Proteomics analysis of plasma from middle-aged adults identifies protein markers of dementia risk in later life

A supervised Bayesian factor model for the identification of multi-omics signatures

MOTIVATION

Predictive biological signatures provide utility as biomarkers for disease diagnosis and prognosis, as well as prediction of responses to vaccination or therapy. These signatures are identified from high-throughput profiling assays through a combination of dimensionality reduction and machine learning techniques. The genes, proteins, metabolites, and other biological analytes that compose signatures also generate hypotheses on the underlying mechanisms driving biological responses, thus improving biological understanding. Dimensionality reduction is a critical step in signature discovery to address the large number of analytes in omics datasets, especially for multi-omics profiling studies with tens of thousands of measurements. Latent factor models, which can account for the structural heterogeneity across diverse assays, effectively integrate multi-omics data and reduce dimensionality to a small number of factors that capture correlations and associations among measurements. These factors provide biologically interpretable features for predictive modeling. However, multi-omics integration and predictive modeling are generally performed independently in sequential steps, leading to suboptimal factor construction. Combining these steps can yield better multi-omics signatures that are more predictive while still being biologically meaningful.

RESULTS

We developed a supervised variational Bayesian factor model that extracts multi-omics signatures from high-throughput profiling datasets that can span multiple data types. Signature-based multiPle-omics intEgration via lAtent factoRs (SPEAR) adaptively determines factor rank, emphasis on factor structure, data relevance and feature sparsity. The method improves the reconstruction of underlying factors in synthetic examples and prediction accuracy of coronavirus disease 2019 severity and breast cancer tumor subtypes.

AVAILABILITY AND IMPLEMENTATION

SPEAR is a publicly available R-package hosted at https://bitbucket.org/kleinstein/SPEAR.

Organ-specific aging in the plasma proteome predicts disease

In their recent Nature paper, Oh et al. use 4979 plasma proteins collected across multiple cohorts, publicly available gene expression data, and machine learning models to identify 11 organ-specific aging scores that are linked to organ-specific disease and mortality risk, including heart failure, cognitive decline, and Alzheimer's disease.

Towards early diagnosis of Alzheimer's disease: advances in immune-related blood biomarkers and computational approaches

Alzheimer's disease has an increasing prevalence in the population world-wide, yet current diagnostic methods based on recommended biomarkers are only available in specialized clinics. Due to these circumstances, Alzheimer's disease is usually diagnosed late, which contrasts with the currently available treatment options that are only effective for patients at an early stage. Blood-based biomarkers could fill in the gap of easily accessible and low-cost methods for early diagnosis of the disease. In particular, immune-based blood-biomarkers might be a promising option, given the recently discovered cross-talk of immune cells of the central nervous system with those in the peripheral immune system. Here, we give a background on recent advances in research on brain-immune system cross-talk in Alzheimer's disease and review machine learning approaches, which can combine multiple biomarkers with further information (e.g. age, sex, APOE genotype) into predictive models supporting an earlier diagnosis. In addition, mechanistic modeling approaches, such as agent-based modeling open the possibility to model and analyze cell dynamics over time. This review aims to provide an overview of the current state of immune-system related blood-based biomarkers and their potential for the early diagnosis of Alzheimer's disease.

The 'middle-aging' brain

Middle age has historically been an understudied period of life compared to older age, when cognitive and brain health decline are most pronounced, but the scope for intervention may be limited. However, recent research suggests that middle age could mark a shift in brain aging. We review emerging evidence on multiple levels of analysis indicating that midlife is a period defined by unique central and peripheral processes that shape future cognitive trajectories and brain health. Informed by recent developments in aging research and lifespan studies in humans and animal models, we highlight the utility of modeling non-linear changes in study samples with wide subject age ranges to distinguish life stage-specific processes from those acting linearly throughout the lifespan.

