Frontotemporal dementia: insights into the biological underpinnings of disease through gene co-expression network analysis

The non-specific lethal complex regulates genes and pathways genetically linked to Parkinson's disease

Genetic variants conferring risks for Parkinson's disease have been highlighted through genome-wide association studies, yet exploration of their specific disease mechanisms is lacking. Two Parkinson's disease candidate genes, KAT8 and KANSL1, identified through genome-wide studies and a PINK1-mitophagy screen, encode part of the histone acetylating non-specific lethal complex. This complex localizes to the nucleus, where it plays a role in transcriptional activation, and to mitochondria, where it has been suggested to have a role in mitochondrial transcription. In this study, we sought to identify whether the non-specific lethal complex has potential regulatory relationships with other genes associated with Parkinson's disease in human brain. Correlation in the expression of non-specific lethal genes and Parkinson's disease-associated genes was investigated in primary gene co-expression networks using publicly-available transcriptomic data from multiple brain regions (provided by the Genotype-Tissue Expression Consortium and UK Brain Expression Consortium), whilst secondary networks were used to examine cell type specificity. Reverse engineering of gene regulatory networks generated regulons of the complex, which were tested for heritability using stratified linkage disequilibrium score regression. Prioritized gene targets were then validated in vitro using a QuantiGene multiplex assay and publicly-available chromatin immunoprecipitation-sequencing data. Significant clustering of non-specific lethal genes was revealed alongside Parkinson's disease-associated genes in frontal cortex primary co-expression modules, amongst other brain regions. Both primary and secondary co-expression modules containing these genes were enriched for mainly neuronal cell types. Regulons of the complex contained Parkinson's disease-associated genes and were enriched for biological pathways genetically linked to disease. When examined in a neuroblastoma cell line, 41% of prioritized gene targets showed significant changes in mRNA expression following KANSL1 or KAT8 perturbation. KANSL1 and H4K8 chromatin immunoprecipitation-sequencing data demonstrated non-specific lethal complex activity at many of these genes. In conclusion, genes encoding the non-specific lethal complex are highly correlated with and regulate genes associated with Parkinson's disease. Overall, these findings reveal a potentially wider role for this protein complex in regulating genes and pathways implicated in Parkinson's disease.

A role of inflammaging in aortic aneurysm: new insights from bioinformatics analysis

Introduction

Aortic aneurysms (AA) are prevalent worldwide with a notable absence of drug therapies. Thus, identifying potential drug targets is of utmost importance. AA often presents in the elderly, coupled with consistently raised serum inflammatory markers. Given that ageing and inflammation are pivotal processes linked to the evolution of AA, we have identified key genes involved in the inflammaging process of AA development through various bioinformatics methods, thereby providing potential molecular targets for further investigation.

Methods

The transcriptome data of AA was procured from the datasets GSE140947, GSE7084, and GSE47472, sourced from the NCBI GEO database, whilst gene data of ageing and inflammation were obtained from the GeneCards Database. To identify key genes, differentially expressed analysis using the "Limma" package and WGCNA were implemented. Protein-protein intersection (PPI) analysis and machine learning (ML) algorithms were employed for the screening of potential biomarkers, followed by an assessment of the diagnostic value. Following the acquisition of the hub inflammaging and AA-related differentially expressed genes (IADEGs), the TFs-mRNAs-miRNAs regulatory network was established. The CIBERSORT algorithm was utilized to investigate immune cell infiltration in AA. The correlation of hub IADEGs with infiltrating immunocytes was also evaluated. Lastly, wet laboratory experiments were carried out to confirm the expression of hub IADEGs.

Results

342 and 715 AA-related DEGs (ADEGs) recognized from GSE140947 and GSE7084 datasets were procured by intersecting the results of "Limma" and WGCNA analyses. After 83 IADEGs were obtained, PPI analysis and ML algorithms pinpointed 7 and 5 hub IADEGs candidates respectively, and 6 of them demonstrated a high diagnostic value. Immune cell infiltration outcomes unveiled immune dysregulation in AA. In the wet laboratory experiments, 3 hub IADEGs, including BLNK, HLA-DRA, and HLA-DQB1, finally exhibited an expression trend in line with the bioinformatics analysis result.

Discussion

Our research identified three genes - BLNK, HLA-DRA, and HLA-DQB1- that play a significant role in promoting the development of AA through inflammaging, providing novel insights into the future understanding and therapeutic intervention of AA.

Transcriptomic and Network Meta-Analysis of Frontotemporal Dementias

Frontotemporal lobar degeneration (FTLD), also known as frontotemporal dementia (FTD), results in a progressive decline in executive function, leading to behavioral changes, speech problems, and movement disorders. FTD is the second most common cause of young-onset dementia affecting approximately 50–60,000 Americans. FTD exists in familial and sporadic forms, with GRN progranulin and C9orf72 mutations being the most common causes. In this study, we compared the sporadic and familial transcriptome within the cerebellum, frontal cortex, hippocampus, and Brodmann’s area 8 of patients with FTD to determine genes and pathways involved in the disease process. Most dysregulated genes expression occurred in the frontal cortex and Brodmann’s area 8 for genetic and sporadic forms of FTD, respectively. A meta-analysis revealed 50 genes and 95 genes are dysregulated in at least three brain regions in patients with familial mutations and sporadic FTD patients, respectively. Familial FTD genes centered on the Wnt signaling pathway, whereas genes associated with the sporadic form of FTD centered on MAPK signaling. The results reveal the similarities and differences between sporadic and familial FTD. In addition, valproic acid and additional therapeutic agents may be beneficial in treating patients with FTD.

Revelation of candidate genes and molecular mechanism of reproductive seasonality in female rohu (Labeo rohita Ham.) by RNA sequencing

BACKGROUND

Carp fish, rohu (Labeo rohita Ham.) is important freshwater aquaculture species of South-East Asia having seasonal reproductive rhythm. There is no holistic study at transcriptome level revealing key candidate genes involved in such circannual rhythm regulated by biological clock genes (BCGs). Seasonality manifestation has two contrasting phases of reproduction, i.e., post-spawning resting and initiation of gonadal activity appropriate for revealing the associated candidate genes. It can be deciphered by RNA sequencing of tissues involved in BPGL (Brain-Pituitary-Gonad-Liver) axis controlling seasonality. How far such BCGs of this fish are evolutionarily conserved across different phyla is unknown. Such study can be of further use to enhance fish productivity as seasonality restricts seed production beyond monsoon season.

