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This scientific commentary refers to ‘Data-driven neuropathological staging and subtyping of TDP-43 proteinopathies’ by Young et al. (https://doi.org/10.1093/brain/awad145).

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.

BackgroundMultiple system atrophy (MSA) is an atypical parkinsonian disorder marked by autonomic dysfunction, parkinsonism, cerebellar dysfunction, and poor response to dopaminergic medications such as levodopa. Patient-reported quality of life is an important benchmark for clinicians and clinical trials. The Unified Multiple System Atrophy Rating Scale (UMSARS) allows healthcare providers to rate and assess MSA progression. The MSA-QoL questionnaire is a health-related quality of life scale intended to provide patient-reported outcome measures. In this article, we investigated inter-scale correlations between the MSA-QoL and UMSARS to determine factors impacting the quality of life of patients with MSA.MethodsTwenty patients at the Johns Hopkins Atypical Parkinsonism Center's Multidisciplinary Clinic with a diagnosis of clinically probable MSA and who filled out the MSA-QoL and UMSARS questionnaires within 2 weeks of each other were included. Inter-scale correlations between MSA-QoL and UMSARS responses were examined. Linear regressions were also performed to examine relationships between both scales.ResultsSignificant inter-scale correlations were found between the MSA-QoL and UMSARS, both between MSA-QoL total score and UMSARS Part I subtotal scores and for individual scale items. There were no significant correlations between MSA-QoL life satisfaction rating and UMSARS subtotal scores or any specific UMSARS items. Linear regression analysis found significant associations between MSA-QoL total score and UMSARS Part I and total scores, and between MSA-QoL life satisfaction rating and UMSARS Part I, Part II, and total scores (after adjustment for age).ConclusionsOur study demonstrates significant inter-scale correlations between MSA-QoL and UMSARS, particularly relating to activities of daily living and hygiene. MSA-QoL total score and UMSARS Part I subtotal scores, which assess patients' functional status, were significantly correlated. The lack of significant associations between MSA-QoL life satisfaction rating and any UMSARS item suggests there may be aspects to quality of life that are not fully captured by this assessment. Larger cross-sectional and longitudinal analyses utilizing UMSARS and MSA-QoL are warranted and modification of the UMSARS should be considered.

Multiple system atrophy (MSA) is a fatal neurodegenerative disease of unknown etiology characterized by widespread aggregation of the protein alpha-synuclein in neurons and glia. Its orphan status, biological relationship to Parkinson’s disease (PD), and rapid progression have sparked interest in drug development. One significant obstacle to therapeutics is disease heterogeneity. Here, we share our process of developing a clinical trial-ready cohort of MSA patients (69 patients in 2 years) within an outpatient clinical setting, and recruiting 20 of these patients into a longitudinal “n-of-few” clinical trial paradigm. First, we deeply phenotype our patients with clinical scales (UMSARS, BARS, MoCA, NMSS, and UPSIT) and tests designed to establish early differential diagnosis (including volumetric MRI, FDG-PET, MIBG scan, polysomnography, genetic testing, autonomic function tests, skin biopsy) or disease activity (PBR06-TSPO). Second, we longitudinally collect biospecimens (blood, CSF, stool) and clinical, biometric, and imaging data to generate antecedent disease-progression scores. Third, in our Mass General Brigham SCiN study (stemcellsinneurodegeneration), we generate induced pluripotent stem cell (iPSC) models from our patients, matched to biospecimens, including postmortem brain. We present 38 iPSC lines derived from MSA patients and relevant disease controls (spinocerebellar ataxia and PD, including alpha-synuclein triplication cases), 22 matched to whole-genome sequenced postmortem brain. iPSC models may facilitate matching patients to appropriate therapies, particularly in heterogeneous diseases for which patient-specific biology may elude animal models. We anticipate that deeply phenotyped and genotyped patient cohorts matched to cellular models will increase the likelihood of success in clinical trials for MSA.

