Expression Profile of Long Non-Coding RNAs in Serum of Patients with Multiple Sclerosis

Santoro, Massimo; Nociti, Viviana; Lucchini, Matteo; Fino, Chiara De; Losavio, Francesco Antonio; Mirabella, Massimiliano

doi:10.1007/s12031-016-0741-8

Cited by 106 publications

(75 citation statements)

References 33 publications

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“…Notably, LINGO1 interacts with APP 37 and is a promising target for multiple sclerosis (MS) with a LINGO1 neutralising antibody in Phase II trials 38 . Similarly, NEAT1 , a regulatory non-coding RNA that is found increased in serum of patients with relapsing-remitting MS 39 , was highly expressed in a1, a2 and o2 AD subclusters (Fig. 3c, k).…”

Section: Resultsmentioning

confidence: 85%

A single cell brain atlas in human Alzheimer’s disease

Grubman

Chew

Ouyang

et al. 2019

Preprint

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26Alzheimer's disease (AD) is a heterogeneous disease that is largely dependent on the complex 27 cellular microenvironment in the brain. This complexity impedes our understanding of how 28 individual cell types contribute to disease progression and outcome. To characterize the 29 molecular and functional cell diversity in the human AD brain we utilized single nuclei RNA-30 seq in AD and control patient brains in order to map the landscape of cellular heterogeneity in 31 AD. We detail gene expression changes at the level of cells and cell subclusters, highlighting 32 specific cellular contributions to global gene expression patterns between control and 33 Alzheimer's patient brains. We observed distinct cellular regulation of APOE which was 34 repressed in oligodendrocyte progenitor cells (OPCs) and astrocyte AD subclusters, and highly 35 enriched in a microglial AD subcluster. In addition, oligodendrocyte and microglia AD 36 subclusters show discordant expression of APOE. Integration of transcription factor regulatory 37 modules with downstream GWAS gene targets revealed subcluster-specific control of AD cell 38 fate transitions. For example, this analysis uncovered that astrocyte diversity in AD was under 39 the control of transcription factor EB (TFEB), a master regulator of lysosomal function and 40 which initiated a regulatory cascade containing multiple AD GWAS genes. These results 41 establish functional links between specific cellular sub-populations in AD, and provide new 42 insights into the coordinated control of AD GWAS genes and their cell-type specific 43 contribution to disease susceptibility. Finally, we created an interactive reference web resource 44 which will facilitate brain and AD researchers to explore the molecular architecture of subtype 45 and AD-specific cell identity, molecular and functional diversity at the single cell level. 46Highlights 47 • We generated the first human single cell transcriptome in AD patient brains 48 • Our study unveiled 9 clusters of cell-type specific and common gene expression 49 patterns between control and AD brains, including clusters of genes that present 50 properties of different cell types (i.e. astrocytes and oligodendrocytes) 51 • Our analyses also uncovered functionally specialized sub-cellular clusters: 5 52 microglial clusters, 8 astrocyte clusters, 6 neuronal clusters, 6 oligodendrocyte 53 clusters, 4 OPC and 2 endothelial clusters, each enriched for specific ontological 54 gene categories 55 • Our analyses found manifold AD GWAS genes specifically associated with one 56 cell-type, and sets of AD GWAS genes co-ordinately and differentially regulated 57 between different brain cell-types in AD sub-cellular clusters 58 • We mapped the regulatory landscape driving transcriptional changes in AD brain, 59 and identified transcription factor networks which we predict to control cell fate 60 transitions between control and AD sub-cellular clusters 61 • Finally, we provide an interactive web-resource that allows the user to further 62 visua...

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Section: Resultsmentioning

confidence: 85%

A single cell brain atlas in human Alzheimer’s disease

Grubman

Chew

Ouyang

et al. 2019

Preprint

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“…VDR is a nuclear receptor that heterodimerizes with the retinoid X receptor, which after ligation with 1,25(OH) 2 D recognizes vitamin D response elements (VDREs) within regulatory regions of targeted genes . Importantly, several studies have revealed that VD can impact the expression of lncRNAs and that peripheral blood mononuclear cells (PBMCs) and serum of patients with MS exhibit altered levels of lncRNAs compared with controls . Studies aiming to understand the mechanisms underpinning lncRNA regulation of gene expression have greatly benefited from the discovery of HOX transcript antisense intergenic RNA (HOTAIR), a lncRNA molecule encoded within the HoxC gene cluster on chromosome 12 and transcribed in an antisense manner with respect to the canonical HoxC genes .…”

