The role of long noncoding RNAs in amyotrophic lateral sclerosis

Darya Rajabi; Shaghayegh Khanmohammadi; Nima Rezaei

doi:10.1515/revneuro-2023-0155

Article Publicly Available

The role of long noncoding RNAs in amyotrophic lateral sclerosis

Darya Rajabi , Shaghayegh Khanmohammadi and Nima Rezaei

Published/Copyright: March 8, 2024

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From the journal Reviews in the Neurosciences Volume 35 Issue 5

Abstract

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with a poor prognosis leading to death. The diagnosis and treatment of ALS are inherently challenging due to its complex pathomechanism. Long noncoding RNAs (lncRNAs) are transcripts longer than 200 nucleotides involved in different cellular processes, incisively gene expression. In recent years, more studies have been conducted on lncRNA classes and interference in different disease pathologies, showing their promising contribution to diagnosing and treating neurodegenerative diseases. In this review, we discussed the role of lncRNAs like NEAT1 and C9orf72-as in ALS pathogenesis mechanisms caused by mutations in different genes, including TAR DNA-binding protein-43 (TDP-43), fused in sarcoma (FUS), superoxide dismutase type 1 (SOD1). NEAT1 is a well-established lncRNA in ALS pathogenesis; hence, we elaborate on its involvement in forming paraspeckles, stress response, inflammatory response, and apoptosis. Furthermore, antisense lncRNAs (as-lncRNAs), a key group of transcripts from the opposite strand of genes, including ZEB1-AS1 and ATXN2-AS, are discussed as newly identified components in the pathology of ALS. Ultimately, we review the current standing of using lncRNAs as biomarkers and therapeutic agents and the future vision of further studies on lncRNA applications.

Keywords: amyotrophic lateral sclerosis; biomarker; lncRNA; long noncoding RNA; NEAT1; paraspeckles

1 Introduction

Amyotrophic lateral sclerosis (ALS) is the most common motor neuron disease, characterized by the degeneration of motor neurons in the brain and spinal cord. ALS leads to extensive motor and extra-motor symptoms; typically, within 2–5 years, respiratory failure causes patients’ death (Brown and Al-Chalabi 2017; Hardiman et al. 2017). Studies suggest that ALS as an age-relative disease can have a higher prevalence in the future due to the aging of the world population (Arthur et al. 2016; Chiò et al. 2013). Although different randomized controlled trials have failed to provide an effective treatment for ALS due to the disease’s complexity, more research is being conducted (Masrori and Van Damme 2020). This highlights the significance of finding biomarkers and new therapeutic targets.

Gaining a deeper understanding of the role of biomolecules such as noncoding RNAs (ncRNAs) in physiological and pathological mechanisms could provide an opportunity to overcome the complex challenges of diagnosis and treatment of ALS. Only 2–3 percent of the human genome is translated into proteins, while most comprise ncRNAs (Ian et al. 2012). Over the last few decades, studies have revealed the multifaceted function of ncRNAs in different physiological processes (Panni et al. 2020). Long noncoding RNAs (lncRNAs) are a highly diverse group of ncRNAs, characterized by their number of nucleotides and lack of protein-coding potential (Derrien et al. 2012; Hombach and Kretz 2016). Research has shown the role of lncRNAs like NEAT1_2, METTL3, MALAT-1, and ANRIL in the pathogenesis of cancers and neurodegenerative diseases (Li and Wang 2023; Yao et al. 2022).

Over the past few years, more studies have been conducted about the interaction between lncRNA and ALS. Although the exact molecular process of ALS has not been discovered yet, the involvement of lncRNA in different pathways of ALS pathogenesis, like TAR DNA binding protein-43 (TDP-43) and fused in sarcoma (FUS), has been extensively studied (An et al. 2019; Vangoor et al. 2021). Recently, a new pathway has been identified mediated by ZEB1-AS1, a lncRNA present in the pathology of different cancers (Rey et al. 2023).

Understanding the role of lncRNAs in ALS could shed light on the pathomechanism of these diseases and contribute to developing new treatments. Thus, we aimed to review the role of lncRNA in pathogenesis and their potential value as diagnostic and prognostic biomarkers and therapeutic targets in the treatment of ALS.

2 LncRNA definition and classification

LncRNAs are defined as ncRNAs of more than 200 nucleotides; this cutoff excludes small ncRNAs (sncRNAs) like micro RNAs (miRNAs) (O’Brien et al. 2018), PIWI-interacting RNAs (piRNAs) (Ozata et al. 2019), and small interfering RNAs (siRNAs) (Dana et al. 2017; Hombach and Kretz 2016) and ncRNAs close to 200 nucleotides like 75K and 75L. The number of known lncRNAs is increasing, while most work mechanisms still need to be discovered. Different factors make the annotation of lncRNAs more challenging than protein-coding genes. LncRNAs have transcriptional and post-transcriptional features similar to protein-coding genes, but their expression is lower, highly cell-specific, and often restricted to tissue- or time-specific developmental stages (Asim et al. 2021; Corona-Gomez et al. 2022).

Identifying orthologues and paralogues of lncRNAs by sequence similarity is challenging due to their lower conservation during evolution compared to protein-coding RNAs (Uszczynska-Ratajczak et al. 2018). Some subsets of lncRNAs conserve the sequence or genomic position level across species; however, the conservation of lncRNAs does not necessarily lead to conserved functional roles (Bridges et al. 2021). Considering that ncRNAs of the same family have similar functions, different computational methods are developed to predict the ncRNA families. These methods are divided into two main categories: (1) second structure based and (2) sequence based. Sequence-based methods have higher time efficiency and accuracy in comparison to second structure–based methods like GraPPLE (Chen et al. 2023). Several computational methods that utilize a deep-learning framework have been developed in recent years. Sequence-based methods like ncDLRES and ncDENSE are presented to predict ncRNA families (Chen et al. 2023; Wang et al. 2021), whereas GM-lncLoc is designed to predict subcellular localization (Cai et al. 2023). Methods like LncDLSM and LncADeep have improved the process of lncRNA identification and functional annotation (Liu et al. 2019; Wang et al. 2023; Yang et al. 2018). These methods help identify lncRNAs and discover their function, which is crucial for better classification.

