Multi-omics data-driven personalized health profiling can provide valuable insight into metabolic perturbations in people living with HIV (PWH) under successful antiretroviral therapy (ART). We integrated transcriptomics, proteomics, and metabolomics to identify and stratify the immunometabolically compromised treated PWH (n=158). Based on clinical and lifestyle data, 44% (70/158) of PWH were at risk of immunometabolic complications. We identified six plasma biomarkers to define the at-risk phenotype using advanced machine learning and a Bayesian classifier that drives a network of proteins reasoned for monocyte immunosenescence. We identified metabolic perturbations driven by central carbon metabolic flux led to chronic monocyte activation impairing its early functional properties. Further, we discovered that the host-induced spermidine-mediated microenvironment was responsible for chronic inflammation leading to synaptic dysregulation in vitro, potentiating the risk of neuropsychiatric clinical phenotypes in the at-risk PWH. Novel intervention targeting metabolically-perturbed chronic inflammatory conditions can lead to healthier aging in the at-risk PWH.