Diagnosis of early-stage Alzheimer’s disease at mild cognitive impairment using autoantibodies as blood-based biomarkers

Due to the ever-increasing aging population, there is an urgent need to identify biomarkers that can accurately detect and diagnose Alzheimer's disease (AD). Our previous studies have not only demonstrated the ubiquity and abundance of autoantibodies in human sera, but have also determined that subsets of these blood-based autoantibodies can serve as disease-specific biomarkers capable of diagnosing mild-moderate stages of AD and Parkinson's disease with high sensitivity and specificity. Pathological changes linked to AD are known to precede overt clinical symptoms for up to a decade prior to clinical diagnosis, thereby providing a potential window of opportunity for early and even pre-symptomatic detection, which offer the most potential benefit to patients. In the present study, our objective was to identify a panel of autoantibody biomarkers that is useful for accurate diagnosis of patients with mild cognitive impairment (MCI) driven by early stages of AD pathology. Sera from a total of 236 subjects, including 50 MCI subjects with confirmed low CSF Aβ42 levels enrolled in the Alzheimer's Disease Neuroimaging Initiative 2 (ADNI2) study, were screened with human protein microarrays containing 9,486 potential antigen targets to identify autoantibody biomarkers for MCI. Autoantibodies with a higher prevalence in MCI were identified and then tested using Random Forest for their ability to distinguish MCI subjects from age- and sex-matched controls, as well as from individuals with other neurodegenerative and non-neurodegenerative diseases. Autoantibody biomarker performance was further evaluated using Receiver Operating Characteristic (ROC) curves. Results demonstrate that autoantibody biomarkers detected in serum can differentiate early-stage MCI patients from age- and sex-matched controls with an overall accuracy, sensitivity, and specificity of 100.0%. These biomarkers were also capable of differentiating MCI patients from those with mild-moderate AD with an overall accuracy of 98.7%. Additionally, they can also be used to distinguish MCI subjects from those with other neurological (e.g., Parkinson's disease and multiple sclerosis) and non-neurological (e.g., breast cancer) diseases. These results demonstrate, for the first time, that autoantibodies can be used as relatively non-invasive and effective blood-based biomarkers for early diagnosis and staging of AD.