Plasma proteome-wide analysis of cerebral small vessel disease identifies novel biomarkers and disease pathways.

Cerebral small vessel disease (SVD), as defined by neuroimaging characteristics such as white matter hyperintensities (WMHs), cerebral microhemorrhages (CMHs), and lacunar infarcts, is highly prevalent and has been associated with dementia risk and other clinical sequelae. Although conditions such as hypertension are known to contribute to SVD, little is known about the diverse set of subclinical biological processes and molecular mediators that may also influence the development and progression of SVD. To better understand the mechanisms underlying SVD and to identify novel SVD biomarkers, we used a large-scale proteomic platform to relate 4,877 plasma proteins to MRI-defined SVD characteristics within 1,508 participants of the Atherosclerosis Risk in Communities (ARIC) Study cohort. Our proteome-wide analysis of older adults (mean age: 76) identified 13 WMH-associated plasma proteins involved in synaptic function, endothelial integrity, and angiogenesis, two of which remained associated with late-life WMH volume when measured nearly 20 years earlier, during midlife. We replicated the relationship between 9 candidate proteins and WMH volume in one or more external cohorts; we found that 11 of the 13 proteins were associated with risk for future dementia; and we leveraged publicly available proteomic data from brain tissue to demonstrate that a subset of WMH-associated proteins was differentially expressed in the context of cerebral atherosclerosis, pathologically-defined Alzheimer's disease, and cognitive decline. Bidirectional two-sample Mendelian randomization analyses examined the causal relationships between candidate proteins and WMH volume, while pathway and network analyses identified discrete biological processes (lipid/cholesterol metabolism, NF-kB signaling, hemostasis) associated with distinct forms of SVD. Finally, we synthesized these findings to identify two plasma proteins, oligodendrocyte myelin glycoprotein (OMG) and neuronal pentraxin receptor (NPTXR), as top candidate biomarkers for elevated WMH volume and its clinical manifestations.

Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. METHOD: Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. RESULTS: Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. CONCLUSIONS: This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways.

SRRM4-mediated REST to REST4 dysregulation promotes tumor growth and neural adaptation in breast cancer leading to brain metastasis.

BACKGROUND: Effective control of brain metastasis remains an urgent clinical need due a limited understanding of the mechanisms driving it. Although the gain of neuro-adaptive attributes in breast-to-brain metastases (BBMs) has been described, the mechanisms that govern this neural acclimation and the resulting brain metastasis competency are poorly understood. Herein, we define the role of neural-specific splicing factor Serine/Arginine Repetitive Matrix Protein 4 (SRRM4) in regulating microenvironmental adaptation and brain metastasis colonization in breast cancer cells. METHODS: Utilizing pure neuronal cultures and brain-naive and patient-derived BM tumor cells, along with in vivo tumor modeling, we surveyed the early induction of mediators of neural acclimation in tumor cells. RESULTS: When SRRM4 is overexpressed in systemic breast cancer cells, there is enhanced BBM leading to poorer overall survival in vivo. Concomitantly, SRRM4 knockdown expression does not provide any advantage in central nervous system metastasis. In addition, reducing SRRM4 expression in breast cancer cells slows down proliferation and increases resistance to chemotherapy. Conversely, when SRRM4/REST4 levels are elevated, tumor cell growth is maintained even in nutrient-deprived conditions. In neuronal coculture, decreasing SRRM4 expression in breast cancer cells impairs their ability to adapt to the brain microenvironment, while increasing SRRM4/RE-1 Silencing Transcription Factor (REST4) levels leads to greater expression of neurotransmitter and synaptic signaling mediators and a significant colonization advantage. CONCLUSIONS: Collectively, our findings identify SRRM4 as a regulator of brain metastasis colonization, and a potential therapeutic target in breast cancer.

Temporal transcriptional control of neural induction in human induced pluripotent stem cells.

