1
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Schaschl H, Herzog T, Oberreiter V, Kutanan W, Jakobsson M, Larena M. HLA diversity and signatures of selection in the Maniq, a nomadic hunter-gatherer population in Southern Thailand. Immunogenetics 2025; 77:23. [PMID: 40488890 DOI: 10.1007/s00251-025-01380-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2025] [Accepted: 05/26/2025] [Indexed: 06/11/2025]
Abstract
The Maniq, a small and isolated nomadic hunter-gatherer population from the rainforests of Southern Thailand, offer a unique context for investigating how demographic history, genetic drift, and pathogen-driven selection shape human leucocyte antigen (HLA) diversity. Using high-coverage whole-genome data from 21 individuals (12 unrelated), we genotyped HLA alleles with HLA-HD and T1K, identifying 32 alleles in classical and 14 in non-classical HLA genes. Although overall HLA diversity was comparatively low, a few alleles at each locus occurred at high frequency, mirroring patterns observed in other small, isolated populations. Principal-component analysis clustered the Maniq with other Austroasiatic-speaking Semang hunter-gatherers (Jehai, Kintaq) on the Malay Peninsula and, intriguingly, with the Austronesian-speaking Tao of Taiwan, indicating shared immunogenetic features across linguistic boundaries. Despite reduced diversity, multiple loci bore signatures of both long-term balancing and recent positive selection. Several SNPs under selection were in complete linkage disequilibrium with eQTLs known to influence responses to hepatitis B virus (HBV) and other pathogens, suggesting that pathogen-driven pressure-in particular HBV-may have contributed to recent HLA evolution in the Maniq. These findings provide critical insights into how demographic constraints and pathogen landscapes converge to shape HLA diversity and evolution. In light of increasing infectious disease burdens in indigenous communities, our results underscore the importance of studying small, isolated populations to better understand the adaptive significance of HLA genes.
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Affiliation(s)
- Helmut Schaschl
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, 1030, Vienna, Austria.
| | - Tobias Herzog
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, 1030, Vienna, Austria
| | - Victoria Oberreiter
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, 1030, Vienna, Austria
- Human Evolution and Archeological Sciences (HEAS), University of Vienna, Djerassiplatz 1, 1030, Vienna, Austria
- Konrad Lorenz Institute of Ethology, University of Veterinary Medicine Vienna, Savoyenstraße 1 A, 1160, Vienna, Austria
| | - Wibhu Kutanan
- Department of Biology, Faculty of Science, Naresuan University, Phitsanulok, 65000, Thailand
| | - Mattias Jakobsson
- Human Evolution, Department of Organismal Biology, Uppsala University, Norbyvägen 18 C, 75236, Uppsala, Sweden
| | - Maximilian Larena
- Human Evolution, Department of Organismal Biology, Uppsala University, Norbyvägen 18 C, 75236, Uppsala, Sweden
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2
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Velickovic M, Turner TR. Novel HLA-A, -B, -C and -DRB1 alleles identified in the Australian New South Wales tissue typing laboratory. Hum Immunol 2025; 86:111275. [PMID: 40132251 DOI: 10.1016/j.humimm.2025.111275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2024] [Revised: 02/25/2025] [Accepted: 03/05/2025] [Indexed: 03/27/2025]
Abstract
HLA compatibility between patients and donors is a determining factor for the success of stem cell and solid organ transplantations. However, finding suitable donors remains challenging due to the highly polymorphic nature of HLA genes. Here we are describing 16 novel HLA-A, -B, -C and -DRB1 alleles identified over the period of 2 years. Fourteen differed from their closest reference allele sequence by single nucleotide substitutions detected in the coding regions and 13 contained polymorphism outside antigen recognition domains (exons 2 and 3 in class I and exon 2 in HLA class II). Two novel alleles, a non-sense substitution and a deletion of 2 bp resulted in two null alleles, while a substitution in a splice site resulted in an allele with questionable expression status. In HLA matching procedures, particularly in donor selection, it is important to determine alternatively expressed HLA alleles. Thirteen additional HLA-A, -B, -C and -DRB1 alleles detected as novel at the time of testing were already reported by other laboratories by the time of submission.
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Affiliation(s)
- Marija Velickovic
- New South Wales Transplantation and Immunogenetics Services Pathology and Clinical Governance, Australian Red Cross Lifeblood, Sydney, Australia.
| | - Thomas R Turner
- Anthony Nolan Research Institute, Royal Free Hospital, London, UK; UCL Cancer Institute, Royal Free Campus, London, UK
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3
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Turganbekova A, Abdrakhmanova S, Masalimov Z, Almawi WY. Genetic Diversity and Ethnic Tapestry of Kazakhstan as Inferred from HLA Polymorphism and Population Dynamics: A Comprehensive Review. Genes (Basel) 2025; 16:342. [PMID: 40149493 PMCID: PMC11941833 DOI: 10.3390/genes16030342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2025] [Revised: 03/09/2025] [Accepted: 03/14/2025] [Indexed: 03/29/2025] Open
Abstract
Background: The human leukocyte antigen (HLA) system represents the most polymorphic segment within human DNA sequences and constitutes a core component of immune defense responses and in understanding population genetics. This research investigates the distribution of HLA class I and II polymorphisms across different ethnic groups in Kazakhstan, offering valuable insights into the genetic diversity and demographic evolution within this region. Methods: We performed an in-depth examination of HLA class I and II polymorphisms across diverse ethnic communities living in Kazakhstan, including Kazakhs, Russians, Uzbeks, Ukrainians, Germans, Tatars, and Koreans. Utilizing data from high-resolution HLA typing studies allowed us to assess allele frequencies alongside haplotype distributions while analyzing genetic interrelations between these populations. Additionally, we performed comparative assessments with global HLA databases to determine the genetic affiliations between these groups and their relationships with neighboring and more distant populations. Results: Our study revealed over 200 HLA alleles within the analyzed populations, and significant variations were observed in their allele and haplotype frequencies. Notably, the Kazakh group exhibited strong genetic ties to Asian and Siberian demographics; conversely, other ethnicities showed associations reflective of their historical roots. Notable alleles included HLA-A*02:01, B*07:02, C*07:02, DRB1*07:01, and DQB1*03:01, commonly observed across various groups. Linkage disequilibrium analysis revealed the presence of population-specific haplotypes, highlighting distinct genetic structures within these communities. Conclusions: The findings highlight the significant genetic diversity in Kazakhstan, influenced by its geographical location at the crossroads of Europe and Asia. These results are pertinent to immunogenetics, transplantation medicine, and personalized healthcare within Kazakhstan and adjacent regions. Future research should expand the sample size and explore disease associations to enhance our comprehension of HLA genetics across Central Asia.
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Affiliation(s)
- Aida Turganbekova
- Scientific and Production Center for Transfusiology, Astana 010000, Kazakhstan; (A.T.); (S.A.)
| | - Saniya Abdrakhmanova
- Scientific and Production Center for Transfusiology, Astana 010000, Kazakhstan; (A.T.); (S.A.)
| | - Zhaksylyk Masalimov
- Faculty of Natural Sciences, L.N. Gumilyov Eurasian National University, Astana 010000, Kazakhstan;
| | - Wassim Y. Almawi
- Faculty of Sciences, El-Manar University, El-Manar University Campus at El-Manar, Tunis 2092, Tunisia
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4
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Herzog T, Larena M, Kutanan W, Lukas H, Fieder M, Schaschl H. Natural selection and adaptive traits in the Maniq, a nomadic hunter-gatherer society from Mainland Southeast Asia. Sci Rep 2025; 15:4809. [PMID: 39924514 PMCID: PMC11808089 DOI: 10.1038/s41598-024-83657-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 12/16/2024] [Indexed: 02/11/2025] Open
Abstract
Asia is home to diverse hunter-gatherer populations characterized by significant morphological, anthropological, cultural, and linguistic diversity. Despite their importance in understanding ancestral human subsistence, little is known about the essential genetic adaptations of these groups. This study investigates the evolutionary pressures shaping the genome of the Maniq population, a nomadic hunter-gatherer group inhabiting the rainforests of southern Thailand. Using genome-wide approaches, including iHS, xp-EHH, PBE, and beta statistics, we identified signatures of positive and balancing selection. Genes under positive selection were enriched in pathways related to immunity, metabolic regulation, structural adaptation, cardiovascular performance, and neuromodulatory traits. Several genes associated with the Southeast Asian 'negrito-like' phenotype were also under positive selection. Balancing selection was primarily detected in immune-related genes, particularly within the HLA region, underscoring the critical role of genetic diversity in surviving pathogen-rich environments. Additionally, balancing selection in olfactory receptor genes highlights their importance in environmental sensing and adaptation. These results reveal the intricate interplay of positive and balancing selection in shaping the genetic landscape of the Maniq population and highlight their adaptations to the ecological and lifestyle challenges of life in the rainforest. This study contributes to our understanding of human evolutionary processes in tropical environments and hunter-gatherer societies.
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Affiliation(s)
- Tobias Herzog
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, Vienna, 1030, Austria.
| | - Maximilian Larena
- Human Evolution, Department of Organismal Biology, Uppsala University, Norbyvägen 18C, Uppsala, 75236, Sweden
| | - Wibhu Kutanan
- Department of Biology, Faculty of Science, Naresuan University, Phitsanulok, 65000, Thailand
| | - Helmut Lukas
- Institute for Social Anthropology, Austrian Academy of Sciences, Georg-Coch-Platz 2, Vienna, 1010, Austria
| | - Martin Fieder
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, Vienna, 1030, Austria
| | - Helmut Schaschl
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, Vienna, 1030, Austria.
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5
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Chen X, Wang H, Broce I, Dale A, Yu B, Zhou LY, Li X, Argos M, Daviglus ML, Cai J, Franceschini N, Sofer T. Old vs. New Local Ancestry Inference in HCHS/SOL: A Comparative Study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.04.636481. [PMID: 39975339 PMCID: PMC11838596 DOI: 10.1101/2025.02.04.636481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
Hispanic/Latino populations are admixed, with genetic contributions from multiple ancestral populations. Studies of genetic association in these admixed populations often use methods such as admixture mapping, which relies on inferred counts of "local" ancestry, i.e., of the source ancestral population at a locus. Local ancestries are inferred using external reference panels that represent ancestral populations, making the choice of inference method and reference panel critical. This study used a dataset of Hispanic/Latino individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) to evaluate the "old" local ancestry inference performed using the state-of-the-art inference method, RFMix, alongside "new" inferences performed using Fast Local Ancestry Estimation (FLARE), which also used an updated reference panel. We compared their performance in terms of global and local ancestry correlations, as well as admixture mapping-based associations. Overall, the old RFMix and new FLARE inferences were highly similar for both global and local ancestries, with FLARE-inferred datasets yielding admixture mapping results consistent with those computed from RFMix. However, in some genomic regions the old and new local ancestries have relatively lower correlations (Pearson R < 0.9). Most of these genomic regions (86.42%) were mapped to either ENCODE blacklist regions, or to gene clusters, compared to 7.67% of randomly-matched regions with high correlations (Pearson R > 0.97) between old and new local ancestries.
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Affiliation(s)
- Xueying Chen
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- CardioVascular Institute (CVI), Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Hao Wang
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Iris Broce
- Department of Neurosciences, University of California, San Diego, San Diego, California, USA
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, UCSF, San Francisco, California, USA
| | - Anders Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California, San Diego, San Diego, California, USA
| | - Bing Yu
- Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Laura Y Zhou
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xihao Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maria Argos
- Department of Environmental Health, School of Public Health, Boston University, Boston, MA, USA
- Department of Epidemiology and Biostatistics, School of Public Health, University of Illinois Chicago, Chicago, IL, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Nora Franceschini
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tamar Sofer
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- CardioVascular Institute (CVI), Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
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6
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Stoneman HR, Price AM, Trout NS, Lamont R, Tifour S, Pozdeyev N, Crooks K, Lin M, Rafaels N, Gignoux CR, Marker KM, Hendricks AE. Characterizing substructure via mixture modeling in large-scale genetic summary statistics. Am J Hum Genet 2025; 112:235-253. [PMID: 39824191 PMCID: PMC11866976 DOI: 10.1016/j.ajhg.2024.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 12/09/2024] [Accepted: 12/09/2024] [Indexed: 01/20/2025] Open
Abstract
Genetic summary data are broadly accessible and highly useful, including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into summary data, such as allele frequencies, masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted-for substructure limits summary data usability, especially for understudied or admixed populations. There is a need for methods to enable the harmonization of summary data where the underlying substructure is matched between datasets. Here, we present Summix2, a comprehensive set of methods and software based on a computationally efficient mixture model to enable the harmonization of genetic summary data by estimating and adjusting for substructure. In extensive simulations and application to public data, we show that Summix2 characterizes finer-scale population structure, identifies ascertainment bias, and scans for potential regions of selection due to local substructure deviation. Summix2 increases the robust use of diverse, publicly available summary data, resulting in improved and more equitable research.
