Three MBNL paralogs are expressed in mammals, MBNL1, MBNL2, and MBNL3, which can be involved in regulating alternative splicing, mRNA stability, translation and so on (Charizanis et al., 2012; Wang et al., 2012). A large amount of previous studies have revealed the critical role of MBNL proteins in muscle or heart-related disorders, while in recent years, a close relationship between the loss-of-function of MBNL and DM1 brain-related phenotypes were also detected (Matynia et al., 2010; Charizanis et al., 2012; Goodwin et al., 2015), especially MBNL2. Nowadays, hundreds of dysregulated splicing factors, including in Cacna1d (McKinney et al., 2009), Tanc2 (Han et al., 2010), Ndrg4 (Yamamoto et al., 2011), and GRIN1 (Shimizu et al., 2000) have been detected in the brain of Mbnl 2–/– mice, most of which were similarly dysregulated in DM1 patients, indicating a critical role of the Mbnl2 loss in DM1 brain pathology (Charizanis et al., 2012). Further, Mbnl2–/– mice which are exposed to sleep deprivation also developed several CNS features including impaired long-term potentiation (LTP), deficits in spatial memory, reduced synaptic NMDAR response and impaired hippocampal synaptic plasticity (Charizanis et al., 2012), which were similar to the DM1 phenotype. In 2018, one study described prolonged and enhanced responsiveness to intracortical train stimulation in Mbnl2–/– mice, partially attributed to abnormal glutamate neurotransmission (Chen et al., 2018). Particularly, these abnormalities have also been observed in DM1 patients (Meola and Sansone, 2007; Takado et al., 2015).

Several studies also reported a potential role of MBNL1 protein in CNS disorders. For example, cognitive and behavioral abnormalities have been discovered in Mbnl1–/– mice (Matynia et al., 2010). In cultured primary hippocampal neurons and EpA960/CaMKII-Cre mice (a brain-specific DM1 model carrying 960 DMPK CTG repeats in the postnatal brain), expanded CUG repeats led to deubiquitination of cytoplasmic MBNL1, subsequent nuclear translocation, and morphological defects. These effects can be ameliorated by inhibiting the degradation of lysine 63-linked polyubiquitin chains or by promoting MBNL1 ubiquitination (Wang P. Y. et al., 2018). In 2020, cell studies shown that gain-of-function of MBNL1 could reverse the proliferation defect of skeletal muscle satellite cells in DM1 by inhibiting autophagy via the mTOR pathway (Song et al., 2020). Moreover, functional characterization of neuronal cells derived from human embryonic stem (ES) cells reported a reduced proliferative capacity and increased autophagy associated with alterations of the mTOR signaling pathway, while gain-of-function of MBNL1 rescued the phenotype (Denis et al., 2013), suggesting that MBNL1 loss might influence brain pathology by regulating the mTOR signaling pathway. Some important splicing defects have also been detected in the brain of Mbnl1–/– mice, in genes such as Sorbs1, Dclk1, and Camk2d (Suenaga et al., 2012). However, the extent of alternative splicing defects in the brain of Mbnl1–/– mice was much less than that observed in DM1. A number of alternative exons, such as GRIN1 exon 4, APP exon 7, and Tau exons 3 and 9, which have already been reported to be mis-spliced in the brains of DM1 patients, were unaltered in Mbnl1–/– mice, thus indicating a limited contribution of MBNL1 to DM1 CNS defects (Suenaga et al., 2012).

In addition, it’s worth noting that the combined loss of MBNL1 and MBNL2 has shown infant/immature structural phenotypes in mutant brains, similar to that of DM1 patients (Goodwin et al., 2015). Besides, single gene knockout may also contribute to the compensatory upregulation of the remaining Mbnl genes (Lee et al., 2013). In Mbnl1–/– mice, the expression of MBNL2 could be upregulated, which subsequently targets transcripts that are normally regulated by MBNL1 (Lee et al., 2013). These findings indicate a collaborative role of MBNL1 and MBNL2 involved in DM1 CNS.

The human CELF family has six members, all of which are involved in alternative splicing regulation (Ladd et al., 2001, 2004). Among these, the upregulations of CELF1 and CELF2 have been observed in the brain of DM1 patients (Dhaenens et al., 2011).

