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2. Mutations that prevent caspase cleavage of RIPK1 cause autoinflammatory disease

Author

Lalaoui, Najoua, Boyden, Steven E, Oda, Hirotsugu, Wood, Geryl M, Stone, Deborah L, Chau, Diep, Liu, Lin, Stoffels, Monique, Kratina, Tobias, Lawlor, Kate E, Zaal, Kristien JM, Hoffmann, Patrycja M, Etemadi, Nima, Shield-Artin, Kristy, Biben, Christine, Tsai, Wanxia Li, Blake, Mary D, Kuehn, Hye Sun, Yang, Dan, Anderton, Holly, Silke, Natasha, Wachsmuth, Laurens, Zheng, Lixin, Moura, Natalia Sampaio, Beck, David B, Gutierrez-Cruz, Gustavo, Ombrello, Amanda K, Pinto-Patarroyo, Gineth P, Kueh, Andrew J, Herold, Marco J, Hall, Cathrine, Wang, Hongying, Chae, Jae Jin, Dmitrieva, Natalia I, McKenzie, Mark, Light, Amanda, Barham, Beverly K, Jones, Anne, Romeo, Tina M, Zhou, Qing, Aksentijevich, Ivona, Mullikin, James C, Gross, Andrew J, Shum, Anthony K, Hawkins, Edwin D, Masters, Seth L, Lenardo, Michael J, Boehm, Manfred, Rosenzweig, Sergio D, Pasparakis, Manolis, Voss, Anne K, Gadina, Massimo, Kastner, Daniel L, and Silke, John

Subjects
Biochemistry and Cell Biology, Biomedical and Clinical Sciences, Biological Sciences, Biodefense, Prevention, Rare Diseases, Vaccine Related, 1.1 Normal biological development and functioning, Underpinning research, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Animals, Caspase 3, Caspase 8, Female, Hereditary Autoinflammatory Diseases, Humans, MAP Kinase Kinase Kinases, Male, Mice, Mice, Inbred C57BL, Mice, Knockout, Mutation, Pedigree, Receptor-Interacting Protein Serine-Threonine Kinases, General Science & Technology
Abstract

RIPK1 is a key regulator of innate immune signalling pathways. To ensure an optimal inflammatory response, RIPK1 is regulated post-translationally by well-characterized ubiquitylation and phosphorylation events, as well as by caspase-8-mediated cleavage1-7. The physiological relevance of this cleavage event remains unclear, although it is thought to inhibit activation of RIPK3 and necroptosis8. Here we show that the heterozygous missense mutations D324N, D324H and D324Y prevent caspase cleavage of RIPK1 in humans and result in an early-onset periodic fever syndrome and severe intermittent lymphadenopathy-a condition we term 'cleavage-resistant RIPK1-induced autoinflammatory syndrome'. To define the mechanism for this disease, we generated a cleavage-resistant Ripk1D325A mutant mouse strain. Whereas Ripk1-/- mice died postnatally from systemic inflammation, Ripk1D325A/D325A mice died during embryogenesis. Embryonic lethality was completely prevented by the combined loss of Casp8 and Ripk3, but not by loss of Ripk3 or Mlkl alone. Loss of RIPK1 kinase activity also prevented Ripk1D325A/D325A embryonic lethality, although the mice died before weaning from multi-organ inflammation in a RIPK3-dependent manner. Consistently, Ripk1D325A/D325A and Ripk1D325A/+ cells were hypersensitive to RIPK3-dependent TNF-induced apoptosis and necroptosis. Heterozygous Ripk1D325A/+ mice were viable and grossly normal, but were hyper-responsive to inflammatory stimuli in vivo. Our results demonstrate the importance of caspase-mediated RIPK1 cleavage during embryonic development and show that caspase cleavage of RIPK1 not only inhibits necroptosis but also maintains inflammatory homeostasis throughout life.

Published
2020

5. A unified metric of human immune health

Author

Sparks, Rachel, Rachmaninoff, Nicholas, Lau, William W., Hirsch, Dylan C., Bansal, Neha, Martins, Andrew J., Chen, Jinguo, Liu, Candace C., Cheung, Foo, Failla, Laura E., Biancotto, Angelique, Fantoni, Giovanna, Sellers, Brian A., Chawla, Daniel G., Howe, Katherine N., Mostaghimi, Darius, Farmer, Rohit, Kotliarov, Yuri, Calvo, Katherine R., Palmer, Cindy, Daub, Janine, Foruraghi, Ladan, Kreuzburg, Samantha, Treat, Jennifer D., Urban, Amanda K., Jones, Anne, Romeo, Tina, Deuitch, Natalie T., Moura, Natalia Sampaio, Weinstein, Barbara, Moir, Susan, Ferrucci, Luigi, Barron, Karyl S., Aksentijevich, Ivona, Kleinstein, Steven H., Townsley, Danielle M., Young, Neal S., Frischmeyer-Guerrerio, Pamela A., Uzel, Gulbu, Pinto-Patarroyo, Gineth Paola, Cudrici, Cornelia D., Hoffmann, Patrycja, Stone, Deborah L., Ombrello, Amanda K., Freeman, Alexandra F., Zerbe, Christa S., Kastner, Daniel L., Holland, Steven M., and Tsang, John S.

