Copy number variation in familial Parkinson disease

Assessing the reproducibility of machine-learning-based biomarker discovery in Parkinson's disease

Feature selection and machine learning algorithms can be used to analyze Single Nucleotide Polymorphisms (SNPs) data and identify potential disease biomarkers. Reproducibility of identified biomarkers is critical for them to be useful for clinical research; however, genotyping platforms and selection criteria for individuals to be genotyped affect the reproducibility of identified biomarkers. To assess biomarkers reproducibility, we collected five SNPs datasets from the database of Genotypes and Phenotypes (dbGaP) and explored several data integration strategies. While combining datasets can lead to a reduction in classification accuracy, it has the potential to improve the reproducibility of potential biomarkers. We evaluated the agreement among different strategies in terms of the SNPs that were identified as potential Parkinson's disease (PD) biomarkers. Our findings indicate that, on average, 93% of the SNPs identified in a single dataset fail to be identified in other datasets. However, through dataset integration, this lack of replication is reduced to 62%. We discovered fifty SNPs that were identified at least twice, which could potentially serve as novel PD biomarkers. These SNPs are indirectly linked to PD in the literature but have not been directly associated with PD before. These findings open up new potential avenues of investigation.

Genetic landscape of Parkinson's disease and related diseases in Luxembourg

Objectives

To explore the genetic architecture of PD in the Luxembourg Parkinson's Study including cohorts of healthy people and patients with Parkinson's disease (PD) and atypical parkinsonism (AP).

Methods

809 healthy controls, 680 PD and 103 AP were genotyped using the Neurochip array. We screened and validated rare single nucleotide variants (SNVs) and copy number variants (CNVs) within seven PD-causing genes (LRRK2, SNCA, VPS35, PRKN, PARK7, PINK1 and ATP13A2). Polygenic risk scores (PRSs) were generated using the latest genome-wide association study for PD. We then estimated the role of common variants in PD risk by applying gene-set-specific PRSs.

Results

We identified 60 rare SNVs in seven PD-causing genes, nine of which were pathogenic in LRRK2, PINK1 and PRKN. Eleven rare CNVs were detected in PRKN including seven duplications and four deletions. The majority of PRKN SNVs and CNVs carriers were heterozygous and not differentially distributed between cases and controls. The PRSs were significantly associated with PD and identified specific molecular pathways related to protein metabolism and signal transduction as drivers of PD risk.

Conclusion

We performed a comprehensive genetic characterization of the deep-phenotyped individuals of the Luxembourgish Parkinson's Study. Heterozygous SNVs and CNVs in PRKN were not associated with higher PD risk. In particular, we reported novel digenic variants in PD related genes and rare LRRK2 SNVs in AP patients. Our findings will help future studies to unravel the genetic complexity of PD.

Systematic evaluation of multiple NGS platforms for structural variants detection

Structural variations (SV) are critical genome changes affecting human diseases. Although many hybridization-based methods exist, evaluating SVs through next-generation sequencing (NGS) data is still necessary for broader research exploration. Here, we comprehensively compared the performance of 16 SV callers and multiple NGS platforms using NA12878 whole genome sequencing (WGS) datasets. The results indicated that several SV callers performed well relatively, such as Manta, GRIDSS, LUMPY, TARDIS, FermiKit, and Wham. Meanwhile, all NGS platforms have a similar performance using a single software. Additionally, we found that the source of undetected SVs was mostly from long reads datasets, therefore, the more appropriate strategy for accurate SV detection will be an integration of long and shorter reads in the future. At present, in the period of NGS as a mainstream method in bioinformatics, our study would provide helpful and comprehensive guidelines for specific categories of SV research.

USP32 deubiquitinase: cellular functions, regulatory mechanisms, and potential as a cancer therapy target

An essential protein regulatory system in cells is the ubiquitin-proteasome pathway. The substrate is modified by the ubiquitin ligase system (E1-E2-E3) in this pathway, which is a dynamic protein bidirectional modification regulation system. Deubiquitinating enzymes (DUBs) are tasked with specifically hydrolyzing ubiquitin molecules from ubiquitin-linked proteins or precursor proteins and inversely regulating protein degradation, which in turn affects protein function. The ubiquitin-specific peptidase 32 (USP32) protein level is associated with cell cycle progression, proliferation, migration, invasion, and other cellular biological processes. It is an important member of the ubiquitin-specific protease family. It is thought that USP32, a unique enzyme that controls the ubiquitin process, is closely linked to the onset and progression of many cancers, including small cell lung cancer, gastric cancer, breast cancer, epithelial ovarian cancer, glioblastoma, gastrointestinal stromal tumor, acute myeloid leukemia, and pancreatic adenocarcinoma. In this review, we focus on the multiple mechanisms of USP32 in various tumor types and show that USP32 controls the stability of many distinct proteins. Therefore, USP32 is a key and promising therapeutic target for tumor therapy, which could provide important new insights and avenues for antitumor drug development. The therapeutic importance of USP32 in cancer treatment remains to be further proven. In conclusion, there are many options for the future direction of USP32 research.

varAmpliCNV: analyzing variance of amplicons to detect CNVs in targeted NGS data

MOTIVATION

Computational identification of copy number variants (CNVs) in sequencing data is a challenging task. Existing CNV-detection methods account for various sources of variation and perform different normalization strategies. However, their applicability and predictions are restricted to specific enrichment protocols. Here, we introduce a novel tool named varAmpliCNV, specifically designed for CNV-detection in amplicon-based targeted resequencing data (Haloplex™ enrichment protocol) in the absence of matched controls. VarAmpliCNV utilizes principal component analysis (PCA) and/or metric dimensional scaling (MDS) to control variances of amplicon associated read counts enabling effective detection of CNV signals.

RESULTS

Performance of VarAmpliCNV was compared against three existing methods (ConVaDING, ONCOCNV and DECoN) on data of 167 samples run with an aortic aneurysm gene panel (n = 30), including 9 positive control samples. Additionally, we validated the performance on a large deafness gene panel (n = 145) run on 138 samples, containing 4 positive controls. VarAmpliCNV achieved higher sensitivity (100%) and specificity (99.78%) in comparison to competing methods. In addition, unsupervised clustering of CNV segments and visualization plots of amplicons spanning these regions are included as a downstream strategy to filter out false positives.

AVAILABILITY AND IMPLEMENTATION

The tool is freely available through galaxy toolshed and at: https://hub.docker.com/r/cmgantwerpen/varamplicnv. Supplementary Data File S1: https://tinyurl.com/2yzswyhh; Supplementary Data File S2: https://tinyurl.com/ycyf2fb4.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Polishing copy number variant calls on exome sequencing data via deep learning

Accurate and efficient detection of copy number variants (CNVs) is of critical importance owing to their significant association with complex genetic diseases. Although algorithms that use whole-genome sequencing (WGS) data provide stable results with mostly valid statistical assumptions, copy number detection on whole-exome sequencing (WES) data shows comparatively lower accuracy. This is unfortunate as WES data are cost-efficient, compact, and relatively ubiquitous. The bottleneck is primarily due to the noncontiguous nature of the targeted capture: biases in targeted genomic hybridization, GC content, targeting probes, and sample batching during sequencing. Here, we present a novel deep learning model, DECoNT, which uses the matched WES and WGS data, and learns to correct the copy number variations reported by any off-the-shelf WES-based germline CNV caller. We train DECoNT on the 1000 Genomes Project data, and we show that we can efficiently triple the duplication call precision and double the deletion call precision of the state-of-the-art algorithms. We also show that our model consistently improves the performance independent of (1) sequencing technology, (2) exome capture kit, and (3) CNV caller. Using DECoNT as a universal exome CNV call polisher has the potential to improve the reliability of germline CNV detection on WES data sets.