CELF1 has been identified as a (CUG)n repeat-binding protein (Timchenko et al., 1996). Unlike MBNL1, it is increased in DM1 patients mainly through PKC-mediated phosphorylation to stabilize the protein (Kuyumcu-Martinez et al., 2007), or through decreased levels of miR-23a/b (Kalsotra et al., 2014). In opposite, the increasing expression of CELF2 is not related to protein hyperphosphorylation, indicating other potential regulatory mechanisms. CELF1 and CELF2 can influence various transcripts (Ladd, 2013) in the DM1 brain, such as different exons of Tau and NMDAR1 exon 5 (Leroy et al., 2006a,b). Tau proteins can promote neurite outgrowth, organize axonal microtubules, and participate in kinesin-dependent axonal transport (Andreadis, 2012). NMDARs are key components of glutamate-mediated excitatory signaling, which can contribute to excitatory synaptic transmission and synaptic plasticity, thought to be the basis of learning and memory (Zorumski and Izumi, 2012). It has been discovered that four exons (2, 3, 6, and 10) of Tau isoforms could respond to one or more CELF proteins in DM1 (Leroy et al., 2006a,b; Dhaenens et al., 2011). CELF2 can regulate alternative exon 5 transcripts of NMDAR1 to change neuronal excitation in rat brain (Zhang et al., 2002), while CELF1 is inefficient. Aside from alternative splicing regulation, CELF proteins can also participate in regulating mRNA adenylation status, stability, and translation in various cell types (Dasgupta and Ladd, 2012), indicating its potential cytoplasmic functions in the brain.

RBFOX proteins are sequence-specific RNA binding proteins which can regulate alternative splicing in multiple tissues, such as skeletal muscle, heart, and brain (Gehman et al., 2011; Singh et al., 2014; Conboy, 2017; Jacko et al., 2018). Nowadays, it has been discovered that RBFOX1 is involved in the regulation of synapses and autism-related genes in the cytoplasm of neurons (Wang et al., 2016). Klinck et al. (2014) reported that MBNL1 and RBFOX1 protein could co-regulate the splicing of a series genes involved in muscle function and development, some of which are also mis-spliced in DM1 tissues. And the decreased RBFOX1 may amplify the mis-splicing changes caused by the loss-of-function of MBNL1. At the same time, they found that the ectopic expression of RBFOX1 partially rescued the mis-splicing of Tau exon 2 in glioblastoma cells. Since the MBNL proteins have been shown to regulate the splicing of Tau exon 2 in DM1 brains, it is therefore interesting to postulate that cooperation of MBNL and RBFOX1 might regulate Tau splicing in DM1 brains. Nevertheless, Sellier’s researches proposed different results, that RBFOX1 could bind to expanded CUG RNA repeats, competing with MBNL1 and reducing the sequestration of MBNL1 in DM2 muscle cells, which suggest a partly competitive relationship between RBFOX1 and MBNL1 (Sellier et al., 2018). Misra et al. (2020) found a new non-muscle RBFOX2₄₀ splice isoform which is overexpressed in DM1 patient hearts. Particularly, mice expressing the RBFOX2₄₀ isoform in hearts also performed DM1-related cardiac conduction dysfunctions (Misra et al., 2020), which may due to its promotion of the production of pathogenic ion channel splice variants. All of these results provide a novel idea explaining the splicing dysregulation in DM1, though their possible roles in CNS dysfunctions still need further exploration.

Nowadays, hundreds of spliced effector genes changes have been discovered in the DM1 brain (Jiang et al., 2004; de León and Cisneros, 2008; Suenaga et al., 2012; Hernández-Hernández et al., 2013a; Otero et al., 2021). Jiang et al. (2004) screened 45 exons (in 31 genes) spliced in the brain of DM1 patients, wherein four of them changed in the ratio of exon inclusion/exclusion splice products, including decreased inclusion of APP exon 7, Tau exons 2 and 10, and increased inclusion of NMDAR1 receptor exon 5. Interestingly, the sequences encoding APP exons 7 and 8 are excluded in neurons, but are included in astrocytes, indicating the splicing defects in astrocytes. In 2021, via detecting transcriptome alterations in frontal cortex of DM autopsy samples, Otero et al. (2021) reported 130 high-confidence splicing changes, which occur in ion channels, neurotransmitter receptors, and synaptic scaffolds, while mis-splicing of GRIP1 might change kinesin association. In frontal cortex samples, downregulated genes tend to express in neurons, while upregulated genes tended to express preferentially in endothelial and microglial, which suggest neuroinflammatory responses. In DMSXL mice (carrying ∼1,000–1,800 DMPK CTG repeats with multisystemic transgene expression), the mis-splicing patterns of GRIN1 exon 21, Ldb3 exon 11, and Mbnl2 exon 7 in frontal cortex, as well as GRIN1 exon 5, Ldb3 exon 11, APP exon 8, and Frx1 exons 15/16 in brainstem have been detected (Hernández-Hernández et al., 2013a), and GRIN1 and Tau mis-splicing appear to be involved in synaptic dysfunction. In the brain of Mbnl1–/– mice, 14 mis-spliced events have been observed using splicing-sensitive microarray, including Sorbs1 exons 6 and 25, Spag9 exon 31, Dclk1 exon 19, APP exon 7 and 8, GRIN1 exon 4, and so on (Suenaga et al., 2012).

