T-cell exhaustion occurs when T cells are chronically activated, usually in the context of cancer or chronic infection. Exhausted T cells lose effector functions, upregulate inhibitory receptors, and lose proliferation ability. Understanding the mechanisms of T-cell exhaustion is important as it has critical clinical applications, such as checkpoint blockade therapy. CD4+ T cells are understudied in the context of exhaustion, and no large-scale multiomic datasets containing proteomics, phosphoproteomics, or metabolomics exist. We therefor performed a multiomic experiment to profile this cell state using a time course analysis to also capture progression.