There is ongoing debate regarding the definition and classification of lncRNAs, and different criteria have been presented over the years (St Laurent et al. 2015). Figure 1 presents the classification of ncRNAs, with lncRNAs categorized based on three main characteristics: biogenesis, function mechanism, and structure. In this section, we provide a more detailed explanation of the lncRNAs categorization based on biogenesis and mechanism of function.

Figure 1:

Classification of noncoding RNAs, schematic classification of long noncoding RNAs based on biogenesis, mechanism of function, and structure. rRNA: ribosomal RNA; tRNA, transfer RNA; snoRNA, small nucleolar RNA; miRNA, microRNA; piRNA, piwi RNA; cis-lncRNA, cis-acting long noncoding RNA; trans-lncRNA, trans-acting long noncoding RNA; ceRNA, competing endogenous RNA; lincRNA, long intergenic noncoding RNA; eRNA, enhancer-derived RNA.

2.1 Biogenesis

In this classification, lncRNAs are categorized based on the part of the genome they are transcribed from and the mechanism of their biogenesis.

2.1.1 Intergenic and intronic lncRNAs

Intergenic lncRNAs (lincRNAs) are transcripts from intergenic regions, while the transcribed strands from protein-coding genes’ introns are called intronic lncRNAs. The lack of overlap between lincRNAs and protein-coding genes causes distinctions between lincRNAs and genic lncRNAs. While the promoters of lincRNAs share the same level of conservation as the promoters of protein-coding genes, the conservation of lincRNAs is generally weaker, and they tend to undergo rapid evolution (Deniz and Erman 2017). LincRNAs interact with chromatin-modifying enzymes and play a role in gene expression. These lincRNAs can regulate gene expression by two mechanisms: cis- and trans-acting C is-acting lincRNAs control gene expression near their loci on the same chromosome, whereas trans-acting lincRNAs control gene expression of independent loci on other chromosomes (Deniz and Erman 2017; Ransohoff et al. 2018).

2.1.2 Sense and antisense lncRNAs

Sense lncRNAs are transcribed from the sense strand of protein-coding genes, containing their exons, and share the same promoter with that gene. On the other hand, antisense lncRNAs (as-lncRNAs) are transcribed from the opposite strand of either protein-coding or noncoding genes. As-lncRNA, or the long (>200 nucleotides) natural antisense transcripts, can be classified based on their origin, genomic orientation, and mode of action (Khorkova et al. 2014). These transcripts can exert their function in close proximity or at a distance through both cis and trans mechanisms, and this function can be promoted by RNA itself or the transcription process (Pelechano and Steinmetz 2013).

2.1.3 Enhancer and promoter lncRNA

Pol II transcription at promoter and enhancer regions generates promoter upstream transcripts in the antisense direction (PROMPTs) and enhancer lncRNA (eRNA). These transcripts are short-lived lncRNAs with an approximate length of 200–2000 nucleotides, and they are targets of the exosome and have a fast turnover after release from pol II (Wu et al. 2017). eRNAs are mainly transcripts from enhancers more responsive to transcription, like those on open chromatin or low-methylated DNA regions (Han and Li 2022). There are similarities between the functions of PROMPTs and eRNAs, and they also impact each other. Most eukaryotic promoters of protein-coding genes are bidirectional; therefore, in addition to mRNA (sense), they can produce lncRNAs from transcription of antisense direction (Ransohoff et al. 2018). Bidirectional transcription of promoters allows them to function as enhancers and promoters for the same gene. On the other hand, high-expression eRNAs can exert the promoters’ functions, while bidirectional enhancers can act as weak promoters (Han and Li 2022).

2.2 The mechanism of action

The function of lncRNAs is diverse and context-dependent. LncRNAs carry out different roles, such as epigenetic regulation, regulation of transcriptions, post-transcriptional regulation, mRNA splicing, miRNA regulation, and genomic imprinting (Li et al. 2014). LncRNA action involves the up and down-regulation of gene expression mediated by different mechanisms categorized as signal, decoy, guide, and scaffold. These categories are discussed below.

Specific time and developmental stages limit lncRNA transcription. As a result, lncRNAs can function as signals that respond to diverse stimuli. Signal lncRNAs are frequently involved in the transcription of downstream genes. Some lncRNAs of this archetype act as regulators themselves or in combination with proteins like transcription factors (TFs), while others are produced as by-products. The regulatory function of these by-product lncRNAs is exerted indirectly through the initiation, elongation, or termination of transcription (Ahmad et al. 2021; Gao et al. 2020). It is important to mention that developmental stimuli and stress conditions such as DNA damage or cold exposure can induce the signal pathways. For example, KCNQ1ot1 and Xist are expressed in response to developmental stimuli and act in allele specificity of imprinting. They cause active silence of the maternal or paternal allele of the respective imprinted gene (Wang and Chang 2011). Decoy lncRNAs act as “molecular sinks” for miRNAs, TFs, or other RNA-binding proteins (RBPs). This group of lncRNAs implicates negative regulation, and their action leads to transcriptional and translational inhibition by mechanisms like mRNA degradation (Wang and Chang 2011). Guide lncRNAs act as guiding molecules by aiding specific proteins (e.g., TFs) in reaching their target location and performing their biological functions on specific DNA sequences. They use a combination of two molecular processes, binding to a protein and interfacing with selective regions of the genome (Rinn and Chang 2012). Therefore, their function is exerted by RNA–RNA, RNA–protein, and RNA–DNA interactions. The gene regulatory function of this archetype can be repressive or activating, and these molecules can act by both cis and trans mechanisms (Gao et al. 2020; Wang and Chang 2011). Scaffold lncRNAs act as “central platforms” to assemble ribonucleoprotein complexes from multiple proteins (Wang and Chang 2011). The scaffold action of lncRNAs is essential in chromatin and epigenetic modification, as thousands of lincRNAs, as-lncRNAs, and promoter-associated ncRNAs bind to chromatin-modifying complexes (Spitale et al. 2011).