Recently, the heterogeneity of splicing defects in the DM1 brain also attracted increasing attention. In Mbnl knockdown mice, it has been identified that abnormal alternative splicing in the cerebellum are fewer than in other brain regions (Charizanis et al., 2012; Suenaga et al., 2012). The inclusion of Mbnl1 exon 5 and Mbnl2 exons 5 and 8 were higher in most brain areas, except in the cerebellum for Mbnl2 exons 5 and 8. Besides, RNA foci preferentially accumulate in the frontal cortex and certain areas of the brainstem of DM1 transgenic mice (Huguet et al., 2012; Hernández-Hernández et al., 2013a), and seem to be more abundant in cortical astrocytes than in neurons (Hernández-Hernández et al., 2013a). Using autopsied brain tissues of DM1 patients, researchers further observed varying degrees of mis-splicing among the cerebellar cell layers (Furuta et al., 2018). LASER capture microdissection revealed splicing defects in the molecular layer of the cerebellum, but not in the granular layer (Furuta et al., 2018). Similarly, one study reported that mis-splicing in WM is less apparent than in GM of the DM1 brain, which may be attributed to the inability to transfer the abnormal/fetal splicing isoform to the axon (Nishi et al., 2020). Future analysis of the mis-splicing diversity in the DM1 brain may favor a precise therapy targeting specific sites.

Though sharing with a common pathogenetic mechanism, alternative splicing defects, further findings suggested a new perspective influencing the performances of DM patients. According to the results of Salvatori et al. (2009) the molecular and biochemical differences of troponin T and the insulin receptor between DM1 and DM2 due to different translational patterns and distribution patterns might partially explain the apparent differences on their clinical phenotypes. This phenomenon promotes the exploration of DM1 pathogenesis at the translation level.

Recently, an important aspect of the pathogenesis of DM1 regarding to somatic expansion has attracted increasing attention. It has been demonstrated that the length of modal allele in blood DNA samples of DM1 patients increased over time, driven primarily by the inherited progenitor allele length (ePAL), age-at-sampling, and age-at-onset (Morales et al., 2020). Since the DNA mismatch repair proteins MSH2, MSH3, and MSH6, are considered critical players in CTG repeat expansion, and their decreased expressions inhibit the expansion (Dragileva et al., 2009; Tomé et al., 2009), they provide a new insight into the mechanism of CTG repeat instability in DM1. Tomé et al. (2009) reported that MSH2 ATPase domain mutation could influence somatic instability in DM1 transgenic mice. Compared with fibroblasts, MSH2, MSH3, and MSH6, were highly expressed in DM1 patient-derived iPSC, accompanied with longer CTG repeat, while MSH2 silencing inhibited CTG repeat expansion (Du et al., 2013). Flower et al. (2019) reported that the altered MSH3 levels caused by MSH3 3a repeat allele decreased somatic expansion and changed the DM1 phenotype. Thus, regulation of MSH3 might represent a new roadmap for potential target therapy of DM1.

Synaptic protein dysfunction is an important feature demonstrated in the DM1 brain. RAB3A is an abundant synaptic vesicle protein that regulates neurotransmission by interacting with other synaptic proteins. The upregulation of RAB3A causes spontaneous exocytosis, and plays important roles in spatial learning, sleep control, and synaptic plasticity (Sudhof, 2004). Synapsin I (SYN1) can regulate synaptic vesicle release in a phosphorylation-dependent manner, and its hyperphosphorylation determines short-term synaptic plasticity alterations (Rosahl et al., 1993). Hernández-Hernández et al. (2013a) reported RAB3A upregulation and SYN1 hyperphosphorylation in DMSXL mice, transfected cells, and DM1 patient samples, which were related to altered spontaneous neurosecretion in cell culture, electrophysiological and behavioral deficits in mice, and possibly contributed to the neuropsychological manifestations in DM1 patients. Then, Jimenez-Marin et al. (2021) demonstrated that transcriptional signatures of synaptic vesicle genes at least partially explain the mechanisms of DM1 neurodegeneration. Nowadays, a close relationship between splicing regulator alterations and synaptic protein dysfunctions has been found, possibly contributing to DM1 neurological phenotypes (Hernández-Hernández et al., 2013b). For example, loss-of-function of MBNL1 in DMSXL mice brain mediated the upregulation of RAB3A levels and determined the length of neuronal dendrites and axons (Hernández-Hernández et al., 2013b). The overexpression of CELF1 or CELF2 in neuronal-like PC12 cells containing expanded CUG transcripts mediated SYN1 hyperphosphorylation (Hernández-Hernández et al., 2013b). And other splicing alterations, such as GRIN1 and Tau splicing defects, might also contribute to synaptic dysfunction in DM1 (Hernández-Hernández et al., 2013b). However, although influenced by different splicing regulators, these synaptic protein alterations seem to be independent of mis-splicing of their coding transcripts, suggesting that DM1 neuropathogenesis have far-reaching implications beyond the disruption of splicing programs.

