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14 results on '"Fletez-Brant K."'

1. Genetic analyses identify widespread sex-differential participation bias

Author

Pirastu N., Cordioli M., Nandakumar P., Mignogna G., Abdellaoui A., Hollis B., Kanai M., Rajagopal V. M., Parolo P. D. B., Baya N., Carey C. E., Karjalainen J., Als T. D., Van der Zee M. D., Day F. R., Ong K. K., Agee M., Aslibekyan S., Bell R. K., Bryc K., Clark S. K., Elson S. L., Fletez-Brant K., Fontanillas P., Furlotte N. A., Gandhi P. M., Heilbron K., Hicks B., Huber K. E., Jewett E. M., Jiang Y., Kleinman A., Lin K. -H., Litterman N. K., Luff M. K., McIntyre M. H., McManus K. F., Mountain J. L., Mozaffari S. V., Noblin E. S., Northover C. A. M., O'Connell J., Petrakovitz A. A., Pitts S. J., Poznik G. D., Sathirapongsasuti J. F., Shelton J. F., Shringarpure S., Tian C., Tung J. Y., Tunney R. J., Vacic V., Wang X., Zare A., Mortensen P. B., Mors O., Werge T., Nordentoft M., Hougaard D. M., Bybjerg-Grauholm J., Baekvad-Hansen M., Morisaki T., de Geus E., Bellocco R., Okada Y., Borglum A. D., Joshi P., Auton A., Hinds D., Neale B. M., Walters R. K., Nivard M. G., Perry J. R. B., Ganna A., Pirastu, N, Cordioli, M, Nandakumar, P, Mignogna, G, Abdellaoui, A, Hollis, B, Kanai, M, Rajagopal, V, Parolo, P, Baya, N, Carey, C, Karjalainen, J, Als, T, Van der Zee, M, Day, F, Ong, K, Agee, M, Aslibekyan, S, Bell, R, Bryc, K, Clark, S, Elson, S, Fletez-Brant, K, Fontanillas, P, Furlotte, N, Gandhi, P, Heilbron, K, Hicks, B, Huber, K, Jewett, E, Jiang, Y, Kleinman, A, Lin, K, Litterman, N, Luff, M, Mcintyre, M, Mcmanus, K, Mountain, J, Mozaffari, S, Noblin, E, Northover, C, O'Connell, J, Petrakovitz, A, Pitts, S, Poznik, G, Sathirapongsasuti, J, Shelton, J, Shringarpure, S, Tian, C, Tung, J, Tunney, R, Vacic, V, Wang, X, Zare, A, Mortensen, P, Mors, O, Werge, T, Nordentoft, M, Hougaard, D, Bybjerg-Grauholm, J, Baekvad-Hansen, M, Morisaki, T, de Geus, E, Bellocco, R, Okada, Y, Borglum, A, Joshi, P, Auton, A, Hinds, D, Neale, B, Walters, R, Nivard, M, Perry, J, Ganna, A, Biological Psychology, APH - Personalized Medicine, APH - Mental Health, and Adult Psychiatry

Subjects
Adult, Inheritance Pattern, Male, Sex Characteristics, Inheritance Patterns, Sex Characteristic, Polymorphism, Single Nucleotide, Article, United Kingdom, Bias, Genetic Loci, Sample Size, Bia, Artifact, Biological Specimen Bank, Humans, Chromosomes, Human, Female, Artifacts, Biological Specimen Banks, Genome-Wide Association Study, Human
Abstract

Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of participation bias is challenging since it requires the genotypes of unseen individuals. Here we demonstrate that it is possible to estimate comparative biases by performing a genome-wide association study contrasting one subgroup versus another. For example, we showed that sex exhibits artifactual autosomal heritability in the presence of sex-differential participation bias. By performing a genome-wide association study of sex in approximately 3.3 million males and females, we identified over 158 autosomal loci spuriously associated with sex and highlighted complex traits underpinning differences in study participation between the sexes. For example, the body mass index-increasing allele at FTO was observed at higher frequency in males compared to females (odds ratio = 1.02, P = 4.4 × 10-36). Finally, we demonstrated how these biases can potentially lead to incorrect inferences in downstream analyses and propose a conceptual framework for addressing such biases. Our findings highlight a new challenge that genetic studies may face as sample sizes continue to grow.

