An atlas of cells in the human tonsil.

Palatine tonsils are secondary lymphoid organs (SLOs) representing the first line of immunological defense against inhaled or ingested pathogens. We generated an atlas of the human tonsil composed of >556,000 cells profiled across five different data modalities, including single-cell transcriptome, epigenome, proteome, and immune repertoire sequencing, as well as spatial transcriptomics. This census identified 121 cell types and states, defined developmental trajectories, and enabled an understanding of the functional units of the tonsil. Exemplarily, we stratified myeloid slan-like subtypes, established a BCL6 enhancer as locally active in follicle-associated T and B cells, and identified SIX5 as putative transcriptional regulator of plasma cell maturation. Analyses of a validation cohort confirmed the presence, annotation, and markers of tonsillar cell types and provided evidence of age-related compositional shifts. We demonstrate the value of this resource by annotating cells from B cell-derived mantle cell lymphomas, linking transcriptional heterogeneity to normal B cell differentiation states of the human tonsil.

ß-Glucan Reverses the Epigenetic State of LPS-Induced Immunological Tolerance.

Innate immune memory is the phenomenon whereby innate immune cells such as monocytes or macrophages undergo functional reprogramming after exposure to microbial components such as lipopolysaccharide (LPS). We apply an integrated epigenomic approach to characterize the molecular events involved in LPS-induced tolerance in a time-dependent manner. Mechanistically, LPS-treated monocytes fail to accumulate active histone marks at promoter and enhancers of genes in the lipid metabolism and phagocytic pathways. Transcriptional inactivity in response to a second LPS exposure in tolerized macrophages is accompanied by failure to deposit active histone marks at promoters of tolerized genes. In contrast, ß-glucan partially reverses the LPS-induced tolerance in vitro. Importantly, ex vivo ß-glucan treatment of monocytes from volunteers with experimental endotoxemia re-instates their capacity for cytokine production. Tolerance is reversed at the level of distal element histone modification and transcriptional reactivation of otherwise unresponsive genes. VIDEO ABSTRACT.

Leveraging European infrastructures to access 1 million human genomes by 2022.

Human genomics is undergoing a step change from being a predominantly research-driven activity to one driven through health care as many countries in Europe now have nascent precision medicine programmes. To maximize the value of the genomic data generated, these data will need to be shared between institutions and across countries. In recognition of this challenge, 21 European countries recently signed a declaration to transnationally share data on at least 1 million human genomes by 2022. In this Roadmap, we identify the challenges of data sharing across borders and demonstrate that European research infrastructures are well-positioned to support the rapid implementation of widespread genomic data access.

Author Correction: Leveraging European infrastructures to access 1 million human genomes by 2022.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A critical spotlight on the paradigms of FFPE-DNA sequencing.

In the late 19th century, formalin fixation with paraffin-embedding (FFPE) of tissues was developed as a fixation and conservation method and is still used to this day in routine clinical and pathological practice. The implementation of state-of-the-art nucleic acid sequencing technologies has sparked much interest for using historical FFPE samples stored in biobanks as they hold promise in extracting new information from these valuable samples. However, formalin fixation chemically modifies DNA, which potentially leads to incorrect sequences or misinterpretations in downstream processing and data analysis. Many publications have concentrated on one type of DNA damage, but few have addressed the complete spectrum of FFPE-DNA damage. Here, we review mitigation strategies in (I) pre-analytical sample quality control, (II) DNA repair treatments, (III) analytical sample preparation and (IV) bioinformatic analysis of FFPE-DNA. We then provide recommendations that are tested and illustrated with DNA from 13-year-old liver specimens, one FFPE preserved and one fresh frozen, applying target-enriched sequencing. Thus, we show how DNA damage can be compensated, even when using low quantities (50 ng) of fragmented FFPE-DNA (DNA integrity number 2.0) that cannot be amplified well (Q129 bp/Q41 bp = 5%). Finally, we provide a checklist called 'ERROR-FFPE-DNA' that summarises recommendations for the minimal information in publications required for assessing fitness-for-purpose and inter-study comparison when using FFPE samples.

The ulcerative colitis-associated gene FUT8 regulates the quantity and quality of secreted mucins.