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Affiliation(s)
- Hayley R Stoneman
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Adelle M Price
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Nikole Scribner Trout
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Riley Lamont
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Souha Tifour
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Nikita Pozdeyev
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Kristy Crooks
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Meng Lin
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Nicholas Rafaels
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Christopher R Gignoux
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Katie M Marker
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Audrey E Hendricks
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA; Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
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7
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Haglund A, Zuber V, Abouzeid M, Yang Y, Ko JH, Wiemann L, Otero-Jimenez M, Muhammed L, Feleke R, Nott A, Mills JD, Laaniste L, Gveric DO, Clode D, Babtie AC, Pagni S, Bellampalli R, Somani A, McDade K, Anink JJ, Mesarosova L, Fancy N, Willumsen N, Smith A, Jackson J, Alegre-Abarrategui J, Aronica E, Matthews PM, Thom M, Sisodiya SM, Srivastava PK, Malhotra D, Bryois J, Bottolo L, Johnson MR. Cell state-dependent allelic effects and contextual Mendelian randomization analysis for human brain phenotypes. Nat Genet 2025; 57:358-368. [PMID: 39794547 PMCID: PMC11821528 DOI: 10.1038/s41588-024-02050-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 12/04/2024] [Indexed: 01/13/2025]
Abstract
Gene expression quantitative trait loci are widely used to infer relationships between genes and central nervous system (CNS) phenotypes; however, the effect of brain disease on these inferences is unclear. Using 2,348,438 single-nuclei profiles from 391 disease-case and control brains, we report 13,939 genes whose expression correlated with genetic variation, of which 16.7-40.8% (depending on cell type) showed disease-dependent allelic effects. Across 501 colocalizations for 30 CNS traits, 23.6% had a disease dependency, even after adjusting for disease status. To estimate the unconfounded effect of genes on outcomes, we repeated the analysis using nondiseased brains (n = 183) and reported an additional 91 colocalizations not present in the larger mixed disease and control dataset, demonstrating enhanced interpretation of disease-associated variants. Principled implementation of single-cell Mendelian randomization in control-only brains identified 140 putatively causal gene-trait associations, of which 11 were replicated in the UK Biobank, prioritizing candidate peripheral biomarkers predictive of CNS outcomes.
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Grants
- MR/W029790/1 RCUK | Medical Research Council (MRC)
- MR/S02638X/1 RCUK | Medical Research Council (MRC)
- MR/W029790/1) RCUK | Medical Research Council (MRC)
- EP/N510129/1 RCUK | Engineering and Physical Sciences Research Council (EPSRC)
- DH | National Institute for Health Research (NIHR)
- Brain tissue samples and associated clinical and neuropathological data were supplied by the Parkinson’s UK Brain Bank at Imperial, funded by Parkinson’s UK, a charity registered in England and Wales (258197) and in Scotland (SC037554); the Oxford Brain Bank, supported by the Medical Research Council (MRC), Brains for Dementia Research (BDR) (Alzheimer Society and Alzheimer Research UK), Autistica UK and the NIHR Oxford Biomedical Research Centre; the Edinburgh Brain Bank supported by the MRC; and the Amsterdam Medical Centre Brain Bank. In addition, we also acknowledge the support of the Epilepsy Society from the Department of Health’s NIHR Biomedical Research Centres funding scheme.
- UK Dementia Research Institute, which receives its funding from UK DRI Ltd, funded by the UK MRC, Alzheimer’s Society, and Alzheimer’s Research UK
- Epilepsy Society UK
- Brain tissue samples and associated clinical and neuropathological data were supplied by the Parkinson’s UK Brain Bank at Imperial, funded by Parkinson’s UK, a charity registered in England and Wales (258197) and in Scotland (SC037554);
- UK Dementia Research Institute, which receives its funding from UK DRI Ltd, funded by the UK MRC, Alzheimer’s Society, and Alzheimer’s Research UK.
- Alan Turing Institute
- Alan Turing institute under UKRI EPSRC (EP/N510129/1) and Marmaduke Sheild Fund.
- the Edinburgh Brain Bank supported by the MRC
- Amsterdam Medical Centre Brain Bank
- Epilepsy Society from the Department of Health’s NIHR Biomedical Research Centres funding scheme.
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Affiliation(s)
- Alexander Haglund
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Verena Zuber
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College, Imperial College London, London, UK
| | - Maya Abouzeid
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Yifei Yang
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Jeong Hun Ko
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Liv Wiemann
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Maria Otero-Jimenez
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Louwai Muhammed
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Rahel Feleke
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Alexi Nott
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College, Imperial College London, London, UK
| | - James D Mills
- Departments of Neuropathology and Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
- Amsterdam UMC, University of Amsterdam, Department of (Neuro)pathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Liisi Laaniste
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Djordje O Gveric
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Daniel Clode
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Ann C Babtie
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Susanna Pagni
- Departments of Neuropathology and Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Ravishankara Bellampalli
- Departments of Neuropathology and Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Alyma Somani
- Departments of Neuropathology and Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Karina McDade
- Department of Neuropathology, University of Edinburgh, Edinburgh, UK
| | - Jasper J Anink
- Amsterdam UMC, University of Amsterdam, Department of (Neuro)pathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Lucia Mesarosova
- Amsterdam UMC, University of Amsterdam, Department of (Neuro)pathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Nurun Fancy
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College, Imperial College London, London, UK
| | - Nanet Willumsen
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College, Imperial College London, London, UK
| | - Amy Smith
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College, Imperial College London, London, UK
| | - Johanna Jackson
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College, Imperial College London, London, UK
| | | | - Eleonora Aronica
- Amsterdam UMC, University of Amsterdam, Department of (Neuro)pathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands
| | - Paul M Matthews
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College, Imperial College London, London, UK
| | - Maria Thom
- Departments of Neuropathology and Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Sanjay M Sisodiya
- Departments of Neuropathology and Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | | | - Dheeraj Malhotra
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases Research, Roche Innovation Center, Basel, Switzerland
- MS Research Unit, Biogen, Cambridge, MA, USA
| | - Julien Bryois
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases Research, Roche Innovation Center, Basel, Switzerland
| | - Leonardo Bottolo
- Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Alan Turing Institute, London, UK.
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
| | - Michael R Johnson
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK.
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8
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Hoang Nguyen KH, Le NV, Nguyen PH, Nguyen HHT, Hoang DM, Huynh CD. Human immune system: Exploring diversity across individuals and populations. Heliyon 2025; 11:e41836. [PMID: 39911431 PMCID: PMC11795082 DOI: 10.1016/j.heliyon.2025.e41836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2024] [Revised: 12/23/2024] [Accepted: 01/08/2025] [Indexed: 02/07/2025] Open
Abstract
The immune response is an intricate system that involves the complex connection of cellular and molecular components, each with distinct functional specialisations. It has a distinct capacity to adjust and mould the immune response in accordance with specific stimuli, influenced by both genetic and environmental factors. The presence of genetic diversity, particularly across different ethnic and racial groups, significantly contributes to the impact of incidence of diseases, disease susceptibility, autoimmune disorders, and cancer risks in specific regions and certain populations. Environmental factors, including geography and socioeconomic status, further modulate the variety of the immune system responses. These, in turn, affect the susceptibility to infectious diseases and development of autoimmune disorders. Despite the complexity of the relationship, there remains a gap in understanding the specificity of immune indices across races, immune reference ranges among populations, highlighting the need for deeper understanding of immune diversity for personalized approaches in diagnostics and therapeutics. This review systematically organizes these findings, with the goal of emphasizing the potential of targeted interventions to address health disparities and advance translational research, enabling a more comprehensive strategy. This approach promises significant advancements in identifying specific immunological conditions, focusing on personalized interventions, through both genetic and environmental factors.
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Affiliation(s)
| | - Nghi Vinh Le
- College of Health Sciences, VinUniversity, Hanoi, Viet Nam
| | | | - Hien Hau Thi Nguyen
- College of Health Sciences, VinUniversity, Hanoi, Viet Nam
- Institute of Research and Development, Duy Tan University, Da Nang, Viet Nam
- School of Medicine and Pharmacy, Duy Tan University, Da Nang, Viet Nam
| | - Duy Mai Hoang
- College of Health Sciences, VinUniversity, Hanoi, Viet Nam
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9
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Liu T, Li K, Wang Y, Li H, Zhao H. Evaluating the Utilities of Foundation Models in Single-cell Data Analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.08.555192. [PMID: 38464157 PMCID: PMC10925156 DOI: 10.1101/2023.09.08.555192] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Foundation Models (FMs) have made significant strides in both industrial and scientific domains. In this paper, we evaluate the performance of FMs for single-cell sequencing data analysis through comprehensive experiments across eight downstream tasks pertinent to single-cell data. Overall, the top FMs include scGPT, Geneformer, and CellPLM by considering model performances and user accessibility among ten single-cell FMs. However, by comparing these FMs with task-specific methods, we found that single-cell FMs may not consistently excel than task-specific methods in all tasks, which challenges the necessity of developing foundation models for single-cell analysis. In addition, we evaluated the effects of hyper-parameters, initial settings, and stability for training single-cell FMs based on a proposed scEval framework, and provide guidelines for pre-training and fine-tuning, to enhance the performances of single-cell FMs. Our work summarizes the current state of single-cell FMs, points to their constraints and avenues for future development, and offers a freely available evaluation pipeline to benchmark new models and improve method development.
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10
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Zhou Y, Song L, Li H. Full-resolution HLA and KIR gene annotations for human genome assemblies. Genome Res 2024; 34:1931-1941. [PMID: 38839374 PMCID: PMC11610593 DOI: 10.1101/gr.278985.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 05/22/2024] [Indexed: 06/07/2024]
Abstract
The human leukocyte antigen (HLA) genes and the killer cell immunoglobulin-like receptor (KIR) genes are critical to immune responses and are associated with many immune-related diseases. Located in highly polymorphic regions, it is difficult to study them with traditional short-read alignment-based methods. Although modern long-read assemblers can often assemble these genes, using existing tools to annotate HLA and KIR genes in these assemblies remains a nontrivial task. Here, we describe Immuannot, a new computation tool to annotate the gene structures of HLA and KIR genes and to type the allele of each gene. Applying Immuannot to 56 regional and 212 whole-genome assemblies from previous studies, we annotate 9931 HLA and KIR genes and found that almost half of these genes, 4068, have novel sequences compared with the current Immuno Polymorphism Database (IPD). These novel gene sequences are represented by 2664 distinct alleles, some of which contained nonsynonymous variations, resulting in 92 novel protein sequences. We demonstrate the complex haplotype structures at the two loci and report the linkage between HLA/KIR haplotypes and gene alleles. We anticipate that Immuannot will speed up the discovery of new HLA/KIR alleles and enable the association of HLA/KIR haplotype structures with clinical outcomes in the future.
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Affiliation(s)
- Ying Zhou
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts 02115, USA
| | - Li Song
- Department of Biomedical Data Science, Dartmouth College, Hanover, New Hampshire 03755, USA
| | - Heng Li
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts 02115, USA;
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02115, USA
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11
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Arron HE, Marsh BD, Kell DB, Khan MA, Jaeger BR, Pretorius E. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: the biology of a neglected disease. Front Immunol 2024; 15:1386607. [PMID: 38887284 PMCID: PMC11180809 DOI: 10.3389/fimmu.2024.1386607] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 04/11/2024] [Indexed: 06/20/2024] Open
Abstract
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic, debilitating disease characterised by a wide range of symptoms that severely impact all aspects of life. Despite its significant prevalence, ME/CFS remains one of the most understudied and misunderstood conditions in modern medicine. ME/CFS lacks standardised diagnostic criteria owing to variations in both inclusion and exclusion criteria across different diagnostic guidelines, and furthermore, there are currently no effective treatments available. Moving beyond the traditional fragmented perspectives that have limited our understanding and management of the disease, our analysis of current information on ME/CFS represents a significant paradigm shift by synthesising the disease's multifactorial origins into a cohesive model. We discuss how ME/CFS emerges from an intricate web of genetic vulnerabilities and environmental triggers, notably viral infections, leading to a complex series of pathological responses including immune dysregulation, chronic inflammation, gut dysbiosis, and metabolic disturbances. This comprehensive model not only advances our understanding of ME/CFS's pathophysiology but also opens new avenues for research and potential therapeutic strategies. By integrating these disparate elements, our work emphasises the necessity of a holistic approach to diagnosing, researching, and treating ME/CFS, urging the scientific community to reconsider the disease's complexity and the multifaceted approach required for its study and management.
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Affiliation(s)
- Hayley E. Arron
- Department of Physiological Sciences, Faculty of Science, Stellenbosch University, Stellenbosch, South Africa
| | - Benjamin D. Marsh
- MRCPCH Consultant Paediatric Neurodisability, Exeter, Devon, United Kingdom
| | - Douglas B. Kell
- Department of Physiological Sciences, Faculty of Science, Stellenbosch University, Stellenbosch, South Africa
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, United Kingdom
- The Novo Nordisk Foundation Centre for Biosustainability, Technical University of Denmark, Lyngby, Denmark
| | - M. Asad Khan
- Directorate of Respiratory Medicine, Manchester University Hospitals, Wythenshawe Hospital, Manchester, United Kingdom
| | - Beate R. Jaeger
- Long COVID department, Clinic St Georg, Bad Aibling, Germany
| | - Etheresia Pretorius
- Department of Physiological Sciences, Faculty of Science, Stellenbosch University, Stellenbosch, South Africa
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, United Kingdom
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12
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Sanchez-Mazas A, Nunes JM. The most frequent HLA alleles around the world: A fundamental synopsis. Best Pract Res Clin Haematol 2024; 37:101559. [PMID: 39098805 DOI: 10.1016/j.beha.2024.101559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 06/10/2024] [Accepted: 06/27/2024] [Indexed: 08/06/2024]
Abstract
A comprehensive knowledge of human leukocyte antigen (HLA) molecular variation worldwide is essential in human population genetics research and disease association studies and is also indispensable for clinical applications such as allogeneic hematopoietic cell transplantation, where ensuring HLA compatibility between donors and recipients is paramount. Enormous progress has been made in this field thanks to several decades of HLA population studies allowing the development of helpful databases and bioinformatics tools. However, it is still difficult to appraise the global HLA population diversity in a synthetic way. We thus introduce here a novel approach, based on approximately 2000 data sets, to assess this complexity by providing a fundamental synopsis of the most frequent HLA alleles observed in different regions of the world. This new knowledge will be useful not only as a fundamental reference for basic research, but also as an efficient guide for clinicians working in the field of transplantation.
