Search

Intermediate CAG (polyQ) expansions in the gene ataxin-2 (ATXN2) are now recognized as a risk factor for amyotrophic lateral sclerosis. The threshold for increased risk is not yet firmly established, with reports ranging from 27 to 31 repeats. We investigated the presence of ATXN2 polyQ expansions in 9268 DNA samples collected from people with amyotrophic lateral sclerosis, amyotrophic lateral sclerosis with frontotemporal dementia, frontotemporal dementia alone, Lewy body dementia and age matched controls. This analysis confirmed ATXN2 intermediate polyQ expansions of ≥31 as a risk factor for amyotrophic lateral sclerosis with an odds ratio of 6.31. Expansions were an even greater risk for amyotrophic lateral sclerosis with frontotemporal dementia (odds ratio 27.59) and a somewhat lesser risk for frontotemporal dementia alone (odds ratio 3.14). There was no increased risk for Lewy body dementia. In a subset of 1362 patients with amyotrophic lateral sclerosis with complete clinical data, we could not confirm previous reports of earlier onset of amyotrophic lateral sclerosis or shorter survival in 25 patients with expansions. These new data confirm ≥31 polyQ repeats in ATXN2 increase the risk for amyotrophic lateral sclerosis, and also for the first time show an even greater risk for amyotrophic lateral sclerosis with frontotemporal dementia. The lack of a more aggressive phenotype in amyotrophic lateral sclerosis patients with expansions has implications for ongoing gene-silencing trials for amyotrophic lateral sclerosis.

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer’s dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia.

Objective.Despite recent advances, it is not clear whether the various genes/genetic variants related to ALS interact in modifying patients phenotype. The aim of this study was to determine if the co-presence of genetic variants related to ALS has interactive effects on the course of the disease.Methods.The study population includes 1,245 ALS patients identified through the Piemonte Register for ALS between 2007 and 2016 and not carryingSOD1, TARDBPandFUSpathogenic variants. Controls were 766 Italian subjects age-, sex-, and geographically-matched to cases. We consideredUNC13A (rs12608932), CAMTA1 (rs2412208), SLC11A2 (rs407135) andZNF512B (rs2275294)variants, as well asATXN2polyQ intermediate repeats (≥31) andC9orf72GGGGCC intronic expansions( ≥30).Results.The median survival time of the whole cohort was 2.67 years (IQR 1.67-5.25). In univariate analysis onlyC9orf72(2.51 years, IQR 1.74-3.82; p=0.016),ATXN2(1.82 years, IQR 1.08-2.33; pUNC13AC/C(2.3 years, IQR 1.3-3.9; pCAMTA1emerged to be independently related to survival (HR 1.13, 95% c.i. 1.001-1.30, p=0.048). The co-presence of two detrimental alleles/expansions was correlated with shorter survival. In particular, the median survival of patients withCAMTA1G/G+G/TandUNC13AC/Calleles was 1.67 years (1.16-3.08) years compared to 2.75 years (1.67-5.26) of the patients not carrying these variants (pCAMTA1G/G+G/Talleles andATXN2≥31intermediate polyQ repeats was 1.75 years (0.84-2.18) (pATXN2≥31polyQ repeats andUNC13AC/Callele was 1.33 years (0.84-1.75) (pC9ORF72≥30andUNC13AC/Callele was 1.66 years (1.41-2.16). Each pair of detrimental alleles/expansions was associated to specific clinical phenotypes.Conclusions.We showed that gene variants acting as modifiers of ALS survival or phenotype can act on their own or in unison. Overall, 54% of patients carried at least one detrimental common variant or repeat expansion, emphasizing the clinical impact of our findings. In addition, the identification of the interactive effects of modifier genes represents a crucial clue for explaining ALS clinical heterogeneity and should be considered when designing and interpreting clinical trials results.

To characterize the clinical and cognitive behavioral phenotype and brainThe study population included 1,409 patients with ALS withoutThe C/C genotype was associated with an increased risk of ALS (odds ratio: 1.54, 95% confidence interval 1.18-2.01,C/C rs12608932 genotype of

Age at onset of amyotrophic lateral sclerosis (ALS) is highly variable (eg, 27–74 years in carriers of the G4C2-expansion in C9orf72). It might be influenced by environmental and genetic factors via the modulation of DNA methylation (DNAm) at CpG-sites. Hence, we combined an epigenetic and genetic approach to test the hypothesis that some common single nucleotide polymorphisms (SNPs) at CpG-sites (CpG-SNPs) could modify ALS age of onset. Our genome-wide DNAm analysis suggested three CpG-SNPs whose DNAm levels are significantly associated with age of onset in 249 ALS patients (q C9orf72-carriers (n = 333; P = 0.025), suggesting that each A-allele delays onset by 1.6 years. Analysis of Genotype-Tissue Expression data revealed that the protective A-allele is linked with the reduced expression of CTSS in cerebellum (P = 0.00018), which is a critical brain region in the distributed neural circuits subserving motor control. CTSS encodes cathepsin S protein playing a key role in antigen presentation. In conclusion, we identified a 16 Kb locus tagged by rs4970944 as a modifier of ALS age of onset. Our findings support the role of antigen presenting processes in modulating age of onset of ALS and suggest potential drug targets (eg, CTSS). Future replication studies are encouraged to validate the link between the locus tagged by rs4970944 and age of onset in independent ALS cohorts, including different ethnic groups.

Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive degenerative disease of upper and lower motor neurons. Approximately 15% of patients display clinical features consistent with frontotemporal dementia (FTD) and 35% display milder degrees of cognitive and behavioural impairment at some stage during their illness.1 Several genes have been reported to cause both ALS and FTD. Nevertheless, it remains unclear why some patients with ALS develop cognitive impairment, while other cases, often within the same family, remain unaffected. The GBA gene (OMIM *606463) encodes glucocerebrosidase (GCase), a lysosomal enzyme that converts glucocerebroside into glucose and ceramide. Heterozygous GBA mutations increase the risk of Parkinson’s disease (PD) and the risk of cognitive impairment in patients with PD.2 It is increasingly recognised that variants in genes causing Mendelian neurodegenerative diseases may exhibit pleiotropic effects and impact the phenotypic heterogeneity of those disorders. Moreover, lysosomal dysfunction has recently been associated with both Dementia with Lewy Bodies and FTD spectrum (online supplemental table 1). Based on this, we postulated that GBA variants may influence the cognitive status of patients with ALS. ### Supplementary data [jnnp-2021-327426supp001.pdf] We examined the GBA variants’ association with the risk of cognitive impairment in 751 patients with ALS from the population-based Piemonte and Valle d’Aosta Register for ALS that had undergone both a detailed neuropsychological evaluation and a whole-genome sequencing screening.3 Patients were classified as ALS with normal cognitive function (ALS-CN), ALS-FTD and ALS with intermediate cognitive deficits. The characteristics of the study population and a detailed description of neuropsychological testing and genetic screening are reported in online supplementarl materials in the Methods section. A mutational screening of GBA exonic variants was performed and their frequencies were compared with an internal control cohort (see online supplemental methods, Subjects). To assess whether pathogenic rare variants (minor allele frequency

Genomics has emerged over the last two decades as a fundamental approach to understanding the molecular basis of human diseases. This Collection brings together some recent articles published in Brain, selected to illustrate the impact of genomics on neurology and to highlight emerging themes in the neurogenetics space.

ObjectiveTo assess the burden of rare genetic variants and to estimate the contribution of known amyotrophic lateral sclerosis (ALS) genes in an Italian population-based cohort, we performed whole genome sequencing in 959 patients with ALS and 677 matched healthy controls.MethodsWe performed genome sequencing in a population-based cohort (Piemonte and Valle d'Aosta Registry for ALS [PARALS]). A panel of 40 ALS genes was analyzed to identify potential disease-causing genetic variants and to evaluate the gene-wide burden of rare variants among our population.ResultsA total of 959 patients with ALS were compared with 677 healthy controls from the same geographical area. Gene-wide association tests demonstrated a strong association with SOD1, whose rare variants are the second most common cause of disease after C9orf72 expansion. A lower signal was observed for TARDBP, proving that its effect on our cohort is driven by a few known causal variants. We detected rare variants in other known ALS genes that did not surpass statistical significance in gene-wise tests, thus highlighting that their contribution to disease risk in our cohort is limited.ConclusionsWe identified potential disease-causing variants in 11.9% of our patients. We identified the genes most frequently involved in our cohort and confirmed the contribution of rare variants in disease risk. Our results provide further insight into the pathologic mechanism of the disease and demonstrate the importance of genome-wide sequencing as a diagnostic tool.

Polygenic inheritance plays a central role in Parkinson disease (PD). A priority in elucidating PD etiology lies in defining the biological basis of genetic risk. Unraveling how risk leads to disruption will yield disease-modifying therapeutic targets that may be effective. Here, we utilized a high-throughput and hypothesis-free approach to determine biological processes underlying PD using the largest currently available cohorts of genetic and gene expression data from International Parkinson’s Disease Genetics Consortium (IPDGC) and the Accelerating Medicines Partnership-Parkinson’s disease initiative (AMP-PD), among other sources. We applied large-scale gene-set specific polygenic risk score (PRS) analyses to assess the role of common variation on PD risk focusing on publicly annotated gene sets representative of curated pathways. We nominated specific molecular sub-processes underlying protein misfolding and aggregation, post-translational protein modification, immune response, membrane and intracellular trafficking, lipid and vitamin metabolism, synaptic transmission, endosomal–lysosomal dysfunction, chromatin remodeling and apoptosis mediated by caspases among the main contributors to PD etiology. We assessed the impact of rare variation on PD risk in an independent cohort of whole-genome sequencing data and found evidence for a burden of rare damaging alleles in a range of processes, including neuronal transmission-related pathways and immune response. We explored enrichment linked to expression cell specificity patterns using single-cell gene expression data and demonstrated a significant risk pattern for dopaminergic neurons, serotonergic neurons, hypothalamic GABAergic neurons, and neural progenitors. Subsequently, we created a novel way of building de novo pathways by constructing a network expression community map using transcriptomic data derived from the blood of PD patients, which revealed functional enrichment in inflammatory signaling pathways, cell death machinery related processes, and dysregulation of mitochondrial homeostasis. Our analyses highlight several specific promising pathways and genes for functional prioritization and provide a cellular context in which such work should be done. Electronic supplementary material The online version of this article (10.1007/s00401-020-02181-3) contains supplementary material, which is available to authorized users.

