A glimpse of the genetics of young-onset Parkinson's disease in Central Asia

Background: Knowledge of the genetic background of many human diseases is currently lacking from genetically undiscovered regions, including Central Asia. Kazakhstan is the first Central Asian country where the genetic studies of Parkinson's disease (PD) have been emerging since it had become a member of the International Parkinson Disease Genomics Consortium. Here we report on the results of whole‐exome sequencing (WES) in 50 young‐onset PD (YOPD) cases from Kazakhstan. / Methodology: WES was performed on 50 unrelated individuals with YOPD from Kazakhstan. Exome data were screened for novel/ultra‐rare deleterious variants in known and candidate PD genes. Copy number variants and small indels were also called. / Results: Only three cases (6%) were found to be positive for known PD genes including two unrelated familial PD cases with LRRK2 p.(Arg1441Cys) and one case with a homozygous pathogenic PRKN p.(Arg84Trp) variant. Four cases had novel and ultra‐rare variants of uncertain significance in LRRK2, DNAJC13, and VPS35. Novel deleterious variants were found in candidate Mendelian PD genes including CSMD1, TNR, EIF4G1, and ATP13A3. Eight cases harbored the East Asian‐specific LRRK2 p.(Ala419Val) variant. Conclusions The low diagnostic yield in our study might imply that a significant proportion of YOPD cases in Central Asia remains unresolved. Therefore, a better understanding of the genetic architecture of PD among populations of Central Asian ancestry and the pathogenicity of numerous rare variants should be further investigated. WES is a valuable technique for large‐scale YOPD genetic studies in Central Asia

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background: Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. / Methods: We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. / Findings: Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). / Interpretation: These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. / Funding: The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Identification of sixteen novel candidate genes for late onset Parkinson’s disease

Background Parkinson’s disease (PD) is a neurodegenerative movement disorder affecting 1–5% of the general population for which neither effective cure nor early diagnostic tools are available that could tackle the pathology in the early phase. Here we report a multi-stage procedure to identify candidate genes likely involved in the etiopathogenesis of PD. Methods The study includes a discovery stage based on the analysis of whole exome data from 26 dominant late onset PD families, a validation analysis performed on 1542 independent PD patients and 706 controls from different cohorts and the assessment of polygenic variants load in the Italian cohort (394 unrelated patients and 203 controls). Results Family-based approach identified 28 disrupting variants in 26 candidate genes for PD including PARK2, PINK1, DJ-1(PARK7), LRRK2, HTRA2, FBXO7, EIF4G1, DNAJC6, DNAJC13, SNCAIP, AIMP2, CHMP1A, GIPC1, HMOX2, HSPA8, IMMT, KIF21B, KIF24, MAN2C1, RHOT2, SLC25A39, SPTBN1, TMEM175, TOMM22, TVP23A and ZSCAN21. Sixteen of them have not been associated to PD before, were expressed in mesencephalon and were involved in pathways potentially deregulated in PD. Mutation analysis in independent cohorts disclosed a significant excess of highly deleterious variants in cases (p = 0.0001), supporting their role in PD. Moreover, we demonstrated that the co-inheritance of multiple rare variants (≥ 2) in the 26 genes may predict PD occurrence in about 20% of patients, both familial and sporadic cases, with high specificity (> 93%; p = 4.4 × 10− 5). Moreover, our data highlight the fact that the genetic landmarks of late onset PD does not systematically differ between sporadic and familial forms, especially in the case of small nuclear families and underline the importance of rare variants in the genetics of sporadic PD. Furthermore, patients carrying multiple rare variants showed higher risk of manifesting dyskinesia induced by levodopa treatment. Conclusions Besides confirming the extreme genetic heterogeneity of PD, these data provide novel insights into the genetic of the disease and may be relevant for its prediction, diagnosis and treatment

Finding genetically-supported drug targets for Parkinson’s disease using Mendelian randomization of the druggable genome

Parkinson’s disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson’s disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson’s disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson’s disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson’s disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson’s disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson’s disease drug development

Measurement of compliance posttransplantation - The results of a 12-month study using electronic monitoring

Cold-water coral carbonate mounds, owing their presence mainly to the framework building coral Lophelia pertusa and the activity of associated organisms, are common along the European margin with their spatial distribution allowing them to be divided into a number of mound provinces. Variation in mound attributes are explored via a series of case studies on mound provinces that have been the most intensely investigated: Belgica, Hovland, Pelagia, Logachev and Norwegian Mounds. Morphological variation between mound provinces is discussed under the premise that mound morphology is an expression of the environmental conditions under which mounds are initiated and grow. Cold-water coral carbonate mounds can be divided into those exhibiting “inherited” morphologies (where mound morphology reflects the morphology of the colonised features) and “developed” morphology (where the mounds assume their own gross morphology mainly reflecting dominant hydrodynamic controls). Finer-scale, surface morphological features mainly reflecting biological growth forms are also discussed