A study published in Nature Medicine (2014) identifies a set of ten plasma phospholipids that can predict the development of amnestic mild cognitive impairment (aMCI) or Alzheimer’s disease (AD) in older adults. The research involved 525 cognitively normal participants aged 70 and older, followed over five years. Of these, 74 participants met criteria for aMCI or AD, with 28 converting from nonimpaired memory status to impaired memory. The study found that a panel of ten lipids, including phosphatidylcholines (PCs) and acylcarnitines (ACs), could accurately predict conversion to aMCI or AD with over 90% accuracy. These lipids reflect cell membrane integrity and may indicate early neurodegeneration in preclinical Alzheimer’s disease. The study used an untargeted metabolomic approach to identify these lipids, followed by targeted analysis using stable isotope dilution–multiple reaction monitoring mass spectrometry (SID-MRM-MS). The ten-metabolite panel showed significant differences in plasma levels between converters and normal controls, with converters showing lower levels of certain lipids and amino acids. The panel was validated using an independent cohort, confirming its accuracy in classifying participants. The study also found that the ten-metabolite panel was not significantly affected by the APOE ε4 allele, suggesting it is independent of genetic factors. The findings suggest that the ten-lipid biomarker panel could be a valuable tool for early detection of Alzheimer’s disease, offering a non-invasive alternative to current biomarkers. The study highlights the potential of plasma-based biomarkers for identifying preclinical Alzheimer’s disease, which could aid in the development of disease-modifying or preventative therapies. The results support the need for further validation in diverse populations and emphasize the importance of developing reliable biomarkers for early diagnosis and intervention in Alzheimer’s disease.A study published in Nature Medicine (2014) identifies a set of ten plasma phospholipids that can predict the development of amnestic mild cognitive impairment (aMCI) or Alzheimer’s disease (AD) in older adults. The research involved 525 cognitively normal participants aged 70 and older, followed over five years. Of these, 74 participants met criteria for aMCI or AD, with 28 converting from nonimpaired memory status to impaired memory. The study found that a panel of ten lipids, including phosphatidylcholines (PCs) and acylcarnitines (ACs), could accurately predict conversion to aMCI or AD with over 90% accuracy. These lipids reflect cell membrane integrity and may indicate early neurodegeneration in preclinical Alzheimer’s disease. The study used an untargeted metabolomic approach to identify these lipids, followed by targeted analysis using stable isotope dilution–multiple reaction monitoring mass spectrometry (SID-MRM-MS). The ten-metabolite panel showed significant differences in plasma levels between converters and normal controls, with converters showing lower levels of certain lipids and amino acids. The panel was validated using an independent cohort, confirming its accuracy in classifying participants. The study also found that the ten-metabolite panel was not significantly affected by the APOE ε4 allele, suggesting it is independent of genetic factors. The findings suggest that the ten-lipid biomarker panel could be a valuable tool for early detection of Alzheimer’s disease, offering a non-invasive alternative to current biomarkers. The study highlights the potential of plasma-based biomarkers for identifying preclinical Alzheimer’s disease, which could aid in the development of disease-modifying or preventative therapies. The results support the need for further validation in diverse populations and emphasize the importance of developing reliable biomarkers for early diagnosis and intervention in Alzheimer’s disease.