84 Figure 3 | The genetic contribution to antibody-bound peptide variability. A. Manhattan plot from genome-wide association study of 2,798 antibody-bound peptides. Genome-wide association threshold (5x10-8, blue) and study-wide significance (5.67x10-11, red) are shown as horizontal lines. Labels indicate the three major loci identified. Colored dots represent a recessive model. Gray dots represent additive models. B. Peptide motif deconvolution maps of DR3, DQ2.5 and DR14 (amino acids code: negatively charged = red, positively charged = blue, polar uncharged = green, hydrophobic = black) compared with the Streptococcus agalactiae C5a peptidase peptide core and percentage of elution score (%Rank_EL: strong binding ≤ 2.0, weak binding 2.0–10.0, no binding > 10) predicted by NetMHCIIpan-4.0.51 Predicted binding mode, polar molecular interactions (dashes, hydrogen bonds: green, salt bridges: yellow), binding energy and dissociation constant (Kd) of the Streptococcus agalactiae C5a peptidase peptide core (red cartoon and sticks) into HLA-II receptors (chain A in green and chain B in blue). Phenotypic and environmental effects on antibody-bound peptide enrichment More than 200,000 bacterial antigens, including proteins originating from pathogenic, probiotic, and commensal gut microbial species, were included in the peptide libraries. We therefore explored the relations between gut microbiome composition, analyzed by metagenomics sequencing, and presence of antibody responses. To increase the power of the study, we performed taxonomic abundance–peptide associations in 1,051 LLD participants and then ran the meta-analysis including 137 IBD participants.29 Neither the cohort-specific analysis nor the meta-analysis strongly supported taxonomy metagenomic association with antibody-bound peptides (minimum FDR 0.52) (Supplementary Table 2.4). These results are also in line with previous observations.21 To uncover specific effects of lifestyle and environmental factors in the antibody-bound peptide profile, we associated 84 available phenotypes (Supplementary Table 1.3) with the presence/absence of antibody-bound peptide profiles in 1,437 LLD participants. Here, we uncovered 837 strongly supported associations between the presence of antibody-bound peptides and lifestyle- and environmental factors (FDR < 0.05), covering 544 different peptides and 48 different phenotypes (Figure 4A, Supplementary Table 2.5). Phenotypic factors that were associated (after age, gender and sequencing plate correction) with most antibody-bound peptides included age (386 associations), lymphocyte counts (101 associations, both absolute counts and cell proportions), neutrophil counts (86 associations, absolute counts and cell proportions), smoking (84 associations, both former and current smoking), sex (43 associations), allergies (35 associations, including any, pollen, dust or animals), autoantibodies (40 associations) and blood cholesterol levels (13 associations, both total cholesterol and LDL-cholesterol). Of the 386 significant associations with age, 199 were positive and 187 were negative. Older age was associated with a higher prevalence of antibody-bound peptides from several herpes viruses (including CMV, EBV and Herpes simplex virus (HSV) 1 and 2), Streptococcus bacteria (in particular S. pyogenes and S. dysgalactiae) and several pathogenic bacteria (including Shigella flexneri, Yersinia enterocolitica, Campylobacter genus and Helicobacter pylori). Younger individuals had higher frequencies of antibody-bound peptides related to particular viruses (including human rhinovirus serotype 2, influenza A virus and enteroviruses) and bacteria, Chapter 3
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