Network-Driven Proteogenomics Unveils an Aging-Related Imbalance in the Olfactory IκBα-NFκB p65 Complex Functionality in Tg2576 Alzheimer's Disease Mouse Model

Olfactory Dysfunction and Alzheimer's Disease: A Review

 Alzheimer's disease is the most common cause of dementia, and it is one of the leading causes of death globally. Identification and validation of biomarkers that herald the onset and progression of Alzheimer's disease is of paramount importance for early reliable diagnosis and effective pharmacological therapy commencement. A substantial body of evidence has emerged demonstrating that olfactory dysfunction is a preclinical symptom of neurodegenerative diseases including Alzheimer's disease. While a correlation between olfactory dysfunction and Alzheimer's disease onset and progression in humans exists, the mechanism underlying this relationship remains unknown. The aim of this article is to review the current state of knowledge regarding the range of potential factors that may contribute to the development of Alzheimer's disease-related olfactory dysfunction. This review predominantly focuses on genetic mutations associated with Alzheimer's disease including amyloid-β protein precursor, presenilin 1 and 2, and apolipoprotein E mutations, that may (in varying ways) drive the cellular events that lead to and sustain olfactory dysfunction.

Pathway-based integration of multi-omics data reveals lipidomics alterations validated in an Alzheimer's disease mouse model and risk loci carriers

Alzheimer's disease (AD) is a highly prevalent neurodegenerative disorder. Despite increasing evidence of the importance of metabolic dysregulation in AD, the underlying metabolic changes that may impact amyloid plaque formation are not understood, particularly for late-onset AD. This study analyzed genome-wide association studies (GWAS), transcriptomics, and proteomics data obtained from several data repositories to obtain differentially expressed (DE) multi-omics elements in mouse models of AD. We characterized the metabolic modulation in these data sets using gene ontology, transcription factor, pathway, and cell-type enrichment analyses. A predicted lipid signature was extracted from genome-scale metabolic networks (GSMN) and subsequently validated in a lipidomic data set derived from cortical tissue of ABCA-7 null mice, a mouse model of one of the genes associated with late-onset AD. Moreover, a metabolome-wide association study (MWAS) was performed to further characterize the association between dysregulated lipid metabolism in human blood serum and genes associated with AD risk. We found 203 DE transcripts, 164 DE proteins, and 58 DE GWAS-derived mouse orthologs associated with significantly enriched metabolic biological processes. Lipid and bioenergetic metabolic pathways were significantly over-represented across the AD multi-omics data sets. Microglia and astrocytes were significantly enriched in the lipid-predominant AD-metabolic transcriptome. We also extracted a predicted lipid signature that was validated and robustly modeled class separation in the ABCA7 mice cortical lipidome, with 11 of these lipid species exhibiting statistically significant modulations. MWAS revealed 298 AD single nucleotide polymorphisms-metabolite associations, of which 70% corresponded to lipid classes. These results support the importance of lipid metabolism dysregulation in AD and highlight the suitability of mapping AD multi-omics data into GSMNs to identify metabolic alterations.

Pathway-based integration of multi-omics data reveals lipidomics alterations validated in an Alzheimer's disease mouse model and risk loci carriers

Alzheimer's disease (AD) is a highly prevalent neurodegenerative disorder. Despite increasing evidence of the importance of metabolic dysregulation in AD, the underlying metabolic changes that may impact amyloid plaque formation are not understood, particularly for late-onset AD. This study analyzed genome-wide association studies (GWAS), transcriptomics, and proteomics data obtained from several data repositories to obtain differentially expressed (DE) multi-omics elements in mouse models of AD. We characterized the metabolic modulation in these data sets using gene ontology, transcription factor, pathway, and cell-type enrichment analyses. A predicted lipid signature was extracted from genome-scale metabolic networks (GSMN) and subsequently validated in a lipidomic data set derived from cortical tissue of ABCA-7 null mice, a mouse model of one of the genes associated with late-onset AD. Moreover, a metabolome-wide association study (MWAS) was performed to further characterize the association between dysregulated lipid metabolism in human blood serum and genes associated with AD risk. We found 203 DE transcripts, 164 DE proteins, and 58 DE GWAS-derived mouse orthologs associated with significantly enriched metabolic biological processes. Lipid and bioenergetic metabolic pathways were significantly over-represented across the AD multi-omics data sets. Microglia and astrocytes were significantly enriched in the lipid-predominant AD-metabolic transcriptome. We also extracted a predicted lipid signature that was validated and robustly modeled class separation in the ABCA7 mice cortical lipidome, with 11 of these lipid species exhibiting statistically significant modulations. MWAS revealed 298 AD single nucleotide polymorphisms-metabolite associations, of which 70% corresponded to lipid classes. These results support the importance of lipid metabolism dysregulation in AD and highlight the suitability of mapping AD multi-omics data into GSMNs to identify metabolic alterations.

