Transdiagnostic memory, mood, and motor circuits in Alzheimer’s and neurodegenerative diseases Clinical diagnoses such as Alzheimer’s disease are based on symptoms, but patients with the same diagnosis can have different symptoms and similar symptoms can be present across diagnoses. This includes memory, mood, and motor impairment, each of which can each be disabling. Understanding this symptom heterogeneity and overlap could lead to improved clinical trial design, personalized prognosis, and better treatment. Here, we test the hypothesis that specific symptoms in Alzheimer’s disease can be predicted based on individualized patterns of brain atrophy to trans-diagnostic human brain circuits. To test this hypothesis, we leverage three recent advances. First, there are now longitudinal databases of symptoms and anatomical MRI data from thousands of patients with Alzheimer’s and other neurodegenerative diseases. Second, advances in MRI processing allow us to detect patterns of brain atrophy at the single-subject level. Finally, we now have a wiring diagram of the human brain (the human connectome) that allows us to map symptoms to brain circuits in ways not previously possible. We have previously shown that focal brain lesions causing memory, mood, and motor symptoms map to specific human brain circuits. Our preliminary data shows that this same approach works well for atrophy patterns in Alzheimer’s disease. These atrophy circuits appear to be symptom-specific, transdiagnostic, and prognostic. Interestingly, regions of increased brain volume (rather than atrophy) are also detected using this method and may map to compensatory circuits associated with resilience or preservation of function. Here, we will test whether locations of brain atrophy in Alzheimer’s diseases map to transdiagnostic brain circuits for memory (Aim 1), mood (Aim 2), and motor symptoms (Aim 3). Successful completion of these aims will determine 1) whether individual differences in the location of neurodegeneration, as measured by brain atrophy, are responsible for individual differences in symptoms, 2) whether similarities in brain atrophy are responsible for similar symptoms across diagnoses, 3) whether baseline atrophy to brain circuits predicts future symptoms, and 4) whether increased brain volume in related circuits is associated with preserved function. This knowledge can be used to control for symptom heterogeneity in clinical trials, predict which symptoms an individual patient is likely to develop, and identify therapeutic targets for symptomatic treatment of Alzheimer’s and other neurodegenerative diseases.