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Veldink, J. H.

Publications and source records attributed to Veldink, J. H..

16 recordsLinked to original sources

NEK1 autophosphorylation is disrupted by amyotrophic lateral sclerosis-associated missense variants: activity biomarkers and structural insights

Rare variants in NEK1, encoding a serine/threonine kinase, are amongst the most consistently implicated genetic contributors to amyotrophic lateral sclerosis (ALS), reported in approximately 2-3% of cases. Yet, whilst recent studies have characterised the cell biological consequences of NEK1 loss-of-function, the biochemical effects of ALS-associated missense variants on kinase activity have not been directly investigated. This distinction is mechanistically important, because missense alleles encode mutant proteins rather than simply reducing protein dosage. Here, we provide the most comprehensive cell-based phosphoproteomic map of NEK1 phosphorylation to date, identifying ten recurrent phosphorylation sites across independent expression and acquisition conditions. We experimentally assign pSer14, pThr156 and pSer418 as NEK1 autophosphorylation sites using kinase-dead controls, targeted extracted ion chromatogram analysis, phosphosite mutagenesis and phosphospecific antibodies. Leveraging activation-loop pThr156 as a readout of NEK1 activity, we assessed nine ALS-associated missense variants spanning the major functional regions of the protein. Amongst catalytic-domain variants, R261C produced the most robust reduction in pThr156 autophosphorylation, R232C produced a smaller reduction, and R232H increased pThr156; the basic-region variant, A313T, also showed a smaller reduction. Structural modelling provides a mechanistic framework for understanding these variant-specific effects. Our study establishes the first activity-based framework for functional classification of NEK1 missense variants, and provides direct evidence that ALS-associated missense variants can alter NEK1 autophosphorylation through a mechanism distinct from simple haploinsufficiency. The phosphospecific antibodies, isogenic cell lines and curated phosphoproteomic datasets generated here provide a community resource for future studies of NEK1 regulation, variant interpretation and therapeutic target validation.

neuroscience↗

Computing Linkage Disequilibrium Aware Genome Embeddings using Autoencoders

MotivationThe completion of the human genome has paved the way for genome-wide association studies (GWAS), which have already succeeded in explaining certain proportions of heritability. GWAS are not optimally suited to detect potential non-linear effects in disease risk, possibly hidden in non-additive interactions (epistasis). Alternative methods for epistasis detection using e.g. deep neural networks are currently under active development. Despite their promise to scale to high-dimensional data, deep neural networks (DNNs) are constrained by finite computational resources, which can be rapidly depleted due to increasing complexity with the sheer size of the genome. Besides, the curse of dimensionality complicates the task of capturing meaningful genetic patterns for DNNs; therefore calls for precaution in the form of dimensionality reduction. ResultsWe propose a method to compress genotyping data, involving single nucleotide polymorphisms (SNPs), while leveraging the LD structure in the genome and preserving non-linear relations among variants. This method involves clustering correlated SNPs into haplotype blocks and training per-block autoencoders that are able to learn a compressed representation of the blocks relevant genetic content. We provide an adjustable autoencoder design to accommodate diverse blocks and to bypass extensive hyperparameter tuning. We applied this method to genotyping data from Project MinE which involves a total of 23,209 ALS cases and 90,249 healthy controls. We compressed the haplotype blocks of an entire chromosome using our autoencoder-based approach, and show that this leads to more than 99% average test reconstruction accuracy - i.e. minimal information loss - while compressing the input to nearly 10% of the original size. We demonstrate that haplotype-block based autoencoders outperform their linear alternative Principal Component Analysis (PCA) by approximately 3% chromosome-wide accuracy of reconstructed variants. To the extent of our knowledge, our approach is the first to simultaneously leverage genome haplotype structure and deep neural networks for dimensionality reduction of genetic data. Availability and ImplementationData used in this study are available for academic use through the Project MinE Consortium at https://www.projectmine.com/research/data-sharing/. Data accessibility is contingent upon any terms or requirements specified by the source studies. Codes for data compression are available at https://github.com/gizem-tas/haploblock-autoencoders.

genomics↗

Molecular dynamics analysis of Superoxide Dismutase 1 mutations suggests decoupling between mechanisms underlying ALS onset and progression