Human microRNA-4433 (hsa-miR-4443) Targets 18 Genes to be a Risk Factor of Neurodegenerative Diseases

BACKGROUND

Neurodegenerative diseases, such as Alzheimer's disease patients (AD), Huntington's disease (HD) and Parkinson's disease (PD), are common causes of morbidity, mortality, and cognitive impairment in older adults.

OBJECTIVE

We aimed to understand the transcriptome characteristics of the cortex of neurodegenerative diseases and to provide an insight into the target genes of differently expressed microRNAs in the occurrence and development of neurodegenerative diseases.

METHODS

The Limma package of R software was used to analyze GSE33000, GSE157239, GSE64977 and GSE72962 datasets to identify the differentially expressed genes (DEGs) and microRNAs in the cortex of neurodegenerative diseases. Bioinformatics methods, such as GO enrichment analysis, KEGG enrichment analysis and gene interaction network analysis, were used to explore the biological functions of DEGs. Weighted gene co-expression network analysis (WGCNA) was used to cluster DEGs into modules. RNA22, miRDB, miRNet 2.0 and TargetScan7 databases were performed to predict the target genes of microRNAs.

RESULTS

Among 310 Alzheimer's disease (AD) patients, 157 Huntington's disease (HD) patients and 157 non-demented control (Con) individuals, 214 co-DEGs were identified. Those co-DEGs were filtered into 2 different interaction network complexes, representing immune-related genes and synapserelated genes. The WGCNA results identified five modules: yellow, blue, green, turquoise, and brown. Most of the co-DEGs were clustered into the turquoise module and blue module, which respectively regulated synapse-related function and immune-related function. In addition, human microRNA-4433 (hsa-miR-4443), which targets 18 co-DEGs, was the only 1 co-up-regulated microRNA identified in the cortex of neurodegenerative diseases.

CONCLUSION

214 DEGs and 5 modules regulate the immune-related and synapse-related function of the cortex in neurodegenerative diseases. Hsa-miR-4443 targets 18 co-DEGs and may be a potential molecular mechanism in neurodegenerative diseases' occurrence and development.

Small Heat Shock Protein 22 Improves Cognition and Learning in the Tauopathic Brain

The microtubule-associated protein tau pathologically accumulates and aggregates in Alzheimer's disease (AD) and other tauopathies, leading to cognitive dysfunction and neuronal loss. Molecular chaperones, like small heat-shock proteins (sHsps), can help deter the accumulation of misfolded proteins, such as tau. Here, we tested the hypothesis that the overexpression of wild-type Hsp22 (wtHsp22) and its phosphomimetic (S24,57D) Hsp22 mutant (mtHsp22) could slow tau accumulation and preserve memory in a murine model of tauopathy, rTg4510. Our results show that Hsp22 protected against deficits in synaptic plasticity and cognition in the tauopathic brain. However, we did not detect a significant change in tau phosphorylation or levels in these mice. This led us to hypothesize that the functional benefit was realized through the restoration of dysfunctional pathways in hippocampi of tau transgenic mice since no significant benefit was measured in non-transgenic mice expressing wtHsp22 or mtHsp22. To identify these pathways, we performed mass spectrometry of tissue lysates from the injection site. Overall, our data reveal that Hsp22 overexpression in neurons promotes synaptic plasticity by regulating canonical pathways and upstream regulators that have been characterized as potential AD markers and synaptogenesis regulators, like EIF4E and NFKBIA.

