A method of diagnosing or prognosing a disease or disorder in a subject, or for selecting appropriate and optimal therapies for said disease or disorder, wherein the disease or disorder is one in which an adaptive immune response occurs, and wherein the method comprises: a) providing a biological sample from the subject, said sample comprising a plurality of antibodies; b) contacting the biological sample with a plurality of peptides in a peptide display library; c) identifying members of the plurality of peptides that form a complex with members of the plurality of antibodies in the sample following contacting in (b); d) identifying at least one peptide motif predetermined to be indicative of the disease or disorder by aligning the sequences of the members of the plurality of peptides identified in step c) using a computational peptide sequence clustering algorithm, wherein the motifs were predetermined to be indicative of the disease or disorder using positive and negative control samples, wherein the negative control samples are from subjects without the disease or disorder, and the positive control samples are from subjects who have the disease or disorder; e) calculating the enrichment of the identified motif(s); f) comparing the enrichment of the identified motif(s) determined in step e) (i) with the enrichment of the same peptide motif in a negative control sample, wherein the enrichment of the motif(s) in the control sample is calculated as in steps (a) to (e), or (ii) with established thresholds of the same peptide motif(s), said thresholds predetermined to be indicative of the disease or disorder using control samples as in (i) and using the same method as in (a)-(e), wherein enrichment is defined as the number of observations of a motif within an epitope repertoire divided by the number expected within a random dataset of equivalent size. a) providing a biological sample from the subject, said sample comprising a plurality of antibodies; b) contacting the biological sample with a plurality of peptides in a peptide display library; c) identifying members of the plurality of peptides that form a complex with members of the plurality of antibodies in the sample following contacting in (b); d) identifying at least one peptide motif predetermined to be indicative of the disease or disorder by aligning the sequences of the members of the plurality of peptides identified in step c) using a computational peptide sequence clustering algorithm, wherein the motifs were predetermined to be indicative of the disease or disorder using positive and negative control samples, wherein the negative control samples are from subjects without the disease or disorder, and the positive control samples are from subjects who have the disease or disorder; e) calculating the enrichment of the identified motif(s); f) comparing the enrichment of the identified motif(s) determined in step e) (i) with the enrichment of the same peptide motif in a negative control sample, wherein the enrichment of the motif(s) in the control sample is calculated as in steps (a) to (e), or (ii) with established thresholds of the same peptide motif(s), said thresholds predetermined to be indicative of the disease or disorder using control samples as in (i) and using the same method as in (a)-(e), wherein enrichment is defined as the number of observations of a motif within an epitope repertoire divided by the number expected within a random dataset of equivalent size. (i) with the enrichment of the same peptide motif in a negative control sample, wherein the enrichment of the motif(s) in the control sample is calculated as in steps (a) to (e), or (ii) with established thresholds of the same peptide motif(s), said thresholds predetermined to be indicative of the disease or disorder using control samples as in (i) and using the same method as in (a)-(e), <EOS>