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1. Neisseria species as pathobionts in bronchiectasis.

Author

Li, L, primary, Mac Aogáin, M, additional, Xu, T, additional, Jaggi, T, additional, L Y Chan, L, additional, Qu, J, additional, Wei, L, additional, Liao, S, additional, Sheng Cheng, H, additional, R Keir, H, additional, J Dicker, A, additional, Sen Tan, K, additional, De Yun, W, additional, Siyue Koh, M, additional, Thun How, O, additional, Lim Yick Hou, A, additional, Arputhan Abisheganaden, J, additional, Boon Low, T, additional, Maharani Hassan, T, additional, Long, X, additional, A.B. Wark, P, additional, G. Oliver, B, additional, I Drautz-Moses, D, additional, C. Schuster, S, additional, Soon Tan, N, additional, Fang, M, additional, D Chalmers, J, additional, and H. Chotirmall, S, additional

Published
2022
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2. Neisseria species as pathobionts in bronchiectasis.

Author

Li, L, Mac Aogáin, M, Xu, T, Jaggi, TK, Chan, LLY, Qu, J, Wei, L, Liao, S, Cheng, HS, Keir, HR, Dicker, AJ, Tan, KS, De Yun, W, Koh, MS, Ong, TH, Lim, AYH, Abisheganaden, JA, Low, TB, Hassan, TM, Long, X, Wark, PAB, Oliver, B, Drautz-Moses, DI, Schuster, SC, Tan, NS, Fang, M, Chalmers, JD, Chotirmall, SH, Li, L, Mac Aogáin, M, Xu, T, Jaggi, TK, Chan, LLY, Qu, J, Wei, L, Liao, S, Cheng, HS, Keir, HR, Dicker, AJ, Tan, KS, De Yun, W, Koh, MS, Ong, TH, Lim, AYH, Abisheganaden, JA, Low, TB, Hassan, TM, Long, X, Wark, PAB, Oliver, B, Drautz-Moses, DI, Schuster, SC, Tan, NS, Fang, M, Chalmers, JD, and Chotirmall, SH

Abstract

Neisseria species are frequently identified in the bronchiectasis microbiome, but they are regarded as respiratory commensals. Using a combination of human cohorts, next-generation sequencing, systems biology, and animal models, we show that bronchiectasis bacteriomes defined by the presence of Neisseria spp. associate with poor clinical outcomes, including exacerbations. Neisseria subflava cultivated from bronchiectasis patients promotes the loss of epithelial integrity and inflammation in primary epithelial cells. In vivo animal models of Neisseria subflava infection and metabolipidome analysis highlight immunoinflammatory functional gene clusters and provide evidence for pulmonary inflammation. The murine metabolipidomic data were validated with human Neisseria-dominant bronchiectasis samples and compared with disease in which Pseudomonas-, an established bronchiectasis pathogen, is dominant. Metagenomic surveillance of Neisseria across various respiratory disorders reveals broader importance, and the assessment of the home environment in bronchiectasis implies potential environmental sources of exposure. Thus, we identify Neisseria species as pathobionts in bronchiectasis, allowing for improved risk stratification in this high-risk group.