Mutations in the superoxide dismutase 1 (SOD1) gene are the second most common known cause of ALS. SOD1 variants express high phenotypic variability and over 200 have been reported in people with ALS. Investigating how different SOD1 variants affect the protein dynamics might help in understanding their pathogenic mechanism and explaining their heterogeneous clinical presentation. It was previously proposed that variants can be broadly classified in two groups, wild-type like (WTL) and metal binding region (MBR) variants, based on their structural location and biophysical properties. MBR variants are associated with a loss of SOD1 enzymatic activity. In this study we used molecular dynamics and large clinical datasets to characterise the differences in the structural and dynamic behaviour of WTL and MBR variants with respect to the wild-type SOD1, and how such differences influence the ALS clinical phenotype. Our study identified marked structural differences, some of which are observed in both variant groups, while others are group specific. Moreover, applying graph theory to a network representation of the proteins, we identified differences in the intramolecular contacts of the two classes of variants. Finally, collecting clinical data of approximately 500 SOD1 ALS patients carrying variants from both classes, we showed that the survival time of patients carrying an MBR variant is generally longer (~6 years median difference, p < 0.001) with respect to patients with a WTL variant. In conclusion, our study highlights key differences in the dynamic behaviour of the WTL and MBR SOD1 variants, and wild-type SOD1 at an atomic and molecular level. We identified interesting structural features that could be further investigated to explain the associated phenotypic variability. Our results support the hypothesis of a decoupling between mechanisms of onset and progression of SOD1 ALS, and an involvement of loss-of-function of SOD1 with the disease progression.

neuroscience↗

C21orf2 mutations found in ALS disrupt primary cilia function

Amyotrophic lateral sclerosis (ALS) is a devastating progressive neurodegenerative disease that affects 1 in 400 people. Almost 40 genes have been associated with ALS, currently explaining about 15% of the ALS risk. These genes tend to cluster in certain disease pathways such as protein quality control, RNA metabolism and axonal function. Despite these advances, adequate treatments for ALS patients are still missing. In this study, we investigate the role of a newly discovered ALS gene, C21orf2, in ALS pathology. We show that C21orf2 is localized to the basal body of the primary cilium and plays an important role in ciliogenesis in vitro and in vivo. Knock down of C21orf2 also lowers cilia frequency and length in human iPSC-derived spinal motor neurons (sMNs). Furthermore, we show that intraflagellar transport is impaired, causing primary cilia to fail in transducing extracellular signals essential in the sonic hedgehog pathway. ALS-associated mutations in C21orf2 lead to loss of binding to centrosomal proteins, loss of proper localization at the basal body and hereby prevent C21orf2 from carrying out its normal function in cilia by loss-of-function. Finally, we confirm that sMNs derived from iPSCs from ALS patients with C21orf2 mutations display similar cilia dysfunction and have disturbed sonic hedgehog signaling. Collectively, our data reveal impaired cilia homeostasis as a novel disease mechanism at play in ALS, opening new avenues for further research.

neuroscience↗

Non-Coding Genetic Analysis Implicates Interleukin 18 Receptor Accessory Protein 3'UTR in Amyotrophic Lateral Sclerosis

The non-coding genome is substantially larger than the protein-coding genome but is largely unexplored by genetic association studies. Here, we performed region-based burden analysis of >25,000 variants in untranslated regions of 6,139 amyotrophic lateral sclerosis (ALS) whole-genomes and 70,403 non-ALS controls. We identified Interleukin-18 Receptor Accessory Protein (IL18RAP) 3'UTR variants significantly enriched in non-ALS genomes, replicated in an independent cohort, and associated with a five-fold reduced risk of developing ALS. Variant IL18RAP 3'UTR reduces mRNA stability and the binding of RNA-binding proteins. Variant IL18RAP 3'UTR further dampens neurotoxicity of human iPSC-derived C9orf72-ALS microglia that depends on NF-{kappa}B signaling. Therefore, the variant IL18RAP 3'UTR provides survival advantage for motor neurons co-cultured with C9-ALS microglia. The study reveals direct genetic evidence and therapeutic targets for neuro-inflammation, and emphasizes the importance of non-coding genetic association studies. One Sentence SummaryNon-coding genetic variants in IL-18 receptor 3UTR decrease ALS risk by modifying IL-18-NF-{kappa}B signaling in microglia.