In addition, other synaptic-related abnormalities have also been identified in the DM1 brain. Lee et al. (2019) found distribution defects of cortical neurons, abnormal dendritic morphology and complexity and postsynaptic densities in the Mbnl1/2–/– mice. A time-course study using EpA960/CaMKII-Cre mice revealed that hippocampus (HPC)-related learning and synaptic potentiation were damaged before structural alterations occurred in the brain, followed by brain atrophy associated with progressively reduced axon and dendrite integrity. Notably, cytoplasmic MBNL1 level on dendrites decreased before dendrite degeneration, whereas MBNL2 expression reduction and MBNL-mediated alternative splicing defects were evident after degeneration (Wang et al., 2017), suggesting that MBNL1 reduction might contribute to synaptic transmission dysfunction in the DM1 brain.

A recent study shows that compared to neurons, cortical astrocytes contain more ribonuclear foci in DM1 transgenic mice (carrying 45 kb of human genomic DNA cloned from a DM1 patient) (Hernández-Hernández et al., 2013a). Meanwhile, RNA sequencing discovered more frequent splicing deficits in glia of DMSXL mice (Oude Ophuis et al., 2009; González-Barriga et al., 2021), suggesting a non-negligible presence of neuroglial damage in DM1. Glutamate transporter 1 (GLT1) is a glial-specific glutamate transporter that can recapture excitatory glutamate from the synaptic cleft and protect it from neurotoxicity caused by glutamate overstimulation (Bellamy, 2006). In the Bergmann glia of the cerebellum in DMSXL mice, scientists found glutamate excitotoxicity associated with decreased GLT1 (Sicot et al., 2017). In astrocytes of DMSXL mice, downregulation of GLT1 increased glutamate neurotoxicity and caused neuronal damage, while the upregulation of GLT1 corrected Purkinje cell firing and motor incoordination (Sicot et al., 2017). These studies indicated that the loss-of-function of GLT1 and defective neuroglial interactions might play critical roles in inducing DM1 brain disorders.

Nowadays, studies have identified that the expression of GLT1 is regulated by RNA transcription, splicing and stability, post-translational modifications, and protein activity (Kim et al., 2011). Specifically, loss-of-function of MBNL1 can perturb GLT1 polyadenylation, thus decreasing the levels of GLT1 glutamate transporter, while MBNL2 inactivation did not affect GLT1 levels, but contributed to the compensating increase in MBNL1 protein (Batra et al., 2014; Mohan et al., 2014). In the future, restoring GLT1 protein and glutamate neurotransmission by regulating MBNL proteins might be promising approaches to reverse the defective neuroglial interactions in DM1. Besides, in an inducible glial cell model of DM1 derived from human retinal Müller glial cells (MIO-M1) expressing 648 CUG repeats [MIO-M1 CTG(648)], scientists identified that the activation of inflammatory pathways and immune responses could partially explain DM1 CNS defects associated with defective glia (Azotla-Vilchis et al., 2021; González-Barriga et al., 2021). In glial cells of DMSXL mice, expanded CUG RNA affected preferentially differentiation-associated molecular events, which open new avenues in studying DM1 brain pathology with cell type resolution (González-Barriga et al., 2021).

Previous studies have observed the insulin resistance (IR) phenotype in DM1 patients (Moxley et al., 1978), which could be attributed to the mis-splicing of the insulin receptor gene. While recently, altered insulin signaling in the brain has also been proposed, thus provides potential alternative explanations for the DM1 neuropathogenesis (Nieuwenhuis et al., 2019). For example, animals with impaired insulin receptor signaling have shown reduced motivation, which could translate to apathy in humans (Dagenhardt et al., 2017), a critical symptom in adult DM1 patients (Gallais et al., 2015). In patients with obsessive-compulsive disorder, altered brain insulin signaling has been observed (van de Vondervoort et al., 2016). Besides, cognitive deficits, especially visuospatial and verbal memory deficits (Kullmann et al., 2016), depressive symptoms (Minier et al., 2018; van der Velden et al., 2019) and decreased behavioral flexibility (van de Vondervoort et al., 2019), have also been shown to be associated with brain IR. Moreover, a recent review pointed out the effects of insulin signaling on tauopathy and Aβ metabolism (Gonçalves et al., 2019). And several neuroimaging studies have discovered a decrease in glucose uptake in the brain of DM1 patients (Fiorelli et al., 1992; Peric et al., 2017a), however, it remains unclear whether altered insulin signaling is involved.