Genetic and Epigenetic Constructs of Progressive Supranuclear Palsy

BACKGROUND

Progressive supranuclear palsy (PSP) is a rapidly progressive primary tauopathy characterized by vertical gaze palsy, postural instability, and mild dementia. PSP shows high clinical and pathologic heterogeneity. Although a few risk factors exist, such as advanced age and environmental toxins, the precise etiology remains largely elusive. Compelling evidence now suggests that genetic background plays a pivotal role in the pathogenetic pathways of PSP. Notably, PSP is genetically and phenotypically a complex disorder. Given the tau pathology, several studies in the past have identified microtubule-associated protein tau (MAPT) gene mutations/variations and its haplotype as the major genetic risk factor of PSP, both in the sporadic and the familial forms. Subsequently, genome-wide association studies (GWAS) also identified several novel risk variants. However, these genetic risk determinants fail to explain the pathogenetic basis of PSP and its phenotypic spectrum in majority of the cases. Some genetic variants are known to confer the risk, while others seem to act as modifier genes.

SUMMARY

Besides the complex genetic basis of PSP, the pathobiological mechanisms, differential diagnosis, and management of patients with PSP have further been complicated by genetic conditions that mimic the phenotypes of PSP. This is now becoming increasingly apparent that interactions between genetic and environmental factors significantly contribute to PSP development. Further, the effect of environmental factors seems to be mediated through epigenetic modifications.

KEY MESSAGE

Herein, we provide a comprehensive overview of the genetic and epigenetic constructs of PSP and highlight the relevance of genetic and epigenetic findings in the pathobiology of PSP.

CNV-P: a machine-learning framework for predicting high confident copy number variations

Background

Copy-number variants (CNVs) have been recognized as one of the major causes of genetic disorders. Reliable detection of CNVs from genome sequencing data has been a strong demand for disease research. However, current software for detecting CNVs has high false-positive rates, which needs further improvement.

Methods

Here, we proposed a novel and post-processing approach for CNVs prediction (CNV-P), a machine-learning framework that could efficiently remove false-positive fragments from results of CNVs detecting tools. A series of CNVs signals such as read depth (RD), split reads (SR) and read pair (RP) around the putative CNV fragments were defined as features to train a classifier.

Results

The prediction results on several real biological datasets showed that our models could accurately classify the CNVs at over 90% precision rate and 85% recall rate, which greatly improves the performance of state-of-the-art algorithms. Furthermore, our results indicate that CNV-P is robust to different sizes of CNVs and the platforms of sequencing.

Conclusions

Our framework for classifying high-confident CNVs could improve both basic research and clinical diagnosis of genetic diseases.

isoCNV: in silico optimization of copy number variant detection from targeted or exome sequencing data

Background

Accurate copy number variant (CNV) detection is especially challenging for both targeted sequencing (TS) and whole‐exome sequencing (WES) data. To maximize the performance, the parameters of the CNV calling algorithms should be optimized for each specific dataset. This requires obtaining validated CNV information using either multiplex ligation-dependent probe amplification (MLPA) or array comparative genomic hybridization (aCGH). They are gold standard but time-consuming and costly approaches.

Results

We present isoCNV which optimizes the parameters of DECoN algorithm using only NGS data. The parameter optimization process is performed using an in silico CNV validated dataset obtained from the overlapping calls of three algorithms: CNVkit, panelcn.MOPS and DECoN. We evaluated the performance of our tool and showed that increases the sensitivity in both TS and WES real datasets.

Conclusions

isoCNV provides an easy-to-use pipeline to optimize DECoN that allows the detection of analysis-ready CNV from a set of DNA alignments obtained under the same conditions. It increases the sensitivity of DECoN without the need for orthogonal methods. isoCNV is available at https://gitlab.com/sequentiateampublic/isocnv.

Potential Common Genetic Risks of Sporadic Parkinson's Disease and Amyotrophic Lateral Sclerosis in the Han Population of Mainland China

Sporadic Parkinson’s disease (sPD) and sporadic amyotrophic lateral sclerosis (sALS) are neurodegenerative diseases characterized by progressive and selective neuron death, with some genetic similarities. In order to investigate the genetic risk factors common to both sPD and sALS, we carried out a screen of risk alleles for sALS and related loci in 530 sPD patients and 530 controls from the Han population of Mainland China (HPMC). We selected 27 single-nucleotide polymorphisms in 10 candidate genes associated with sALS, and we performed allelotyping and genotyping to determine their frequencies in the study population as well as bioinformatics analysis to assess their functional significance in these diseases. The minor alleles of rs17115303 in DAB adaptor protein 1 (DAB1) gene and rs6030462 in protein tyrosine phosphatase receptor type T (PTPRT) gene were correlated with increased risk of both sPD and sALS. Polymorphisms of rs17115303 and rs6030462 were associated with alterations in transcription factor binding sites, secondary structures, long non-coding RNA interactions, and nervous system regulatory networks; these changes involved biological processes associated with neural cell development, differentiation, neurogenesis, migration, axonogenesis, cell adhesion, and metabolism of phosphate-containing compounds. Thus, variants of DAB1 gene (rs17115303) and PTPRT gene (rs6030462) are risk factors common to sPD and sALS in the HPMC. These findings provide insight into the molecular pathogenesis of both diseases and can serve as a basis for the development of targeted therapies.

Alpha-Synuclein and Lipids: The Elephant in the Room?

Since the initial identification of alpha-synuclein (α-syn) at the synapse, numerous studies demonstrated that α-syn is a key player in the etiology of Parkinson's disease (PD) and other synucleinopathies. Recent advances underline interactions between α-syn and lipids that also participate in α-syn misfolding and aggregation. In addition, increasing evidence demonstrates that α-syn plays a major role in different steps of synaptic exocytosis. Thus, we reviewed literature showing (1) the interplay among α-syn, lipids, and lipid membranes; (2) advances of α-syn synaptic functions in exocytosis. These data underscore a fundamental role of α-syn/lipid interplay that also contributes to synaptic defects in PD. The importance of lipids in PD is further highlighted by data showing the impact of α-syn on lipid metabolism, modulation of α-syn levels by lipids, as well as the identification of genetic determinants involved in lipid homeostasis associated with α-syn pathologies. While questions still remain, these recent developments open the way to new therapeutic strategies for PD and related disorders including some based on modulating synaptic functions.