Abstract

Immunological health has been challenging to characterize but could be defined as the absence of immune pathology. While shared features of some immune diseases and the concept of immunologic resilience based on age-independent adaptation to antigenic stimulation have been developed, general metrics of immune health and its utility for assessing clinically healthy individuals remain ill defined. Here we integrated transcriptomics, serum protein, peripheral immune cell frequency and clinical data from 228 patients with 22 monogenic conditions impacting key immunological pathways together with 42 age- and sex-matched healthy controls. Despite the high penetrance of monogenic lesions, differences between individuals in diverse immune parameters tended to dominate over those attributable to disease conditions or medication use. Unsupervised or supervised machine learning independently identified a score that distinguished healthy participants from patients with monogenic diseases, thus suggesting a quantitative immune health metric (IHM). In ten independent datasets, the IHM discriminated healthy from polygenic autoimmune and inflammatory disease states, marked aging in clinically healthy individuals, tracked disease activities and treatment responses in both immunological and nonimmunological diseases, and predicted age-dependent antibody responses to immunizations with different vaccines. This discriminatory power goes beyond that of the classical inflammatory biomarkers C-reactive protein and interleukin-6. Thus, deviations from health in diverse conditions, including aging, have shared systemic immune consequences, and we provide a web platform for calculating the IHM for other datasets, which could empower precision medicine.

Published
2024
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6. TNF inhibition in vasculitis management in adenosine deaminase 2 deficiency (DADA2)

Author

Deuitch, Natalie T., primary, Yang, Dan, additional, Lee, Pui Y., additional, Yu, Xiaomin, additional, Moura, Natalia Sampaio, additional, Schnappauf, Oskar, additional, Ombrello, Amanda K., additional, Stone, Deborah, additional, Kuehn, Hye Sun, additional, Rosenzweig, Sergio D., additional, Hoffmann, Patrycja, additional, Cudrici, Cornelia, additional, Levy, Deborah M., additional, Kessler, Elizabeth, additional, Soep, Jennifer B., additional, Hay, Arielle D., additional, Dalrymple, Austin, additional, Zhang, Yu, additional, Sun, Li, additional, Zhang, Qiuye, additional, Tang, Xuemei, additional, Wu, Yuan, additional, Rao, Koneti, additional, Li, Haibo, additional, Luo, Hong, additional, Zhang, Yao, additional, Burnham, Jon M., additional, Boehm, Manfred, additional, Barron, Karyl, additional, Kastner, Daniel L., additional, Aksentijevich, Ivona, additional, and Zhou, Qing, additional

Published
2022
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10. The Spectrum of the Deficiency of Adenosine Deaminase 2: An Observational Analysis of a 60 Patient Cohort

Author

Barron, Karyl S., primary, Aksentijevich, Ivona, additional, Deuitch, Natalie T., additional, Stone, Deborah L., additional, Hoffmann, Patrycja, additional, Videgar-Laird, Ryan, additional, Soldatos, Ariane, additional, Bergerson, Jenna, additional, Toro, Camilo, additional, Cudrici, Cornelia, additional, Nehrebecky, Michele, additional, Romeo, Tina, additional, Jones, Anne, additional, Boehm, Manfred, additional, Kanakry, Jennifer A., additional, Dimitrova, Dimana, additional, Calvo, Katherine R., additional, Alao, Hawwa, additional, Kapuria, Devika, additional, Ben-Yakov, Gil, additional, Pichard, Dominique C., additional, Hathaway, Londa, additional, Brofferio, Alessandra, additional, McRae, Elisa, additional, Moura, Natalia Sampaio, additional, Schnappauf, Oskar, additional, Rosenzweig, Sofia, additional, Heller, Theo, additional, Cowen, Edward W., additional, Kastner, Daniel L., additional, and Ombrello, Amanda K., additional

Published
2022
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11. Next generation sequencing panel screening of 320 patients with clinically unclassified systemic autoinflammatory diseases

Author

Schnappauf, Oskar, primary, Wang, Hongying, additional, Deuitch, Natalie, additional, Moura, Natalia Sampaio, additional, Rosenzweig, Sofia, additional, Cardona, Daniela Ospina, additional, Hoffmann, Patrycja, additional, Stone, Deborah, additional, Ombrello, Amanda, additional, Kastner, Daniel, additional, and Aksentijevich, Ivona, additional