A series of neurochemical changes were also found in DM1, which may account for specific symptoms. For example, the loss of serotonin (5-HT)-containing neurons in the dorsal raphe nucleus (DRN) and the superior central nucleus (SCN) of DM1 patients is associated with hypersomnia (Ono et al., 1998). And the alteration of serotonergic raphe structures might be involved in the pathogenesis of hypersomnia (Peric et al., 2014b; Krogias et al., 2015; Krogias and Walter, 2016). The hypoechogenicity of nucleus raphe might be correlated with EDS and depression in DM patients (Peric et al., 2014b). The extent of WM hyperintensities might be correlated with fatigue (Minnerop et al., 2011). Using conditional Mbnl2NEX-cKO mice (a tissue-specific knockout mouse model lacking the Mbnl2 gene in forebrain glutamatergic neurons), long-term cognitive impairment and depression were found (Ramon-Duaso et al., 2020). This might be associated with significant neuronal loss, reduced neurogenesis, and fewer proliferating and immature neurons in the dentate gyrus of the HPC. Additionally, in Mbnl2–/– mice, increased proinflammatory microglia, dopamine levels as well as Dat, Drd1, and Drd2 transcripts levels, decreased expression of the brain derived-neurotrophic factor (BDNF) gene, and impaired neural spiking and oscillatory activities in the medial prefrontal cortex (mPFC) and the HPC have been found, accompanied with progressive cognitive and affective changes (Ramon-Duaso et al., 2019). Similar abnormalities have also been observed in the mPFC and HPC of DM1 patients with severe depression and cognitive impairment (Romeo et al., 2010b). Currently, chronic treatment with methylphenidate (MPH) has been shown to reverse the behavioral abnormalities, reduce proinflammatory microglia and Dat level, and increase BDNF and Nrf2 mRNA expressions in Mbnl2–/– mice. This makes it a promising drug candidate to treat CNS dysfunctions in DM1 patients (Ramon-Duaso et al., 2019). However, this intervention also impaired glutamate uptake and increased glutamate levels in juvenile rats (Schmitz et al., 2016, 2017), querying whether MPH therapy would increase glutamate neurotoxicity and induce the defective neuroglial interactions.

In addition, dysregulation of cerebrospinal fluid (CSF) homeostasis was observed in early onset DM1. A study introducing DMPK CTG expansions into the mouse found that mis-splicing significantly affected brain choroid plexus epithelial cells (Nutter et al., 2019). Besides, increased levels of total-Tau, IgG, γ-globulin, and myelin basic protein (MBP), as well as decreased levels of Aß1-42 and orexin-A were found in the CSF of DM1 patients (Hirase and Araki, 1984; Martínez-Rodríguez et al., 2003; Winblad et al., 2008; Peric et al., 2014a). Orexins are hypothalamic peptides that play critical roles in sleep/wake regulation (Sakurai, 2014). A possible correlation between an altered CSF orexin-A levels and EDS in systemic lupus erythematosus (SLE) patients with hypothalamic lesions and patients with frontotemporal dementia (FTD) have been reported (Çoban et al., 2013; Suzuki et al., 2018). Notably, significantly lower orexin-A levels were also detected in the CSF of 6 DM1 patients affected by EDS (Martínez-Rodríguez et al., 2003), thus providing potential explanations for DM1 sleep disorders. Furthermore, in 2015, a decreased level of BDNF, a neurotrophin participate in learning and memory, was detected in the serum of DM1 patients. Since it can cross the brain-blood barrier (BBB), it might be considered a promising biomarker of CNS defects (Comim et al., 2015).

To determine the expression patterns of DMPK with age, Langbehn et al. (2021) analyzed the brain from 99 donors with DM1 ranging from 5 postconceptional weeks to 80 years old. They found that peak expression of wildtype DMPK coincides with a time of dynamic brain development, thus indicating that the abnormalities in DM1 brain DMPK expression may affect early brain development. Besides, direct injection of (CUG)₉₁ repeat-containing mRNA into single-cell embryos of zebrafish induced CNS toxicity during early development, resulting in morphological abnormalities, behavioral abnormalities, and extensive transcriptional alterations, while co-injection of zebrafish Mbnl2 RNA suppressed this toxicity and reversed the associated behavioral and transcriptional abnormalities (Todd et al., 2014). In addition, defects in the genes involved in dysfunctional neurite outgrowth and synaptogenesis at the neuromuscular junction were also observed in neuronal progeny derived from DM1 mutant human ES cells, which are associated with the decreased expression of two genes that belong to the SLITRK family, SLITRK2 and SLITRK4 (Marteyn et al., 2011). Transfection of SLITRK2 and SLITRK4 into cultured DM1 cells restored neurite length to control levels. However, it is interesting that DMPK mutation and dysregulation of splicing by MBNL1 do not appear to be involved in SLITRK misexpression or neurite outgrowth, suggesting other new molecular mechanisms involved in DM1 abnormal neurodevelopment (Marteyn et al., 2011).