Background Whole‐genome sequencing data are available from several large studies across a variety of diseases and traits. However, massive storage and computation resources are required to use these data, and to achieve sufficient power for discoveries, harmonization of multiple cohorts is critical. Objectives The Accelerating Medicines Partnership Parkinson's Disease program has developed a research platform for Parkinson's disease (PD) that integrates the storage and analysis of whole‐genome sequencing data, RNA expression data, and clinical data, harmonized across multiple cohort studies. Methods The version 1 release contains whole‐genome sequencing data derived from 3941 participants from 4 cohorts. Samples underwent joint genotyping by the TOPMed Freeze 9 Variant Calling Pipeline. We performed descriptive analyses of these whole‐genome sequencing data using the Accelerating Medicines Partnership Parkinson's Disease platform. Results The clinical diagnosis of participants in version 1 release includes 2005 idiopathic PD patients, 963 healthy controls, 64 prodromal subjects, 62 clinically diagnosed PD subjects without evidence of dopamine deficit, and 705 participants of genetically enriched cohorts carrying PD risk‐associated GBA variants or LRRK2 variants, of whom 304 were affected. We did not observe significant enrichment of pathogenic variants in the idiopathic PD group, but the polygenic risk score was higher in PD both in nongenetically enriched cohorts and genetically enriched cohorts. The population analysis showed a correlation between genetically enriched cohorts and Ashkenazi Jewish ancestry. Conclusions We describe the genetic component of the Accelerating Medicines Partnership Parkinson's Disease platform, a solution to democratize data access and analysis for the PD research community. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article is a U.S. Government work and is in the public domain in the USA.

Parkinson’s disease is the second most common neurodegenerative disease, and its prevalence has been projected to double over the next generation. Nonetheless, an accurate diagnosis of Parkinson’s disease remains challenging, and identifying the earliest stages of the disease is a major unmet need. Recent developments include the validation of modified clinical diagnostic criteria, the introduction and testing of research criteria for prodromal Parkinson’s disease, and the identification of genetic subtypes and a growing number of genetic variants associated with Parkinson’s disease risk. There has also been significant progress in the development of diagnostic biomarkers, of which genetic and imaging tests are already part of routine work-up protocols in clinical practice, while novel tissue and fluid markers are under investigation. Parkinson’s disease is evolving from a clinical to a biomarker-supported diagnostic entity, in which an earlier identification is possible, different subtypes with diverse prognosis are recognized and novel disease-modifying treatments are in development.

Multiple system atrophy is considered a sporadic disease, but neuropathologically confirmed cases with a family history of parkinsonism have been occasionally described. Here we report a North-Bavarian (colloquially, Lion’s tail region) six-generation pedigree, including neuropathologically confirmed multiple system atrophy and Parkinson’s disease with dementia. Between 2012 and 2020, we examined all living and consenting family members of age and calculated the risk of prodromal Parkinson’s disease in those without overt parkinsonism. The index case and one paternal cousin with Parkinson’s disease with dementia died at follow-up and underwent neuropathological examination. Genetic analysis was performed in both and another family member with Parkinson’s disease. The index case was a female patient with cerebellar variant multiple system atrophy and a positive maternal and paternal family history for Parkinson’s disease and dementia in multiple generations. The families of the index case and her spouse were genealogically related, and one of the spouse's siblings met the criteria for possible prodromal Parkinson’s disease. Neuropathological examination confirmed multiple system atrophy in the index case and advanced Lewy body disease, as well as tau pathology in her cousin. A comprehensive analysis of genes known to cause hereditary forms of parkinsonism or multiple system atrophy lookalikes was unremarkable in the index case and the other two affected family members. Here, we report an extensive European pedigree with multiple system atrophy and Parkinson`s disease suggesting a complex underlying α-synucleinopathy as confirmed on neuropathological examination. The exclusion of known genetic causes of parkinsonism or multiple system atrophy lookalikes suggests that variants in additional, still unknown genes, linked to α-synucleinopathy lesions underlie such neurodegenerative clustering.

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

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.