Section: Introductionmentioning

confidence: 99%

HOTAIR but not ANRIL long non‐coding RNA contributes to the pathogenesis of multiple sclerosis

et al. 2017

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Studies have revealed that dysregulation in gene expression is one of the main aspects of multiple sclerosis (MS) pathogenesis. Although the molecular pathways underlying the immunomodulatory role of vitamin D (VD) in MS is not completely elucidated, VD has more recently become a topic of interest in immune regulation and is widely administered to patients with MS as an immunomodulatory supplement. Long non-coding RNAs (lncRNAs) are known to play important roles in regulation of gene expression via different mechanisms. Given that VD-related genes are regulated by epigenetic mechanisms, here we aimed to evaluate the role of VD in combination with HOTAIR and ANRIL lncRNAs using in vivo, in vitro and in silico experiments in MS pathogenesis. Our data revealed that HOTAIR but not ANRIL lncRNA is probably involved in the pathogenesis of MS and experimental autoimmune encephalomyelitis through an unclear mechanism and it seems that by affecting the expression, inflammation and VD can influence HOTAIR-related mechanisms, which require further study.

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“…For data analysis, the CT values of pre‐ and post‐stimulation were exported to an Excel file and uploaded into web portal at https://www.qiagen.com/dataanalysiscenter. CT values were normalized using as reference genes Ribosomal protein, large, P0 ( RPLP0 , NM_001002), ZNFX1 antisense RNA 1 ( ZFAS1 , NR_003604) and Growth arrest‐specific 5 ( non‐protein coding ; GAS5 , NR_002578) as previously described (Santoro et al, ).…”

Section: Methodsmentioning

confidence: 99%

ZNRD1‐AS and RP11‐819C21.1 long non‐coding RNA changes following painful laser stimulation correlate with laser‐evoked potential amplitude and habituation in healthy subjects: A pilot study

Santoro

Vollono

Pazzaglia

et al. 2020

European Journal of Pain

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Background Non‐coding RNAs (lncRNAs) are a group of non‐coding RNAs that act as regulators of gene expression; they are implicated in various human diseases and have been reported to be involved in the modulation of pain. We aimed to study whether: (a) lncRNAs modifications could be found in an experimental model of pain; (b) there was a correlation between lncRNA changes and laser evoked potential (LEP) amplitude/laser‐pain rating. Methods Laser evoked potentials were recorded from 11 healthy subjects to both left hand and perioral region stimulation. Three consecutive averages were calculated for each stimulation site in order to investigate the LEP amplitude habituation. Blood samples were obtained immediately before LEP recording (pre‐pain) and 30‐min after the recording of the last LEP average (post‐pain). Eighty‐four lncRNAs, involved in autoimmunity and human inflammatory response, were screened. The criteria used for lncRNAs analysis were fold change >2 and p < .05. By Real‐Time PCR, we identified two lncRNAs up‐regulated at the post‐pain time, as compared to the pre‐pain time: RP11‐819C21.1 (fold change = 8.2; p = .038) and ZNRD1 antisense RNA 1 non‐protein coding (ZNRD1‐AS; fold change = 6.3; p = .037). Results The ZNRD1‐AS up‐regulation was directly correlated with the N1 amplitude, while the RP11‐819C21.1 increase after pain showed a correlation with the reduced N2/P2 amplitude and laser‐pain habituation. Conclusion IncRNA changes in a human experimental phasic pain model. The correlation between lncRNA changes and LEP amplitude and habituation suggests that RP11‐819C21.1 and ZNRD1‐AS could be involved in the pathophysiology of painful diseases characterized by abnormal excitability of the cerebral cortex. Significance Long non‐coding RNAs are upregulated after experimental pain. RP11‐819C21.1 and ZNRD1 could be involved in the pathophysiology of diseases characterized by reduced habituation to pain.

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Expression Profile of Long Non-Coding RNAs in Serum of Patients with Multiple Sclerosis

Cited by 106 publications

References 33 publications

A single cell brain atlas in human Alzheimer’s disease

A single cell brain atlas in human Alzheimer’s disease

HOTAIR but not ANRIL long non‐coding RNA contributes to the pathogenesis of multiple sclerosis

ZNRD1‐AS and RP11‐819C21.1 long non‐coding RNA changes following painful laser stimulation correlate with laser‐evoked potential amplitude and habituation in healthy subjects: A pilot study

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