Mucins are the main macrocomponents of the mucus layer that protects the digestive tract from pathogens. Fucosylation of mucins increases mucus viscoelasticity and its resistance to shear stress. These properties are altered in patients with ulcerative colitis (UC), which is marked by a chronic inflammation of the distal part of the colon. Here, we show that levels of Fucosyltransferase 8 (FUT8) and specific mucins are increased in the distal inflamed colon of UC patients. Recapitulating this FUT8 overexpression in mucin-producing HT29-18N2 colonic cell line increases delivery of MUC1 to the plasma membrane and extracellular release of MUC2 and MUC5AC. Mucins secreted by FUT8 overexpressing cells are more resistant to removal from the cell surface than mucins secreted by FUT8-depleted cells (FUT8 KD). FUT8 KD causes intracellular accumulation of MUC1 and alters the ratio of secreted MUC2 to MUC5AC. These data fit well with the Fut8-/- mice phenotype, which are protected from UC. Fut8-/- mice exhibit a thinner proximal colon mucus layer with an altered ratio of neutral to acidic mucins. Together, our data reveal that FUT8 modifies the biophysical properties of mucus by controlling levels of cell surface MUC1 and quantity and quality of secreted MUC2 and MUC5AC. We suggest that these changes in mucus viscoelasticity likely facilitate bacterial-epithelial interactions leading to inflammation and UC progression.

A single-cell tumor immune atlas for precision oncology.

The tumor immune microenvironment is a main contributor to cancer progression and a promising therapeutic target for oncology. However, immune microenvironments vary profoundly between patients, and biomarkers for prognosis and treatment response lack precision. A comprehensive compendium of tumor immune cells is required to pinpoint predictive cellular states and their spatial localization. We generated a single-cell tumor immune atlas, jointly analyzing published data sets of >500,000 cells from 217 patients and 13 cancer types, providing the basis for a patient stratification based on immune cell compositions. Projecting immune cells from external tumors onto the atlas facilitated an automated cell annotation system. To enable in situ mapping of immune populations for digital pathology, we applied SPOTlight, combining single-cell and spatial transcriptomics data and identifying colocalization patterns of immune, stromal, and cancer cells in tumor sections. We expect the tumor immune cell atlas, together with our versatile toolbox for precision oncology, to advance currently applied stratification approaches for prognosis and immunotherapy.

Convert-Pheno: A software toolkit for the interconversion of standard data models for phenotypic data.

Efficient sharing and integration of phenotypic data is crucial for advancing biomedical research and enhancing patient outcomes in precision medicine and public health. To achieve this, the health data community has developed standards to promote the harmonization of variable names and values. However, the use of diverse standards across different research centers can hinder progress. Here we present Convert-Pheno, an open-source software toolkit that enables the interconversion of common data models for phenotypic data such as Beacon v2 Models, CDISC-ODM, OMOP-CDM, Phenopackets v2, and REDCap. Along with the software, we have created a detailed documentation that includes information on deployment and installation.

Chromatin activation as a unifying principle underlying pathogenic mechanisms in multiple myeloma.

Multiple myeloma (MM) is a plasma cell neoplasm associated with a broad variety of genetic lesions. In spite of this genetic heterogeneity, MMs share a characteristic malignant phenotype whose underlying molecular basis remains poorly characterized. In the present study, we examined plasma cells from MM using a multi-epigenomics approach and demonstrated that, when compared to normal B cells, malignant plasma cells showed an extensive activation of regulatory elements, in part affecting coregulated adjacent genes. Among target genes up-regulated by this process, we found members of the NOTCH, NF-kB, MTOR signaling, and TP53 signaling pathways. Other activated genes included sets involved in osteoblast differentiation and response to oxidative stress, all of which have been shown to be associated with the MM phenotype and clinical behavior. We functionally characterized MM-specific active distant enhancers controlling the expression of thioredoxin (TXN), a major regulator of cellular redox status and, in addition, identified PRDM5 as a novel essential gene for MM. Collectively, our data indicate that aberrant chromatin activation is a unifying feature underlying the malignant plasma cell phenotype.

SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes.

Spatially resolved gene expression profiles are key to understand tissue organization and function. However, spatial transcriptomics (ST) profiling techniques lack single-cell resolution and require a combination with single-cell RNA sequencing (scRNA-seq) information to deconvolute the spatially indexed datasets. Leveraging the strengths of both data types, we developed SPOTlight, a computational tool that enables the integration of ST with scRNA-seq data to infer the location of cell types and states within a complex tissue. SPOTlight is centered around a seeded non-negative matrix factorization (NMF) regression, initialized using cell-type marker genes and non-negative least squares (NNLS) to subsequently deconvolute ST capture locations (spots). Simulating varying reference quantities and qualities, we confirmed high prediction accuracy also with shallowly sequenced or small-sized scRNA-seq reference datasets. SPOTlight deconvolution of the mouse brain correctly mapped subtle neuronal cell states of the cortical layers and the defined architecture of the hippocampus. In human pancreatic cancer, we successfully segmented patient sections and further fine-mapped normal and neoplastic cell states. Trained on an external single-cell pancreatic tumor references, we further charted the localization of clinical-relevant and tumor-specific immune cell states, an illustrative example of its flexible application spectrum and future potential in digital pathology.