Published
2021

2. Genetic analyses identify widespread sex-differential participation bias

Author

Pirastu, N, Cordioli, M, Nandakumar, P, Mignogna, G, Abdellaoui, A, Hollis, B, Kanai, M, Rajagopal, V, Parolo, P, Baya, N, Carey, C, Karjalainen, J, Als, T, Van der Zee, M, Day, F, Ong, K, Agee, M, Aslibekyan, S, Bell, R, Bryc, K, Clark, S, Elson, S, Fletez-Brant, K, Fontanillas, P, Furlotte, N, Gandhi, P, Heilbron, K, Hicks, B, Huber, K, Jewett, E, Jiang, Y, Kleinman, A, Lin, K, Litterman, N, Luff, M, Mcintyre, M, Mcmanus, K, Mountain, J, Mozaffari, S, Noblin, E, Northover, C, O'Connell, J, Petrakovitz, A, Pitts, S, Poznik, G, Sathirapongsasuti, J, Shelton, J, Shringarpure, S, Tian, C, Tung, J, Tunney, R, Vacic, V, Wang, X, Zare, A, Mortensen, P, Mors, O, Werge, T, Nordentoft, M, Hougaard, D, Bybjerg-Grauholm, J, Baekvad-Hansen, M, Morisaki, T, de Geus, E, Bellocco, R, Okada, Y, Borglum, A, Joshi, P, Auton, A, Hinds, D, Neale, B, Walters, R, Nivard, M, Perry, J, Ganna, A, Pirastu N., Cordioli M., Nandakumar P., Mignogna G., Abdellaoui A., Hollis B., Kanai M., Rajagopal V. M., Parolo P. D. B., Baya N., Carey C. E., Karjalainen J., Als T. D., Van der Zee M. D., Day F. R., Ong K. K., Agee M., Aslibekyan S., Bell R. K., Bryc K., Clark S. K., Elson S. L., Fletez-Brant K., Fontanillas P., Furlotte N. A., Gandhi P. M., Heilbron K., Hicks B., Huber K. E., Jewett E. M., Jiang Y., Kleinman A., Lin K. -H., Litterman N. K., Luff M. K., McIntyre M. H., McManus K. F., Mountain J. L., Mozaffari S. V., Noblin E. S., Northover C. A. M., O'Connell J., Petrakovitz A. A., Pitts S. J., Poznik G. D., Sathirapongsasuti J. F., Shelton J. F., Shringarpure S., Tian C., Tung J. Y., Tunney R. J., Vacic V., Wang X., Zare A., Mortensen P. B., Mors O., Werge T., Nordentoft M., Hougaard D. M., Bybjerg-Grauholm J., Baekvad-Hansen M., Morisaki T., de Geus E., Bellocco R., Okada Y., Borglum A. D., Joshi P., Auton A., Hinds D., Neale B. M., Walters R. K., Nivard M. G., Perry J. R. B., Ganna A., Pirastu, N, Cordioli, M, Nandakumar, P, Mignogna, G, Abdellaoui, A, Hollis, B, Kanai, M, Rajagopal, V, Parolo, P, Baya, N, Carey, C, Karjalainen, J, Als, T, Van der Zee, M, Day, F, Ong, K, Agee, M, Aslibekyan, S, Bell, R, Bryc, K, Clark, S, Elson, S, Fletez-Brant, K, Fontanillas, P, Furlotte, N, Gandhi, P, Heilbron, K, Hicks, B, Huber, K, Jewett, E, Jiang, Y, Kleinman, A, Lin, K, Litterman, N, Luff, M, Mcintyre, M, Mcmanus, K, Mountain, J, Mozaffari, S, Noblin, E, Northover, C, O'Connell, J, Petrakovitz, A, Pitts, S, Poznik, G, Sathirapongsasuti, J, Shelton, J, Shringarpure, S, Tian, C, Tung, J, Tunney, R, Vacic, V, Wang, X, Zare, A, Mortensen, P, Mors, O, Werge, T, Nordentoft, M, Hougaard, D, Bybjerg-Grauholm, J, Baekvad-Hansen, M, Morisaki, T, de Geus, E, Bellocco, R, Okada, Y, Borglum, A, Joshi, P, Auton, A, Hinds, D, Neale, B, Walters, R, Nivard, M, Perry, J, Ganna, A, Pirastu N., Cordioli M., Nandakumar P., Mignogna G., Abdellaoui A., Hollis B., Kanai M., Rajagopal V. M., Parolo P. D. B., Baya N., Carey C. E., Karjalainen J., Als T. D., Van der Zee M. D., Day F. R., Ong K. K., Agee M., Aslibekyan S., Bell R. K., Bryc K., Clark S. K., Elson S. L., Fletez-Brant K., Fontanillas P., Furlotte N. A., Gandhi P. M., Heilbron K., Hicks B., Huber K. E., Jewett E. M., Jiang Y., Kleinman A., Lin K. -H., Litterman N. K., Luff M. K., McIntyre M. H., McManus K. F., Mountain J. L., Mozaffari S. V., Noblin E. S., Northover C. A. M., O'Connell J., Petrakovitz A. A., Pitts S. J., Poznik G. D., Sathirapongsasuti J. F., Shelton J. F., Shringarpure S., Tian C., Tung J. Y., Tunney R. J., Vacic V., Wang X., Zare A., Mortensen P. B., Mors O., Werge T., Nordentoft M., Hougaard D. M., Bybjerg-Grauholm J., Baekvad-Hansen M., Morisaki T., de Geus E., Bellocco R., Okada Y., Borglum A. D., Joshi P., Auton A., Hinds D., Neale B. M., Walters R. K., Nivard M. G., Perry J. R. B., and Ganna A.

Abstract

Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of participation bias is challenging since it requires the genotypes of unseen individuals. Here we demonstrate that it is possible to estimate comparative biases by performing a genome-wide association study contrasting one subgroup versus another. For example, we showed that sex exhibits artifactual autosomal heritability in the presence of sex-differential participation bias. By performing a genome-wide association study of sex in approximately 3.3 million males and females, we identified over 158 autosomal loci spuriously associated with sex and highlighted complex traits underpinning differences in study participation between the sexes. For example, the body mass index–increasing allele at FTO was observed at higher frequency in males compared to females (odds ratio = 1.02, P = 4.4 × 10−36). Finally, we demonstrated how these biases can potentially lead to incorrect inferences in downstream analyses and propose a conceptual framework for addressing such biases. Our findings highlight a new challenge that genetic studies may face as sample sizes continue to grow.

Published
2021

3. Genome-wide association study of REM sleep behavior disorder identifies polygenic risk and brain expression effects

Author

Krohn, L., Heilbron, K., Blauwendraat, C., Reynolds, R. H., Yu, E., Senkevich, K., Rudakou, U., Estiar, M. A., Gustavsson, E. K., Brolin, K., Ruskey, J. A., Freeman, K., Asayesh, F., Chia, R., Arnulf, I., M. T. M., Hu, Montplaisir, J. Y., Gagnon, J. -F., Desautels, A., Dauvilliers, Y., Gigli, G. L., Valente, M., Janes, F., Bernardini, A., Hogl, B., Stefani, A., Ibrahim, A., Sonka, K., Kemlink, D., Oertel, W., Janzen, A., Plazzi, G., Biscarini, F., Antelmi, E., Figorilli, M., Puligheddu, M., Mollenhauer, B., Trenkwalder, C., Sixel-Doring, F., Cochen De Cock, V., Monaca, C. C., Heidbreder, A., Ferini-Strambi, L., Dijkstra, F., Viaene, M., Abril, B., Boeve, B. F., Aslibekyan, S., Auton, A., Babalola, E., Bell, R. K., Bielenberg, J., Bryc, K., Bullis, E., Coker, D., Partida, G. C., Dhamija, D., Das, S., Elson, S. L., Filshtein, T., Fletez-Brant, K., Fontanillas, P., Freyman, W., Gandhi, P. M., Hicks, B., Hinds, D. A., Jewett, E. M., Jiang, Y., Kukar, K., Lin, K. -H., Lowe, M., Mccreight, J. C., Mcintyre, M. H., Micheletti, S. J., Moreno, M. E., Mountain, J. L., Nandakumar, P., Noblin, E. S., O'Connell, J., Petrakovitz, A. A., Poznik, G. D., Schumacher, M., Shastri, A. J., Shelton, J. F., Shi, J., Shringarpure, S., Tran, V., Tung, J. Y., Wang, X., Wang, W., Weldon, C. H., Wilton, P., Hernandez, A., Wong, C., Tchakoute, C. T., Scholz, S. W., Ryten, M., Bandres-Ciga, S., Noyce, A., Cannon, P., Pihlstrom, L., Nalls, M. A., Singleton, A. B., Rouleau, G. A., Postuma, R. B., Gan-Or, Z., and 23andMe Research Team

