Browsing by Author "Fellay, J."

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Open Access
Autoantibodies neutralizing type I IFNs are present in ~4% of uninfected individuals over 70 years old and account for ~20% of COVID-19 deaths
(American Association for the Advancement of Science (AAAS), 2021-08-20) Bastard, P.; Gervais, A.; Le Voyer, T.; Rosain, J.; Philippot, Q.; Manry, J.; Michailidis, E.; Hoffmann, H. H.; Eto, S.; Garcia-Prat, M.; Bizien, L.; Parra-Martinez, A.; Yang, R.; Haljasmagi, L.; Migaud, M.; Sarekannu, K.; Maslovskaja, J.; de Prost, N.; Tandjaoui-Lambiotte, Y.; Luyt, C. E.; Amador-Borrero, B.; Gaudet, A.; Poissy, J.; Morel, P.; Richard, P.; Cognasse, F.; Troya, J.; Trouillet-Assant, S.; Belot, A.; Saker, K.; Garcon, P.; Riviere, J. G.; Lagier, J. C.; Gentile, S.; Rosen, L. B.; Shaw, E.; Morio, T.; Tanaka, J.; Dalmau, D.; Tharaux, PL.; Sene, D.; Stepanian, A.; Megarbane, B.; Triantafyllia, V.; Fekkar, A.; Heath, J. R.; Franco, JL.; Anaya, J. M.; Sole-Violan, J.; Imberti, L.; Biondi, A.; Bonfanti, P.; Castagnoli, R.; Delmonte, O. M.; Zhang, Y.; Snow, A. L.; Holland, S. M.; Biggs, C. M.; Moncada-Velez, M.; Arias, A. A.; Lorenzo, L.; Boucherit, S.; Coulibaly, B.; Anglicheau, D.; Planas, A. M.; Haerynck, F.; Duvlis, S.; Nussbaum, R. L.; Özçelik, Tayfun; Keles, S.; Bousfiha, A. A.; El Bakkouri, J.; Ramirez-Santana, C.; Paul, S.; Pan-Hammarstrom, Q.; Hammarstrom, L.; Dupont, A.; Kurolap, A.; Metz, CN.; Aiuti, A.; Casari, G.; Lampasona, V.; Ciceri, F.; Barreiros, L. A.; Dominguez-Garrido, E.; Vidigal, M.; Zatz, M.; van de Beek, D.; Sahanic, S.; Tancevski, I.; Stepanovskyy, Y.; Boyarchuk, O.; Nukui, Y.; Tsumura, M.; Vidaur, L.; Tangye, S. G.; Burrel, S.; Duffy, D.; Quintana-Murci, L.; Klocperk, A.; Kann, N. Y.; Shcherbina, A.; Lau, Y. L.; Leung, D.; Coulongeat, M.; Marlet, J.; Koning, R.; Reyes, L. F.; Chauvineau-Grenier, A.; Venet, F.; Monneret, G.; Nussenzweig, MC.; Arrestier, R.; Boudhabhay, I.; Baris-Feldman, H.; Hagin, D.; Wauters, J.; Meyts, I.; Dyer, A. H.; Kennelly, SP.; Bourke, N. M.; Halwani, R.; Sharif-Askari, N. S.; Dorgham, K.; Sallette, J.; Sedkaoui, S. M.; AlKhater, S.; Rigo-Bonnin, R.; Morandeira, F.; Roussel, L.; Vinh, DC.; Ostrowski, SR.; Condino-Neto, A.; Prando, C.; Bondarenko, A.; Spaan, A. N.; Gilardin, L.; Fellay, J.; Lyonnet, S.; Bilguvar, K.; Lifton, R. P.; Mane, S.; Anderson, M. S.; Boisson, B.; Beziat, V.; Zhang, SY.; Andreakos, E.; Hermine, O.; Pujol, A.; Peterson, P.; Mogensen, T. H.; Rowen, L.; Mond, J.; Debette, S.; de Lamballerie, X.; Duval, X.; Mentre, F.; Zins, M.; Soler-Palacin, P.; Colobran, R.; Gorochov, G.; Solanich, X.; Susen, S.; Martinez-Picado, J.; Raoult, D.; Vasse, M.; Gregersen, P. K.; Piemonti, L.; Rodriguez-Gallego, C.; Notarangelo, LD.; Su, H. C.; Kisand, K.; Okada, S.; Puel, A.; Jouanguy, E.; Rice, C. M.; Tiberghien, P.; Zhang, Q.; Cobat, A.; Abel, L.; Casanova, J. L.