Mitochondrial DNA copy number (mtDNAcn) in tissues and blood can be altered in conditions like diabetes and major depression and may play a role in aging and longevity. However, little is known about the association between mtDNAcn and personality traits linked to emotional states, metabolic health, and longevity. This study tests the hypothesis that blood mtDNAcn is related to personality traits and mediates the association between personality and mortality.We assessed the big five personality domains and facets using the Revised NEO Personality Inventory (NEO-PI-R), assessed depressive symptoms with the Center for Epidemiologic Studies Depression Scale (CES-D), estimated mtDNAcn levels from whole-genome sequencing, and tracked mortality in participants from the Baltimore Longitudinal Study of Aging. Results were replicated in the SardiNIA Project.We found that mtDNAcn was negatively associated with the Neuroticism domain and its facets and positively associated with facets from the other four domains. The direction and size of the effects were replicated in the SardiNIA cohort and were robust to adjustment for potential confounders in both samples. Consistent with the Neuroticism finding, higher depressive symptoms were associated with lower mtDNAcn. Finally, mtDNAcn mediated the association between personality and mortality risk.To our knowledge, this is the first study to show a replicable association between mtDNAcn and personality. Furthermore, the results support our hypothesis that mtDNAcn is a biomarker of the biological process that explains part of the association between personality and mortality.Support for this work was provided by the Intramural Research Program of the National Institute on Aging (Z01-AG000693, Z01-AG000970, and Z01-AG000949) and the National Institute of Neurological Disorders and Stroke of the National Institutes of Health. AT was also supported by the National Institute on Aging of the National Institutes of Health Grant R01AG068093.Cells are powered by internal structures called mitochondria which have their own DNA molecules. How many copies of mitochondrial DNA blood cells contain is one aspect of mitochondrial health and is considered to provide a good indication of an individual’s ability to convert glucose into energy. Consequently, changes in the amount of mitochondrial DNA in the blood are linked to conditions like diabetes and cancer, and have also been associated with aging and mortality. A set of well-classified personality traits known as ‘the Big Five’ have also been shown to affect energy levels and the longevity of individuals. However, it remained unclear if there is a relationship between these characteristics and the number of copies of mitochondrial DNA in the blood. To investigate, Oppong et al. used a specialized test to assess the personality traits of participants from two separate cohorts: Baltimore Longitudinal Study of Ageing and the SardiNIA Project. The genomic sequence of each person was then analyzed to calculate the amount of mitochondrial DNA in their blood, and their mortality was recorded based on whether they were alive or dead multiple years later. Oppong et al. found that low levels of mitochondrial DNA were linked with high scores in neuroticism (a trait typically associated with anxiety, depression, and self-doubt). Further statistical tests revealed that mitochondrial DNA levels mediate the relationship between a person’s personality and their risk of death. These findings suggest that personality traits impact the number of mitochondrial DNA molecules in a person’s blood, which, in turn, influences how long they are likely to live. However, further work is needed to find out what causes this effect.

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.

GBA variants carriers are at increased risk of Parkinson’s disease (PD) and Lewy body dementia (LBD). The presence of pseudogene GBAP1 predisposes to structural variants, complicating genetic analysis. We present two methods to resolve recombinant alleles and other variants in GBA: Gauchian, a tool for short-read, whole-genome sequencing data analysis, and Oxford Nanopore sequencing after PCR enrichment. Both methods were concordant for 42 samples carrying a range of recombinants and GBAP1-related mutations, and Gauchian outperformed the GATK Best Practices pipeline. Applying Gauchian to sequencing of over 10,000 individuals shows that copy number variants (CNVs) spanning GBAP1 are relatively common in Africans. CNV frequencies in PD and LBD are similar to controls. Gains may coexist with other mutations in patients, and a modifying effect cannot be excluded. Gauchian detects more GBA variants in LBD than PD, especially severe ones. These findings highlight the importance of accurate GBA analysis in these patients.