Introduction: Neural induction of human induced pluripotent stem cells represents a critical switch in cell state during which pluripotency is lost and commitment to a neural lineage is initiated. Although many of the key transcription factors involved in neural induction are known, we know little of the temporal and causal relationships that are required for this state transition. Methods: Here, we have carried out a longitudinal analysis of the transcriptome of human iPSCs undergoing neural induction. Using the temporal relationships between the changing profile of key transcription factors and subsequent changes in their target gene expression profiles, we have identified distinct functional modules operative throughout neural induction. Results: In addition to modules that govern loss of pluripotency and gain of neural ectoderm identity, we discover other modules governing cell cycle and metabolism. Strikingly, some of these functional modules are retained throughout neural induction, even though the gene membership of the module changes. Systems analysis identifies other modules associated with cell fate commitment, genome integrity, stress response and lineage specification. We then focussed on OTX2, one of the most precociously activated transcription factors during neural induction. Our temporal analysis of OTX2 target gene expression identified several OTX2 regulated gene modules representing protein remodelling, RNA splicing and RNA processing. Further CRISPRi inhibition of OTX2 prior to neural induction promotes an accelerated loss of pluripotency and a precocious and aberrant neural induction disrupting some of the previously identified modules. Discussion: We infer that OTX2 has a diverse role during neural induction and regulates many of the biological processes that are required for loss of pluripotency and gain of neural identity. This dynamical analysis of transcriptional changes provides a unique perspective of the widespread remodelling of the cell machinery that occurs during neural induction of human iPSCs.

Multiomics profiling of human plasma and cerebrospinal fluid reveals ATN-derived networks and highlights causal links in Alzheimer's disease.

INTRODUCTION: This study employed an integrative system and causal inference approach to explore molecular signatures in blood and CSF, the amyloid/tau/neurodegeneration [AT(N)] framework, mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD), and genetic risk for AD. METHODS: Using the European Medical Information Framework (EMIF)-AD cohort, we measured 696 proteins in cerebrospinal fluid (n = 371), 4001 proteins in plasma (n = 972), 611 metabolites in plasma (n = 696), and genotyped whole-blood (7,778,465 autosomal single nucleotide epolymorphisms, n = 936). We investigated associations: molecular modules to AT(N), module hubs with AD Polygenic Risk scores and APOE4 genotypes, molecular hubs to MCI conversion and probed for causality with AD using Mendelian randomization (MR). RESULTS: AT(N) framework associated with protein and lipid hubs. In plasma, Proprotein Convertase Subtilisin/Kexin Type 7 showed evidence for causal associations with AD. AD was causally associated with Reticulocalbin 2 and sphingomyelins, an association driven by the APOE isoform. DISCUSSION: This study reveals multi-omics networks associated with AT(N) and causal AD molecular candidates.

Predicting AT(N) pathologies in Alzheimer's disease from blood-based proteomic data using neural networks.

Background and objective: Blood-based biomarkers represent a promising approach to help identify early Alzheimer's disease (AD). Previous research has applied traditional machine learning (ML) to analyze plasma omics data and search for potential biomarkers, but the most modern ML methods based on deep learning has however been scarcely explored. In the current study, we aim to harness the power of state-of-the-art deep learning neural networks (NNs) to identify plasma proteins that predict amyloid, tau, and neurodegeneration (AT[N]) pathologies in AD. Methods: We measured 3,635 proteins using SOMAscan in 881 participants from the European Medical Information Framework for AD Multimodal Biomarker Discovery study (EMIF-AD MBD). Participants underwent measurements of brain amyloid ß (Aß) burden, phosphorylated tau (p-tau) burden, and total tau (t-tau) burden to determine their AT(N) statuses. We ranked proteins by their association with Aß, p-tau, t-tau, and AT(N), and fed the top 100 proteins along with age and apolipoprotein E (APOE) status into NN classifiers as input features to predict these four outcomes relevant to AD. We compared NN performance of using proteins, age, and APOE genotype with performance of using age and APOE status alone to identify protein panels that optimally improved the prediction over these main risk factors. Proteins that improved the prediction for each outcome were aggregated and nominated for pathway enrichment and protein-protein interaction enrichment analysis. Results: Age and APOE alone predicted Aß, p-tau, t-tau, and AT(N) burden with area under the curve (AUC) scores of 0.748, 0.662, 0.710, and 0.795. The addition of proteins significantly improved AUCs to 0.782, 0.674, 0.734, and 0.831, respectively. The identified proteins were enriched in five clusters of AD-associated pathways including human immunodeficiency virus 1 infection, p53 signaling pathway, and phosphoinositide-3-kinase-protein kinase B/Akt signaling pathway. Conclusion: Combined with age and APOE genotype, the proteins identified have the potential to serve as blood-based biomarkers for AD and await validation in future studies. While the NNs did not achieve better scores than the support vector machine model used in our previous study, their performances were likely limited by small sample size.