Exome hits demystified: The next frontier

Severe mental illnesses such as schizophrenia and bipolar disorder have complex inheritance patterns, involving both common and rare variants. Whole exome sequencing is a promising approach to find out the rare genetic variants. We had previously reported several rare variants in multiplex families with severe mental illnesses. The current article tries to summarise the biological processes and pattern of expression of genes harbouring the aforementioned variants, linking them to known clinical manifestations through a methodical narrative review. Of the 28 genes considered for this review from 7 families with multiple affected individuals, 6 genes are implicated in various neuropsychiatric manifestations including some variations in the brain morphology assessed by magnetic resonance imaging. Another 15 genes, though associated with neuropsychiatric manifestations, did not have established brain morphological changes whereas the remaining 7 genes did not have any previously recorded neuropsychiatric manifestations at all. Wnt/b-catenin signaling pathway was associated with 6 of these genes and PI3K/AKT, calcium signaling, ERK, RhoA and notch signaling pathways had at least 2 gene associations. We present a comprehensive review of biological and clinical knowledge about the genes previously reported in multiplex families with severe mental illness. A 'disease in dish approach' can be helpful to further explore the fundamental mechanisms.

RHO to the DOCK for GDP disembarking: Structural insights into the DOCK GTPase nucleotide exchange factors

The human dedicator of cytokinesis (DOCK) family consists of 11 structurally conserved proteins that serve as atypical RHO guanine nucleotide exchange factors (RHO GEFs). These regulatory proteins act as mediators in numerous cellular cascades that promote cytoskeletal remodeling, playing roles in various crucial processes such as differentiation, migration, polarization, and axon growth in neurons. At the molecular level, DOCK DHR2 domains facilitate nucleotide dissociation from small GTPases, a process that is otherwise too slow for rapid spatiotemporal control of cellular signaling. Here, we provide an overview of the biological and structural characteristics for the various DOCK proteins and describe how they differ from other RHO GEFs and between DOCK subfamilies. The expression of the family varies depending on cell or tissue type, and they are consequently implicated in a broad range of disease phenotypes, particularly in the brain. A growing body of available structural information reveals the mechanism by which the catalytic DHR2 domain elicits nucleotide dissociation and also indicates strategies for the discovery and design of high-affinity small-molecule inhibitors. Such compounds could serve as chemical probes to interrogate the cellular function and provide starting points for drug discovery of this important class of enzymes.

Genome-Wide Analysis of Copy Number Variation in Latin American Parkinson's Disease Patients

BACKGROUND

Parkinson's disease is the second most common neurodegenerative disorder and affects people from all ethnic backgrounds, yet little is known about the genetics of Parkinson's disease in non-European populations. In addition, the overall identification of copy number variants at a genome-wide level has been understudied in Parkinson's patients. The objective of this study was to understand the genome-wide burden of copy number variants in Latinos and its association with Parkinson's disease.

METHODS

We used genome-wide genotyping data from 747 Parkinson's disease patients and 632 controls from the Latin American Research Consortium on the Genetics of Parkinson's disease.

RESULTS

Genome-wide copy number burden analysis showed that patients were significantly enriched for copy number variants overlapping known Parkinson's disease genes compared with controls (odds ratio, 3.97; 95%CI, 1.69-10.5; P = 0.018). PRKN showed the strongest copy number burden, with 20 copy number variant carriers. These patients presented an earlier age of disease onset compared with patients with other copy number variants (median age at onset, 31 vs 57 years, respectively; P = 7.46 × 10-7 ).

CONCLUSIONS

We found that although overall genome-wide copy number variant burden was not significantly different, Parkinson's disease patients were significantly enriched with copy number variants affecting known Parkinson's disease genes. We also identified that of 250 patients with early-onset disease, 5.6% carried a copy number variant on PRKN in our cohort. Our study is the first to analyze genome-wide copy number variant association in Latino Parkinson's disease patients and provides insights about this complex disease in this understudied population. © 2020 International Parkinson and Movement Disorder Society.

Assessing the relationship between monoallelic PRKN mutations and Parkinson's risk

Biallelic Parkin (PRKN) mutations cause autosomal recessive Parkinson’s disease (PD); however, the role of monoallelic PRKN mutations as a risk factor for PD remains unclear. We investigated the role of single heterozygous PRKN mutations in three large independent case-control cohorts totalling 10 858 PD cases and 8328 controls. Overall, after exclusion of biallelic carriers, single PRKN mutations were more common in PD than controls conferring a >1.5-fold increase in the risk of PD [P-value (P) = 0.035], with meta-analysis (19 574 PD cases and 468 488 controls) confirming increased risk [Odds ratio (OR) = 1.65, P = 3.69E-07]. Carriers were shown to have significantly younger ages at the onset compared with non-carriers (NeuroX: 56.4 vs. 61.4 years; exome: 38.5 vs. 43.1 years). Stratifying by mutation type, we provide preliminary evidence for a more pathogenic risk profile for single PRKN copy number variant (CNV) carriers compared with single nucleotide variant carriers. Studies that did not assess biallelic PRKN mutations or consist of predominantly early-onset cases may be biasing these estimates, and removal of these resulted in a loss of association (OR = 1.23, P = 0.614; n = 4). Importantly, when we looked for additional CNVs in 30% of PD cases with apparent monoallellic PRKN mutations, we found that 44% had biallelic mutations, suggesting that previous estimates may be influenced by cryptic biallelic mutation status. While this study supports the association of single PRKN mutations with PD, it highlights confounding effects; therefore, caution is needed when interpreting current risk estimates. Together, we demonstrate that comprehensive assessment of biallelic mutation status is essential when elucidating PD risk associated with monoallelic PRKN mutations.

A population scale analysis of rare SNCA variation in the UK Biobank

Parkinson's disease (PD) is a complex neurodegenerative disease with a variety of genetic and environmental factors contributing to disease. The SNCA gene encodes for the alpha-synuclein protein which plays a central role in PD, where aggregates of this protein are one of the pathological hallmarks of disease. Rare point mutations and copy number gains of the SNCA gene have been shown to cause autosomal dominant PD, and common DNA variants identified using Genome-Wide Association Studies (GWAS) are a moderate risk factor for PD. The UK Biobank is a large-scale population prospective study including ~500,000 individuals that has revolutionized human genetics. Here we assessed the frequency of SNCA variation in this cohort and identified 30 subjects carrying variants of interest including duplications (n = 6), deletions (n = 6) and large complex likely mosaic events (n = 18). No known pathogenic missense variants were identified. None of these subjects were reported to be a PD case, although it is possible that these individuals may develop PD at a later age, and whilst three had known prodromal features, these did not meet defined clinical criteria for being considered 'prodromal' cases. Seven of the 18 large complex carriers showed a history of blood based cancer. Overall, we identified copy number variants in the SNCA region in a large population based cohort without reported PD phenotype and symptoms. Putative mosaicism of the SNCA gene was identified, however, it is unclear whether it is associated with PD. These individuals are potential candidates for further investigation by performing SNCA RNA and protein expression studies, as well as promising clinical trial candidates to understand how duplication carriers potentially escape PD.

Performance of copy number variants detection based on whole-genome sequencing by DNBSEQ platforms

BACKGROUND

DNBSEQ™ platforms are new massively parallel sequencing (MPS) platforms that use DNA nanoball technology. Use of data generated from DNBSEQ™ platforms to detect single nucleotide variants (SNVs) and small insertions and deletions (indels) has proven to be quite effective, while the feasibility of copy number variants (CNVs) detection is unclear.

