Deep learning modeling of rare noncoding genetic variants in human motor neurons defines CCDC146 as a therapeutic target for ALS.

Amyotrophic lateral sclerosis (ALS) is a fatal and incurable neurodegenerative disease caused by the selective and progressive death of motor neurons (MNs). Understanding the genetic and molecular factors influencing ALS survival is crucial for disease management and therapeutics. In this study, we introduce a deep learning-powered genetic analysis framework to link rare noncoding genetic variants to ALS survival. Using data from human induced pluripotent stem cell (iPSC)-derived MNs, this method prioritizes functional noncoding variants using deep learning, links cis-regulatory elements (CREs) to target genes using epigenomics data, and integrates these data through gene-level burden tests to identify survival-modifying variants, CREs, and genes. We apply this approach to analyze 6,715 ALS genomes, and pinpoint four novel rare noncoding variants associated with survival, including chr7:76,009,472:C>T linked to CCDC146. CRISPR-Cas9 editing of this variant increases CCDC146 expression in iPSC-derived MNs and exacerbates ALS-specific phenotypes, including TDP-43 mislocalization. Suppressing CCDC146 with an antisense oligonucleotide (ASO), showing no toxicity, completely rescues ALS-associated survival defects in neurons derived from sporadic ALS patients and from carriers of the ALS-associated G4C2-repeat expansion within C9ORF72. ASO targeting of CCDC146 may be a broadly effective therapeutic approach for ALS. Our framework provides a generic and powerful approach for studying noncoding genetics of complex human diseases.

BLM helicase protein negatively regulates stress granule formation through unwinding RNA G-quadruplex structures.

Bloom's syndrome (BLM) protein is a known nuclear helicase that is able to unwind DNA secondary structures such as G-quadruplexes (G4s). However, its role in the regulation of cytoplasmic processes that involve RNA G-quadruplexes (rG4s) has not been previously studied. Here, we demonstrate that BLM is recruited to stress granules (SGs), which are cytoplasmic biomolecular condensates composed of RNAs and RNA-binding proteins. BLM is enriched in SGs upon different stress conditions and in an rG4-dependent manner. Also, we show that BLM unwinds rG4s and acts as a negative regulator of SG formation. Altogether, our data expand the cellular activity of BLM and shed light on the function that helicases play in the dynamics of biomolecular condensates.

microRNA-based predictor for diagnosis of frontotemporal dementia.

AIMS: This study aimed to explore the non-linear relationships between cell-free microRNAs (miRNAs) and their contribution to prediction of Frontotemporal dementia (FTD), an early onset dementia that is clinically heterogeneous, and too often suffers from delayed diagnosis. METHODS: We initially studied a training cohort of 219 subjects (135 FTD and 84 non-neurodegenerative controls) and then validated the results in a cohort of 74 subjects (33 FTD and 41 controls). RESULTS: On the basis of cell-free plasma miRNA profiling by next generation sequencing and machine learning approaches, we develop a non-linear prediction model that accurately distinguishes FTD from non-neurodegenerative controls in ~90% of cases. CONCLUSIONS: The fascinating potential of diagnostic miRNA biomarkers might enable early-stage detection and a cost-effective screening approach for clinical trials that can facilitate drug development.

MiR-142-3p is a Critical Modulator of TNF-mediated Neuronal Toxicity in Multiple Sclerosis.

BACKGROUND: TNF-dependent synaptotoxicity contributes to the neuronal damage occurring in patients with Multiple Sclerosis (pwMS) and its mouse model Experimental Autoimmune Encephalomyelitis (EAE). Here, we investigated miR-142-3p, a synaptotoxic microRNA induced by inflammation in EAE and MS, as a potential downstream effector of TNF signalling. METHODS: Electrophysiological recordings, supported by molecular, biochemical and histochemical analyses, were performed to explore TNF-synaptotoxicity in the striatum of EAE and healthy mice. MiR-142 heterozygous (miR-142 HE) mice and/or LNA-anti miR-142-3p strategy were used to verify the TNF-miR-142-3p axis hypothesis. The cerebrospinal fluid (CSF) of 151 pwMS was analysed to evaluate possible correlation between TNF and miR-142-3p levels and their impact on clinical parameters (e.g. progression index (PI), age-related clinical severity (gARMSS)) and MRI measurements at diagnosis (T0). RESULTS: High levels of TNF and miR-142-3p were detected in both EAE striatum and MS-CSF. The TNF-dependent glutamatergic alterations were prevented in the inflamed striatum of EAE miR-142 HE mice. Accordingly, TNF was ineffective in healthy striatal slices incubated with LNA-anti miR- 142-3p. However, both preclinical and clinical data did not validate the TNF-miR-142-3p axis hypothesis, suggesting a permissive neuronal role of miR-142-3p on TNF-signalling. Clinical data showed a negative impact of each molecule on disease course and/or brain lesions and unveiled that their high levels exert a detrimental synergistic effect on disease activity, PI and white matter lesion volume. CONCLUSION: We propose miR-142-3p as a critical modulator of TNF-mediated neuronal toxicity and suggest a detrimental synergistic action of these molecules on MS pathology.