Several lncRNAs exert their function using different archetypes; for instance, the function of COLDAIR is a combination of signal and guide archetypes (Wang and Chang 2011). This function overlap indicates that, based on current understanding, accurately classifying lncRNAs by their function is challenging. Another more accurate classification for lncRNAs has been suggested. In this classification, lncRNAs, based on their transcription site, where their function is exerted, and the distance between these two locations, are categorized into two groups: cis- and trans-acting lncRNAs.

C is-acting lncRNAs regulate the gene expression on the same chromosome, and their action is dependent on the loci from where they are transcribed. Numerous promoter-associated ncRNAs, eRNAs, lincRNAs, and as-lncRNAs use the cis-acting mechanism (Rai et al. 2019). These transcripts participate in chromatin-related processes like modification and modulation of chromatin (Gil and Ulitsky 2020). The action of some lncRNAs on local regulation can be exerted by the interplay between the lncRNA transcripts and regulatory factors. However, regardless of the sequence of transcripts or the production of mature lncRNAs, the processes of transcription and/or splicing the lncRNA, as well as the interaction between DNA elements and lncRNA promoter or gene locus, can execute the expected function of specific lncRNAs (Kopp and Mendell 2018).

T rans-acting lncRNAs exert their function at loci on a different chromosome and/or on the homologous chromosome from which they are transcribed. These molecules are expected to be involved in at least three modes of action: (1) gene regulation at distant loci from their transcription sites, (2) participating in nuclear structure, and (3) regulating the behavior of proteins and/or other RNA molecules (Kopp and Mendell 2018). T rans-acting lncRNAs participate in a process called endogenous target mimicry, in which they, as a decoy, bind miRNAs and block the interaction between miRNAs and their target mRNAs (Rai et al. 2019). Notably, some lncRNAs, including NEAT1, that act near their transcription sites can be rescued by trans expression; this means that NEAT1 scaffold function can also be expressed exogenously (Gil and Ulitsky 2020).

3 LncRNAs in ALS pathogenesis

3.1 NEAT1

Nuclear paraspeckles assembly transcripts 1, named initially as nuclear enriched abundant transcript 1 (NEAT1), is one of the most abundant lncRNAs produced from the multiple endocrine neoplasia type 1 (MEN1) locus on human chromosome 11 (Guru et al. 1997). Two significant isoforms of NEAT1 are identified, which share the same promoter for RNA polymerase II. The first isoform, NEAT1_1 (also known as MENepsilon), is approximately 3.7 kb long in humans and is the sorter and polyadenylated isoform. The second isoform, NEAT1_2 (also known as MENbeta), is the longer isoform with a length of 23 kb in humans. These two isoforms overlap at their 5′ end, but NEAT1_2 differs from NEAT1_1 at its 3′ end with a short poly(A)-rich tract that shows some similarity to metastasis associated lung adenocarcinoma transcript 1 (MALAT1) (Sasaki et al. 2009; Sunwoo et al. 2009). In contrast with other lncRNAs with weak conservation, NEAT1 is relatively conserved across mammalian species. NEAT1 gene structure and NEAT1_1 sequence show a spectrum of conservation between humans and mice, as in opossum. At the same time, a low level of sequence homology of NEAT1_2 is found comparing human, mouse, and opossum DNA (Cornelis et al. 2016). NEAT1_2 is considered an architectural RNA as it is localized and enriched in a specific nuclear body (paraspeckles), and its removal leads to the subcellular location alteration or dispersal of RBPs (Chujo et al. 2016; Nakagawa et al. 2022). NEAT1_1 does not play a direct role in assembling paraspeckles and regulating their number and size (Li et al. 2017). Furthermore, the localization of NEAT1_1 in numerous nonparaspeckle foci in cells called microspeckles indicates NEAT1_1’s independent function (Hirose et al. 2019).

Paraspeckles are unequally small, irregular-sized subnuclear bodies present in varying numbers ranging from 5 to 20 foci per nucleus, depending on the cell type (Fox and Lamond 2010). The primary role of NEAT1_2 is to provide the architectural scaffold of paraspeckles, enabling the construction and preservation of these nuclear bodies. Figure 2 illustrates the structure of a paraspeckle, highlighting its hydrophobic shell, hydrophilic core, and protein distribution. Paraspeckles are enriched for over 40 RBPs (Lee et al. 2022; Smith et al. 2020). These proteins have their specified function exerted by their interactions with NEAT1_2; for example, PSP1 and PSF are involved in paraspeckles localization, and p54nrb/NONO forms heterodimers with PSF and PSP1 (Sasaki et al. 2009). Other proteins like CPSF6 and NUDT21 regulate the ratio of the two isoforms, as FUS and DAZAP1 maintain secondary paraspeckles structure (Yamazaki et al. 2018). Core paraspeckle proteins NONO and SFPQ interact with NEAT1_2 to form a heterodimer. FUS and other proteins then bond the structure of NEAT1_2 strands together to form paraspeckles (An et al. 2019).

Figure 2:

Paraspeckles core and shell structure and the assembly of paraspeckles. SFPQ and NONO proteins multimerization in the middle region of NEAT1-2 forms a heterodimer, and other core proteins, such as FUS, then stabilize the structure. Once the core is formed, the hydrophilic shell proteins will bind to NEAT1_2 considering the 3′ or 5′ ends; FUS proteins prefer to bind to the 5′ end, while the 3′ end bonds more with TDP-43.