Subjects
Multidisciplinary, Risk factors, General Physics and Astronomy, Genomics, General Chemistry, Human medicine, Genome-wide association studies, General Biochemistry, Genetics and Molecular Biology
Abstract

Rapid-eye movement (REM) sleep behavior disorder (RBD), enactment of dreams during REM sleep, is an early clinical symptom of alpha-synucleinopathies and defines a more severe subtype. The genetic background of RBD and its underlying mechanisms are not well understood. Here, we perform a genome-wide association study of RBD, identifying five RBD risk loci near SNCA, GBA, TMEM175, INPP5F, and SCARB2. Expression analyses highlight SNCA-AS1 and potentially SCARB2 differential expression in different brain regions in RBD, with SNCA-AS1 further supported by colocalization analyses. Polygenic risk score, pathway analysis, and genetic correlations provide further insights into RBD genetics, highlighting RBD as a unique alpha-synucleinopathy subpopulation that will allow future early intervention. REM-sleep behavior disorder often precedes Parkinson's disease or dementia. Here, the authors perform a genome-wide association study for REM-sleep behavior disorder, and discover how it potentially affects gene expression in the brain.

Published
2022

4. FUT6 deficiency compromises basophil function by selectively abrogating their sialyl-Lewis x expression

Author

Puan, K., San Luis, B., Yusof, N., Kumar, D., Andiappan, A., Lee, W., Cajic, S., Vuckovic, D., Chan, J., Döllner, T., Hou, H., Jiang, Y., Tian, C., Agee, M., Aslibekyan, S., Auton, A., Babalola, E., Bell, R., Bielenberg, J., Bryc, K., Bullis, E., Cameron, B., Coker, D., Partida, G., Dhamija, D., Das, S., Elson, S., Filshtein, T., Fletez-Brant, K., Fontanillas, P., Freyman, W., Gandhi, P., Heilbron, K., Hicks, B., Hinds, D., Huber, K., Jewett, E., Kleinman, A., Kukar, K., Lane, V., Lin, K., Lowe, M., Luff, M., McCreight, J., McIntyre, M., McManus, K., Micheletti, S., Moreno, M., Mountain, J., Mozaffari, S., Nandakumar, P., Noblin, E., O’Connell, J., Petrakovitz, A., Poznik, G., Schumacher, M., Shastri, A., Shelton, J., Shi, J., Shringarpure, S., Tran, V., Tung, J., Wang, X., Wang, W., Weldon, C., Wilton, P., Rapp, E., Poidinger, M., Wang, D., Soranzo, N., Lee, B., Rötzschke, O., Puan, Kia Joo [0000-0003-2445-3154], Kumar, Dilip [0000-0002-1848-3034], Andiappan, Anand Kumar [0000-0002-8442-1544], Cajic, Samanta [0000-0001-5820-0732], Chan, Jing De [0000-0002-2249-5273], Hou, Han Wei [0000-0001-6631-6321], Rapp, Erdmann [0000-0001-6618-2626], Poidinger, Michael [0000-0002-1047-2277], Soranzo, Nicole [0000-0003-1095-3852], Rötzschke, Olaf [0000-0001-8336-5248], Apollo - University of Cambridge Repository, Lee Kong Chian School of Medicine (LKCMedicine), and School of Mechanical and Aerospace Engineering

Subjects
0301 basic medicine, Fucosyltransferase, Allergy, QH301-705.5, Population, Medicine (miscellaneous), T-Cells, Genetic predisposition to disease, Gene Expression, Basophil, Immunoglobulin E, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, Cohort Studies, 03 medical and health sciences, chemistry.chemical_compound, Leukocyte Count, 0302 clinical medicine, Sequence Homology, Nucleic Acid, medicine, Humans, Medicine [Science], Leukocyte Rolling, Biology (General), education, Sialyl Lewis X Antigen, Cells, Cultured, education.field_of_study, biology, Base Sequence, Gene Expression Profiling, Mast-Cells, Eosinophil, Mast cell, Fucosyltransferases, Molecular biology, Null allele, Basophils, 030104 developmental biology, medicine.anatomical_structure, Sialyl-Lewis X, chemistry, 030220 oncology & carcinogenesis, biology.protein, Mechanical engineering [Engineering], General Agricultural and Biological Sciences, E-Selectin
Abstract

Sialyl-Lewis x (sLex, CD15s) is a tetra-saccharide on the surface of leukocytes required for E-selectin-mediated rolling, a prerequisite for leukocytes to migrate out of the blood vessels. Here we show using flow cytometry that sLex expression on basophils and mast cell progenitors depends on fucosyltransferase 6 (FUT6). Using genetic association data analysis and qPCR, the cell type-specific defect was associated with single nucleotide polymorphisms (SNPs) in the FUT6 gene region (tagged by rs17855739 and rs778798), affecting coding sequence and/or expression level of the mRNA. Heterozygous individuals with one functional FUT6 gene harbor a mixed population of sLex+ and sLex- basophils, a phenomenon caused by random monoallelic expression (RME). Microfluidic assay demonstrated FUT6-deficient basophils rolling on E-selectin is severely impaired. FUT6 null alleles carriers exhibit elevated blood basophil counts and a reduced itch sensitivity against insect bites. FUT6-deficiency thus dampens the basophil-mediated allergic response in the periphery, evident also in lower IgE titers and reduced eosinophil counts., Puan and San Luis et al. find that FUT6, encoding a fucosyltransferase, is required for the “rolling” behavior of certain white blood cells that enables them to move from blood vessels to tissues. They show that FUT6 deficiency leads to a loss of the tetrasaccharide sLex on the surface of basophils, resulting in cells that are less sticky and therefore less able to form the necessary adhesions for exiting the blood vessel to drive the allergic reaction.

