The application provides an
autism prediction model based on blood microorganisms and application thereof. The prediction model takes blood microorganisms as markers, and predicts the risk of
autism of a blood sample through the decrease of a blood
microorganism one
detection rate or relative abundance, or the increase of a blood
microorganism two
detection rate or relative abundance. The blood
microorganism one comprises Xanthobacteraceae bacterium,
Pseudomonas sp.3J6,
Rhodococcus equi, Parabacteroides distasonis, Xylella fastidiosa, Enterorhabdus hofmannii,
Wolbachia,
Yersinia enterocolitica, Borrelia parkeri and Elizabethkingia sp. The blood microorganism two comprises
Klebsiella michiganensis and
Bdellovibrio sp. The application constructs a model based on blood metagenomic data of 1946 standard four-generation families of
autism, fully develops the advantages of blood microorganisms, sensitively and accurately realizes the capture of
disease signals, and can be applied to the prediction of autism in the clinic, and realizes the early
risk assessment and stratification of diseases.