rG4detector, a novel RNA G-quadruplex predictor, uncovers their impact on stress granule formation.

RNA G-quadruplexes (rG4s) are RNA secondary structures, which are formed by guanine-rich sequences and have important cellular functions. Existing computational tools for rG4 prediction rely on specific sequence features and/or were trained on small datasets, without considering rG4 stability information, and are therefore sub-optimal. Here, we developed rG4detector, a convolutional neural network to identify potential rG4s in transcriptomics data. rG4detector outperforms existing methods in both predicting rG4 stability and in detecting rG4-forming sequences. To demonstrate the biological-relevance of rG4detector, we employed it to study RNAs that are bound by the RNA-binding protein G3BP1. G3BP1 is central to the induction of stress granules (SGs), which are cytoplasmic biomolecular condensates that form in response to a variety of cellular stresses. Unexpectedly, rG4detector revealed a dynamic enrichment of rG4s bound by G3BP1 in response to cellular stress. In addition, we experimentally characterized G3BP1 cross-talk with rG4s, demonstrating that G3BP1 is a bona fide rG4-binding protein and that endogenous rG4s are enriched within SGs. Furthermore, we found that reduced rG4 availability impairs SG formation. Hence, we conclude that rG4s play a direct role in SG biology via their interactions with RNA-binding proteins and that rG4detector is a novel useful tool for rG4 transcriptomics data analyses.

Crosstalk between Biomolecular Condensates and Proteostasis.

Proper homeostasis of the proteome, referred to as proteostasis, is maintained by chaperone-dependent refolding of misfolded proteins and by protein degradation via the ubiquitin-proteasome system and the autophagic machinery. This review will discuss a crosstalk between biomolecular condensates and proteostasis, whereby the crowding of proteostasis factors into macromolecular assemblies is often established by phase separation of membraneless biomolecular condensates. Specifically, ubiquitin and other posttranslational modifications come into play as agents of phase separation, essential for the formation of condensates and for ubiquitin-proteasome system activity. Furthermore, an intriguing connection associates malfunction of the same pathways to the accumulation of misfolded and ubiquitinated proteins in aberrant condensates, the formation of protein aggregates, and finally, to the pathogenesis of neurodegenerative diseases. The crosstalk between biomolecular condensates and proteostasis is an emerging theme in cellular and disease biology and further studies will focus on delineating specific molecular pathways involved in the pathogenesis of amyotrophic lateral sclerosis (ALS) and other neurodegenerative diseases.

Muscle microRNAs in the cerebrospinal fluid predict clinical response to nusinersen therapy in type II and type III spinal muscular atrophy patients.

BACKGROUND AND PURPOSE: The antisense oligonucleotide nusinersen (Spinraza) regulates splicing of the survival motor neuron 2 (SMN2) messenger RNA to increase SMN protein expression. Nusinersen has improved ventilator-free survival and motor function outcomes in infantile onset forms of spinal muscular atrophy (SMA), treated early in the course of the disease. However, the response in later onset forms of SMA is highly variable and dependent on symptom severity and disease duration at treatment initiation. Therefore, we aimed to identify novel noninvasive biomarkers that could predict the response to nusinersen in type II and III SMA patients. METHODS: Thirty-four SMA patients were included. We applied next generation sequencing to identify microRNAs in the cerebrospinal fluid (CSF) as candidate biomarkers predicting response to nusinersen. Hammersmith Functional Motor Scale Expanded (HFMSE) was conducted at baseline and 6 months after initiation of nusinersen therapy to assess motor function. Patients changing by ≥3 or ≤0 points in the HFMSE total score were considered to be responders or nonresponders, respectively. RESULTS: Lower baseline levels of two muscle microRNAs (miR-206 and miR-133a-3p), alone or in combination, predicted the clinical response to nusinersen after 6 months of therapy. Moreover, miR-206 levels were inversely correlated with the HFMSE score. CONCLUSIONS: Lower miR-206 and miR-133a-3p in the CSF predict more robust clinical response to nusinersen treatment in later onset SMA patients. These novel findings have high clinical relevance for identifying early treatment response to nusinersen in later onset SMA patients and call for testing the ability of miRNAs to predict more sustained long-term benefit.

