Robust and accessible biomarkers that can capture the heterogeneity of Alzheimer’s disease and its diverse pathological processes are urgently needed. Here, we undertook an investigation of Alzheimer’s disease cerebrospinal fluid (CSF) and plasma from the same subjects (n=18 control, n=18 AD) using three different proteomic platforms—SomaLogic SomaScan, Olink proximity extension assay, and tandem mass tag-based mass spectrometry—to assess which protein markers in these two biofluids may serve as reliable biomarkers of AD pathophysiology observed from unbiased brain proteomics studies. Median correlation of overlapping protein measurements across platforms in CSF (r~0.7) and plasma (r~0.6) was good, with more variability in plasma. The SomaScan technology provided the most measurements in plasma. Surprisingly, many proteins altered in AD CSF were found to be altered in the opposite direction in plasma, including important members of AD brain co-expression modules. An exception was SMOC1, a key member of the brain matrisome module associated with amyloid-β deposition in AD, which was found to be elevated in both CSF and plasma. Protein co-expression analysis on greater than 7000 protein measurements in CSF and 9500 protein measurements in plasma across all proteomic platforms revealed strong changes in modules related to autophagy, ubiquitination, and sugar metabolism in CSF, and endocytosis and the matrisome in plasma. Cross-platform and cross-biofluid proteomics represents a promising approach for AD biomarker development.

Background: Language deficits frequently occur during the prodromal stages of Alzheimer’s disease (AD). However, the characteristics of linguistic impairment and its underlying mechanism(s) remain to be explored for the early diagnosis of AD. Methods: The percentage of silence duration (PSD) of 324 subjects was analyzed, including patients with AD, amnestic mild cognitive impairment (aMCI), and normal controls (NC) recruited from the China multi-center cohort, and the diagnostic efficiency was replicated from the Pitt center cohort. Furthermore, the specific language network involved in the fragmented speech was analyzed using task-based functional magnetic resonance. Results: In the China cohort, PSD increased significantly in aMCI and AD patients. The area under the curve of the receiver operating characteristic curves is 0.74, 0.84, and 0.80 in the classification of NC/aMCI, NC/AD, and NC/aMCI+AD. In the Pitt center cohort, PSD was verified as a reliable diagnosis biomarker to differentiate mild AD patients from NC. Next, in response to fluency tasks, clusters in the bilateral inferior frontal gyrus, precentral gyrus, left inferior temporal gyrus, and inferior parietal lobule deactivated markedly in the aMCI/AD group (cluster-level P < 0.05, family-wise error (FWE) corrected). In the patient group (AD+aMCI), higher activation level of the right pars triangularis was associated with higher PSD in in both semantic and phonemic tasks. Conclusions: PSD is a reliable diagnostic biomarker for the early stage of AD and aMCI. At as early as aMCI phase, the brain response to fluency tasks was inhibited markedly, partly explaining why PSD was elevated simultaneously.

Background: Despite being twice as likely to get Alzheimer’s disease (AD), African Americans have been grossly underrepresented in AD research. While emerging evidence indicates that African Americans with AD have lower cerebrospinal fluid (CSF) levels of Tau compared to Caucasians, other differences in AD CSF biomarkers have not been fully elucidated. Here, we performed unbiased proteomic profiling of CSF from African Americans and Caucasians with and without AD to identify both common and divergent AD CSF biomarkers. Methods: Multiplex tandem mass tag-based mass spectrometry (TMT-MS) quantified 1,840 proteins from 105 control and 98 AD patients of which 100 identified as Caucasian while 103 identified as African American. We used differential protein expression and co-expression approaches to assess how changes in the CSF proteome are related to race and AD. Co-expression network analysis organized the CSF proteome into 14 modules associated with brain cell-types and biological pathways. A targeted mass spectrometry method, selected reaction monitoring (SRM), with heavy labeled internal standards was used to measure a panel of CSF module proteins across a subset of African Americans and Caucasians with or without AD. A receiver operating characteristic (ROC) curve analysis assessed the performance of each protein biomarker in differentiating controls and AD by race. Results: Consistent with previous findings, the increase of Tau levels in AD was greater in Caucasians than in African Americans by both immunoassay and TMT-MS measurements. CSF modules which included 14–3-3 proteins (YWHAZ and YWHAG) demonstrated equivalent disease-related elevations in both African Americans and Caucasians with AD, whereas other modules demonstrated more profound disease changes within race. Modules enriched with proteins involved with glycolysis and neuronal/cytoskeletal proteins, including Tau, were more increased in Caucasians than in African Americans with AD. In contrast, a module enriched with synaptic proteins including VGF, SCG2, and NPTX2 was significantly lower in African Americans than Caucasians with AD. Following SRM and ROC analysis, VGF, SCG2, and NPTX2 were significantly better at classifying African Americans than Caucasians with AD. Conclusions: Our findings provide insight into additional protein biomarkers and pathways reflecting underlying brain pathology that are shared or differ by race.