Background and ObjectivesTo characterize the clinical and cognitive behavioral phenotype and brain18F-2-fluoro-2-deoxy-d-glucose-PET (18F-FDG-PET) metabolism of patients with amyotrophic lateral sclerosis (ALS) carrying the rs12608932 variant of theUNC13Agene.MethodsThe study population included 1,409 patients with ALS withoutC9orf72, SOD1, TARDBP, andFUSmutations identified through a prospective epidemiologic ALS register. Control participants included 1,012 geographically matched, age-matched, and sex-matched participants. Clinical and cognitive differences between patients carrying the C/C rs12608932 genotype and those carrying the A/A + A/C genotype were assessed. A subset of patients underwent18F-FDG-PET.ResultsThe C/C genotype was associated with an increased risk of ALS (odds ratio: 1.54, 95% confidence interval 1.18–2.01,p= 0.001). Patients with the C/C genotype were older, had more frequent bulbar onset, and manifested a higher rate of weight loss. In addition, they showed significantly reduced performance in the letter fluency test, fluency domain of Edinburgh Cognitive and Behavioural ALS Screen (ECAS) and story-based empathy task (reflecting social cognition). Patients with the C/C genotype had a shorter survival (median survival time, C/C 2.25 years, interquartile range [IQR] 1.33–3.92; A/A + C/C: 2.90 years, IQR 1.74–5.41;p= 0.0001). In Cox multivariable analysis, C/C genotype resulted to be an independent prognostic factor. Finally, patients with a C/C genotype had a specific pattern of hypometabolism on brain18F-FDG-PET extending to frontal and precentral areas of the right hemisphere.DiscussionC/C rs12608932 genotype ofUNC13Ais associated with a specific motor and cognitive/behavioral phenotype, which reflects on18F-FDG-PET findings. Our observations highlight the importance of adding the rs12608932 variant inUNC13Ato the ALS genetic panel to refine the individual prognostic prediction and reduce heterogeneity in clinical trials.

Mutations in FUS gene have been described classically in young ALS patients with aggressive disease course. Here we report a large family carrying a missense mutation c.1520 GA in FUS gene with a tight association with an atypical FUS-ALS phenotype. A 60-year-old man with unilateral leg involvement at onset showed very slow disease progression with selective posterior legs atrophy, tracing his aunt's disease history. His father and uncle died for ALS after a long disease course. Another patient with a 14 years history of ALS with the same phenotype, was found to belong to the same family. In all cases, genetic analysis of FUS gene revealed a missense mutation c.1520 GA (p.G507D) inherited with a heterozygous pattern. Co-segregation of p.G507D mutation and a specific disease phenotype within the family, characterised by predominant involvement at the lower limbs, slow progression, late bulbar and respiratory failure, demonstrates pathogenicity of this mutation, establishes a well-defined genotype-phenotype correlation and expands the clinical spectrum of heterogeneity in FUS-ALS.

Amyotrophic lateral sclerosis (ALS) is known to represent a collection of overlapping syndromes. Various classification systems based on empirical observations have been proposed, but it is unclear to what extent they reflect ALS population substructures. We aimed to use machine-learning techniques to identify the number and nature of ALS subtypes to obtain a better understanding of this heterogeneity, enhance our understanding of the disease, and improve clinical care.In this retrospective study, we applied unsupervised Uniform Manifold Approximation and Projection [UMAP]) modelling, semi-supervised (neural network UMAP) modelling, and supervised (ensemble learning based on LightGBM) modelling to a population-based discovery cohort of patients who were diagnosed with ALS while living in the Piedmont and Valle d'Aosta regions of Italy, for whom detailed clinical data, such as age at symptom onset, were available. We excluded patients with missing Revised ALS Functional Rating Scale (ALSFRS-R) feature values from the unsupervised and semi-supervised steps. We replicated our findings in an independent population-based cohort of patients who were diagnosed with ALS while living in the Emilia Romagna region of Italy.Between Jan 1, 1995, and Dec 31, 2015, 2858 patients were entered in the discovery cohort. After excluding 497 (17%) patients with missing ALSFRS-R feature values, data for 42 clinical features across 2361 (83%) patients were available for the unsupervised and semi-supervised analysis. We found that semi-supervised machine learning produced the optimum clustering of the patients with ALS. These clusters roughly corresponded to the six clinical subtypes defined by the Chiò classification system (ie, bulbar, respiratory, flail arm, classical, pyramidal, and flail leg ALS). Between Jan 1, 2009, and March 1, 2018, 1097 patients were entered in the replication cohort. After excluding 108 (10%) patients with missing ALSFRS-R feature values, data for 42 clinical features across 989 patients were available for the unsupervised and semi-supervised analysis. All 1097 patients were included in the supervised analysis. The same clusters were identified in the replication cohort. By contrast, other ALS classification schemes, such as the El Escorial categories, Milano-Torino clinical staging, and King's clinical stages, did not adequately label the clusters. Supervised learning identified 11 clinical parameters that predicted ALS clinical subtypes with high accuracy (area under the curve 0·982 [95% CI 0·980-0·983]).Our data-driven study provides insight into the ALS population substructure and confirms that the Chiò classification system successfully identifies ALS subtypes. Additional validation is required to determine the accuracy and clinical use of these algorithms in assigning clinical subtypes. Nevertheless, our algorithms offer a broad insight into the clinical heterogeneity of ALS and help to determine the actual subtypes of disease that exist within this fatal neurodegenerative syndrome. The systematic identification of ALS subtypes will improve clinical care and clinical trial design.US National Institute on Aging, US National Institutes of Health, Italian Ministry of Health, European Commission, University of Torino Rita Levi Montalcini Department of Neurosciences, Emilia Romagna Regional Health Authority, and Italian Ministry of Education, University, and Research.For the Italian and German translations of the abstract see Supplementary Materials section.