neuroscience↗

Dutch population structure across space, time and GWAS design

We studied fine-grained population genetic structure and demographic change across the Netherlands using genome-wide single nucleotide polymorphism data (1,626 individuals) with associated geography (1,422 individuals). We applied ChromoPainter/fineSTRUCTURE, identifying 40 haplotypic clusters exhibiting strong north/south variation and fine-scale differentiation within provinces. Clustering is tied to country-wide ancestry gradients from neighbouring lands and to locally restricted gene flow across major Dutch rivers. Despite superexponential population growth, north-south structure is temporally stable, with west-east differentiation more transient, potentially influenced by migrations during the middle ages. Within Dutch and international data, GWAS incorporating fine-grained haplotypic covariates are less confounded than standard methods.

genetics↗

ExpansionHunter Denovo: A computational method for locating known and novel repeat expansions in short-read sequencing data

Expansions of short tandem repeats are responsible for over 40 monogenic disorders, and undoubtedly many more pathogenic repeat expansions (REs) remain to be discovered. Existing methods for detecting REs in short-read sequencing data require predefined repeat catalogs. However recent discoveries have emphasized the need for detection methods that do not require candidate repeats to be specified in advance. To address this need, we introduce ExpansionHunter Denovo, an efficient catalog-free method for genome-wide detection of REs. Analysis of real and simulated data shows that our method can identify large expansions of 41 out of 44 pathogenic repeats, including nine recently reported non-reference REs not discoverable via existing methods. ExpansionHunter Denovo is freely available at https://github.com/Illumina/ExpansionHunterDenovo

bioinformatics↗

Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference

DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identified 818 genes that influence DNA methylation patterns in blood using large-scale population genomics data. By employing genetic instruments as causal anchors, we identified directed associations between gene expression and distant DNA methylation levels, whilst ensuring specificity of the associations by correcting for linkage disequilibrium and pleiotropy among neighboring genes. We found that DNA methylation patterns are commonly shaped by transcription factors that consistently increase or decrease DNA methylation levels. However, we also observed genes encoding proteins without DNA binding activity with widespread effects on DNA methylation (e.g. NFKBIE, CDCA7(L) and NLRC5) and we suggest plausible mechanisms underlying these findings. Many of the reported genes were unknown to influence DNA methylation, resulting in a comprehensive resource providing insights in the principles underlying epigenetic regulation.

genomics↗

ExpansionHunter: A sequence-graph based tool to analyze variation in short tandem repeat regions

We describe a novel computational method for genotyping repeats using sequence graphs. This method addresses the long-standing need to accurately genotype medically important loci containing repeats adjacent to other variants or imperfect DNA repeats such as polyalanine repeats. Here we introduce a new version of our repeat genotyping software, ExpansionHunter, that uses this method to perform targeted genotyping of a broad class of such loci.\n\nAvailability and implementationExpansionHunter is implemented in C++ and is available under the Apache License Version 2.0. The source code, documentation, and Linux/macOS binaries are available at https://github.com/Illumina/ExpansionHunter/.\n\nContactmeberle@illumina.com

bioinformatics↗

Partitioning the genetic architecture of amyotrophic lateral sclerosis

The genetic basis of sporadic amyotrophic lateral sclerosis (ALS) is not well understood. Using large genome-wide association studies and validated tools to quantify genetic overlap, we systematically identified single nucleotide polymorphisms (SNPs) associated with ALS conditional on genetic data from 65 different traits and diseases from >3 million people. We found strong genetic enrichment between ALS and a number of disparate traits including frontotemporal dementia, coronary artery disease, C-reactive protein, celiac disease and memory function. Beyond C9ORF72, we detected novel genetic signal within numerous loci including GIPC1, ELMO1 and COL16A and confirmed previously reported variants, such as ATXN2, KIF5A, UNC13A and MOBP. We found that ALS variants form a small-world co-expression network characterized by highly inter-connected hub genes. This network clustered into smaller sub-networks, each associated with a unique function. Altered gene expression of several sub-networks and hubs was over-represented in neuropathological samples from ALS patients and SOD1 G93A mice. Our collective findings indicate that the genetic architecture of ALS can be partitioned into distinct components where some genes are highly important for developing disease. These findings have implications for stratification and enrichment strategies for ALS clinical trials.