Associations of plasma proteomics and age-related outcomes with brain age in a diverse cohort

Machine learning models are increasingly being used to estimate "brain age" from neuroimaging data. The gap between chronological age and the estimated brain age gap (BAG) is potentially a measure of accelerated and resilient brain aging. Brain age calculated in this fashion has been shown to be associated with mortality, measures of physical function, health, and disease. Here, we estimate the BAG using a voxel-based elastic net regression approach, and then, we investigate its associations with mortality, cognitive status, and measures of health and disease in participants from Atherosclerosis Risk in Communities (ARIC) study who had a brain MRI at visit 5 of the study. Finally, we used the SOMAscan assay containing 4877 proteins to examine the proteomic associations with the MRI-defined BAG. Among N = 1849 participants (age, 76.4 (SD 5.6)), we found that increased values of BAG were strongly associated with increased mortality and increased severity of the cognitive status. Strong associations with mortality persisted when the analyses were performed in cognitively normal participants. In addition, it was strongly associated with BMI, diabetes, measures of physical function, hypertension, prevalent heart disease, and stroke. Finally, we found 33 proteins associated with BAG after a correction for multiple comparisons. The top proteins with positive associations to brain age were growth/differentiation factor 15 (GDF-15), Sushi, von Willebrand factor type A, EGF, and pentraxin domain-containing protein 1 (SEVP 1), matrilysin (MMP7), ADAMTS-like protein 2 (ADAMTS), and heat shock 70 kDa protein 1B (HSPA1B) while EGF-receptor (EGFR), mast/stem-cell-growth-factor-receptor (KIT), coagulation-factor-VII, and cGMP-dependent-protein-kinase-1 (PRKG1) were negatively associated to brain age. Several of these proteins were previously associated with dementia in ARIC. These results suggest that circulating proteins implicated in biological aging, cellular senescence, angiogenesis, and coagulation are associated with a neuroimaging measure of brain aging.

Heparin-enriched plasma proteome is significantly altered in Alzheimer's Disease

Introduction

Heparin binding proteins (HBPs) with roles in extracellular matrix assembly are strongly correlated to β-amyloid (Aβ) and tau pathology in Alzheimer's disease (AD) brain and cerebrospinal fluid (CSF). However, it remains challenging to detect these proteins in plasma using standard mass spectrometry-based proteomic approaches.

Methods

We employed heparin affinity chromatography, followed by off-line fractionation and tandem mass tag mass spectrometry (TMT-MS), to capture and enrich HBPs in plasma obtained from AD (n=62) and control (n=47) samples. These profiles were then correlated to a consensus AD brain proteome, as well as with Aβ, tau and phosphorylated tau (pTau) CSF biomarkers from the same individuals. We then leveraged published human postmortem brain proteome datasets to assess the overlap with the heparin-enriched plasma proteome.

Results

Heparin-enrichment from plasma was highly reproducible, enriched well-known HBPs like APOE and thrombin, and depleted high-abundance proteins such as albumin. A total of 2865 proteins, spanning 10 orders of magnitude were detectable. Utilizing a consensus AD brain protein co-expression network, we observed that specific plasma HBPs exhibited consistent direction of change in both brain and plasma, whereas others displayed divergent changes highlighting the complex interplay between the two compartments. Elevated HBPs in AD plasma, when compared to controls, included members of the matrisome module in brain that accumulate within Aβ deposits, such as SMOC1, SMOC2, SPON1, MDK, OLFML3, FRZB, GPNMB, and APOE. Additionally, heparin enriched plasma proteins demonstrated significant correlations with conventional AD CSF biomarkers, including Aβ, total tau, pTau, and plasma pTau from the same individuals.

Conclusion

These findings support the utility of a heparin-affinity approach for enriching amyloid-associated proteins, as well as a wide spectrum of plasma biomarkers that reflect pathological changes in the AD brain.

Plasma proteomic profiles predict future dementia in healthy adults

The advent of proteomics offers an unprecedented opportunity to predict dementia onset. We examined this in data from 52,645 adults without dementia in the UK Biobank, with 1,417 incident cases and a follow-up time of 14.1 years. Of 1,463 plasma proteins, GFAP, NEFL, GDF15 and LTBP2 consistently associated most with incident all-cause dementia (ACD), Alzheimer's disease (AD) and vascular dementia (VaD), and ranked high in protein importance ordering. Combining GFAP (or GDF15) with demographics produced desirable predictions for ACD (area under the curve (AUC) = 0.891) and AD (AUC = 0.872) (or VaD (AUC = 0.912)). This was also true when predicting over 10-year ACD, AD and VaD. Individuals with higher GFAP levels were 2.32 times more likely to develop dementia. Notably, GFAP and LTBP2 were highly specific for dementia prediction. GFAP and NEFL began to change at least 10 years before dementia diagnosis. Our findings strongly highlight GFAP as an optimal biomarker for dementia prediction, even more than 10 years before the diagnosis, with implications for screening people at high risk for dementia and for early intervention.