The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases.

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.

Genome-wide nucleosome specificity and function of chromatin remodellers in ES cells.

ATP-dependent chromatin remodellers allow access to DNA for transcription factors and the general transcription machinery, but whether mammalian chromatin remodellers target specific nucleosomes to regulate transcription is unclear. Here we present genome-wide remodeller-nucleosome interaction profiles for the chromatin remodellers Chd1, Chd2, Chd4, Chd6, Chd8, Chd9, Brg1 and Ep400 in mouse embryonic stem (ES) cells. These remodellers bind one or both full nucleosomes that flank micrococcal nuclease (MNase)-defined nucleosome-free promoter regions (NFRs), where they separate divergent transcription. Surprisingly, large CpG-rich NFRs that extend downstream of annotated transcriptional start sites are nevertheless bound by non-nucleosomal or subnucleosomal histone variants (H3.3 and H2A.Z) and marked by H3K4me3 and H3K27ac modifications. RNA polymerase II therefore navigates hundreds of base pairs of altered chromatin in the sense direction before encountering an MNase-resistant nucleosome at the 3' end of the NFR. Transcriptome analysis after remodeller depletion reveals reciprocal mechanisms of transcriptional regulation by remodellers. Whereas at active genes individual remodellers have either positive or negative roles via altering nucleosome stability, at polycomb-enriched bivalent genes the same remodellers act in an opposite manner. These findings indicate that remodellers target specific nucleosomes at the edge of NFRs, where they regulate ES cell transcriptional programs.

bigSCale: an analytical framework for big-scale single-cell data.

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin (Reln)-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets.

Occurrence of the p019 Gene in the blaKPC-Harboring Plasmids: Adverse Clinical Impact for Direct Tracking of KPC-Producing Klebsiella pneumoniae by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry.

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been used for the direct detection of KPC-producing isolates by analysis of the 11,109 Da mass peak representing the P019 protein. In this study, we evaluate the presence of the 11,109 Da mass peak in a collection of 435 unduplicated Klebsiella pneumoniae clinical isolates. The prevalence of the P019 peak in the blaKPC K. pneumoniae isolates was 49.2% (32/65). The 11,109 Da mass peak was not observed in any of the other carbapenemase (319) or noncarbapenemase producers (116). Computational analysis of the presence of the p019 gene was performed in the aforementioned carbapenemase-producing K. pneumoniae isolates fully characterized by whole-genome sequencing (WGS) and in a further collection of 1,649 K. pneumoniae genomes included in EuSCAPE. Herein, we have demonstrated that the p019 gene is not exclusively linked to the pKpQil plasmid but that it is present in the following plasmids: IncFIB(K)/IncFII(K)/ColRNAI, IncFIB(pQil), IncFIB(pQil)/ColRNAI, IncFIB(pQil)/IncFII(K), IncFIB(K)/IncFII(K), and IncX3. In addition, we have proven the independent movement of the Tn4401 and the ISKpn31, of which the p019 gene is a component. The absence of the p019 gene was obvious in Col440I, Col(pHAD28), IncFIB(K)/IncX3/IncFII(K), and IncFIB(K)/IncFII(K) plasmids. In addition, we also observed another plasmid in which neither Tn4401 nor ISKpn31 was found, IncP6. In the EuSCAPE, the occurrence of p019 varied from 0% to 100% among the different geographical locations. The adverse clinical impact of the diminished prevalence of the p019 gene within the plasmid encoding KPC-producing Klebsiella pneumoniae puts forward the need for reconsideration when applying this technique in a clinical setting.

An Improved Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Data Analysis Pipeline for the Identification of Carbapenemase-Producing Klebsiella pneumoniae.