genetics↗

Joint sequencing of human and pathogen genomes reveals the genetics of pneumococcal meningitis

Streptococcus pneumoniae is a common nasopharyngeal colonizer, but can also cause life-threatening invasive diseases such as empyema, bacteremia and meningitis. Genetic variation of host and pathogen is known to play a role in invasive pneumococcal disease, though to what extent is unknown. In a genome-wide association study of human and pathogen we show that human variation explains almost half of variation in susceptibility to pneumococcal meningitis and one-third of variation in severity, and identified variants in CCDC33 associated with susceptibility. Pneumococcal variation explained a large amount of invasive potential, but serotype explained only half of this variation. Newly developed methods identified pneumococcal genes involved in invasiveness including pspC and zmpD, and allowed a human-bacteria interaction analysis, finding associations between pneumococcal lineage and STK32C.

genomics↗

Genome-wide identification of directed gene networks using large-scale population genomics data

Identification of causal drivers behind regulatory gene networks is crucial in understanding gene function. We developed a method for the large-scale inference of gene-gene interactions in observational population genomics data that are both directed (using local genetic instruments as causal anchors, akin to Mendelian Randomization) and specific (by controlling for linkage disequilibrium and pleiotropy). The analysis of genotype and whole-blood RNA-sequencing data from 3,072 individuals identified 49 genes as drivers of downstream transcriptional changes (P < 7 x 10-10), among which transcription factors were overrepresented (P = 3.3 x 10-7). Our analysis suggests new gene functions and targets including for SENP7 (zinc-finger genes involved in retroviral repression) and BCL2A1 (novel target genes possibly involved in auditory dysfunction). Our work highlights the utility of population genomics data in deriving directed gene expression networks. A resource of trans-effects for all 6,600 genes with a genetic instrument can be explored individually using a web-based browser.

genomics↗

Immune-related genetic enrichment in frontotemporal dementia

BackgroundConverging evidence suggests that immune-mediated dysfunction plays an important role in the pathogenesis of frontotemporal dementia (FTD). Although genetic studies have shown that immune-associated loci are associated with increased FTD risk, a systematic investigation of genetic overlap between immune-mediated diseases and the spectrum of FTD-related disorders has not been performed.\n\nMethods and findingsUsing large genome-wide association studies (GWAS) (total n = 192,886 cases and controls) and recently developed tools to quantify genetic overlap/pleiotropy, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with FTD-related disorders namely FTD, corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), and amyotrophic lateral sclerosis (ALS) - and one or more immune-mediated diseases including Crohns disease (CD), ulcerative colitis (UC), rheumatoid arthritis (RA), type 1 diabetes (T1D), celiac disease (CeD), and psoriasis (PSOR). We found up to 270-fold genetic enrichment between FTD and RA and comparable enrichment between FTD and UC, T1D, and CeD. In contrast, we found only modest genetic enrichment between any of the immune-mediated diseases and CBD, PSP or ALS. At a conjunction false discovery rate (FDR) < 0.05, we identified numerous FTD-immune pleiotropic SNPs within the human leukocyte antigen (HLA) region on chromosome 6. By leveraging the immune diseases, we also found novel FTD susceptibility loci within LRRK2 (Leucine Rich Repeat Kinase 2), TBKBP1 (TANK-binding kinase 1 Binding Protein 1), and PGBD5 (PiggyBac Transposable Element Derived 5). Functionally, we found that expression of FTD-immune pleiotropic genes (particularly within the HLA region) is altered in postmortem brain tissue from patients with frontotemporal dementia and is enriched in microglia compared to other central nervous system (CNS) cell types.\n\nConclusionsWe show considerable immune-mediated genetic enrichment specifically in FTD, particularly within the HLA region. Our genetic results suggest that for a subset of patients, immune dysfunction may contribute to risk for FTD. These findings have potential implications for clinical trials targeting immune dysfunction in patients with FTD.

genetics↗

Project MinE: study design and pilot analyses of a large-scale whole-genome sequencing study in amyotrophic lateral sclerosis