RESULTS

Here, we first benchmarked different CNV detection tools based on Illumina whole-genome sequencing (WGS) data of NA12878 and then assessed these tools in CNV detection based on DNBSEQ™ sequencing data from the same sample. When the same tool was used, the CNVs detected based on DNBSEQ™ and Illumina data were similar in quantity, length and distribution, while great differences existed within results from different tools and even based on data from a single platform. We further estimated the CNV detection power based on available CNV benchmarks of NA12878 and found similar precision and sensitivity between the DNBSEQ™ and Illumina platforms. We also found higher precision of CNVs shorter than 1 kbp based on DNBSEQ™ platforms than those based on Illumina platforms by using Pindel, DELLY and LUMPY. We carefully compared these two available benchmarks and found a large proportion of specific CNVs between them. Thus, we constructed a more complete CNV benchmark of NA12878 containing 3512 CNV regions.

CONCLUSIONS

We assessed and benchmarked CNV detections based on WGS with DNBSEQ™ platforms and provide guidelines for future studies.

Analysis of Heterozygous PRKN Variants and Copy-Number Variations in Parkinson's Disease

BACKGROUND

Biallelic PRKN mutation carriers with Parkinson's disease (PD) typically have an earlier disease onset, slow disease progression, and, often, different neuropathology compared to sporadic PD patients. However, the role of heterozygous PRKN variants in the risk of PD is controversial.

OBJECTIVES

Our aim was to examine the association between heterozygous PRKN variants, including single-nucleotide variants and copy-number variations (CNVs), and PD.

METHODS

We fully sequenced PRKN in 2809 PD patients and 3629 healthy controls, including 1965 late-onset (63.97 ± 7.79 years, 63% men) and 553 early-onset PD patients (43.33 ± 6.59 years, 68% men). PRKN was sequenced using targeted next-generation sequencing with molecular inversion probes. CNVs were identified using a combination of multiplex ligation-dependent probe amplification and ExomeDepth. To examine whether rare heterozygous single-nucleotide variants and CNVs in PRKN are associated with PD risk and onset, we used optimized sequence kernel association tests and regression models.

RESULTS

We did not find any associations between all types of PRKN variants and risk of PD. Pathogenic and likely-pathogenic heterozygous single-nucleotide variants and CNVs were less common among PD patients (1.52%) than among controls (1.8%, false discovery rate-corrected P = 0.55). No associations with age at onset and in stratified analyses were found.

CONCLUSIONS

Heterozygous single-nucleotide variants and CNVs in PRKN are not associated with PD. Molecular inversion probes allow for rapid and cost-effective detection of all types of PRKN variants, which may be useful for pretrial screening and for clinical and basic science studies targeting specifically PRKN patients. © 2020 International Parkinson and Movement Disorder Society.

Integrated sequencing and array comparative genomic hybridization in familial Parkinson disease

Objective

To determine how single nucleotide variants (SNVs) and copy number variants (CNVs) contribute to molecular diagnosis in familial Parkinson disease (PD), we integrated exome sequencing (ES) and genome-wide array-based comparative genomic hybridization (aCGH) and further probed CNV structure to reveal mutational mechanisms.

Methods

We performed ES on 110 subjects with PD and a positive family history; 99 subjects were also evaluated using genome-wide aCGH. We interrogated ES and aCGH data for pathogenic SNVs and CNVs at Mendelian PD gene loci. We confirmed SNVs via Sanger sequencing and further characterized CNVs with custom-designed high-density aCGH, droplet digital PCR, and breakpoint sequencing.

Results

Using ES, we discovered individuals with known pathogenic SNVs in GBA (p.Glu365Lys, p.Thr408Met, p.Asn409Ser, and p.Leu483Pro) and LRRK2 (p.Arg1441Gly and p.Gly2019Ser). Two subjects were each double heterozygotes for variants in GBA and LRRK2. Based on aCGH, we additionally discovered cases with an SNCA duplication and heterozygous intragenic GBA deletion. Five additional subjects harbored both SNVs (p.Asn52Metfs*29, p.Thr240Met, p.Pro437Leu, and p.Trp453*) and likely disrupting CNVs at the PRKN locus, consistent with compound heterozygosity. In nearly all cases, breakpoint sequencing revealed microhomology, a mutational signature consistent with CNV formation due to DNA replication errors.

Conclusions

Integrated ES and aCGH yielded a genetic diagnosis in 19.3% of our familial PD cohort. Our analyses highlight potential mechanisms for SNCA and PRKN CNV formation, uncover multilocus pathogenic variation, and identify novel SNVs and CNVs for further investigation as potential PD risk alleles.

The Role of Genetic Testing in the Clinical Practice and Research of Early-Onset Parkinsonian Disorders in a Hungarian Cohort: Increasing Challenge in Genetic Counselling, Improving Chances in Stratification for Clinical Trials

The genetic analysis of early-onset Parkinsonian disorder (EOPD) is part of the clinical diagnostics. Several genes have been implicated in the genetic background of Parkinsonism, which is clinically indistinguishable from idiopathic Parkinson's disease. The identification of patient's genotype could support clinical decision-making process and also track and analyse outcomes in a comprehensive fashion. The aim of our study was to analyse the genetic background of EOPD in a Hungarian cohort and to evaluate the clinical usefulness of different genetic investigations. The age of onset was between 25 and 50 years. To identify genetic alterations, multiplex ligation-dependent probe amplification (n = 142), Sanger sequencing of the most common PD-associated genes (n = 142), and next-generation sequencing (n = 54) of 127 genes which were previously associated to neurodegenerative disorders were carried out. The genetic analysis identified several heterozygous damaging substitutions in PD-associated genes (C19orf12, DNAJC6, DNAJC13, EIF4G1, LRRK2, PRKN, PINK1, PLA2G6, SYNJ1). CNVs in PRKN and SNCA genes were found in five patients. In our cohort, nine previously published genetic risk factors were detected in three genes (GBA, LRRK2, and PINK1). In nine cases, two or three coexisting pathogenic mutations and risk variants were identified. Advances of sequencing technologies make it possible to aid diagnostics of PD by widening the scope of analysis to genes which were previously linked to other neurodegenerative disorders. Our data suggested that rare damaging variants are enriched versus neutral variants, among PD patients in the Hungarian population, which raise the possibility of an oligogenic effect. Heterozygous mutations of multiple recessive genes involved in the same pathway may perturb the molecular process linked to PD pathogenesis. Comprehensive genetic assessment of individual patients can rarely reveal monogenic cause in EOPD, although it may identify the involvement of multiple PD-associated genes in the background of the disease and may facilitate the better understanding of clinically distinct phenocopies. Due to the genetic complexity of the disease, genetic counselling and management is getting more challenging. Clinical geneticist should be prepared for counselling of patients with coexisting disease-causing mutations and susceptibility factors. At the same time, genomic-based stratification has increasing importance in future clinical trials.

Copy number variations in individuals with conotruncal heart defects reveal some shared developmental pathways irrespective of 22q11.2 deletion status

Over 50% of patients with 22q11.2 deletion syndrome (DS) have a conotruncal or related cardiac defect (CTRD). We hypothesized that similar genetic variants, developmental pathways and biological functions, contribute to disease risk for CTRD in patients without a 22q11.2 deletion (ND-CTRD) and with a 22q11.2 deletion (DS-CTRD). To test this hypothesis, we performed rare CNV (rCNV)-based analyses on 630 ND-CTRD cases and 602 DS-CTRD cases with comparable cardiac lesions separately and jointly. First, we detected a collection of heart development related pathways from Gene Ontology and Mammalian Phenotype Ontology analysis. We then constructed gene regulation networks using unique genes collected from the rCNVs found in the ND-CTRD and DS-CTRD cohorts. These gene networks were clustered and their predicted functions were examined. We further investigated expression patterns of those unique genes using publicly available mouse embryo microarray expression data from single-cell embryos to fully developed hearts. By these bioinformatics approaches, we identified a commonly shared gene expression pattern in both the ND-CTRD and DS-CTRD cohorts. Computational analysis of gene functions characterized with this expression pattern revealed a collection of significantly enriched terms related to cardiovascular development. By our combined analysis of rCNVs in the ND-CTRD and DS-CTRD cohorts, a group of statistically significant shared pathways, biological functions, and gene expression patterns were identified that can be tested in future studies for their biological relevance.