Neurons derived from individual early Alzheimer's disease patients reflect their clinical vulnerability.

Establishing preclinical models of Alzheimer's disease that predict clinical outcomes remains a critically important, yet to date not fully realized, goal. Models derived from human cells offer considerable advantages over non-human models, including the potential to reflect some of the inter-individual differences that are apparent in patients. Here we report an approach using induced pluripotent stem cell-derived cortical neurons from people with early symptomatic Alzheimer's disease where we sought a match between individual disease characteristics in the cells with analogous characteristics in the people from whom they were derived. We show that the response to amyloid-ß burden in life, as measured by cognitive decline and brain activity levels, varies between individuals and this vulnerability rating correlates with the individual cellular vulnerability to extrinsic amyloid-ß in vitro as measured by synapse loss and function. Our findings indicate that patient-induced pluripotent stem cell-derived cortical neurons not only present key aspects of Alzheimer's disease pathology but also reflect key aspects of the clinical phenotypes of the same patients. Cellular models that reflect an individual's in-life clinical vulnerability thus represent a tractable method of Alzheimer's disease modelling using clinical data in combination with cellular phenotypes.

Glycosylated clusterin species facilitate Aß toxicity in human neurons.

Clusterin (CLU) is one of the most significant genetic risk factors for late onset Alzheimer's disease (AD). However, the mechanisms by which CLU contributes to AD development and pathogenesis remain unclear. Studies have demonstrated that the trafficking and localisation of glycosylated CLU proteins is altered by CLU-AD mutations and amyloid-ß (Aß), which may contribute to AD pathogenesis. However, the roles of non-glycosylated and glycosylated CLU proteins in mediating Aß toxicity have not been studied in human neurons. iPSCs with altered CLU trafficking were generated following the removal of CLU exon 2 by CRISPR/Cas9 gene editing. Neurons were generated from control (CTR) and exon 2 -/- edited iPSCs and were incubated with aggregated Aß peptides. Aß induced changes in cell death and neurite length were quantified to determine if altered CLU protein trafficking influenced neuronal sensitivity to Aß. Finally, RNA-Seq analysis was performed to identify key transcriptomic differences between CLU exon 2 -/- and CTR neurons. The removal of CLU exon 2, and the endoplasmic reticulum (ER)-signal peptide located within, abolished the presence of glycosylated CLU and increased the abundance of intracellular, non-glycosylated CLU. While non-glycosylated CLU levels were unaltered by Aß25-35 treatment, the trafficking of glycosylated CLU was altered in control but not exon 2 -/- neurons. The latter also displayed partial protection against Aß-induced cell death and neurite retraction. Transcriptome analysis identified downregulation of multiple extracellular matrix (ECM) related genes in exon 2 -/- neurons, potentially contributing to their reduced sensitivity to Aß toxicity. This study identifies a crucial role of glycosylated CLU in facilitating Aß toxicity in human neurons. The loss of these proteins reduced both, cell death and neurite damage, two key consequences of Aß toxicity identified in the AD brain. Strikingly, transcriptomic differences between exon 2 -/- and control neurons were small, but a significant and consistent downregulation of ECM genes and pathways was identified in exon 2 -/- neurons. This may contribute to the reduced sensitivity of these neurons to Aß, providing new mechanistic insights into Aß pathologies and therapeutic targets for AD.

Repressor element 1-silencing transcription factor deficiency yields profound hearing loss through Kv7.4 channel upsurge in auditory neurons and hair cells.