Published
2021

5. A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer’s disease

Author

Wightman, D. P., Jansen, I. E., Savage, J. E., Shadrin, A. A., Bahrami, S., Holland, D., Rongve, A., Børte, S., Winsvold, B. S., Drange, O. K., Martinsen, A. E., Skogholt, A. H., Willer, C., Bråthen, G., Bosnes, I., Nielsen, J. B., Fritsche, L. G., Thomas, L. F., Pedersen, L. M., Gabrielsen, M. E., Johnsen, M. B., Meisingset, T. W., Zhou, W., Proitsi, P., Hodges, A., Dobson, R., Velayudhan, L., Agee, M., Aslibekyan, S., Babalola, E., Bell, R. K., Bielenberg, J., Bryc, K., Bullis, E., Cameron, B., Coker, D., Partida, G. C., Dhamija, D., Das, S., Elson, S. L., Filshtein, T., Fletez-Brant, K., Fontanillas, P., Freyman, W., Gandhi, P. M., Hicks, B., Hinds, D. A., Huber, K. E., Jewett, E. M., Jiang, Y., Kleinman, A., Kukar, K., Lane, V., Lin, K. -H, Lowe, M., Luff, M. K., McCreight, J. C., McIntyre, M. H., McManus, K. F., Micheletti, S. J., Moreno, M. E., Mountain, J. L., Mozaffari, S. V., Nandakumar, P., Noblin, E. S., O’Connell, J., Petrakovitz, A. A., Poznik, G. D., Schumacher, M., Shastri, A. J., Shelton, J. F., Shi, J., Shringarpure, S., Tian, C., Tran, V., Tung, J. Y., Wang, X., Wang, W., Weldon, C. H., Wilton, P., Sealock, J. M., Davis, L. K., Pedersen, N. L., Reynolds, C. A., Karlsson, Ida K., Magnusson, S., Stefansson, H., Thordardottir, S., Jonsson, P. V., Snaedal, J., Zettergren, A., Skoog, I., Kern, S., Waern, M., Zetterberg, H., Blennow, K., Stordal, E., Hveem, K., Zwart, J. -A, Athanasiu, L., Selnes, P., Saltvedt, I., Sando, S. B., Ulstein, I., Djurovic, S., Fladby, T., Aarsland, D., Selbæk, G., Ripke, S., Stefansson, K., Andreassen, O. A., Posthuma, D., Team, 23andMe Research, Wightman, D. P., Jansen, I. E., Savage, J. E., Shadrin, A. A., Bahrami, S., Holland, D., Rongve, A., Børte, S., Winsvold, B. S., Drange, O. K., Martinsen, A. E., Skogholt, A. H., Willer, C., Bråthen, G., Bosnes, I., Nielsen, J. B., Fritsche, L. G., Thomas, L. F., Pedersen, L. M., Gabrielsen, M. E., Johnsen, M. B., Meisingset, T. W., Zhou, W., Proitsi, P., Hodges, A., Dobson, R., Velayudhan, L., Agee, M., Aslibekyan, S., Babalola, E., Bell, R. K., Bielenberg, J., Bryc, K., Bullis, E., Cameron, B., Coker, D., Partida, G. C., Dhamija, D., Das, S., Elson, S. L., Filshtein, T., Fletez-Brant, K., Fontanillas, P., Freyman, W., Gandhi, P. M., Hicks, B., Hinds, D. A., Huber, K. E., Jewett, E. M., Jiang, Y., Kleinman, A., Kukar, K., Lane, V., Lin, K. -H, Lowe, M., Luff, M. K., McCreight, J. C., McIntyre, M. H., McManus, K. F., Micheletti, S. J., Moreno, M. E., Mountain, J. L., Mozaffari, S. V., Nandakumar, P., Noblin, E. S., O’Connell, J., Petrakovitz, A. A., Poznik, G. D., Schumacher, M., Shastri, A. J., Shelton, J. F., Shi, J., Shringarpure, S., Tian, C., Tran, V., Tung, J. Y., Wang, X., Wang, W., Weldon, C. H., Wilton, P., Sealock, J. M., Davis, L. K., Pedersen, N. L., Reynolds, C. A., Karlsson, Ida K., Magnusson, S., Stefansson, H., Thordardottir, S., Jonsson, P. V., Snaedal, J., Zettergren, A., Skoog, I., Kern, S., Waern, M., Zetterberg, H., Blennow, K., Stordal, E., Hveem, K., Zwart, J. -A, Athanasiu, L., Selnes, P., Saltvedt, I., Sando, S. B., Ulstein, I., Djurovic, S., Fladby, T., Aarsland, D., Selbæk, G., Ripke, S., Stefansson, K., Andreassen, O. A., Posthuma, D., and Team, 23andMe Research

Abstract

Late-onset Alzheimer’s disease is a prevalent age-related polygenic disease that accounts for 50–70% of dementia cases. Currently, only a fraction of the genetic variants underlying Alzheimer’s disease have been identified. Here we show that increased sample sizes allowed identification of seven previously unidentified genetic loci contributing to Alzheimer’s disease. This study highlights microglia, immune cells and protein catabolism as relevant to late-onset Alzheimer’s disease, while identifying and prioritizing previously unidentified genes of potential interest. We anticipate that these results can be included in larger meta-analyses of Alzheimer’s disease to identify further genetic variants that contribute to Alzheimer’s pathology.

Published
2021
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6. Genome-wide study identifies association between HLA-B∗55:01 and Self-Reported Penicillin Allergy

