A somatic hypermutation-based machine learning model stratifies individuals with Crohn's disease and controls.
Genome Res
; 33(1): 71-79, 2023 01.
Article
en En
| MEDLINE
| ID: mdl-36526432
ABSTRACT
Crohn's disease (CD) is a chronic relapsing-remitting inflammatory disorder of the gastrointestinal tract that is characterized by altered innate and adaptive immune function. Although massively parallel sequencing studies of the T cell receptor repertoire identified oligoclonal expansion of unique clones, much less is known about the B cell receptor (BCR) repertoire in CD. Here, we present a novel BCR repertoire sequencing data set from ileal biopsies from pediatric patients with CD and controls, and identify CD-specific somatic hypermutation (SHM) patterns, revealed by a machine learning (ML) algorithm trained on BCR repertoire sequences. Moreover, ML classification of a different data set from blood samples of adults with CD versus controls identified that V gene usage, clusters, or mutation frequencies yielded excellent results in classifying the disease (F1 > 90%). In summary, we show that an ML algorithm enables the classification of CD based on unique BCR repertoire features with high accuracy.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Enfermedad de Crohn
Límite:
Adult
/
Child
/
Humans
Idioma:
En
Revista:
Genome Res
Asunto de la revista:
BIOLOGIA MOLECULAR
/
GENETICA
Año:
2023
Tipo del documento:
Article
País de afiliación:
Israel