Published
2022

3. MACVIA clinical decision algorithm in adolescents and adults with allergic rhinitis

Author

Bousquet, J. Schünemann, H.J. Hellings, P.W. Arnavielhe, S. Bachert, C. Bedbrook, A. Bergmann, K.-C. Bosnic-Anticevich, S. Brozek, J. Calderon, M. Canonica, G.W. Casale, T.B. Chavannes, N.H. Cox, L. Chrystyn, H. Cruz, A.A. Dahl, R. De Carlo, G. Demoly, P. Devillier, P. Dray, G. Fletcher, M. Fokkens, W.J. Fonseca, J. Gonzalez-Diaz, S.N. Grouse, L. Keil, T. Kuna, P. Larenas-Linnemann, D. Lodrup Carlsen, K.C. Meltzer, E.O. Mullol, J. Muraro, A. Naclerio, R.N. Palkonen, S. Papadopoulos, N.G. Passalacqua, G. Price, D. Ryan, D. Samolinski, B. Scadding, G.K. Sheikh, A. Spertini, F. Valiulis, A. Valovirta, E. Walker, S. Wickman, M. Yorgancioglu, A. Haahtela, T. Zuberbier, T. Aberer, W. Adachi, M. Agache, I. Akdis, C. Akdis, M. Annesi-Maesano, I. Ansotegui, I.J. Anto, J.M. Arshad, S.H. Baiardini, I. Baigenzhin, A.K. Barbara, C. Bateman, E.D. Beghé, B. Bel, E.H. Ben Kheder, A. Bennoor, K.S. Benson, M. Bernstein, D. Michael, B. Thomas, B. Bindslev-Jensen, C. Bjermer, L. Blain, H. Boner, A. Bonini, M. Bonini, S. Bosse, I. Bouchard, J. Boulet, L.-P. Bourret, R.A. Bousquet, P.J. Braido, F. Briggs, A.H. Brightling, C.E. Buhl, R. Burney, P. Bush, A. Caballero-Fonseca, F. Caimmi, D.P. Camargos, P. Camuzat, T. Carlsen, K.-H. Carr, W. Casale, T.B. Sarabia, A.C. Chatzi, L. Chen, Y. Chiron, R. Chkhartishvili, E. Chuchalin, A. Ciprandi, G. Cirule, I. Correia de Sousa, J. Costa, D. Crooks, G. Custovic, A. Dahlen, S.-E. Darsow, U. De Blay, F. De Manuel Keenoy, E. Dedeu, T. Deleanu, D. Denburg, J. Didier, A. Dinh-Xuan, A.-T. Dokic, D. Douagui, H.B. Dubakiene, R. Durham, S. Dykewicz, M. El-Gamal, Y. Emuzyte, R. Fink-Wagner, A. Fiocchi, A. Forastiere, F. Gamkrelidze, A. Gemicioğlu, B. Gereda, J.E. Gerth van Wijk, R. Gotua, M. Grisle, I. Guzmán, M.A. Haahtela, T. Heinrich, J. Hellquist-Dahl, B. Horak, F. Howarth, P.H. Humbert, M. Hyland, M. Ivancevich, J.-C. Jares, E.J. Johnston, S.L. Jonquet, O. Joos, G. Jung, K.-S. Just, J. Jutel, M. Kaidashev, I.P. Khaitov, M. Kalayci, O. Kalyoncu, F. Keith, P. Khaltaev, N. Kleine-Tebbe, J. Klimek, L. N'Goran, B.K. Kolek, V. Koppelman, G.H. Kowalski, M. Kull, I. Kvedariene, V. Lambrecht, B. Lau, S. Laune, D. Le Thi Tuyet, L. Li, J. Lieberman, P. Lipworth, B.J. Renaud, L. Magard, Y. Magnan, A. Mahboub, B. Majer, I. Makela, M. Manning, P.J. Masjedi, M.R. Maurer, M. Mavale-Manuel, S. Melén, E. Melo-Gomes, E. Mercier, J. Merk, H. Miculinic, N. Mihaltan, F. Milenkovic, B. Mohammad, Y. Molimard, M. Momas, I. Montilla-Santana, A. Morais-Almeida, M. Mösges, R. Nadif, R. Namazova-Baranova, L. Neffen, H. Nekam, K. Neou, A. Niggemann, B. Nyembue, D. O'Hehir, R. Ohta, K. Okamoto, Y. Okubo, K. Ouedraogo, S. Paggiaro, P.-L. Pali-Schöll, I. Palmer, S. Panzner, P. Papi, A. Park, H.-S. Pavord, I. Pawankar, R. Pfaar, O. Picard, R. Pigearias, B. Pin, I. Plavec, D. Pohl, W. Popov, T. Postma, D.S. Potter, P. Poulsen, L.K. Rabe, K.F. Raciborski, F. Pontal, F.R. Reitamo, S. Repka-Ramirez, M.-S. Robalo-Cordeiro, C. Roberts, G. Rodenas, F. Rolland, C. Rodriguez, M.R. Romano, A. Rosado-Pinto, J. Rosario, N.A. Rosenwasser, L. Rottem, M. Sanchez-Borges, M. Sastre-Dominguez, J. Schmid-Grendelmeier, P. Serrano, E. Simons, F.E.R. Sisul, J.-C. Skrindo, I. Smit, H.A. Solé, D. Sooronbaev, T. Spranger, O. Stelmach, R. Strandberg, T. Sunyer, J. Thijs, C. Todo-Bom, A.-M. Triggiani, M. Valenta, R. Valero, A.L. van Hage, M. Vandenplas, O. Vezzani, G. Vichyanond, P. Viegi, G. Wagenmann, M. Wahn, U. De Yun, W. Williams, D. Wright, J. Yawn, B.P. Yiallouros, P. Yusuf, O.M. Zar, H.J. Zernotti, M. Zhang, L. Zhong, N. Zidarn, M.

