In this study by Jing and Yang et al., intersubject variability in functional connectivity (IVFC) in grey matter (GM) and white matter (WM) was examined as a potential biomarker for predicting suicideal ideation (SI) and suicide attempts (SA) among major depressive disorder (MDD) patients. This study was conducted with a homogeneous Chinese cohort of 178 MDD patients and 173 healthy controls; after the exclusion of certain subjects for health-related reasons, MDD subjects were then split into three categories based on suicide status - non-suicidal (NS), SI, and SA. IVFC information was determined using fMRI scans of the subjects and, after statistical filtering, was used to train Support Vector Machine (SVM) and eXtreme Gradient Boosting Tree (XGBoost) models for suicide status and diagnosis prediction. From the results, utilizing a combination of WM and GM IVFC biomarkers consistently improved model accuracy for both SVM and XGBoost in SI and SA prediction. Furthermore, These models detected significant IVFC differences among NS, SI, and SA patients in the limbic system and other brain regions, such as the thalamus and the superior frontal gyrus. While certain factors, such as the differences of IVFC among MDD patients across different demographics and time-related variability of IVFC biomarkers, were not considered for this study, the usage of WM and GM IVFC biomarkers potentially offers a highly accurate means of assessing suicide risk among MDD patients.