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Affiliation(s)
- Alicia Sanchez-Mazas
- Laboratory of Anthropology, Genetics and Peopling History (AGP), Department of Genetics and Evolution & Institute of Genetics and Genomics in Geneva (IGE3), University of Geneva, 30 Quai Ernest-Ansermet, 1205, Geneva, Switzerland.
| | - José Manuel Nunes
- Laboratory of Anthropology, Genetics and Peopling History (AGP), Department of Genetics and Evolution & Institute of Genetics and Genomics in Geneva (IGE3), University of Geneva, 30 Quai Ernest-Ansermet, 1205, Geneva, Switzerland.
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13
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Stoneman HR, Price A, Trout NS, Lamont R, Tifour S, Pozdeyev N, Crooks K, Lin M, Rafaels N, Gignoux CR, Marker KM, Hendricks AE. Characterizing substructure via mixture modeling in large-scale genetic summary statistics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.29.577805. [PMID: 38766180 PMCID: PMC11100604 DOI: 10.1101/2024.01.29.577805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Genetic summary data are broadly accessible and highly useful including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into groups masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted substructure limits summary data usability, especially for understudied or admixed populations. Here, we present Summix2, a comprehensive set of methods and software based on a computationally efficient mixture model to estimate and adjust for substructure in genetic summary data. In extensive simulations and application to public data, Summix2 characterizes finer-scale population structure, identifies ascertainment bias, and identifies potential regions of selection due to local substructure deviation. Summix2 increases the robust use of diverse publicly available summary data resulting in improved and more equitable research.
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Affiliation(s)
- Hayley R Stoneman
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Adelle Price
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Nikole Scribner Trout
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Riley Lamont
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Souha Tifour
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Nikita Pozdeyev
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Kristy Crooks
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Department of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Meng Lin
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Nicholas Rafaels
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Christopher R Gignoux
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Katie M Marker
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Audrey E Hendricks
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
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14
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Gil-Etayo FJ, Arroyo-Sánchez D, Niño Ramírez JE, Vicente Parra A, Tejeda Velarde A. Two new HLA-DQB1*03:02:01 variants with substitutions in intron 2: HLA-DQB1*03:02:01:19 and -DQB1*03:02:01:21. HLA 2024; 103:e15492. [PMID: 38706128 DOI: 10.1111/tan.15492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 04/06/2024] [Accepted: 04/09/2024] [Indexed: 05/07/2024]
Abstract
Two different single nucleotide substitutions in intron 2 give rise to novel HLA-DQB1*03:02:01 alleles.
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Affiliation(s)
- Francisco Javier Gil-Etayo
- Laboratorio de HLA-Biología Molecular, Servicio de Hematología, Hospital Universitario de Salamanca, Salamanca, Spain
- Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
| | - Daniel Arroyo-Sánchez
- Laboratorio de HLA-Biología Molecular, Servicio de Hematología, Hospital Universitario de Salamanca, Salamanca, Spain
| | - Jairo Eduardo Niño Ramírez
- Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
- Universidad de Salamanca (USAL), Salamanca, Spain
| | - Ariadna Vicente Parra
- Laboratorio de HLA-Biología Molecular, Servicio de Hematología, Hospital Universitario de Salamanca, Salamanca, Spain
| | - Amalia Tejeda Velarde
- Laboratorio de HLA-Biología Molecular, Servicio de Hematología, Hospital Universitario de Salamanca, Salamanca, Spain
- Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
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15
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Hayeck TJ, Li Y, Mosbruger TL, Bradfield JP, Gleason AG, Damianos G, Shaw GTW, Duke JL, Conlin LK, Turner TN, Fernández-Viña MA, Sarmady M, Monos DS. The Impact of Patterns in Linkage Disequilibrium and Sequencing Quality on the Imprint of Balancing Selection. Genome Biol Evol 2024; 16:evae009. [PMID: 38302106 PMCID: PMC10853003 DOI: 10.1093/gbe/evae009] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 01/08/2024] [Accepted: 01/12/2024] [Indexed: 02/03/2024] Open
Abstract
Regions under balancing selection are characterized by dense polymorphisms and multiple persistent haplotypes, along with other sequence complexities. Successful identification of these patterns depends on both the statistical approach and the quality of sequencing. To address this challenge, at first, a new statistical method called LD-ABF was developed, employing efficient Bayesian techniques to effectively test for balancing selection. LD-ABF demonstrated the most robust detection of selection in a variety of simulation scenarios, compared against a range of existing tests/tools (Tajima's D, HKA, Dng, BetaScan, and BalLerMix). Furthermore, the impact of the quality of sequencing on detection of balancing selection was explored, as well, using: (i) SNP genotyping and exome data, (ii) targeted high-resolution HLA genotyping (IHIW), and (iii) whole-genome long-read sequencing data (Pangenome). In the analysis of SNP genotyping and exome data, we identified known targets and 38 new selection signatures in genes not previously linked to balancing selection. To further investigate the impact of sequencing quality on detection of balancing selection, a detailed investigation of the MHC was performed with high-resolution HLA typing data. Higher quality sequencing revealed the HLA-DQ genes consistently demonstrated strong selection signatures otherwise not observed from the sparser SNP array and exome data. The HLA-DQ selection signature was also replicated in the Pangenome samples using considerably less samples but, with high-quality long-read sequence data. The improved statistical method, coupled with higher quality sequencing, leads to more consistent identification of selection and enhanced localization of variants under selection, particularly in complex regions.
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Affiliation(s)
- Tristan J Hayeck
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yang Li
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy L Mosbruger
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Adam G Gleason
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - George Damianos
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Grace Tzun-Wen Shaw
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jamie L Duke
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Laura K Conlin
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Tychele N Turner
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Marcelo A Fernández-Viña
- Department of Pathology, Stanford University School of Medicine, Palo Alto, CA, USA
- Histocompatibility and Immunogenetics Laboratory, Stanford Blood Center, Palo Alto, CA, USA
| | - Mahdi Sarmady
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dimitri S Monos
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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16
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Pagliuca S, Ferraro F. Immune-driven clonal cell selection at the intersection among cancer, infections, autoimmunity and senescence. Semin Hematol 2024; 61:22-34. [PMID: 38341340 DOI: 10.1053/j.seminhematol.2024.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Revised: 12/14/2023] [Accepted: 01/02/2024] [Indexed: 02/12/2024]
Abstract
Immune surveillance mechanisms play a crucial role in maintaining lifelong immune homeostasis in response to pathologic stimuli and aberrant cell states. However, their persistence, especially in the context of chronic antigenic exposure, can create a fertile ground for immune evasion. These escaping cell phenotypes, harboring a variety of genomic and transcriptomic aberrances, chiefly in human leukocyte antigen (HLA) and antigen presentation machinery genes, may survive and proliferate, featuring a scenario of clonal cell expansion with immune failure characteristics. While well characterized in solid and, to some extent, hematological malignancies, little is known about their occurrence and significance in other disease contexts. Historical literature highlights the role for escaping HLA-mediated recognition as a strategy adopted by virus to evade from the immune system, hinting at the potential for immune aberrant cell expansion in the context of chronic infections. Additionally, unmasked in idiopathic aplastic anemia as a mechanism able to rescue failing hematopoiesis, HLA clonal escape may operate in autoimmune disorders, particularly in tissues targeted by aberrant immune responses. Furthermore, senescent cell status emerging as immunogenic phenotypes stimulating T cell responses, may act as a bottleneck for the selection of such immune escaping clones, blurring the boundaries between neoplastic transformation, aging and inflammation. Here we provide a fresh overview and perspective on this immune-driven clonal cell expansion, linking pathophysiological features of neoplastic, autoimmune, infectious and senescence processes exposed to immune surveillance.
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Affiliation(s)
- Simona Pagliuca
- Hematology Department, Nancy University Hospital and UMR7365, IMoPA, University of Lorraine, Vandoeuvre-lès-Nancy, France.
| | - Francesca Ferraro
- Division of Oncology, Department of Internal Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO
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17
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Zhou Y, Song L, Li H. Full resolution HLA and KIR genes annotation for human genome assemblies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.20.576452. [PMID: 38328160 PMCID: PMC10849470 DOI: 10.1101/2024.01.20.576452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
The HLA (Human Leukocyte Antigen) genes and the KIR (Killer cell Immunoglobulin-like Receptor) genes are critical to immune responses and are associated with many immune-related diseases. Located in highly polymorphic regions, they are hard to be studied with traditional short-read alignment-based methods. Although modern long-read assemblers can often assemble these genes, using existing tools to annotate HLA and KIR genes in these assemblies remains a non-trivial task. Here, we describe Immuannot, a new computation tool to annotate the gene structures of HLA and KIR genes and to type the allele of each gene. Applying Immuannot to 56 regional and 212 whole-genome assemblies from previous studies, we annotated 9,931 HLA and KIR genes and found that almost half of these genes, 4,068, had novel sequences compared to the current Immuno Polymorphism Database (IPD). These novel gene sequences were represented by 2,664 distinct alleles, some of which contained non-synonymous variations resulting in 92 novel protein sequences. We demonstrated the complex haplotype structures at the two loci and reported the linkage between HLA/KIR haplotypes and gene alleles. We anticipate that Immuannot will speed up the discovery of new HLA/KIR alleles and enable the association of HLA/KIR haplotype structures with clinical outcomes in the future.
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Affiliation(s)
- Ying Zhou
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02115, USA
| | - Li Song
- Department of Biomedical Data Science, Dartmouth College, Hanover, NH, 03755, USA
| | - Heng Li
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
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18
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Lenz TL. HLA Genes: A Hallmark of Functional Genetic Variation and Complex Evolution. Methods Mol Biol 2024; 2809:1-18. [PMID: 38907887 DOI: 10.1007/978-1-0716-3874-3_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/24/2024]
Abstract
The major histocompatibility complex (MHC) with its highly polymorphic HLA genes represents one of the most intensely studied genomic regions in the genome. MHC proteins play a key role in antigen-specific immunity and are associated with a wide range of complex diseases. Despite decades of research and many advances in the field, the characterization and interpretation of its genetic and genomic variability remain challenging. Here an overview is provided of the MHC, the nature of its exceptional variability, and the complex evolutionary processes assumed to drive this variability. Highlighted are also recent advances in the field that promise to improve our understanding of the variability in the MHC and in antigen-specific immunity more generally.
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Affiliation(s)
- Tobias L Lenz
- Research Unit for Evolutionary Immunogenomics, Department of Biology, University of Hamburg, Hamburg, Germany.
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19
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Malas N, Kochaji C, Soukkarieh C, Almonakel MB, Alzoubi H. Association of Dental Caries in Primary Teeth With HLA Class II Gene Among Syrian Children. Cureus 2024; 16:e53081. [PMID: 38414691 PMCID: PMC10897358 DOI: 10.7759/cureus.53081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/27/2024] [Indexed: 02/29/2024] Open
Abstract
Background and objectives Numerous studies have shown that there is evidence that genetic factors contribute in different ways to the occurrence of caries lesions, and the multiple differences in the human leucocytes antigen (HLA) gene patterns play an important role in the body's immune response. Therefore, this study aimed to evaluate the association between some HLA class II alleles (HLA-DR4, HLA-DQ2, HLA-DQ4) and early childhood caries (ECC) occurrence in Syrian children. Materials and methods The study included 80 children aged three to six, divided into two groups: Group 1 (n = 40) being severe early childhood caries (S-ECC) children (deft ≥ 10) and Group 2 (n = 40) being free caries children (deft = 0). The genomic DNAs were extracted and collected by taking a buccal swab using a sterile metal strip and were amplified by polymerase chain reaction-single specific primer (PCR-SSP) and then HLA-typing was performed for all alleles. Results There were no statistically significant differences in the frequency of occurrence of S-ECC, HLA-DR4, and HLA-DQ2 alleles (p = 0.626, 0.256 respectively), while the incidence of S-ECC was associated with the DQ4 allele (p = 0.012). Conclusion HLA class II molecules may play a crucial role in predisposing to ECC, since positive HLA-DQ4 may enhance the chance of developing ECC. However, no association were found between (HLA-DR4 and HLA-DQ2) and ECC.
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Affiliation(s)
- Nassouh Malas
- Pediatric Dentistry, Damascus University, Damascus, SYR
| | - Chaza Kochaji
- Pediatric Dentistry, Damascus University, Damascus, SYR
| | | | | | - Hasan Alzoubi
- Pediatric Dentistry, Damascus University, Damascus, SYR
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20
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Kang JB, Shen AZ, Gurajala S, Nathan A, Rumker L, Aguiar VRC, Valencia C, Lagattuta KA, Zhang F, Jonsson AH, Yazar S, Alquicira-Hernandez J, Khalili H, Ananthakrishnan AN, Jagadeesh K, Dey K, Daly MJ, Xavier RJ, Donlin LT, Anolik JH, Powell JE, Rao DA, Brenner MB, Gutierrez-Arcelus M, Luo Y, Sakaue S, Raychaudhuri S. Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution. Nat Genet 2023; 55:2255-2268. [PMID: 38036787 PMCID: PMC10787945 DOI: 10.1038/s41588-023-01586-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 10/19/2023] [Indexed: 12/02/2023]
Abstract
The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.
