Background: The ability to quantify pathogenic proteins related to Alzheimer's disease (AD) in plasma neuronal extracellular vesicles (NEVs) was vital to their development as diagnostic biomarkers. A similar approach can be employed to assess the biomarker potential of saliva EVs. A head-to-head comparison was conducted to characterize plasma and saliva EVs derived patients enrolled in the Nathan Shock Healthy Aging Study, where participants range in age from 30-70+ years, representing the full breadth of the healthy adult human age span.
Method: Matched plasma and saliva EVs were precipitated from two cohorts, normal controls (NC, 55+ years of age) and patients with mild cognitive impairment (MCI; 55+ years of age) as defined by the Modified Mini-Mental State Test (3MS). EVs were precipitated and enriched against neuronal-origin, L1CAM using magnetic immunocapture and fluorescence-activated cell sorting. EVs and NEVs were characterized for size and shape using NanoSight and marker profiling using Western Blot. AD-related pathogenic proteins Aβ40-42, p-tau, and Nf-L will be quantified in EVs using SIMOA assays.
Result: Plasma and saliva EVs derived from NC and MCI subjects demonstrated similar size distributions and shape characteristics as previously reported. EV marker profiling revealed differential expression of well characterized EV and cellular markers in saliva and plasma EVs. We determined that the rabbit monoclonal antibody raised against tetraspannin CD81 (Abcam) did not identify populations of plasma and saliva EVs while mouse monoclonal antibody against CD81 (Santa Cruz) identified separate populations of plasma and saliva EVs. CD9, TSG101 and ALIX markers positively identified subpopulations of EVs in plasma and saliva while CD63+ EVs were only observed in plasma EVs derived from NC and MCI subjects. MAP2 confirmed neuronal origin of NEVs derived from the plasma of NC and MCI subjects.
Conclusion: The presence of different subpopulations of EVs in plasma and saliva may impact their AD biomarker potential and requires further investigation. Additional analyses will be employed to confirm neuronal origin of EVs from saliva. EV cargo analyses will be performed to assess the biomarker potential of plasma and saliva EVs derived from NC and MCI subjects.
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http://dx.doi.org/10.1002/alz.092263 | DOI Listing |
Alzheimers Dement
December 2024
The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
Background: Approximately 6.7 million people in the US are diagnosed with an Alzheimer's disease (AD), with greater incidence in women and minorities. Approximately 11 million family members provide uncompensated care to their family members with dementia, with more than 60% reporting high or very high levels of stress, a condition associated with increased risk for AD.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Thai Red Cross Emerging Infectious Diseases Health Science Centre, King Chulalongkorn Memorial Hospital, Bangkok, Thailand.
Background: Alzheimer's disease (AD) is referred as one of the most common causes of dementia and frailty. To address this impending public health crisis, there is a critical need to identify simple and reliable biomarkers for early AD diagnosis. Recent research has highlighted the potential utility of salivary lactoferrin (Lf) as a promising biomarker for AD diagnosis.
View Article and Find Full Text PDFBackground: The ability to quantify pathogenic proteins related to Alzheimer's disease (AD) in plasma neuronal extracellular vesicles (NEVs) was vital to their development as diagnostic biomarkers. A similar approach can be employed to assess the biomarker potential of saliva EVs. A head-to-head comparison was conducted to characterize plasma and saliva EVs derived patients enrolled in the Nathan Shock Healthy Aging Study, where participants range in age from 30-70+ years, representing the full breadth of the healthy adult human age span.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
USC Leonard Davis School of Gerontology, Los Angeles, CA, USA.
Background: Alzheimer's disease, along with other cognitive disorders such as frontotemporal dementia (FTD), dementia with Lewy body (DLB) Parkinson's disease dementia (PDD), and vascular cognitive impairment and dementia (VCD), comprise a range of conditions with similar cognitive symptoms but different pathophysiology. Currently, there is no biomarkers to distinguish them before death. The pathophysiological mechanisms differ significantly across these disorders, which implies a varied response to potential treatments.
View Article and Find Full Text PDFBackground: Recent developments in physiological and digital biomarkers provide an opportunity to shift the first diagnostic steps to the home-setting, thus allowing earlier detection and treatment of Alzheimer's disease (AD). Blood-based, magnetic resonance imaging, electrophysiological, digital and microbiome biomarkers have shown great promise and call for an evaluation of their accuracy, feasibility and safety in primary care and the community. The aim of PREDICTOM is to develop and test the accuracy of an artificial intelligence (AI) driven screening platform for the prediction and early detection of AD and to extend the clinical pathway to home-based screening using established and novel biomarkers.
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