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Parkinson's disease is the second most common neurodegenerative disease and its prevalence has been projected to double over the next 30 years. An accurate diagnosis of Parkinson's disease remains challenging and the characterisation of the earliest stages of the disease is ongoing. Recent developments over the past 5 years include the validation of 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 risk of Parkinson's disease. Substantial progress has been made in the development of diagnostic biomarkers, and genetic and imaging tests are already part of routine 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, for which earlier identification is possible, different subtypes with diverse prognosis are recognised, and novel disease-modifying treatments are in development.

Calling structural variations (SVs) is technically challenging, but using long reads remains the most accurate way to identify complex genomic alterations. Here we present Sniffles2, which improves over current methods by implementing a repeat aware clustering coupled with a fast consensus sequence and coverage-adaptive filtering. Sniffles2 is 11.8 times faster and 29% more accurate than state-of-the-art SV callers across different coverages (5–50×), sequencing technologies (ONT and HiFi) and SV types. Furthermore, Sniffles2 solves the problem of family-level to population-level SV calling to produce fully genotyped VCF files. Across 11 probands, we accurately identified causative SVs around MECP2 , including highly complex alleles with three overlapping SVs. Sniffles2 also enables the detection of mosaic SVs in bulk long-read data. As a result, we identified multiple mosaic SVs in brain tissue from a patient with multiple system atrophy. The identified SV showed a remarkable diversity within the cingulate cortex, impacting both genes involved in neuron function and repetitive elements. Sniffles2 detects mosaic structural variation from bulk long-read sequencing data.

Long-read sequencing technologies substantially overcome the limitations of short-reads but have not been considered as a feasible replacement for population-scale projects, being a combination of too expensive, not scalable enough or too error-prone. Here we develop an efficient and scalable wet lab and computational protocol, Napu, for Oxford Nanopore Technologies long-read sequencing that seeks to address those limitations. We applied our protocol to cell lines and brain tissue samples as part of a pilot project for the National Institutes of Health Center for Alzheimer’s and Related Dementias. Using a single PromethION flow cell, we can detect single nucleotide polymorphisms with F1-score comparable to Illumina short-read sequencing. Small indel calling remains difficult within homopolymers and tandem repeats, but achieves good concordance to Illumina indel calls elsewhere. Further, we can discover structural variants with F1-score on par with state-of-the-art de novo assembly methods. Our protocol phases small and structural variants at megabase scales and produces highly accurate, haplotype-specific methylation calls. This work introduces a wet lab and computational pipeline, Napu, for small variant calling and de novo assembly of Nanopore sequencing data, which leads to comparable performances to short-read sequencing and allows for large-scale long-read sequencing projects.

Dementia with Lewy bodies is the second most common form of dementia in elderly people but has been overshadowed in the research field, partly because of similarities between dementia with Lewy bodies, Parkinson's disease, and Alzheimer's disease. So far, to our knowledge, no large-scale genetic study of dementia with Lewy bodies has been done. To better understand the genetic basis of dementia with Lewy bodies, we have done a genome-wide association study with the aim of identifying genetic risk factors for this disorder. In this two-stage genome-wide association study, we collected samples from white participants of European ancestry who had been diagnosed with dementia with Lewy bodies according to established clinical or pathological criteria. In the discovery stage (with the case cohort recruited from 22 centres in ten countries and the controls derived from two publicly available database of Genotypes and Phenotypes studies [phs000404.v1.p1 and phs000982.v1.p1] in the USA), we performed genotyping and exploited the recently established Haplotype Reference Consortium panel as the basis for imputation. Pathological samples were ascertained following autopsy in each individual brain bank, whereas clinical samples were collected after participant examination. There was no specific timeframe for collection of samples. We did association analyses in all participants with dementia with Lewy bodies, and also only in participants with pathological diagnosis. In the replication stage, we performed genotyping of significant and suggestive results from the discovery stage. Lastly, we did a meta-analysis of both stages under a fixed-effects model and used logistic regression to test for association in each stage. This study included 1743 patients with dementia with Lewy bodies (1324 with pathological diagnosis) and 4454 controls (1216 patients with dementia with Lewy bodies vs 3791 controls in the discovery stage; 527 vs 663 in the replication stage). Results confirm previously reported associations: APOE (rs429358; odds ratio [OR] 2·40, 95% CI 2·14–2·70; p=1·05 × 10−48), SNCA (rs7681440; OR 0·73, 0·66–0·81; p=6·39 × 10−10), an GBA (rs35749011; OR 2·55, 1·88–3·46; p=1·78 × 10−9). They also provide some evidence for a novel candidate locus, namely CNTN1 (rs7314908; OR 1·51, 1·27–1·79; p=2·32 × 10−6); further replication will be important. Additionally, we estimate the heritable component of dementia with Lewy bodies to be about 36%. Despite the small sample size for a genome-wide association study, and acknowledging the potential biases from ascertaining samples from multiple locations, we present the most comprehensive and well powered genetic study in dementia with Lewy bodies so far. These data show that common genetic variability has a role in the disease. The Alzheimer's Society and the Lewy Body Society.