Summary: Various genetic and environmental risk factors have been implicated in the pathogenesis of amyotrophic lateral sclerosis (ALS). Despite this, the cause of most ALS cases remains obscure. In this review, we describe the current evidence implicating genetic and environmental factors in motor neuron degeneration. While the risk exerted by many environmental factors may appear small, their effect could be magnified by the presence of a genetic predisposition. We postulate that gene-environment interactions account for at least a portion of the unknown etiology in ALS. Climate underlies multiple environmental factors, some of which have been implied in ALS etiology, and the impact of global temperature increase on the gene-environment interactions should be carefully monitored. We describe the main concepts underlying such interactions. Although a lack of large cohorts with detailed genetic and environmental information hampers the search for gene-environment interactions, newer algorithms and machine learning approaches offer an opportunity to break this stalemate. Understanding how genetic and environmental factors interact to cause ALS may ultimately pave the way towards precision medicine becoming an integral part of ALS care.

To analyze the frequencies of major genetic variants and the clinical features in Finnish patients with amyotrophic lateral sclerosis (ALS) with or without theA cohort of patients with motor neuron disease was recruited between 1993 and 2020 at the Helsinki University Hospital and 2 second-degree outpatient clinics in Helsinki. Finnish ancestry patients with ALS fulfilled the diagnosis according to the revised El Escorial criteria and the Awaji-criteria. Two categories of familial ALS (FALS) were used. A patient was defined FALS-A if at least 1 first- or second-degree family member had ALS, and FALS-NP, if family members had additional neurologic or psychiatric endophenotypes.Of the 815 patients, 25% had FALS-A and 45% FALS-NP.These results provide further evidence for the short survival of

Amyotrophic lateral sclerosis is a progressive fatal neurodegenerative disease caused by loss of motor neurons and characterized neuropathologically in almost all cases by nuclear depletion and cytoplasmic aggregation of TDP-43, a nuclear RNA binding protein (RBP). We identified ELAVL3 as one of the most downregulated genes in our transcriptome profiles of laser captured microdissection of motor neurons from sporadic ALS nervous systems and the top dysregulated RBPs. Neuropathological characterizations showed ELAVL3 nuclear depletion in a great percentage of remnant motor neurons, sometimes accompanied by cytoplasmic accumulations. These abnormalities were common in sporadic cases with and without intermediate expansions in ATXN2 and familial cases carrying mutations in C9orf72 and SOD1. Depletion of ELAVL3 occurred at both the RNA and protein levels and a short protein isoform was identified but it is not related to a TDP-43-dependent cryptic exon in intron 3. Strikingly, ELAVL3 abnormalities were more frequent than TDP-43 abnormalities and occurred in motor neurons still with normal nuclear TDP-43 present, but all neurons with abnormal TDP-43 also had abnormal ELAVL3. In a neuron-like cell culture model using SH-SY5Y cells, ELAVL3 mislocalization occurred weeks before TDP-43 abnormalities were seen. We interrogated genetic databases but did not identify association of ELAVL3 genetic structure associated with ALS. Taken together, these findings suggest that ELAVL3 is an important RBP in ALS pathogenesis acquired early and the neuropathological data suggest it is involved by loss of function rather than cytoplasmic toxicity.

Amyotrophic lateral sclerosis is a progressive fatal neurodegenerative disease caused by loss of motor neurons and characterized neuropathologically in almost all cases by nuclear depletion and cytoplasmic aggregation of TDP-43, a nuclear RNA-binding protein (RBP). We identified ELAVL3 as one of the most downregulated genes in our transcriptome profiles of laser captured microdissection of motor neurons from sporadic ALS nervous systems and the most dysregulated of all RBPs. Neuropathological characterizations showed ELAVL3 nuclear depletion in a great percentage of remnant motor neurons, sometimes accompanied by cytoplasmic accumulations. These abnormalities were common in sporadic cases with and without intermediate expansions in ATXN2 and familial cases carrying mutations in C9orf72 and SOD1. Depletion of ELAVL3 occurred at both the RNA and protein levels and a short protein isoform was identified, but it is not related to a TDP-43-dependent cryptic exon in intron 3. Strikingly, ELAVL3 abnormalities were more frequent than TDP-43 abnormalities and occurred in motor neurons still with normal nuclear TDP-43 present, but all neurons with abnormal TDP-43 also had abnormal ELAVL3. In a neuron-like cell culture model using SH-SY5Y cells, ELAVL3 mislocalization occurred weeks before TDP-43 abnormalities were seen. We interrogated genetic databases, but did not identify association of ELAVL3 genetic structure with ALS. Taken together, these findings suggest that ELAVL3 is an important RBP in ALS pathogenesis acquired early and the neuropathological data suggest that it is involved by loss of function rather than cytoplasmic toxicity. Supplementary Information The online version contains supplementary material available at 10.1007/s00401-021-02374-4.