DNAJB12 and DNJB14 are non-redundant Hsp40 redox chaperones involved in endoplasmic reticulum protein reflux

BACKGROUND

The endoplasmic reticulum (ER) transmembrane chaperones DNAJB12(B12) and DNAJB14(B14) are cofactors that cooperate with cytosolic Heat Shock-70 protein (HSC70) facilitating folding/degradation of nascent membrane proteins and supporting the ER-membrane penetration of viral particles. Here, we assessed structural/functional features of B12/B14 with respect to their regulation by ER stress and their involvement in ER stress-mediated protein reflux.

METHODS

We investigated the effect of Unfolded Protein Response(UPR)-eliciting drugs on the expression/regulation of B12-B14 and their roles in ER-to-cytosol translocation of Protein Disulfide Isomerase-A1(PDI).

RESULTS

We show that B12 and B14 are similar but do not seem redundant. They share predicted structural features and show high homology of their cytosolic J-domains, while their ER-lumen DUF1977 domains are quite dissimilar. Interactome analysis suggested that B12/B14 associate with different biological processes. UPR activation did not significantly impact on B12 gene expression, while B14 transcripts were up-regulated. Meanwhile, B12 and B14 (33.4 kDa isoform) protein levels were degraded by the proteasome upon acute reductive challenge. Also, B12 degradation was impaired upon sulfenic-acid trapping by dimedone. We originally report that knockdown of B12/B14 and their cytosolic partner SGTA in ER-stressed cells significantly impaired the amount of the ER redox-chaperone PDI in a cytosolic-enriched fraction. Additionally, B12 but not B14 overexpression increased PDI relocalization in non-stressed cells.

CONCLUSIONS AND GENERAL SIGNIFICANCE

Our findings reveal that B12/B14 regulation involves thiol redox processes that may impact on their stability and possibly on physiological effects. Furthermore, we provide novel evidence that these proteins are involved in UPR-induced ER protein reflux.

Comparison of Commonly Measured Plasma and Cerebrospinal Fluid Proteins and Their Significance for the Characterization of Cognitive Impairment Status

BACKGROUND

Although cerebrospinal fluid (CSF) amyloid-β42 peptide (Aβ42) and phosphorylated tau (p-tau) and blood p-tau are valuable for differential diagnosis of Alzheimer's disease (AD) from cognitively normal (CN) there is a lack of validated biomarkers for mild cognitive impairment (MCI).

OBJECTIVE

This study sought to determine how plasma and CSF protein markers compared in the characterization of MCI and AD status.

METHODS

This cohort study included Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who had baseline levels of 75 proteins measured commonly in plasma and CSF (257 total, 46 CN, 143 MCI, and 68 AD). Logistic regression, least absolute shrinkage and selection operator (LASSO) and Random Forest (RF) methods were used to identify the protein candidates for the disease classification.

RESULTS

We observed that six plasma proteins panel (APOE, AMBP, C3, IL16, IGFBP2, APOD) outperformed the seven CSF proteins panel (VEGFA, HGF, PRL, FABP3, FGF4, CD40, RETN) as well as AD markers (CSF p-tau and Aβ42) to distinguish the MCI from AD [area under the curve (AUC) = 0.75 (plasma proteins), AUC = 0.60 (CSF proteins) and AUC = 0.56 (CSF p-tau and Aβ42)]. Also, these six plasma proteins performed better than the CSF proteins and were in line with CSF p-tau and Aβ42 in differentiating CN versus MCI subjects [AUC = 0.89 (plasma proteins), AUC = 0.85 (CSF proteins) and AUC = 0.89 (CSF p-tau and Aβ42)]. These results were adjusted for age, sex, education, and APOEϵ4 genotype.

CONCLUSIONS

This study suggests that the combination of 6 plasma proteins can serve as an effective marker for differentiating MCI from AD and CN.