RESULT

A total of ~ 150 Gb of transcriptomic data of four tissues viz., BPGL were generated using Illumina TruSeq. De-novo assembled BPGL tissues revealed 75,554 differentially expressed transcripts, 115,534 SSRs, 65,584 SNPs, 514 pathways, 5379 transcription factors, 187 mature miRNA which regulates candidate genes represented by 1576 differentially expressed transcripts are available in the form of web-genomic resources. Findings were validated by qPCR. This is the first report in carp fish having 32 BCGs, found widely conserved in fish, amphibian, reptile, birds, prototheria, marsupials and placental mammals. This is due to universal mechanism of rhythmicity in response to environment and earth rotation having adaptive and reproductive significance.

CONCLUSION

This study elucidates evolutionary conserved mechanism of photo-periodism sensing, neuroendocrine secretion, metabolism and yolk synthesis in liver, gonadal maturation, muscular growth with sensory and auditory perception in this fish. Study reveals fish as a good model for research on biological clock besides its relevance in reproductive efficiency enhancement.

A Shotgun Proteomic Platform for a Global Mapping of Lymphoblastoid Cells to Gain Insight into Nasu-Hakola Disease

Nasu-Hakola Disease (NHD) is a recessively inherited systemic leukodystrophy disorder characterized by a combination of frontotemporal presenile dementia and lytic bone lesions. NHD is known to be genetically related to a structural defect of TREM2 and DAP12, two genes that encode for different subunits of the membrane receptor signaling complex expressed by microglia and osteoclast cells. Because of its rarity, molecular or proteomic studies on this disorder are absent or scarce, only case reports based on neuropsychological and genetic tests being reported. In light of this, the aim of this paper is to provide evidence on the potential of a label-free proteomic platform based on the Multidimensional Protein Identification Technology (MudPIT), combined with in-house software and on-line bioinformatics tools, to characterize the protein expression trends and the most involved pathways in NHD. The application of this approach on the Lymphoblastoid cells from a family composed of individuals affected by NHD, healthy carriers and control subjects allowed for the identification of about 3000 distinct proteins within the three analyzed groups, among which proteins anomalous to each category were identified. Of note, several differentially expressed proteins were associated with neurodegenerative processes. Moreover, the protein networks highlighted some molecular pathways that may be involved in the onset or progression of this rare frontotemporal disorder. Therefore, this fully automated MudPIT platform which allowed, for the first time, the generation of the whole protein profile of Lymphoblastoid cells from Nasu-Hakola subjects, could be a valid approach for the investigation of similar neurodegenerative diseases.

Glial cells and adaptive immunity in frontotemporal dementia with tau pathology

Neuroinflammation is involved in the aetiology of many neurodegenerative disorders including Alzheimer's disease, Parkinson's disease and motor neuron disease. Whether neuroinflammation also plays an important role in the pathophysiology of frontotemporal dementia is less well known. Frontotemporal dementia is a heterogeneous classification that covers many subtypes, with the main pathology known as frontotemporal lobar degeneration. The disease can be categorized with respect to the identity of the protein that causes the frontotemporal lobar degeneration in the brain. The most common subgroup describes diseases caused by frontotemporal lobar degeneration associated with tau aggregation, also known as primary tauopathies. Evidence suggests that neuroinflammation may play a role in primary tauopathies with genome-wide association studies finding enrichment of genetic variants associated with specific inflammation-related gene loci. These loci are related to both the innate immune system, including brain resident microglia, and the adaptive immune system through possible peripheral T-cell involvement. This review discusses the genetic evidence and relates it to findings in animal models expressing pathogenic tau as well as to post-mortem and PET studies in human disease. Across experimental paradigms, there seems to be a consensus regarding the involvement of innate immunity in primary tauopathies, with increased microglia and astrocyte density and/or activation, as well as increases in pro-inflammatory markers. Whilst it is less clear as to whether inflammation precedes tau aggregation or vice versa; there is strong evidence to support a microglial contribution to the propagation of hyperphosphorylated in tau frontotemporal lobar degeneration associated with tau aggregation. Experimental evidence-albeit limited-also corroborates genetic data pointing to the involvement of cellular adaptive immunity in primary tauopathies. However, it is still unclear whether brain recruitment of peripheral immune cells is an aberrant result of pathological changes or a physiological aspect of the neuroinflammatory response to the tau pathology.

Ronin overexpression induces cerebellar degeneration in a mouse model of ataxia

Spinocerebellar ataxias (SCAs) are a group of genetically heterogeneous inherited neurodegenerative disorders characterized by progressive ataxia and cerebellar degeneration. Here, we used a mouse model to test a possible connection between SCA and Ronin (Thap11), a polyglutamine-containing transcriptional regulator encoded in a region of human chromosome 16q22.1 that has been genetically linked to SCA type 4. We report that transgenic expression of Ronin in mouse cerebellar Purkinje cells leads to detrimental loss of these cells and the development of severe ataxia as early as 10 weeks after birth. Mechanistically, we find that several SCA-causing genes harbor Ronin DNA-binding motifs and are transcriptionally deregulated in transgenic animals. In addition, ectopic expression of Ronin in embryonic stem cells significantly increases the protein level of Ataxin-1, the protein encoded by Atxn1, alterations of which cause SCA type 1. This increase is also seen in the cerebellum of transgenic animals, although the latter was not statistically significant. Hence, our data provide evidence for a link between Ronin and SCAs, and suggest that Ronin may be involved in the development of other neurodegenerative diseases.

Summary: Ronin is a polyglutamine protein encoded in a region of human chromosome 16q22.1 linked to spinocerebellar ataxia type 4. Overexpression of Ronin in mouse cerebellar Purkinje cells leads to their loss and ataxia.