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Affiliation(s)
- Joyce B Kang
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Amber Z Shen
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Saisriram Gurajala
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Aparna Nathan
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Laurie Rumker
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Vitor R C Aguiar
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Cristian Valencia
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Kaitlyn A Lagattuta
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology and the Center for Health Artificial Intelligence, University of Colorado School of Medicine, Aurora, CO, USA
| | - Anna Helena Jonsson
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Seyhan Yazar
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | | | - Hamed Khalili
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ashwin N Ananthakrishnan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Kushal Dey
- Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Physiology, Biophysics and Systems Biology Program, Weill Cornell Medicine, New York, NY, USA
| | - Mark J Daly
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ramnik J Xavier
- Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Laura T Donlin
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Jennifer H Anolik
- Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA
| | - Joseph E Powell
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Deepak A Rao
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael B Brenner
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Maria Gutierrez-Arcelus
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yang Luo
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Saori Sakaue
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA.
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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21
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Fu ZH, He SZ, Wu Y, Zhao GR. Design and deep learning of synthetic B-cell-specific promoters. Nucleic Acids Res 2023; 51:11967-11979. [PMID: 37889080 PMCID: PMC10681721 DOI: 10.1093/nar/gkad930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 09/20/2023] [Accepted: 10/10/2023] [Indexed: 10/28/2023] Open
Abstract
Synthetic biology and deep learning synergistically revolutionize our ability for decoding and recoding DNA regulatory grammar. The B-cell-specific transcriptional regulation is intricate, and unlock the potential of B-cell-specific promoters as synthetic elements is important for B-cell engineering. Here, we designed and pooled synthesized 23 640 B-cell-specific promoters that exhibit larger sequence space, B-cell-specific expression, and enable diverse transcriptional patterns in B-cells. By MPRA (Massively parallel reporter assays), we deciphered the sequence features that regulate promoter transcriptional, including motifs and motif syntax (their combination and distance). Finally, we built and trained a deep learning model capable of predicting the transcriptional strength of the immunoglobulin V gene promoter directly from sequence. Prediction of thousands of promoter variants identified in the global human population shows that polymorphisms in promoters influence the transcription of immunoglobulin V genes, which may contribute to individual differences in adaptive humoral immune responses. Our work helps to decipher the transcription mechanism in immunoglobulin genes and offers thousands of non-similar promoters for B-cell engineering.
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Affiliation(s)
- Zong-Heng Fu
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin 300072, China
| | - Si-Zhe He
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin 300072, China
| | - Yi Wu
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin 300072, China
| | - Guang-Rong Zhao
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin 300072, China
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22
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Redruello-Romero A, Benitez-Cantos MS, Lopez-Perez D, García-Rubio J, Tamayo F, Pérez-Bartivas D, Moreno-SanJuan S, Ruiz-Palmero I, Puentes-Pardo JD, Vilchez JR, López-Nevot MÁ, García F, Cano C, León J, Carazo Á. Human adipose tissue as a major reservoir of cytomegalovirus-reactive T cells. Front Immunol 2023; 14:1303724. [PMID: 38053998 PMCID: PMC10694288 DOI: 10.3389/fimmu.2023.1303724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 11/01/2023] [Indexed: 12/07/2023] Open
Abstract
Introduction Cytomegalovirus (CMV) is a common herpesvirus with a high prevalence worldwide. After the acute infection phase, CMV can remain latent in several tissues. CD8 T cells in the lungs and salivary glands mainly control its reactivation control. White adipose tissue (WAT) contains a significant population of memory T cells reactive to viral antigens, but CMV specificity has mainly been studied in mouse WAT. Therefore, we obtained blood, omental WAT (oWAT), subcutaneous WAT (sWAT), and liver samples from 11 obese donors to characterize the human WAT adaptive immune landscape from a phenotypic and immune receptor specificity perspective. Methods We performed high-throughput sequencing of the T cell receptor (TCR) locus to analyze tissue and blood TCR repertoires of the 11 donors. The presence of TCRs specific to CMV epitopes was tested through ELISpot assays. Moreover, phenotypic characterization of T cells was carried out through flow cytometry. Results High-throughput sequencing analyses revealed that tissue TCR repertoires in oWAT, sWAT, and liver samples were less diverse and dominated by hyperexpanded clones when compared to blood samples. Additionally, we predicted the presence of TCRs specific to viral epitopes, particularly from CMV, which was confirmed by ELISpot assays. Remarkably, we found that oWAT has a higher proportion of CMV-reactive T cells than blood or sWAT. Finally, flow cytometry analyses indicated that most WAT-infiltrated lymphocytes were tissue-resident effector memory CD8 T cells. Discussion Overall, these findings postulate human oWAT as a major reservoir of CMV-specific T cells, presumably for latent viral reactivation control. This study enhances our understanding of the adaptive immune response in human WAT and highlights its potential role in antiviral defense.
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Affiliation(s)
| | - Maria S. Benitez-Cantos
- Research Unit, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
- Department of Biochemistry and Molecular Biology III and Immunology, Faculty of Medicine, University of Granada, Granada, Spain
- GENYO, Centre for Genomics and Oncological Research: Pfizer/University of Granada/Andalusian Regional Government, Granada, Spain
| | - David Lopez-Perez
- Research Unit, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
- Department of Pharmacology, Faculty of Pharmacy, University of Granada, Granada, Spain
| | | | | | - Daniel Pérez-Bartivas
- Research Unit, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
| | - Sara Moreno-SanJuan
- Research Unit, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
- Cytometry and Microscopy Research Service, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
| | - Isabel Ruiz-Palmero
- Research Unit, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
| | - Jose D. Puentes-Pardo
- Research Unit, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
- Department of Pharmacology, Faculty of Pharmacy, University of Granada, Granada, Spain
| | - Jose R. Vilchez
- Research Unit, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
- Clinical Analyses and Immunology Unit, Virgen de las Nieves University Hospital, Granada, Spain
| | - Miguel Á. López-Nevot
- Research Unit, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
- Department of Biochemistry and Molecular Biology III and Immunology, Faculty of Medicine, University of Granada, Granada, Spain
- Clinical Analyses and Immunology Unit, Virgen de las Nieves University Hospital, Granada, Spain
| | - Federico García
- Research Unit, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
- Clinical Microbiology Unit, San Cecilio University Hospital, Granada, Spain
- Centro de Investigación Biomédica en Red (CIBER) of Infectious Diseases, Health Institute Carlos III, Madrid, Spain
| | - Carlos Cano
- Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
| | - Josefa León
- Research Unit, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
- Digestive Unit, San Cecilio University Hospital, Granada, Spain
| | - Ángel Carazo
- Research Unit, Biosanitary Research Institute of Granada (ibs.GRANADA), Granada, Spain
- Clinical Microbiology Unit, San Cecilio University Hospital, Granada, Spain
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23
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Goovaerts S, Hoskens H, Eller RJ, Herrick N, Musolf AM, Justice CM, Yuan M, Naqvi S, Lee MK, Vandermeulen D, Szabo-Rogers HL, Romitti PA, Boyadjiev SA, Marazita ML, Shaffer JR, Shriver MD, Wysocka J, Walsh S, Weinberg SM, Claes P. Joint multi-ancestry and admixed GWAS reveals the complex genetics behind human cranial vault shape. Nat Commun 2023; 14:7436. [PMID: 37973980 PMCID: PMC10654897 DOI: 10.1038/s41467-023-43237-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 11/01/2023] [Indexed: 11/19/2023] Open
Abstract
The cranial vault in humans is highly variable, clinically relevant, and heritable, yet its genetic architecture remains poorly understood. Here, we conduct a joint multi-ancestry and admixed multivariate genome-wide association study on 3D cranial vault shape extracted from magnetic resonance images of 6772 children from the ABCD study cohort yielding 30 genome-wide significant loci. Follow-up analyses indicate that these loci overlap with genomic risk loci for sagittal craniosynostosis, show elevated activity cranial neural crest cells, are enriched for processes related to skeletal development, and are shared with the face and brain. We present supporting evidence of regional localization for several of the identified genes based on expression patterns in the cranial vault bones of E15.5 mice. Overall, our study provides a comprehensive overview of the genetics underlying normal-range cranial vault shape and its relevance for understanding modern human craniofacial diversity and the etiology of congenital malformations.
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Affiliation(s)
- Seppe Goovaerts
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium.
| | - Hanne Hoskens
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Ryan J Eller
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Noah Herrick
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Anthony M Musolf
- Statistical Genetics Section, Computational and Statistical Genomics Branch, NHGRI, NIH, MD, Baltimore, USA
| | - Cristina M Justice
- Genometrics Section, Computational and Statistical Genomics Branch, Division of Intramural Research, NHGRI, NIH, Baltimore, MD, USA
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Meng Yuan
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Departments of Genetics and Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Myoung Keun Lee
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dirk Vandermeulen
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Heather L Szabo-Rogers
- Department of Anatomy, Physiology and Pharmacology, University of Saskatchewan, Saskatchewan, Canada
| | - Paul A Romitti
- Department of Epidemiology, College of Public Health, The University of Iowa, Iowa City, IA, USA
| | - Simeon A Boyadjiev
- Department of Pediatrics, University of California Davis, Sacramento, CA, USA
| | - Mary L Marazita
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - John R Shaffer
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mark D Shriver
- Department of Anthropology, Pennsylvania State University, State College, PA, USA
| | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Susan Walsh
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Seth M Weinberg
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Anthropology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium.
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium.
- Murdoch Children's Research Institute, Melbourne, VIC, Australia.
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24
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Liu H, Huang L, Li L, Lu T, Liang H, Liu C. HLA-DQ and alcohol in the pathogenesis of irritable bowel syndrome in college students: a case-control study. Sci Rep 2023; 13:13023. [PMID: 37563425 PMCID: PMC10415344 DOI: 10.1038/s41598-023-40295-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 08/08/2023] [Indexed: 08/12/2023] Open
Abstract
Some researchers have shown that genetics contribute to the incidence of IBS. However, no research has focused on the interaction between HLA-DQ and living habits in the pathogenesis of IBS. The present study explored the risk factors for IBS in college students of Guangxi Han nationality and explored the interaction between HLA-DQ and living habits on the pathogenesis of IBS. Univariate and multivariate analyses were used to determine the risk factors for IBS. Logistic interaction analysis and the Excel table made by Andersson were used to explore the interaction between genes and living habits in the context of IBS. We found that low expression of HLA-DQ2 and DQ8 were associated with the pathogenesis of IBS, while mild to moderate alcohol consumption was associated with the occurrence of IBS symptoms. Only the HLA-DQ8 gene and alcohol consumption had additive interactions in the context of the occurrence of IBS. In other words, for college students of Guangxi Han nationality, HLA-DQ2 and HLA-DQ8 might be protective against IBS, while alcohol consumption might be an independent risk factor. There was an additive interaction between HLA-DQ8 and alcohol consumption in the occurrence of IBS.
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Affiliation(s)
- Huaying Liu
- Department of Medicine, Guangxi Medical College, No 8 Kunlun Road, Nanning, 530023, Guangxi, China
| | - Lan Huang
- Dean's Office of Guangxi Medical College, No 8 Kunlun Road, Nanning, 530023, Guangxi, China
| | - Li Li
- Department of Medicine, Guangxi Medical College, No 8 Kunlun Road, Nanning, 530023, Guangxi, China
| | - Tingting Lu
- Department of Medical Technology, Guangxi Medical College, No 8 Kunlun Road, Nanning, 530023, Guangxi, China
| | - Huiping Liang
- Department of Medicine, Guangxi Medical College, No 8 Kunlun Road, Nanning, 530023, Guangxi, China.
| | - Chunbin Liu
- Department of Internal Medicine, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, 530022, Guangxi, China.
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25
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Vaill M, Kawanishi K, Varki N, Gagneux P, Varki A. Comparative physiological anthropogeny: exploring molecular underpinnings of distinctly human phenotypes. Physiol Rev 2023; 103:2171-2229. [PMID: 36603157 PMCID: PMC10151058 DOI: 10.1152/physrev.00040.2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/26/2022] [Accepted: 12/28/2022] [Indexed: 01/06/2023] Open
Abstract
Anthropogeny is a classic term encompassing transdisciplinary investigations of the origins of the human species. Comparative anthropogeny is a systematic comparison of humans and other living nonhuman hominids (so-called "great apes"), aiming to identify distinctly human features in health and disease, with the overall goal of explaining human origins. We begin with a historical perspective, briefly describing how the field progressed from the earliest evolutionary insights to the current emphasis on in-depth molecular and genomic investigations of "human-specific" biology and an increased appreciation for cultural impacts on human biology. While many such genetic differences between humans and other hominids have been revealed over the last two decades, this information remains insufficient to explain the most distinctive phenotypic traits distinguishing humans from other living hominids. Here we undertake a complementary approach of "comparative physiological anthropogeny," along the lines of the preclinical medical curriculum, i.e., beginning with anatomy and considering each physiological system and in each case considering genetic and molecular components that are relevant. What is ultimately needed is a systematic comparative approach at all levels from molecular to physiological to sociocultural, building networks of related information, drawing inferences, and generating testable hypotheses. The concluding section will touch on distinctive considerations in the study of human evolution, including the importance of gene-culture interactions.
