The article introduces a new biomarker classification system for Alzheimer's disease (AD) called the A/T/N classification system, proposed by Jack et al. This system categorizes biomarkers into three categories: amyloid (A), tau (T), and neurodegeneration (N). The rationale behind this system includes the advent of tau PET tracers, the uncertainty in the temporal relationships among current biomarkers, the need to be independent of cognitive-based diagnostic schemes, and the inclusion of all biomarker profiles found in the population. The A/T/N system is designed to be agnostic of cognitive status, making it suitable for classifying individuals from normal older adults to those with established AD. It includes both CSF and brain MRI biomarkers, such as positive amyloid PET, reduced CSF Aβ42, positive tau PET, raised CSF phosphorylated tau, temporoparietal deficits on PET, temporal atrophy on MRI, and raised CSF total tau. The system can classify individuals into states ranging from A−/T−/N− to A+/T+/N+ or any of the six intervening states. A major advantage of the A/T/N system is its independence from cognitive impairment, which can confound traditional classification methods. However, the system has limitations, including the lack of inclusion of biomarkers for cerebrovascular disease and Lewy body disease. The authors suggest that the system could be further refined with quantitative and topographic modifications and applied to datasets like the Alzheimer's Disease Neuroimaging Initiative. Overall, the A/T/N system offers a novel approach to reporting biomarkers in AD research, moving away from opinion-based guidelines to factual biomarker reporting.The article introduces a new biomarker classification system for Alzheimer's disease (AD) called the A/T/N classification system, proposed by Jack et al. This system categorizes biomarkers into three categories: amyloid (A), tau (T), and neurodegeneration (N). The rationale behind this system includes the advent of tau PET tracers, the uncertainty in the temporal relationships among current biomarkers, the need to be independent of cognitive-based diagnostic schemes, and the inclusion of all biomarker profiles found in the population. The A/T/N system is designed to be agnostic of cognitive status, making it suitable for classifying individuals from normal older adults to those with established AD. It includes both CSF and brain MRI biomarkers, such as positive amyloid PET, reduced CSF Aβ42, positive tau PET, raised CSF phosphorylated tau, temporoparietal deficits on PET, temporal atrophy on MRI, and raised CSF total tau. The system can classify individuals into states ranging from A−/T−/N− to A+/T+/N+ or any of the six intervening states. A major advantage of the A/T/N system is its independence from cognitive impairment, which can confound traditional classification methods. However, the system has limitations, including the lack of inclusion of biomarkers for cerebrovascular disease and Lewy body disease. The authors suggest that the system could be further refined with quantitative and topographic modifications and applied to datasets like the Alzheimer's Disease Neuroimaging Initiative. Overall, the A/T/N system offers a novel approach to reporting biomarkers in AD research, moving away from opinion-based guidelines to factual biomarker reporting.