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In this study, we aimed to examine the diagnostic yield achieved by applying a trio approach in exome sequencing (ES) and the interdependency between the clinical specificity in families with neurodevelopmental delay. Thirty-seven families were recruited and trio-ES as well as three criteria for estimating the clinical phenotypic specificity were suggested and applied to the underaged children. All our patients showed neurodevelopmental delay and most of them a large spectrum of congenital anomalies. Applying the pathogenicity guidelines of the American College of Medical Genetics (ACMG), likely pathogenic (29.7%) and pathogenic variants (8.1%) were found in 40,5% of our index patients. Additionally, we found four variants of uncertain significance (VUS; according to ACMG) and two genes of interest (GOI; going beyond ACMG classification) (GLRA4, NRXN2). Spastic Paraplegia 4 (SPG4) caused by a formerly known SPAST variant was diagnosed in a patient with a complex phenotype, in whom a second genetic disorder may be present. A potential pathogenic variant linked to severe intellectual disability in GLRA4 requires further investigation. No interdependency between the diagnostic yield and the clinical specificity of the phenotypes could be observed. In consequence, trio-ES should be used early in the diagnostic process, independently from the specificity of the patient., Competing Interests: Disclosure of conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest., (Copyright © 2023 Elsevier Masson SAS. All rights reserved.)

Both air pollution exposure and systemic inflammation have been linked to Parkinson's disease (PD). In the PASIDA study, 408 incident cases of PD diagnosed in 2006-2009 and their 495 population controls were interviewed and provided DNA samples. Markers of long term traffic related air pollution measures were derived from geographic information systems (GIS)-based modeling. Furthermore, we genotyped functional polymorphisms in genes encoding proinflammatory cytokines, namely rs1800629 in TNFα (tumor necrosis factor alpha) and rs16944 in IL1B (interleukin-1β). In logistic regression models, long-term exposure to NO 2 increased PD risk overall (odds ratio (OR)=1.06 per 2.94μg/m 3 increase, 95% CI=1.00-1.13). The OR for PD in individuals with high NO 2 exposure (≧75th percentile) and the AA genotype of IL1B rs16944 was 3.10 (95% CI=1.14-8.38) compared with individuals with lower NO 2 exposure (<75th percentile) and the GG genotype. The interaction term was nominally significant on the multiplicative scale (p=0.01). We did not find significant gene-environment interactions with TNF rs1800629. Our finds may provide suggestive evidence that a combination of traffic-related air pollution and genetic variation in the proinflammatory cytokine gene IL1B contribute to risk of developing PD. However, as statistical evidence was only modest in this large sample we cannot rule out that these results represent a chance finding, and additional replication efforts are warranted., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Many single nucleotide polymorphisms (SNPs) have been described as putative risk factors for melanoma. The aim of our study was to validate the most prominent genetic risk loci in an independent Greek melanoma case-control dataset and to assess their cumulative effect solely or combined with established phenotypic risk factors on individualized risk prediction. We genotyped 59 SNPs in 800 patients and 800 controls and tested their association with melanoma using logistic regression analyses. We constructed a weighted genetic risk score (GRSGWS) based on SNPs that showed genome-wide significant (GWS) association with melanoma in previous studies and assessed their impact on risk prediction. Fifteen independent SNPs from 12 loci were significantly associated with melanoma (P < 0.05). Risk score analysis yielded an odds ratio of 1.36 per standard deviation increase of the GRSGWS (P = 1.1 × 10(-7)). Individuals in the highest 20% of the GRSGWS had a 1.88-fold increase in melanoma risk compared with those in the middle quintile. By adding the GRSGWS to a phenotypic risk model, the C-statistic increased from 0.764 to 0.775 (P = 0.007). In summary, the GRSGWS is associated with melanoma risk and achieves a modest improvement in risk prediction when added to a phenotypic risk model., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

We updated a field synopsis of genetic associations of cutaneous melanoma (CM) by systematically retrieving and combining data from all studies in the field published as of August 31, 2013. Data were available from 197 studies, which included 83,343 CM cases and 187,809 controls and reported on 1,126 polymorphisms in 289 different genes. Random-effects meta-analyses of 81 eligible polymorphisms evaluated in >4 data sets confirmed 20 single-nucleotide polymorphisms across 10 loci (TYR, AFG3L1P, CDK10, MYH7B, SLC45A2, MTAP, ATM, CLPTM1L, FTO, and CASP8) that have previously been published with genome-wide significant evidence for association (P<5 × 10(-8)) with CM risk, with certain variants possibly functioning as proxies of already tagged genes. Four other loci (MITF, CCND1, MX2, and PLA2G6) were also significantly associated with 5 × 10(-8)

Our objective was to design a genotyping platform that would allow rapid genetic characterization of samples in the context of genetic mutations and risk factors associated with common neurodegenerative diseases. The platform needed to be relatively affordable, rapid to deploy, and use a common and accessible technology. Central to this project, we wanted to make the content of the platform open to any investigator without restriction. In designing this array we prioritized a number of types of genetic variability for inclusion, such as known risk alleles, disease-causing mutations, putative risk alleles, and other functionally important variants. The array was primarily designed to allow rapid screening of samples for disease-causing mutations and large population studies of risk factors. Notably, an explicit aim was to make this array widely available to facilitate data sharing across and within diseases. The resulting array, NeuroX, is a remarkably cost and time effective solution for high-quality genotyping. NeuroX comprises a backbone of standard Illumina exome content of approximately 240,000 variants, and over 24,000 custom content variants focusing on neurologic diseases. Data are generated at approximately $50-$60 per sample using a 12-sample format chip and regular Infinium infrastructure; thus, genotyping is rapid and accessible to many investigators. Here, we describe the design of NeuroX, discuss the utility of NeuroX in the analyses of rare and common risk variants, and present quality control metrics and a brief primer for the analysis of NeuroX derived data., (Published by Elsevier Inc.)

Purpose: The aim of this study was to demonstrate that modern data mining tools can be used as one step in reducing the labor necessary to produce and maintain systematic reviews., Methods: We used four continuously updated, manually curated resources that summarize MEDLINE-indexed articles in entire fields using systematic review methods (PDGene, AlzGene, and SzGene for genetic determinants of Parkinson disease, Alzheimer disease, and schizophrenia, respectively; and the Tufts Cost-Effectiveness Analysis (CEA) Registry for cost-effectiveness analyses). In each data set, we trained a classification model on citations screened up until 2009. We then evaluated the ability of the model to classify citations published in 2010 as "relevant" or "irrelevant" using human screening as the gold standard., Results: Classification models did not miss any of the 104, 65, and 179 eligible citations in PDGene, AlzGene, and SzGene, respectively, and missed only 1 of 79 in the CEA Registry (100% sensitivity for the first three and 99% for the fourth). The respective specificities were 90, 93, 90, and 73%. Had the semiautomated system been used in 2010, a human would have needed to read only 605/5,616 citations to update the PDGene registry (11%) and 555/7,298 (8%), 717/5,381 (13%), and 334/1,015 (33%) for the other three databases., Conclusion: Data mining methodologies can reduce the burden of updating systematic reviews, without missing more papers than humans.