Identifying individuals who are ready for the challenge to renounce addiction (and those who are not ready) holds enormous possibilities including intervention and therapy programs. Further, strengthening the AUD individual by altering those biomarkers, psychosocial or demographic “protective” characteristics, can elevate motivation for the initiation of successful remission. Overall, our findings demonstrate the importance of embedded ancestry and sex in the analysis towards the formulation of personalized prediction model. Interestingly, we found that identifying ancestry by genetic data might increase group homogeneity leading to higher accuracy of the prediction model. We further show that the model based on various features from different areas of health (genetics, electrophysiology, medication, and demographic data) outperform prediction models based on features derived from a single domain. We identified specific robust features of PRS and EEG functional connectivity for each sex/ancestry group, further expanding our knowledge of the predisposition biomarkers including genetics and brain mechanisms underlying the process of remission from AUD.