Whole-genome sequencing reveals that variants in the Interleukin 18 Receptor Accessory Protein 3'UTR protect against ALS.

The noncoding genome is substantially larger than the protein-coding genome but has been largely unexplored by genetic association studies. Here, we performed region-based rare variant association analysis of >25,000 variants in untranslated regions of 6,139 amyotrophic lateral sclerosis (ALS) whole genomes and the whole genomes of 70,403 non-ALS controls. We identified interleukin-18 receptor accessory protein (IL18RAP) 3' untranslated region (3'UTR) variants as significantly enriched in non-ALS genomes and associated with a fivefold reduced risk of developing ALS, and this was replicated in an independent cohort. These variants in the IL18RAP 3'UTR reduce mRNA stability and the binding of double-stranded RNA (dsRNA)-binding proteins. Finally, the variants of the IL18RAP 3'UTR confer a survival advantage for motor neurons because they dampen neurotoxicity of human induced pluripotent stem cell (iPSC)-derived microglia bearing an ALS-associated expansion in C9orf72, and this depends on NF-κB signaling. This study reveals genetic variants that protect against ALS by reducing neuroinflammation and emphasizes the importance of noncoding genetic association studies.

Physically interacting beta-delta pairs in the regenerating pancreas revealed by single-cell sequencing.

OBJECTIVES: Until recently, communication between neighboring cells in islets of Langerhans was overlooked by genomic technologies, which require rigorous tissue dissociation into single cells. METHODS: We utilize sorting of physically interacting cells (PICs) with single-cell RNA-sequencing to systematically map cellular interactions in the endocrine pancreas after pancreatectomy. RESULTS: The pancreas cellular landscape features pancreatectomy associated heterogeneity of beta-cells, including an interaction-specific program between paired beta and delta-cells. CONCLUSIONS: Our analysis suggests that the particular cluster of beta-cells that pairs with delta-cells benefits from stress protection, implying that the interaction between beta- and delta-cells might safeguard against pancreatectomy associated challenges. The work encourages testing the potential relevance of physically-interacting beta-delta-cells also in diabetes mellitus.

Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases.

MiR-142-3p regulates synaptopathy-driven disease progression in multiple sclerosis.

AIM: We recently proposed miR-142-3p as a molecular player in inflammatory synaptopathy, a new pathogenic hallmark of multiple sclerosis (MS) and of its mouse model experimental autoimmune encephalomyelitis (EAE), that leads to neuronal loss independently of demyelination. MiR-142-3p seems to be unique among potential biomarker candidates in MS, since it is an inflammatory miRNA playing a dual role in the immune and central nervous systems. Here, we aimed to verify the impact of miR-142-3p circulating in the cerebrospinal fluid (CSF) of MS patients on clinical parameters, neuronal excitability and its potential interaction with disease modifying therapies (DMTs). METHODS AND RESULTS: In a cohort of 151 MS patients, we found positive correlations between CSF miR-142-3p levels and clinical progression, IL-1ß signalling as well as synaptic excitability measured by transcranial magnetic stimulation. Furthermore, therapy response of patients with 'low miR-142-3p' to dimethyl fumarate (DMF), an established disease-modifying treatment (DMT), was superior to that of patients with 'high miR-142-3p' levels. Accordingly, the EAE clinical course of heterozygous miR-142 mice was ameliorated by peripheral DMF treatment with a greater impact relative to their wild type littermates. In addition, a central protective effect of this drug was observed following intracerebroventricular and ex vivo acute treatments of EAE wild type mice, showing a rescue of miR-142-3p-dependent glutamatergic alterations. By means of electrophysiology, molecular and biochemical analysis, we suggest miR-142-3p as a molecular target of DMF. CONCLUSION: MiR-142-3p is a novel and potential negative prognostic CSF marker of MS and a promising tool for identifying personalised therapies.

microRNAs trip down memory lane.

