Cornelis Blauwendraat

Discovery and functional prioritization of Parkinson's disease candidate genes from large-scale whole exome sequencing

BackgroundWhole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson’s disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models.ResultsAssuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes—GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C—also showed evidence consistent with genetic replication.ConclusionsBy integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies.

The wide genetic landscape of clinical frontotemporal dementia: systematic combined sequencing of 121 consecutive subjects

PurposeTo define the genetic spectrum and relative gene frequencies underlying clinical frontotemporal dementia (FTD).MethodsWe investigated the frequencies and mutations in neurodegenerative disease genes in 121 consecutive FTD subjects using an unbiased, combined sequencing approach, complemented by cerebrospinal fluid Aβ1-42 and serum progranulin measurements. Subjects were screened for C9orf72 repeat expansions, GRN and MAPT mutations, and, if negative, mutations in other neurodegenerative disease genes, by whole-exome sequencing (WES) (n = 108), including WES-based copy-number variant (CNV) analysis.ResultsPathogenic and likely pathogenic mutations were identified in 19% of the subjects, including mutations in C9orf72 (n = 8), GRN (n = 7, one 11-exon macro-deletion) and, more rarely, CHCHD10, TARDBP, SQSTM1 and UBQLN2 (each n = 1), but not in MAPT or TBK1. WES also unraveled pathogenic mutations in genes not commonly linked to FTD, including mutations in Alzheimer (PSEN1, PSEN2), lysosomal (CTSF, 7-exon macro-deletion) and cholesterol homeostasis pathways (CYP27A1).ConclusionOur unbiased approach reveals a wide genetic spectrum underlying clinical FTD, including 11% of seemingly sporadic FTD. It unravels several mutations and CNVs in genes and pathways hitherto not linked to FTD. This suggests that clinical FTD might be the converging downstream result of a delicate susceptibility of frontotemporal brain networks to insults in various pathways.

Increased brain expression of GPNMB is associated with genome wide significant risk for Parkinson's disease on chromosome 7p15.3

Genome wide association studies (GWAS) for Parkinson’s disease (PD) have previously revealed a significant association with a locus on chromosome 7p15.3, initially designated as the glycoprotein non-metastatic melanoma protein B (GPNMB) locus. In this study, the functional consequences of this association on expression were explored in depth by integrating different expression quantitative trait locus (eQTL) datasets (Braineac, CAGEseq, GTEx, and Phenotype-Genotype Integrator (PheGenI)). Top risk SNP rs199347 eQTLs demonstrated increased expressions of GPNMB, KLHL7, and NUPL2 with the major allele (AA) in brain, with most significant eQTLs in cortical regions, followed by putamen. In addition, decreased expression of the antisense RNA KLHL7-AS1 was observed in GTEx. Furthermore, rs199347 is an eQTL with long non-coding RNA (AC005082.12) in human tissues other than brain. Interestingly, transcript-specific eQTLs in immune-related tissues (spleen and lymphoblastoid cells) for NUPL2 and KLHL7-AS1 were observed, which suggests a complex functional role of this eQTL in specific tissues, cell types at specific time points. Significantly increased expression of GPNMB linked to rs199347 was consistent across all datasets, and taken in combination with the risk SNP being located within the GPNMB gene, these results suggest that increased expression of GPNMB is the causative link explaining the association of this locus with PD. However, other transcript eQTLs and subsequent functional roles cannot be excluded. This highlights the importance of further investigations to understand the functional interactions between the coding genes, antisense, and non-coding RNA species considering the tissue and cell-type specificity to understand the underlying biological mechanisms in PD.