GBA variants cause the autosomal recessive Gaucher disease, and carriers are at increased risk of Parkinson’s disease (PD) and Lewy body dementia (LBD). The presence of a highly homologous nearby pseudogene (GBAP1) predisposes to a range of structural variants arising from either gene conversion or reciprocal recombination, the latter resulting in copy number gains or losses, complicating genetic testing and analysis. To date, short-read sequencing has not been able to fully resolve these or other variants in the key homology region, and targeted long-read sequencing has not previously resolved reciprocal recombinants. We present and validate two independent methods to resolve recombinant alleles and other variants in GBA: Gauchian, a novel bioinformatics tool for short-read, whole-genome sequencing data analysis, and Oxford Nanopore long-read sequencing after enrichment with appropriate PCR. The methods were concordant for 42 samples including 30 with a range of recombinants and GBAP1-related mutations, and Gauchian outperforms the GATK Best Practices pipeline. Applying Gauchian to Illumina sequencing of over 10,000 individuals from publicly available cohorts shows that copy number variants (CNVs) spanning GBAP1 are relatively common in Africans. CNV frequencies in PD and LBD are similar to controls, but gains may coexist with other mutations in patients, and a modifying effect cannot be excluded. Gauchian detects a higher frequency of GBA variants in LBD than PD, especially severe ones. These findings highlight the importance of accurate GBA mutation detection in these patients, which is possible by either Gauchian analysis of short-read whole genome sequencing, or targeted long-read sequencing.

Human induced pluripotent stem cell (iPSC) lines are a powerful tool for studying development and disease, but the considerable phenotypic variation between lines makes it challenging to replicate key findings and integrate data across research groups. To address this issue, we sub-cloned candidate human iPSC lines and deeply characterized their genetic properties using whole genome sequencing, their genomic stability upon CRISPR-Cas9-based gene editing, and their phenotypic properties including differentiation to commonly used cell types. These studies identified KOLF2.1J as an all-around well-performing iPSC line. We then shared KOLF2.1J with groups around the world who tested its performance in head-to-head comparisons with their own preferred iPSC lines across a diverse range of differentiation protocols and functional assays. On the strength of these findings, we have made KOLF2.1J and its gene-edited derivative clones readily accessible to promote the standardization required for large-scale collaborative science in the stem cell field.

Rapid eye movement (REM) sleep behavior disorder (RBD), enactment of dreams during REM sleep, is an early clinical symptom of alpha-synucleinopathies. RBD also defines more severe forms of alpha-synucleinopathies. The genetic background of RBD and its underlying mechanisms are not well understood. Here, we performed the first genome-wide association study of RBD, identifying five RBD risk loci. Expression analyses highlight SNCA-AS1 and SCARB2 differential expression in different brain regions in RBD, with SNCA-AS1 further supported by colocalization analyses. Genetic risk score and other analyses provide further insights into RBD genetics, highlighting RBD as a unique subpopulation that will allow future early intervention.

Atypical parkinsonism syndromes are a heterogeneous group of neurodegenerative disorders that include corticobasal degeneration (CBD), Lewy body dementia (LBD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). The APOE e4 allele is a well-established risk factor for Alzheimer's disease; however, the role of APOE in atypical parkinsonism syndromes remains controversial. To examine the associations of APOE e4 and e2 alleles with risk of developing these syndromes, a total of 991 pathologically-confirmed atypical parkinsonism cases were genotyped using the Illumina NeuroChip array. We also performed genotyping and logistic regression analyses to examine APOE frequency and associated risk in patients with Alzheimer's disease (n = 571) and Parkinson's disease (n = 348). APOE genotypes were compared to those from neurologically healthy controls (n = 591). We demonstrate that APOE e4 and e2 carriers have a significantly increased and decreased risk, respectively, of developing Alzheimer's disease (e4: OR: 4.13, 95% CI: 3.23–5.26, p = 3.67 × 10−30; e2: OR: 0.21, 95% CI: 0.13–0.34; p = 5.39 × 10−10) and LBD (e4: OR: 2.94, 95% CI: 2.34–3.71, p = 6.60 × 10−20; e2: OR = OR: 0.39, 95% CI: 0.26–0.59; p = 6.88 × 10−6). No significant associations with risk for CBD, MSA, or PSP were observed. We also show that APOE e4 decreases survival in a dose-dependent manner in Alzheimer's disease and LBD. Taken together, this study does not provide evidence to implicate a role of APOE in the neuropathogenesis of CBD, MSA, or PSP. However, we confirm association of the APOE e4 allele with increased risk for LBD, and importantly demonstrate that APOE e2 reduces risk of this disease.