Resveratrol differentially affects MMP-9 release from neurons and glia; implications for therapeutic efficacy

Resveratrol, a naturally occurring polyphenol that activates sirtuin 1 (SIRT1), has been shown to reduce overall levels of matrix metalloprotease-9 (MMP-9) in cerebrospinal fluid (CSF) samples from patients with Alzheimer's dementia (AD). Depending on the site of release, however, MMP-9 has the potential to improve or impair cognition. In particular, its release from microglia or pericytes proximal to the blood brain barrier can damage the basement membrane, while neuronal activity-dependent release of this protease from glutamatergic neurons can instead promote dendritic spine expansion and long-term potentiation of synaptic plasticity. In the present study, we test the hypothesis that resveratrol reduces overall MMP-9 levels in CSF samples from patients with APOE4, an allele associated with increased glial inflammation. We also examine the possibility that resveratrol reduces inflammation-associated MMP release from cultured glia but spares neuronal activity-dependent release from cultured cortical neurons. We observe that resveratrol decreases overall levels of MMP-2 and MMP-9 in CSF samples from AD patients. Resveratrol also reduces CSF levels of tissue inhibitor of metalloproteinases-1 (TIMP-1), glial-derived protein that restricts long-term potentiation of synaptic transmission, in individuals homozygous for APOE4. Consistent with these results, we observe that resveratrol reduces basal and lipopolysaccharide (LPS)-stimulated MMP and TIMP-1 release from cultured microglia and astrocytes. In contrast, however, resveratrol does not inhibit release of MMP-9 from cortical neurons. Overall, these results are consistent with the possibility that while resveratrol reduces potentially maladaptive MMP and TIMP-1 release from activated glia, neuroplasticity-promoting MMP release from neurons is spared. In contrast, resveratrol reduces release of neurocan and brevican, extracellular matrix components that restrict neuroplasticity, from both neurons and glia. These data underscore the diversity of resveratrol's actions with respect to affected cell types and molecular targets and also suggest that further studies may be warranted to determine if its effects on glial MMP release could make it a useful adjunct for AD- and/or anti-amyloid therapy-related damage to the blood brain barrier.

Peripheral immune function and Alzheimer's disease: a living systematic review and critical appraisal

BACKGROUND

A growing body of literature examines the relationship between peripheral immune function and Alzheimer's Disease (AD) in human populations. Our living systematic review summarizes the characteristics and findings of these studies, appraises their quality, and formulates recommendations for future research.

METHODS

We searched the electronic databases PubMed, PsycINFO, and Web of Science, and reviewed references of previous reviews and meta-analyses to identify human studies examining the relationship between any peripheral immune biomarkers and AD up to September 7th, 2023. We examined patterns of reported statistical associations (positive, negative, and null) between each biomarker and AD across studies. Evidence for each biomarker was categorized into four groups based on the proportion of studies reporting different associations: corroborating a positive association with AD, a negative association, a null association, and presenting contradictory findings. A modified Newcastle-Ottawa scale (NOS) was employed to assess the quality of the included studies.

FINDINGS

In total, 286 studies were included in this review. The majority were cross-sectional (n = 245, 85.7%) and hospital-based (n = 248, 86.7%), examining relationships between 187 different peripheral immune biomarkers and AD. Cytokines were the most frequently studied group of peripheral immune biomarkers. Evidence supported a positive association with AD for six biomarkers, including IL-6, IL-1β, IFN-γ, ACT, IL-18, and IL-12, and a negative association for two biomarkers, including lymphocytes and IL-6R. Only a small proportion of included studies (n = 22, 7.7%) were deemed to be of high quality based on quality assessment.

INTERPRETATION

Existing research on peripheral immune function and AD exhibits substantial methodological variations and limitations, with a notable lack of longitudinal, population-based studies investigating a broad range of biomarkers with prospective AD outcomes. The extent and manner in which peripheral immune function can contribute to AD pathophysiology remain open questions. Given the biomarkers that we identified to be associated with AD, we posit that targeting peripheral immune dysregulation may present a promising intervention point to reduce the burden of AD.

Fluid-Based Protein Biomarkers in Traumatic Brain Injury: The View from the Bedside

There has been an explosion of research into biofluid (blood, cerebrospinal fluid, CSF)-based protein biomarkers in traumatic brain injury (TBI) over the past decade. The availability of very large datasets, such as CENTRE-TBI and TRACK-TBI, allows for correlation of blood- and CSF-based molecular (protein), radiological (structural) and clinical (physiological) marker data to adverse clinical outcomes. The quality of a given biomarker has often been framed in relation to the predictive power on the outcome quantified from the area under the Receiver Operating Characteristic (ROC) curve. However, this does not in itself provide clinical utility but reflects a statistical association in any given population between one or more variables and clinical outcome. It is not currently established how to incorporate and integrate biofluid-based biomarker data into patient management because there is no standardized role for such data in clinical decision making. We review the current status of biomarker research and discuss how we can integrate existing markers into current clinical practice and what additional biomarkers do we need to improve diagnoses and to guide therapy and to assess treatment efficacy. Furthermore, we argue for employing machine learning (ML) capabilities to integrate the protein biomarker data with other established, routinely used clinical diagnostic tools, to provide the clinician with actionable information to guide medical intervention.