Compared with early-onset familial AD (FAD), the heritability of most familial late-onset Alzheimer's disease (FLOAD) cases still remains unclear. However, there are few reported genetic profiles of FLOAD to date. In the present study, targeted sequencing of selected candidate genes was conducted for each of 90 probands with FLOAD and 101 unrelated matched normal controls among Chinese Han population. Results show a significantly lower rate of mutation in APP and PSENs, and APOE ε4 genetic risk is higher for FLOAD. Among the Chinese FLOAD population, the most frequent variant was CR1 rs116806486 [5.6%, 95% CI (1.8%, 12.5%)], followed by coding variants of TREM2 (4.4%, 95%CI (1.2%, 10.9%)) and novel mutations of ACE [3.3%, 95%CI (0.7%, 9.4%)]. Next, we found that novel pathogenic mutations in ACE including frame-shift and nonsense mutations were in association with FLOAD regardless of APOE ε4 status. Evidence from the Alzheimer's disease Neuroimaging Initiative (ADNI) database also supported this finding in different ethnicities. Results of in vitro analysis suggest that frame-shift and nonsense mutations in ACE may be involved in LOAD through decreased ACE protein levels without affecting direct processing of APP.

There is a pressing 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 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. Here 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 hippocampus and cortex (n=3,368 proteins). Protein co-expression network analysis identified 16 modules of highly co-expressed proteins common across 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 response 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 to AD genotype in hippocampus compared to cortex. Our findings suggest that 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.

Different brain cell types play distinct roles in brain development and disease. Molecular characterization of cell-specific mechanisms using cell type–specific approaches at the protein (proteomic) level can provide biological and therapeutic insights. To overcome the barriers of conventional isolation-based methods for cell type–specific proteomics, in vivo proteomic labeling with proximity-dependent biotinylation of cytosolic proteins using biotin ligase TurboID, coupled with mass spectrometry (MS) of labeled proteins, emerged as a powerful strategy for cell type–specific proteomics in the native state of cells without the need for cellular isolation. To complement in vivo proximity labeling approaches, in vitro studies are needed to ensure that cellular proteomes using the TurboID approach are representative of the whole-cell proteome and capture cellular responses to stimuli without disruption of cellular processes. To address this, we generated murine neuroblastoma (N2A) and microglial (BV2) lines stably expressing cytosolic TurboID to biotinylate the cellular proteome for downstream purification and analysis using MS. TurboID-mediated biotinylation captured 59% of BV2 and 65% of N2A proteomes under homeostatic conditions. TurboID labeled endolysosome, translation, vesicle, and signaling proteins in BV2 microglia and synaptic, neuron projection, and microtubule proteins in N2A neurons. TurboID expression and biotinylation minimally impacted homeostatic cellular proteomes of BV2 and N2A cells and did not affect lipopolysaccharide-mediated cytokine production or resting cellular respiration in BV2 cells. MS analysis of the microglial biotin-labeled proteins captured the impact of lipopolysaccharide treatment (>500 differentially abundant proteins) including increased canonical proinflammatory proteins (Il1a, Irg1, and Oasl1) and decreased anti-inflammatory proteins (Arg1 and Mgl2).