Identification of a novel mutation in MEF2C gene in an atypical patient with frontotemporal lobar degeneration

The MEF2C gene encodes a transcription factor known to play a crucial role in molecular pathways affecting neuronal development. MEF2C mutations were described as a genetic cause of developmental disease (MRD20), and several reports sustain its involvement in dementia-related conditions, such as Alzheimer's disease and amyotrophic lateral sclerosis. These pathologies and frontotemporal degeneration (FTLD) are thought to share common physiopathological pathways. In this exploratory study, we searched for alterations in the DNA sequence of exons and boundaries, including 5'- and 3'-untranslated regions (5'UTR, 3'UTR), of MEF2C gene in 11 patients with clinical phenotypes related with MRD20 or FTLD. We identified a heterozygous deletion of 13 nucleotides in the 5'UTR region of a 69 years old FTLD patient. This alteration was absent in 200 healthy controls, suggesting a contribution to this patient's disease phenotype. In silico analysis of the mutated sequence indicated changes in mRNA secondary structure and stability, thus potentially affecting MEF2C protein levels. Furthermore, in vitro functional analysis of this mutation revealed that the presence of this deletion abolished the transcriptional activity of the gene in human embryonic cells and rat brain neurons, probably by modifying MEF2C expression. Altogether, our results provide evidence for the involvement of MEF2C in FTLD manifesting with seizures.

Myeloid Arginase 1 Insufficiency Exacerbates Amyloid-β Associated Neurodegenerative Pathways and Glial Signatures in a Mouse Model of Alzheimer's Disease: A Targeted Transcriptome Analysis

Brain myeloid cells, include infiltrating macrophages and resident microglia, play an essential role in responding to and inducing neurodegenerative diseases, such as Alzheimer's disease (AD). Genome-wide association studies (GWAS) implicate many AD casual and risk genes enriched in brain myeloid cells. Coordinated arginine metabolism through arginase 1 (Arg1) is critical for brain myeloid cells to perform biological functions, whereas dysregulated arginine metabolism disrupts them. Altered arginine metabolism is proposed as a new biomarker pathway for AD. We previously reported Arg1 deficiency in myeloid biased cells using lysozyme M (LysM) promoter-driven deletion worsened amyloidosis-related neuropathology and behavioral impairment. However, it remains unclear how Arg1 deficiency in these cells impacts the whole brain to promote amyloidosis. Herein, we aim to determine how Arg1 deficiency driven by LysM restriction during amyloidosis affects fundamental neurodegenerative pathways at the transcriptome level. By applying several bioinformatic tools and analyses, we found that amyloid-β (Aβ) stimulated transcriptomic signatures in autophagy-related pathways and myeloid cells' inflammatory response. At the same time, myeloid Arg1 deficiency during amyloidosis promoted gene signatures of lipid metabolism, myelination, and migration of myeloid cells. Focusing on Aβ associated glial transcriptomic signatures, we found myeloid Arg1 deficiency up-regulated glial gene transcripts that positively correlated with Aβ plaque burden. We also observed that Aβ preferentially activated disease-associated microglial signatures to increase phagocytic response, whereas myeloid Arg1 deficiency selectively promoted homeostatic microglial signature that is non-phagocytic. These transcriptomic findings suggest a critical role for proper Arg1 function during normal and pathological challenges associated with amyloidosis. Furthermore, understanding pathways that govern Arg1 metabolism may provide new therapeutic opportunities to rebalance immune function and improve microglia/macrophage fitness.

CoExp: A Web Tool for the Exploitation of Co-expression Networks

Gene co-expression networks are a powerful type of analysis to construct gene groupings based on transcriptomic profiling. Co-expression networks make it possible to discover modules of genes whose mRNA levels are highly correlated across samples. Subsequent annotation of modules often reveals biological functions and/or evidence of cellular specificity for cell types implicated in the tissue being studied. There are multiple ways to perform such analyses with weighted gene co-expression network analysis (WGCNA) amongst one of the most widely used R packages. While managing a few network models can be done manually, it is often more advantageous to study a wider set of models derived from multiple independently generated transcriptomic data sets (e.g., multiple networks built from many transcriptomic sources). However, there is no software tool available that allows this to be easily achieved. Furthermore, the visual nature of co-expression networks in combination with the coding skills required to explore networks, makes the construction of a web-based platform for their management highly desirable. Here, we present the CoExp Web application, a user-friendly online tool that allows the exploitation of the full collection of 109 co-expression networks provided by the CoExpNets suite of R packages. We describe the usage of CoExp, including its contents and the functionality available through the family of CoExpNets packages. All the tools presented, including the web front- and back-ends are available for the research community so any research group can build its own suite of networks and make them accessible through their own CoExp Web application. Therefore, this paper is of interest to both researchers wishing to annotate their genes of interest across different brain network models and specialists interested in the creation of GCNs looking for a tool to appropriately manage, use, publish, and share their networks in a consistent and productive manner.

scLM: Automatic Detection of Consensus Gene Clusters Across Multiple Single-cell Datasets

In gene expression profiling studies, including single-cell RNAsequencing (scRNA-seq) analyses, the identification and characterization of co-expressed genes provides critical information on cell identity and function. Gene co-expression clustering in scRNA-seq data presents certain challenges. We show that commonly used methods for single-cell data are not capable of identifying co-expressed genes accurately, and produce results that substantially limit biological expectations of co-expressed genes. Herein, we present single-cell Latent-variable Model (scLM), a gene co-clustering algorithm tailored to single-cell data that performs well at detecting gene clusters with significant biologic context. Importantly, scLM can simultaneously cluster multiple single-cell datasets, i.e., consensus clustering, enabling users to leverage single-cell data from multiple sources for novel comparative analysis. scLM takes raw count data as input and preserves biological variation without being influenced by batch effects from multiple datasets. Results from both simulation data and experimental data demonstrate that scLM outperforms the existing methods with considerably improved accuracy. To illustrate the biological insights of scLM, we apply it to our in-house and public experimental scRNA-seq datasets. scLM identifies novel functional gene modules and refines cell states, which facilitates mechanism discovery and understanding of complex biosystems such as cancers. A user-friendly R package with all the key features of the scLM method is available at https://github.com/QSong-github/scLM.

