Patrizia Malaspina, Carla Jodice, Bianca Maria Ciminelli, Michela Biancolella, Vito Luigi Colona, Andrea Latini, Francesca Leonardis, Paola Rogliani, Antonio Novelli, Giuseppe Novelli, Andrea Novelletto
{"title":"Genetic diversity of the immunoglobulin heavy chain locus in cohorts of patients affected with SARS-CoV-2.","authors":"Patrizia Malaspina, Carla Jodice, Bianca Maria Ciminelli, Michela Biancolella, Vito Luigi Colona, Andrea Latini, Francesca Leonardis, Paola Rogliani, Antonio Novelli, Giuseppe Novelli, Andrea Novelletto","doi":"10.1186/s40246-025-00719-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The Immunoglobulin Heavy Chain (IGH) genomic region is responsible for the production of circulating antibodies and warrants careful investigation for its association with COVID-19 characteristics. Multiple allelic variants within and across different IGH gene segments form a limited set of haplotypes. Previous studies have shown associations between some of these haplotypes and clinical outcomes of COVID-19. We typed 445 individuals of European ancestry, stratified for gender, age, and clinical status for 4 SNPs, two of which result in amino acid substitutions in IGHA2 and IGHG4, respectively. We analyzed associations at the single-locus level and for 4-loci haplotypes, inferred by phasing, after stratifying the overall cohort by gender, age, and disease severity.</p><p><strong>Results: </strong>Only weak evidence of significant differences between subgroups was obtained at the level of a single SNP. However, when the haplotypic data were analyzed for the young and old subgroups separately, uneven partitioning was observed regarding the occurrence of severe cases and Resistors. We then examined the cross-tabulation of disease severity in males and females, based on the presence of each haplotype in the genotype. Two haplotypes were underrepresented in young severe cases compared to old severe ones. The same two haplotypes were overrepresented among young Resistors. These findings provide stronger support for, the weak associations observed at the single locus level.</p><p><strong>Conclusions: </strong>Two haplotypes seem to act as protective factors specifically in young individuals, counteracting the general increase in vulnerability with age. This observation aligns with stronger genetic effects seen in young patients for other susceptibility genes. Our findings complement previous research identifying specific genetic variants that influence COVID-19 susceptibility and severity, emphasizing the complex interplay between host genetics and viral infection outcomes. Our results are consistent with a potential causative role of IGH regulatory regions (e.g. HS1.2), which are flanked by the SNP set here analyzed.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"7"},"PeriodicalIF":3.8000,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11780896/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Genomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40246-025-00719-8","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The Immunoglobulin Heavy Chain (IGH) genomic region is responsible for the production of circulating antibodies and warrants careful investigation for its association with COVID-19 characteristics. Multiple allelic variants within and across different IGH gene segments form a limited set of haplotypes. Previous studies have shown associations between some of these haplotypes and clinical outcomes of COVID-19. We typed 445 individuals of European ancestry, stratified for gender, age, and clinical status for 4 SNPs, two of which result in amino acid substitutions in IGHA2 and IGHG4, respectively. We analyzed associations at the single-locus level and for 4-loci haplotypes, inferred by phasing, after stratifying the overall cohort by gender, age, and disease severity.
Results: Only weak evidence of significant differences between subgroups was obtained at the level of a single SNP. However, when the haplotypic data were analyzed for the young and old subgroups separately, uneven partitioning was observed regarding the occurrence of severe cases and Resistors. We then examined the cross-tabulation of disease severity in males and females, based on the presence of each haplotype in the genotype. Two haplotypes were underrepresented in young severe cases compared to old severe ones. The same two haplotypes were overrepresented among young Resistors. These findings provide stronger support for, the weak associations observed at the single locus level.
Conclusions: Two haplotypes seem to act as protective factors specifically in young individuals, counteracting the general increase in vulnerability with age. This observation aligns with stronger genetic effects seen in young patients for other susceptibility genes. Our findings complement previous research identifying specific genetic variants that influence COVID-19 susceptibility and severity, emphasizing the complex interplay between host genetics and viral infection outcomes. Our results are consistent with a potential causative role of IGH regulatory regions (e.g. HS1.2), which are flanked by the SNP set here analyzed.
期刊介绍:
Human Genomics is a peer-reviewed, open access, online journal that focuses on the application of genomic analysis in all aspects of human health and disease, as well as genomic analysis of drug efficacy and safety, and comparative genomics.
Topics covered by the journal include, but are not limited to: pharmacogenomics, genome-wide association studies, genome-wide sequencing, exome sequencing, next-generation deep-sequencing, functional genomics, epigenomics, translational genomics, expression profiling, proteomics, bioinformatics, animal models, statistical genetics, genetic epidemiology, human population genetics and comparative genomics.