The family history of ALS patients indicates that 10 % of cases are familial ALS (fALS) and show an autosomal-dominant inheritance pattern. The remaining 90 % are classified as sporadic ALS (sALS) and do not have an inherited effect on family members (Masrori and Van Damme 2020). ALS-associated mutations exert their pathogenic function through two main mechanisms: loss of nucleolus function and gain of a toxic function in cytoplasm. The presence of paraspeckles in the motoneurons of the ventral horn is a marker in both sALS and fALS, and their RBPs are the main character of ALS pathogenesis in TDP-43 and FUS-related ALS (Shelkovnikova et al. 2018). TDP-43 is a DNA and RNA binding protein distinguished by its high conservation level and expression. This protein plays a role in different steps of RNA metabolism, including transcription, translation, miRNA, and lncRNA processing (Prasad et al. 2019). FUS is an RBP, and its mutation leads to FUS-related ALS in fALS and sALS (Hewitt et al. 2010). Interrupting the interaction of NEAT1 with FUS and TDP-43 prevents the proteins from processing RNA (Nishimoto et al. 2013). The loss of function of TDP-43 leads to its mislocalization and higher deposition into cytoplasm in the stricken neurons. The accumulated TDP-43 in the cytoplasm interacts with different proteins. It gets involved in mRNA splicing and other RNA metabolism processes, and the formation of inclusion bodies not only impairs the normal function of the protein but also leads to gaining toxic features (Prasad et al. 2019). Similarly, in ALS-associated FUS mutations, FUS mislocalization in cytoplasm leads to the formation of multiple cytoplasmic aggregates, confirming the high affinity of FUS protein for nucleus bodies (Shelkovnikova et al. 2014).

TDP-43 and FUS are both involved in stress response and liquid–liquid phase separation (LLPS) via the formation of cytoplasmic stress granules (SGs) (Birsa et al. 2020). As Figure 3 demonstrates, under stressful stimulation, FUS and TDP-43 molecules in the cytoplasm trigger the formation of stress granules (SGs), which promptly induce up-regulation of NEAT1 and recruit core paraspeckle proteins NONO and SFPQ to increase the formation of paraspeckles (An et al. 2019; Li and Wang 2023). At the early disease stages, the NEAT1_2 expression and, consequently, paraspeckles in the motor neurons increase to their highest in both sALS and fALS patients (Nishimoto et al. 2013; Shelkovnikova et al. 2018). At this stage, the elevation of NEAT1_2 levels, considering the protective function of paraspeckles, can be considered a cell response to resist the stress in TDP-43 and FUS-related ALS (McCluggage and Fox 2021; Wang et al. 2020). If the stressful condition continues, splicing factors, as well as TDP-43 and FUS, will be sequestered into cytoplasmic SGs. As paraspeckle density and formation increase, their protective function tends to decline, eventually reaching functional saturation. As a result, the deleterious splicing process cannot be inhibited, leading to an elevation of free NEAT1_1. The increase of free NEAT1_1, decreased NEAT1_2, and reduced paraspeckle function lead to a decline in protective function, which is believed to contribute to motor neuron death (Nishimoto et al. 2021).

Figure 3:

Neuron stress response in TDP-43 and FUS-related ALS. (A) The stress-induced elevation of NEAT1 isoforms and ALS pathogenic proteins in the cytoplasm induces the formation of paraspeckles and stress granules to sequester the NEAT1 isoforms, TDP-43, and FUS proteins and inhibit their accumulation. (B) As the stress continues, paraspeckles and stress granules formation and density increase to the point of saturation. (C) The increase of NEAT1_1 in cytoplasm and imbalanced NEAT1_1 to NEAT1_2 ratio leads to cell apoptosis.

The up-regulation of NEAT1 strands under stress conditions assists in forming TDP-43 nuclear bodies via liquid–liquid phase separation. This process reduces the need for SG assembly, ultimately preventing the accumulation of TDP-43 in the cytoplasm (Wang et al. 2020). The complex secondary structure of NEAT1 creates several binding sites for TDP-43 and other binding proteins, resulting in polyvalent interaction and co-phase separation of TDP-43 and NAET1. On the other hand, shorter RNAs (e.g., tRNAs), which cannot neutralize numerous TDP-43 proteins, segregate TDP-43 molecules individually and suppress LLPS. This implies the multifaceted cross-regulation between TDP-43, NEAT1, SGs, and paraspeckles (Malik and Barmada 2020; Wang et al. 2020). It has been reported that the excess amount of full-length TDP-43 causes an up-regulation of NEAT1_1 isoform in the murine CNS, and this isoform can suppress the TDP-43 toxicity in yeast and fly models (Matsukawa et al. 2021).

Genome analysis showed that FUS prefers binding to the 5′ end of NEAT1, whereas TDP-43 binds to the 3′ end (Lagier-Tourenne et al. 2012). This indicates that FUS proteins can be influenced by both NEAT1_1 and NEAT1_2, while for TDP-43, it is more likely that it only binds to NEAT1_2 (Li and Wang 2023). FUS, similar to other significant paraspeckles proteins such as p54nrb/NONO and PSF, contributes to maintaining the steady-state level of NEAT1 transcripts. The overexpression of other paraspeckle proteins compensates for the effect of FUS knockdown; in particular, p54nrb/NONO is suggested as a potential substitute for the architectural role of FUS in paraspeckles. FUS is not directly involved in NEAT1_2 stabilization, and its function is exerted downstream of NEAT1_2 synthesis in paraspeckle maturation (An et al. 2019). Regarding FUS’s association with the 5′ end of NEAT1, it appears that FUS could be instrumental in recruiting NEAT1_1 to paraspeckle formation as the construction rate increases (An et al. 2019). Notably, the lack of mutant FUS at paraspeckles formation loci induces the segregation of NEAT1_1 from paraspeckles (An et al. 2019).