A new study by Islam et al, in this issue of EMBO Molecular Medicine, reports three microRNAs in the blood that are linked to inter-individual differences in cognition, prior to any sign of cognitive decline. The novel miRNA biomarkers may assist in predicting the risk of cognitive decline and later of developing dementia and can contribute to decision strategies about early therapeutic interventions.

Circulating miR-181 is a prognostic biomarker for amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a relentless neurodegenerative disease of the human motor neuron system, where variability in progression rate limits clinical trial efficacy. Therefore, better prognostication will facilitate therapeutic progress. In this study, we investigated the potential of plasma cell-free microRNAs (miRNAs) as ALS prognostication biomarkers in 252 patients with detailed clinical phenotyping. First, we identified, in a longitudinal cohort, miRNAs whose plasma levels remain stable over the course of disease. Next, we showed that high levels of miR-181, a miRNA enriched in neurons, predicts a greater than two-fold risk of death in independent discovery and replication cohorts (126 and 122 patients, respectively). miR-181 performance is similar to neurofilament light chain (NfL), and when combined together, miR-181 + NfL establish a novel RNA-protein biomarker pair with superior prognostication capacity. Therefore, plasma miR-181 alone and a novel miRNA-protein biomarker approach, based on miR-181 + NfL, boost precision of patient stratification. miR-181-based ALS biomarkers encourage additional validation and might enhance the power of clinical trials.

SUMO: Glue or Solvent for Phase-Separated Ribonucleoprotein Complexes and Molecular Condensates?

Spatial organization of cellular processes in membranous or membrane-less organelles (MLOs, alias molecular condensates) is a key concept for compartmentalizing biochemical pathways. Prime examples of MLOs are the nucleolus, PML nuclear bodies, nuclear splicing speckles or cytosolic stress granules. They all represent distinct sub-cellular structures typically enriched in intrinsically disordered proteins and/or RNA and are formed in a process driven by liquid-liquid phase separation. Several MLOs are critically involved in proteostasis and their formation, disassembly and composition are highly sensitive to proteotoxic insults. Changes in the dynamics of MLOs are a major driver of cell dysfunction and disease. There is growing evidence that post-translational modifications are critically involved in controlling the dynamics and composition of MLOs and recent evidence supports an important role of the ubiquitin-like SUMO system in regulating both the assembly and disassembly of these structures. Here we will review our current understanding of SUMO function in MLO dynamics under both normal and pathological conditions.

Rare Variant Burden Analysis within Enhancers Identifies CAV1 as an ALS Risk Gene.

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease. CAV1 and CAV2 organize membrane lipid rafts (MLRs) important for cell signaling and neuronal survival, and overexpression of CAV1 ameliorates ALS phenotypes in vivo. Genome-wide association studies localize a large proportion of ALS risk variants within the non-coding genome, but further characterization has been limited by lack of appropriate tools. By designing and applying a pipeline to identify pathogenic genetic variation within enhancer elements responsible for regulating gene expression, we identify disease-associated variation within CAV1/CAV2 enhancers, which replicate in an independent cohort. Discovered enhancer mutations reduce CAV1/CAV2 expression and disrupt MLRs in patient-derived cells, and CRISPR-Cas9 perturbation proximate to a patient mutation is sufficient to reduce CAV1/CAV2 expression in neurons. Additional enrichment of ALS-associated mutations within CAV1 exons positions CAV1 as an ALS risk gene. We propose CAV1/CAV2 overexpression as a personalized medicine target for ALS.

Spatiotemporal Proteomic Analysis of Stress Granule Disassembly Using APEX Reveals Regulation by SUMOylation and Links to ALS Pathogenesis.

Stress granules (SGs) are cytoplasmic assemblies of proteins and non-translating mRNAs. Whereas much has been learned about SG formation, a major gap remains in understanding the compositional changes SGs undergo during normal disassembly and under disease conditions. Here, we address this gap by proteomic dissection of the SG temporal disassembly sequence using multi-bait APEX proximity proteomics. We discover 109 novel SG proteins and characterize distinct SG substructures. We reveal dozens of disassembly-engaged proteins (DEPs), some of which play functional roles in SG disassembly, including small ubiquitin-like modifier (SUMO) conjugating enzymes. We further demonstrate that SUMOylation regulates SG disassembly and SG formation. Parallel proteomics with amyotrophic lateral sclerosis (ALS)-associated C9ORF72 dipeptides uncovered attenuated DEP recruitment during SG disassembly and impaired SUMOylation. Accordingly, SUMO activity ameliorated C9ORF72-ALS-related neurodegeneration in Drosophila. By dissecting the SG spatiotemporal proteomic landscape, we provide an in-depth resource for future work on SG function and reveal basic and disease-relevant mechanisms of SG disassembly.