Abstract

The selection of pharmacotherapy for patients with allergic rhinitis (AR) depends on several factors, including age, prominent symptoms, symptom severity, control of AR, patient preferences, and cost. Allergen exposure and the resulting symptoms vary, and treatment adjustment is required. Clinical decision support systems (CDSSs) might be beneficial for the assessment of disease control. CDSSs should be based on the best evidence and algorithms to aid patients and health care professionals to jointly determine treatment and its step-up or step-down strategy depending on AR control. Contre les MAladies Chroniques pour un VIeillissement Actif en Languedoc-Roussillon (MACVIA-LR [fighting chronic diseases for active and healthy ageing]), one of the reference sites of the European Innovation Partnership on Active and Healthy Ageing, has initiated an allergy sentinel network (the MACVIA-ARIA Sentinel Network). A CDSS is currently being developed to optimize AR control. An algorithm developed by consensus is presented in this article. This algorithm should be confirmed by appropriate trials. © 2016 The Authors

Published
2016

4. MACVIA clinical decision algorithm in adolescents and adults with allergic rhinitis

Author

Bousquet, J., Schunemann, H. J., Hellings, P. W., Arnavielhe, S., Bachert, C., Bedbrook, A., Bergmann, K. -C., Bosnic-Anticevich, S., Brozek, J., Calderon, M., Canonica, G. W., Casale, T. B., Chavannes, N. H., Cox, L., Chrystyn, H., Cruz, A. A., Dahl, R., De Carlo, G., Demoly, P., Devillier, P., Dray, G., Fletcher, M., Fokkens, W. J., Fonseca, J., Gonzalez-Diaz, S. N., Grouse, L., Keil, T., Kuna, P., Larenas-Linnemann, D., Lodrup Carlsen, K. C., Meltzer, E. O., Mullol, J., Muraro, A., Naclerio, R. N., Palkonen, S., Papadopoulos, N. G., Passalacqua, G., Price, D., Ryan, D., Samolinski, B., Scadding, G. K., Sheikh, A., Spertini, F., Valiulis, A., Valovirta, E., Walker, S., Wickman, M., Yorgancioglu, A., Haahtela, T., Zuberbier, T., Aberer, W., Adachi, M., Agache, I., Akdis, C., Akdis, M., Annesi-Maesano, I., Ansotegui, I. J., Anto, J. M., Arshad, S. H., Baiardini, I., Baigenzhin, A. K., Barbara, C., Bateman, E. D., Beghe, B., Bel, E. H., Ben Kheder, A., Bennoor, K. S., Benson, M., Bernstein, D., Michael, B., Thomas, B., Bindslev-Jensen, C., Bjermer, L., Blain, H., Boner, A., Bonini, Matteo, Bonini, S., Bosse, I., Bouchard, J., Boulet, L. -P., Bourret, R. A., Bousquet, P. J., Braido, F., Briggs, A. H., Brightling, C. E., Buhl, R., Burney, P., Bush, A., Caballero-Fonseca, F., Caimmi, D. P., Camargos, P., Camuzat, T., Carlsen, K. -H., Carr, W., Sarabia, A. C., Chatzi, L., Chen, Y., Chiron, R., Chkhartishvili, E., Chuchalin, A., Ciprandi, G., Cirule, I., Correia de Sousa, J., Costa, D., Crooks, G., Custovic, A., Dahlen, S. -E., Darsow, U., De Blay, F., De Manuel Keenoy, E., Dedeu, T., Deleanu, D., Denburg, J., Didier, A., Dinh-Xuan, A. -T., Dokic, D., Douagui, H. B., Dubakiene, R., Durham, S., Dykewicz, M., El-Gamal, Y., Emuzyte, R., Fink-Wagner, A., Fiocchi, A., Forastiere, F., Gamkrelidze, A., Gemicioglu, B., Gereda, J. E., Gerth