Smelling the Dark Proteome: Functional Characterization of PITH Domain-Containing Protein 1 (C1orf128) in Olfactory Metabolism

The Human Proteome Project (HPP) consortium aims to functionally characterize the dark proteome. On the basis of the relevance of olfaction in early neurodegeneration, we have analyzed the dark proteome using data mining in public resources and omics data sets derived from the human olfactory system. Multiple dark proteins localize at synaptic terminals and may be involved in amyloidopathies such as Alzheimer's disease (AD). We have characterized the dark PITH domain-containing protein 1 (PITHD1) in olfactory metabolism using bioinformatics, proteomics, in vitro and in vivo studies, and neuropathology. PITHD1^-/- mice exhibit olfactory bulb (OB) proteome changes related to synaptic transmission, cognition, and memory. OB PITHD1 expression increases with age in wild-type (WT) mice and decreases in Tg2576 AD mice at late stages. The analysis across 6 neurological disorders reveals that olfactory tract (OT) PITHD1 is specifically upregulated in human AD. Stimulation of olfactory neuroepithelial (ON) cells with PITHD1 alters the ON phosphoproteome, modifies the proliferation rate, and induces a pro-inflammatory phenotype. This workflow applied by the Spanish C-HPP and Human Brain Proteome Project (HBPP) teams across the ON-OB-OT axis can be adapted as a guidance to decipher functional features of dark proteins. Data are available via ProteomeXchange with identifiers PXD018784 and PXD021634.

Proteomic Characterization of the Olfactory Molecular Imbalance in Dementia with Lewy Bodies

Olfactory dysfunction is one of the prodromal symptoms in dementia with Lewy bodies (DLB). However, the molecular pathogenesis associated with decreased smell function remains largely undeciphered. We generated quantitative proteome maps to detect molecular alterations in olfactory bulbs (OB) derived from DLB subjects compared to neurologically intact controls. A total of 3214 olfactory proteins were quantified, and 99 proteins showed significant alterations in DLB cases. Protein interaction networks disrupted in DLB indicated an imbalance in translation and the synaptic vesicle cycle. These alterations were accompanied by alterations in AKT/MAPK/SEK1/p38 MAPK signaling pathways that showed a distinct expression profile across the OB–olfactory tract (OT) axis. Taken together, our data partially reflect the missing links in the biochemical understanding of olfactory dysfunction in DLB.

The human olfactory system in two proteinopathies: Alzheimer's and Parkinson's diseases

Alzheimer's and Parkinson's diseases are the most prevalent neurodegenerative disorders. Their etiologies are idiopathic, and treatments are symptomatic and orientated towards cognitive or motor deficits. Neuropathologically, both are proteinopathies with pathological aggregates (plaques of amyloid-β peptide and neurofibrillary tangles of tau protein in Alzheimer's disease, and Lewy bodies mostly composed of α-synuclein in Parkinson's disease). These deposits appear in the nervous system in a predictable and accumulative sequence with six neuropathological stages. Both disorders present a long prodromal period, characterized by preclinical signs including hyposmia. Interestingly, the olfactory system, particularly the anterior olfactory nucleus, is initially and preferentially affected by the pathology. Cerebral atrophy revealed by magnetic resonance imaging must be complemented by histological analyses to ascertain whether neuronal and/or glial loss or neuropil remodeling are responsible for volumetric changes. It has been proposed that these proteinopathies could act in a prion-like manner in which a misfolded protein would be able to force native proteins into pathogenic folding (seeding), which then propagates through neurons and glia (spreading). Existing data have been examined to establish why some neuronal populations are vulnerable while others are resistant to pathology and to what extent glia prevent and/or facilitate proteinopathy spreading. Connectomic approaches reveal a number of hubs in the olfactory system (anterior olfactory nucleus, olfactory entorhinal cortex and cortical amygdala) that are key interconnectors with the main hubs (the entorhinal-hippocampal-cortical and amygdala-dorsal motor vagal nucleus) of network dysfunction in Alzheimer's and Parkinson's diseases.