SUMMARYBackgroundThe disease entity known as amyotrophic lateral sclerosis (ALS) is now known to represent a collection of overlapping syndromes. A better understanding of this heterogeneity and the ability to distinguish ALS subtypes would improve the clinical care of patients and enhance our understanding of the disease. Subtype profiles could be incorporated into the clinical trial design to improve our ability to detect a therapeutic effect. A variety of classification systems have been proposed over the years based on empirical observations, but it is unclear to what extent they genuinely reflect ALS population substructure.MethodsWe applied machine learning algorithms to a prospective, population-based cohort consisting of 2,858 Italian patients diagnosed with ALS for whom detailed clinical phenotype data were available. We replicated our findings in an independent population-based cohort of 1,097 Italian ALS patients.FindingsWe found that semi-supervised machine learning based on UMAP applied to the output of a multi-layered perceptron neural network produced the optimum clustering of the ALS patients in the discovery cohort. These clusters roughly corresponded to the six clinical subtypes defined by the Chiò classification system (bulbar ALS, respiratory ALS, flail arm ALS, classical ALS, pyramidal ALS, and flail leg ALS). The same clusters were identified in the replication cohort. A supervised learning approach based on ensemble learning identified twelve clinical parameters that predicted ALS clinical subtype with high accuracy (area under the curve = 0·94).InterpretationOur data-driven study provides insight into the ALS population’s substructure and demonstrates that the Chiò classification system robustly identifies ALS subtypes. We provide an interactive website (https://share.streamlit.io/anant-dadu/machinelearningforals/main) so that clinical researchers can predict the clinical subtype of an ALS patient based on a small number of clinical parameters.FundingNational Institute on Aging and the Italian Ministry of Health.RESEARCH IN CONTEXTEvidence before this studyWe searched PubMed for articles published in English from database inception until January 5, 2021, about the use of machine learning and the identification of clinical subtypes within the amyotrophic lateral sclerosis (ALS) population, using the search terms “machine learning”, AND “classification”, AND “amyotrophic lateral sclerosis”. This inquiry identified twenty-nine studies. Most previous studies used machine learning to diagnose ALS (based on gait, imaging, electromyography, gene expression, proteomic, and metabolomic data) or improve brain-computer interfaces. One study used machine learning algorithms to stratify ALS postmortem cortex samples into molecular subtypes based on transcriptome data. Kueffner and colleagues crowdsourced the development of machine learning algorithms to approximately thirty teams to obtain a consensus in an attempt to identify ALS patients subpopulation. In addition to clinical trial information in the PRO-ACT database (www.ALSdatabase.org), this effort used data from the Piedmont and Valle d’Aosta Registry for ALS (PARALS). Four ALS patient categories were identified: slow progressing, fast progressing, early stage, and late stage. This approach’s clinical relevance was unclear, as all ALS patients will necessarily pass through an early and late stage of the disease.Furthermore, no attempt was made to discern which of the existing clinical classification systems, such as the El Escorial criteria, the Chiò classification system, and the King’s clinical staging system, can identify ALS subtypes. We concluded that there remained an unmet need to identify the ALS population’s substructure in a data-driven, non-empirical manner. Building on this, there was a need for a tool that reliably predicts the clinical subtype of an ALS patient. This knowledge would improve our understanding of the clinical heterogeneity associated with this fatal neurodegenerative disease.Added value of this studyThis study developed a machine learning algorithm to detect ALS patients’ clinical subtypes using clinical data collected from the 2,858 Italian ALS patients in PARALS. Ascertainment of these patients within the catchment area was near complete, meaning that the dataset truly represented the ALS population. We replicated our approach using clinical data obtained from an independent cohort of 1,097 Italian ALS patients that had also been collected in a population-based, longitudinal manner. Semi-supervised learning based on Uniform Manifold Approximation and Projection (UMAP) applied to a multilayer perceptron neural network provided the optimum results based on visual inspection. The observed clusters equated to the six clinical subtypes previously defined by the Chiò classification system (bulbar ALS, respiratory ALS, flail arm ALS, classical ALS, pyramidal ALS, and flail leg ALS). Using a small number of clinical parameters, an ensemble learning approach could predict the ALS clinical subtype with high accuracy (area under the curve = 0·94).Implications of all available evidenceAdditional validation is required to determine these algorithms’ accuracy and clinical utility in assigning clinical subtypes. Nevertheless, our algorithms offer a broad insight into the clinical heterogeneity of ALS and help to determine the actual subtypes of disease that exist within this fatal neurodegenerative syndrome. The systematic identification of ALS subtypes will improve clinical care and clinical trial design.