Human genetics and neuropathology suggest a link between miR-218 and amyotrophic lateral sclerosis pathophysiology.

Motor neuron-specific microRNA-218 (miR-218) has recently received attention because of its roles in mouse development. However, miR-218 relevance to human motor neuron disease was not yet explored. Here, we demonstrate by neuropathology that miR-218 is abundant in healthy human motor neurons. However, in amyotrophic lateral sclerosis (ALS) motor neurons, miR-218 is down-regulated and its mRNA targets are reciprocally up-regulated (derepressed). We further identify the potassium channel Kv10.1 as a new miR-218 direct target that controls neuronal activity. In addition, we screened thousands of ALS genomes and identified six rare variants in the human miR-218-2 sequence. miR-218 gene variants fail to regulate neuron activity, suggesting the importance of this small endogenous RNA for neuronal robustness. The underlying mechanisms involve inhibition of miR-218 biogenesis and reduced processing by DICER. Therefore, miR-218 activity in motor neurons may be susceptible to failure in human ALS, suggesting that miR-218 may be a potential therapeutic target in motor neuron disease.

miR-17-92 and miR-106b-25 clusters regulate beta cell mitotic checkpoint and insulin secretion in mice.

AIMS/HYPOTHESIS: Adult beta cells in the pancreas are the sole source of insulin in the body. Beta cell loss or increased demand for insulin impose metabolic challenges because adult beta cells are generally quiescent and infrequently re-enter the cell division cycle. The aim of this study is to test the hypothesis that a family of proto-oncogene microRNAs that includes miR-17-92 and miR-106b-25 clusters regulates beta cell proliferation or function in the adult endocrine pancreas. METHODS: To elucidate the role of miR-17-92 and miR-106b-25 clusters in beta cells, we used a conditional miR-17-92/miR-106b-25 knockout mouse model. We employed metabolic assays in vivo and ex vivo, together with advanced microscopy of pancreatic sections, bioinformatics, mass spectrometry and next generation sequencing, to examine potential targets of miR-17-92/miR-106b-25, by which they might regulate beta cell proliferation and function. RESULTS: We demonstrate that miR-17-92/miR-106b-25 regulate the adult beta cell mitotic checkpoint and that miR-17-92/miR-106b-25 deficiency results in reduction in beta cell mass in vivo. Furthermore, we reveal a critical role for miR-17-92/miR-106b-25 in glucose homeostasis and in controlling insulin secretion. We identify protein kinase A as a new relevant molecular pathway downstream of miR-17-92/miR-106b-25 in control of adult beta cell division and glucose homeostasis. CONCLUSIONS/INTERPRETATION: The study contributes to the understanding of proto-oncogene miRNAs in the normal, untransformed endocrine pancreas and illustrates new genetic means for regulation of beta cell mitosis and function by non-coding RNAs. DATA AVAILABILITY: Sequencing data that support the findings of this study have been deposited in GEO with the accession code GSE126516.

Evaluation of methodologies for microRNA biomarker detection by next generation sequencing.

In recent years, microRNAs (miRNAs) in tissues and biofluids have emerged as a new class of promising biomarkers for numerous diseases. Blood-based biomarkers are particularly desirable since serum or plasma is easily accessible and can be sampled repeatedly. To comprehensively explore the biomarker potential of miRNAs, sensitive, accurate and cost-efficient miRNA profiling techniques are required. Next generation sequencing (NGS) is emerging as the preferred method for miRNA profiling; offering high sensitivity, single-nucleotide resolution and the possibility to profile a considerable number of samples in parallel. Despite the excitement about miRNA biomarkers, challenges associated with insufficient characterization of the sequencing library preparation efficacy, precision and method-related quantification bias have not been addressed in detail and are generally underappreciated in the wider research community. Here, we have tested in parallel four commercially available small RNA sequencing kits against a cohort of samples comprised of human plasma, human serum, murine brain tissue and a reference library containing ~ 950 synthetic miRNAs. We discuss the advantages and limits of these methodologies for massive parallel microRNAs profiling. This work can serve as guideline for choosing an adequate library preparation method, based on sensitivity, specificity and accuracy of miRNA quantification, workflow convenience and potential for automation.