Abstract: Methods and systems for detecting an autism state are disclosed. A plurality of data arrays are received, each including a plurality of values. Each of the plurality of values represent a concentration of a different metabolite. A score for each of the plurality of data arrays is calculated based on a relationship between the plurality of values of each of the respective plurality of data arrays. The score for each of the plurality of data arrays is classified into an autism class and a neurotypical class. A test score for a test data array is calculated based on a relationship between the plurality of test values and can then be grouped into one of the autism class and the neurotypical class. The system thus can use biomarkers identified in a metabolic pathway, such as abnormalities in folate-dependent one-carbon metabolism (FOCM) and transsulfuration (TS), to identify patients with a high likelihood of having autism.