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Affiliation(s)
- Michael Vaill
- Center for Academic Research and Training in Anthropogeny, University of California, San Diego, La Jolla, California
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, California
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, California
| | - Kunio Kawanishi
- Center for Academic Research and Training in Anthropogeny, University of California, San Diego, La Jolla, California
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, California
- Department of Experimental Pathology, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Nissi Varki
- Center for Academic Research and Training in Anthropogeny, University of California, San Diego, La Jolla, California
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, California
- Department of Pathology, University of California, San Diego, La Jolla, California
| | - Pascal Gagneux
- Center for Academic Research and Training in Anthropogeny, University of California, San Diego, La Jolla, California
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, California
- Department of Pathology, University of California, San Diego, La Jolla, California
| | - Ajit Varki
- Center for Academic Research and Training in Anthropogeny, University of California, San Diego, La Jolla, California
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, California
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, California
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26
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Caballero M, Koren A. The landscape of somatic mutations in lymphoblastoid cell lines. CELL GENOMICS 2023; 3:100305. [PMID: 37388907 PMCID: PMC10300552 DOI: 10.1016/j.xgen.2023.100305] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 02/03/2023] [Accepted: 03/28/2023] [Indexed: 07/01/2023]
Abstract
Somatic mutations have important biological ramifications while exerting substantial rate, type, and genomic location heterogeneity. Yet, their sporadic occurrence makes them difficult to study at scale and across individuals. Lymphoblastoid cell lines (LCLs), a model system for human population and functional genomics, harbor large numbers of somatic mutations and have been extensively genotyped. By comparing 1,662 LCLs, we report that the mutational landscape of the genome varies across individuals in terms of the number of mutations, their genomic locations, and their spectra; this variation may itself be modulated by somatic trans-acting mutations. Mutations attributed to the translesion DNA polymerase η follow two different modes of formation, with one mode accounting for the hypermutability of the inactive X chromosome. Nonetheless, the distribution of mutations along the inactive X chromosome appears to follow an epigenetic memory of the active form.
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Affiliation(s)
- Madison Caballero
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Amnon Koren
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
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27
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Palmer WH, Norman PJ. The impact of HLA polymorphism on herpesvirus infection and disease. Immunogenetics 2023; 75:231-247. [PMID: 36595060 PMCID: PMC10205880 DOI: 10.1007/s00251-022-01288-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 11/24/2022] [Indexed: 01/04/2023]
Abstract
Human Leukocyte Antigens (HLA) are cell surface molecules, central in coordinating innate and adaptive immune responses, that are targets of strong diversifying natural selection by pathogens. Of these pathogens, human herpesviruses have a uniquely ancient relationship with our species, where coevolution likely has reciprocating impact on HLA and viral genomic diversity. Consistent with this notion, genetic variation at multiple HLA loci is strongly associated with modulating immunity to herpesvirus infection. Here, we synthesize published genetic associations of HLA with herpesvirus infection and disease, both from case/control and genome-wide association studies. We analyze genetic associations across the eight human herpesviruses and identify HLA alleles that are associated with diverse herpesvirus-related phenotypes. We find that whereas most HLA genetic associations are virus- or disease-specific, HLA-A*01 and HLA-A*02 allotypes may be more generally associated with immune susceptibility and control, respectively, across multiple herpesviruses. Connecting genetic association data with functional corroboration, we discuss mechanisms by which diverse HLA and cognate receptor allotypes direct variable immune responses during herpesvirus infection and pathogenesis. Together, this review examines the complexity of HLA-herpesvirus interactions driven by differential T cell and Natural Killer cell immune responses.
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Affiliation(s)
- William H. Palmer
- Department of Biomedical Informatics, University of Colorado, Aurora, CO USA
- Department of Immunology & Microbiology, University of Colorado, Aurora, CO USA
| | - Paul J. Norman
- Department of Biomedical Informatics, University of Colorado, Aurora, CO USA
- Department of Immunology & Microbiology, University of Colorado, Aurora, CO USA
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28
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Solloch UV, Giani AS, Pattillo Garnham MI, Sauter J, Bernas SN, Lange V, Barriga F, Fernández-Viña MA, Schmidt AH. HLA allele and haplotype frequencies of registered stem cell donors in Chile. Front Immunol 2023; 14:1175135. [PMID: 37313414 PMCID: PMC10258311 DOI: 10.3389/fimmu.2023.1175135] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 05/15/2023] [Indexed: 06/15/2023] Open
Abstract
Patients in need of hematopoietic stem cell transplantation often rely on unrelated stem cell donors matched in certain human leukocyte antigen (HLA) genes. Donor search is complicated by the extensive allelic variability of the HLA system. Therefore, large registries of potential donors are maintained in many countries worldwide. Population-specific HLA characteristics determine the registry benefits for patients and also the need for further regional donor recruitment. In this work, we analyzed HLA allele and haplotype frequencies of donors of DKMS Chile, the first Chilean donor registry, with self-assessed "non-Indigenous" (n=92,788) and "Mapuche" (n=1,993) ancestry. We identified HLA alleles that were distinctly more abundant in the Chilean subpopulations than in worldwide reference populations, four of them particularly characteristic for the Mapuche subpopulation, namely B*39:09g, B*35:09, DRB1*04:07g, and DRB1*16:02g. Both population subsamples carried haplotypes of both Native American and European origin at high frequencies, reflecting Chile's complex history of admixture and immigration. Matching probability analysis revealed limited benefits for Chilean patients (both non-Indigenous and Mapuche) from donor registries of non-Chilean donors, thus indicating a need for ongoing significant donor recruitment efforts in Chile.
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29
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Cotter DJ, Hofgard EF, Novembre J, Szpiech ZA, Rosenberg NA. A rarefaction approach for measuring population differences in rare and common variation. Genetics 2023; 224:iyad070. [PMID: 37075098 PMCID: PMC10213490 DOI: 10.1093/genetics/iyad070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 12/20/2022] [Accepted: 04/07/2023] [Indexed: 04/20/2023] Open
Abstract
In studying allele-frequency variation across populations, it is often convenient to classify an allelic type as "rare," with nonzero frequency less than or equal to a specified threshold, "common," with a frequency above the threshold, or entirely unobserved in a population. When sample sizes differ across populations, however, especially if the threshold separating "rare" and "common" corresponds to a small number of observed copies of an allelic type, discreteness effects can lead a sample from one population to possess substantially more rare allelic types than a sample from another population, even if the two populations have extremely similar underlying allele-frequency distributions across loci. We introduce a rarefaction-based sample-size correction for use in comparing rare and common variation across multiple populations whose sample sizes potentially differ. We use our approach to examine rare and common variation in worldwide human populations, finding that the sample-size correction introduces subtle differences relative to analyses that use the full available sample sizes. We introduce several ways in which the rarefaction approach can be applied: we explore the dependence of allele classifications on subsample sizes, we permit more than two classes of allelic types of nonzero frequency, and we analyze rare and common variation in sliding windows along the genome. The results can assist in clarifying similarities and differences in allele-frequency patterns across populations.
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Affiliation(s)
- Daniel J Cotter
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Elyssa F Hofgard
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305, USA
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Zachary A Szpiech
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
- Institute for Computational and Data Sciences, Pennsylvania State University, University Park, PA 16802, USA
| | - Noah A Rosenberg
- Department of Biology, Stanford University, Stanford, CA 94305, USA
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30
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Caro-Consuegra R, Lucas-Sánchez M, Comas D, Bosch E. Identifying signatures of positive selection in human populations from North Africa. Sci Rep 2023; 13:8166. [PMID: 37210386 DOI: 10.1038/s41598-023-35312-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 05/16/2023] [Indexed: 05/22/2023] Open
Abstract
Because of its location, North Africa (NA) has witnessed continuous demographic movements with an impact on the genomes of present-day human populations. Genomic data describe a complex scenario with varying proportions of at least four main ancestry components: Maghrebi, Middle Eastern-, European-, and West-and-East-African-like. However, the footprint of positive selection in NA has not been studied. Here, we compile genome-wide genotyping data from 190 North Africans and individuals from surrounding populations, investigate for signatures of positive selection using allele frequencies and linkage disequilibrium-based methods and infer ancestry proportions to discern adaptive admixture from post-admixture selection events. Our results show private candidate genes for selection in NA involved in insulin processing (KIF5A), immune function (KIF5A, IL1RN, TLR3), and haemoglobin phenotypes (BCL11A). We also detect signatures of positive selection related to skin pigmentation (SLC24A5, KITLG), and immunity function (IL1R1, CD44, JAK1) shared with European populations and candidate genes associated with haemoglobin phenotypes (HPSE2, HBE1, HBG2), other immune-related (DOCK2) traits, and insulin processing (GLIS3) traits shared with West and East African populations. Finally, the SLC8A1 gene, which codifies for a sodium-calcium exchanger, was the only candidate identified under post-admixture selection in Western NA.
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Affiliation(s)
- Rocio Caro-Consuegra
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, 08003, Barcelona, Spain
| | - Marcel Lucas-Sánchez
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, 08003, Barcelona, Spain
| | - David Comas
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, 08003, Barcelona, Spain
| | - Elena Bosch
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, 08003, Barcelona, Spain.
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, 28029, Madrid, Spain.
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31
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Ahadova A, Witt J, Haupt S, Gallon R, Hüneburg R, Nattermann J, Ten Broeke S, Bohaumilitzky L, Hernandez-Sanchez A, Santibanez-Koref M, Jackson MS, Ahtiainen M, Pylvänäinen K, Andini K, Grolmusz VK, Möslein G, Dominguez-Valentin M, Møller P, Fürst D, Sijmons R, Borthwick GM, Burn J, Mecklin JP, Heuveline V, von Knebel Doeberitz M, Seppälä T, Kloor M. Is HLA type a possible cancer risk modifier in Lynch syndrome? Int J Cancer 2023; 152:2024-2031. [PMID: 36214792 DOI: 10.1002/ijc.34312] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/02/2022] [Accepted: 09/16/2022] [Indexed: 11/05/2022]
Abstract
Lynch syndrome (LS) is the most common inherited cancer syndrome. It is inherited via a monoallelic germline variant in one of the DNA mismatch repair (MMR) genes. LS carriers have a broad 30% to 80% risk of developing various malignancies, and more precise, individual risk estimations would be of high clinical value, allowing tailored cancer prevention and surveillance. Due to MMR deficiency, LS cancers are characterized by the accumulation of frameshift mutations leading to highly immunogenic frameshift peptides (FSPs). Thus, immune surveillance is proposed to inhibit the outgrowth of MMR-deficient cell clones. Recent studies have shown that immunoediting during the evolution of MMR-deficient cancers leads to a counter-selection of highly immunogenic antigens. The immunogenicity of FSPs is dependent on the antigen presentation. One crucial factor determining antigen presentation is the HLA genotype. Hence, a LS carrier's HLA genotype plays an important role in the presentation of FSP antigens to the immune system, and may influence the likelihood of progression from precancerous lesions to cancer. To address the challenge of clarifying this possibility including diverse populations with different HLA types, we have established the INDICATE initiative (Individual cancer risk by HLA type, http://indicate-lynch.org/), an international network aiming at a systematic evaluation of the HLA genotype as a possible cancer risk modifier in LS. Here we summarize the current knowledge on the role of HLA type in cancer risk and outline future research directions to delineate possible association in the scenario of LS with genetically defined risk population and highly immunogenic tumors.