Circulating autoantibodies (auto-Abs) neutralizing high concentrations (10 ng/ml; in plasma diluted 1:10) of IFN-α and/or IFN-ω are found in about 10% of patients with critical COVID-19 (coronavirus disease 2019) pneumonia but not in individuals with asymptomatic infections. We detect auto-Abs neutralizing 100-fold lower, more physiological, concentrations of IFN-α and/or IFN-ω (100 pg/ml; in 1:10 dilutions of plasma) in 13.6% of 3595 patients with critical COVID-19, including 21% of 374 patients >80 years, and 6.5% of 522 patients with severe COVID-19. These antibodies are also detected in 18% of the 1124 deceased patients (aged 20 days to 99 years; mean: 70 years). Moreover, another 1.3% of patients with critical COVID-19 and 0.9% of the deceased patients have auto-Abs neutralizing high concentrations of IFN-β. We also show, in a sample of 34,159 uninfected individuals from the general population, that auto-Abs neutralizing high concentrations of IFN-α and/or IFN-ω are present in 0.18% of individuals between 18 and 69 years, 1.1% between 70 and 79 years, and 3.4% >80 years. Moreover, the proportion of individuals carrying auto-Abs neutralizing lower concentrations is greater in a subsample of 10,778 uninfected individuals: 1% of individuals <70 years, 2.3% between 70 and 80 years, and 6.3% >80 years. By contrast, auto-Abs neutralizing IFN-β do not become more frequent with age. Auto-Abs neutralizing type I IFNs predate SARS-CoV-2 infection and sharply increase in prevalence after the age of 70 years. They account for about 20% of both critical COVID-19 cases in the over 80s and total fatal COVID-19 cases.
Open Access
From your nose to your toes: a review of severe acute respiratory syndrome coronavirus 2 pandemic‒associated pernio
(Elsevier Ltd, 2021) Arkin, L. M.; Moon, J. J.; Tran, J. M.; Asgari, S.; O'Farrelly, C.; Casanova, J. -L.; Cowen, E. W.; Mays, J. W.; Singh, A. M.; Drolet, B. A.; Aiuti, A.; Belot, A.; Bolze, A.; Bondarenko, A.; Sediva, A.; Shcherbina, A.; Planas, A. M.; Condino-Neto, A.; Pujol, A.; Catherine, B.; Flores, C.; Rodríguez-Gallego, C.; Prando, C.; Dalgard, C. L.; Roger, C.; Mansouri, D.; van, de Beek, D.; Vinh, D. C.; Hsieh, E.; Andreakos, E.; Haerynck, F.; Uddin, F.; Casari, G.; Novelli, G.; Pesole, G.; Meyts, I.; Tancevski, I.; Fellay, J.; Tur, J.; Kisand, K.; Okamoto, K.; Mironska, K.; Abel, L.; Renia, L.; Ng, L. F. P.; Shahrooei, M.; Soler-Palacín, P.; Brodin, P.; Pan-Hammarström, Q.; Halwani, R.; Perez, de Diego, R.; Al-Muhsen, S.; Espinosa-Padilla, S.; Okada, S.; Özçelik, Tayfun; Tayoun, A. A.; Karamitros, T.; Mogensen, T. H.; Lau, Y. L.
