Alzheimer's disease (AD) is the most common cause of dementia, characterized by progressive cognitive decline. Protein biomarkers of AD brain pathology, including β-amyloid and Tau, are reflected in ...cerebrospinal fluid (CSF), yet the identification of additional biomarkers linked to other brain pathophysiologies remains elusive. We recently reported a multiplex tandem-mass tag (TMT) CSF proteomic analysis of nearly 3000 proteins, following depletion of highly abundant proteins and off-line fractionation, across control and AD cases. Of these, over 500 proteins were significantly increased or decreased in AD, including markers reflecting diverse biological functions in brain. Here, we use a targeted mass spectrometry (MS) approach, termed parallel reaction monitoring (PRM), to quantify select CSF biomarkers without pre-depletion or fractionation to assess the reproducibility of our findings and the specificity of changes for AD versus other causes of cognitive impairment.
We nominated 41 proteins (94 peptides) from the TMT CSF discovery dataset, representing a variety of brain cell-types and biological functions, for label-free PRM analysis in a replication cohort of 88 individuals that included 20 normal controls, 37 clinically diagnosed AD cases and 31 cases with non-AD cognitive impairment. To control for technical variables, isotopically labeled synthetic heavy peptide standards were added into each of the 88 CSF tryptic digests. Furthermore, a peptide pool, representing an equivalent amount of peptide from all samples, was analyzed (
= 10) across each batch. Together, this approach enabled us to assess both the intra- and inter-sample differences in peptide signal response and retention time.
Despite differences in sample preparation, quantitative MS approaches and patient samples, 25 proteins, including Tau, had a consistent and significant change in AD in both the discovery and replication cohorts. Validated CSF markers with low coefficient of variation included the protein products for neuronal/synaptic (GDA, GAP43, SYN1, BASP1, YWHAB, YWHAZ, UCHL1, STMN1 and MAP1B), glial/inflammation (SMOC1, ITGAM, CHI3L1, SPP1, and CHIT1) and metabolic (PKM, ALDOA and FABP3) related genes. Logistical regression analyses revealed several proteins with high sensitivity and specificity for classifying AD cases from controls and other non-AD dementias. SMOC1, YWHAZ, ALDOA and MAP1B emerged as biomarker candidates that could best discriminate between individuals with AD and non-AD cognitive impairment as well as Tau/β-amyloid ratio. Notably, SMOC1 levels in postmortem brain are highly correlated with AD pathology even in the preclinical stage of disease, indicating that CSF SMOC1 levels reflect underlying brain pathology specific for AD.
Collectively these findings highlight the utility of targeted MS approaches to quantify biomarkers associated with AD that could be used for monitoring disease progression, stratifying patients for clinical trials and measuring therapeutic response.
Alzheimer's disease (AD) is the most common form of dementia, with cerebrospinal fluid (CSF) β-amyloid (Aβ), total Tau, and phosphorylated Tau (pTau) providing the most sensitive and specific ...biomarkers for diagnosis. However, these diagnostic biomarkers do not reflect the complex changes in AD brain beyond amyloid (A) and Tau (T) pathologies. Here, we report a selected reaction monitoring mass spectrometry (SRM-MS) method with isotopically labeled standards for relative protein quantification in CSF. Biomarker positive (AT+) and negative (AT-) CSF pools were used as quality controls (QCs) to assess assay precision. We detected 62 peptides (51 proteins) with an average coefficient of variation (CV) of ~13% across 30 QCs and 133 controls (cognitively normal, AT-), 127 asymptomatic (cognitively normal, AT+) and 130 symptomatic AD (cognitively impaired, AT+). Proteins that could distinguish AT+ from AT- individuals included SMOC1, GDA, 14-3-3 proteins, and those involved in glycolysis. Proteins that could distinguish cognitive impairment were mainly neuronal proteins (VGF, NPTX2, NPTXR, and SCG2). This demonstrates the utility of SRM-MS to quantify CSF protein biomarkers across stages of AD.
Alzheimer's disease (AD) is a neurodegenerative disease with heterogenous pathophysiological changes that develop years before the onset of clinical symptoms. These preclinical changes have generated ...considerable interest in identifying markers for the pathophysiological mechanisms linked to AD and AD-related disorders (ADRD). On the basis of our prior work integrating cerebrospinal fluid (CSF) and brain proteome networks, we developed a reliable and high-throughput mass spectrometry-selected reaction monitoring assay that targets 48 key proteins altered in CSF. To test the diagnostic utility of these proteins and compare them with existing AD biomarkers, CSF collected at baseline visits was assayed from 706 participants recruited from the Alzheimer's Disease Neuroimaging Initiative. We found that the targeted CSF panel of 48 proteins (CSF 48 panel) performed at least as well as existing AD CSF biomarkers (Aβ
, tTau, and pTau
) for predicting clinical diagnosis, FDG PET, hippocampal volume, and measures of cognitive and dementia severity. In addition, for each of those outcomes, the CSF 48 panel plus the existing AD CSF biomarkers significantly improved diagnostic performance. Furthermore, the CSF 48 panel plus existing AD CSF biomarkers significantly improved predictions for changes in FDG PET, hippocampal volume, and measures of cognitive decline and dementia severity compared with either measure alone. A potential reason for these improvements is that the CSF 48 panel reflects a range of altered biology observed in AD/ADRD. In conclusion, we show that the CSF 48 panel complements existing AD CSF biomarkers to improve diagnosis and predict future cognitive decline and dementia severity.