van Wijk, R., Gotua, M., Grisle, I., Guzman, M. A., Heinrich, J., Hellquist-Dahl, B., Horak, F., Howarth, P. H., Humbert, M., Hyland, M., Ivancevich, J. -C., Jares, E. J., Johnston, S. L., Jonquet, O., Joos, G., Jung, K. -S., Just, J., Jutel, M., Kaidashev, I. P., Khaitov, M., Kalayci, O., Kalyoncu, F., Keith, P., Khaltaev, N., Kleine-Tebbe, J., Klimek, L., N'Goran, B. K., Kolek, V., Koppelman, G. H., Kowalski, M., Kull, I., Kvedariene, V., Lambrecht, B., Lau, S., Laune, D., Le Thi Tuyet, L., Li, J., Lieberman, P., Lipworth, B. J., Renaud, L., Magard, Y., Magnan, A., Mahboub, B., Majer, I., Makela, M., Manning, P. J., Masjedi, M. R., Maurer, M., Mavale-Manuel, S., Melen, E., Melo-Gomes, E., Mercier, J., Merk, H., Miculinic, N., Mihaltan, F., Milenkovic, B., Mohammad, Y., Molimard, M., Momas, I., Montilla-Santana, A., Morais-Almeida, M., Mosges, R., Nadif, R., Namazova-Baranova, L., Neffen, H., Nekam, K., Neou, A., Niggemann, B., Nyembue, D., O'Hehir, R., Ohta, K., Okamoto, Y., Okubo, K., Ouedraogo, S., Paggiaro, P. -L., Pali-Scholl, I., Palmer, S., Panzner, P., Papi, A., Park, H. -S., Pavord, I., Pawankar, R., Pfaar, O., Picard, R., Pigearias, B., Pin, I., Plavec, D., Pohl, W., Popov, T., Postma, D. S., Potter, P., Poulsen, L. K., Rabe, K. F., Raciborski, F., Pontal, F. R., Reitamo, S., Repka-Ramirez, M. -S., Robalo-Cordeiro, C., Roberts, G., Rodenas, F., Rolland, C., Rodriguez, M. R., Romano, A., Rosado-Pinto, J., Rosario, N. A., Rosenwasser, L., Rottem, M., Sanchez-Borges, M., Sastre-Dominguez, J., Schmid-Grendelmeier, P., Serrano, E., Simons, F. E. R., Sisul, J. -C., Skrindo, I., Smit, H. A., Sole, D., Sooronbaev, T., Spranger, O., Stelmach, R., Strandberg, T., Sunyer, J., Thijs, C., Todo-Bom, A. -M., Triggiani, M., Valenta, R., Valero, A. L., van Hage, M., Vandenplas, O., Vezzani, G., Vichyanond, P., Viegi, G., Wagenmann, M., Wahn, U., De Yun, W., Williams, D., Wright, J., Yawn, B. P., Yiallouros, P., Yusuf, O. M., Zar, H. J., Zernotti, M., Zhang, L., Zhong, N., Zidarn, M., Bonini M. (ORCID:0000-0002-3042-0765), Bousquet, J., Schunemann, H. J., Hellings, P. W., Arnavielhe, S., Bachert, C., Bedbrook, A., Bergmann, K. -C., Bosnic-Anticevich, S., Brozek, J., Calderon, M., Canonica, G. W., Casale, T. B., Chavannes, N. H., Cox, L., Chrystyn, H., Cruz, A. A., Dahl, R., De Carlo, G., Demoly, P., Devillier, P., Dray, G., Fletcher, M., Fokkens, W. J., Fonseca, J., Gonzalez-Diaz, S. N., Grouse, L., Keil, T., Kuna, P., Larenas-Linnemann, D., Lodrup Carlsen, K. C., Meltzer, E. O., Mullol, J., Muraro, A., Naclerio, R. N., Palkonen, S., Papadopoulos, N. G., Passalacqua, G., Price, D., Ryan, D., Samolinski, B., Scadding, G. K., Sheikh, A., Spertini, F., Valiulis, A., Valovirta, E., Walker, S., Wickman, M., Yorgancioglu, A., Haahtela, T., Zuberbier, T., Aberer, W., Adachi, M., Agache, I., Akdis, C., Akdis, M., Annesi-Maesano, I., Ansotegui, I. J., Anto, J. M., Arshad, S. H., Baiardini, I., Baigenzhin, A. K., Barbara, C., Bateman, E. D., Beghe, B., Bel, E. H., Ben