IntroductionThere is an urgent need to identify biomarkers that can accurately detect and diagnose Alzheimer's disease (AD). Autoantibodies are abundant and ubiquitous in human sera and have been previously demonstrated as disease-specific biomarkers capable of accurately diagnosing mild-moderate stages of AD and Parkinson's disease.MethodsSera from 236 subjects, including 50 mild cognitive impairment (MCI) subjects with confirmed low CSF Aβ42 levels, were screened with human protein microarrays to identify potential biomarkers for MCI. Autoantibody biomarker performance was evaluated using Random Forest and Receiver Operating Characteristic curves.ResultsAutoantibody biomarkers can differentiate MCI patients from age-matched and gender-matched controls with an overall accuracy, sensitivity, and specificity of 100.0%. They were also capable of differentiating MCI patients from those with mild-moderate AD and other neurologic and non-neurologic controls with high accuracy.DiscussionAutoantibodies can be used as noninvasive and effective blood-based biomarkers for early diagnosis and staging of AD.

These results demonstrate, for the first time, that a panel of selected autoantibodies may prove to be useful as effective blood-based biomarkers for the diagnosis of early-stage PD.

The goal of this preliminary proof-of-concept study was to use human protein microarrays to identify blood-based autoantibody biomarkers capable of diagnosing multiple sclerosis (MS). Using sera from 112 subjects, including 51 MS subjects, autoantibody biomarkers effectively differentiated MS subjects from age- and gender-matched normal and breast cancer controls with 95.0% and 100% overall accuracy, but not from subjects with Parkinson's disease. Autoantibody biomarkers were also useful in distinguishing subjects with the relapsing-remitting form of MS from those with the secondary progressive subtype. These results demonstrate that autoantibodies can be used as noninvasive blood-based biomarkers for the detection and subtyping of MS.

The authors describe the development and preliminary evaluation of the Lifestyle and Habits Questionnaire-brief version (LHQ-B). Three hundred seventy-seven undergraduate students (ages 18-25) participated. Responses were collected through either a web-based or face-to-face survey. Data reductive procedures were used with a preexisting lifestyle inventory to create an abbreviated measure. The relationship between lifestyle domains and indicators of wellbeing (levels of stress and quality of life (QOL)) were also examined. Eight lifestyle domains, encompassing 42 items, were identified and found to have good psychometric properties. The resulting LHQ-B measure can be self-administered/scored and contains norm-referenced feedback. The domains of psychological health, physical health and exercise, and sense of purpose were the best predictors of QOL while psychological health, social concern, and the accident prevention domains predicted levels of stress. The results support the use of the LHQ-B in lifestyle research or as a self-administered measure promoting self-awareness of lifestyle behaviors/attitudes in young adults (18-25 years).

No abstract