Proteomic Network Analysis of Alzheimer's Disease Cerebrospinal Fluid Reveals Alterations Associated with APOE ε4 Genotype and Atomoxetine Treatment

Alzheimer's disease (AD) is currently defined at the research level by the aggregation of amyloid-β (Aβ) and tau proteins in brain. While biofluid biomarkers are available to measure Aβ and tau pathology, few biomarkers are available to measure the complex pathophysiology that is associated with these two cardinal neuropathologies. Here we describe the proteomic landscape of cerebrospinal fluid (CSF) changes associated with Aβ and tau pathology in 300 individuals as assessed by two different proteomic technologies-tandem mass tag (TMT) mass spectrometry and SomaScan. Harmonization and integration of both data types allowed for generation of a robust protein co-expression network consisting of 34 modules derived from 5242 protein measurements, including disease-relevant modules associated with autophagy, ubiquitination, endocytosis, and glycolysis. Three modules strongly associated with the apolipoprotein E ε4 (APOE ε4) AD risk genotype mapped to oxidant detoxification, mitogen associated protein kinase (MAPK) signaling, neddylation, and mitochondrial biology, and overlapped with a previously described lipoprotein module in serum. Neddylation and oxidant detoxification/MAPK signaling modules had a negative association with APOE ε4 whereas the mitochondrion module had a positive association with APOE ε4. The directions of association were consistent between CSF and blood in two independent longitudinal cohorts, and altered levels of all three modules in blood were associated with dementia over 20 years prior to diagnosis. Dual-proteomic platform analysis of CSF samples from an AD phase 2 clinical trial of atomoxetine (ATX) demonstrated that abnormal elevations in the glycolysis CSF module-the network module most strongly correlated to cognitive function-were reduced by ATX treatment. Individuals who had more severe glycolytic changes at baseline responded better to ATX. Clustering of individuals based on their CSF proteomic network profiles revealed ten groups that did not cleanly stratify by Aβ and tau status, underscoring the heterogeneity of pathological changes not fully reflected by Aβ and tau. AD biofluid proteomics holds promise for the development of biomarkers that reflect diverse pathologies for use in clinical trials and precision medicine.

The Expression of Major Facilitator Superfamily Domain-Containing Protein2a (Mfsd2a) and Aquaporin 4 Is Altered in the Retinas of a 5xFAD Mouse Model of Alzheimer's Disease

Cerebral amyloid angiopathy (CAA) is characterized by amyloid β (Aβ) accumulation in the blood vessels and is associated with cognitive impairment in Alzheimer's disease (AD). The increased accumulation of Aβ is also present in the retinal blood vessels and a significant correlation between retinal and brain amyloid deposition was demonstrated in living patients and animal AD models. The Aβ accumulation in the retinal blood vessels can be the result of impaired transcytosis and/or the dysfunctional ocular glymphatic system in AD and during aging. We analyzed the changes in the mRNA and protein expression of major facilitator superfamily domain-containing protein2a (Mfsd2a), the major regulator of transcytosis, and of Aquaporin4 (Aqp4), the key player implicated in the functioning of the glymphatic system, in the retinas of 4- and 12-month-old WT and 5xFAD female mice. A strong decrease in the Mfsd2a mRNA and protein expression was observed in the 4 M and 12 M 5xFAD and 12 M WT retinas. The increase in the expression of srebp1-c could be at least partially responsible for the Mfsd2a decrease in the 4 M 5xFAD retinas. The decrease in the pericyte (CD13+) coverage of retinal blood vessels in the 4 M and 12 M 5xFAD retinas and in the 12 M WT retinas suggests that pericyte loss could be associated with the Mfsd2a downregulation in these experimental groups. The observed increase in Aqp4 expression in 4 M and 12 M 5xFAD and 12 M WT retinas accompanied by the decreased perivascular Aqp4 expression is indicative of the impaired glymphatic system. The findings in this study reveal the impaired Mfsd2a and Aqp4 expression and Aqp4 perivascular mislocalization in retinal blood vessels during physiological (WT) and pathological (5xFAD) aging, indicating their importance as putative targets for the development of new treatments that can improve the regulation of transcytosis or the function of the glymphatic system.