Background Increasing evidence supports an extensive and complex genetic contribution to PD. Previous genome-wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age at onset are largely unknown. Objectives To identify the genetic determinants of PD age at onset. Methods Using genetic data of 28,568 PD cases, we performed a genome-wide association study based on PD age at onset. Results We estimated that the heritability of PD age at onset attributed to common genetic variation was similar to 0.11, lower than the overall heritability of risk for PD (similar to 0.27), likely, in part, because of the subjective nature of this measure. We found two genome-wide significant association signals, one at SNCA and the other a protein-coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni-corrected significant effect at other known PD risk loci, GBA, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. Notably, SNCA, TMEM175, SCARB2, BAG3, and GBA have all been shown to be implicated in alpha-synuclein aggregation pathways. Remarkably, other well-established PD risk loci, such as GCH1 and MAPT, did not show a significant effect on age at onset of PD. Conclusions Overall, we have performed the largest age at onset of PD genome-wide association studies to date, and our results show that not all PD risk loci influence age at onset with significant differences between risk alleles for age at onset. This provides a compelling picture, both within the context of functional characterization of disease-linked genetic variability and in defining differences between risk alleles for age at onset, or frank risk for disease. (c) 2019 International Parkinson and Movement Disorder Society

BACKGROUND: Cytoplasmic inclusions of α-synuclein in brainstem neurons are characteristic of idiopathic Parkinson’ disease. Parkinson’s disease also entails α-synuclein buildup in sympathetic nerves. Among genetic forms of Parkinson’s disease the relative extents of sympathetic intra-neuronal accumulation of α-synuclein have not been reported. OBJECTIVE: This cross-sectional observational study compared magnitudes of intra-neuronal deposition of α-synuclein in common and rare genetic forms of Parkinson’s disease. METHODS: α-Synuclein deposition was quantified by the α-synuclein-tyrosine hydroxylase colocalization index in C2 cervical skin biopsies from 65 subjects. These included 30 subjects with pathogenic mutations in SNCA (N=3), PRKN (biallelic [N=7] and monoallelic [N=3]), LRRK2 (N=7), GBA (N=7), or PARK7/DJ1 (biallelic [N=1] and monoallelic [N=2]). 25 of the mutation carriers had Parkinson’s disease and 5 did not. Data were also analyzed from 19 idiopathic Parkinson’s disease patients and 16 control participants. RESULTS: α-Synuclein deposition varied as a function of genotype (F=16.7, p

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).

Human induced pluripotent stem cell (iPSC) lines are a powerful tool for studying development and disease, but the considerable phenotypic variation between lines makes it challenging to replicate key findings and integrate data across research groups. To address this issue, we sub-cloned candidate iPSC lines and deeply characterised their genetic properties using whole genome sequencing, their genomic stability upon CRISPR/Cas9-based gene editing, and their phenotypic properties including differentiation to commonly-used cell types. These studies identified KOLF2.1J as an all-around well-performing iPSC line. We then shared KOLF2.1J with groups around the world who tested its performance in head-to-head comparisons with their own preferred iPSC lines across a diverse range of differentiation protocols and functional assays. On the strength of these findings, we have made KOLF2.1J and hundreds of its gene-edited derivative clones readily accessible to promote the standardization required for large-scale collaborative science in the stem cell field.SummaryThe authors of this collaborative study deeply characterized human induced pluripotent stem cell (iPSC) lines to rationally select a clonally-derived cell line that performs well across multiple modalities. KOLF2.1J was identified as a candidate reference cell line based on single-cell analysis of its gene expression in the pluripotent state, whole genome sequencing, genomic stability after highly efficient CRISPR-mediated gene editing, integrity of the p53 pathway, and the efficiency with which it differentiated into multiple target cell populations. Since it is deeply characterized and can be readily acquired, KOLF2.1J is an attractive reference cell line for groups working with iPSCs.Graphical abstract

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.