Kheder, A., Bennoor, K. S., Benson, M., Bernstein, D., Michael, B., Thomas, B., Bindslev-Jensen, C., Bjermer, L., Blain, H., Boner, A., Bonini, Matteo, Bonini, S., Bosse, I., Bouchard, J., Boulet, L. -P., Bourret, R. A., Bousquet, P. J., Braido, F., Briggs, A. H., Brightling, C. E., Buhl, R., Burney, P., Bush, A., Caballero-Fonseca, F., Caimmi, D. P., Camargos, P., Camuzat, T., Carlsen, K. -H., Carr, W., Sarabia, A. C., Chatzi, L., Chen, Y., Chiron, R., Chkhartishvili, E., Chuchalin, A., Ciprandi, G., Cirule, I., Correia de Sousa, J., Costa, D., Crooks, G., Custovic, A., Dahlen, S. -E., Darsow, U., De Blay, F., De Manuel Keenoy, E., Dedeu, T., Deleanu, D., Denburg, J., Didier, A., Dinh-Xuan, A. -T., Dokic, D., Douagui, H. B., Dubakiene, R., Durham, S., Dykewicz, M., El-Gamal, Y., Emuzyte, R., Fink-Wagner, A., Fiocchi, A., Forastiere, F., Gamkrelidze, A., Gemicioglu, B., Gereda, J. E., Gerth van Wijk, R., Gotua, M., Grisle, I., Guzman, M. A., Heinrich, J., Hellquist-Dahl, B., Horak, F., Howarth, P. H., Humbert, M., Hyland, M., Ivancevich, J. -C., Jares, E. J., Johnston, S. L., Jonquet, O., Joos, G., Jung, K. -S., Just, J., Jutel, M., Kaidashev, I. P., Khaitov, M., Kalayci, O., Kalyoncu, F., Keith, P., Khaltaev, N., Kleine-Tebbe, J., Klimek, L., N'Goran, B. K., Kolek, V., Koppelman, G. H., Kowalski, M., Kull, I., Kvedariene, V., Lambrecht, B., Lau, S., Laune, D., Le Thi Tuyet, L., Li, J., Lieberman, P., Lipworth, B. J., Renaud, L., Magard, Y., Magnan, A., Mahboub, B., Majer, I., Makela, M., Manning, P. J., Masjedi, M. R., Maurer, M., Mavale-Manuel, S., Melen, E., Melo-Gomes, E., Mercier, J., Merk, H., Miculinic, N., Mihaltan, F., Milenkovic, B., Mohammad, Y., Molimard, M., Momas, I., Montilla-Santana, A., Morais-Almeida, M., Mosges, R., Nadif, R., Namazova-Baranova, L., Neffen, H., Nekam, K., Neou, A., Niggemann, B., Nyembue, D., O'Hehir, R., Ohta, K., Okamoto, Y., Okubo, K., Ouedraogo, S., Paggiaro, P. -L., Pali-Scholl, I., Palmer, S., Panzner, P., Papi, A., Park, H. -S., Pavord, I., Pawankar, R., Pfaar, O., Picard, R., Pigearias, B., Pin, I., Plavec, D., Pohl, W., Popov, T., Postma, D. S., Potter, P., Poulsen, L. K., Rabe, K. F., Raciborski, F., Pontal, F. R., Reitamo, S., Repka-Ramirez, M. -S., Robalo-Cordeiro, C., Roberts, G., Rodenas, F., Rolland, C., Rodriguez, M. R., Romano, A., Rosado-Pinto, J., Rosario, N. A., Rosenwasser, L., Rottem, M., Sanchez-Borges, M., Sastre-Dominguez, J., Schmid-Grendelmeier, P., Serrano, E., Simons, F. E. R., Sisul, J. -C., Skrindo, I., Smit, H. A., Sole, D., Sooronbaev, T., Spranger, O., Stelmach, R., Strandberg, T., Sunyer, J., Thijs, C., Todo-Bom, A. -M., Triggiani, M., Valenta, R., Valero, A. L., van Hage, M., Vandenplas, O., Vezzani, G., Vichyanond, P., Viegi, G., Wagenmann, M., Wahn, U., De Yun, W., Williams, D., Wright, J., Yawn, B. P., Yiallouros, P., Yusuf, O. M., Zar, H. J., Zernotti, M., Zhang, L., Zhong, N., Zidarn, M., and Bonini M. (ORCID:0000-0002-3042-0765)