In the DM1 brain, dysregulation of alternative splicing could lead to pathologic Tau proteins accumulations and the formation of neurofibrillary tangles (NFTs) (Caillet-Boudin et al., 2014), which are mainly located in the HPC, entorhinal cortex, and most of the temporal areas, called Tau pathology. Nowadays, Tau pathology has been confirmed a critical histopathological characteristic in the brain of DM1 patients (Caillet-Boudin et al., 2014), and could interfere with axonal transport and neurosecretion (Caillet-Boudin et al., 2014). Although there is no direct evidence, current research suggests that this pathology may be related to cognitive dysfunctions in DM1.

In the adult brain, Tau gene could encode six Tau isoforms through alternative splicing of exons 2, 3, and 10, whereas in DM1, all of these exons are absent, thus promoting fetal expression of the 3-repeat Tau isoform (Sergeant et al., 2001; Jiang et al., 2004). Interestingly, a recent study in a congenital DM1 patient with intellectual disability also suggested the existence of a 4-repeat tau dominant pathology (Mizuno et al., 2018). Originally, cell studies identified that long CUG repeats-mediated loss-of-function of MBNL1 could be responsible for the changes in Tau splicing (Dhaenens et al., 2008). While in 2014, researchers discovered that both MBNL1 and MBNL2 have an enhancer activity of Tau exon 2 inclusion, and only the interaction of MBNL1 and MBNL2 can fully reverse the splicing defect of Tau exon 2 induced by the mutant CUG repeats, similar to that observed in DM1 (Carpentier et al., 2014). Then in 2015, a further study examining the Tau splicing using Nestin-Cre DKO mice (a Mbnl1/2–/– mouse model) suggested that both MBNL1 and MBNL2 synergize to regulate Tau exon 2, 3, and 10 splicing (Goodwin et al., 2015). These findings proved that the regulation of MBNL1/2 and their interactions are highly essential in DM1 Tau pathology. Except MBNL proteins, CELF proteins also serve as potential regulators of Tau splicing. Four exons (2, 3, 6, and 10) of Tau isoforms have been discovered to respond to one or more CELF proteins (Leroy et al., 2006a,b). Among them, Tau exon 10 responds specifically to CELF2 upregulation (Dhaenens et al., 2011). Tau exon 6 splicing is regulated by CELF5 and CELF6 (Leroy et al., 2006b). Notably, the heterogeneous distribution of Tau protein in the DM1 brain has also been reported, which may affect its splicing regulation patterns.

Other than Tau pathology, several kinds of protein and nucleotide deposits have also been observed in the brain of DM1 patients (Weijs et al., 2021), including Lewy bodies (LBs), neuronal intranuclear eosinophilic inclusion bodies, intracytoplasmic inclusion bodies, increased Marinesco bodies, gliosis (Itoh et al., 2010; Jinnai et al., 2013), skein-like ubiquitin-positive inclusions and granulovacuolar degeneration (GVD), which suggest neurodegeneration in the DM1 brain (Itoh et al., 2010; Yamazaki et al., 2011; Nakamori et al., 2012).

In the DM1 brain, the mutant DMPK RNA accumulates as nuclear foci in extensive areas, which contributes to abnormal alternative splicing (Miller et al., 2000; Fardaei et al., 2002). The nuclear foci are widely distributed throughout the brain of DM1 patients, including cortex, WM in subcortical and callosal areas, HPC, thalamus, brainstem, and cerebellum, and presented in various cell types, such as neurons, astrocytes, oligodendrocytes, Purkinje cells and human DM1 iPSC or ES-cell-derived NSCs (Jiang et al., 2004; Denis et al., 2013; Hernández-Hernández et al., 2013a). Their distributions varied from different genetic features, histological features and clinical features in each person (Jiang et al., 2004). Abnormal alternative splicing has been considered the critical pathogenesis of DM1. Changes in RNA-binding proteins, such as MBNL and CELF proteins, can lead to splicing defects of a variety of pre-mRNAs and misexpressions of different protein isoforms. Nowadays, the interaction between RNAopathy, spliceopathy, and Tau pathology have accounted for essential parts of DM1 neuropathology (Caillet-Boudin et al., 2014).