USP32 regulates late endosomal transport and recycling through deubiquitylation of Rab7

The endosomal system is a highly dynamic multifunctional organelle, whose complexity is regulated in part by reversible ubiquitylation. Despite the wide-ranging influence of ubiquitin in endosomal processes, relatively few enzymes utilizing ubiquitin have been described to control endosome integrity and function. Here we reveal the deubiquitylating enzyme (DUB) ubiquitin-specific protease 32 (USP32) as a powerful player in this context. Loss of USP32 inhibits late endosome (LE) transport and recycling of LE cargos, resulting in dispersion and swelling of the late compartment. Using SILAC-based ubiquitome profiling we identify the small GTPase Rab7—the logistical centerpiece of LE biology—as a substrate of USP32. Mechanistic studies reveal that LE transport effector RILP prefers ubiquitylation-deficient Rab7, while retromer-mediated LE recycling benefits from an intact cycle of Rab7 ubiquitylation. Collectively, our observations suggest that reversible ubiquitylation helps switch Rab7 between its various functions, thereby maintaining global spatiotemporal order in the endosomal system.

Though ubiquitin is known to broadly influence endosomal trafficking, few ubiquitin-utilizing enzymes targeting endosomal regulators are known. Here, the authors find that the deubiquitylating enzyme (DUB) USP32 influences endosomal membrane dynamics by deubiquitinating Rab7.

Significantly altered peripheral blood cell DNA methylation profile as a result of immediate effect of metformin use in healthy individuals

BACKGROUND

Metformin is a widely prescribed antihyperglycemic agent that has been also associated with multiple therapeutic effects in various diseases, including several types of malignancies. There is growing evidence regarding the contribution of the epigenetic mechanisms in reaching metformin's therapeutic goals; however, the effect of metformin on human cells in vivo is not comprehensively studied. The aim of our study was to examine metformin-induced alterations of DNA methylation profiles in white blood cells of healthy volunteers, employing a longitudinal study design.

RESULTS

Twelve healthy metformin-naïve individuals where enrolled in the study. Genome-wide DNA methylation pattern was estimated at baseline, 10 h and 7 days after the start of metformin administration. The whole-genome DNA methylation analysis in total revealed 125 differentially methylated CpGs, of which 11 CpGs and their associated genes with the most consistent changes in the DNA methylation profile were selected: POFUT2, CAMKK1, EML3, KIAA1614, UPF1, MUC4, LOC727982, SIX3, ADAM8, SNORD12B, VPS8, and several differentially methylated regions as novel potential epigenetic targets of metformin. The main functions of the majority of top-ranked differentially methylated loci and their representative cell signaling pathways were linked to the well-known metformin therapy targets: regulatory processes of energy homeostasis, inflammatory responses, tumorigenesis, and neurodegenerative diseases.

CONCLUSIONS

Here we demonstrate for the first time the immediate effect of short-term metformin administration at therapeutic doses on epigenetic regulation in human white blood cells. These findings suggest the DNA methylation process as one of the mechanisms involved in the action of metformin, thereby revealing novel targets and directions of the molecular mechanisms underlying the various beneficial effects of metformin.

TRIAL REGISTRATION

EU Clinical Trials Register, 2016-001092-74. Registered 23 March 2017, https://www.clinicaltrialsregister.eu/ctr-search/trial/2016-001092-74/LV .

A comprehensive screening of copy number variability in dementia with Lewy bodies

The role of genetic variability in dementia with Lewy bodies (DLB) is now indisputable; however, data regarding copy number variation (CNV) in this disease has been lacking. Here, we used whole-genome genotyping of 1454 DLB cases and 1525 controls to assess copy number variability. We used 2 algorithms to confidently detect CNVs, performed a case-control association analysis, screened for candidate CNVs previously associated with DLB-related diseases, and performed a candidate gene approach to fully explore the data. We identified 5 CNV regions with a significant genome-wide association to DLB; 2 of these were only present in cases and absent from publicly available databases: one of the regions overlapped LAPTM4B, a known lysosomal protein, whereas the other overlapped the NME1 locus and SPAG9. We also identified DLB cases presenting rare CNVs in genes previously associated with DLB or related neurodegenerative diseases, such as SNCA, APP, and MAPT. To our knowledge, this is the first study reporting genome-wide CNVs in a large DLB cohort. These results provide preliminary evidence for the contribution of CNVs in DLB risk.

Review: Somatic mutations in neurodegeneration

Somatic mutations are postzygotic mutations which may lead to mosaicism, the presence of cells with genetic differences in an organism. Their role in cancer is well established, but detailed investigation in health and other diseases has only been recently possible. This has been empowered by the improvements of sequencing techniques, including single-cell sequencing, which can still be error-prone but is rapidly improving. Mosaicism appears relatively common in the human body, including the normal brain, probably arising in early development, but also potentially during ageing. In this review, we first discuss theoretical considerations and current evidence relevant to somatic mutations in the brain. We present a framework to explain how they may be integrated with current views on neurodegeneration, focusing mainly on sporadic late-onset neurodegenerative diseases (Parkinson's disease, Alzheimer's disease and amyotrophic lateral sclerosis). We review the relevant studies so far, with the first evidence emerging in Alzheimer's in particular. We also discuss the role of mosaicism in inherited neurodegenerative disorders, particularly somatic instability of tandem repeats. We summarize existing views and data to present a model whereby the time of origin and spatial distribution of relevant somatic mutations, combined with any additional risk factors, may partly determine the development and onset age of sporadic neurodegenerative diseases.

Copy Number Variations Detection: Unravelling the Problem in Tangible Aspects

In the midst of the important genomic variants associated to the susceptibility and resistance to complex diseases, Copy Number Variations (CNV) has emerged as a prevalent class of structural variation. Following the flood of next-generation sequencing data, numerous tools publicly available have been developed to provide computational strategies to identify CNV at improved accuracy. This review goes beyond scrutinizing the main approaches widely used for structural variants detection in general, including Split-Read, Paired-End Mapping, Read-Depth, and Assembly-based. In this paper, (1) we characterize the relevant technical details around the detection of CNV, which can affect the estimation of breakpoints and number of copies, (2) we pinpoint the most important insights related to GC-content and mappability biases, and (3) we discuss the paramount caveats in the tools evaluation process. The points brought out in this study emphasize common assumptions, a variety of possible limitations, valuable insights, and directions for desirable contributions to the state-of-the-art in CNV detection tools.