Repressor element 1-silencing transcription factor (REST) is a transcriptional repressor that recognizes neuron-restrictive silencer elements in the mammalian genomes in a tissue- and cell-specific manner. The identity of REST target genes and molecular details of how REST regulates them are emerging. We performed conditional null deletion of Rest (cKO), mainly restricted to murine hair cells (HCs) and auditory neurons (aka spiral ganglion neurons [SGNs]). Null inactivation of full-length REST did not affect the development of normal HCs and SGNs but manifested as progressive hearing loss in adult mice. We found that the inactivation of REST resulted in an increased abundance of Kv7.4 channels at the transcript, protein, and functional levels. Specifically, we found that SGNs and HCs from Rest cKO mice displayed increased Kv7.4 expression and augmented Kv7 currents; SGN's excitability was also significantly reduced. Administration of a compound with Kv7.4 channel activator activity, fasudil, recapitulated progressive hearing loss in mice. In contrast, inhibition of the Kv7 channels by XE991 rescued the auditory phenotype of Rest cKO mice. Previous studies identified some loss-of-function mutations within the Kv7.4-coding gene, Kcnq4, as a causative factor for progressive hearing loss in mice and humans. Thus, the findings reveal that a critical homeostatic Kv7.4 channel level is required for proper auditory functions.

Identification of plasma proteins relating to brain neurodegeneration and vascular pathology in cognitively normal individuals.

INTRODUCTION: This study aims to first discover plasma proteomic biomarkers relating to neurodegeneration (N) and vascular (V) damage in cognitively normal individuals and second to discover proteins mediating sex-related difference in N and V pathology. METHODS: Five thousand and thirty-two plasma proteins were measured in 1061 cognitively normal individuals (628 females and 433 males), nearly 90% of whom had magnetic resonance imaging measures of hippocampal volume (as N) and white matter hyperintensities (as V). RESULTS: Differential protein expression analysis and co-expression network analysis revealed different proteins and modules associated with N and V, respectively. Furthermore, causal mediation analysis revealed four proteins mediated sex-related difference in N and one protein mediated such difference in V damage. DISCUSSION: Once validated, the identified proteins could help to select cognitively normal individuals with N and V pathology for Alzheimer's disease clinical trials and provide targets for further mechanistic studies on brain sex differences, leading to sex-specific therapeutic strategies.

Plasma Proteomic Biomarkers Relating to Alzheimer's Disease: A Meta-Analysis Based on Our Own Studies.

Background and Objective: Plasma biomarkers for the diagnosis and stratification of Alzheimer's disease (AD) are intensively sought. However, no plasma markers are well established so far for AD diagnosis. Our group has identified and validated various blood-based proteomic biomarkers relating to AD pathology in multiple cohorts. The study aims to conduct a meta-analysis based on our own studies to systematically assess the diagnostic performance of our previously identified blood biomarkers. Methods: To do this, we included seven studies that our group has conducted during the last decade. These studies used either Luminex xMAP or ELISA to measure proteomic biomarkers. As proteins measured in these studies differed, we selected protein based on the criteria that it must be measured in at least four studies. We then examined biomarker performance using random-effect meta-analyses based on the mean difference between biomarker concentrations in AD and controls (CTL), AD and mild cognitive impairment (MCI), MCI, and CTL as well as MCI converted to dementia (MCIc) and non-converted (MCInc) individuals. Results: An overall of 2,879 subjects were retrieved for meta-analysis including 1,053 CTL, 895 MCI, 882 AD, and 49 frontotemporal dementia (FTD) patients. Six proteins were measured in at least four studies and were chosen for meta-analyses for AD diagnosis. Of them, three proteins had significant difference between AD and controls, among which alpha-2-macroglobulin (A2M) and ficolin-2 (FCN2) increased in AD while fibrinogen gamma chain (FGG) decreased in AD compared to CTL. Furthermore, FGG significantly increased in FTD compared to AD. None of the proteins passed the significance between AD and MCI, or MCI and CTL, or MCIc and MCInc, although complement component 4 (CC4) tended to increase in MCIc individuals compared to MCInc. Conclusions: The results suggest that A2M, FCN2, and FGG are promising biomarkers to discriminate AD patients from controls, which are worthy of further validation.

Replication study of plasma proteins relating to Alzheimer's pathology.

INTRODUCTION: This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis. METHODS: Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively. RESULTS: Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis. DISCUSSION: Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis.

High Blood Pressure and Risk of Dementia: A Two-Sample Mendelian Randomization Study in the UK Biobank.

