, Jorgensen, Ryan M., additional, Leach, Desiree F., additional, Sinha, Arjun, additional, Salamone, Isabella M., additional, Johnston, Jamie R., additional, Dellefave-Castillo, Lisa M., additional, Choudhury, Lubna, additional, McNally, Elizabeth M., additional, and Wilsbacher, Lisa D., additional

Published
2023
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