White matter hyperintensities (WMH) are among the most common radiological abnormalities in the ageing population and an established risk factor for stroke and dementia. While common variant association studies have revealed multiple genetic loci with an influence on their volume, the contribution of rare variants to the WMH burden in the general population remains largely unexplored. We conducted a comprehensive analysis of this burden in the UK Biobank using publicly available whole-exome sequencing data (n up to 17 830) and found a splice-site variant in GBE1, encoding 1,4-alpha-glucan branching enzyme 1, to be associated with lower white matter burden on an exome-wide level [c.691+2T>C, β = −0.74, standard error (SE) = 0.13, P = 9.7 × 10(−9)]. Applying whole-exome gene-based burden tests, we found damaging missense and loss-of-function variants in HTRA1 (frequency of 1 in 275 in the UK Biobank population) to associate with an increased WMH volume (P = 5.5 × 10(−6), false discovery rate = 0.04). HTRA1 encodes a secreted serine protease implicated in familial forms of small vessel disease. Domain-specific burden tests revealed that the association with WMH volume was restricted to rare variants in the protease domain (amino acids 204–364; β = 0.79, SE = 0.14, P = 9.4 × 10(−8)). The frequency of such variants in the UK Biobank population was 1 in 450. The WMH volume was brought forward by ∼11 years in carriers of a rare protease domain variant. A comparison with the effect size of established risk factors for WMH burden revealed that the presence of a rare variant in the HTRA1 protease domain corresponded to a larger effect than meeting the criteria for hypertension (β = 0.26, SE = 0.02, P = 2.9 × 10(−59)) or being in the upper 99.8% percentile of the distribution of a polygenic risk score based on common genetic variants (β = 0.44, SE = 0.14, P = 0.002). In biochemical experiments, most (6/9) of the identified protease domain variants resulted in markedly reduced protease activity. We further found EGFL8, which showed suggestive evidence for association with WMH volume (P = 1.5 × 10(−4), false discovery rate = 0.22) in gene burden tests, to be a direct substrate of HTRA1 and to be preferentially expressed in cerebral arterioles and arteries. In a phenome-wide association study mapping ICD-10 diagnoses to 741 standardized Phecodes, rare variants in the HTRA1 protease domain were associated with multiple neurological and non-neurological conditions including migraine with aura (odds ratio = 12.24, 95%CI: 2.54–35.25; P = 8.3 × 10(−5)]. Collectively, these findings highlight an important role of rare genetic variation and the HTRA1 protease in determining WMH burden in the general population.

Summary Background The genetic basis of variation in the progression of primary tauopathies has not been determined. We aimed to identify genetic determinants of survival in progressive supranuclear palsy (PSP). Methods In stage one of this two stage genome-wide association study (GWAS), we included individuals with PSP, diagnosed according to pathological and clinical criteria, from two separate cohorts: the 2011 PSP GWAS cohort, from brain banks based at the Mayo Clinic (Jacksonville, FL, USA) and in Munich (Germany), and the University College London PSP cohort, from brain banks and the PROSPECT study, a UK-wide longitudinal study of patients with atypical parkinsonian syndromes. Individuals were included if they had clinical data available on sex, age at motor symptom onset, disease duration (from motor symptom onset to death or to the date of censoring, Dec 1, 2019, if individuals were alive), and PSP phenotype (with reference to the 2017 Movement Disorder Society criteria). Genotype data were used to do a survival GWAS using a Cox proportional hazards model. In stage two, data from additional individuals from the Mayo Clinic brain bank, which were obtained after the 2011 PSP GWAS, were used for a pooled analysis. We assessed the expression quantitative trait loci (eQTL) profile of variants that passed genome-wide significance in our GWAS using the Functional Mapping and Annotation of GWAS platform, and did colocalisation analyses using the eQTLGen and PsychENCODE datasets. Findings Data were collected and analysed between Aug 1, 2016, and Feb 1, 2020. Data were available for 1001 individuals of white European ancestry with PSP in stage one. We found a genome-wide significant association with survival at chromosome 12 (lead single nucleotide polymorphism rs2242367, p=7·5 × 10−10, hazard ratio 1·42 [95% CI 1·22–1·67]). rs2242367 was associated with survival in the individuals added in stage two (n=238; p=0·049, 1·22 [1·00–1·48]) and in the pooled analysis of both stages (n=1239; p=1·3 × 10−10, 1·37 [1·25–1·51]). An eQTL database screen revealed that rs2242367 is associated with increased expression of LRRK2 and two long intergenic non-coding RNAs (lncRNAs), LINC02555 and AC079630.4, in whole blood. Although we did not detect a colocalisation signal for LRRK2, analysis of the PSP survival signal and eQTLs for LINC02555 in the eQTLGen blood dataset revealed a posterior probability of hypothesis 4 of 0·77, suggesting colocalisation due to a single shared causal variant. Interpretation Genetic variation at the LRRK2 locus was associated with survival in PSP. The mechanism of this association might be through a lncRNA-regulated effect on LRRK2 expression because LINC02555 has previously been shown to regulate LRRK2 expression. LRRK2 has been associated with sporadic and familial forms of Parkinson's disease, and our finding suggests a genetic overlap with PSP. Further functional studies will be important to assess the potential of LRRK2 modulation as a disease-modifying therapy for PSP and related tauopathies. Funding PSP Association, CBD Solutions, Medical Research Council (UK).