C9orf72 is differentially expressed in the central nervous system and myeloid cells and consistently reduced in C9orf72, MAPT and GRN mutation carriers

A non-coding hexanucleotide repeat expansion (HRE) in C9orf72 is a common cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) acting through a loss of function mechanism due to haploinsufficiency of C9orf72 or a gain of function mediated by aggregates of bidirectionally transcribed HRE-RNAs translated into di-peptide repeat (DPR) proteins. To fully understand regulation of C9orf72 expression we surveyed the C9orf72 locus using Cap Analysis of Gene Expression sequence data (CAGEseq). We observed C9orf72 was generally lowly expressed with the exception of a subset of myeloid cells, particularly CD14+ monocytes that showed up to seven fold higher expression as compared to central nervous system (CNS) and other tissues. The expression profile at the C9orf72 locus showed a complex architecture with differential expression of the transcription start sites (TSSs) for the annotated C9orf72 transcripts between myeloid and CNS tissues suggesting cell and/or tissue specific functions. We further detected novel TSSs in both the sense and antisense strand at the C9orf72 locus and confirmed their existence in brain tissues and CD14+ monocytes. Interestingly, our experiments showed a consistent decrease of C9orf72 coding transcripts not only in brain tissue and monocytes from C9orf72-HRE patients, but also in brains from MAPT and GRN mutation carriers together with an increase in antisense transcripts suggesting these could play a role in regulation of C9orf72. We found that the non-HRE related expression changes cannot be explained by promoter methylation but by the presence of the C9orf72-HRE risk haplotype and unknown functional interactions between C9orf72, MAPT and GRN.

NeuroChip, an updated version of the NeuroX genotyping platform to rapidly screen for variants associated with neurological diseases

Genetics has proven to be a powerful approach in neurodegenerative diseases research, resulting in the identification of numerous causal and risk variants. Previously, we introduced the NeuroX Illumina genotyping array, a fast and efficient genotyping platform designed for the investigation of genetic variation in neurodegenerative diseases. Here, we present its updated version, named NeuroChip. The NeuroChip is a low-cost, custom-designed array containing a tagging variant backbone of about 306,670 variants complemented with a manually curated custom content comprised of 179,467 variants implicated in diverse neurological diseases, including Alzheimers disease, Parkinsons disease, Lewy body dementia, amyotrophic lateral sclerosis, frontotemporal dementia, progressive supranuclear palsy, corticobasal degeneration, and multiple system atrophy. The tagging backbone was chosen because of the low cost and good genome-wide resolution; the custom content can be combined with other backbones, like population or drug development arrays. Using the NeuroChip, we can accurately identify rare variants and impute over 5.3 million common SNPs from the latest release of the Haplotype Reference Consortium. In summary, we describe the design and usage of the NeuroChip array and show its capability for detecting rare pathogenic variants in numerous neurodegenerative diseases. The NeuroChip has a more comprehensive and improved content, which makes it a reliable, high-throughput, cost-effective screening tool for genetic research and molecular diagnostics in neurodegenerative diseases.

Comprehensive promoter level expression quantitative trait loci analysis of the human frontal lobe

BackgroundExpression quantitative trait loci (eQTL) analysis is a powerful method to detect correlations between gene expression and genomic variants and is widely used to interpret the biological mechanism underlying identified genome wide association studies (GWAS) risk loci. Numerous eQTL studies have been performed on different cell types and tissues of which the majority has been based on microarray technology.MethodsWe present here an eQTL analysis based on cap analysis gene expression sequencing (CAGEseq) data created from human postmortem frontal lobe tissue combined with genotypes obtained through genotyping arrays, exome sequencing, and CAGEseq. Using CAGEseq as an expression profiling technique combined with these different genotyping techniques allows measurement of the molecular effect of variants on individual transcription start sites and increases the resolution of eQTL analysis by also including the non-annotated parts of the genome.ResultsWe identified 2410 eQTLs and show that non-coding transcripts are more likely to contain an eQTL than coding transcripts, in particular antisense transcripts. We provide evidence for how previously identified GWAS loci for schizophrenia (NRGN), Parkinson’s disease, and Alzheimer’s disease (PARK16 and MAPT loci) could increase the risk for disease at a molecular level. Furthermore, we demonstrate that CAGEseq improves eQTL analysis because variants obtained from CAGEseq are highly enriched for having a functional effect and thus are an efficient method towards the identification of causal variants.ConclusionOur data contain both coding and non-coding transcripts and has the added value that we have identified eQTLs for variants directly adjacent to TSS. Future eQTL studies would benefit from combining CAGEseq with RNA sequencing for a more complete interpretation of the transcriptome and increased understanding of eQTL signals.

ADORA1 mutations are not a common cause of Parkinson's disease and dementia with Lewy bodies.