BACKGROUND: Findings from randomized controlled trials have yielded conflicting results on the association between blood pressure (BP) and dementia traits. We tested the hypothesis that a causal relationship exists between systolic BP (SBP) and/or diastolic BP (DBP) and risk of Alzheimer's disease (AD). METHODS: We performed a generalized summary Mendelian randomization (GSMR) analysis using summary statistics of a genome-wide association study meta-analysis of 299,024 individuals of SBP or DBP as exposure variables against three different outcomes: 1) AD diagnosis (International Genomics of Alzheimer's Project), 2) maternal family history of AD (UK Biobank), and 3) paternal family history of AD (UK Biobank). Finally, a combined meta-analysis of 368,440 individuals that included these three summary statistics was used as final outcome. RESULTS: GSMR applied to the International Genomics of Alzheimer's Project dataset revealed a significant effect of high SBP lowering the risk of AD (ßGSMR = -0.19, p = .04). GSMR applied to the maternal family history of AD UK Biobank dataset (SBP [ßGSMR = -0.12, p = .02], DBP [ßGSMR = -0.10, p = .05]) and to the paternal family history of AD UK Biobank dataset (SBP [ßGSMR = -0.16, p = .02], DBP [ßGSMR = -0.24, p = 7.4 × 10-4]) showed the same effect. A subsequent combined meta-analysis confirmed the overall significant effect for the other SBP analyses (ßGSMR = -0.14, p = .03). The DBP analysis in the combined meta-analysis also confirmed a DBP effect on AD (ßGSMR = -0.14, p = .03). CONCLUSIONS: A causal effect exists between high BP and a reduced late-life risk of AD. The results were obtained through careful consideration of confounding factors and the application of complementary MR methods on independent cohorts.

Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer's Disease Pathology.

BACKGROUND: Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown. OBJECTIVE: We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes. METHODS: We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677). RESULTS: We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts. CONCLUSIONS: Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo.

Validation of Plasma Proteomic Biomarkers Relating to Brain Amyloid Burden in the EMIF-Alzheimer's Disease Multimodal Biomarker Discovery Cohort.

We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ɛ4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure.

Δ9-tetrahydrocannabinol and 2-AG decreases neurite outgrowth and differentially affects ERK1/2 and Akt signaling in hiPSC-derived cortical neurons.

Endocannabinoids regulate different aspects of neurodevelopment. In utero exposure to the exogenous psychoactive cannabinoid Δ9-tetrahydrocannabinol (Δ9-THC), has been linked with abnormal cortical development in animal models. However, much less is known about the actions of endocannabinoids in human neurons. Here we investigated the effect of the endocannabinoid 2-arachidonoyl glycerol (2AG) and Δ9-THC on the development of neuronal morphology and activation of signaling kinases, in cortical neurons derived from human induced pluripotent stem cells (hiPSCs). Our data indicate that the cannabinoid type 1 receptor (CB1R), but not the cannabinoid 2 receptor (CB2R), GPR55 or TRPV1 receptors, is expressed in young, immature hiPSC-derived cortical neurons. Consistent with previous reports, 2AG and Δ9-THC negatively regulated neurite outgrowth. Interestingly, acute exposure to both 2AG and Δ9-THC inhibited phosphorylation of serine/threonine kinase extracellular signal-regulated protein kinases (ERK1/2), whereas Δ9-THC also reduced phosphorylation of Akt (aka PKB). Moreover, the CB1R inverse agonist SR 141716A attenuated the decrease in neurite outgrowth and ERK1/2 phosphorylation induced by 2AG and Δ9-THC. Taken together, our data suggest that hiPSC-derived cortical neurons express CB1Rs and are responsive to exogenous cannabinoids. Thus, hiPSC-neurons may represent a good cellular model for investigating the role of the endocannabinoid system in regulating cellular processes in developing human neurons.

Discovery and validation of plasma proteomic biomarkers relating to brain amyloid burden by SOMAscan assay.

INTRODUCTION: Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins. METHODS: 4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid. RESULTS: A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) ε4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization. DISCUSSION: The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition.

Repressor element 1-silencing transcription factor drives the development of chronic pain states.

