RESUMEN
Alzheimer's disease (AD) and related dementias (ADRD) is a complex disease with multiple pathophysiological drivers that determine clinical symptomology and disease progression. These diseases develop insidiously over time, through many pathways and disease mechanisms and continue to have a huge societal impact for affected individuals and their families. While emerging blood-based biomarkers, such as plasma p-tau181 and p-tau217, accurately detect Alzheimer neuropthology and are associated with faster cognitive decline, the full extension of plasma proteomic changes in ADRD remains unknown. Earlier detection and better classification of the different subtypes may provide opportunities for earlier, more targeted interventions, and perhaps a higher likelihood of successful therapeutic development. In this study, we aim to leverage unbiased mass spectrometry proteomics to identify novel, blood-based biomarkers associated with cognitive decline. 1,786 plasma samples from 1,005 patients were collected over 12 years from partcipants in the Massachusetts Alzheimer's Disease Research Center Longitudinal Cohort Study. Patient metadata includes demographics, final diagnoses, and clinical dementia rating (CDR) scores taken concurrently. The Proteograph™ Product Suite (Seer, Inc.) and liquid-chromatography mass-spectrometry (LC-MS) analysis were used to process the plasma samples in this cohort and generate unbiased proteomics data. Data-independent acquisition (DIA) mass spectrometry results yielded 36,259 peptides and 4,007 protein groups. Linear mixed effects models revealed 138 differentially abundant proteins between AD and healthy controls. Machine learning classification models for AD diagnosis identified potential candidate biomarkers including MBP, BGLAP, and APoD. Cox regression models were created to determine the association of proteins with disease progression and suggest CLNS1A, CRISPLD2, and GOLPH3 as targets of further investigation as potential biomarkers. The Proteograph workflow provided deep, unbiased coverage of the plasma proteome at a speed that enabled a cohort study of almost 1,800 samples, which is the largest, deep, unbiased proteomics study of ADRD conducted to date.
RESUMEN
The integrin Mac-1 plays a critical role in Fc receptor (FcR)-mediated antibody-dependent cellular cytotoxicity (ADCC). However, the mechanism by which Mac-1 facilitates the functions of FcgammaRIIA, a major FcR expressed on human leukocytes, is not fully understood. We report here that Mac-1 sustains cell adhesion, enhances cell spreading, and accelerates cell migration on preformed immune complexes (ICs) by directly interacting with FcgammaRIIA but not with the IC substrate. Coupling Mac-1 to FcgammaRIIA allows FcgammaRIIA to reside in the leading front of actin polymerization at the filopodial extension and thus could potentially enhance FcgammaRIIA-mediated cell spreading and migration. The direct interaction between Mac-1 and FcgammaRIIA is demonstrated by co-immunoprecipitation, by cell surface co-localization, and by solid-phase binding assays using recombinant alpha(M)I-domain and soluble FcgammaRIIA. Further mutational analysis identifies the E(253)-R(261) sequence within the alpha(M)I-domain as part of the FcgammaRIIA binding interface within Mac-1. Altogether, these results demonstrate that FcgammaRIIA recognizes Mac-1 via the alpha(M)I-domain but not the lectin domain, a distinct feature from other FcRs, and that Mac-1 binding confers FcgammaRIIA with the ability to prolong cell adhesion as well as to spread and migrate on the ICs, leading to effective cell killing by ADCC.