Despite thousands of reported patients with pandemic-associated pernio, low rates of seroconversion and PCR positivity have defied causative linkage to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Pernio in uninfected children is associated with monogenic disorders of excessive IFN-1 immunity, whereas severe COVID-19 pneumonia can result from insufficient IFN-1. Moreover, SARS-CoV-2 spike protein and robust IFN-1 response are seen in the skin of patients with pandemic-associated pernio, suggesting an excessive innate immune skin response to SARS-CoV-2. Understanding the pathophysiology of this phenomenon may elucidate the host mechanisms that drive a resilient immune response to SARS-CoV-2 and could produce relevant therapeutic targets.
Open Access
A global effort to define the human genetics of protective immunity to SARS-CoV-2 infection
(Elsevier, 2020) Casanova, J.-L.; Su, H. C.; Abel, L.; Aiuti, A.; Almuhsen, S.; Arias, A. A.; Bastard, P.; Biggs, C.; Bogunovic, D.; Boisson, B.; Boisson-Dupuis, S.; Bolze, A.; Bondarenko, A.; Bousfiha, A.; Brodin, P.; Bustamante, J.; Butte, M.; Casari, G.; Ciancanelli, M.; Cobat, A.; Condino-Neto, A.; Cooper, M.; Dalgard, C.; Espinosa, S.; Feldman, H.; Fellay, J.; Franco, J. L.; Hagin, D.; Itan, Y.; Jouanguy, E.; Lucas, C.; Mansouri, D.; Meyts, I.; Milner, J.; Mogensen, T.; Morio, T.; Ng, L.; Notarangelo, L. D.; Okada, S.; Özçelik, Tayfun; Palacín, P. S.; Planas, A.; Prando, C.; Puel, A.; Pujol, A.; Redin, C.; Renia, L.; Gallego, J. C. R.; Quintana-Murci, L.; Sancho-Shimizu, V.; Sankaran, V.; Seppänen, M. R. J.; Shahrooei, M.; Snow, A.; Spaan, A.; Tangye, S.; Tur, J. P.; Turvey, S.; Vinh, D. C.; von Bernuth, H.; Wang, X.; Zawadzki, P.; Zhang, Q.; Zhang, S.
SARS-CoV-2 infection displays immense inter-individual clinical variability, ranging from silent infection to lethal disease. The role of human genetics in determining clinical response to the virus remains unclear. Studies of outliers—individuals remaining uninfected despite viral exposure and healthy young patients with life-threatening disease—present a unique opportunity to reveal human genetic determinants of infection and disease.
Open Access
Privacy-preserving genomic testing in the clinic: a model using HIV treatment
(Nature Publishing Group, 2016) Mclaren, P. J.; Raisaro, J. L.; Aouri, M.; Rotger, M.; Ayday, E.; Bartha, I.; Delgado, M. B.; Vallet, Y.; Günthard, H. F.; Cavassini, M.; Furrer, H.; Doco-Lecompte, T.; Marzolini, C.; Schmid, P.; Di Benedetto, C.; Decosterd, L. A.; Fellay, J.; Hubaux, Jean-Pierre; Telenti A.
Purpose:The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics.Methods:We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers.Results:A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865 ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%.Conclusions:The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine.