An evaluation of copy number variation detection tools for cancer using whole exome sequencing data

BACKGROUND

Recently copy number variation (CNV) has gained considerable interest as a type of genomic/genetic variation that plays an important role in disease susceptibility. Advances in sequencing technology have created an opportunity for detecting CNVs more accurately. Recently whole exome sequencing (WES) has become primary strategy for sequencing patient samples and study their genomics aberrations. However, compared to whole genome sequencing, WES introduces more biases and noise that make CNV detection very challenging. Additionally, tumors' complexity makes the detection of cancer specific CNVs even more difficult. Although many CNV detection tools have been developed since introducing NGS data, there are few tools for somatic CNV detection for WES data in cancer.

RESULTS

In this study, we evaluated the performance of the most recent and commonly used CNV detection tools for WES data in cancer to address their limitations and provide guidelines for developing new ones. We focused on the tools that have been designed or have the ability to detect cancer somatic aberrations. We compared the performance of the tools in terms of sensitivity and false discovery rate (FDR) using real data and simulated data. Comparative analysis of the results of the tools showed that there is a low consensus among the tools in calling CNVs. Using real data, tools show moderate sensitivity (~50% - ~80%), fair specificity (~70% - ~94%) and poor FDRs (~27% - ~60%). Also, using simulated data we observed that increasing the coverage more than 10× in exonic regions does not improve the detection power of the tools significantly.

CONCLUSIONS

The limited performance of the current CNV detection tools for WES data in cancer indicates the need for developing more efficient and precise CNV detection methods. Due to the complexity of tumors and high level of noise and biases in WES data, employing advanced novel segmentation, normalization and de-noising techniques that are designed specifically for cancer data is necessary. Also, CNV detection development suffers from the lack of a gold standard for performance evaluation. Finally, developing tools with user-friendly user interfaces and visualization features can enhance CNV studies for a broader range of users.

Rare copy number variants in patients with congenital conotruncal heart defects

BACKGROUND

Previous studies using different cardiac phenotypes, technologies and designs suggest a burden of large, rare or de novo copy number variants (CNVs) in subjects with congenital heart defects. We sought to identify disease-related CNVs, candidate genes, and functional pathways in a large number of cases with conotruncal and related defects that carried no known genetic syndrome.

METHODS

Cases and control samples were divided into two cohorts and genotyped to assess each subject's CNV content. Analyses were performed to ascertain differences in overall CNV prevalence and to identify enrichment of specific genes and functional pathways in conotruncal cases relative to healthy controls.

RESULTS

Only findings present in both cohorts are presented. From 973 total conotruncal cases, a burden of rare CNVs was detected in both cohorts. Candidate genes from rare CNVs found in both cohorts were identified based on their association with cardiac development or disease, and/or their reported disruption in published studies. Functional and pathway analyses revealed significant enrichment of terms involved in either heart or early embryonic development.

CONCLUSION

Our study tested one of the largest cohorts specifically with cardiac conotruncal and related defects. These results confirm and extend previous findings that CNVs contribute to disease risk for congenital heart defects in general and conotruncal defects in particular. As disease heterogeneity renders identification of single recurrent genes or loci difficult, functional pathway and gene regulation network analyses appear to be more informative. Birth Defects Research 109:271-295, 2017. © 2017 Wiley Periodicals, Inc.

Copy number variability in Parkinson's disease: assembling the puzzle through a systems biology approach

Parkinson’s disease (PD), the second most common progressive neurodegenerative disorder of aging, was long believed to be a non-genetic sporadic origin syndrome. The proof that several genetic loci are responsible for rare Mendelian forms has represented a revolutionary breakthrough, enabling to reveal molecular mechanisms underlying this debilitating still incurable condition. While single nucleotide polymorphisms (SNPs) and small indels constitute the most commonly investigated DNA variations accounting for only a limited number of PD cases, larger genomic molecular rearrangements have emerged as significant PD-causing mutations, including submicroscopic Copy Number Variations (CNVs). CNVs constitute a prevalent source of genomic variations and substantially participate in each individual’s genomic makeup and phenotypic outcome. However, the majority of genetic studies have focused their attention on single candidate-gene mutations or on common variants reaching a significant statistical level of acceptance. This gene-centric approach is insufficient to uncover the genetic background of polygenic multifactorial disorders like PD, and potentially masks rare individual CNVs that all together might contribute to disease development or progression. In this review, we will discuss literature and bioinformatic data describing the involvement of CNVs on PD pathobiology. We will analyze the most frequent copy number changes in familiar PD genes and provide a “systems biology” overview of rare individual rearrangements that could functionally act on commonly deregulated molecular pathways. Assessing the global genome-wide burden of CNVs in PD patients may reveal new disease-related molecular mechanisms, and open the window to a new possible genetic scenario in the unsolved PD puzzle.

A customized high-resolution array-comparative genomic hybridization to explore copy number variations in Parkinson's disease

Parkinson’s disease (PD), the second most common progressive neurodegenerative disorder, was long believed to be a non-genetic sporadic syndrome. Today, only a small percentage of PD cases with genetic inheritance patterns are known, often complicated by reduced penetrance and variable expressivity. The few well-characterized Mendelian genes, together with a number of risk factors, contribute to the major sporadic forms of the disease, thus delineating an intricate genetic profile at the basis of this debilitating and incurable condition. Along with single nucleotide changes, gene-dosage abnormalities and copy number variations (CNVs) have emerged as significant disease-causing mutations in PD. However, due to their size variability and to the quantitative nature of the assay, CNV genotyping is particularly challenging. For this reason, innovative high-throughput platforms and bioinformatics algorithms are increasingly replacing classical CNV detection methods. Here, we report the design strategy, development, validation and implementation of NeuroArray, a customized exon-centric high-resolution array-based comparative genomic hybridization (aCGH) tailored to detect single/multi-exon deletions and duplications in a large panel of PD-related genes. This targeted design allows for a focused evaluation of structural imbalances in clinically relevant PD genes, combining exon-level resolution with genome-wide coverage. The NeuroArray platform may offer new insights in elucidating inherited potential or de novo structural alterations in PD patients and investigating new candidate genes.

Heterozygote carriers for CNVs in PARK2 are at increased risk of Parkinson's disease

Together with point mutations, homozygous deletions or duplications in PARK2 are responsible for the majority of autosomal recessive juvenile Parkinsonism. It is debated, however, whether heterozygous carriers of these mutations are at increased risk of Parkinson's disease (PD). Our goal was to determine whether heterozygous carriers of copy number variants (CNVs) affecting exons of the PARK2 gene are at risk of PD that is greater than that of non-carriers. We searched for CNVs affecting exons of PARK2 in a sample of 105 749 genotyped Icelanders. In total, 989 carriers, including 24 diagnosed with PD, were identified. The heterozygous carriers were tested for association in a sample of 1415 PD patients and 40 474 controls ≥65 years of age. PD patients were more often heterozygous carriers of PARK2 CNVs than controls [odds ratio (OR) = 1.69, P = 0.03] and compound heterozygous PD patients for a CNV and a missense mutation were not found. Furthermore, we conducted a meta-analysis of studies reporting on case-control samples screened for heterozygous PARK2 CNVs. Ten studies were included in the final analysis, with 4538 cases and 4213 controls. The pooled OR and P-value for the published and Icelandic results showed significant association between PARK2 CNVs and risk of PD (OR = 2.11, P = 2.54 × 10(-6)). Our analysis shows that heterozygous carriers of CNVs affecting exons of PARK2 have greater risk of PD than non-carriers.