The increasing emergence of carbapenemase-producing Klebsiella pneumoniae (CPK) isolates is a global health alarm. Rapid methods that require minimum sample preparation and rapid data analysis are urgently required. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been used by clinical laboratories for identification of antibiotic-resistant bacteria; however, discrepancies have arisen regarding biological and technical issues. The aim of this study was to standardize an operating procedure and data analysis for identification of CPK by MALDI-TOF MS. To evaluate this approach, a series of 162 K. pneumoniae isolates (112 CPK and 50 non-CPK) were processed in the MALDI BioTyper system (Bruker Daltonik, Germany) following a standard operating procedure. The study was conducted in two stages; the first is denominated the "reproducibility stage" and the second "CPK identification." The first stage was designed to evaluate the biological and technical variation associated with the entire analysis of CPK and the second stage to assess the final accuracy of MALDI-TOF MS for the identification of CPK. Therefore, we present an improved MALDI-TOF MS data analysis pipeline using neural network analysis implemented in Clover MS Data Analysis Software (Clover Biosoft, Spain) that is designed to reduce variability, guarantee interlaboratory reproducibility, and maximize the information selected from the bacterial proteome. Using the random forest (RF) algorithm, 100% of CPK isolates were correctly identified when all the peaks in the spectra were selected as input features and total ion current (TIC) normalization was applied. Thus, we have demonstrated that real-time direct tracking of CPK is possible using MALDI-TOF MS.

Activity of imipenem/relebactam against a Spanish nationwide collection of carbapenemase-producing Enterobacterales.

BACKGROUND: Imipenem/relebactam is a novel carbapenem/ß-lactamase inhibitor combination, developed to act against carbapenemase-producing Enterobacterales (CPE). OBJECTIVES: To assess the in vitro activity of imipenem/relebactam against a Spanish nationwide collection of CPE by testing the susceptibility of these isolates to 16 widely used antimicrobials and to determine the underlying ß-lactam resistance mechanisms involved and the molecular epidemiology of carbapenemases in Spain. MATERIALS AND METHODS: Clinical CPE isolates (n = 401) collected for 2 months from 24 hospitals in Spain were tested. MIC50, MIC90 and susceptibility/resistance rates were interpreted in accordance with the EUCAST guidelines. ß-Lactam resistance mechanisms and molecular epidemiology were characterized by WGS. RESULTS: For all isolates, high rates of susceptibility to colistin (86.5%; MIC50/90 = 0.12/8 mg/L), imipenem/relebactam (85.8%; MIC50/90 = 0.5/4 mg/L) and ceftazidime/avibactam (83.8%, MIC50/90 = 1/≥256 mg/L) were observed. The subgroups of isolates producing OXA-48-like (n = 305, 75.1%) and KPC-like enzymes (n = 44, 10.8%) were highly susceptible to ceftazidime/avibactam (97.7%, MIC50/90 = 1/2 mg/L) and imipenem/relebactam (100.0%, MIC50/90 = ≤0.25/1 mg/L), respectively.The most widely disseminated high-risk clones of carbapenemase-producing Klebsiella pneumoniae across Spain were found to be ST11, ST147, ST392 and ST15 (mostly associated with OXA-48) and ST258/512 (in all cases producing KPC). CONCLUSIONS: Imipenem/relebactam, colistin and ceftazidime/avibactam were the most active antimicrobials against all CPEs. Imipenem/relebactam is a valuable addition to the antimicrobial arsenal used in the fight against CPE, particularly against KPC-producing isolates, which in all cases were susceptible to this combination.

Labelled regulatory elements are pervasive features of the macrophage genome and are dynamically utilized by classical and alternative polarization signals.

The concept of tissue-specific gene expression posits that lineage-determining transcription factors (LDTFs) determine the open chromatin profile of a cell via collaborative binding, providing molecular beacons to signal-dependent transcription factors (SDTFs). However, the guiding principles of LDTF binding, chromatin accessibility and enhancer activity have not yet been systematically evaluated. We sought to study these features of the macrophage genome by the combination of experimental (ChIP-seq, ATAC-seq and GRO-seq) and computational approaches. We show that Random Forest and Support Vector Regression machine learning methods can accurately predict chromatin accessibility using the binding patterns of the LDTF PU.1 and four other key TFs of macrophages (IRF8, JUNB, CEBPA and RUNX1). Any of these TFs alone were not sufficient to predict open chromatin, indicating that TF binding is widespread at closed or weakly opened chromatin regions. Analysis of the PU.1 cistrome revealed that two-thirds of PU.1 binding occurs at low accessible chromatin. We termed these sites labelled regulatory elements (LREs), which may represent a dormant state of a future enhancer and contribute to macrophage cellular plasticity. Collectively, our work demonstrates the existence of LREs occupied by various key TFs, regulating specific gene expression programs triggered by divergent macrophage polarizing stimuli.

Variation in predicted COVID-19 risk among lemurs and lorises.

