ABSTRACT: The identification of mutations modifying the age of onset (AOO) in Alzheimer’s disease (AD) is crucial for understanding the natural history of AD and, therefore, for early interventions. Patients with sporadic AD (sAD) from a genetic isolate in the extremes of the AOO distribution were whole-exome genotyped. Single- and multi-locus linear mixed-effects models were used to identify functional variants modifying AOO. A posteriori enrichment and bioinformatic analyses were applied to evaluate the non-random clustering of the associate variants to physiopathological pathways involved in AD. We identified more than 20 pathogenic, genome-wide statistically significant mutations of major modifier effect on the AOO. These variants are harbored in genes implicated in neuron apoptosis, neurogenesis, inflammatory processes linked to AD, ligodendrocyte differentiation, and memory processes. This set of new genes harboring these mutations could be of importance for prediction, follow-up and eventually as therapeutical targets of AD.COL0010744