Objective To identify potential biomarkers of preclinical and clinical progression in chromosome 9 open reading frame 72 gene (C9orf72)-associated disease by assessing the expression levels of plasma microRNAs (miRNAs) in C9orf72 patients and presymptomatic carriers. Methods The PREV-DEMALS study is a prospective study including 22 C9orf72 patients, 45 presymptomatic C9orf72 mutation carriers and 43 controls. We assessed the expression levels of 2576 miRNAs, among which 589 were above noise level, in plasma samples of all participants using RNA sequencing. The expression levels of the differentially expressed miRNAs between patients, presymptomatic carriers and controls were further used to build logistic regression classifiers. Results Four miRNAs were differentially expressed between patients and controls: miR-34a-5p and miR-345-5p were overexpressed, while miR-200c-3p and miR-10a-3p were underexpressed in patients. MiR-34a-5p was also overexpressed in presymptomatic carriers compared with healthy controls, suggesting that miR-34a-5p expression is deregulated in cases with C9orf72 mutation. Moreover, miR-345-5p was also overexpressed in patients compared with presymptomatic carriers, which supports the correlation of miR-345-5p expression with the progression of C9orf72-associated disease. Together, miR-200c-3p and miR-10a-3p underexpression might be associated with full-blown disease. Four presymptomatic subjects in transitional/prodromal stage, close to the disease conversion, exhibited a stronger similarity with the expression levels of patients. Conclusions We identified a signature of four miRNAs differentially expressed in plasma between clinical conditions that have potential to represent progression biomarkers for C9orf72-associated frontotemporal dementia and amyotrophic lateral sclerosis. This study suggests that dysregulation of miRNAs is dynamically altered throughout neurodegenerative diseases progression, and can be detectable even long before clinical onset. Trial registration number NCT02590276.

Massive genetic analysis identifies critical pathways and cell types involved in pathogenesis of amyotrophic lateral sclerosis., Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely, neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated six differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, MAPKAPK3, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

Aggregation and cytoplasmic mislocalization of TDP-43 are pathological hallmarks of amyotrophic lateral sclerosis and frontotemporal dementia spectrum. However, the molecular mechanism by which TDP-43 aggregates form and cause neurodegeneration remains poorly understood. Cyclophilin A, also known as peptidyl-prolyl cis-trans isomerase A (PPIA), is a foldase and molecular chaperone. We previously found that PPIA interacts with TDP-43 and governs some of its functions, and its deficiency accelerates disease in a mouse model of amyotrophic lateral sclerosis. Here we characterized PPIA knock-out mice throughout their lifespan and found that they develop a neurodegenerative disease with key behavioural features of frontotemporal dementia, marked TDP-43 pathology and late-onset motor dysfunction. In the mouse brain, deficient PPIA induces mislocalization and aggregation of the GTP-binding nuclear protein Ran, a PPIA interactor and a master regulator of nucleocytoplasmic transport, also for TDP-43. Moreover, in absence of PPIA, TDP-43 autoregulation is perturbed and TDP-43 and proteins involved in synaptic function are downregulated, leading to impairment of synaptic plasticity. Finally, we found that PPIA was downregulated in several patients with amyotrophic lateral sclerosis and amyotrophic lateral sclerosis-frontotemporal dementia, and identified a PPIA loss-of-function mutation in a patient with sporadic amyotrophic lateral sclerosis . The mutant PPIA has low stability, altered structure and impaired interaction with TDP-43. These findings strongly implicate that defective PPIA function causes TDP-43 mislocalization and dysfunction and should be considered in future therapeutic approaches., Pasetto et al. show that PPIA helps protect against TDP-43-mediated neurodegeneration. They identify a PPIA loss-of-function mutation in a patient with sporadic ALS, and reveal reduced PPIA levels in several other ALS and ALS-FTD patients. PPIA knock-out mice develop a neurodegenerative disease with a clear ALS-FTD phenotype.

Hannu Laaksovirta konsortion jäsenenä. The Genomics England Research Consortium, The International ALS/FTD Genomics Consortium (iAFGC), The International FTD Genetics Consortium (IFGC), The International LBD Genomics Consortium (iLBDGC), The NYGC ALS Consortium, The PROSPECT Consortium,17 James B. Rowe,17 Luisa Benussi,18 Giuliano Binetti,18,19 Roberta Ghidoni,18 Edwin Jabbari,20,21 Coralie Viollet,22 Jonathan D. Glass,23 Andrew B. Singleton,24 Vincenzo Silani,25,26 Owen A. Ross,27 Mina Ryten,8,28,29 Ali Torkamani,30 Toshiko Tanaka,31 Luigi Ferrucci,31 Susan M. Resnick,32 We examined the role of repeat expansions in the pathogenesis of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) by analyzing whole-genome sequence data from 2,442 FTD/ALS patients, 2,599 Lewy body dementia (LBD) patients, and 3,158 neurologically healthy subjects. Pathogenic expansions (range, 40?64 CAG repeats) in the huntingtin (HTT) gene were found in three (0.12%) patients diagnosed with pure FTD/ALS syndromes but were not present in the LBD or healthy cohorts. We replicated our findings in an independent collection of 3,674 FTD/ALS patients. Postmortem evaluations of two patients revealed the classical TDP-43 pathology of FTD/ALS, as well as huntingtin-positive, ubiquitin-positive aggregates in the frontal cortex. The neostriatal atrophy that pathologically defines Huntington?s disease was absent in both cases. Our findings reveal an etiological relationship between HTT repeat expansions and FTD/ALS syndromes and indicate that genetic screening of FTD/ALS patients for HTT repeat expansions should be considered. We examined the role of repeat expansions in the pathogenesis of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) by analyzing whole-genome sequence data from 2,442 FTD/ALS patients, 2,599 Lewy body dementia (LBD) patients, and 3,158 neurologically healthy subjects. Pathogenic expansions (range, 40?64 CAG repeats) in the huntingtin (HTT) gene were found in three (0.12%) patients diagnosed with pure FTD/ALS syndromes but were not present in the LBD or healthy cohorts. We replicated our findings in an independent collection of 3,674 FTD/ALS patients. Postmortem evaluations of two patients revealed the classical TDP-43 pathology of FTD/ALS, as well as huntingtin-positive, ubiquitin-positive aggregates in the frontal cortex. The neostriatal atrophy that pathologically defines Huntington?s disease was absent in both cases. Our findings reveal an etiological relationship between HTT repeat expansions and FTD/ALS syndromes and indicate that genetic screening of FTD/ALS patients for HTT repeat expansions should be considered.