A small molecule named ISRIB has recently been described to enhance memory in rodents. In this study we aimed to test whether ISRIB would reverse learning and memory deficits in the J20 mouse model ...of human amyloid precursor protein (hAPP) overexpression, a model that simulates many aspects of Alzheimer's disease in which memory deficits are a hallmark feature. We did not observe a significant rescue effect with ISRIB treatment on spatial learning and memory as assessed in the Morris water maze in J20 mice. We also did not observe a significant enhancement of spatial learning or memory in nontransgenic mice with ISRIB treatment, although a trend emerged for memory enhancement in one cohort of mice. Future preclinical studies with ISRIB would benefit from additional robust markers of target engagement in the brain.
There is an urgent need to improve the translational validity of Alzheimer's disease (AD) mouse models. Introducing genetic background diversity in AD mouse models has been proposed as a way to ...increase validity and enable the discovery of previously uncharacterized genetic contributions to AD susceptibility or resilience. However, the extent to which genetic background influences the mouse brain proteome and its perturbation in AD mouse models is unknown. In this study, we crossed the 5XFAD AD mouse model on a C57BL/6J (B6) inbred background with the DBA/2J (D2) inbred background and analyzed the effects of genetic background variation on the brain proteome in F1 progeny. Both genetic background and 5XFAD transgene insertion strongly affected protein variance in the hippocampus and cortex (
= 3,368 proteins). Protein co-expression network analysis identified 16 modules of highly co-expressed proteins common across the hippocampus and cortex in 5XFAD and non-transgenic mice. Among the modules strongly influenced by genetic background were those related to small molecule metabolism and ion transport. Modules strongly influenced by the 5XFAD transgene were related to lysosome/stress responses and neuronal synapse/signaling. The modules with the strongest relationship to human disease-neuronal synapse/signaling and lysosome/stress response-were not significantly influenced by genetic background. However, other modules in 5XFAD that were related to human disease, such as GABA synaptic signaling and mitochondrial membrane modules, were influenced by genetic background. Most disease-related modules were more strongly correlated with AD genotype in the hippocampus compared with the cortex. Our findings suggest that the genetic diversity introduced by crossing B6 and D2 inbred backgrounds influences proteomic changes related to disease in the 5XFAD model, and that proteomic analysis of other genetic backgrounds in transgenic and knock-in AD mouse models is warranted to capture the full range of molecular heterogeneity in genetically diverse models of AD.
Mass spectrometry (MS)-based proteomics is a powerful tool to explore pathogenic changes of a disease in an unbiased manner and has been used extensively in Alzheimer disease (AD) research. Here, by ...performing a meta-analysis of high-quality proteomic studies, we address which pathological changes are observed consistently and therefore most likely are of great importance for AD pathogenesis. We retrieved datasets, comprising a total of 21,588 distinct proteins identified across 857 postmortem human samples, from ten studies using labeled or label-free MS approaches. Our meta-analysis findings showed significant alterations of 757 and 1,195 proteins in AD in the labeled and label-free datasets, respectively. Only 33 proteins, some of which were associated with synaptic signaling, had the same directional change across the individual studies. However, despite alterations in individual proteins being different between the labeled and the label-free datasets, several pathways related to synaptic signaling, oxidative phosphorylation, immune response and extracellular matrix were commonly dysregulated in AD. These pathways represent robust changes in the human AD brain and warrant further investigation.
Data-driven analyses are increasingly valued in modern medicine. We integrate quantitative proteomics and transcriptomics from over 1,000 post-mortem brains from six cohorts representing Alzheimer’s ...disease (AD), asymptomatic AD, progressive supranuclear palsy (PSP), and control patients from the Accelerating Medicines Partnership – Alzheimer’s Disease consortium. We define robust co-expression trajectories related to disease progression, including early neuronal, microglial, astrocyte, and immune response modules, and later mRNA splicing and mitochondrial modules. The majority of, but not all, modules are conserved at the transcriptomic level, including module C3, which is only observed in proteome networks and enriched in mitogen-activated protein kinase (MAPK) signaling. Genetic risk enriches in modules changing early in disease and indicates that AD and PSP have distinct causal biological drivers at the pathway level, despite aspects of similar pathology, including synaptic loss and glial inflammatory changes. The conserved, high-confidence proteomic changes enriched in genetic risk represent targets for drug discovery.
