21 research outputs found
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<i>HLA</i> and autoantibodies define scleroderma subtypes and risk in African and European Americans and suggest a role for molecular mimicry
Systemic sclerosis (SSc) is a clinically heterogeneous autoimmune disease characterized by mutually exclusive autoantibodies directed against distinct nuclear antigens. We examined HLA associations in SSc and its autoantibody subsets in a large, newly recruited African American (AA) cohort and among European Americans (EA). In the AA population, the African ancestry-predominant HLA-DRB1*08:04 and HLA-DRB1*11:02 alleles were associated with overall SSc risk, and the HLA-DRB1*08:04 allele was strongly associated with the severe antifibrillarin (AFA) antibody subset of SSc (odds ratio = 7.4). These African ancestry-predominant alleles may help explain the increased frequency and severity of SSc among the AA population. In the EA population, the HLA-DPB1*13:01 and HLA-DRB1*07:01 alleles were more strongly associated with antitopoisomerase (ATA) and anticentromere antibody-positive subsets of SSc, respectively, than with overall SSc risk, emphasizing the importance of HLA in defining autoantibody subtypes. The association of the HLA-DPB1*13:01 allele with the ATA+ subset of SSc in both AA and EA patients demonstrated a transancestry effect. A direct correlation between SSc prevalence and HLA-DPB1*13:01 allele frequency in multiple populations was observed (r = 0.98, P = 3 × 10−6). Conditional analysis in the autoantibody subsets of SSc revealed several associated amino acid residues, mostly in the peptide-binding groove of the class II HLA molecules. Using HLA α / β allelic heterodimers, we bioinformatically predicted immunodominant peptides of topoisomerase 1, fibrillarin, and centromere protein A and discovered that they are homologous to viral protein sequences from the Mimiviridae and Phycodnaviridae families. Taken together, these data suggest a possible link between HLA alleles, autoantibodies, and environmental triggers in the pathogenesis of SSc
A communal catalogue reveals Earth's multiscale microbial diversity
Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.Peer reviewe
A communal catalogue reveals Earth’s multiscale microbial diversity
Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity