The brain represents one of the most divergent and critical organs in the human body. Yet, it can be afflicted by a variety of neurodegenerative diseases specifically linked to aging, about which we lack a full biomolecular understanding of onset and progression, such as Alzheimer's Disease (AD). Here we provide a proteomic resource comprising nine anatomically distinct sections from three aged individuals, across a spectrum of disease progression, categorized by quantity of neurofibrillary tangles. Using state-of-the-art mass spectrometry, we identify a core brain proteome that exhibits only small variance in expression, accompanied by a group of proteins that are highly differentially expressed in individual sections and broader regions. AD affected tissue exhibited slightly elevated levels of tau protein with similar relative expression to factors associated with the AD pathology. Substantial differences were identified between previous proteomic studies of mature adult brains and our aged cohort. Our findings suggest considerable value in examining specifically the brain proteome of aged human populations from a multiregional perspective. This resource can serve as a guide, as well as a point of reference for how specific regions of the brain are affected by aging and neurodegeneration.

Current methods to isolate synaptic vesicles (SVs), the organellar quanta of synaptic transmission, require highly specialized materials and up to 24 hours. These technical obstacles have thus far limited the study of SVs in models of synaptic function and pathophysiology. Here, we describe techniques for the rapid isolation of SVs by immunoprecipitation with widely available antibodies conjugated to magnetic beads. We report that the inexpensive rho1D4 monoclonal antibody binds SVs and show that elution with the 1D4 peptide yields native vesicles that are ≥ 10-fold purer than those obtained with classical techniques. These methods substantially widen the accessibility of SVs, enabling their purification in 60-90 minutes for downstream analyses including mass spectrometry and cryoelectron microscopy. Immunopurified SV preparations from mouse brain contained apolipoprotein E (ApoE), the low-density lipoprotein (LDL) receptor Lrp1, and enzymes involved in lipid metabolism, suggesting that SVs may play direct roles in lipid homeostasis and lipoprotein trafficking at the nerve terminal.Significance Statement Synaptic vesicles (SVs) are small organelles that form and recycle at nerve terminals to enable synaptic transmission. Much remains unknown about the processes that enable the formation and function of SVs. Moreover, nerve terminals appear to be particularly vulnerable to pathophysiologic processes underlying neurodegenerative diseases and schizophrenia. While techniques to purify synaptic vesicles thus have the potential to yield significant insights into physiology and pathophysiology of nerve terminals, current methods rely on either esoteric materials or expression of transgenes. This paper addresses these problems by establishing robust, efficient methods for SV purification using widely available materials, and it highlights several promising areas of future study arising from proteomic analyses of immunopurified SVs.

Proteomic analysis of cerebrospinal fluid (CSF) holds great promise in understanding the progression of neurodegenerative diseases, including Alzheimer's disease (AD).As one of the primary reservoirs of neuronal biomolecules, CSF provides a window into the biochemical and cellular aspects of the neurological environment. CSF can be drawn from living participants allowing the potential alignment of clinical changes with these biochemical markers. Using cutting-edge mass spectrometry technologies, we perform a streamlined proteomic analysis of CSF. We quantify greater than 700 proteins across 10 pairs of age-and sex-matched participants in approximately one hour of analysis time each. Using the paired participant study structure, we identify a small group of biologically relevant proteins that show substantial changes in abundance between cognitive normal and AD participants, which were then analyzed at the peptide level using parallel reaction monitoring experiments. Our findings suggest the utility of fractionating a single sample and using matching to increase proteomic depth in cerebrospinal fluid, as well as the potential power of an expanded study.

A major hallmark of Alzheimer's disease (AD) is the aggregation of misfolded proteins (β-amyloid (A) and hyperphosphorylated tau (T)) in the brain. As these proteins can be monitored by cerebrospinal fluid (CSF) measures, the AD proteome in CSF has been of particular interest. Here, we conducted a proteome-wide assessment of the CSF in an AD cohort among participants with and without AD pathology (n = 137 total participants: 56 A-T-, 39 A+T-, and 42 A+T+; 915 proteins analyzed), identifying a diverse set of proteins in the CSF enriched for extracellular and immune system processes. We then interrogated the proteome using the amyloid, tau, and neurodegeneration (ATN) framework of AD and a panel of 9 CSF biomarkers for neurodegeneration and neuroinflammation. After multiple testing correction, we identified a total of 61 proteins significantly associated with AT group (P < 5.46 x 10-5; strongest was SMOC1, P = 1.87 x 10-12) and 636 significant protein-biomarker associations (P < 6.07 x 10-6; strongest was a positive association between neurogranin and EPHA4, P = 2.42 x 10-25) across all measures except for interleukin-6, which had no significantly associated proteins. Community network and pathway enrichment analyses highlighted three biomarker-associated protein networks: one related to amyloid and tau measures, one to CSF neurogranin, and one to the remaining CSF biomarkers. Glucose metabolic pathways were enriched primarily among the amyloid- and tau-associated proteins, including malate dehydrogenase and aldolase A, both of which were replicated as strongly associated with AD (P = 1.07 x 10-19 and P = 7.43 x 10-14, respectively) in an independent CSF proteomics cohort (n = 717 participants). Comparative performance of the CSF proteome in predicting AT categorization was high (mean AUC range 0.891-0.924 with number of protein predictors ranging from 37-97) relative to other omic predictors from the genome, CSF metabolome, and demographics from the same cohort of individuals. Collectively, these results emphasize the importance of the CSF proteome relative to other omics and implicate glucose metabolic dysregulation as amyloid and tau pathology emerges in AD.