Knockdown of NEAT1 relatively reverses the impact of lipopolysaccharide on cell viability and suppresses cell apoptosis and inflammatory responses as short interference NEAT1 inhibits the tumor necrosis factor-α, interleukin-1β, and interleukin-6 expression (An et al. 2021). miR-211-5p is a miRNA on chromosome 15q13 and plays a regulatory role in various diseases, including spinal cord injuries (SCI), by directly targeting the activating transcription factor 6 (An et al. 2021). Mitogen-activated protein kinase 1 (MAPK1), a downstream target gene of miR-211-5p, which is also known as extracellular signal-regulated kinase 2 (the function pathway of protein), is involved in the initiation of the secondary injury of SCI and is identified as a gene involved in neuronal developmental disorders including ALS (An et al. 2021; Yadav and Srivastava 2018). It is suggested that NEAT1 acts as a sponge for this miRNA as it has multiple binding sites for this lncRNA. miR-211-5p suppression or down-regulation reverses the NEAT1 effects on cell viability, and overexpression of MAPK1 partially disaffects NEAT1 knockdown. Altogether, NEAT1 knockdown reduces the apoptosis and inflammation via miR-211-5p/MAPK1 axis (An et al. 2021). Another study showed that the knockdown of NEAT1 reverses the increase of caspase-3, which is induced by 1-methyl-4-phenylpyridinium (MPP+, a neurotoxin used in Parkinson’s Disease [PD] models) apoptotic pathway, and reduces the Bax/Bcl2 ratio, which is an apoptosis marker (Liu and Lu 2018). Together, this suggests another path in which the knockdown of NEAT1 can suppress cell apoptosis.

However, most of the results regarding the interaction between NEAT1 and p53 are in the context of cancer and tumor suppression; NEAT1 is essential to p53-dependent apoptosis in response to DNA damage (Mello et al. 2017). It is suggested that NEAT1_2 can be an important target in the p53 pathway, as p53 stimulates NEAT1_2 expression and induces paraspeckle formation to prevent DNA damage accumulation in response to stress (Adriaens et al. 2016; Idogawa et al. 2017). It should be mentioned that NEAT1_1, which compared to NEAT1_2, is widely expressed in most human tissues, and its elevated levels likely cause changes in gene expression; it has also been demonstrated to interact with the p53 pathway (Idogawa et al. 2017; Mello et al. 2017). In light of NEAT1_2’s antiapoptosis function and NEAT1_1’s role in promoting apoptosis and neuron death, it seems that the balance between these two isoforms determines the cell’s fate (Nishimoto et al. 2021).

3.2 C9ORF72

The well-established genetic cause of ALS is a GGGGCC (G₄C₂) repeat expansion in the first intron of C9ORF72 on chromosome 9 (Renton et al. 2011), which accounts for 10 % of sALS and 50 % of fALS cases (Majounie et al. 2012). This gene can be transcribed bidirectionally, and both strands are transcribed to produce sense transcripts with G₄C₂ repeats and antisense transcripts (C9ORF72-AS) with G₄C₂ repeats. These RNA foci accumulate in cells; interestingly, the antisense foci are more numerous compared to sense strands (Lagier-Tourenne et al. 2013). The aberrant RNA foci seem to isolate RBPs like hnRNP-A3, FUS, and TDP-43 and affect RNA metabolism (Laneve et al. 2021). Sense and antisense strands transcribed from this locus form dipeptide repeat (DPR) proteins, including poly(PA), poly(GA), poly(GP), poly(GR), and poly(PR) (Krishnan et al. 2022). Emerging evidence suggests that the activation of the TDP-43 pathology pathway could be facilitated by the presence of both or each one of repeat RNA and DPR proteins, particularly poly(GR) and poly(PR) (Cook et al. 2020). Poly(PR) has been shown to interact with NEAT1 through two primary pathways: (a) an increase in the expression of NEAT1, specifically NEAT1_2, can occur due to the overexpression of hnRNPM, and (b) the interaction between poly(PR) and paraspeckle proteins such as NONO and SFPQ may result in an indirect impact on NEAT1 (Suzuki et al. 2019). The localization of NEAT1_1 outside of paraspeckles supports this proposition that poly(PR) influence on NEAT1 regulation could be exerted by modulating NEAT1_1, leading to neurotoxicity (Suzuki et al. 2019). Furthermore, poly(PR) and, more significantly, C9ORF72-AS have exhibited a significant association with the nuclear depletion of TDP-43 and its accumulation in the cytoplasm in C9-ALS cases (Cooper-Knock et al. 2015; Suzuki et al. 2019). Altogether, the interaction of poly(PR) with paraspeckles proteins and NEAT1 isoforms disrupts the paraspeckles regulation and NEAT1 isoforms balance, which, as mentioned earlier, triggers the apoptotic response and motoneurons death. In gene therapy, antisense oligonucleotides (ASOs) are utilized to target the repeat expansion in C9ORF72 in order to avoid RNA foci accumulation and rehabilitate the genetic alterations (Laneve et al. 2021; Lagier-Tourenne et al. 2013).

3.3 ATXN2-AS

Spinocerebellar ataxia type 2 (SCA2) is an autosomal-dominant genetic disease caused by a CAG mutation in the first exon of the ATXN2 gene. ATXN2 protein is a ubiquitous RBP that plays roles in cellular processes, including mRNA maturation and transcription (Magaña et al. 2013). Certain genetic overlaps between ALS and SCA2 have been identified, as expanded CAG repeats of ≥29 in ATXN2 are associated with ALS (Van Damme et al. 2011). Intermediate-length ATXN2 polyQ repeat expansions with a repeat of ≥27 (the normal repeat 22 or 23) and ≤34 (the repeat responsible for SCA2) are associated with ALS in both FUS and TDP-43 pathogenic mechanisms (Elden et al. 2010; Farg et al. 2013). ATXN2 is a bidirectional locus, and ATXN2-AS accounts for approximately 12 % of ATXN2 expression. The CUG repeat expansion of ATXN2-AS causes a neurotoxic feature, and it is assumed that expanded ATSN2-AS (expATXN2-AS) enhances ALS pathogenesis. Similar to antisense transcripts at mutant C9ORF72, expATXN2-AS interacts with RBPs and sequesters them, leading to the failure in rRNA processing and mRNA splicing (Li et al. 2016; Tollervey et al. 2011).

