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2. Human germline heterozygous gain-of-function STAT6 variants cause severe allergic disease

Author

Sharma, Mehul, Leung, Daniel, Momenilandi, Mana, Jones, Lauren CW, Pacillo, Lucia, James, Alyssa E, Murrell, Jill R, Delafontaine, Selket, Maimaris, Jesmeen, Vaseghi-Shanjani, Maryam, Del Bel, Kate L, Lu, Henry Y, Chua, Gilbert T, Di Cesare, Silvia, Fornes, Oriol, Liu, Zhongyi, Di Matteo, Gigliola, Fu, Maggie P, Amodio, Donato, San Tam, Issan Yee, Chan, Gavin Shueng Wai, Sharma, Ashish A, Dalmann, Joshua, van der Lee, Robin, Blanchard-Rohner, Géraldine, Lin, Susan, Philippot, Quentin, Richmond, Phillip A, Lee, Jessica J, Matthews, Allison, Seear, Michael, Turvey, Alexandra K, Philips, Rachael L, Brown-Whitehorn, Terri F, Gray, Christopher J, Izumi, Kosuke, Treat, James R, Wood, Kathleen H, Lack, Justin, Khleborodova, Asya, Niemela, Julie E, Yang, Xingtian, Liang, Rui, Kui, Lin, Wong, Christina Sze Man, Poon, Grace Wing Kit, Hoischen, Alexander, van der Made, Caspar I, Yang, Jing, Chan, Koon Wing, Da Rosa Duque, Jaime Sou, Lee, Pamela Pui Wah, Ho, Marco Hok Kung, Chung, Brian Hon Yin, Le, Huong Thi Minh, Yang, Wanling, Rohani, Pejman, Fouladvand, Ali, Rokni-Zadeh, Hassan, Changi-Ashtiani, Majid, Miryounesi, Mohammad, Puel, Anne, Shahrooei, Mohammad, Finocchi, Andrea, Rossi, Paolo, Rivalta, Beatrice, Cifaldi, Cristina, Novelli, Antonio, Passarelli, Chiara, Arasi, Stefania, Bullens, Dominique, Sauer, Kate, Claeys, Tania, Biggs, Catherine M, Morris, Emma C, Rosenzweig, Sergio D, O’Shea, John J, Wasserman, Wyeth W, Bedford, H Melanie, van Karnebeek, Clara DM, Palma, Paolo, Burns, Siobhan O, Meyts, Isabelle, Casanova, Jean-Laurent, Lyons, Jonathan J, Parvaneh, Nima, Van Nguyen, Anh Thi, Cancrini, Caterina, Heimall, Jennifer, Ahmed, Hanan, McKinnon, Margaret L, Lau, Yu Lung, Béziat, Vivien, and Turvey, Stuart E

Subjects
Genetics, Rare Diseases, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Humans, STAT6 Transcription Factor, Gain of Function Mutation, Asthma, Food Hypersensitivity, Immunoglobulin E, Medical and Health Sciences, Immunology
Abstract

STAT6 (signal transducer and activator of transcription 6) is a transcription factor that plays a central role in the pathophysiology of allergic inflammation. We have identified 16 patients from 10 families spanning three continents with a profound phenotype of early-life onset allergic immune dysregulation, widespread treatment-resistant atopic dermatitis, hypereosinophilia with esosinophilic gastrointestinal disease, asthma, elevated serum IgE, IgE-mediated food allergies, and anaphylaxis. The cases were either sporadic (seven kindreds) or followed an autosomal dominant inheritance pattern (three kindreds). All patients carried monoallelic rare variants in STAT6 and functional studies established their gain-of-function (GOF) phenotype with sustained STAT6 phosphorylation, increased STAT6 target gene expression, and TH2 skewing. Precision treatment with the anti-IL-4Rα antibody, dupilumab, was highly effective improving both clinical manifestations and immunological biomarkers. This study identifies heterozygous GOF variants in STAT6 as a novel autosomal dominant allergic disorder. We anticipate that our discovery of multiple kindreds with germline STAT6 GOF variants will facilitate the recognition of more affected individuals and the full definition of this new primary atopic disorder.

Published
2023

6. Optimal non-pharmaceutical intervention policy for Covid-19 epidemic via neuroevolution algorithm

Author

Saeidpour, Arash and Rohani, Pejman

Subjects
Quantitative Biology - Populations and Evolution, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, 49N10, G.1.6
Abstract

National responses to the Covid-19 pandemic varied markedly across countries, from business-as-usual to complete shutdowns. Policies aimed at disrupting the viral transmission cycle and preventing the healthcare system from being overwhelmed, simultaneously exact an economic toll. We developed a intervention policy model that comprised the relative human, economic and healthcare costs of non-pharmaceutical epidemic intervention and arrived at the optimal strategy using the neuroevolution algorithm. The proposed model finds the minimum required reduction in contact rates to maintain the burden on the healthcare system below the maximum capacity. We find that such a policy renders a sharp increase in the control strength at the early stages of the epidemic, followed by a steady increase in the subsequent ten weeks as the epidemic approaches its peak, and finally control strength is gradually decreased as the population moves towards herd immunity. We have also shown how such a model can provide an efficient adaptive intervention policy at different stages of the epidemic without having access to the entire history of its progression in the population. This work emphasizes the importance of imposing intervention measures early and provides insights into adaptive intervention policies to minimize the economic impacts of the epidemic without putting an extra burden on the healthcare system., Comment: 18 pages, 10 figures

Published
2021

7. Nonlinear dynamic analysis of an epidemiological model for COVID-19 including public behavior and government action

Author

Kwuimy, C. A. K., Nazari, Foad, Jiao, Xun, Rohani, Pejman, and Nataraj, C.