Retrovirus reactivation in CHMP2BIntron5 models of frontotemporal dementia

Frontotemporal dementia (FTD) is the second most prevalent form of pre-senile dementia after Alzheimer's disease. Amyotrophic lateral sclerosis (ALS) can overlap genetically, pathologically and clinically with FTD indicating the two conditions are ends of a spectrum and may share common pathological mechanisms. FTD-ALS causing mutations are known to be involved in endosomal trafficking and RNA regulation. Using an unbiased genome-wide genetic screen to identify mutations affecting an FTD-ALS-related phenotype in Drosophila caused by CHMP2BIntron5 expression, we have uncovered repressors of retrovirus (RV) activity as modifiers of CHMP2BIntron5 toxicity. We report that neuronal expression of CHMP2BIntron5 causes an increase in the activity of the endogenous Drosophila RV, gypsy, in the nervous system. Genetically blocking Drosophila gypsy activation and pharmacologically inhibiting viral reverse transcriptase activity prevents degenerative phenotypes observed in fly and rat neurons. These findings directly link endosomal dysfunction to RV de-repression in an FTD-ALS model without TDP-43 pathology. These observations may contribute an understanding to previous discoveries of RV activation in ALS affected patients.

Microglial burden, activation and dystrophy patterns in frontotemporal lobar degeneration

Background

Microglial dysfunction is implicated in frontotemporal lobar degeneration (FTLD). Although studies have reported excessive microglial activation or senescence (dystrophy) in Alzheimer’s disease (AD), few have explored this in FTLD. We examined regional patterns of microglial burden, activation and dystrophy in sporadic and genetic FTLD, sporadic AD and controls.

Methods

Immunohistochemistry was performed in frontal and temporal grey and white matter from 50 pathologically confirmed FTLD cases (31 sporadic, 19 genetic: 20 FTLD-tau, 26 FTLD-TDP, four FTLD-FUS), five AD cases and five controls, using markers to detect phagocytic (CD68-positive) and antigen-presenting (CR3/43-positive) microglia, and microglia in general (Iba1-positive). Microglial burden and activation (morphology) were assessed quantitatively for each microglial phenotype. Iba1-positive microglia were assessed semi-quantitatively for dystrophy severity and qualitatively for rod-shaped and hypertrophic morphology. Microglia were compared in each region between FTLD, AD and controls, and between different pathological subtypes of FTLD, including its main subtypes (FTLD-tau, FTLD-TDP, FTLD-FUS), and subtypes of FTLD-tau, FTLD-TDP and genetic FTLD. Microglia were also compared between grey and white matter within each lobe for each group.

Results

There was a higher burden of phagocytic and antigen-presenting microglia in FTLD and AD cases than controls, but activation was often not increased. Burden was generally higher in white matter than grey matter, but activation was greater in grey matter. However, microglia varied regionally according to FTLD subtype and disease mechanism. Dystrophy was more severe in FTLD and AD than controls, and more severe in white than grey matter, but this also varied regionally and was particularly extensive in FTLD due to progranulin (GRN) mutations. Presence of rod-shaped and hypertrophic microglia also varied by FTLD subtype.

Conclusions

This study demonstrates regionally variable microglial involvement in FTLD and links this to underlying disease mechanisms. This supports investigation of microglial dysfunction in disease models and consideration of anti-senescence therapies in clinical trials.

Dysregulation of Exosome Cargo by Mutant Tau Expressed in Human-induced Pluripotent Stem Cell (iPSC) Neurons Revealed by Proteomics Analyses

Accumulation and propagation of hyperphosphorylated Tau (p-Tau) is a common neuropathological hallmark associated with neurodegeneration of Alzheimer's disease (AD), frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17), and related tauopathies. Extracellular vesicles, specifically exosomes, have recently been demonstrated to participate in mediating Tau propagation in brain. Exosomes produced by human induced pluripotent stem cell (iPSC)-derived neurons expressing mutant Tau (mTau), containing the P301L and V337M Tau mutations of FTDP-17, possess the ability to propagate p-Tau pathology after injection into mouse brain. To gain an understanding of the mTau exosome cargo involved in Tau pathogenesis, these pathogenic exosomes were analyzed by proteomics and bioinformatics. The data showed that mTau expression dysregulates the exosome proteome to result in 1) proteins uniquely present only in mTau, and not control exosomes, 2) the absence of proteins in mTau exosomes, uniquely present in control exosomes, and 3) shared proteins which were significantly upregulated or downregulated in mTau compared with control exosomes. Notably, mTau exosomes (not control exosomes) contain ANP32A (also known as I1PP2A), an endogenous inhibitor of the PP2A phosphatase which regulates the phosphorylation state of p-Tau. Several of the mTau exosome-specific proteins have been shown to participate in AD mechanisms involving lysosomes, inflammation, secretases, and related processes. Furthermore, the mTau exosomes lacked a substantial portion of proteins present in control exosomes involved in pathways of localization, vesicle transport, and protein binding functions. The shared proteins present in both mTau and control exosomes represented exosome functions of vesicle-mediated transport, exocytosis, and secretion processes. These data illustrate mTau as a dynamic regulator of the biogenesis of exosomes to result in acquisition, deletion, and up- or downregulation of protein cargo to result in pathogenic mTau exosomes capable of in vivo propagation of p-Tau neuropathology in mouse brain.

Bioinformatic Analysis Reveals Phosphodiesterase 4D-Interacting Protein as a Key Frontal Cortex Dementia Switch Gene

The mechanisms that initiate dementia are poorly understood and there are currently no treatments that can slow their progression. The identification of key genes and molecular pathways that may trigger dementia should help reveal potential therapeutic reagents. In this study, SWItch Miner software was used to identify phosphodiesterase 4D-interacting protein as a key factor that may lead to the development of Alzheimer’s disease, vascular dementia, and frontotemporal dementia. Inflammation, PI3K-AKT, and ubiquitin-mediated proteolysis were identified as the main pathways that are dysregulated in these dementias. All of these dementias are regulated by 12 shared transcription factors. Protein–chemical interaction network analysis of dementia switch genes revealed that valproic acid may be neuroprotective for these dementias. Collectively, we identified shared and unique dysregulated gene expression, pathways and regulatory factors among dementias. New key mechanisms that lead to the development of dementia were revealed and it is expected that these data will advance personalized medicine for patients.