3.4 ZEB1-AS1

Zinc finger E-box binding homeobox 1 antisense 1 (ZEB1-AS1) is a well-known as-lncRNA catheterized as an oncogenic regulator. ZEB1-AS1 is involved in the pathology of different cancers, including glioma, B-lymphoblastic leukemia, prostate cancer, bladder cancer, osteosarcoma, thyroid cancer, colorectal cancer, hepatocellular carcinoma, and esophageal squamous cell carcinoma (Ghafouri-Fard et al. 2023; Khanmohammadi and Fallahtafti 2023; Li et al. 2018). This lncRNA exerts its regulatory or pathologic function via different signaling pathways, many of which are miR axes (Ghafouri-Fard et al. 2023). ZEB1-AS1 is transcribed from a bidirectional promoter of the ZEB1 gene and is found down-regulated in peripheral blood mononuclear cells (PBMCs) of sALS patients (Gagliardi et al. 2018). Glycogen synthase kinase 3-β (GSK3β) and β-catenin, downstream targets of ZEB1-AS1, are potentially involved in the action mechanism of this lncRNA (Rey et al. 2023). GSK3 is a serine/threonine protein kinase that is up-regulated in the brain and spinal cord of ALS patients, and β-catenin accumulation, as a critical molecule in Wnt pathway activation, leads to a decrease of Wnt pathway initiation in in vitro ALS model (Pinto et al. 2019). Additionally, has-miR-139 may connect ZEB1-AS1 with motor neuron death in sALS and FUS-related ALS by targeting β-catenin (Rey et al. 2023).

3.5 Competing endogenous RNAs

Competing endogenous RNAs (ceRNAs) are transcripts that, regardless of their ability to code a protein or not, share the common miRNA recognition element. The hypothesis is that site-containing RNAs act as a sponge to titrate miRNAs, and the crosstalk between these site-containing RNAs leads to a potential competition for the miRNA pools, indicating a regulatory function as the expression of a ceRNA is up- or down-regulated (Denzler et al. 2014). In recent years, two ceRNA networks composed of circRNA, miRNA, and mRNA regarding ALS disease have been introduced (Dolinar et al. 2019; Ravnik-Glavač and Glavač 2020). PSEN1, LRRK2, and APP are hub genes recently identified as involved genes of sALS and its prognostic biomarkers. Three ceRNA networks have been presented as potential regulatory pathways in sALS pathogenesis: (a) NEAT1-miR-373-3p/miR-372-3p-APP/miR-302c-3p, (b) circ_0000002-miR-302d-3p/miR-373-3p-APP, and (c) XIST-miR-9-5p/miR-671-5p-LRRK2/miR-30e-5p (Liao et al. 2023).

Although few studies have investigated the role of lncRNA in ceRNA networks associated with ALS, the ceRNA mechanisms that regulate myogenesis could be relevant to ALS. Some of the lncRNAs involved in these mechanisms are linc-MD1, lncRNA H19, MALAT1, lnc-mg, lncMD, Yam, and Sirt1-AS (Moreno-García et al. 2020). MALAT1, also known as nuclear enriched abundant transcript 2 (NEAT2), is a gene with greater than 80 % conservation at its 3′ end on human chromosome 11q13.1 (Arun et al. 2020). The degeneration of this lncRNA is involved in the pathological mechanism of cancers, diabetes, aging, and other immunomodulatory diseases (Abdulle et al. 2019; Ghafouri-Fard et al. 2021; Goyal et al. 2021; Huang et al. 2022; Masrour et al. 2023). The expression level of MALAT1, like NEAT1, is increased in ALS patients, and TDP-43 can also bind to this transcript (Tollervey et al. 2011). A functional annotation of this lncRNA and the genes it regulates suggests a ceRNA network, as MALAT1 forms a miRNA sponge for 75 genes in ALS samples, in which some genes, including DECR1, CPEB4, VPS37A, SP1, EEA1, RB1, and GCLC, reported to be involved in ALS pathogenesis (Liu et al. 2021).

3.6 Hsrω/sat III

Hsrω (heat shock RNA omega) is a noncoding gene that produces several lncRNAs and is expressed in almost every cell type in flies. This gene is essential for normal development in addition to stress shocks. Similar to NEAT1, the produced transcripts and specific nuclear RBPs would assemble nuclear structures called omega speckles that disappear after the heat shock in approximately 30–60 min (Jolly and Lakhotia 2006; Prasanth et al. 2000). There is no homolog of the hsrω in mammalian cells. However, the sat III in the human genome showed similarities, including accumulation at the site of synthesis and interactions with different RNA-processing factors in stress response (Jolly and Lakhotia 2006). When RBPs of omega speckles in Drosophila are matched with RBPs of paraspeckles in humans, the Cabeza or dFUS and TBPH are humans’ homologs of FUS and TDP-43 (Singh 2022). Hsrω lncRNA regulates the quantity of arginine methyltransferases type I and type II in Drosophila, the enzymes involved in FUS methylation. After depletion of hsrω lncRNA, dFUS accumulates in the cytoplasm and loses its nuclear function (Singh 2022; Lo Piccolo and Yamaguchi 2017). TBPH is a constituent of omega speckles in Drosophila; it accumulates at the gene locus and binds to hsrω lncRNA to assemble the omega speckless (Lo Piccolo et al. 2018). Further studies on hsrω lncRNA could indicate how sat III could be used in the future treatment of ALS, as during heat shock, this lncRNA binds to RBPs including CBP, HSF1, 9G8, HAP, C2PA, Sam68, SRp30, and ASF/SF2 to form nuclear bodies (Singh 2022).