Chronic pain is an unmet clinical problem with vast individual, societal, and economic impact. Pathologic activity of the peripheral somatosensory afferents is one of the major drivers of chronic pain. This overexcitable state of somatosensory neurons is, in part, produced by the dysregulation of genes controlling neuronal excitability. Despite intense research, a unifying theory behind neuropathic remodelling is lacking. Here, we show that transcriptional suppressor, repressor element 1-silencing transcription factor (REST; neuron-restrictive silencing factor, NRSF), is necessary and sufficient for the development of hyperalgesic state after chronic nerve injury or inflammation. Viral overexpression of REST in mouse dorsal root ganglion (DRG) induced prominent mechanical and thermal hyperalgesia in vivo. Sensory neuron-specific, inducible Rest knockout prevented the development of such hyperalgesic state in 3 different chronic pain models. Genetic deletion of Rest reverted injury-induced hyperalgesia. Moreover, viral overexpression of REST in the same neurons in which its gene has been genetically deleted restored neuropathic hyperalgesia. Finally, sensory neuron specific Rest knockout prevented injury-induced downregulation of REST target genes in DRG neurons. This work identified REST as a major regulator of peripheral somatosensory neuron remodelling leading to chronic pain. The findings might help to develop a novel therapeutic approache to combat chronic pain.

Clusterin in Alzheimer's Disease: Mechanisms, Genetics, and Lessons From Other Pathologies.

Clusterin (CLU) or APOJ is a multifunctional glycoprotein that has been implicated in several physiological and pathological states, including Alzheimer's disease (AD). With a prominent extracellular chaperone function, additional roles have been discussed for clusterin, including lipid transport and immune modulation, and it is involved in pathways common to several diseases such as cell death and survival, oxidative stress, and proteotoxic stress. Although clusterin is normally a secreted protein, it has also been found intracellularly under certain stress conditions. Multiple hypotheses have been proposed regarding the origin of intracellular clusterin, including specific biogenic processes leading to alternative transcripts and protein isoforms, but these lines of research are incomplete and contradictory. Current consensus is that intracellular clusterin is most likely to have exited the secretory pathway at some point or to have re-entered the cell after secretion. Clusterin's relationship with amyloid beta (Aß) has been of great interest to the AD field, including clusterin's apparent role in altering Aß aggregation and/or clearance. Additionally, clusterin has been more recently identified as a mediator of Aß toxicity, as evidenced by the neuroprotective effect of CLU knockdown and knockout in rodent and human iPSC-derived neurons. CLU is also the third most significant genetic risk factor for late onset AD and several variants have been identified in CLU. Although the exact contribution of these variants to altered AD risk is unclear, some have been linked to altered CLU expression at both mRNA and protein levels, altered cognitive and memory function, and altered brain structure. The apparent complexity of clusterin's biogenesis, the lack of clarity over the origin of the intracellular clusterin species, and the number of pathophysiological functions attributed to clusterin have all contributed to the challenge of understanding the role of clusterin in AD pathophysiology. Here, we highlight clusterin's relevance to AD by discussing the evidence linking clusterin to AD, as well as drawing parallels on how the role of clusterin in other diseases and pathways may help us understand its biological function(s) in association with AD.

Transcriptional and epigenetic mechanisms underlying astrocyte identity.

Astrocytes play a significant role in coordinating neural development and provide critical support for the function of the CNS. They possess important adaptation capacities that range from their transition towards reactive astrocytes to their ability to undergo reprogramming, thereby revealing their potential to retain latent features of neural progenitor cells. We propose that the mechanisms underlying reactive astrogliosis or astrocyte reprogramming provide an opportunity for initiating neuronal regeneration, a process that is notably reduced in the mammalian nervous system throughout evolution. Conversely, this plasticity may also affect normal astrocytic functions resulting in pathologies ranging from neurodevelopmental disorders to neurodegenerative diseases and brain tumors. We postulate that epigenetic mechanisms linking extrinsic cues and intrinsic transcriptional programs are key factors to maintain astrocyte identity and function, and critically, to control the balance of regenerative and degenerative activity. Here, we will review the main evidences supporting this concept. We propose that unravelling the epigenetic and transcriptional mechanisms underlying the acquisition of astrocyte identity and plasticity, as well as understanding how these processes are modulated by the local microenvironment under specific threatening or pathological conditions, may pave the way to new therapeutic avenues for several neurological disorders including neurodegenerative diseases and brain tumors of astrocytic lineage.