Alzheimer’s disease (AD) continuum is defined as a cascade of several neuropathological processes that can be measured using biomarkers such as cerebrospinal fluid (CSF) levels of Aβ, p-tau and t-tau. In parallel, brain anatomy can be characterized through imaging techniques such as magnetic resonance imaging (MRI). In this work, we relate both sets of measurements seeking associations between biomarkers and brain structure that can be indicative of AD progression. The goal is to uncover underlying multivariate effects of AD pathology on regional brain morphological information. For this purpose, we use the projection to latent structures (PLS) method. Using PLS, we find a low dimensional latent space that best describes the covariance between both sets of measurements on the same subjects. Possible confounder effects (age and sex) on brain morphology are included in the model and regressed out using an orthogonal PLS model. We look for statistically significant correlations between brain morphology and CSF biomarkers that explain part of the volumetric variance at each region-of-interest (ROI). Furthermore, we use a clustering technique to discover a small set of CSF-related patterns describing the AD continuum. We apply this technique to the study of subjects in the whole AD continuum from the preclinical asymptomatic stages all through to the symptomatic groups. Subsequent analyses involve splitting the course of the disease into diagnostic categories: cognitively unimpaired subjects (CU), mild cognitive impaired subjects (MCI) and dementia subjects (AD-dementia) where all symptoms are due to AD.