The emerging role of guanine nucleotide exchange factors in ALS and other neurodegenerative diseases

Small GTPases participate in a broad range of cellular processes such as proliferation, differentiation, and migration. The exchange of GDP for GTP resulting in the activation of these GTPases is catalyzed by a group of enzymes called guanine nucleotide exchange factors (GEFs), of which two classes: Dbl-related exchange factors and the more recently described dedicator of cytokinesis proteins family exchange factors. Increasingly, deregulation of normal GEF activity or function has been associated with a broad range of disease states, including neurodegeneration and neurodevelopmental disorders. In this review, we examine this evidence with special emphasis on the novel role of Rho guanine nucleotide exchange factor (RGNEF/p190RhoGEF) in the pathogenesis of amyotrophic lateral sclerosis. RGNEF is the first neurodegeneration-linked GEF that regulates not only RhoA GTPase activation but also functions as an RNA binding protein that directly acts with low molecular weight neurofilament mRNA 3' untranslated region to regulate its stability. This dual role for RGNEF, coupled with the increasing understanding of the key role for GEFs in modulating the GTPase function in cell survival suggests a prominent role for GEFs in mediating a critical balance between cytotoxicity and neuroprotection which, when disturbed, contributes to neuronal loss.

Copy number deletion has little impact on gene expression levels in racehorses

Copy number variations (CNVs), important genetic factors for study of human diseases, may have as large of an effect on phenotype as do single nucleotide polymorphisms. Indeed, it is widely accepted that CNVs are associated with differential disease susceptibility. However, the relationships between CNVs and gene expression have not been characterized in the horse. In this study, we investigated the effects of copy number deletion in the blood and muscle transcriptomes of Thoroughbred racing horses. We identified a total of 1,246 CNVs of deletion polymorphisms using DNA re-sequencing data from 18 Thoroughbred racing horses. To discover the tendencies between CNV status and gene expression levels, we extracted CNVs of four Thoroughbred racing horses of which RNA sequencing was available. We found that 252 pairs of CNVs and genes were associated in the four horse samples. We did not observe a clear and consistent relationship between the deletion status of CNVs and gene expression levels before and after exercise in blood and muscle. However, we found some pairs of CNVs and associated genes that indicated relationships with gene expression levels: a positive relationship with genes responsible for membrane structure or cytoskeleton and a negative relationship with genes involved in disease. This study will lead to conceptual advances in understanding the relationship between CNVs and global gene expression in the horse.

Association studies of sporadic Parkinson's disease in the genomic era

Parkinson's disease is a common age-related progressive neurodegenerative disorder. Over the last 10 years, advances have been made in our understanding of the etiology of the disease with the greatest insights perhaps coming from genetic studies, including genome-wide association approaches. These large scale studies allow the identification of genomic regions harboring common variants associated to disease risk. Since the first genome-wide association study on sporadic Parkinson's disease performed in 2005, improvements in study design, including the advent of meta-analyses, have allowed the identification of ~21 susceptibility loci. The first loci to be nominated were previously associated to familial PD (SNCA, MAPT, LRRK2) and these have been extensively replicated. For other more recently identified loci (SREBF1, SCARB2, RIT2) independent replication is still warranted. Cumulative risk estimates of associated variants suggest that more loci are still to be discovered. Additional association studies combined with deep re-sequencing of known genome-wide association study loci are necessary to identify the functional variants that drive disease risk. As each of these associated genes and variants are identified they will give insight into the biological pathways involved the etiology of Parkinson's disease. This will ultimately lead to the identification of molecules that can be used as biomarkers for diagnosis and as targets for the development of better, personalized treatment.

Low-Frequency Copy-Number Variants and General Cognitive Ability: No Evidence of Association

Although twin, family, and adoption studies have shown that general cognitive ability (GCA) is substantially heritable, GWAS has not uncovered a genetic polymorphism replicably associated with this phenotype. However, most polymorphisms used in GWAS are common SNPs. The present study explores use of a different class of genetic variant, the copy-number variant (CNV), to predict GCA in a sample of 6,199 participants, combined from two longitudinal family studies. We aggregated low-frequency (<5%) CNV calls into eight different mutational burden scores, each reflecting a different operationalization of mutational burden. We further conducted three genome-wide association scans, each of which utilized a different subset of identified low-frequency CNVs. Association signals from the burden analyses were generally small in effect size, and none were statistically significant after a careful Type I error correction was applied. No signal from the genome-wide scans significantly differed from zero at the adjusted Type I error rate. Thus, the present study provides no evidence that CNVs underlie heritable variance in GCA, though we cannot rule out the possibility of very rare or small-effect CNVs for this trait, which would require even larger samples to detect. We interpret these null results in light of recent breakthroughs that aggregate SNP effects to explain much, but not all, of the heritable variance in some quantitative traits.

Genome-wide analysis of rare copy number variations reveals PARK2 as a candidate gene for attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is a common, highly heritable neurodevelopmental disorder. Genetic loci have not yet been identified by genome-wide association studies. Rare copy number variations (CNVs), such as chromosomal deletions or duplications, have been implicated in ADHD and other neurodevelopmental disorders. To identify rare (frequency ≤1%) CNVs that increase the risk of ADHD, we performed a whole-genome CNV analysis based on 489 young ADHD patients and 1285 adult population-based controls and identified one significantly associated CNV region. In tests for a global burden of large (>500 kb) rare CNVs, we observed a nonsignificant (P=0.271) 1.126-fold enriched rate of subjects carrying at least one such CNV in the group of ADHD cases. Locus-specific tests of association were used to assess if there were more rare CNVs in cases compared with controls. Detected CNVs, which were significantly enriched in the ADHD group, were validated by quantitative (q)PCR. Findings were replicated in an independent sample of 386 young patients with ADHD and 781 young population-based healthy controls. We identified rare CNVs within the parkinson protein 2 gene (PARK2) with a significantly higher prevalence in ADHD patients than in controls (P=2.8 × 10(-4) after empirical correction for genome-wide testing). In total, the PARK2 locus (chr 6: 162 659 756-162 767 019) harboured three deletions and nine duplications in the ADHD patients and two deletions and two duplications in the controls. By qPCR analysis, we validated 11 of the 12 CNVs in ADHD patients (P=1.2 × 10(-3) after empirical correction for genome-wide testing). In the replication sample, CNVs at the PARK2 locus were found in four additional ADHD patients and one additional control (P=4.3 × 10(-2)). Our results suggest that copy number variants at the PARK2 locus contribute to the genetic susceptibility of ADHD. Mutations and CNVs in PARK2 are known to be associated with Parkinson disease.

Copy number polymorphism in plant genomes

Copy number variants (CNVs) are genomic rearrangements resulting from gains or losses of DNA segments. Typically, the term refers to rearrangements of sequences larger than 1 kb. This type of polymorphism has recently been shown to be a key contributor to intra-species genetic variation, along with single-nucleotide polymorphisms and short insertion-deletion polymorphisms. Over the last decade, a growing number of studies have highlighted the importance of copy number variation (CNV) as a factor affecting human phenotype and individual CNVs have been linked to risks for severe diseases. In plants, the exploration of the extent and role of CNV is still just beginning. Initial genomic analyses indicate that CNVs are prevalent in plants and have greatly affected plant genome evolution. Many CNV events have been observed in outcrossing and autogamous species. CNVs are usually found on all chromosomes, with CNV hotspots interspersed with regions of very low genetic variation. Although CNV is mainly associated with intergenic regions, many CNVs encompass protein-coding genes. The collected data suggest that CNV mainly affects the members of large families of functionally redundant genes. Thus, the effects of individual CNV events on phenotype are usually modest. Nevertheless, there are many cases in which CNVs for specific genes have been linked to important traits such as flowering time, plant height and resistance to biotic and abiotic stress. Recent reports suggest that CNVs may form rapidly in response to stress.