Other neuropathological features of DM1 include neuronal loss in different areas, such as the superficial layer of the frontal and parietal cortices, the occipital cortex, the medullary arcuate nuclei, the anterior and dorsomedial thalamic nuclei, the midbrain, and pontine reticular formation, which may be related to cortical atrophy (Culebras et al., 1973; Ono et al., 1995, 1998; Mizukami et al., 1999). The cell loss of specific areas might also contribute to the cognitive and behavioral abnormalities in DM1 patients (Rosman and Kakulas, 1966; Ono et al., 1996; Mizukami et al., 1999). In the post mortem brain and spinal cord of DM1 patients with congenital or childhood onset with intellectual deficiency, heterotopic neurons have been found, suggesting abnormal neurodevelopment (Ogata et al., 1998). Degenerative WM changes were also reported in DM1 patients, including myelin and axonal loss, expansion of perivascular spaces, gliosis, and hyalinization of capillaries in deep and subcortical WM (Itoh et al., 2010). However, most studies exploring the microscopic brain pathology in DM1 patients, as well as their relationships with neuroimaging features and splicing changes are case reports or small-scale researches. Clearly, larger follow-up studies are eagerly needed to improve the understandings of pathological alterations in DM1.

To date, there are no specific therapeutic agents available to reverse neurological defects in DM1. Modalities for management mainly rely on supportive care, including sleep hygiene improvement, cognitive−behavioral therapy, aerobic exercise training, and careful use of stimulant drugs. Sleep−related disorders have been recognized as primary symptoms of CNS involvement in DM1. Early recognition and treatment of sleep disorder breathing with nocturnal non-invasive mechanical ventilation have served as important countermeasures to deal with these problems (Pincherle et al., 2012). In a large clinical cohort study, scientists found that patients who insist on home mechanical ventilation for ≥5 h/24 h shown significantly higher survival rates than those who use it less (Seijger et al., 2021), and their tolerance and adherence were remarkably high. Besides, the biggest multicenter, randomized clinical trial in DM1 named the Observational Prolonged Trial in Myotonic Dystrophy Type 1 to Improve Quality of Life-Standards, a Target Identification Collaboration (OPTIMISTIC) revealed that cognitive behavioral therapy significantly improved the ability for activity and social participation at 10 months in severely fatigued patients with DM1 (NCT02118779) (Okkersen et al., 2018). Compared with usual care, cognitive behavioral therapy plus aerobic exercise training also increased the physical activity in DM1 patients (OPTIMISTIC) (van Engelen, 2015), indicating this therapy as a promising interventions for severe fatigue in DM1. Stimulant drugs also shown the potential to treat EDS. In 2007, the American Academy of Sleep Medicine (AASM) declared that MPH might be an effective tool for treating DM1-related EDS (Morgenthaler et al., 2007). However, a Cochrane review on well-designed psychostimulant trials in patients with DM1 and EDS pointed out the lack of evidence to support its routine use (Annane et al., 2002). Some clinical studies reported that modafinil might improve hypersomnia and fatigue without significantly increasing activity levels in DM1 (Hilton-Jones et al., 2012; Laberge et al., 2013). However, respiratory insufficiency (due to abnormal central drive and respiratory muscle weakness) and sleep fragmentation related to central or obstructive apnea must be excluded (Harper et al., 2002). Except for treating sleep-related disorders, in Mbnl2–/– mice, mirtazapine, a kind of antidepressant, has been discovered to reverse cognitive impairments and depression, as well as reduce microglia and neuronal loss (Ramon-Duaso et al., 2020). Moreover, metformin treatment reversed the metabolic and mitochondrial dysfunction and the accelerated aging process, such as impaired proliferation, in fibroblasts derived from DM1 patients (García-Puga et al., 2020). And its beneficial effects on muscle function have been confirmed in several clinical trials (Bassez et al., 2018). Since basic science reports have proposed the important role of abnormal insulin signaling in the brain (Nieuwenhuis et al., 2019), it indicates another possible therapeutic mechanism for metformin in DM1 brain. Furthermore, therapies via modulating glutamate levels and dopaminergic function have also emerged to attract more and more attention (Sicot et al., 2017; Serra et al., 2020b), which provide new insights for future DM1 CNS treatment.

Great progress of molecular therapies has been made in DM1, however, before we can move these treatments into clinical trials, there is also a great need to identify feasible outcome measures to evaluate the effectiveness of these therapies by characterizing the component of CNS deficits in DM1. Currently, the main outcome measures actually used to study CNS involvements in DM1 patients are represented by a variety of patient questionnaires and clinical neuropsychological tests which can assess cognitive and behavioral dysfunctions, and computerized neuroimaging techniques which can assess neuroimaging alterations (summarized in Tables 2–4). Besides, given the high heterogeneity of symptoms in DM1 patients, several patient-reported outcome measures are also developed, such as DM1 activity and participation scale for clinical use (DM1-ActivC), and the fatigue and daytime sleepiness scale (FDSS) (Hermans et al., 2013, 2015), which have shown valid measurements in DM1 populations (Angelini and Siciliano, 2020). Notably, due to the increasing risk and higher severity of COVID-19 in DM1 patients, and the difficulty in contacting a doctor during the COVID-19 epidemic, the Italian Association for Glycogenosis (AIG) developed telemedicine equipment, the AIGkit application (AIGkit app), which allows patients to receive constant remote monitoring by using dedicated questionnaires and getting personalized treatment (Symonds et al., 2017). A review by Simoncini et al. (2020) comprehensively summarized the clinical instruments available for cognitive and behavioral measures and neuroimaging assessment in DM1 brain. In the future, additional investigations are warranted to improve the reliability of these available measures, as well as to discover the new outcome markers.