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Affiliation(s)
- Aysel Ahadova
- Department of Applied Tumor Biology, Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.,Cooperation Unit Applied Tumor Biology, German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | - Johannes Witt
- Department of Applied Tumor Biology, Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.,Cooperation Unit Applied Tumor Biology, German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | - Saskia Haupt
- Engineering Mathematics and Computing Lab (EMCL), Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany.,Data Mining and Uncertainty Quantification (DMQ), Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany
| | - Richard Gallon
- Translational and Clinical Research Institute, Newcastle University, International Centre for Life, Newcastle upon Tyne, UK
| | - Robert Hüneburg
- Department of Internal Medicine I, University Hospital Bonn, Bonn, Germany.,National Center for Hereditary Tumor Syndromes, University Hospital Bonn, Bonn, Germany
| | - Jacob Nattermann
- Department of Internal Medicine I, University Hospital Bonn, Bonn, Germany.,National Center for Hereditary Tumor Syndromes, University Hospital Bonn, Bonn, Germany
| | - Sanne Ten Broeke
- Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands
| | - Lena Bohaumilitzky
- Department of Applied Tumor Biology, Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.,Cooperation Unit Applied Tumor Biology, German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | - Alejandro Hernandez-Sanchez
- Department of Applied Tumor Biology, Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.,Cooperation Unit Applied Tumor Biology, German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | - Mauro Santibanez-Koref
- Translational and Clinical Research Institute, Newcastle University, International Centre for Life, Newcastle upon Tyne, UK
| | - Michael S Jackson
- Translational and Clinical Research Institute, Newcastle University, International Centre for Life, Newcastle upon Tyne, UK
| | | | - Kirsi Pylvänäinen
- Department of Education and science, Nova Hospital, Jyväskylä, Finland
| | - Katarina Andini
- Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands
| | - Vince Kornel Grolmusz
- Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary.,Hereditary Cancers Research Group, Hungarian Academy of Sciences-Semmelweis University, Budapest, Hungary
| | - Gabriela Möslein
- Department of Surgery, Ev. Krankenhaus Bethesda Hospital, Duisburg, Germany
| | - Mev Dominguez-Valentin
- Department of Tumor Biology, Institute of Cancer Research, The Norwegian Radium Hospital, Oslo, Norway
| | - Pål Møller
- Department of Tumor Biology, Institute of Cancer Research, The Norwegian Radium Hospital, Oslo, Norway
| | - Daniel Fürst
- Institute of Clinical Transfusion Medicine and Immunogenetics Ulm, German Red Cross Blood Transfusion Service, Baden Wuerttemberg-Hessen, University Hospital Ulm, Ulm, Germany.,Institute of Transfusion Medicine, University of Ulm, Ulm, Germany
| | - Rolf Sijmons
- Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands
| | - Gillian M Borthwick
- Translational and Clinical Research Institute, Newcastle University, International Centre for Life, Newcastle upon Tyne, UK
| | - John Burn
- Translational and Clinical Research Institute, Newcastle University, International Centre for Life, Newcastle upon Tyne, UK
| | - Jukka-Pekka Mecklin
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.,Department of Surgery, Nova Hospital, Jyväskylä, Finland
| | - Vincent Heuveline
- Engineering Mathematics and Computing Lab (EMCL), Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany.,Data Mining and Uncertainty Quantification (DMQ), Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany
| | - Magnus von Knebel Doeberitz
- Department of Applied Tumor Biology, Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.,Cooperation Unit Applied Tumor Biology, German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | - Toni Seppälä
- Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Center, Tampere University Hospital, Tampere, Finland.,Department of Gastrointestinal Surgery, Helsinki University Central Hospital, Helsinki, Finland.,Applied Tumor Genomics Research Program, University of Helsinki, Helsinki, Finland
| | - Matthias Kloor
- Department of Applied Tumor Biology, Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.,Cooperation Unit Applied Tumor Biology, German Cancer Research Centre (DKFZ), Heidelberg, Germany
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32
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Membrive-Jiménez C, Pérez-Ramírez C, Arias-Santiago S, Richetta AG, Ottini L, Pineda-Lancheros LE, Ramírez-Tortosa MDC, Jiménez-Morales A. Impact of Functional Polymorphisms on Drug Survival of Biological Therapies in Patients with Moderate-to-Severe Psoriasis. Int J Mol Sci 2023; 24:ijms24108703. [PMID: 37240048 DOI: 10.3390/ijms24108703] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/09/2023] [Accepted: 05/10/2023] [Indexed: 05/28/2023] Open
Abstract
Biological therapies (BTs) indicated for psoriasis are highly effective; however, not all patients obtain good results, and loss of effectiveness is the main reason for switching. Genetic factors may be involved. The objective of this study was to evaluate the influence of single-nucleotide polymorphisms (SNPs) on the drug survival of tumor necrosis factor inhibitors (anti-TNF) medications and ustekinumab (UTK) in patients diagnosed with moderate-to-severe psoriasis. We conducted an ambispective observational cohort study that included 379 lines of treatment with anti-TNF (n = 247) and UTK (132) in 206 white patients from southern Spain and Italy. The genotyping of the 29 functional SNPs was carried out using real-time polymerase chain reaction (PCR) with TaqMan probes. Drug survival was evaluated with Cox regression and Kaplan-Meier curves. The multivariate analysis showed that the HLA-C rs12191877-T (hazard ratio [HR] = 0.560; 95% CI = 0.40-0.78; p = 0.0006) and TNF-1031 (rs1799964-C) (HR = 0.707; 95% CI = 0.50-0.99; p = 0.048) polymorphisms are associated with anti-TNF drug survival, while TLR5 rs5744174-G (HR = 0.589; 95% CI = 0.37-0.92; p = 0.02), CD84 rs6427528-GG (HR = 0.557; 95% CI = 0.35-0.88; p = 0.013) and PDE3A rs11045392-T together with SLCO1C1 rs3794271-T (HR = 0.508; 95% CI = 0.32-0.79; p = 0.002) are related to UTK survival. The limitations are the sample size and the clustering of anti-TNF drugs; we used a homogeneous cohort of patients from 2 hospitals only. In conclusion, SNPs in the HLA-C, TNF, TLR5, CD84, PDE3A, and SLCO1C1 genes may be useful as biomarkers of drug survival of BTs indicated for psoriasis, making it possible to implement personalized medicine that will reduce financial healthcare costs, facilitate medical decision-making and improve patient quality of life. However, further pharmacogenetic studies need to be conducted to confirm these associations.
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Affiliation(s)
- Cristina Membrive-Jiménez
- Pharmacogenetics Unit, Pharmacy Service, University Hospital Virgen de las Nieves, Avenida. de las Fuerzas Armadas 2, 18004 Granada, Spain
| | - Cristina Pérez-Ramírez
- Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, Campus Universitario de Cartuja, University of Granada, 18011 Granada, Spain
| | | | - Antonio Giovanni Richetta
- Unit of Dermatology, Department of Internal Medicine and Medical Specialties Sapienza, University of Rome, 00161 Rome, Italy
| | - Laura Ottini
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy
| | - Laura Elena Pineda-Lancheros
- Pharmacogenetics Unit, Pharmacy Service, University Hospital Virgen de las Nieves, Avenida. de las Fuerzas Armadas 2, 18004 Granada, Spain
| | - Maria Del Carmen Ramírez-Tortosa
- Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, Campus Universitario de Cartuja, University of Granada, 18011 Granada, Spain
| | - Alberto Jiménez-Morales
- Pharmacogenetics Unit, Pharmacy Service, University Hospital Virgen de las Nieves, Avenida. de las Fuerzas Armadas 2, 18004 Granada, Spain
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33
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Kang JB, Shen AZ, Sakaue S, Luo Y, Gurajala S, Nathan A, Rumker L, Aguiar VRC, Valencia C, Lagattuta K, Zhang F, Jonsson AH, Yazar S, Alquicira-Hernandez J, Khalili H, Ananthakrishnan AN, Jagadeesh K, Dey K, Accelerating Medicines Partnership Program: Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Network, Daly MJ, Xavier RJ, Donlin LT, Anolik JH, Powell JE, Rao DA, Brenner MB, Gutierrez-Arcelus M, Raychaudhuri S. Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.14.23287257. [PMID: 36993194 PMCID: PMC10055604 DOI: 10.1101/2023.03.14.23287257] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation, and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here, we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues, using personalized reference genomes to mitigate technical confounding. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B, and T cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.
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Affiliation(s)
- Joyce B. Kang
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Amber Z. Shen
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Saori Sakaue
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Yang Luo
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Saisriram Gurajala
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Aparna Nathan
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Laurie Rumker
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Vitor R. C. Aguiar
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Cristian Valencia
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Kaitlyn Lagattuta
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology and the Center for Health Artificial Intelligence, University of Colorado School of Medicine, Aurora, CO, USA
| | - Anna Helena Jonsson
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Seyhan Yazar
- Garvan Institute of Medical Research, Sydney, NSW, Australia
| | | | - Hamed Khalili
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Ashwin N. Ananthakrishnan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | | | - Kushal Dey
- Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | | | - Mark J. Daly
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ramnik J. Xavier
- Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Laura T. Donlin
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Jennifer H. Anolik
- Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA
| | | | - Deepak A. Rao
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael B. Brenner
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Maria Gutierrez-Arcelus
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
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34
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Vicuña L, Barrientos E, Norambuena T, Alvares D, Gana JC, Leiva-Yamaguchi V, Meza C, Santos JL, Mericq V, Pereira A, Eyheramendy S. New insights from GWAS on BMI-related growth traits in a longitudinal cohort of admixed children with Native American and European ancestry. iScience 2023; 26:106091. [PMID: 36844456 PMCID: PMC9947275 DOI: 10.1016/j.isci.2023.106091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 05/04/2022] [Accepted: 01/25/2023] [Indexed: 02/02/2023] Open
Abstract
Body-mass index (BMI) is a hallmark of adiposity. In contrast with adulthood, the genetic architecture of BMI during childhood is poorly understood. The few genome-wide association studies (GWAS) on children have been performed almost exclusively in Europeans and at single ages. We performed cross-sectional and longitudinal GWAS for BMI-related traits on 904 admixed children with mostly Mapuche Native American and European ancestries. We found regulatory variants of the immune gene HLA-DQB3 strongly associated with BMI at 1.5 - 2.5 years old. A variant in the sex-determining gene DMRT1 was associated with the age at adiposity rebound (Age-AR) in girls (P = 9.8 × 10 - 9 ). BMI was significantly higher in Mapuche than in Europeans between 5.5 and 16.5 years old. Finally, Age-AR was significantly lower (P = 0.004 ) by 1.94 years and BMI at AR was significantly higher (P = 0.04 ) by 1.2 kg/m 2 , in Mapuche children compared with Europeans.
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Affiliation(s)
- Lucas Vicuña
- Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Peñalolén, Santiago, Chile
- Instituto Milenio Fundamentos de los Datos (IMFD), Santiago, Chile
| | - Esteban Barrientos
- Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Peñalolén, Santiago, Chile
- Instituto Milenio Fundamentos de los Datos (IMFD), Santiago, Chile
| | - Tomás Norambuena
- Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Peñalolén, Santiago, Chile
- Instituto Milenio Fundamentos de los Datos (IMFD), Santiago, Chile
| | - Danilo Alvares
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Juan Cristobal Gana
- Department of Pediatric Gastroenterology and Nutrition, Division of Pediatrics, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | | | - Cristian Meza
- INGEMAT-CIMFAV, Faculty of Engineering, Universidad de Valparaiso, Valparaiso, Chile
| | - José L. Santos
- Department of Nutrition, Diabetes and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Veronica Mericq
- Institute of Maternal and Child Research, Faculty of Medicine, University of Chile, Santiago, Chile
| | - Ana Pereira
- Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | - Susana Eyheramendy
- Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Peñalolén, Santiago, Chile
- Instituto Milenio Fundamentos de los Datos (IMFD), Santiago, Chile
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Gibson WS, Rodriguez OL, Shields K, Silver CA, Dorgham A, Emery M, Deikus G, Sebra R, Eichler EE, Bashir A, Smith ML, Watson CT. Characterization of the immunoglobulin lambda chain locus from diverse populations reveals extensive genetic variation. Genes Immun 2023; 24:21-31. [PMID: 36539592 PMCID: PMC10041605 DOI: 10.1038/s41435-022-00188-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 10/07/2022] [Accepted: 10/13/2022] [Indexed: 12/24/2022]
Abstract
Immunoglobulins (IGs), crucial components of the adaptive immune system, are encoded by three genomic loci. However, the complexity of the IG loci severely limits the effective use of short read sequencing, limiting our knowledge of population diversity in these loci. We leveraged existing long read whole-genome sequencing (WGS) data, fosmid technology, and IG targeted single-molecule, real-time (SMRT) long-read sequencing (IG-Cap) to create haplotype-resolved assemblies of the IG Lambda (IGL) locus from 6 ethnically diverse individuals. In addition, we generated 10 diploid assemblies of IGL from a diverse cohort of individuals utilizing IG-Cap. From these 16 individuals, we identified significant allelic diversity, including 36 novel IGLV alleles. In addition, we observed highly elevated single nucleotide variation (SNV) in IGLV genes relative to IGL intergenic and genomic background SNV density. By comparing SNV calls between our high quality assemblies and existing short read datasets from the same individuals, we show a high propensity for false-positives in the short read datasets. Finally, for the first time, we nucleotide-resolved common 5-10 Kb duplications in the IGLC region that contain functional IGLJ and IGLC genes. Together these data represent a significant advancement in our understanding of genetic variation and population diversity in the IGL locus.
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Affiliation(s)
- William S Gibson
- Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, USA
| | - Oscar L Rodriguez
- Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, USA
| | - Kaitlyn Shields
- Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, USA
| | - Catherine A Silver
- Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, USA
| | - Abdullah Dorgham
- Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, USA
| | - Matthew Emery
- Icahn Institute of Genomics Technology and Data Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gintaras Deikus
- Icahn Institute of Genomics Technology and Data Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert Sebra
- Icahn Institute of Genomics Technology and Data Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Sema4, Stamford, CT, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Ali Bashir
- Google Accelerated Science Team, Google Inc, Mountain View, CA, USA
| | - Melissa L Smith
- Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, USA.
| | - Corey T Watson
- Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, USA.
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Qu H, Connolly JJ, Kraft P, Long J, Pereira A, Flatley C, Turman C, Prins B, Mentch F, Lotufo PA, Magnus P, Stampfer MJ, Tamimi R, Eliassen AH, Zheng W, Knudsen GPS, Helgeland O, Butterworth AS, Hakonarson H, Sleiman PM. Trans-ethnic Polygenic Risk Scores for Body Mass Index: An International Hundred K+ Cohorts Consortium Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.17.23284675. [PMID: 36712066 PMCID: PMC9882470 DOI: 10.1101/2023.01.17.23284675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Background While polygenic risk scores hold significant promise in estimating an individual's risk of developing a complex trait such as obesity, their application in the clinic has, to date, been limited by a lack of data from non-European populations. As a collaboration model of the International Hundred K+ Cohorts Consortium (IHCC), we endeavored to develop a globally applicable trans-ethnic PRS for body mass index (BMI) through this relatively new international effort. Methods The PRS model was developed trained and tested at the Center for Applied Genomics (CAG) of The Children's Hospital of Philadelphia (CHOP) based on a BMI meta-analysis from the GIANT consortium. The validated PRS models were subsequently disseminated to the participating sites. Scores were generated by each site locally on their cohorts and summary statistics returned to CAG for final analysis. Results We show that in the absence of a well powered trans-ethnic GWAS from which to derive SNPs and effect estimates, trans-ethnic scores can be generated from European ancestry GWAS using Bayesian approaches such as LDpred to adjust the summary statistics using trans-ethnic linkage disequilibrium reference panels. The ported trans-ethnic scores outperform population specific-PRS across all non-European ancestry populations investigated including East Asians and three-way admixed Brazilian cohort. Conclusions Widespread use of PRS in the clinic is hampered by a lack of genotyping data in individuals of non-European ancestry for the vast majority of traits. Here we show that for a truly polygenic trait such as BMI adjusting the summary statistics of a well powered European ancestry study using trans-ethnic LD reference results in a score that is predictive across a range of ancestries including East Asians and three-way admixed Brazilians.