Author

Krebs, K., Bovijn, J., Zheng, N., Lepamets, M., Censin, J.C., Jürgenson, T., Särg, D., Abner, E., Laisk, T., Luo, Y., Skotte, L., Geller, F., Feenstra, B., Wang, W., Auton, A., Raychaudhuri, S., Esko, T., Metspalu, A., Laur, S., Roden, D.M., Wei, W-Q, Holmes, M.V., Lindgren, C.M., Phillips, E.J., Mägi, R., Milani, L., Fadista, J., Agee, M., Aslibekyan, S., Bell, R.K., Bryc, K., Clark, S.K., Elson, S.L., Fletez-Brant, K., Fontanillas, P., Furlotte, N.A., Gandhi, P.M., Heilbron, K., Hicks, B., Hinds, D.A., Huber, K.E., Jewett, E.M., Jiang, Y., Kleinman, A., Lin, K-H, Litterman, N.K., Luff, M.K., McCreight, J.C., McIntyre, M.H., McManus, K.F., Mountain, J.L., Mozaffari, S.V., Nandakumar, P., Noblin, E.S., Northover, C.A.M., O’Connell, J., Petrakovitz, A.A., Pitts, S.J., Poznik, G.D., Sathirapongsasuti, J.F., Shastri, A.J., Shelton, J.F., Shringarpure, S., Tian, C., Tung, J.Y., Tunney, R.J., Vacic, V., Wang, X., Zare, A.S., Krebs, K., Bovijn, J., Zheng, N., Lepamets, M., Censin, J.C., Jürgenson, T., Särg, D., Abner, E., Laisk, T., Luo, Y., Skotte, L., Geller, F., Feenstra, B., Wang, W., Auton, A., Raychaudhuri, S., Esko, T., Metspalu, A., Laur, S., Roden, D.M., Wei, W-Q, Holmes, M.V., Lindgren, C.M., Phillips, E.J., Mägi, R., Milani, L., Fadista, J., Agee, M., Aslibekyan, S., Bell, R.K., Bryc, K., Clark, S.K., Elson, S.L., Fletez-Brant, K., Fontanillas, P., Furlotte, N.A., Gandhi, P.M., Heilbron, K., Hicks, B., Hinds, D.A., Huber, K.E., Jewett, E.M., Jiang, Y., Kleinman, A., Lin, K-H, Litterman, N.K., Luff, M.K., McCreight, J.C., McIntyre, M.H., McManus, K.F., Mountain, J.L., Mozaffari, S.V., Nandakumar, P., Noblin, E.S., Northover, C.A.M., O’Connell, J., Petrakovitz, A.A., Pitts, S.J., Poznik, G.D., Sathirapongsasuti, J.F., Shastri, A.J., Shelton, J.F., Shringarpure, S., Tian, C., Tung, J.Y., Tunney, R.J., Vacic, V., Wang, X., and Zare, A.S.

Abstract

Hypersensitivity reactions to drugs are often unpredictable and can be life threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. We extracted data from the electronic health records of more than 600,000 participants from the UK, Estonian, and Vanderbilt University Medical Center’s BioVU biobanks to study the role of genetic variation in the occurrence of self-reported penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from these cohorts to further fine map the human leukocyte antigen (HLA) association and replicated our results in 23andMe’s research cohort involving a total of 1.12 million individuals. Genome-wide meta-analysis of penicillin allergy revealed two loci, including one located in the HLA region on chromosome 6. This signal was further fine-mapped to the HLA-B∗55:01 allele (OR 1.41 95% CI 1.33–1.49, p value 2.04 × 10−31) and confirmed by independent replication in 23andMe’s research cohort (OR 1.30 95% CI 1.25–1.34, p value 1.00 × 10−47). The lead SNP was also associated with lower lymphocyte counts and in silico follow-up suggests a potential effect on T-lymphocytes at HLA-B∗55:01. We also observed a significant hit in PTPN22 and the GWAS results correlated with the genetics of rheumatoid arthritis and psoriasis. We present robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.

Published
2020

7. Genetic Consequences of the Transatlantic Slave Trade in the Americas

Author

Micheletti, Steven J., primary, Bryc, Kasia, additional, Ancona Esselmann, Samantha G., additional, Freyman, William A., additional, Moreno, Meghan E., additional, Poznik, G. David, additional, Shastri, Anjali J., additional, Beleza, Sandra, additional, Mountain, Joanna L., additional, Agee, M., additional, Aslibekyan, S., additional, Auton, A., additional, Bell, R., additional, Clark, S., additional, Das, S., additional, Elson, S., additional, Fletez-Brant, K., additional, Fontanillas, P., additional, Gandhi, P., additional, Heilbron, K., additional, Hicks, B., additional, Hinds, D., additional, Huber, K., additional, Jewett, E., additional, Jiang, Y., additional, Kleinman, A., additional, Lin, K., additional, Litterman, N., additional, McCreight, J., additional, McIntyre, M., additional, McManus, K., additional, Mozaffari, S., additional, Nandakumar, P., additional, Noblin, L., additional, Northover, C., additional, O’Connell, J., additional, Petrakovitz, A., additional, Pitts, S., additional, Shelton, J., additional, Shringarpure, S., additional, Tian, C., additional, Tung, J., additional, Tunney, R., additional, Vacic, V., additional, Wang, X., additional, and Zare, A., additional

Published
2020
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8. Genome-wide analysis of 53,400 people with irritable bowel syndrome highlights shared genetic pathways with mood and anxiety disorders