With significant advances in understanding the molecular pathogenesis of DM1, several approaches targeting disease mechanisms have been developed, such as antisense oligonucleotide (ASO)-based therapy, small-molecule therapy, genome editing, non-coding RNAs (ncRNAs)-based therapy, and iPSC technique, which target different steps in the pathological process of DM1 (Mulders et al., 2010; Magaña and Cisneros, 2011). Focusing on the most upstream target should block the initiation of the toxic cascade and correct more defects in tissues. Since most therapeutic efforts of DM1 mainly focused on the myocardium and skeletal muscle, and only few studies described their effects on the neurological defects, we briefly introduce their roles in the treatment of DM1 and their therapeutic potential in CNS deficits, hoping to provide references for DM1 CNS treatment. Figure 2 specifically introduced the current management measures as well as promising therapeutic strategies expected to be applied to DM1 CNS disorders.

The current advances in therapeutic strategies should also be applicable in principle to CNS since the pathogenesis of CNS deficits is similar to that of other organs, such as RNA toxicity and splicing defects. However, the existence of BBB hinders the delivery and distribution of drugs in the brain. Therefore, the ideal therapeutic agents need to be able to cross the BBB readily. Some improvements have been made, such as intracellular delivery of the therapeutic molecules to promote uptake, administering molecules intracerebroventricularly or intrathecally (Baughan et al., 2009; Geary et al., 2015), or regulating the molecule size and charge to achieve an efficient delivery to the brain. Recent advances also found that intranasal delivery efficiently bypasses the BBB and highly increases the CNS concentrations of drugs and is non-invasive. Besides, the combination of U7 methodology with highly efficient AAV-mediated delivery, receptor-mediated endocytosis of ASOs, and nanoparticles-, exosomes- or CPP-based delivery of large cargos also favor the BBB passage and the higher distributions of drugs in the CNS (Foust and Kaspar, 2009; Krupa et al., 2014; McGowan et al., 2015, 2016; Bai et al., 2016; Kristensen et al., 2016). In conclusion, all of these therapeutic agents, administration routes, and assisted delivery systems create numerous chances for the discovery of effective therapies for CNS disorders.

Several molecules applied for CNS treatment have shown positive effects in preclinical trials, which may provide new thoughts for DM1 CNS treatment. For example, in mice overexpressing APP, intracerebroventricular injections of PS-modified ASOs significantly reduced the expression of APP protein and improved learning and memory deficits (Kumar et al., 2000). In the Alzheimer’s disease (AD) mouse model, a designed 2′-O-Me-PS-modified ASO sustainly increased exon 19 splicing of apolipoprotein E receptor 2 (ApoER2) as well as restored synaptic function and learning and memory (Hinrich et al., 2016). Besides, an 2′MOE-modified ASO called IONIS MAPTRx (ISIS 814907) has been evaluated in a phase I/II study in patients with mild AD (NCT03186989), as it highly reduced the expression of tau protein through targeting MAPT mRNA. Hu et al. (2021) using a 20-mer RNase H-active gapmer ASO combined with a 3-month exercise training program in old HSA^LR mice reversed all measures of fatigue, though they did not detect the index of fatigue due to CNS dysfunctions. These findings may provide new thoughts for DM1 CNS treatment. Murlidharan et al. (2016) discovered a lab-derived AAV chimeric (AAV2g9), which has favorable CNS properties derived from both parental counterparts, AAV2 and AAV9. Administration of CRISPR/Cas9 with this synthetic AAV vector into the CSF minimized systemic leakage and reduced the sequestration and gene transfer in off-target organs.

The modification of stem cells also offers a new chance for CNS treatment. Previous studies have shown that NSC derived from ES cells or iPSCs could present critical features of DM1 (Marteyn et al., 2011; Denis et al., 2013; Xia and Ashizawa, 2015; Xia et al., 2015). In DM1 NSCs, insertion of poly A signals upstream of DMPK CTG repeats by TALEN-mediated homologous recombination significantly eliminated mutant transcripts and nuclear RNA foci, corrected mis-splicing, and ultimately reversed phenotypes (Xia et al., 2015; Gao et al., 2016). Despite the broad prospects of strategies in CNS treatment, there are still many challenges, such as lower efficiency and distribution to CNS and safety regarding immune response and gene therapy specificity. In addition, no studies have discussed the targeted brain cell types of different strategies and the corresponding alterations of brain cells after treatment. The resolution of these issues may provide a deeper understanding of the therapeutic mechanisms of drugs.