Published
2021
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15. Deficiency of Adenosine Deaminase 2 (DADA2): Hidden Variants, Reduced Penetrance, and Unusual Inheritance

Author

Schnappauf, Oskar, primary, Zhou, Qing, additional, Moura, Natalia Sampaio, additional, Ombrello, Amanda K., additional, Michael, Drew G., additional, Deuitch, Natalie, additional, Barron, Karyl, additional, Stone, Deborah L., additional, Hoffmann, Patrycja, additional, Hershfield, Michael, additional, Applegate, Carolyn, additional, Bjornsson, Hans T., additional, Beck, David B., additional, Witmer, P. Dane, additional, Sobreira, Nara, additional, Wohler, Elizabeth, additional, Chiorini, John A., additional, Center, The American Genome, additional, Dalgard, Clifton L., additional, Center, NIH Intramural Sequencing, additional, Kastner, Daniel L., additional, and Aksentijevich, Ivona, additional

Published
2020
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16. Mutations that prevent caspase cleavage of RIPK1 cause autoinflammatory disease

Author

Lalaoui, Najoua, primary, Boyden, Steven E., additional, Oda, Hirotsugu, additional, Wood, Geryl M., additional, Stone, Deborah L., additional, Chau, Diep, additional, Liu, Lin, additional, Stoffels, Monique, additional, Kratina, Tobias, additional, Lawlor, Kate E., additional, Zaal, Kristien J. M., additional, Hoffmann, Patrycja M., additional, Etemadi, Nima, additional, Shield-Artin, Kristy, additional, Biben, Christine, additional, Tsai, Wanxia Li, additional, Blake, Mary D., additional, Kuehn, Hye Sun, additional, Yang, Dan, additional, Anderton, Holly, additional, Silke, Natasha, additional, Wachsmuth, Laurens, additional, Zheng, Lixin, additional, Moura, Natalia Sampaio, additional, Beck, David B., additional, Gutierrez-Cruz, Gustavo, additional, Ombrello, Amanda K., additional, Pinto-Patarroyo, Gineth P., additional, Kueh, Andrew J., additional, Herold, Marco J., additional, Hall, Cathrine, additional, Wang, Hongying, additional, Chae, Jae Jin, additional, Dmitrieva, Natalia I., additional, McKenzie, Mark, additional, Light, Amanda, additional, Barham, Beverly K., additional, Jones, Anne, additional, Romeo, Tina M., additional, Zhou, Qing, additional, Aksentijevich, Ivona, additional, Mullikin, James C., additional, Gross, Andrew J., additional, Shum, Anthony K., additional, Hawkins, Edwin D., additional, Masters, Seth L., additional, Lenardo, Michael J., additional, Boehm, Manfred, additional, Rosenzweig, Sergio D., additional, Pasparakis, Manolis, additional, Voss, Anne K., additional, Gadina, Massimo, additional, Kastner, Daniel L., additional, and Silke, John, additional

Published
2019
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19. Multiomics integration of 22 immune-mediated monogenic diseases reveals an emergent axis of human immune health.

Author

Sparks R, Rachmaninoff N, Hirsch DC, Bansal N, Lau WW, Martins AJ, Chen J, Liu CC, Cheung F, Failla LE, Biancotto A, Fantoni G, Sellers BA, Chawla DG, Howe KN, Mostaghimi D, Farmer R, Kotliarov Y, Calvo KR, Palmer C, Daub J, Foruraghi L, Kreuzburg S, Treat J, Urban AK, Jones A, Romeo T, Deuitch NT, Moura NS, Weinstein B, Moir S, Ferrucci L, Barron KS, Aksentijevich I, Kleinstein SH, Townsley DM, Young NS, Frischmeyer-Guerrerio PA, Uzel G, Pinto-Patarroyo GP, Cudrici CD, Hoffmann P, Stone DL, Ombrello AK, Freeman AF, Zerbe CS, Kastner DL, Holland SM, and Tsang JS

Abstract

Monogenic diseases are often studied in isolation due to their rarity. Here we utilize multiomics to assess 22 monogenic immune-mediated conditions with age- and sex-matched healthy controls. Despite clearly detectable disease-specific and "pan-disease" signatures, individuals possess stable personal immune states over time. Temporally stable differences among subjects tend to dominate over differences attributable to disease conditions or medication use. Unsupervised principal variation analysis of personal immune states and machine learning classification distinguishing between healthy controls and patients converge to a metric of immune health (IHM). The IHM discriminates healthy from multiple polygenic autoimmune and inflammatory disease states in independent cohorts, marks healthy aging, and is a pre-vaccination predictor of antibody responses to influenza vaccination in the elderly. We identified easy-to-measure circulating protein biomarker surrogates of the IHM that capture immune health variations beyond age. Our work provides a conceptual framework and biomarkers for defining and measuring human immune health., Competing Interests: Declaration of Interests The authors declare no competing interests.

Published
2023
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