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Evaluation of Everolimus Activity against Mycobacterium tuberculosis Using In Vitro Models of Infection. Antibiotics (Basel) 2023; 12:antibiotics12010171. [PMID: 36671372 PMCID: PMC9854797 DOI: 10.3390/antibiotics12010171] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 01/11/2023] [Accepted: 01/12/2023] [Indexed: 01/18/2023] Open
Abstract
Even though Everolimus has been investigated in a phase II randomized trial as a host-directed therapy (HDT) to treat tuberculosis (TB), an oncological patient treated with Everolimus for a neuroendocrine pancreatic neoplasia developed active TB twice and a non-tuberculous mycobacterial (NTM) infection in a year and a half time span. To investigate this interesting case, we isolated and genotypically characterized the Mycobacterium tuberculosis (Mtb) clinical strain from the patient and tested the effect of Everolimus on its viability in an axenic culture and in a peripheral blood mononuclear cell (PBMCs) infection model. To exclude strain-specific resistance, we tested the activity of Everolimus against Mtb strains of ancient and modern lineages. Furthermore, we investigated the Everolimus effect on ROS production and autophagy modulation during Mtb infection. Everolimus did not have a direct effect on mycobacteria viability and a negligible effect during Mtb infection in host cells, although it stimulated autophagy and ROS production. Despite being a biologically plausible HDT against TB, Everolimus does not exert a direct or indirect activity on Mtb. This case underlines the need for a careful approach to drug repurposing and implementation and the importance of pre-clinical experimental studies.
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Pennell M, Rodriguez OL, Watson CT, Greiff V. The evolutionary and functional significance of germline immunoglobulin gene variation. Trends Immunol 2023; 44:7-21. [PMID: 36470826 DOI: 10.1016/j.it.2022.11.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 11/07/2022] [Indexed: 12/04/2022]
Abstract
The recombination between immunoglobulin (IG) gene segments determines an individual's naïve antibody repertoire and, consequently, (auto)antigen recognition. Emerging evidence suggests that mammalian IG germline variation impacts humoral immune responses associated with vaccination, infection, and autoimmunity - from the molecular level of epitope specificity, up to profound changes in the architecture of antibody repertoires. These links between IG germline variants and immunophenotype raise the question on the evolutionary causes and consequences of diversity within IG loci. We discuss why the extreme diversity in IG loci remains a mystery, why resolving this is important for the design of more effective vaccines and therapeutics, and how recent evidence from multiple lines of inquiry may help us do so.
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Affiliation(s)
- Matt Pennell
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA; Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
| | - Oscar L Rodriguez
- Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY, USA
| | - Corey T Watson
- Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY, USA
| | - Victor Greiff
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway.
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Immunogenetic Predisposition to SARS-CoV-2 Infection. BIOLOGY 2022; 12:biology12010037. [PMID: 36671730 PMCID: PMC9855425 DOI: 10.3390/biology12010037] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/15/2022] [Accepted: 12/20/2022] [Indexed: 12/28/2022]
Abstract
Herein, we included 527 individuals from two Hospitals, Chemnitz and University-Hospital Leipzig. In total, 199 were negative for PCR and 328 were positive upon first admission. We used next generation sequencing for HLA-A, B, C, DRB1, DRB345, DQA1, DQB1, DPA1, and DPB1, and in some cases, HLA-E, F, G, and H. Furthermore, we molecularly defined 22 blood group systems comprising 26 genes and 5 platelet antigen genes. We observed a significant enrichment of homozygosity for DQA/DQB in the positive group. Within the negative subjects, HLA-B*57:01, HLA-B*55:01, DRB1*13:01, and DRB1*01:01 were enriched, and in the positive group, homozygosity for DQA/DQB, DRB1*09:01, and DRB1*15:01 was observed. DQA1*01:01, DQA1*02:01, and DQA1*01:03 were enriched in the negative group. HLA-DQB1*06:02 was enriched in the positive group, and HLA-DQB1*05:01 and HLA-DQB1*06:03 were enriched in the negative group. For the blood group systems MNS, RH, LE, FY, JK, YT, DO, and KN, enrichment was seen in both groups, depending on the antigen under observation. Homozygosity for D-positive RHD alleles, as well as the phenotypes M-N+ of the MNS blood group system and Yk(a-) of the KN system, were enriched in the positive group. All of these significances disappeared upon correction. Subjects who carried homozygous HPA-1a were more frequent in the negative group, contrasting with the finding that HPA-1ab was enriched in the positive group.
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40
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Kulski JK, Suzuki S, Shiina T. Human leukocyte antigen super-locus: nexus of genomic supergenes, SNPs, indels, transcripts, and haplotypes. Hum Genome Var 2022; 9:49. [PMID: 36543786 PMCID: PMC9772353 DOI: 10.1038/s41439-022-00226-5] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 11/08/2022] [Accepted: 11/15/2022] [Indexed: 12/24/2022] Open
Abstract
The human Major Histocompatibility Complex (MHC) or Human Leukocyte Antigen (HLA) super-locus is a highly polymorphic genomic region that encodes more than 140 coding genes including the transplantation and immune regulatory molecules. It receives special attention for genetic investigation because of its important role in the regulation of innate and adaptive immune responses and its strong association with numerous infectious and/or autoimmune diseases. In recent years, MHC genotyping and haplotyping using Sanger sequencing and next-generation sequencing (NGS) methods have produced many hundreds of genomic sequences of the HLA super-locus for comparative studies of the genetic architecture and diversity between the same and different haplotypes. In this special issue on 'The Current Landscape of HLA Genomics and Genetics', we provide a short review of some of the recent analytical developments used to investigate the SNP polymorphisms, structural variants (indels), transcription and haplotypes of the HLA super-locus. This review highlights the importance of using reference cell-lines, population studies, and NGS methods to improve and update our understanding of the mechanisms, architectural structures and combinations of human MHC genomic alleles (SNPs and indels) that better define and characterise haplotypes and their association with various phenotypes and diseases.
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Affiliation(s)
- Jerzy K Kulski
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan.
| | - Shingo Suzuki
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan
| | - Takashi Shiina
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan
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Abstract
The worldwide coronavirus disease 2019 pandemic was sparked by the severe acute respiratory syndrome caused by coronavirus 2 (SARS-CoV-2) that first surfaced in December 2019 (COVID-19). The effects of COVID-19 differ substantially not just between patients individually but also between populations with different ancestries. In humans, the human leukocyte antigen (HLA) system coordinates immune regulation. Since HLA molecules are a major component of antigen-presenting pathway, they play an important role in determining susceptibility to infectious disease. It is likely that differential susceptibility to SARS-CoV-2 infection and/or disease course in COVID-19 in different individuals could be influenced by the variations in the HLA genes which are associated with various immune responses to SARS-CoV-2. A growing number of studies have identified a connection between HLA variation and diverse COVID-19 outcomes. Here, we review research investigating the impact of HLA on individual responses to SARS-CoV-2 infection and/or progression, also discussing the significance of MHC-related immunological patterns and its use in vaccine design.
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Affiliation(s)
- Anshika Srivastava
- grid.266102.10000 0001 2297 6811University of California San Francisco, San Francisco, CA USA
| | - Jill A. Hollenbach
- grid.266102.10000 0001 2297 6811University of California San Francisco, San Francisco, CA USA
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42
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Cook CJ, Fletcher JM. Heterogeneity in disease resistance and the impact of antibiotics in the US. ECONOMICS AND HUMAN BIOLOGY 2022; 47:101155. [PMID: 35944452 PMCID: PMC9972546 DOI: 10.1016/j.ehb.2022.101155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 06/22/2022] [Accepted: 07/02/2022] [Indexed: 06/15/2023]
Abstract
We hypothesize that the impact of antibiotics is moderated by a population's inherent (genetic) resistance to infectious disease. Using the introduction of sulfa drugs in 1937, we show that US states that are more genetically susceptible to infectious disease saw larger declines in their bacterial mortality rates following the introduction of sulfa drugs in 1937. This suggests area-level genetic endowments of disease resistance and the discovery of medical technologies have acted as substitutes in determining levels of health across the US. We also document immediate effects of sulfa drug exposure to the age of the workforce and cumulative effects on educational attainment for cohorts exposed to sulfa drugs in early life.
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Pagliuca S, Gurnari C, Rubio MT, Visconte V, Lenz TL. Individual HLA heterogeneity and its implications for cellular immune evasion in cancer and beyond. Front Immunol 2022; 13:944872. [PMID: 36131910 PMCID: PMC9483928 DOI: 10.3389/fimmu.2022.944872] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 08/17/2022] [Indexed: 01/07/2023] Open
Abstract
Structural and functional variability of human leukocyte antigen (HLA) is the foundation for competent adaptive immune responses against pathogen and tumor antigens as it assures the breadth of the presented immune-peptidome, theoretically sustaining an efficient and diverse T cell response. This variability is presumably the result of the continuous selection by pathogens, which over the course of evolution shaped the adaptive immune system favoring the assortment of a hyper-polymorphic HLA system able to elaborate efficient immune responses. Any genetic alteration affecting this diversity may lead to pathological processes, perturbing antigen presentation capabilities, T-cell reactivity and, to some extent, natural killer cell functionality. A highly variable germline HLA genotype can convey immunogenetic protection against infections, be associated with tumor surveillance or influence response to anti-neoplastic treatments. In contrast, somatic aberrations of HLA loci, rearranging the original germline configuration, theoretically decreasing its variability, can facilitate mechanisms of immune escape that promote tumor growth and immune resistance. The purpose of the present review is to provide a unified and up-to-date overview of the pathophysiological consequences related to the perturbations of the genomic heterogeneity of HLA complexes and their impact on human diseases, with a special focus on cancer.
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Affiliation(s)
- Simona Pagliuca
- Translational Hematology and Oncology Research Department, Cleveland Clinic, Cleveland, OH, United States
- Service d’hématologie Clinique, Hôpital Brabois, CHRU Nancy and CNRS UMR 7365 IMoPa, Biopole de l’Université de Loarraine, Vandoeuvre les Nancy, France
| | - Carmelo Gurnari
- Translational Hematology and Oncology Research Department, Cleveland Clinic, Cleveland, OH, United States
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Marie Thérèse Rubio
- Service d’hématologie Clinique, Hôpital Brabois, CHRU Nancy and CNRS UMR 7365 IMoPa, Biopole de l’Université de Loarraine, Vandoeuvre les Nancy, France
| | - Valeria Visconte
- Translational Hematology and Oncology Research Department, Cleveland Clinic, Cleveland, OH, United States
| | - Tobias L. Lenz
- Research Unit for Evolutionary Immunogenomics, Department of Biology, University of Hamburg, Hamburg, Germany
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Mendes M, Jonnalagadda M, Ozarkar S, Lima Torres FC, Borda Pua V, Kendall C, Tarazona-Santos E, Parra EJ. Identifying signatures of natural selection in Indian populations. PLoS One 2022; 17:e0271767. [PMID: 35925921 PMCID: PMC9352006 DOI: 10.1371/journal.pone.0271767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 07/06/2022] [Indexed: 11/18/2022] Open
Abstract
In this study, we present the results of a genome-wide scan for signatures of positive selection using data from four tribal groups (Kokana, Warli, Bhil, and Pawara) and two caste groups (Deshastha Brahmin and Kunbi Maratha) from West of the Maharashtra State In India, as well as two samples of South Asian ancestry from the 1KG project (Gujarati Indian from Houston, Texas and Indian Telugu from UK). We used an outlier approach based on different statistics, including PBS, xpEHH, iHS, CLR, Tajima's D, as well as two recently developed methods: Graph-aware Retrieval of Selective Sweeps (GRoSS) and Ascertained Sequentially Markovian Coalescent (ASMC). In order to minimize the risk of false positives, we selected regions that are outliers in all the samples included in the study using more than one method. We identified putative selection signals in 107 regions encompassing 434 genes. Many of the regions overlap with only one gene. The signals observed using microarray-based data are very consistent with our analyses using high-coverage sequencing data, as well as those identified with a novel coalescence-based method (ASMC). Importantly, at least 24 of these genomic regions have been identified in previous selection scans in South Asian populations or in other population groups. Our study highlights genomic regions that may have played a role in the adaptation of anatomically modern humans to novel environmental conditions after the out of Africa migration.
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Affiliation(s)
- Marla Mendes
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
- Department of Anthropology, University of Toronto—Mississauga Campus, Mississauga, ON, Canada
| | - Manjari Jonnalagadda
- Symbiosis School for Liberal Arts (SSLA), Symbiosis International University (SIU), Pune, India
| | - Shantanu Ozarkar
- Department of Anthropology, Savitribai Phule Pune University, Pune, India
| | - Flávia Carolina Lima Torres
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Victor Borda Pua
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Christopher Kendall
- Department of Anthropology, University of Toronto—Mississauga Campus, Mississauga, ON, Canada
| | - Eduardo Tarazona-Santos
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Esteban J. Parra
- Department of Anthropology, University of Toronto—Mississauga Campus, Mississauga, ON, Canada
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Redondo MJ, Gignoux CR, Dabelea D, Hagopian WA, Onengut-Gumuscu S, Oram RA, Rich SS. Type 1 diabetes in diverse ancestries and the use of genetic risk scores. Lancet Diabetes Endocrinol 2022; 10:597-608. [PMID: 35724677 PMCID: PMC10024251 DOI: 10.1016/s2213-8587(22)00159-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 04/16/2022] [Accepted: 05/06/2022] [Indexed: 02/06/2023]
Abstract
Over 75 genetic loci within and outside of the HLA region influence type 1 diabetes risk. Genetic risk scores (GRS), which facilitate the integration of complex genetic information, have been developed in type 1 diabetes and incorporated into models and algorithms for classification, prognosis, and prediction of disease and response to preventive and therapeutic interventions. However, the development and validation of GRS across different ancestries is still emerging, as is knowledge on type 1 diabetes genetics in populations of diverse genetic ancestries. In this Review, we provide a summary of the current evidence on the evolutionary genetic variation in type 1 diabetes and the racial and ethnic differences in type 1 diabetes epidemiology, clinical characteristics, and preclinical course. We also discuss the influence of genetics on type 1 diabetes with differences across ancestries and the development and validation of GRS in various populations.