Atypical parkinsonism syndromes, such as dementia with Lewy bodies, multiple system atrophy, progressive supranuclear palsy and corticobasal degeneration, are neurodegenerative diseases with complex clinical and pathological features. Heterogeneity in clinical presentations, possible secondary determinants as well as mimic syndromes pose a major challenge to accurately diagnose patients suffering from these devastating conditions. Over the last two decades, significant advancements in genomic technologies have provided us with increasing insights into the molecular pathogenesis of atypical parkinsonism and their intriguing relationships to related neurodegenerative diseases, fueling new hopes to incorporate molecular knowledge into our diagnostic, prognostic and therapeutic approaches towards managing these conditions. In this review article, we summarize the current understanding of genetic mechanisms implicated in atypical parkinsonism syndromes. We further highlight mimic syndromes relevant to differential considerations and possible future directions.

Amyotrophic lateral sclerosis (ALS) is a fatal and rapidly evolving neurodegenerative disease arising from the loss of glutamatergic corticospinal neurons (CSN) and cholinergic motoneurons (MN). Here, we performed comparative cross-species transcriptomics of CSN using published snRNA-seq data from the motor cortex of ALS and control postmortem tissues, and performed longitudinal RNA-seq on CSN purified from male Sod1 G86R mice. We report that CSN undergo ER stress and altered mRNA translation, and identify the transcription factor CREB3 and its regulatory network as a resilience marker of ALS, not only amongst vulnerable neuronal populations, but across all neuronal populations as well as other cell types. Using genetic and epidemiologic analyses we further identify the rare variant CREB3 R119G (rs11538707) as a positive disease modifier in ALS. Through gain of function, CREB3 R119G decreases the risk of developing ALS and the motor progression rate of ALS patients. Cross-species transcriptomics on vulnerable neuronal populations unravels the transcription factor CREB3 and its regulatory network as resilience markers of ALS. Genetics and epidemiology further identify the protective rare variant CREB3R119G.

Familial aggregation of restless legs syndrome has long been recognised, particularly in patients in whom the disorder manifests before age 40 years.4 Despite this pattern, dissection of the genetic architecture underlying restless legs syndrome has proved to be challenging because of genetic heterogeneity, decreased penetrance, and variable expression.The most successful approach so far in the search for genes associated with restless legs syndrome has been genome-wide association studies (GWASs), which at the basic level involves systematic screening of common variants across the genome in large numbers of cases and controls.1 VE Pearson, RP Allen, T Dean, CE Gamaldo, SR Lesage, CJ Earley, Cognitive deficits associated with restless legs syndrome (RLS), Sleep Med, Vol. 7, 2006, 25-30 2 S Sevim, O Dogu, H Kaleagasi, M Aral, O Metin, H Camdeviren, Correlation of anxiety and depression symptoms in patients with restless legs syndrome: a population based survey, J Neurol Neurosurg Psychiatry, Vol. 75, 2004, 226-230 3 Y Li, F Mirzaei, Prospective study of restless legs syndrome and risk of depression in women, Am J Epidemiol, Vol. 176, 2012, 279-288 4 RP Allen, CJ Earley, Defining the phenotype of the restless legs syndrome (RLS) using age-of-symptom-onset, Sleep Med, Vol. 1, 2000, 11-19 5 J Winkelmann, B Schormair, P Lichtner, Genome-wide association study of restless legs syndrome identifies common variants in three genomic regions, Nat Genet, Vol. 39, 2007, 1000-1006 6 B Schormair, D Kemlink, D Roeske, PTPRD, (protein tyrosine phosphatase receptor type delta) is associated with restless legs syndrome, Nat Genet, Vol. 40, 2008, 946-948 7 J Winkelmann, D Czamara, B Schormair, Genome-wide association study identifies novel restless legs syndrome susceptibility loci on 2p14 and 16q12.1, PLoS Genet, Vol. 7, 2011, e1002171 8 B Schormair, C Zhao, S Bell, Identification of novel risk loci for restless legs syndrome in genome-wide association studies in individuals of European ancestry: a meta-analysis, Lancet Neurol, Vol. 16, 2017, 898-907