The most recent genome-wide association study in amyotrophic lateral sclerosis (ALS) demonstrates a disproportionate contribution from low-frequency variants to genetic susceptibility of disease. We have therefore begun Project MinE, an international collaboration that seeks to analyse whole-genome sequence data of at least 15,000 ALS patients and 7,500 controls. Here, we report on the design of Project MinE and pilot analyses of newly whole-genome sequenced 1,264 ALS patients and 611 controls drawn from the Netherlands. As has become characteristic of sequencing studies, we find an abundance of rare genetic variation (minor allele frequency < 0.1 %), the vast majority of which is absent in public data sets. Principal component analysis reveals local geographical clustering of these variants within The Netherlands. We use the whole-genome sequence data to explore the implications of poor geographical matching of cases and controls in a sequence-based disease study and to investigate how ancestry-matched, externally sequenced controls can induce false positive associations. Also, we have publicly released genome-wide minor allele counts in cases and controls, as well as results from genic burden tests.

genetics↗

Comprehensive Pathway Analyses Of Schizophrenia Risk Loci Point To Dysfunctional Postsynaptic Signaling

Large-scale genome-wide association studies (GWAS) have implicated many low-penetrance loci in schizophrenia. However, its pathological mechanisms are poorly understood, which in turn hampers the development of novel pharmacological treatments. Pathway and gene set analyses carry the potential to generate hypotheses about disease mechanisms and have provided biological context to genome-wide data of schizophrenia. We aimed to examine which biological processes are likely candidates to underlie schizophrenia by integrating novel and powerful pathway analysis tools using data from the largest Psychiatric Genomics Consortium schizophrenia GWAS (N = 79 845) and the most recent 2018 schizophrenia GWAS (N = 105 318). By applying a primary unbiased analysis (Multi-marker Analysis of GenoMic Annotation; MAGMA) to weigh the role of biological processes from the MSigDB database, we identified enrichment of common variants in synaptic plasticity and neuron differentiation gene sets. We supported these findings using MAGMA, Meta-Analysis Gene-set Enrichment of variaNT Associations (MAGENTA) and Interval Enrichment Analysis (INRICH) on detailed synaptic signaling pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and found enrichment in mainly the dopaminergic and cholinergic synapses. Moreover, shared genes involved in these neurotransmitter systems had a large contribution to the observed enrichment, protein products of top genes in these pathways showed more direct and indirect interactions than expected by chance, and expression profiles of these genes were largely similar among brain tissues. In conclusion, we provide strong and consistent genetics and protein-interaction informed evidence for the role of postsynaptic signaling processes in schizophrenia, opening avenues for future translational and psychopharmacological studies.

genetics↗

Detection of long repeat expansions from PCR-free whole-genome sequence data

Identifying large repeat expansions such as those that cause amyotrophic lateral sclerosis (ALS) and Fragile X syndrome is challenging for short-read (100-150 bp) whole genome sequencing (WGS) data. A solution to this problem is an important step towards integrating WGS into precision medicine. We have developed a software tool called ExpansionHunter that, using PCR-free WGS short-read data, can genotype repeats at the locus of interest, even if the expanded repeat is larger than the read length. We applied our algorithm to WGS data from 3,001 ALS patients who have been tested for the presence of the C9orf72 repeat expansion with repeat-primed PCR (RP-PCR). Taking the RP-PCR calls as the ground truth, our WGS-based method identified pathogenic repeat expansions with 98.1% sensitivity and 99.7% specificity. Further inspection identified that all 11 conflicts were resolved as errors in the original RP-PCR results. Compared against this updated result, ExpansionHunter correctly classified all (212/212) of the expanded samples as either expansions (208) or potential expansions (4). Additionally, 99.9% (2,786/2,789) of the wild type samples were correctly classified as wild type by this method with the remaining two identified as possible expansions. We further applied our algorithm to a set of 144 samples where every sample had one of eight different pathogenic repeat expansions including examples associated with fragile X syndrome, Friedreichs ataxia and Huntingtons disease and correctly flagged all of the known repeat expansions. Finally, we tested the accuracy of our method for short repeats by comparing our genotypes with results from 860 samples sized using fragment length analysis and determined that our calls were >95% accurate. ExpansionHunter can be used to accurately detect known pathogenic repeat expansions and provides researchers with a tool that can be used to identify new pathogenic repeat expansions.

bioinformatics↗