4 LncRNAs as a biomarker in ALS

The treatment, prognosis, and early diagnosis of ALS is an unresolved challenge due to the complexity of the disease. The absence of valid and sensitive biomarkers results in poor prognosis due to delayed diagnosis and lack of reliable therapy response assessment (Yang et al. 2021a). Biomarkers aid the earlier diagnosis, resolving the diagnosis uncertainties and identification of a pre-symptomatic phase of diseases. Clinical biomarkers with neurophysiological approaches like the study of nerve conduction, electromyography, and motor unit number estimation and imaging techniques, including functional magnetic resonance imaging, positron emission tomography, single-photon emission computed tomography, and diffusion tensor imaging, are used as biomarkers (Chen and Shang 2015). Body fluids, including blood and cerebrospinal fluid (CSF), are suitable resources for detecting molecular biomarkers (Staats et al. 2022). CSF provides a low complex biofluid for assaying low-abundance molecules. However, late-stage ALS complications make invasive procedures like lumbar puncture unsuitable. This results in the use of CSF biomarkers and imaging techniques in the initial stages, while blood and urine samples are utilized as biomarker sources for prognostication and treatment response evaluation in late-stage cases (Sturmey and Malaspina 2022). Detecting protein biomarkers in CSF, blood, and other biofluids poses challenges, including protein aggregation and clearance (Sturmey and Malaspina 2022); therefore, RNAs are considered as another potential biomarker molecule (Grima et al. 2023); however, only a few studies focused on lncRNAs. A summary of studies on lncRNAs as biomarkers is presented in Table 1.

Table 1:

LncRNA as a biomarker in ALS.

Author, year	Population	Sample	LncRNA name	Regulation alteration	Role of lncRNA
S. Gagliardi, 2018	10 sALS, 2 FUS-related ALS patients, 2 TDP-43–related ALS patients, 3 SOD1-related ALS patients, and 3 CTR	Spinal cord tissue and PBMC	In sALS patients: ENST00000423714.1 (ZEB1-AS1)	Down-regulated	ALS diagnostic biomarker
			ENST00000607333.1 (XXbac-BPG252P9.10 or IER3-AS)
			ENST00000536865.1 (ZBTB11-AS1)
			In FUS-related ALS patients: ENST00000458479.1 (PAXBP-AS)	Up-regulated
			In TDP-related ALS patients: ENST00000438646.1 (SNAP25-AS)	Down-regulated
			In SOD1-mutated ALS patients: ENST00000502041.2 (CKMT2-AS)	Down-regulated

Y. Yu, 2022	5 sALS and 5 CTR	Peripheral blood leukocytes	lnc-POTEM-4:7	Down-regulated	sALS specific diagnostic biomarker
			lnc-DYRYK2-7:1
			lnc-ABCA12-3:1
			lnc-NR3C2-8:1	Down-regulated	Diagnostic biomarker for neurodegenerative diseases
			lnc-CNTN4-2:1
			XIST in male cases

D. Sproviero, 2022	6 sALS patients, 9 PD patients, 9 FTD patients, 6 AD patients, and 6 CTR	Plasma	Gene name RNU11 (lincRNA) AP003068.23 (antisense) VIM-AS1 (antisense) LINC00989 (lincRNA) TSIX (lincRNA)	Increased in SEVs of ALS and both SEVs and LEVs of FTD patients	ALS diagnostic biomarker
				Decreased in LEVs of ALS, PD, and FTD patients
				Decreased in LEVs of ALS patients
				Increased in LEVs of FTD patients

F. Rey, 2021	Mice with more than 27 mutant SOD1 copies	Brain and spinal cord tissues	Linc-Brn1a linc-Brn1b	Down-regulated in brain regions significantly in the hippocampus and prefrontal cortex and up-regulated in the spinal cord (especially the lumbar spinal cord)	ALS diagnostic and prognostic biomarker
			Linc-p21
			Tug1
			Hottip	Down-regulated in the mesencephalon, cerebellum, and lumbar spinal cord
			Hottip	Up-regulated in cervical and thoracic spinal cord
			Eldrr	Down-regulated in the mesencephalon and cerebellum and up-regulated in the spinal cord
			Linc-Enc1	Down-regulated in brain parts
			Linc-Enc1	Up-regulated in the lumbar spinal cord at 8 weeks mice and down-regulated in the lumbar spinal cord and prefrontal cortex at 18 weeks mice
			Fendrr	Down-regulated in the prefrontal cortex and up-regulated in the cervical spinal cord at 8 weeks mice
			Fendrr	Down-regulated in the hippocampus and up-regulated in the thoracic spinal cord at 18 weeks mice

Gagliardi et al. performed a whole transcriptome profiling on PBMCs of sALS patients with a FUS, SOD1, or TARDBR mutation and healthy controls. They found 293 differentially expressed (DE) lncRNAs in sALS patients, some of which are already linked to neurodegenerative disease, including UBXN7-AS, ATG10-AS, and ADORA2A-AS. ENST00000607333.1 (XXbac-BPG252P9.10), the antisense of the IER3 gene (involved in regulating antiapoptotic genes), and ENST00000536865.1 (ZBTB11-AS1) were found down-regulated in sALS patients compared to controls. This study targeted the co-expression networks of lncRNAs and mRNAs in sALS patients. They found six co-expressed gene networks; the first comprises 14 coding genes and two lincRNAs. Two clusters with only coding genes and three with lincRNAs only were reported. Further investigation into these lncRNAs and networks could lead to the discovery of new pathological mechanisms, biomarkers, and potential therapeutic agents (Gagliardi et al. 2018).

A study on peripheral blood leucocytes of sALS and PD patients presented lnc-POTEM-4:7, lnc-DYRYK2-7:1, and lnc-ABCA12-3:1 as potential sALS-specific peripheral blood biomarkers. These molecules showed down-regulation in sALS patients, while their expression levels increased in PD patients. It is also worth mentioning that both PD and sALS patients showed decreased expression of lnc-NR3C2-8:1 and lnc-CNTN4-2:1 (Yu et al. 2022).

Extracellular vesicles (EVs) are divided into two groups: small EVs (SEVs; 30–150 nm) and large EVs (LEVs; 100–1000 nm). SEVs are synthesized intracellularly and are released by multivesicular body exocytosis, whereas LEVs are released following the plasma membrane budding in physiologic and, more importantly, pathological conditions (Sproviero et al. 2022). EVs’ potential to cross the blood–brain barrier, their availability in the blood, CSF, urine, and saliva, and their double membrane structure, which protects the proteins and RNAs from degradation, make these molecules intriguing biomarkers (Barbo and Ravnik-Glavač 2023). Plasma-derived EVs showed significant differences between SEVs and LEVs in plasma samples of neurodegenerative disease patients and healthy controls, primarily the differentially expressed (DE) mRNAs, as SEVs were enriched with higher amounts of DE mRNAs compared to LEVs in ALS. No significant difference in lncRNAs in SEVs and LEVs was found; however, DE lncRNAs in SEVs and LEVs were observed to differ from controls (Sproviero et al. 2022).

