A new biomarker classification system for Alzheimer's disease (AD), the A/T/N system, is introduced, which categorizes biomarkers into three domains: amyloid (A), tau (T), and neurodegeneration (N). This system is designed to be independent of cognitive status, allowing for classification based solely on biomarkers. The system uses binary presence or absence of seven biomarkers across the three domains, with additional categories for unavailable ("u") and conflicting ("c") biomarkers. The A/T/N system offers a distinct approach from traditional cognitive-based classifications, making it suitable for normal aging, presymptomatic individuals, and those with established AD. It is advantageous as it avoids confounding factors like education and socioeconomic status, which influence cognitive impairment. However, the system has limitations, including the lack of a cerebrovascular disease biomarker and the exclusion of Lewy body disease. The system could be improved by incorporating more detailed measures of biomarker extent and applying it to known datasets like the Alzheimer's Disease Neuroimaging Initiative. While the A/T/N system is a novel and useful approach for biomarker reporting in AD research, it is not a complete solution and requires further refinement. The authors acknowledge the system's potential and suggest it could evolve with quantitative and topographic modifications. The system allows for classification based on cerebrospinal fluid alone, which is a significant advancement. Overall, the A/T/N system represents a valuable tool for AD research, moving away from opinion-based guidelines to objective biomarker reporting.A new biomarker classification system for Alzheimer's disease (AD), the A/T/N system, is introduced, which categorizes biomarkers into three domains: amyloid (A), tau (T), and neurodegeneration (N). This system is designed to be independent of cognitive status, allowing for classification based solely on biomarkers. The system uses binary presence or absence of seven biomarkers across the three domains, with additional categories for unavailable ("u") and conflicting ("c") biomarkers. The A/T/N system offers a distinct approach from traditional cognitive-based classifications, making it suitable for normal aging, presymptomatic individuals, and those with established AD. It is advantageous as it avoids confounding factors like education and socioeconomic status, which influence cognitive impairment. However, the system has limitations, including the lack of a cerebrovascular disease biomarker and the exclusion of Lewy body disease. The system could be improved by incorporating more detailed measures of biomarker extent and applying it to known datasets like the Alzheimer's Disease Neuroimaging Initiative. While the A/T/N system is a novel and useful approach for biomarker reporting in AD research, it is not a complete solution and requires further refinement. The authors acknowledge the system's potential and suggest it could evolve with quantitative and topographic modifications. The system allows for classification based on cerebrospinal fluid alone, which is a significant advancement. Overall, the A/T/N system represents a valuable tool for AD research, moving away from opinion-based guidelines to objective biomarker reporting.