Parkinson’s disease (PD) and dementia with Lewy bodies (DLB) are 2 common neurodegenerative diseases characterized by a-synuclein inclusions (Lewy bodies) present in the midbrain (PD) or spread throughout the limbic system and neocortex (DLB). A recent study identified a homozygous missense mutation (p.G279S) in the adenosine A1 receptor gene (ADORA1) in an autosomal-recessive, early-onset, L-doparesponsive, consanguineous Iranian family with parkinsonism and cognitive decline. The authors of this study made 2 *Correspondence to: Cornelis Blauwendraat, Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke (NINDS), 35 Convent Drive, Bethesda, MD 20892-3707; cornelis.blauwendraat@nih.gov

The clinical, neuroanatomical, and neuropathologic phenotype of TBK1-associated frontotemporal dementia: A longitudinal case report

Mutations in the TANK‐binding kinase 1 (TBK1) gene have recently been shown to cause frontotemporal dementia (FTD). However, the phenotype of TBK1‐associated FTD is currently unclear.

Parkinson's disease genetics: identifying novel risk loci, providing causal insights and improving estimates of heritable risk.

We performed the largest genetic study of Parkinson9s disease to date, involving analysis of 11.4M SNPs in 37.7K cases, 18.6K 9proxy-cases9 and 1.4M controls, discovering 39 novel risk loci. In total, we identified 92 putative independent genome-wide significant signals including 53 at previously published loci. Next, we dissected risk within these loci, identifying 22 candidate independent risk variants in close proximity to one another representing multiple risk signals in one locus (20 variants proximal to known risk loci). We then employed tests of causality within a Mendelian randomization framework to infer functional genomic consequences for genes within loci of interest in concert with protein-centric network analyses to nominate likely candidates for follow-up investigation. This report also shows expression network signatures of PD loci to be heavily brain enriched and different in comparison to Alzheimer9s disease. We also used risk scoring methods to improve genetic predictions of disease risk, and show that GWAS signals explain 11-15% of the heritable risk of PD at thresholds below genome-wide significance. Additionally, these data also suggest genetic correlations relating to risk overlapping with brain morphology, smoking status and educational attainment. Further analyses of smoking initiation and cognitive performance relating to PD risk in more comprehensive datasets show complex etiological links between PD risk and these traits. These data in sum provide the most comprehensive understanding of the genetic architecture of PD to date, revealing a large number of additional loci, and demonstrating that there remains a considerable genetic component of this disease that has not yet been discovered.We performed the largest genome-wide association study of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases, and 1.4M controls. We identified 90 independent genome-wide significant signals across 78 loci, including 38 independent risk signals in 37 novel loci. These variants explained 26-36% of the heritable risk of PD. Tests of causality within a Mendelian randomization framework identified putatively causal genes for 70 risk signals. Tissue expression enrichment analysis suggested that signatures of PD loci were heavily brain-enriched, consistent with specific neuronal cell types being implicated from single cell expression data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. In sum, these data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified.

Parkinson disease age of onset GWAS: defining heritability, genetic loci and a-synuclein mechanisms

Increasing evidence supports an extensive and complex genetic contribution to Parkinson’s disease (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 of onset are largely unknown. Here we performed an age of onset GWAS based on 28,568 PD cases. We estimated that the heritability of PD age of onset due to common genetic variation was ~0.11, lower than the overall heritability of risk for PD (~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, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. In addition, we identified that GBA coding variant carriers had an earlier age of onset compared to non-carriers. Notably, SNCA, TMEM175, SCARB2, BAG3 and GBA have all been shown to either directly influence alpha-synuclein aggregation or are implicated in alpha-synuclein aggregation pathways. Remarkably, other well-established PD risk loci such as GCH1, MAPT and RAB7L1/NUCKS1 (PARK16) did not show a significant effect on age of onset of PD. While for some loci, this may be a measure of power, this is clearly not the case for the MAPT locus; thus genetic variability at this locus influences whether but not when an individual develops disease. We believe this is an important mechanistic and therapeutic distinction. Furthermore, these data support a model in which alpha-synuclein and lysosomal mechanisms impact not only PD risk but also age of disease onset and highlights that therapies that target alpha-synuclein aggregation are more likely to be disease-modifying than therapies targeting other pathways.