Beyond the diagnostic role of biomarkers, the presence of markers for evaluating response to treatment is necessary. As mentioned, G₄C₂ repeat expansion in C9ORF72 poses a significant role in the genetic cause of ALS, and finding therapies to decrease the repeat-containing RNAs and their products is of great importance (Krishnan et al. 2022). Currently, poly(GP) is utilized to evaluate target engagement in patients’ CSF (Cammack et al. 2019; Gendron et al. 2017). Moreover, poly(GA) and poly(GR) are introduced as target engagement biomarkers due to their almost constant levels and fast response to ASO compared to poly(GP) (Krishnan et al. 2022).

Another study investigated the deregulated expression of a group of lncRNAs (Tug1, linc-p21, linc-Enc1, linc–Brn1a, linc–Brn1b, Hottip, Fendrr, and Eldrr) in a murine familial model of ALS at the presymptomatic (8 weeks) and symptomatic (18 weeks) stage of the disease (Rey et al. 2021). The deregulation pattern of these lncRNAs varies significantly in different parts of the central nervous system, as the expression level of these lncRNAs can be altered variously and even reversely in distinct areas. Linc-p21 showed up-regulation in the spinal cord, whereas it decreased in all central brain areas of 18W mice. This lncRNA suppresses the p53 transcriptional pathway, and its up-regulation could be the reason for the high apoptosis in the spinal cord. In the brain, an inflammatory mechanism was suggested due to the down-regulation of Tug1, which leads to an increased expression of Tril/Tlr4, resulting in an inflammatory response (Rey et al. 2021). Similarly, the distribution of these lncRNAs up and down-regulation in different parts of the brain and spinal cord suggests the need for more investigation on these molecules as they could be diagnostic, prognostic, or therapeutic agents for ALS. Moreover, in this study, the expression of the human homologs of these lncRNAs, which were TUG1 (Tug1), TP53COR (linc-p21), HOTTIP (Hottip), PANTR1 (linc-Brn1a), ELDRR (Eldrr), and FENDRR (Fendrr), was analyzed in an in vitro model. The change in their expression with a tendency to be down-regulated, especially more significant in HOTTIP and ELDRR loci, shows that further investigation into lncRNA expression in ALS patients with SOD1 mutation is required (Rey et al. 2021).

As of 2023, the FDA approved seven drugs, including Qalsody, Relyviro, Radicava, Rilutek, Tiglutik, Exservan, and Nuedexta, to treat ALS and its symptoms (Aschenbrenner 2023; Manjupriya et al. 2023; van Roon-Mom et al. 2023). Gene therapy, immunotherapy, and stem cell-exosome therapy (ASC-exosome) are other ALS treatment approaches. In gene therapy, using ASOs to silence G₄C₂ repeat expansion in C9orf72 and target ATXN2 is considered practical therapy interventions; however, genome editing still faces many challenges (Yang et al. 2021b).

ncRNA-based drugs could directly target the nucleus, influencing gene expression at early stages such as transcription, epigenetic regulation, and RNA processing (Buonaiuto et al. 2021). Different research results show that in the case of CAG/CTG repeat pathogenesis, the pathological mechanism and treatment cannot be about a single gene effect. In addition to targeting sense transcripts/proteins, focusing on antisense transcripts can be of therapeutic value. For instance, suppressing ATXN2-AS can be a further or alternative therapeutic intervention in SCA2, as well as a potential approach for ALS treatment, considering the TDP-43 and Ataxin-2 interaction (Elden et al. 2010; Li et al. 2016). In the case of treatment strategies targeting the NEAT1, two main instructions are considered and urged to be implemented: (a) preserving a proper expression of NEAT1_2 for conserving the cell viability by keeping the paraspeckles balance and (b) removing the free and accumulated NEAT1_1 to stop its apoptotic promoting and other deleterious function (Nishimoto et al. 2021).

5 Conclusions

In conclusion, lncRNAs have emerged as key regulators in the pathogenesis of ALS. They play a crucial role in various cellular processes, such as neuronal differentiation, apoptosis, and oxidative stress. Several studies reported dysregulation of lncRNAs in ALS patients, and their expression patterns were correlated with disease progression and severity. Moreover, lncRNAs have also been identified as potential diagnostic and therapeutic targets for ALS. However, further research is needed to fully understand the mechanisms underlying lncRNA-mediated regulation in ALS and to develop effective therapeutic strategies. Therefore, future studies should focus on identifying novel lncRNAs involved in ALS pathogenesis and elucidating their functional roles, which may lead to the development of novel therapeutic targets for this debilitating disease.

Corresponding author: Nima Rezaei, Research Center for Immunodeficiencies, Children’s Medical Center, No 63, Gharib Ave, Keshavarz Blv, Tehran, 1419733151, Iran; Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Children’s Medical Center, No 63, Gharib Ave, Keshavarz Blv, Tehran, 1419733151, Iran; and Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Felestin St., Keshavarz Blvd., Tehran, 1416634793, Iran, E-mail: rezaei_nima@yahoo.com

Research ethics: Not applicable.
Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission. DR: conceptualization – data gathering – writing primary draft – editing. SK: project administration – writing – editing. NR: conceptualization, editing.
Competing interests: The authors state no conflict of interest.
Research funding: None declared.
Data availability: Not applicable.

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Received: 2023-12-14

Accepted: 2024-02-18

Published Online: 2024-03-08

Published in Print: 2024-07-26

Articles in the same Issue

https://doi.org/10.1515/revneuro-2023-0155

Keywords for this article

amyotrophic lateral sclerosis; biomarker; lncRNA; long noncoding RNA; NEAT1; paraspeckles