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Affiliation(s)
- Maria J Redondo
- Division of Diabetes and Endocrinology, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA.
| | - Christopher R Gignoux
- Department of Medicine and Colorado Center for Personalized Medicine, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Dana Dabelea
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - William A Hagopian
- Division of Diabetes Programs, Pacific Northwest Research Institute, Seattle, WA, USA
| | - Suna Onengut-Gumuscu
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Richard A Oram
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Exeter, UK; The Academic Kidney Unit, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Stephen S Rich
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
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Pollock NR, Harrison GF, Norman PJ. Immunogenomics of Killer Cell Immunoglobulin-Like Receptor (KIR) and HLA Class I: Coevolution and Consequences for Human Health. THE JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY. IN PRACTICE 2022; 10:1763-1775. [PMID: 35561968 PMCID: PMC10038757 DOI: 10.1016/j.jaip.2022.04.036] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/25/2022] [Accepted: 04/26/2022] [Indexed: 12/12/2022]
Abstract
Interactions of killer cell immunoglobin-like receptors (KIR) with human leukocyte antigens (HLA) class I regulate effector functions of key cytotoxic cells of innate and adaptive immunity. The extreme diversity of this interaction is genetically determined, having evolved in the ever-changing environment of pathogen exposure. Diversity of KIR and HLA genes is further facilitated by their independent segregation on separate chromosomes. That fetal implantation relies on many of the same types of immune cells as infection control places certain constraints on the evolution of KIR interactions with HLA. Consequently, specific inherited combinations of receptors and ligands may predispose to specific immune-mediated diseases, including autoimmunity. Combinatorial diversity of KIR and HLA class I can also differentiate success rates of immunotherapy directed to these diseases. Progress toward both etiopathology and predicting response to therapy is being achieved through detailed characterization of the extent and consequences of the combinatorial diversity of KIR and HLA. Achieving these goals is more tractable with the development of integrated analyses of molecular evolution, function, and pathology that will establish guidelines for understanding and managing risks. Here, we present what is known about the coevolution of KIR with HLA class I and the impact of their complexity on immune function and homeostasis.
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Affiliation(s)
- Nicholas R Pollock
- Division of Biomedical Informatics and Personalized Medicine and Department of Immunology and Microbiology, Anschutz Medical Campus, University of Colorado, Aurora, Colo
| | - Genelle F Harrison
- Division of Biomedical Informatics and Personalized Medicine and Department of Immunology and Microbiology, Anschutz Medical Campus, University of Colorado, Aurora, Colo
| | - Paul J Norman
- Division of Biomedical Informatics and Personalized Medicine and Department of Immunology and Microbiology, Anschutz Medical Campus, University of Colorado, Aurora, Colo.
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Kizil C, Sariya S, Kim YA, Rajabli F, Martin E, Reyes-Dumeyer D, Vardarajan B, Maldonado A, Haines JL, Mayeux R, Jiménez-Velázquez IZ, Santa-Maria I, Tosto G. Admixture Mapping of Alzheimer's disease in Caribbean Hispanics identifies a new locus on 22q13.1. Mol Psychiatry 2022; 27:2813-2820. [PMID: 35365809 PMCID: PMC9167722 DOI: 10.1038/s41380-022-01526-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 02/28/2022] [Accepted: 03/14/2022] [Indexed: 11/09/2022]
Abstract
Late-onset Alzheimer's disease (LOAD) is significantly more frequent in Hispanics than in non-Hispanic Whites. Ancestry may explain these differences across ethnic groups. To this end, we studied a large cohort of Caribbean Hispanics (CH, N = 8813) and tested the association between Local Ancestry (LA) and LOAD ("admixture mapping") to identify LOAD-associated ancestral blocks, separately for ancestral components (European [EUR], African [AFR], Native American[NA]) and jointly (AFR + NA). Ancestral blocks significant after permutation were fine-mapped employing multi-ethnic whole-exome sequencing (WES) to identify rare variants associated with LOAD (SKAT-O) and replicated in the UK Biobank WES dataset. Candidate genes were validated studying (A) protein expression in human LOAD and control brains; (B) two animal AD models, Drosophila and Zebrafish. In the joint AFR + NA model, we identified four significant ancestral blocks located on chromosomes 1 (p value = 8.94E-05), 6 (p value = 8.63E-05), 21 (p value = 4.64E-05) and 22 (p value = 1.77E-05). Fine-mapping prioritized the GCAT gene on chromosome 22 (SKAT-O p value = 3.45E-05) and replicated in the UK Biobank (SKAT-O p value = 0.05). In LOAD brains, a decrease of 28% in GCAT protein expression was observed (p value = 0.038), and GCAT knockdown in Amyloid-β42 Drosophila exacerbated rough eye phenotype (68% increase, p value = 4.84E-09). In zebrafish, gcat expression increased after acute amyloidosis (34%, p value = 0.0049), and decreased upon anti-inflammatory Interleukin-4 (39%, p value = 2.3E-05). Admixture mapping uncovered genomic regions harboring new LOAD-associated loci that might explain the observed different frequency of LOAD across ethnic groups. Our results suggest that the inflammation-related activity of GCAT is a response to amyloid toxicity, and reduced GCAT expression exacerbates AD pathology.
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Affiliation(s)
- Caghan Kizil
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West168 th Street, New York, NY, 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital, 710 West 168th Street, New York, NY, 10032, USA
- German Center for Neurodegenerative Diseases (DZNE), Helmholtz Association, Tatzberg 41, 01307, Dresden, Germany
| | - Sanjeev Sariya
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West168 th Street, New York, NY, 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital, 710 West 168th Street, New York, NY, 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA
| | - Yoon A Kim
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West168 th Street, New York, NY, 10032, USA
- Department of Pathology & Cell Biology, Columbia University, New York, NY, USA
| | - Farid Rajabli
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
| | - Eden Martin
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, USA
| | - Dolly Reyes-Dumeyer
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West168 th Street, New York, NY, 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital, 710 West 168th Street, New York, NY, 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA
| | - Badri Vardarajan
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West168 th Street, New York, NY, 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital, 710 West 168th Street, New York, NY, 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA
| | - Aleyda Maldonado
- Department of Medicine, School of Medicine, Medical Sciences Campus, University of Puerto Rico, San Juan, PR, 00936, USA
| | - Jonathan L Haines
- Department of Population & Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Richard Mayeux
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West168 th Street, New York, NY, 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital, 710 West 168th Street, New York, NY, 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA
- Department of Medicine, College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 630 West 168th Street, New York, NY, 10032, USA
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, 1051 Riverside Drive, New York, NY, 10032, USA
| | - Ivonne Z Jiménez-Velázquez
- Department of Medicine, School of Medicine, Medical Sciences Campus, University of Puerto Rico, San Juan, PR, 00936, USA
| | - Ismael Santa-Maria
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West168 th Street, New York, NY, 10032, USA
- Department of Pathology & Cell Biology, Columbia University, New York, NY, USA
| | - Giuseppe Tosto
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West168 th Street, New York, NY, 10032, USA.
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital, 710 West 168th Street, New York, NY, 10032, USA.
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA.
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48
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Human Leukocyte Antigen (HLA) System: Genetics and Association with Bacterial and Viral Infections. J Immunol Res 2022; 2022:9710376. [PMID: 35664353 PMCID: PMC9162874 DOI: 10.1155/2022/9710376] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 05/08/2022] [Indexed: 12/19/2022] Open
Abstract
The human leukocyte antigen (HLA) system is one of the most crucial host factors influencing disease progression in bacterial and viral infections. This review provides the basic concepts of the structure and function of HLA molecules in humans. Here, we highlight the main findings on the associations between HLA class I and class II alleles and susceptibility to important infectious diseases such as tuberculosis, leprosy, melioidosis, Staphylococcus aureus infection, human immunodeficiency virus infection, coronavirus disease 2019, hepatitis B, and hepatitis C in populations worldwide. Finally, we discuss challenges in HLA typing to predict disease outcomes in clinical implementation. Evaluation of the impact of HLA variants on the outcome of bacterial and viral infections would improve the understanding of pathogenesis and identify those at risk from infectious diseases in distinct populations and may improve the individual treatment.
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49
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Alnaqbi H, Tay GK, Chehadeh SEH, Alsafar H. Characterizing the diversity of MHC conserved extended haplotypes using families from the United Arab Emirates. Sci Rep 2022; 12:7165. [PMID: 35504942 PMCID: PMC9065074 DOI: 10.1038/s41598-022-11256-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 04/20/2022] [Indexed: 11/19/2022] Open
Abstract
Aside from its anthropological relevance, the characterization of the allele frequencies of genes in the human Major Histocompatibility Complex (MHC) and the combination of these alleles that make up MHC conserved extended haplotypes (CEHs) is necessary for histocompatibility matching in transplantation as well as mapping disease association loci. The structure and content of the MHC region in Middle Eastern populations remain poorly characterized, posing challenges when establishing disease association studies in ethnic groups that inhabit the region and reducing the capacity to translate genetic research into clinical practice. This study was conceived to address a gap of knowledge, aiming to characterize CEHs in the United Arab Emirates (UAE) population through segregation analysis of high-resolution, pedigree-phased, MHC haplotypes derived from 41 families. Twenty per cent (20.5%) of the total haplotype pool derived from this study cohort were identified as putative CEHs in the UAE population. These consisted of CEHs that have been previously detected in other ethnic groups, including the South Asian CEH 8.2 [HLA- C*07:02-B*08:01-DRB1*03:01-DQA1*05:01-DQB1*02:01 (H.F. 0.094)] and the common East Asian CEH 58.1 [HLA- C*03:02-B*58:01-DRB1*03:01- DQA1*05:01-DQB1*02:01 (H.F. 0.024)]. Additionally, three novel CEHs were identified in the current cohort, including HLA- C*15:02-B*40:06-DRB1*16:02-DQB1*05:02 (H.F. 0.035), HLA- C*16:02-B*51:01-DRB1*16:01-DQA1*01:02-DQB1*05:02 (H.F. 0.029), and HLA- C*03:02-B*58:01-DRB1*16:01-DQA1*01:02-DQB1*05:02 (H.F. 0.024). Overall, the results indicate a substantial gene flow with neighbouring ethnic groups in the contemporary UAE population including South Asian, East Asian, African, and European populations. Importantly, alleles and haplotypes that have been previously associated with autoimmune diseases (e.g., Type 1 Diabetes) were also present. In this regard, this study emphasizes that an appreciation for ethnic differences can provide insights into subpopulation-specific disease-related polymorphisms, which has remained a difficult endeavour.
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Affiliation(s)
- Halima Alnaqbi
- Center for Biotechnology, Khalifa University of Science and Technology, P.O. BOX 127788, Abu Dhabi, UAE.,Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Guan K Tay
- Center for Biotechnology, Khalifa University of Science and Technology, P.O. BOX 127788, Abu Dhabi, UAE.,Division of Psychiatry, UWA Medical School, The University of Western Australia, Perth, WA, Australia.,School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Sarah El Hajj Chehadeh
- Center for Biotechnology, Khalifa University of Science and Technology, P.O. BOX 127788, Abu Dhabi, UAE.,Department of Pharmacology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Habiba Alsafar
- Center for Biotechnology, Khalifa University of Science and Technology, P.O. BOX 127788, Abu Dhabi, UAE. .,Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates. .,Department of Genetics and Molecular Biology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
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50
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Maróstica AS, Nunes K, Castelli EC, Silva NSB, Weir BS, Goudet J, Meyer D. How HLA diversity is apportioned: influence of selection and relevance to transplantation. Philos Trans R Soc Lond B Biol Sci 2022; 377:20200420. [PMID: 35430892 PMCID: PMC9014195 DOI: 10.1098/rstb.2020.0420] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
In his 1972 paper ‘The apportionment of human diversity’, Lewontin showed that, when averaged over loci, genetic diversity is predominantly attributable to differences among individuals within populations. However, selection can alter the apportionment of diversity of specific genes or genomic regions. We examine genetic diversity at the human leucocyte antigen (HLA) loci, located within the major histocompatibility complex (MHC) region. HLA genes code for proteins that are critical to adaptive immunity and are well-documented targets of balancing selection. The single-nucleotide polymorphisms (SNPs) within HLA genes show strong signatures of balancing selection on large timescales and are broadly shared among populations, displaying low FST values. However, when we analyse haplotypes defined by these SNPs (which define ‘HLA alleles’), we find marked differences in frequencies between geographic regions. These differences are not reflected in the FST values because of the extreme polymorphism at HLA loci, illustrating challenges in interpreting FST. Differences in the frequency of HLA alleles among geographic regions are relevant to bone-marrow transplantation, which requires genetic identity at HLA loci between patient and donor. We discuss the case of Brazil's bone marrow registry, where a deficit of enrolled volunteers with African ancestry reduces the chance of finding donors for individuals with an MHC region of African ancestry. This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.
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Affiliation(s)
- André Silva Maróstica
- Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Kelly Nunes
- Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Erick C. Castelli
- Departamento de Patologia, Universidade Estadual Paulista - Unesp, Faculdade de Medicina de Botucatu, Botucatu, SP, Brazil
- Molecular Genetics and Bioinformatics Laboratory, Experimental Research Unit, School of Medicine, São Paulo State University - Unesp, Botucatu, SP, Brazil
| | - Nayane S. B. Silva
- Molecular Genetics and Bioinformatics Laboratory, Experimental Research Unit, School of Medicine, São Paulo State University - Unesp, Botucatu, SP, Brazil
| | - Bruce S. Weir
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Jérôme Goudet
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
- Swiss Institute of Bioinformatics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Diogo Meyer
- Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, SP, Brazil
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