Transcriptomic and Network Analysis Identifies Shared and Unique Pathways across Dementia Spectrum Disorders

Background: Dementia is a growing public health concern with an estimated prevalence of 50 million people worldwide. Alzheimer’s disease (AD) and vascular and frontotemporal dementias (VaD, FTD), share many clinical, genetical, and pathological features making the diagnosis difficult. Methods: In this study, we compared the transcriptome from the frontal cortex of patients with AD, VaD, and FTD to identify dysregulated pathways. Results: Upregulated genes in AD were enriched in adherens and tight junctions, mitogen-activated protein kinase, and phosphatidylinositol 3-kinase and protein kinase B/Akt signaling pathways, whereas downregulated genes associated with calcium signaling. Upregulated genes in VaD were centered on infectious diseases and nuclear factor kappa beta signaling, whereas downregulated genes are involved in biosynthesis of amino acids and the pentose phosphate pathway. Upregulated genes in FTD were associated with ECM receptor interactions and the lysosome, whereas downregulated genes were involved in glutamatergic synapse and MAPK signaling. The transcription factor KFL4 was shared among the 3 types of dementia. Conclusions: Collectively, we identified similarities and differences in dysregulated pathways and transcription factors among the dementias. The shared pathways and transcription factors may indicate a potential common etiology, whereas the differences may be useful for distinguishing dementias.

Network Analysis for Complex Neurodegenerative Diseases

Purpose of Review

Biomedicine is witnessing a paradigm shift in the way complex disorders are investigated. In particular, the need for big data interpretation has led to the development of pipelines that require the cooperation of different fields of expertise, including medicine, functional biology, informatics, mathematics and systems biology. This review sits at the crossroad of different disciplines and surveys the recent developments in the use of graph theory (in the form of network analysis) to interpret large and different datasets in the context of complex neurodegenerative diseases. It aims at a professional audience with different backgrounds.

Recent Findings

Biomedicine has entered the era of big data, and this is actively changing the way we approach and perform research. The increase in size and power of biomedical studies has led to the establishment of multi-centre, international working groups coordinating open access platforms for data generation, storage and analysis. Particularly, pipelines for data interpretation are under development, and network analysis is gaining momentum since it represents a versatile approach to study complex systems made of interconnected multiple players.

Summary

We will describe the era of big data in biomedicine and survey the major freely accessible multi-omics datasets. We will then introduce the principles of graph theory and provide examples of network analysis applied to the interpretation of complex neurodegenerative disorders.

Selective Genetic Overlap Between Amyotrophic Lateral Sclerosis and Diseases of the Frontotemporal Dementia Spectrum

Importance

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by loss of upper and lower motor neurons. Although novel ALS genetic variants have been identified, the shared genetic risk between ALS and other neurodegenerative disorders remains poorly understood.

Objectives

To examine whether there are common genetic variants that determine the risk for ALS and other neurodegenerative diseases and to identify their functional pathways.

Design, Setting, and Participants

In this study conducted from December 1, 2016, to August 1, 2017, the genetic overlap between ALS, sporadic frontotemporal dementia (FTD), FTD with TDP-43 inclusions, Parkinson disease (PD), Alzheimer disease (AD), corticobasal degeneration (CBD), and progressive supranuclear palsy (PSP) were systematically investigated in 124 876 cases and controls. No participants were excluded from this study. Diagnoses were established using consensus criteria.

Main Outcomes and Measures

The primary outcomes were a list of novel loci and their functional pathways in ALS, FTD, PSP, and ALS mouse models.

Results

Among 124 876 cases and controls, genome-wide conjunction analyses of ALS, FTD, PD, AD, CBD, and PSP revealed significant genetic overlap between ALS and FTD at known ALS loci: rs13302855 and rs3849942 (nearest gene, C9orf72; P = .03 for rs13302855 and P = .005 for rs3849942) and rs4239633 (nearest gene, UNC13A; P = .03). Significant genetic overlap was also found between ALS and PSP at rs7224296, which tags the MAPT H1 haplotype (nearest gene, NSF; P = .045). Shared risk genes were enriched for pathways involving neuronal function and development. At a conditional FDR P < .05, 22 novel ALS polymorphisms were found, including rs538622 (nearest gene, ERGIC1; P = .03 for ALS and FTD), which modifies BNIP1 expression in human brains (35 of 137 females; mean age, 59 years; P = .001). BNIP1 expression was significantly reduced in spinal cord motor neurons from patients with ALS (4 controls: mean age, 60.5 years, mean [SE] value, 3984 [760.8] arbitrary units [AU]; 7 patients with ALS: mean age, 56 years, mean [SE] value, 1999 [274.1] AU; P = .02), in an ALS mouse model (mean [SE] value, 13.75 [0.09] AU for 2 SOD1 WT mice and 11.45 [0.03] AU for 2 SOD1 G93A mice; P = .002) and in brains of patients with PSP (80 controls: 39 females; mean age, 82 years, mean [SE] value, 6.8 [0.2] AU; 84 patients with PSP: 33 females, mean age 74 years, mean [SE] value, 6.8 [0.1] AU; β = -0.19; P = .009) or FTD (11 controls: 4 females; mean age, 67 years; mean [SE] value, 6.74 [0.05] AU; 17 patients with FTD: 10 females; mean age, 69 years; mean [SE] value, 6.53 [0.04] AU; P = .005).

Conclusions and Relevance

This study found novel genetic overlap between ALS and diseases of the FTD spectrum, that the MAPT H1 haplotype confers risk for ALS, and identified the mitophagy-associated, proapoptotic protein BNIP1 as an ALS risk gene. Together, these findings suggest that sporadic ALS may represent a selectively pleiotropic, polygenic disorder.