Open Access
A privacy-preserving solution for compressed storage and selective retrieval of genomic data
(Cold Spring Harbor Laboratory Press, 2016) Huang Z.; Ayday, E.; Lin, H.; Aiyar, R. S.; Molyneaux, A.; Xu, Z.; Fellay, J.; Steinmetz, L. M.; Hubaux, Jean-Pierre
In clinical genomics, the continuous evolution of bioinformatic algorithms and sequencing platforms makes it beneficial to store patients' complete aligned genomic data in addition to variant calls relative to a reference sequence. Due to the large size of human genome sequence data files (varying from 30 GB to 200 GB depending on coverage), two major challenges facing genomics laboratories are the costs of storage and the efficiency of the initial data processing. In addition, privacy of genomic data is becoming an increasingly serious concern, yet no standard data storage solutions exist that enable compression, encryption, and selective retrieval. Here we present a privacy-preserving solution named SECRAM (Selective retrieval on Encrypted and Compressed Reference-oriented Alignment Map) for the secure storage of compressed aligned genomic data. Our solution enables selective retrieval of encrypted data and improves the efficiency of downstream analysis (e.g., variant calling). Compared withBAM, thede factostandard for storing aligned genomic data, SECRAM uses 18%less storage. Compared with CRAM, one of the most compressed nonencrypted formats (using 34% less storage than BAM), SECRAM maintains efficient compression and downstream data processing, while allowing for unprecedented levels of security in genomic data storage. Compared with previous work, the distinguishing features of SECRAM are that (1) it is position-based insteadofread-based,and(2)itallowsrandomqueryingofasubregionfromaBAM-likefileinanencryptedform.Ourmethod thus offers a space-saving, privacy-preserving, and effective solution for the storage of clinical genomic data.
Open Access
Quantifying genomic privacy via inference attack with high-order SNV correlations
(IEEE, 2015) Samani, S. S.; Huang, Z.; Ayday, Erman; Elliot, M.; Fellay, J.; Hubaux, J.-P.; Kutalik, Z.
As genomic data becomes widely used, the problem of genomic data privacy becomes a hot interdisciplinary research topic among geneticists, bioinformaticians and security and privacy experts. Practical attacks have been identified on genomic data, and thus break the privacy expectations of individuals who contribute their genomic data to medical research, or simply share their data online. Frustrating as it is, the problem could become even worse. Existing genomic privacy breaches rely on low-order SNV (Single Nucleotide Variant) correlations. Our work shows that far more powerful attacks can be designed if high-order correlations are utilized. We corroborate this concern by making use of different SNV correlations based on various genomic data models and applying them to an inference attack on individuals' genotype data with hidden SNVs. We also show that low-order models behave very differently from real genomic data and therefore should not be relied upon for privacy-preserving solutions.
Open Access
The risk of COVID-19 death is much greater and age dependent with type I IFN autoantibodies