Early-Onset Molecular Derangements in the Olfactory Bulb of Tg2576 Mice: Novel Insights Into the Stress-Responsive Olfactory Kinase Dynamics in Alzheimer's Disease

The olfactory bulb (OB) is the first processing station in the olfactory pathway. Despite smell impairment, which is considered an early event in Alzheimer’s disease (AD), little is known about the initial molecular disturbances that accompany the AD development at olfactory level. We have interrogated the time-dependent OB molecular landscape in Tg2576 AD mice prior to the appearance of neuropathological amyloid plaques (2-, and 6-month-old), using combinatorial omics analysis. The metabolic modulation induced by overproduction of human mutated amyloid precursor protein (APP) clearly differs between both time points. Besides the progressive perturbation of the APP interactome, functional network analysis unveiled an inverse regulation of downstream extracellular signal-regulated kinase (ERK1/2), and p38 mitogen-activated protein kinase (MAPK) routes in 2-month-old Tg2576 mice with respect to wild-type (WT) mice. In contrast, Akt and MAPK kinase 4 (SEK1)/ stress-activated protein kinase (SAPK) axis were parallel activated in the OB of 6-months-old-Tg2576 mice. Furthermore, a survival kinome profiling performed during the aging process (2-, 6-, and 18-month-old) revealed that olfactory APP overexpression leads to changes in the activation dynamics of protein kinase A (PKA), and SEK1/MKK4-SAPK/JNK between 6 and 18 months of age, when memory deficits appear and AD pathology is well established in transgenic mice. Interestingly, both olfactory pathways were differentially activated in a stage-dependent manner in human sporadic AD subjects with different neuropathological grading. Taken together, our data reflect the early impact of mutated APP on the OB molecular homeostasis, highlighting the progressive modulation of specific signaling pathways during the olfactory amyloidogenic pathology.

Deployment of Label-Free Quantitative Olfactory Proteomics to Detect Cerebrospinal Fluid Biomarker Candidates in Synucleinopathies

Nowadays, diagnosis of neurodegenerative disorders is mainly based on neuroimaging and clinical symptoms, although postmortem neuropathological confirmation remains the gold standard diagnostic technique. Therefore, cerebrospinal fluid (CSF) proteome is considered a valuable molecular repository for diagnosing and targeting the neurodegenerative process. It is well known that olfactory dysfunction is among the earliest features of synucleinopathies such as Parkinson's disease (PD). Consequently, we consider that the application of tissue proteomics in primary olfactory structures is an ideal approach to explore early pathophysiological changes, detecting olfactory proteins that might be tested in CSF as potential biomarkers. Data mining of mass spectrometry-generated datasets has revealed that 30% of the olfactory bulb (OB) proteome is also localized in CSF. In this chapter, we describe a method that utilizes label-free quantitative proteomics and computational analysis to characterize human OB proteomes and potential cerebrospinal fluid (CSF) biomarkers associated with neurodegenerative syndromes. For that, we applied peptide fractionation methods, followed by tandem mass spectrometry (nanoLC-MS/MS), in silico analysis, and semi-quantitative orthogonal techniques in OB derived from PD subjects. After obtaining the differential OB proteome across Lewy-type alpha-synucleinopathy (LTS) stages and further validating the method, this workflow was applied to probe changes in NEGR1 (neuronal growth regulator 1) and GNPDA2 (glucosamine-6-phosphate deaminase 2) protein levels in CSF derived from parkinsonian subjects with respect to controls, observing an inverse correlation between both proteins and α-synuclein, the principal component analysis of Lewy pathology.

The Challenge to Search for New Nervous System Disease Biomarker Candidates: the Opportunity to Use the Proteogenomics Approach

Alzheimer's disease, Parkinson's disease, prion diseases, schizophrenia, and multiple sclerosis are the most common nervous system diseases, affecting millions of people worldwide. The current scientific literature associates these pathological conditions to abnormal expression levels of certain proteins, which in turn improved the knowledge concerning normal and affected brains. However, there is no available cure or preventive therapy for any of these disorders. Proteogenomics is a recent approach defined as the data integration of both nucleotide high-throughput sequencing and protein mass spectrometry technologies. In the last years, proteogenomics studies in distinct diseases have emerged as a strategy for the identification of uncharacterized proteoforms, which are all the different protein forms derived from a single gene. For many of these diseases, at least one protein used as biomarker presents more than one proteoform, which fosters the analysis of publicly available data focusing proteoforms. Given this context, we describe the most important biomarkers for each neurodegenerative disease and how genomics, transcriptomics, and proteomics separately contributed to unveil them. Finally, we present a selection of proteogenomics studies in which the combination of nucleotide and proteome high-throughput data, from cell lines or brain tissue samples, is used to uncover proteoforms not previously described. We believe that this new approach may improve our knowledge about nervous system diseases and brain function and an opportunity to identify new biomarker candidates.