The novel coronavirus SARS-CoV-2, which in humans leads to the disease COVID-19, has caused global disruption and more than 2 million fatalities since it first emerged in late 2019. As we write, infection rates are at their highest point globally and are rising extremely rapidly in some areas due to more infectious variants. The primary target of SARS-CoV-2 is the cellular receptor angiotensin-converting enzyme-2 (ACE2). Recent sequence analyses of the ACE2 gene predict that many nonhuman primates are also likely to be highly susceptible to infection. However, the anticipated risk is not equal across the Order. Furthermore, some taxonomic groups show high ACE2 amino acid conservation, while others exhibit high variability at this locus. As an example of the latter, analyses of strepsirrhine primate ACE2 sequences to date indicate large variation among lemurs and lorises compared to other primate clades despite low sampling effort. Here, we report ACE2 gene and protein sequences for 71 individual strepsirrhines, spanning 51 species and 19 genera. Our study reinforces previous results while finding additional variability in other strepsirrhine species, and suggests several clades of lemurs have high potential susceptibility to SARS-CoV-2 infection. Troublingly, some species, including the rare and endangered aye-aye (Daubentonia madagascariensis), as well as those in the genera Avahi and Propithecus, may be at high risk. Given that lemurs are endemic to Madagascar and among the primates at highest risk of extinction globally, further understanding of the potential threat of COVID-19 to their health should be a conservation priority. All feasible actions should be taken to limit their exposure to SARS-CoV-2.

Genomic evidence for recurrent genetic admixture during the domestication of Mediterranean olive trees (Olea europaea L.).

BACKGROUND: Olive tree (Olea europaea L. subsp. europaea, Oleaceae) has been the most emblematic perennial crop for Mediterranean countries since its domestication around 6000 years ago in the Levant. Two taxonomic varieties are currently recognized: cultivated (var. europaea) and wild (var. sylvestris) trees. However, it remains unclear whether olive cultivars derive from a single initial domestication event followed by secondary diversification, or whether cultivated lineages are the result of more than a single, independent primary domestication event. To shed light into the recent evolution and domestication of the olive tree, here we analyze a group of newly sequenced and available genomes using a phylogenomics and population genomics framework. RESULTS: We improved the assembly and annotation of the reference genome, newly sequenced the genomes of twelve individuals: ten var. europaea, one var. sylvestris, and one outgroup taxon (subsp. cuspidata)-and assembled a dataset comprising whole genome data from 46 var. europaea and 10 var. sylvestris. Phylogenomic and population structure analyses support a continuous process of olive tree domestication, involving a major domestication event, followed by recurrent independent genetic admixture events with wild populations across the Mediterranean Basin. Cultivated olives exhibit only slightly lower levels of genetic diversity than wild forms, which can be partially explained by the occurrence of a mild population bottleneck 3000-14,000 years ago during the primary domestication period, followed by recurrent introgression from wild populations. Genes associated with stress response and developmental processes were positively selected in cultivars, but we did not find evidence that genes involved in fruit size or oil content were under positive selection. This suggests that complex selective processes other than directional selection of a few genes are in place. CONCLUSIONS: Altogether, our results suggest that a primary domestication area in the eastern Mediterranean basin was followed by numerous secondary events across most countries of southern Europe and northern Africa, often involving genetic admixture with genetically rich wild populations, particularly from the western Mediterranean Basin.

Loss-of-Function Mutations in LGI4, a Secreted Ligand Involved in Schwann Cell Myelination, Are Responsible for Arthrogryposis Multiplex Congenita.

Arthrogryposis multiplex congenita (AMC) is a developmental condition characterized by multiple joint contractures resulting from reduced or absent fetal movements. Through genetic mapping of disease loci and whole-exome sequencing in four unrelated multiplex families presenting with severe AMC, we identified biallelic loss-of-function mutations in LGI4 (leucine-rich glioma-inactivated 4). LGI4 is a ligand secreted by Schwann cells that regulates peripheral nerve myelination via its cognate receptor ADAM22 expressed by neurons. Immunolabeling experiments and transmission electron microscopy of the sciatic nerve from one of the affected individuals revealed a lack of myelin. Functional tests using affected individual-derived iPSCs showed that these germline mutations caused aberrant splicing of the endogenous LGI4 transcript and in a cell-based assay impaired the secretion of truncated LGI4 protein. This is consistent with previous studies reporting arthrogryposis in Lgi4-deficient mice due to peripheral hypomyelination. This study adds to the recent reports implicating defective axoglial function as a key cause of AMC.