(National Academy of Sciences, 2022-05-16) Manry, J.; Bastard, P.; Gervais, A.; Le Voyer, T.; Rosain, J.; Philippot, Q.; Michailidis, E.; Hoffmann, H.; Eto, S.; Garcia-Prat, M.; Bizien, L.; Parra-Martínez, A.; Yang, R.; Haljasmägi, L.; Migaud, M.; Särekannu, K.; Maslovskaja, J.; de Prost, N.; Tandjaoui-Lambiotte, Y.; Luyt, C.; Amador-Borrero, B.; Gaudet, A.; Poissy, J.; Morel, P.; Richard, P.; Cognasse, F.; Troya, J.; Trouillet-Assant, S.; Belot, A.; Saker, K.; Garçpn, P.; Rivière, J. G.; Lagier, J.; Gentile, S.; Rosen, L. B.; Shaw, E.; Morio, T.; Tanaka, J.; Dalmau, D.; Tharaux, P.; Sene, D.; Stepanian, A.; Mégarbane, B.; Triantafyllia, V.; Fekkar, A.; Heath, J. R.; Franco, J. L.; Anaya, J.; Solé-Violán, J.; Imberti, L.; Biondi, A.; Bonfanti, P.; Castagnoli, R.; Delmonte, O. M.; Zhang, Y.; Snow, A. L.; Holland, S. M.; Biggs, C. M.; Moncada-Vélez, M.; Arias, A. A.; Lorenzo, L.; Boucherit, S.; Anglicheau, D.; Planas, A. M.; Haerynck, F.; Duvlis, S.; Ozcelik, Tayfun; Keles, S.; Bousfiha, A. A.; El Bakkouri, J.; Ramirez-Santana, C.; Paul, S.; Pan-Hammarström, Q.; Hammarström, L.; Dupont, A.; Kurolap, A.; Metz, C. N.; Aiuti, A.; Casari, G.; Lampasona, V.; Ciceri, F.; Barreiros, L. A.; Dominguez-Garrido, E.; Vidigal, M.; Zatz, M.; van de Beek, D.; Sahanic, S.; Tancevski, I.; Stepanovskyy, Y.; Boyarchuk, O.; Nukui, Y.; Tsumura, M.; Vidaur, L.; Tangye, S. G.; Burrel, S.; Duffy, D.; Quintana-Murci, L.; Klocperk, A.; Kann, N. Y.; Shcherbina, A.; Lau, Y.; Leung, D.; Coulongeat, M.; Marlet, J.; Koning, R.; Reyes, L. F.; Chauvineau-Grenier, A.; Venet, F.; Monneret, G.; Nussenzweig, M. C.; Arrestier, R.; Boudhabhay, I.; Baris-Feldman, H.; Hagin, D.; Wauters, J.; Meyts, I.; Dyer, A. H.; Kennelly, S. P.; Bourke, N. M.; Halwani, R.; Sharif-Askari, F. S.; Dorgham, K.; Sallette, J.; Sedkaoui, S. M.; AlKhater, S.; Rigo-Bonnin, R.; Morandeira, F.; Roussel, L.; Vinh, D. C.; Erikstrup, C.; Condino-Neto, A.; Prando, C.; Bondarenko, A.; Spaan, A. N.; Gilardin, L.; Fellay, J.; Lyonnet, S.; Bilguvar, K.; Lifton, R. P.; Mane, S.; Anderson, M. S.; Boisson, B.; Béziat, V.; Zhang, S.; Andreakos, E.; Hermine, O.; Pujol, A.; Peterson, P.; Mogensen, T. H.; Rowen, L.; Mond, J.; Debette, S.; de Lamballerie, X.; Burdet, C.; Bouadma, L.; Zins, M.; Soler-Palacin, P.; Colobran, R.; Gorochov, G.; Solanich, X.; Susen, S.; Martinez-Picado, J.; Raoult, D.; Vasse, M.; Gregersen, P. K.; Piemonti, L.; Rodríguez-Gallego, C.; Notarangelo, L. D.; Su, H. C.; Kisand, K.; Okada, S.; Puel, A.; Jouanguy, E.; Rice, C. M.; Tiberghien, P.; Zhang, Q.; Casanova, J.; Abel, L.; Cobat, A.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection fatality rate (IFR) doubles with every 5 y of age from childhood onward. Circulating autoantibodies neutralizing IFN-α, IFN-ω, and/or IFN-β are found in ∼20% of deceased patients across age groups, and in ∼1% of individuals aged [removed]4% of those >70 y old in the general population. With a sample of 1,261 unvaccinated deceased patients and 34,159 individuals of the general population sampled before the pandemic, we estimated both IFR and relative risk of death (RRD) across age groups for individuals carrying autoantibodies neutralizing type I IFNs, relative to noncarriers. The RRD associated with any combination of autoantibodies was higher in subjects under 70 y old. For autoantibodies neutralizing IFN-α2 or IFN-ω, the RRDs were 17.0 (95% CI: 11.7 to 24.7) and 5.8 (4.5 to 7.4) for individuals <70 y and ≥70 y old, respectively, whereas, for autoantibodies neutralizing both molecules, the RRDs were 188.3 (44.8 to 774.4) and 7.2 (5.0 to 10.3), respectively. In contrast, IFRs increased with age, ranging from 0.17% (0.12 to 0.31) for individuals <40 y old to 26.7% (20.3 to 35.2) for those ≥80 y old for autoantibodies neutralizing IFN-α2 or IFN-ω, and from 0.84% (0.31 to 8.28) to 40.5% (27.82 to 61.20) for autoantibodies neutralizing both. Autoantibodies against type I IFNs increase IFRs, and are associated with high RRDs, especially when neutralizing both IFN-α2 and IFN-ω. Remarkably, IFRs increase with age, whereas RRDs decrease with age. Autoimmunity to type I IFNs is a strong and common predictor of COVID-19 death.