ObjectivesTo approximate the rate of familial myasthenia gravis and the coexistence of other autoimmune disorders in the patients and their families.DesignRetrospective cohort study.SettingClinics across North America.ParticipantsThe study included 1032 patients diagnosed with acetylcholine receptor antibody (AChR)-positive myasthenia gravis.MethodsPhenotype information of 1032 patients diagnosed with AChR-positive myasthenia gravis was obtained from clinics at 14 centres across North America between January 2010 and January 2011. A critical review of the epidemiological literature on the familial rate of myasthenia gravis was also performed.ResultsAmong 1032 patients, 58 (5.6%) reported a family history of myasthenia gravis. A history of autoimmune diseases was present in 26.6% of patients and in 28.4% of their family members.DiscussionThe familial rate of myasthenia gravis was higher than would be expected for a sporadic disease. Furthermore, a high proportion of patients had a personal or family history of autoimmune disease. Taken together, these findings suggest a genetic contribution to the pathogenesis of myasthenia gravis.

Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic cortical interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated five differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

Fibroblasts from an amyotrophic lateral sclerosis patient with simultaneous mutations in the MATR3 gene and KIF5A gene were isolated and reprogrammed into induced pluripotent stem cells via a non-integrating Sendai viral vector. The generated iPSC clones demonstrated normal karyotype, expression of pluripotency markers, and the capacity to differentiate into three germ layers. The unique presence of two simultaneous mutations in ALS-associated genes represent a novel tool for the study of ALS disease mechanisms.

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer’s and Parkinson’s disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.

Aggregation and cytoplasmic mislocalization of TDP-43 are pathological hallmarks of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) spectrum. However, the molecular mechanism by which TDP-43 aggregates form and cause neurodegeneration remains poorly understood. Cyclophilin A, also known as peptidyl-prolyl cis-trans isomerase A (PPIA), is a foldase and molecular chaperone. We previously found that PPIA interacts with TDP-43 and governs some of its functions, and its deficiency accelerates disease in a mouse model of ALS. Here we characterized PPIA knock-out mice throughout their lifespan and found that they develop a neurodegenerative disease with key behavioural features of FTD, marked TDP-43 pathology and late-onset motor dysfunction. In the mouse brain, deficient PPIA induces aggregation of the GTP-binding nuclear protein Ran, a PPIA substrate required for TDP-43 nucleocytoplasmic trafficking. Moreover, in absence of PPIA, TDP-43 autoregulation is perturbed and TDP-43 and proteins involved in synaptic function are downregulated, leading to impairment of synaptic plasticity. Finally, we found that PPIA was downregulated in several ALS and ALS-FTD patients and identified a PPIA loss-of-function mutation in a sporadic ALS patient. The mutant PPIA has low stability, altered structure and impaired interaction with TDP-43. These findings strongly implicate that defective PPIA function causes TDP-43 mislocalization and dysfunction and should be considered in future therapeutic approaches.

Polygenic inheritance plays a central role in Parkinson disease (PD). A priority in elucidating PD etiology lies in defining the biological basis of genetic risk. Unraveling how risk leads to disruption will yield disease-modifying therapeutic targets that may be effective. Here, we utilized a high-throughput and hypothesis-free approach to determine biological pathways underlying PD using the largest currently available cohorts of genetic data and gene expression data from International Parkinson’s Disease Genetics Consortium (IPDGC) and the Accelerating Medicines Partnership - Parkinson’s disease initiative (AMP-PD), among other sources. We placed these insights into a cellular context. We applied large-scale pathway-specific polygenic risk score (PRS) analyses to assess the role of common variation on PD risk in a cohort of 457,110 individuals by focusing on a compilation of 2,199 publicly annotated gene sets representative of curated pathways, of which we nominate 46 pathways associated with PD risk. We assessed the impact of rare variation on PD risk in an independent cohort of whole-genome sequencing data, including 4,331 individuals. We explored enrichment linked to expression cell specificity patterns using single-cell gene expression data and demonstrated a significant risk pattern for adult dopaminergic neurons, serotonergic neurons, and radial glia. Subsequently, we created a novel way of building de novo pathways by constructing a network expression community map using transcriptomic data derived from the blood of 1,612 PD patients, which revealed 54 connecting networks associated with PD. Our analyses highlight several promising pathways and genes for functional prioritization and provide a cellular context in which such work should be done.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are two diseases that form a broad neurodegenerative continuum. Considerable effort has been made to unravel the genetics of these disorders, and, based on this work, it is now clear that ALS and FTD have a significant genetic overlap. TARDBP, SQSTM1, VCP, FUS, TBK1, CHCHD10, and most importantly C9orf72, are the critical genetic players in these neurological disorders. Discoveries of these genes have implicated autophagy, RNA regulation, and vesicle and inclusion formation as the central pathways involved in neurodegeneration. Here we provide a summary of the significant genes identified in these two intrinsically linked neurodegenerative diseases and highlight the genetic and pathological overlaps.