Author

Eijsbouts, Chris, Zheng, Tenghao, Kennedy, Nicholas A., Bonfiglio, Ferdinando, Anderson, Carl A., Moutsianas, Loukas, Holliday, Joanne, Shi, Jingchunzi, Shringarpure, Suyash, Voda, Alexandru-Ioan, Farrugia, Gianrico, Franke, Andre, H��benthal, Matthias, Abecasis, Gon��alo, Zawistowski, Matthew, Skogholt, Anne Heidi, Ness-Jensen, Eivind, Hveem, Kristian, Esko, T��nu, Teder-Laving, Maris, Zhernakova, Alexandra, Camilleri, Michael, Boeckxstaens, Guy, Whorwell, Peter J., Spiller, Robin, McVean, Gil, D���Amato, Mauro, Jostins, Luke, Parkes, Miles, Agee, Michelle, Aslibekyan, Stella, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Clark, Sarah K., Elson, Sarah L., Fletez-Brant, Kipper, Fontanillas, Pierre, Furlotte, Nicholas A., Gandhi, Pooja M., Heilbron, Karl, Hicks, Barry, Hinds, David A., Huber, Karen E., Jewett, Ethan M., Jiang, Yunxuan, Kleinman, Aaron, Lin, Keng-Han, Litterman, Nadia K., Luff, Marie K., McCreight, Jey C., McIntyre, Matthew H., McManus, Kimberly F., Mountain, Joanna L., Mozaffari, Sahar V., Nandakumar, Priyanka, Noblin, Elizabeth S., Northover, Carrie A. M., O���Connell, Jared, Petrakovitz, Aaron A., Pitts, Steven J., Poznik, G. David, Sathirapongsasuti, J. Fah, Shastri, Anjali J., Shelton, Janie F., Tian, Chao, Tung, Joyce Y., Tunney, Robert J., Vacic, Vladimir, Wang, Xin, Zare, Amir S., Kashyap, Purna, Chang, Lin, Mayer, Emeran, Heitkemper, Margaret, Sayuk, Gregory S., Ringel-Kulka, Tamar, Ringel, Yehuda, Chey, William D., Eswaran, Shanti, Merchant, Juanita L., Shulman, Robert J., Bujanda, Luis, Garcia-Etxebarria, Koldo, Dlugosz, Aldona, Lindberg, Greger, Schmidt, Peter T., Karling, Pontus, Ohlsson, Bodil, Walter, Susanna, Faresj��, ��shild O., Simren, Magnus, Halfvarson, Jonas, Portincasa, Piero, Barbara, Giovanni, Usai-Satta, Paolo, Neri, Matteo, Nardone, Gerardo, Cuomo, Rosario, Galeazzi, Francesca, Bellini, Massimo, Latiano, Anna, Houghton, Lesley, Jonkers, Daisy, Kurilshikov, Alexander, Weersma, Rinse K., Netea, Mihai, Tesarz, Jonas, Gauss, Annika, Goebel-Stengel, Miriam, Andresen, Viola, Frieling, Thomas, Pehl, Christian, Schaefert, Rainer, Niesler, Beate, Lieb, Wolfgang, Hanevik, Kurt, Langeland, Nina, Wensaas, Knut-Arne, Litleskare, Sverre, Gabrielsen, Maiken E., Thomas, Laurent, Thijs, Vincent, Lemmens, Robin, Van Oudenhove, Lukas, Wouters, Mira, Eijsbouts C., Zheng T., Kennedy N.A., Bonfiglio F., Anderson C.A., Moutsianas L., Holliday J., Shi J., Shringarpure S., Agee M., Aslibekyan S., Auton A., Bell R.K., Bryc K., Clark S.K., Elson S.L., Fletez-Brant K., Fontanillas P., Furlotte N.A., Gandhi P.M., Heilbron K., Hicks B., Hinds D.A., Huber K.E., Jewett E.M., Jiang Y., Kleinman A., Lin K.-H., Litterman N.K., Luff M.K., McCreight J.C., McIntyre M.H., McManus K.F., Mountain J.L., Mozaffari S.V., Nandakumar P., Noblin E.S., Northover C.A.M., O'Connell J., Petrakovitz A.A., Pitts S.J., Poznik G.D., Sathirapongsasuti J.F., Shastri A.J., Shelton J.F., Tian C., Tung J.Y., Tunney R.J., Vacic V., Wang X., Zare A.S., Voda A.-I., Kashyap P., Chang L., Mayer E., Heitkemper M., Sayuk G.S., Ringel-Kulka T., Ringel Y., Chey W.D., Eswaran S., Merchant J.L., Shulman R.J., Bujanda L., Garcia-Etxebarria K., Dlugosz A., Lindberg G., Schmidt P.T., Karling P., Ohlsson B., Walter S., Faresjo A.O., Simren M., Halfvarson J., Portincasa P., Barbara G., Usai-Satta P., Neri M., Nardone G., Cuomo R., Galeazzi F., Bellini M., Latiano A., Houghton L., Jonkers D., Kurilshikov A., Weersma R.K., Netea M., Tesarz J., Gauss A., Goebel-Stengel M., Andresen V., Frieling T., Pehl C., Schaefert R., Niesler B., Lieb W., Hanevik K., Langeland N., Wensaas K.-A., Litleskare S., Gabrielsen M.E., Thomas L., Thijs V., Lemmens R., Van Oudenhove L., Wouters M., Farrugia G., Franke A., Hubenthal M., Abecasis G., Zawistowski M., Skogholt A.H., Ness-Jensen E., Hveem K., Esko T., Teder-Laving M., Zhernakova A., Camilleri M., Boeckxstaens G., Whorwell P.J., Spiller R., McVean G., D'Amato M., Jostins L., Parkes M., Eijsbouts, Chris [0000-0001-5179-0653], Anderson, Carl A. [0000-0003-1719-7009], Moutsianas, Loukas [0000-0001-5453-345X], Holliday, Joanne [0000-0003-4568-7320], Shringarpure, Suyash [0000-0001-6464-2668], Voda, Alexandru-Ioan [0000-0003-2974-6992], Farrugia, Gianrico [0000-0003-3473-5235], Hübenthal, Matthias [0000-0002-5956-3006], Abecasis, Gonçalo [0000-0003-1509-1825], Zawistowski, Matthew [0000-0002-3005-083X], Ness-Jensen, Eivind [0000-0001-6005-0729], Teder-Laving, Maris [0000-0002-5872-1850], Camilleri, Michael [0000-0001-6472-7514], Whorwell, Peter J. [0000-0002-5220-8474], Spiller, Robin [0000-0001-6371-4500], McVean, Gil [0000-0002-5012-4162], D’Amato, Mauro [0000-0003-2743-5197], Jostins, Luke [0000-0002-2475-3969], Parkes, Miles [0000-0002-6467-0631], Apollo - University of Cambridge Repository, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Translational Immunology Groningen (TRIGR), Eijsbouts, C., Zheng, T., Kennedy, N. A., Bonfiglio, F., Anderson, C. A., Moutsianas, L., Holliday, J., Shi, J., Shringarpure, S., Agee, M., Aslibekyan, S., Auton, A., Bell, R. K., Bryc, K., Clark, S. K., Elson, S. L., Fletez-Brant, K., Fontanillas, P., Furlotte, N. A., Gandhi, P. M., Heilbron, K., Hicks, B., Hinds, D. A., Huber, K. E., Jewett, E. M., Jiang, Y., Kleinman, A., Lin, K. -H., Litterman, N. K., Luff, M. K., Mccreight, J. C., Mcintyre, M. H., Mcmanus, K. F., Mountain, J. L., Mozaffari, S. V., Nandakumar, P., Noblin, E. S., Northover, C. A. M., O'Connell, J., Petrakovitz, A. A., Pitts, S. J., Poznik, G. D., Sathirapongsasuti, J. F., Shastri, A. J., Shelton, J. F., Tian, C., Tung, J. Y., Tunney, R. J., Vacic, V., Wang, X., Zare, A. S., Voda, A. -I., Kashyap, P., Chang, L., Mayer, E., Heitkemper, M., Sayuk, G. S., Ringel-Kulka, T., Ringel, Y., Chey, W. D., Eswaran, S., Merchant, J. L., Shulman, R. J., Bujanda, L., Garcia-Etxebarria, K., Dlugosz, A., Lindberg, G., Schmidt, P. T., Karling, P., Ohlsson, B., Walter, S., Faresjo, A. O., Simren, M., Halfvarson, J., Portincasa, P., Barbara, G., Usai-Satta, P., Neri, M., Nardone, G., Cuomo, R., Galeazzi, F., Bellini, M., Latiano, A., Houghton, L., Jonkers, D., Kurilshikov, A., Weersma, R. K., Netea, M., Tesarz, J., Gauss, A., Goebel-Stengel, M., Andresen, V., Frieling, T., Pehl, C., Schaefert, R., Niesler, B., Lieb, W., Hanevik, K., Langeland, N., Wensaas, K. -A., Litleskare, S., Gabrielsen, M. E., Thomas, L., Thijs, V., Lemmens, R., Van Oudenhove, L., Wouters, M., Farrugia, G., Franke, A., Hubenthal, M., Abecasis, G., Zawistowski, M., Skogholt, A. H., Ness-Jensen, E., Hveem, K., Esko, T., Teder-Laving, M., Zhernakova, A., Camilleri, M., Boeckxstaens, G., Whorwell, P. J., Spiller, R., Mcvean, G., D'Amato, M., Jostins, L., and Parkes, M.