Genetics and molecular mechanisms of frontotemporal lobar degeneration: an update and future avenues

Frontotemporal lobar degeneration (FTLD) is the second most common form of dementia after Alzheimer's disease. The study and the dissection of FTLD is complex due to its clinical, pathological, and genetic heterogeneity. In this review, we survey the state-of-the-art genetics of familial FTLD and recapitulate our current understanding of the genetic architecture of sporadic FTLD by summarizing results of genome-wide association studies performed in FTLD to date. We then discuss the challenges of translating these heterogeneous genetic features into the understanding of the molecular underpinnings of FTLD pathogenesis. We particularly highlight a number of susceptibility processes that appear to be conserved across familial and sporadic cases (e.g., and the cellular waste disposal pathways, and immune system signaling) and finally describe cutting-edge approaches, based on mathematical prediction tools, highlighting novel intriguing risk pathways such as DNA damage response as an emerging theme in FTLD.

Aberrant activation of non-coding RNA targets of transcriptional elongation complexes contributes to TDP-43 toxicity

TDP-43 is the major disease protein associated with amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration with ubiquitinated inclusions (FTLD-TDP). Here we identify the transcriptional elongation factor Ell—a shared component of little elongation complex (LEC) and super elongation complex (SEC)—as a strong modifier of TDP-43-mediated neurodegeneration. Our data indicate select targets of LEC and SEC become upregulated in the fly ALS/FTLD-TDP model. Among them, U12 snRNA and a stress-induced long non-coding RNA Hsrω, functionally contribute to TDP-43-mediated degeneration. We extend the findings of Hsrω, which we identify as a chromosomal target of TDP-43, to show that the human orthologue Sat III is elevated in a human cellular disease model and FTLD-TDP patient tissue. We further demonstrate an interaction between TDP-43 and human ELL2 by co-immunoprecipitation from human cells. These findings reveal important roles of Ell-complexes LEC and SEC in TDP-43-associated toxicity, providing potential therapeutic insight for TDP-43-associated neurodegeneration.

TDP-43 is associated with amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration with ubiquitinated inclusions (FTD-TDP). Here, the authors identify the transcriptional elongation factor Ell as a strong modifier of TDP-43-mediated neurodegeneration through the Ell transcriptional elongation complexes LEC and SEC.

Tau Mutations Serve as a Novel Risk Factor for Cancer

In addition to its well-recognized role in neurodegeneration, tau participates in maintenance of genome stability and chromosome integrity. In particular, peripheral cells from patients affected by frontotemporal lobar degeneration carrying a mutation in tau gene (genetic tauopathies), as well as cells from animal models, show chromosome numerical and structural aberrations, chromatin anomalies, and a propensity toward abnormal recombination. As genome instability is tightly linked to cancer development, we hypothesized that mutated tau may be a susceptibility factor for cancer. Here we conducted a retrospective cohort study comparing cancer incidence in families affected by genetic tauopathies to control families. In addition, we carried out a bioinformatics analysis to highlight pathways associated with the tau protein interactome. We report that the risk of developing cancer is significantly higher in families affected by genetic tauopathies, and a high proportion of tau protein interactors are involved in cellular processes particularly relevant to cancer. These findings disclose a novel role of tau as a risk factor for cancer, providing new insights in the various pathologic roles of mutated tau.Significance: This study reveals a novel role for tau as a risk factor for cancer, providing new insights beyond its role in neurodegeneration. Cancer Res; 78(13); 3731-9. ©2018 AACR.

The pro-apoptotic JNK scaffold POSH/SH3RF1 mediates CHMP2BIntron5-associated toxicity in animal models of frontotemporal dementia

Frontotemporal dementia (FTD) is one of the most prevalent forms of early-onset dementia. However, the pathological mechanisms driving neuronal atrophy in FTD remain poorly understood. Here we identify a conserved role for the novel pro-apoptotic protein plenty of SH3s (POSH)/SH3 domain containing ring finger 1 in mediating neuropathology in Drosophila and mammalian models of charged multivesicular body protein 2B (CHMP2BIntron5) associated FTD. Aberrant, AKT dependent, accumulation of POSH was observed throughout the nervous system of both Drosophila and mice expressing CHMP2BIntron5. Knockdown of POSH was shown to be neuroprotective and sufficient to alleviate aberrant neuronal morphology, behavioral deficits and premature-lethality in Drosophila models, as well as dendritic collapse and cell death in CHMP2BIntron5expressing rat primary neurons. POSH knockdown also ameliorated elevated markers of Jun N-terminal kinase and apoptotic cascades in both Drosophila and mammalian models. This study provides the first characterization of POSH as a potential component of an FTD neuropathology, identifying a novel apoptotic pathway with relevance to the FTD spectrum.

Aspirin-Mediated Acetylation Protects Against Multiple Neurodegenerative Pathologies by Impeding Protein Aggregation

AIMS

Many progressive neurological disorders, including Alzheimer's disease (AD), Huntington's disease, and Parkinson's disease (PD), are characterized by accumulation of insoluble protein aggregates. In prospective trials, the cyclooxygenase inhibitor aspirin (acetylsalicylic acid) reduced the risk of AD and PD, as well as cardiovascular events and many late-onset cancers. Considering the role played by protein hyperphosphorylation in aggregation and neurodegenerative diseases, and aspirin's known ability to donate acetyl groups, we asked whether aspirin might reduce both phosphorylation and aggregation by acetylating protein targets.

RESULTS

Aspirin was substantially more effective than salicylate in reducing or delaying aggregation in human neuroblastoma cells grown in vitro, and in Caenorhabditis elegans models of human neurodegenerative diseases in vivo. Aspirin acetylates many proteins, while reducing phosphorylation, suggesting that acetylation may oppose phosphorylation. Surprisingly, acetylated proteins were largely excluded from compact aggregates. Molecular-dynamic simulations indicate that acetylation of amyloid peptide energetically disfavors its association into dimers and octamers, and oligomers that do form are less compact and stable than those comprising unacetylated peptides.

