Machine‐learning based MRI neuro‐anatomical signatures associated with cardiovascular and metabolic risk factors

Lower gray matter (GM) and higher white matter (WM) volumes have been observed in cognitively unimpaired people with cardiovascular and metabolic risk factors (CVMs) such as hypertension, hyperlipidemia, diabetes, obesity, and smoking [Erus 2015, Habes 2016]. However, these group‐level observations do not explain the heterogeneous accumulated effects of CVMs on individual neuroanatomy. Multivariate CVM‐related changes characterized at the individual level using machine learning (ML)‐derived summary indices may better capture their differential roles in brain aging and dementia. In this work, we derive ML‐based indices that summarize brain changes from MRI related to CVMs.