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•We distinguish robust early and late proteomic changes in AD in multiple cohorts•Changes in dementias are not preserved in other neurodegenerative diseases•Genetic risk is enriched in glial-immune modules for AD and synaptic for PSP•Protein expression variance is reflected both at RNA and post-transcriptional levels
Swarup et al. use a multi-omic, multi-cohort approach to identify robust early and late proteomic changes in AD and other neurodegenerative dementias and find that genetic risk is differentially enriched across disorders. Shared co-expression modules showing consistent molecular alterations at multi-omic levels are ripe for future investigation as drug targets.
Cognitive impairment in the elderly features complex molecular pathophysiology extending beyond the hallmark pathologies of traditional disease classification. Molecular subtyping using large-scale ...-omic strategies can help resolve this biological heterogeneity. Using quantitative mass spectrometry, we measured ∼8000 proteins across >600 dorsolateral prefrontal cortex tissues with clinical diagnoses of no cognitive impairment (NCI), mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia. Unbiased classification of MCI and AD cases based on individual proteomic profiles resolved three classes with expression differences across numerous cell types and biological ontologies. Two classes displayed molecular signatures atypical of AD neurodegeneration, such as elevated synaptic and decreased inflammatory markers. In one class, these atypical proteomic features were associated with clinical and pathological hallmarks of cognitive resilience. We were able to replicate these classes and their clinicopathological phenotypes across two additional tissue cohorts. These results promise to better define the molecular heterogeneity of cognitive impairment and meaningfully impact its diagnostic and therapeutic precision.
•Novel subtypes of cognitive impairment identified with distinct network proteomic signatures.•Proteomic subtypes feature defined clinical and neuropathological phenotypes.•Proteomic subtypes reflect differences in genetic risk of Alzheimer's disease.•Proteomic subtypes reveal protein signatures associated with cognitive resilience.
Polymorphic alleles in the apolipoprotein E (
) gene are the main genetic determinants of late-onset Alzheimer's disease (AD) risk. Individuals carrying the
E4 allele are at increased risk to develop ...AD compared to those carrying the more common E3 allele, whereas those carrying the E2 allele are at decreased risk for developing AD. How ApoE isoforms influence risk for AD remains unclear. To help fill this gap in knowledge, we performed a comparative unbiased mass spectrometry-based proteomic analysis of post-mortem brain cortical tissues from pathologically-defined AD or control cases of different
genotypes. Control cases (
= 10) were homozygous for the common E3 allele, whereas AD cases (
= 24) were equally distributed among E2/3, E3/3, and E4/4 genotypes. We used differential protein expression and co-expression analytical approaches to assess how changes in the brain proteome are related to
genotype. We observed similar levels of amyloid-β, but reduced levels of neurofibrillary tau, in E2/3 brains compared to E3/3 and E4/4 AD brains. Weighted co-expression network analysis revealed 33 modules of co-expressed proteins, 12 of which were significantly different by
genotype in AD. The modules that were significantly different by
genotype were associated with synaptic transmission and inflammation, among other biological processes. Deconvolution and analysis of brain cell type changes revealed that the E2 allele suppressed homeostatic and disease-associated cell type changes in astrocytes, microglia, oligodendroglia, and endothelia. The E2 allele-specific effect on brain cell type changes was validated in a separate cohort of 130 brains. Our systems-level proteomic analyses of AD brain reveal alterations in the brain proteome and brain cell types associated with allelic variants in
, and suggest further areas for investigation into the upstream mechanisms that drive ApoE-associated risk for AD.
Objective Alzheimer's disease (AD) is believed to be more common in African Americans (AA), but biomarker studies in AA populations are limited. This report represents the largest study to date ...examining cerebrospinal fluid AD biomarkers in AA individuals. Methods We analyzed 3,006 cerebrospinal fluid samples from controls, AD cases, and non‐AD cases, including 495 (16.5%) self‐identified black/AA and 2,456 (81.7%) white/European individuals using cutoffs derived from the Alzheimer's Disease Neuroimaging Initiative, and using a data‐driven multivariate Gaussian mixture of regressions. Results Distinct effects of race were found in different groups. Total Tauand phospho181‐Tau were lower among AA individuals in all groups ( p < 0.0001), and Aβ 42 was markedly lower in AA controls compared with white controls ( p < 0.0001). Gaussian mixture of regressions modeling of cerebrospinal fluid distributions incorporating adjustments for covariates revealed coefficient estimates for AA race comparable with 2‐decade change in age. Using Alzheimer's Disease Neuroimaging Initiative cutoffs, fewer AA controls were classified as biomarker‐positive asymptomatic AD (8.0% vs 13.4%). After adjusting for covariates, our Gaussian mixture of regressions model reduced this difference, but continued to predict lower prevalence of asymptomatic AD among AA controls (9.3% vs 13.5%). Interpretation Although the risk of dementia is higher, data‐driven modeling indicates lower frequency of asymptomatic AD in AA controls, suggesting that dementia among AA populations may not be driven by higher rates of AD. ANN NEUROL 2024
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