The genetic cause of amyotrophic lateral sclerosis (ALS) is not well understood. Finland is a well suited location for a genome-wide association study of ALS because the incidence of the disease is one of the highest in the world, and because the genetic homogeneity of the Finnish population enhances the ability to detect risk loci. We aimed to identify genetic risk factors for ALS in the Finnish population. We did a genome-wide association study of Finnish patients with ALS and control individuals by use of Illumina genome-wide genotyping arrays. DNA was collected from patients who attended an ALS specialty clinic that receives referrals from neurologists throughout Finland. Control samples were from a population-based study of elderly Finnish individuals. Patients known to carry D90A alleles of the SOD1 gene (n=40) were included in the final analysis as positive controls to assess whether our genome-wide association study was able to detect an association signal at this locus. We obtained samples from 442 patients with ALS and 521 control individuals. After quality control filters were applied, 318 167 single nucleotide polymorphisms (SNPs) from 405 people with ALS and 497 control individuals were available for analysis. We identified two association peaks that exceeded genome-wide significance. One was located on chromosome 21q22 (rs13048019, p=2·58×10 −8), which corresponds to the autosomal recessive D90A allele of the SOD1 gene. The other was detected in a 232 kb block of linkage disequilibrium (rs3849942, p=9·11×10 −11) in a region of chromosome 9p that was previously identified in linkage studies of families with ALS. Within this region, we defined a 42-SNP haplotype that was associated with significantly increased risk of ALS (p=7·47×10 −33 when people with familial ALS were compared with controls, odds ratio 21·0, 95% CI 11·2–39·1) and which overlapped with an association locus recently reported for frontotemporal dementia. For the 93 patients with familial ALS, the population attributable risk for the chromosome 9p21 locus was 37·9% (95% CI 27·7–48·1) and that for D90A homozygosity was 25·5% (16·9–34·1). The chromosome 9p21 locus is a major cause of familial ALS in the Finnish population. Our data suggest the presence of a founder mutation for chromosome 9p21-linked ALS. Furthermore, the overlap with the risk haplotype recently reported for frontotemporal dementia provides further evidence of a shared genetic cause for these two neurodegenerative diseases. National Institutes of Health and National Institute on Aging, Microsoft Research, ALS Association, Helsinki University Central Hospital, Finnish Academy, Finnish Medical Society Duodecim, and Kuopio University.

The clinical manifestations of Parkinson’s disease (PD) are characterized by heterogeneity in age at onset, disease duration, rate of progression, and the constellation of motor versus non-motor features. There is an unmet need for the characterization of distinct disease subtypes as well as improved, individualized predictions of the disease course. We used unsupervised and supervised machine learning methods on comprehensive, longitudinal clinical data from the Parkinson’s Disease Progression Marker Initiative ( n  = 294 cases) to identify patient subtypes and to predict disease progression. The resulting models were validated in an independent, clinically well-characterized cohort from the Parkinson’s Disease Biomarker Program ( n  = 263 cases). Our analysis distinguished three distinct disease subtypes with highly predictable progression rates, corresponding to slow, moderate, and fast disease progression. We achieved highly accurate projections of disease progression 5 years after initial diagnosis with an average area under the curve (AUC) of 0.92 (95% CI: 0.95 ± 0.01) for the slower progressing group (PDvec1), 0.87 ± 0.03 for moderate progressors, and 0.95 ± 0.02 for the fast-progressing group (PDvec3). We identified serum neurofilament light as a significant indicator of fast disease progression among other key biomarkers of interest. We replicated these findings in an independent cohort, released the analytical code, and developed models in an open science manner. Our data-driven study provides insights to deconstruct PD heterogeneity. This approach could have immediate implications for clinical trials by improving the detection of significant clinical outcomes. We anticipate that machine learning models will improve patient counseling, clinical trial design, and ultimately individualized patient care.

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). 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. 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. 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. PSP Association, CBD Solutions, Medical Research Council (UK).