Subjects
Male, Molecular Chaperone, Mood Disorder, 631/208/205/2138, Biology, 692/699/1503/1502/2071, Bioinformatics, Polymorphism, Single Nucleotide, Genetic pathways, 38/43, Irritable Bowel Syndrome, Cytoskeletal Protein, Genetics, medicine, Genetic predisposition, Aged, Anxiety Disorders, CD56 Antigen, Cell Adhesion Molecules, Cytoskeletal Proteins, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Guanine Nucleotide Exchange Factors, Homeodomain Proteins, Humans, Middle Aged, Molecular Chaperones, Mood Disorders, United Kingdom, Polymorphism, 692/699/476, Irritable bowel syndrome, Depression (differential diagnoses), article, Homeodomain Protein, Single Nucleotide, Guanine Nucleotide Exchange Factor, medicine.disease, Neuroticism, Biobank, Mood, Cell Adhesion Molecule, Anxiety, medicine.symptom, Anxiety Disorder, Human
Abstract

Funder: Kennedy Trust Rheumatology Research Prize Studentship, Funder: DFG Cluster of Excellence ���Precision Medicine in Chronic In-flammation��� (PMI; ID: EXC2167), Funder: EC | EC Seventh Framework Programm | FP7 Ideas: European Research Council (FP7-IDEAS-ERC - Specific Programme: ���Ideas��� Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013)); doi: https://doi.org/10.13039/100011199; Grant(s): 715772, Funder: NWO-VIDI grant 016.178.056, the Netherlands Heart Foundation CVON grant 2018-27, and NWO Gravitation grant ExposomeNL, Funder: Li Ka Shing Foundation (Li Ka Shing Foundation Limited); doi: https://doi.org/10.13039/100007421, Irritable bowel syndrome (IBS) results from disordered brain���gut interactions. Identifying susceptibility genes could highlight the underlying pathophysiological mechanisms. We designed a digestive health questionnaire for UK Biobank and combined identified cases with IBS with independent cohorts. We conducted a genome-wide association study with 53,400 cases and 433,201 controls and replicated significant associations in a 23andMe panel (205,252 cases and 1,384,055 controls). Our study identified and confirmed six genetic susceptibility loci for IBS. Implicated genes included NCAM1, CADM2, PHF2/FAM120A, DOCK9, CKAP2/TPTE2P3 and BAG6. The first four are associated with mood and anxiety disorders, expressed in the nervous system, or both. Mirroring this, we also found strong genome-wide correlation between the risk of IBS and anxiety, neuroticism and depression (rg > 0.5). Additional analyses suggested this arises due to shared pathogenic pathways rather than, for example, anxiety causing abdominal symptoms. Implicated mechanisms require further exploration to help understand the altered brain���gut interactions underlying IBS.

Published
2021

9. Removing unwanted variation between samples in Hi-C experiments.

Author

Fletez-Brant K, Qiu Y, Gorkin DU, Hu M, and Hansen KD

Subjects
Humans, Computational Biology, Quantitative Trait Loci
Abstract

Hi-C data are commonly normalized using single sample processing methods, with focus on comparisons between regions within a given contact map. Here, we aim to compare contact maps across different samples. We demonstrate that unwanted variation, of likely technical origin, is present in Hi-C data with replicates from different individuals, and that properties of this unwanted variation change across the contact map. We present band-wise normalization and batch correction, a method for normalization and batch correction of Hi-C data and show that it substantially improves comparisons across samples, including in a quantitative trait loci analysis as well as differential enrichment across cell types., (© The Author(s) 2024. Published by Oxford University Press.)

Published
2024
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10. The UGT2A1/UGT2A2 locus is associated with COVID-19-related loss of smell or taste.

Author

Shelton JF, Shastri AJ, Fletez-Brant K, Aslibekyan S, and Auton A

Subjects
Adult, Aged, Female, Humans, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide genetics, Sample Size, Ageusia enzymology, Ageusia genetics, Anosmia enzymology, Anosmia genetics, COVID-19 genetics, Genetic Loci, Genome-Wide Association Study, Glucuronosyltransferase genetics, UDP-Glucuronosyltransferase 1A9 genetics
Abstract

Using online surveys, we collected data regarding COVID-19-related loss of smell or taste from 69,841 individuals. We performed a multi-ancestry genome-wide association study and identified a genome-wide significant locus in the vicinity of the UGT2A1 and UGT2A2 genes. Both genes are expressed in the olfactory epithelium and play a role in metabolizing odorants. These findings provide a genetic link to the biological mechanisms underlying COVID-19-related loss of smell or taste., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2022
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11. Assessing stationary distributions derived from chromatin contact maps.

Author

Segal MR and Fletez-Brant K

Subjects
Chromosomes, Genome, Genomics methods, Molecular Conformation, Reproducibility of Results, Chromatin chemistry
Abstract