INNOVATION

Hyperphosphorylation predisposes certain proteins to aggregate (e.g., tau, α-synuclein, and transactive response DNA-binding protein 43 [TDP-43]), and it is a critical pathogenic marker in both cardiovascular and neurodegenerative diseases. We present novel evidence that acetylated proteins are underrepresented in protein aggregates, and that aggregation varies inversely with acetylation propensity after diverse genetic and pharmacologic interventions.

CONCLUSIONS

These results are consistent with the hypothesis that aspirin inhibits protein aggregation and the ensuing toxicity of aggregates through its acetyl-donating activity. This mechanism may contribute to the neuro-protective, cardio-protective, and life-prolonging effects of aspirin. Antioxid. Redox Signal. 27, 1383-1396.

Identifying pathway modules of tuberculosis in children by analyzing multiple different networks

Tuberculosis (TB), which is caused by the mycobacterium TB, is the major cause of human death worldwide. The aim of this study was to identify the biomarkers involved in child TB. Gene expression data were obtained from the Array Express Archive of Functional Genomics Data. Gene expression data and protein-protein interaction (PPI) data were downloaded to construct differential gene co-expression networks (DCNs). The Benjamini-Hochberg algorithm was used to correct the P-value. In total, 3,820 edges (PPIs) and 1,359 nodes (genes) were obtained from the human-related PPIs data and gene expression data at the criteria of absolute value of Pearson's correlation coefficient >0.8. The DCNs were formed by these edges and nodes. Thirteen seed genes were obtained by ranging z-scores. Eight significant multiple different modules were identified from DCNs using the statistical significant test. In conclusion, the seed genes and significant modules constitute potential biomarkers that reveal the underlying mechanisms in child TB. The new identified biomarkers may contribute to an understanding of TB and provide a new therapeutic method for the treatment of TB.

A novel network analysis approach reveals DNA damage, oxidative stress and calcium/cAMP homeostasis-associated biomarkers in frontotemporal dementia

Frontotemporal Dementia (FTD) is the form of neurodegenerative dementia with the highest prevalence after Alzheimer’s disease, equally distributed in men and women. It includes several variants, generally characterized by behavioural instability and language impairments. Although few mendelian genes (MAPT, GRN, and C9orf72) have been associated to the FTD phenotype, in most cases there is only evidence of multiple risk loci with relatively small effect size. To date, there are no comprehensive studies describing FTD at molecular level, highlighting possible genetic interactions and signalling pathways at the origin FTD-associated neurodegeneration. In this study, we designed a broad FTD genetic interaction map of the Italian population, through a novel network-based approach modelled on the concepts of disease-relevance and interaction perturbation, combining Steiner tree search and Structural Equation Model (SEM) analysis. Our results show a strong connection between Calcium/cAMP metabolism, oxidative stress-induced Serine/Threonine kinases activation, and postsynaptic membrane potentiation, suggesting a possible combination of neuronal damage and loss of neuroprotection, leading to cell death. In our model, Calcium/cAMP homeostasis and energetic metabolism impairments are primary causes of loss of neuroprotection and neural cell damage, respectively. Secondly, the altered postsynaptic membrane potentiation, due to the activation of stress-induced Serine/Threonine kinases, leads to neurodegeneration. Our study investigates the molecular underpinnings of these processes, evidencing key genes and gene interactions that may account for a significant fraction of unexplained FTD aetiology. We emphasized the key molecular actors in these processes, proposing them as novel FTD biomarkers that could be crucial for further epidemiological and molecular studies.

The wide genetic landscape of clinical frontotemporal dementia: systematic combined sequencing of 121 consecutive subjects

Purpose

To define the genetic spectrum and relative gene frequencies underlying clinical frontotemporal dementia (FTD).

Methods

We investigated the frequencies and mutations in neurodegenerative disease genes in 121 consecutive FTD subjects using an unbiased, combined sequencing approach, complemented by cerebrospinal fluid Aβ_1-42 and serum progranulin measurements. Subjects were screened for C9orf72 repeat expansions, GRN and MAPT mutations, and, if negative, mutations in other neurodegenerative disease genes, by whole-exome sequencing (WES) (n = 108), including WES-based copy-number variant (CNV) analysis.

Results

Pathogenic and likely pathogenic mutations were identified in 19% of the subjects, including mutations in C9orf72 (n = 8), GRN (n = 7, one 11-exon macro-deletion) and, more rarely, CHCHD10, TARDBP, SQSTM1 and UBQLN2 (each n = 1), but not in MAPT or TBK1. WES also unraveled pathogenic mutations in genes not commonly linked to FTD, including mutations in Alzheimer (PSEN1, PSEN2), lysosomal (CTSF, 7-exon macro-deletion) and cholesterol homeostasis pathways (CYP27A1).

Conclusion

Our unbiased approach reveals a wide genetic spectrum underlying clinical FTD, including 11% of seemingly sporadic FTD. It unravels several mutations and CNVs in genes and pathways hitherto not linked to FTD. This suggests that clinical FTD might be the converging downstream result of a delicate susceptibility of frontotemporal brain networks to insults in various pathways.

CSF sAPPβ, YKL-40, and neurofilament light in frontotemporal lobar degeneration

Objective:

To analyze the clinical utility of 3 CSF biomarkers and their structural imaging correlates in a large cohort of patients with different dementia and parkinsonian syndromes within the spectrum of frontotemporal lobar degeneration (FTLD).

Methods:

We analyzed 3 CSF biomarkers (YKL-40, soluble β fragment of amyloid precursor protein [sAPPβ], neurofilament light [NfL]) and core Alzheimer disease (AD) biomarkers (β-amyloid1-42, total tau, phosphorylated tau) in patients with FTLD-related clinical syndromes (n = 159): behavioral variant of frontotemporal dementia (n = 68), nonfluent (n = 23) and semantic (n = 19) variants of primary progressive aphasia, progressive supranuclear palsy (n = 28), and corticobasal syndrome (n = 21). We also included patients with AD (n = 72) and cognitively normal controls (CN; n = 76). We compared cross-sectional biomarker levels between groups, studied their correlation with cortical thickness, and evaluated their potential diagnostic utility.