Abstract

The selection of pharmacotherapy for patients with allergic rhinitis (AR) depends on several factors, including age, prominent symptoms, symptom severity, control of AR, patient preferences, and cost. Allergen exposure and the resulting symptoms vary, and treatment adjustment is required. Clinical decision support systems (CDSSs) might be beneficial for the assessment of disease control. CDSSs should be based on the best evidence and algorithms to aid patients and health care professionals to jointly determine treatment and its step-up or step-down strategy depending on AR control. Contre les MAladies Chroniques pour un VIeillissement Actif en Languedoc-Roussillon (MACVIA-LR [fighting chronic diseases for active and healthy ageing]), one of the reference sites of the European Innovation Partnership on Active and Healthy Ageing, has initiated an allergy sentinel network (the MACVIA-ARIA Sentinel Network). A CDSS is currently being developed to optimize AR control. An algorithm developed by consensus is presented in this article. This algorithm should be confirmed by appropriate trials.

Published
2016

5. Neisseria species as pathobionts in bronchiectasis.

Author

Li L, Mac Aogáin M, Xu T, Jaggi TK, Chan LLY, Qu J, Wei L, Liao S, Cheng HS, Keir HR, Dicker AJ, Tan KS, De Yun W, Koh MS, Ong TH, Lim AYH, Abisheganaden JA, Low TB, Hassan TM, Long X, Wark PAB, Oliver B, Drautz-Moses DI, Schuster SC, Tan NS, Fang M, Chalmers JD, and Chotirmall SH

Subjects
Animals, Humans, Metagenome, Mice, Neisseria genetics, Bronchiectasis epidemiology, Microbiota
Abstract

Neisseria species are frequently identified in the bronchiectasis microbiome, but they are regarded as respiratory commensals. Using a combination of human cohorts, next-generation sequencing, systems biology, and animal models, we show that bronchiectasis bacteriomes defined by the presence of Neisseria spp. associate with poor clinical outcomes, including exacerbations. Neisseria subflava cultivated from bronchiectasis patients promotes the loss of epithelial integrity and inflammation in primary epithelial cells. In vivo animal models of Neisseria subflava infection and metabolipidome analysis highlight immunoinflammatory functional gene clusters and provide evidence for pulmonary inflammation. The murine metabolipidomic data were validated with human Neisseria-dominant bronchiectasis samples and compared with disease in which Pseudomonas-, an established bronchiectasis pathogen, is dominant. Metagenomic surveillance of Neisseria across various respiratory disorders reveals broader importance, and the assessment of the home environment in bronchiectasis implies potential environmental sources of exposure. Thus, we identify Neisseria species as pathobionts in bronchiectasis, allowing for improved risk stratification in this high-risk group., Competing Interests: Declaration of interests J.D.C. has received research grants from GSK, BI, AZ, Gilead Sciences, Grifols, and Insmed and has received personal fees from GSK, BI, AZ, Chiesi, Grifols, Napp, Novartis, Insmed, and Zambon, all outside the submitted work. S.H.C. is on advisory boards for CSL Behring, Pneumagen, and BI, serves on Data and Safety Monitoring Boards for Inovio Pharmaceuticals and Imam Abdulrahman Bin Faisal University, and has received personal fees from AZ, all outside of the submitted work., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Published
2022
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6. Resistin expression in human monocytes is controlled by two linked promoter SNPs mediating NFKB p50/p50 binding and C-methylation.

Author

Kumar D, Lee B, Puan KJ, Lee W, Luis BS, Yusof N, Andiappan AK, Del Rosario R, Poschmann J, Kumar P, DeLibero G, Singhal A, Prabhakar S, De Yun W, Poidinger M, and Rötzschke O

Subjects
Cells, Cultured, DNA Methylation, Epigenesis, Genetic, Humans, Promoter Regions, Genetic, Protein Binding, Protein Multimerization, Monocytes metabolism, NF-kappa B p50 Subunit metabolism, Polymorphism, Single Nucleotide, Resistin genetics
Abstract

