Introduction: In the last decade, magnetic resonance imaging has unveiled specific AD alterations at different stages of the AD pathophysiologic continuum that conform what has been established as the AD signature. To which extent MRI can detect structural changes at the preclinical asymptomatic stage of AD -the preclinical AD signature- is still an area open for exploration. Methods: Longitudinal Magnetic Resonance Imaging (MRI-T13D) data was acquired from a subset of the ADNI cohort comprising 817 subjects (174 controls, 125 preclinical, 518 MCI/Dementia due to AD, at baseline) for which cerebrospinal fluid (CSF) biomarker data is publicly available. For each subject, volumetric changes in brain structure between two consecutive acquisition timepoints (average time interval of 2 years) were defined by calculating jacobian determinants using the SPM longitudinal Voxel-Based Morphometry pipeline. Statistical analysis was performed to identify brain regions with significantly different changes between five progressive groups: (1) Normal controls, (2) Normal control subjects that convert to amyloid positive, (3) Preclinical subjects, (4) Preclinical subjects that become symptomatic, (5) Symptomatic (MCI and AD) subjects. Results: We define the preclinical AD signature as statistically significant structural brain changes between normal controls vs. preclinical subjects (group 1 vs 3). We found certain brain regions that show early subtle atrophy (e.g. Middle Temporal). Other regions show volume increments (e.g. Hippocampus) whereas they display longitudinal atrophy in symptomatic stages (Figure 1), probably resulting in expansion of CSF. Thus, the characterized preclinical AD signature presents regions that overlap with the well-established AD signature (e.g. Precuneus), and others that do not (e.g. Caudate). We will also describe changes that are specific for groups (2) and (4). Conclusions: Our work supports the idea that there are brain volumetric changes specific to preclinical AD subjects and defines the preclinical AD signature based on longitudinal data. While some regions show a pattern of atrophy that overlaps with the AD signature, other specific regions exhibit changes that are unique to this early asymptomatic AD stage. Promising applications of these jacobian determinant features may, in the future, be used for subject classification.