Association between early-onset Parkinson disease and 22q11.2 deletion syndrome: identification of a novel genetic form of Parkinson disease and its clinical implications

IMPORTANCE

Clinical case reports of parkinsonism co-occurring with hemizygous 22q11.2 deletions and the associated multisystem syndrome, 22q11.2 deletion syndrome (22q11.2DS), suggest that 22q11.2 deletions may lead to increased risk of early-onset Parkinson disease (PD). The frequency of PD and its neuropathological presentation remain unknown in this common genetic condition.

OBJECTIVE

To evaluate a possible association between 22q11.2 deletions and PD.

DESIGN, SETTING, AND PARTICIPANTS

An observational study of the occurrence of PD in the world's largest cohort of well-characterized adults with a molecularly confirmed diagnosis of 22q11.2DS (n = 159 [6 with postmortem tissue]; age range, 18.1-68.6 years) was conducted in Toronto, Ontario, Canada. Rare postmortem brain tissue from individuals with 22q11.2DS and a clinical history of PD was investigated for neurodegenerative changes and compared with that from individuals with no history of a movement disorder.

MAIN OUTCOMES AND MEASURES

A clinical diagnosis of PD made by a neurologist and neuropathological features of PD. RESULTS Adults with 22q11.2DS had a significantly elevated occurrence of PD compared with standard population estimates (standardized morbidity ratio = 69.7; 95% CI, 19.0-178.5). All cases showed early onset and typical PD symptom pattern, treatment response, and course. All were negative for family history of PD and known pathogenic PD-related mutations. The common use of antipsychotics in patients with 22q11.2DS to manage associated psychiatric symptoms delayed diagnosis of PD by up to 10 years. Postmortem brain tissue revealed classic loss of midbrain dopaminergic neurons in all 3 postmortem 22q11.2DS-PD cases. Typical α-synuclein-positive Lewy bodies were present in the expected distribution in 2 cases but absent in another.

CONCLUSIONS AND RELEVANCE

These findings suggest that 22q11.2 deletions represent a novel genetic risk factor for early-onset PD with variable neuropathological presentation reminiscent of LRRK2-associated PD neuropathology. Individuals with early-onset PD and classic features of 22q11.2DS should be considered for genetic testing, and those with a known 22q11.2 deletion should be monitored for the development of parkinsonian symptoms. Molecular studies of the implicated genes, including DGCR8, may help shed light on the underlying pathophysiology of PD in 22q11.2DS and idiopathic PD.

Dock protein family in brain development and neurological disease

The family of dedicator of cytokinesis (Dock), a protein family that belongs to the atypical Rho guanine nucleotide exchange factors (GEFs) for Rac and/or Cdc42 GTPases, plays pivotal roles in various processes of brain development. To date, 11 members of Docks have been identified in the mammalian system. Emerging evidence has suggested that members of the Dock family are associated with several neurodegenerative and neuropsychiatric diseases, including Alzheimer disease and autism spectrum disorders. This review summarizes recent advances on the understanding of the roles of the Dock protein family in normal and diseased processes in the nervous system. Furthermore, interacting proteins and the molecular regulation of Docks are discussed.

A PARK2 polymorphism associated with delayed neuropsychological sequelae after carbon monoxide poisoning

Background

Delayed neuropsychological sequelae (DNS) are the most severe and clinically intractable complications following acute carbon monoxide (CO) poisoning. Symptoms of DNS often resemble those of Parkinson’s disease (PD), suggesting shared neurological deficits. Furthermore, Parkinson protein 2 (PARK2) mutations are associated with PD and other neurodegenerative diseases. The association signal was detected between PARK2 and DNS after acute CO poisoning in our DNA pooling base genome-wide association study.

Methods

Two PARK2 single nucleotide polymorphisms (SNPs), rs1784594 (C/T allele) and rs1893895 (G/A allele), selected from DNA pooling base genome-wide association study, were genotyped by in 514 CO poisoning patients using polymerase chain reaction restriction fragment length polymorphisms (PCR-RFLPs). The patient group consisted of 231 patients with DNS and 283 patients with no signs of lasting neurological damage (control population).

Results

The frequency of the rs1784594 T allele was significantly lower in the DNS population (OR = 1.42, 95%CI: 1.08 − 1.87), as was the TT vs. CC genotype (OR = 1.95, 95%CI: 1.15 − 3.23) and the TT vs. CT + CC frequency (OR = 1.68, 95%CI: 1.32 − 2.49) compared to controls. Association analysis revealed a significant association between DNS and rs1784594 (P < 0.01) but not rs1893895 (P > 0.05). In female cases, the T allele frequency of rs1784594 was significantly lower in DNS patients compared to female controls (OR = 1.48, 95%CI: 1.01 − 2.17).

Conclusion

These data suggest that the allelic variant of rs1784594 is a risk factor for DNS following acute CO poisoning, especially in females. The PARK2 protein may modulate the susceptibility to DNS, underscoring the importance of examining the relationship between other PARK2 polymorphisms and clinical outcome following CO poisoning.

Next-generation sequencing in understanding complex neurological disease

Next-generation sequencing techniques have made vast quantities of data on human genomes and transcriptomes available to researchers. Huge progress has been made towards understanding the basis of many Mendelian neurological conditions, but progress has been considerably slower in complex neurological diseases (multiple sclerosis, migraine, Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and so on). The authors review current next-generation sequencing methodologies and present selected studies illustrating how these have been used to cast light on the genetic etiology of complex neurological diseases with specific focus on multiple sclerosis. The authors highlight particular pitfalls in next-generation sequencing experiments and speculate on both clinical and research applications of these sequencing platforms for complex neurological disorders in the future.

Impacts of variation in the human genome on gene regulation

Recent advances in fast and inexpensive DNA sequencing have enabled the extensive study of genomic and transcriptomic variation in humans. Human genomic variation is composed of sequence and structural changes including single-nucleotide and multinucleotide variants, short insertions or deletions (indels), larger copy number variants, and similarly sized copy neutral inversions and translocations. It is now well established that any two genomes differ extensively and that structural changes constitute a prominent source of this variation. There have also been major technological advances in RNA sequencing to globally quantify and describe diversity in transcripts. Large consortia such as the 1000 Genomes Project and the ENCODE (ENCyclopedia Of DNA Elements) Project are producing increasingly comprehensive maps outlining the regions of the human genome containing variants and functional elements, respectively. Integration of genetic variation data and extensive annotation of functional genomic elements, along with the ability to measure global transcription, allow the impacts of genetic variants on gene expression to be resolved. There are several well-established models by which genetic variants affect gene regulation depending on the type, nature, and position of the variant with respect to the affected genes. These effects can be manifested in two ways: changes to transcript sequences and isoforms by coding variants, and changes to transcript abundance by dosage or regulatory variants. Here, we review the current state of how genetic variations impact gene regulation locally and globally in the human genome.