Resistin is a key cytokine associated with metabolic and inflammatory diseases. Especially in East Asian populations, the expression levels are strongly influenced by genetic polymorphisms. Mechanisms and functional implications of this genetic control are still unknown. By employing reporter assays, EMSA, inhibition studies, bisulphite sequencing, ChIP-Seq and gene-editing we show that the p50/p50 homodimer known to act as repressor for a number of pro-inflammatory genes plays a central role in the genetic regulation of resistin in monocytes along with promoter methylation. In the common RETN haplotype p50/p50 constitutively dampens the expression by binding to the promoter. In an Asian haplotype variant however this interaction is disrupted by the A allele of rs3219175. The SNP is in very close linkage to rs34861192, a CpG SNP, located 280 bp upstream which provides an allele-specific C-methylation site. rs34861192 is located in a 100 bp region found to be methylated in the common but not in the Asian haplotype, resulting in the latter having a higher basal expression, which also associates with elevated histone acetylation (H3K27ac). Genotype associations within cohort data of 200 East Asian individuals revealed significant associations between this haplotype and the plasma levels of factors such as TGF-b, S100B, sRAGE and IL-8 as well as with myeloid DC counts. Thus, the common RETN haplotype is tightly regulated by the epigenetic mechanism linked to p50/p50-binding. This control is lost in the Asian haplotype, which may have evolved to balance the antagonistic RETN effects on pathogen protection vs. metabolic and inflammatory disease induction.

Published
2019
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7. Toll-like receptor gene polymorphisms are associated with allergic rhinitis: a case control study.

Author

Nilsson D, Andiappan AK, Halldén C, De Yun W, Säll T, Tim CF, and Cardell LO

Subjects
Adult, Case-Control Studies, China epidemiology, Female, Genotype, Humans, Male, Phenotype, Prognosis, Rhinitis, Allergic, Seasonal epidemiology, Risk Factors, Sweden epidemiology, Young Adult, Genetic Predisposition to Disease, Haplotypes genetics, Polymorphism, Single Nucleotide genetics, Rhinitis, Allergic, Seasonal genetics, Toll-Like Receptor 7 genetics, Toll-Like Receptor 8 genetics
Abstract

Background: The Toll-like receptor proteins are important in host defense and initiation of the innate and adaptive immune responses. A number of studies have identified associations between genetic variation in the Toll-like receptor genes and allergic disorders such as asthma and allergic rhinitis. The present study aim to search for genetic variation associated with allergic rhinitis in the Toll-like receptor genes., Methods: A first association analysis genotyped 73 SNPs in 182 cases and 378 controls from a Swedish population. Based on these results an additional 24 SNPs were analyzed in one Swedish population with 352 cases and 709 controls and one Chinese population with 948 cases and 580 controls., Results: The first association analysis identified 4 allergic rhinitis-associated SNPs in the TLR7-TLR8 gene region. Subsequent analysis of 24 SNPs from this region identified 7 and 5 significant SNPs from the Swedish and Chinese populations, respectively. The corresponding risk-associated haplotypes are significant after Bonferroni correction and are the most common haplotypes in both populations. The associations are primarily detected in females in the Swedish population, whereas it is seen in males in the Chinese population. Further independent support for the involvement of this region in allergic rhinitis was obtained from quantitative skin prick test data generated in both populations., Conclusions: Haplotypes in the TLR7-TLR8 gene region were associated with allergic rhinitis in one Swedish and one Chinese population. Since this region has earlier been associated with asthma and allergic rhinitis in a Danish linkage study this speaks strongly in favour of this region being truly involved in the development of this disease.

Published
2012
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8. Wireless Hearing Aid System Simulations using Advanced Design System™: A Behavioral Modeling Approach.

Author

Singh Rana R, Bin T, Liang Z, Hari Krishna G, and De Yun W

Abstract

The stringent requirements on size and power consumption constrain the conventional hearing aid devices from providing the patients an economic and user friendly solution, specifically for better noise cancellation. With the advancements in technologies such as integrated circuits design, wireless communications and digital signal processing techniques, the wireless hearing aids having multi-microphones, analog, digital and mixed signals and radio frequency signals processing circuits, DSP and programmable units seem to be promising to provide enhanced performance. The focus of this paper is about the system simulation of a typical wireless hearing aid using Agilent Advanced Design System™. The behavioral modeling features are exploited to enable the whole system simulations including electro-acoustic transducers. A few system level simulation results are included.

Published
2005
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