Herein disclosed are a computer-implemented method, a system, and a kit for assessing/classifying the health status associated with a microbiome profile of a gastrointestinal (GI) sample. The method includes receiving data regarding expression levels of amplicon sequence variants (ASVs) of a V4 region of 16S rRNA in a GI sample of a subject, and utilizing a machine learning algorithm that is trained to distinguish a healthy state from a sick state, a score is computed, and a prediction is made for the presence of a general microbial response that is shared by a large variety of diseases.