Results:

Patients with FTLD-related syndromes had lower levels of sAPPβ than CN and patients with AD. The levels of sAPPβ showed a strong correlation with cortical structural changes in frontal and cingulate areas. NfL and YKL-40 levels were high in both the FTLD and AD groups compared to controls. In the receiver operating characteristic analysis, the sAPPβ/YKL-40 and NfL/sAPPβ ratios had areas under the curve of 0.91 and 0.96, respectively, distinguishing patients with FTLD from CN, and of 0.84 and 0.85, distinguishing patients with FTLD from patients with AD.

Conclusions:

The combination of sAPPβ with YKL-40 and with NfL in CSF could be useful to increase the certainty of the diagnosis of FTLD-related syndromes in clinical practice.

Classification of evidence:

This study provides Class III evidence that CSF levels of sAPPβ, YKL-40, and NfL are useful to identify patients with FTLD-related syndromes.

Genetic architecture of sporadic frontotemporal dementia and overlap with Alzheimer's and Parkinson's diseases

BACKGROUND

Clinical, pathological and genetic overlap between sporadic frontotemporal dementia (FTD), Alzheimer's disease (AD) and Parkinson's disease (PD) has been suggested; however, the relationship between these disorders is still not well understood. Here we evaluated genetic overlap between FTD, AD and PD to assess shared pathobiology and identify novel genetic variants associated with increased risk for FTD.

METHODS

Summary statistics were obtained from the International FTD Genomics Consortium, International PD Genetics Consortium and International Genomics of AD Project (n>75 000 cases and controls). We used conjunction false discovery rate (FDR) to evaluate genetic pleiotropy and conditional FDR to identify novel FTD-associated SNPs. Relevant variants were further evaluated for expression quantitative loci.

RESULTS

We observed SNPs within the HLA, MAPT and APOE regions jointly contributing to increased risk for FTD and AD or PD. By conditioning on polymorphisms associated with PD and AD, we found 11 loci associated with increased risk for FTD. Meta-analysis across two independent FTD cohorts revealed a genome-wide signal within the APOE region (rs6857, 3'-UTR=PVRL2, p=2.21×10^-12), and a suggestive signal for rs1358071 within the MAPT region (intronic=CRHR1, p=4.91×10^-7) with the effect allele tagging the H1 haplotype. Pleiotropic SNPs at the HLA and MAPT loci associated with expression changes in cis-genes supporting involvement of intracellular vesicular trafficking, immune response and endo/lysosomal processes.

CONCLUSIONS

Our findings demonstrate genetic pleiotropy in these neurodegenerative diseases and indicate that sporadic FTD is a polygenic disorder where multiple pleiotropic loci with small effects contribute to increased disease risk.

Weighted Protein Interaction Network Analysis of Frontotemporal Dementia

The genetic analysis of complex disorders has undoubtedly led to the identification of a wealth of associations between genes and specific traits. However, moving from genetics to biochemistry one gene at a time has, to date, rather proved inefficient and under-powered to comprehensively explain the molecular basis of phenotypes. Here we present a novel approach, weighted protein–protein interaction network analysis (W-PPI-NA), to highlight key functional players within relevant biological processes associated with a given trait. This is exemplified in the current study by applying W-PPI-NA to frontotemporal dementia (FTD): We first built the state of the art FTD protein network (FTD-PN) and then analyzed both its topological and functional features. The FTD-PN resulted from the sum of the individual interactomes built around FTD-spectrum genes, leading to a total of 4198 nodes. Twenty nine of 4198 nodes, called inter-interactome hubs (IIHs), represented those interactors able to bridge over 60% of the individual interactomes. Functional annotation analysis not only reiterated and reinforced previous findings from single genes and gene-coexpression analyses but also indicated a number of novel potential disease related mechanisms, including DNA damage response, gene expression regulation, and cell waste disposal and potential biomarkers or therapeutic targets including EP300. These processes and targets likely represent the functional core impacted in FTD, reflecting the underlying genetic architecture contributing to disease. The approach presented in this study can be applied to other complex traits for which risk-causative genes are known as it provides a promising tool for setting the foundations for collating genomics and wet laboratory data in a bidirectional manner. This is and will be critical to accelerate molecular target prioritization and drug discovery.

Brain activation in frontotemporal and Alzheimer's dementia: a functional near-infrared spectroscopy study

Background

Frontotemporal dementia is an increasingly studied disease, the underlying functional impairments on a neurobiological level of which have not been fully understood. Patients with the behavioral-subtype frontotemporal dementia (bvFTD) are particularly challenging for clinical measurements such as functional imaging due to their behavioral symptoms. Here, an alternative imaging method, functional near-infrared spectroscopy (fNIRS), is introduced to measure task-related cortical brain activation based on blood oxygenation. The current study investigated differences in cortical activation patterns of patients with bvFTD, Alzheimer’s dementia (AD), and healthy elderly subjects measured by fNIRS.

Method

Eight probable bvFTD patients completed the semantic, phonological, and control conditions of a verbal fluency task. Eight AD patients and eight healthy controls were compared on the same task. Simultaneously, an fNIRS measurement was conducted and analyzed using a correction method based on the expected negative correlation between oxygenated and deoxygenated hemoglobin.

Results

Healthy controls show an increase in cortical activation measured in frontoparietal areas such as the dorsolateral prefrontal cortex. The activation pattern of patients with AD is similar, but weaker. In contrast, bvFTD patients show a more frontopolar pattern, with activation of Broca’s area, instead of the dorsolateral prefrontal cortex and the superior temporal gyrus. The frontoparietal compensation mechanisms, seen in the healthy elderly, were missing in bvFTD patients.

Conclusion

Different frontoparietal cortical activation patterns may indicate a correlate of diverse pathophysiological mechanisms of AD and bvFTD during verbal fluency processing. The AD pattern is weaker and more similar to the healthy pattern, whereas the bvFTD pattern is qualitatively different, namely more frontopolar and without frontoparietal compensation activation. It adheres to a change of cortical activation during the course of the disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s13195-016-0224-8) contains supplementary material, which is available to authorized users.