Subjects
Quantitative Biology - Populations and Evolution, Physics - Physics and Society
Abstract

This paper is concerned with nonlinear modeling and analysis of the COVID-19 pandemic currently ravaging the planet. There are two objectives: to arrive at an appropriate model that captures the collected data faithfully, and to use that as a basis to explore the nonlinear behavior. We use a nonlinear SEIR (Susceptible, Exposed, Infectious & Removed) transmission model with added behavioral and government policy dynamics. We develop a genetic algorithm technique to identify key model parameters employing COVID19 data from South Korea. Stability, bifurcations and dynamic behavior are analyzed. Parametric analysis reveals conditions for sustained epidemic equilibria to occur. This work points to the value of nonlinear dynamic analysis in pandemic modeling and demonstrates the dramatic influence of social and government behavior on disease dynamics.

Published
2020
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20. Avoidable errors in the modeling of outbreaks of emerging pathogens, with special reference to Ebola

Author

King, Aaron A., de Cellès, Matthieu Domenech, Magpantay, Felicia M. G., and Rohani, Pejman

Subjects
Quantitative Biology - Populations and Evolution, Statistics - Applications
Abstract

As an emergent infectious disease outbreak unfolds, public health response is reliant on information on key epidemiological quantities, such as transmission potential and serial interval. Increasingly, transmission models fit to incidence data are used to estimate these parameters and guide policy. Some widely-used modeling practices lead to potentially large errors in parameter estimates and, consequently, errors in model-based forecasts. Even more worryingly, in such situations, confidence in parameter estimates and forecasts can itself be far over-estimated, leading to the potential for large errors that mask their own presence. Fortunately, straightforward and computationally inexpensive alternatives exist that avoid these problems. Here, we first use a simulation study to demonstrate potential pitfalls of the standard practice of fitting deterministic models to cumulative incidence data. Next, we demonstrate an alternative based on stochastic models fit to raw data from an early phase of 2014 West Africa Ebola Virus Disease outbreak. We show not only that bias is thereby reduced, but that uncertainty in estimates and forecasts is better quantified and that, critically, lack of model fit is more readily diagnosed. We conclude with a short list of principles to guide the modeling response to future infectious disease outbreaks., Comment: 40 pages, 11 figures, 2 tables. Published by Proceedings of the Royal Society of London, Series. Published online 1 April 2015

Published
2014
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21. The epidemic volatility index, a novel early warning tool for identifying new waves in an epidemic

Author

Kostoulas, Polychronis, Meletis, Eletherios, Pateras, Konstantinos, Eusebi, Paolo, Kostoulas, Theodoros, Furuya-Kanamori, Luis, Speybroeck, Niko, Denwood, Matthew, Doi, Suhail A. R., Althaus, Christian L., Kirkeby, Carsten, Rohani, Pejman, Dhand, Navneet K., Peñalvo, José L., Thabane, Lehana, BenMiled, Slimane, Sharifi, Hamid, and Walter, Stephen D.

Published
2021
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25. The interaction of regional and local in the dynamics of the coffee rust disease

Author

Vandermeer, John and Rohani, Pejman

Subjects
Quantitative Biology - Populations and Evolution
Abstract

A simple mean field model is proposed that captures the two scales of dynamic processes involved in the spread of the coffee rust disease. At a local level the state variable is the fraction of coffee plants on an average farm that are infested with the disease and at the regional level the state variable is the fraction of farms that are infested with the disease. These two levels are interactive with one another in obvious ways, producing qualitatively interesting results. Specifically there are three distinct outcomes: disease disappears, disease is potentially persistent, and disease is inevitably persistent. The basic structure of the model generates the potential for tipping point behavior due to the presence of a blue sky bifurcation, suggesting that the emergence of epizootics of the disease may be unpredictable.

Published
2014

44. The association between vitamin D status and inflammatory bowel disease among children and adolescents: A systematic review and meta-analysis

Author

Fatahi, Somaye, primary, Alyahyawi, Naseem, additional, Albadawi, Naryman, additional, Mardali, Farzaneh, additional, Dara, Naghi, additional, Sohouli, Mohammad Hassan, additional, Prabahar, Kousalya, additional, Rohani, Pejman, additional, Koushki, Nazanin, additional, Sayyari, Aliakbar, additional, Hosseini, Amir Hossein, additional, and Abu-Zaid, Ahmed, additional

Published
2023
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