Proteomic studies using postmortem human brain tissue samples have yielded robust assessments of the aging and neurodegenerative disease(s) proteomes. While these analyses provide lists of molecular alterations in human conditions, like Alzheimer’s disease (AD), identifying individual proteins that affect biological processes remains a challenge. To complicate matters, protein targets may be highly understudied and have limited information on their function. To address these hurdles, we sought to establish a blueprint to aid selection and functional validation of targets from proteomic datasets. A cross-platform pipeline was engineered to focus on synaptic processes in the entorhinal cortex (EC) of human patients, including controls, preclinical AD, and AD cases. Label-free quantification mass spectrometry (MS) data (n=2260 proteins) was generated on synaptosome fractionated tissue from Brodmann area 28 (BA28; n=58 samples). In parallel, dendritic spine density and morphology was measured in the same individuals. Weighted gene co-expression network analysis was used to construct a network of protein co-expression modules that were correlated with dendritic spine metrics. Module-trait correlations were used to guide unbiased selection of Twinfilin-2 (TWF2), which was the top hub protein of a module that positively correlated with thin spine length. Using CRISPR-dCas9 activation strategies, we demonstrated that boosting endogenous TWF2 protein levels in primary hippocampal neurons increased thin spine length, thus providing experimental validation for the human network analysis. Collectively, this study describes alterations in dendritic spine density and morphology as well as synaptic proteins and phosphorylated tau from the entorhinal cortex of preclinical and advanced stage AD patients.

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.

Large scale -omics datasets can provide new insights into normal and disease-related biology when analyzed through a systems biology framework. However, technical artefacts present in most -omics datasets due to variations in sample preparation, batching, platform settings, personnel, and other experimental procedures prevent useful analyses of such data without prior adjustment for these technical factors. Here, we demonstrate a tunable median polish of ratio (TAMPOR) approach for batch effect correction and agglomeration of multiple, multi-batch, site-specific cohorts into a single analyte abundance data matrix that is suitable for systems biology analyses. We illustrate the utility and versatility of TAMPOR through four distinct use cases where the method has been applied to different proteomic datasets, some of which contain a specific defect that must be addressed prior to analysis. We compare quality control metrics and sources of variance before and after application of TAMPOR to show that TAMPOR is effective at removing batch effects and other unwanted sources of variance in -omics data. We also show how TAMPOR can be used to harmonize -omics datasets even when the data are acquired using different analytical approaches. TAMPOR is a powerful and flexible approach for cleaning and harmonization of -omics data prior to downstream systems biology analysis.

While evidence supporting the notion that exposures to heavy ion radiation increase the risk for cancer and other disease development is accumulating, the underlying biological mechanisms remain poorly understood. To identify novel phenotypes that persist over time that may be related to increased disease development risk, we performed a quantitative global proteome analysis of immortalized human bronchial epithelial cells (HBEC3-KT) at day 7 post exposure to 0.5 Gy Fe ion (600 MeV/nucleon, Linear Energy Transfer (LET) = 175 keV/μm). The analysis revealed a significant increase in the expression of 4 enzymes of the cholesterol biosynthesis pathway. Elevated expression of enzymes of the cholesterol pathway was associated with increased cholesterol levels in irradiated cells and in lung tissue measured by a biochemical method and by filipin staining of cell-bound cholesterol. While a 1 Gy dose of Fe ion was sufficient to induce a robust response, a dose of 5 Gy X-rays was necessary to induce a similar cholesterol accumulation in HBEC3-KT cells. Radiation-increased cholesterol levels were reduced by treatment with inhibitors affecting the activity of enzymes in the biosynthesis pathway. To examine the implications of this finding for radiotherapy exposures, we screened a panel of lung cancer cell lines for cholesterol levels following exposure to X-rays. We identified a subset of cell lines that increased cholesterol levels in response to 5 Gy X-rays. Survival studies revealed that statin treatment is radioprotective, suggesting that cholesterol increases are associated with cytotoxicity. In summary, our findings uncovered a novel radiation-induced response, which may modify radiation treatment outcomes and contribute to risk for radiation–induced cardiovascular disease and carcinogenesis.