Background: The spatial configuration of chromosomes is essential to various cellular processes, notably gene regulation, while architecture related alterations, such as translocations and gene fusions, are often cancer drivers. Thus, eliciting chromatin conformation is important, yet challenging due to compaction, dynamics and scale. However, a variety of recent assays, in particular Hi-C, have generated new details of chromatin structure, spawning a number of novel biological findings. Many findings have resulted from analyses on the level of native contact data as generated by the assays. Alternatively, reconstruction based approaches often proceed by first converting contact frequencies into distances, then generating a three dimensional (3D) chromatin configuration that best recapitulates these distances. Subsequent analyses can enrich contact level analyses via superposition of genomic attributes on the reconstruction. But, such advantages depend on the accuracy of the reconstruction which, absent gold standards, is inherently difficult to assess. Attempts at accuracy evaluation have relied on simulation and/or FISH imaging that typically features a handful of low resolution probes. While newly advanced multiplexed FISH imaging offers possibilities for refined 3D reconstruction accuracy evaluation, availability of such data is limited due to assay complexity and the resolution thereof is appreciably lower than the reconstructions being assessed. Accordingly, there is demand for new methods of reconstruction accuracy appraisal., Results: Here we explore the potential of recently proposed stationary distributions, hereafter StatDns, derived from Hi-C contact matrices, to serve as a basis for reconstruction accuracy assessment. Current usage of such StatDns has focussed on the identification of highly interactive regions (HIRs): computationally defined regions of the genome purportedly involved in numerous long-range intra-chromosomal contacts. Consistent identification of HIRs would be informative with respect to inferred 3D architecture since the corresponding regions of the reconstruction would have an elevated number of k nearest neighbors (kNNs). More generally, we anticipate a monotone decreasing relationship between StatDn values and kNN distances. After initially evaluating the reproducibility of StatDns across replicate Hi-C data sets, we use this implied StatDn - kNN relationship to gauge the utility of StatDns for reconstruction validation, making recourse to both real and simulated examples., Conclusions: Our analyses demonstrate that, as constructed, StatDns do not provide a suitable measure for assessing the accuracy of 3D genome reconstructions. Whether this is attributable to specific choices surrounding normalization in defining StatDns or to the logic underlying their very formulation remains to be determined.

Published
2020
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12. Common DNA sequence variation influences 3-dimensional conformation of the human genome.

Author

Gorkin DU, Qiu Y, Hu M, Fletez-Brant K, Liu T, Schmitt AD, Noor A, Chiou J, Gaulton KJ, Sebat J, Li Y, Hansen KD, and Ren B

Subjects
Epigenome, Humans, Quantitative Trait Loci, Transcriptome, Base Sequence, Genetic Variation, Genome, Human, Nucleic Acid Conformation
Abstract

Background: The 3-dimensional (3D) conformation of chromatin inside the nucleus is integral to a variety of nuclear processes including transcriptional regulation, DNA replication, and DNA damage repair. Aberrations in 3D chromatin conformation have been implicated in developmental abnormalities and cancer. Despite the importance of 3D chromatin conformation to cellular function and human health, little is known about how 3D chromatin conformation varies in the human population, or whether DNA sequence variation between individuals influences 3D chromatin conformation., Results: To address these questions, we perform Hi-C on lymphoblastoid cell lines from 20 individuals. We identify thousands of regions across the genome where 3D chromatin conformation varies between individuals and find that this variation is often accompanied by variation in gene expression, histone modifications, and transcription factor binding. Moreover, we find that DNA sequence variation influences several features of 3D chromatin conformation including loop strength, contact insulation, contact directionality, and density of local cis contacts. We map hundreds of quantitative trait loci associated with 3D chromatin features and find evidence that some of these same variants are associated at modest levels with other molecular phenotypes as well as complex disease risk., Conclusion: Our results demonstrate that common DNA sequence variants can influence 3D chromatin conformation, pointing to a more pervasive role for 3D chromatin conformation in human phenotypic variation than previously recognized.

Published
2019
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13. flowClean: Automated identification and removal of fluorescence anomalies in flow cytometry data.

Author

Fletez-Brant K, Špidlen J, Brinkman RR, Roederer M, and Chattopadhyay PK

Subjects
Cell Tracking instrumentation, Cell Tracking methods, Datasets as Topic, Fluorescence, Humans, Quality Control, Algorithms, Flow Cytometry standards
Abstract

Modern flow cytometry systems can be coupled to plate readers for high-throughput acquisition. These systems allow hundreds of samples to be analyzed in a single day. Quality control of the data remains challenging, however, and is further complicated when a large number of parameters is measured in an experiment. Our examination of 29,228 publicly available FCS files from laboratories worldwide indicates 13.7% have a fluorescence anomaly. In particular, fluorescence measurements for a sample over the collection time may not remain stable due to fluctuations in fluid dynamics; the impact of instabilities may differ between samples and among parameters. Therefore, we hypothesized that tracking cell populations (which represent a summary of all parameters) in centered log ratio space would provide a sensitive and consistent method of quality control. Here, we present flowClean, an algorithm to track subset frequency changes within a sample during acquisition, and flag time periods with fluorescence perturbations leading to the emergence of false populations. Aberrant time periods are reported as a new parameter and added to a revised data file, allowing users to easily review and exclude those events from further analysis. We apply this method to proof-of-concept datasets and also to a subset of data from a recent vaccine trial. The algorithm flags events that are suspicious by visual inspection, as well as those showing more subtle effects that might not be consistently flagged by investigators reviewing the data manually, and out-performs the current state-of-the-art. flowClean is available as an R package on Bioconductor, as a module on the free-to-use GenePattern web server, and as a plugin for FlowJo X. © 2016 International Society for Advancement of Cytometry., (© 2016 International Society for Advancement of Cytometry.)

Published
2016
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14. Reconstitution of Peripheral T Cells by Tissue-Derived CCR4+ Central Memory Cells Following HIV-1 Antiretroviral Therapy.

Author

Mahnke YD, Fletez-Brant K, Sereti I, and Roederer M

Abstract

Background: Highly active antiretroviral therapy induces clinical benefits to HIV-1 infected individuals, which can be striking in those with progressive disease. Improved survival and decreased incidence of opportunistic infections go hand in hand with a suppression of the plasma viral load, an increase in peripheral CD4 + T-cell counts, as well as a reduction in the activation status of both CD4 + and CD8 + T cells., Methods: We investigated T-cell dynamics during ART by polychromatic flow cytometry in total as well as in HIV-1-specific CD4 + and CD8 + T cells in patients with advanced disease. We also measured gene expression by single cell transcriptomics to assess functional state., Results: The cytokine pattern of HIV-specific CD8 + T cells was not altered after ART, though their magnitude decreased significantly as the plasma viral load was suppressed to undetectable levels. Importantly, while CD4 + T cell numbers increased substantially during the first year, the population did not normalize: the increases were largely due to expansion of mucosal-derived CCR4 + CD4 + T CM ; transcriptomic analysis revealed that these are not classical Th 2 -type cells., Conclusion: The apparent long-term normalization of CD4 + T-cell numbers following ART does not comprise a normal balance of functionally distinct cells, but results in a dramatic Th 2 shift of the reconstituting immune system., Competing Interests: CONFLICTS The authors declare no competing interests.

Published
2016
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