BackgroundWhole-genome sequencing (WGS) data is available from several large studies across a variety of diseases and traits. However, massive storage and computation resources are required to use these data, and, to achieve the sufficient power for discoveries, harmonization of multiple cohorts is critical.ObjectivesThe Accelerating Medicines Partnership Parkinson’s Disease (AMP PD) program has developed a research platform for Parkinson’s disease (PD) which integrates the storage and analysis of WGS data, RNA expression data, and clinical data, harmonized across multiple cohort studies.MethodsThe version 1 release contains WGS data derived from 3,941 participants from 4 cohorts. Samples underwent joint genotyping by the TOPMed Freeze 9 Variant Calling Pipeline. We performed descriptive analyses of these WGS data using the AMP PD platform.ResultsThe clinical diagnosis of participants in version 1 release includes 2,005 idiopathic PD patients, 963 healthy controls, 64 prodromal subjects, 62 clinically diagnosed PD subjects without evidence of dopamine deficit (SWEDD) and 705 participants of genetically enriched cohorts carrying PD risk associated GBA variants or LRRK2 variants in which 304 were affected. We did not observe a significant enrichment of pathogenic variants in the idiopathic PD group, but the polygenic risk score (PRS) was higher in PD both in non-genetically enriched cohorts and genetically enriched cohorts. The population analysis showed a correlation between genetically enriched cohorts and Ashkenazi Jewish ancestry.ConclusionsWe describe the genetic component of the AMP PD platform, a solution to democratise data access and analysis for the PD research community.(d) Financial Disclosure/CoI

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.

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.

The genetic basis of variation in the rate of disease progression of primary tauopathies has not been determined. In two independent progressive supranuclear palsy cohorts, we show that common variation at the LRRK2 locus determines survival from motor symptom onset to death, possibly through regulation of gene expression. This links together genetic risk in alpha-synuclein and tau disorders, and suggests that modulation of proteostasis and neuro-inflammation by LRRK2 inhibitors may have a therapeutic role across disorders.

BackgroundAlzheimer’s disease (AD) is a common, age-related, neurodegenerative disease that impairs a person’s ability to perform day-to-day activities. Diagnosing AD is challenging, especially in the early stages. Many patients still go undiagnosed, partly due to the complex heterogeneity in disease progression. This highlights a need for early prediction of the disease course to assist its treatment and tailor therapy options to the disease progression rate. Recent developments in machine learning techniques provide the potential to not only predict disease progression and trajectory of AD but also to classify the disease into different etiological subtypes.Methods and findingsThe work shown here clusters participants in distinct and multifaceted progression subgroups of AD and discusses an approach to predict the progression rate from baseline diagnosis. We observed that the myriad of clinically reported symptoms summarized in the proposed AD progression space corresponds directly with memory and cognitive measures, which are routinely used to monitor disease onset and progression. Our analysis demonstrated accurate prediction of disease progression after four years from the first 12 months of post-diagnosis clinical data (Area Under the Curve of 0.96 (95% confidence interval (CI), 0.92-1.0), 0.81 (95% CI, 0.74-0.88) and 0.98 (95% CI, 0.96-1.0) for slow, moderate and fast progression rate patients respectively). Further, we explored the long short-term memory (LSTM) neural networks to predict the trajectory of an individual patient’s progression.ConclusionThe machine learning techniques presented in this study may assist providers in identifying different progression rates and trajectories in the early stages of the disease, hence allowing for more efficient and personalized healthcare deliveries. With additional information about the progression rate of AD at hand, providers may further individualize the treatment plans. The predictive tests discussed in this study not only allow for early AD diagnosis but also facilitate the characterization of distinct AD subtypes relating to trajectories of disease progression. These findings are a crucial step forward for early disease detection. These models can be used to design improved clinical trials for AD research.

The interplay between viral infection and Alzheimer's disease (AD) has long been an area of interest, but proving causality has been elusive. Several recent studies have renewed the debate concerning the role of herpesviruses, and human herpesvirus 6 (HHV-6) in particular, in AD. We screened for HHV-6 detection across three independent AD brain repositories using (1) RNA sequencing (RNA-seq) datasets and (2) DNA samples extracted from AD and non-AD control brains. The RNA-seq data were screened for pathogens against taxon references from over 25,000 microbes, including 118 human viruses, whereas DNA samples were probed for PCR reactivity to HHV-6A and HHV-6B. HHV-6 demonstrated little specificity to AD brains over controls by either method, whereas other viruses, such as Epstein-Barr virus (EBV) and cytomegalovirus (CMV), were detected at comparable levels. These direct methods of viral detection do not suggest an association between HHV-6 and AD.