A noise-reduction GWAS analysis implicates altered regulation of neurite outgrowth and guidance in autism

<p>Abstract</p> <p>Background</p> <p>Genome-wide Association Studies (GWAS) have proved invaluable for the identification of disease susceptibility genes. However, the prioritization of candidate genes and regions for follow-up studies often proves difficult due to false-positive associations caused by statistical noise and multiple-testing. In order to address this issue, we propose the novel GWAS noise reduction (GWAS-NR) method as a way to increase the power to detect true associations in GWAS, particularly in complex diseases such as autism.</p> <p>Methods</p> <p>GWAS-NR utilizes a linear filter to identify genomic regions demonstrating correlation among association signals in multiple datasets. We used computer simulations to assess the ability of GWAS-NR to detect association against the commonly used joint analysis and Fisher's methods. Furthermore, we applied GWAS-NR to a family-based autism GWAS of 597 families and a second existing autism GWAS of 696 families from the Autism Genetic Resource Exchange (AGRE) to arrive at a compendium of autism candidate genes. These genes were manually annotated and classified by a literature review and functional grouping in order to reveal biological pathways which might contribute to autism aetiology.</p> <p>Results</p> <p>Computer simulations indicate that GWAS-NR achieves a significantly higher classification rate for true positive association signals than either the joint analysis or Fisher's methods and that it can also achieve this when there is imperfect marker overlap across datasets or when the closest disease-related polymorphism is not directly typed. In two autism datasets, GWAS-NR analysis resulted in 1535 significant linkage disequilibrium (LD) blocks overlapping 431 unique reference sequencing (RefSeq) genes. Moreover, we identified the nearest RefSeq gene to the non-gene overlapping LD blocks, producing a final candidate set of 860 genes. Functional categorization of these implicated genes indicates that a significant proportion of them cooperate in a coherent pathway that regulates the directional protrusion of axons and dendrites to their appropriate synaptic targets.</p> <p>Conclusions</p> <p>As statistical noise is likely to particularly affect studies of complex disorders, where genetic heterogeneity or interaction between genes may confound the ability to detect association, GWAS-NR offers a powerful method for prioritizing regions for follow-up studies. Applying this method to autism datasets, GWAS-NR analysis indicates that a large subset of genes involved in the outgrowth and guidance of axons and dendrites is implicated in the aetiology of autism.</p

Targeted massively parallel sequencing of autism spectrum disorder-associated genes in a case control cohort reveals rare loss-of-function risk variants

BACKGROUND: Autism spectrum disorder (ASD) is highly heritable, yet genome-wide association studies (GWAS), copy number variation screens, and candidate gene association studies have found no single factor accounting for a large percentage of genetic risk. ASD trio exome sequencing studies have revealed genes with recurrent de novo loss-of-function variants as strong risk factors, but there are relatively few recurrently affected genes while as many as 1000 genes are predicted to play a role. As such, it is critical to identify the remaining rare and low-frequency variants contributing to ASD. METHODS: We have utilized an approach of prioritization of genes by GWAS and follow-up with massively parallel sequencing in a case-control cohort. Using a previously reported ASD noise reduction GWAS analyses, we prioritized 837 RefSeq genes for custom targeting and sequencing. We sequenced the coding regions of those genes in 2071 ASD cases and 904 controls of European white ancestry. We applied comprehensive annotation to identify single variants which could confer ASD risk and also gene-based association analysis to identify sets of rare variants associated with ASD. RESULTS: We identified a significant over-representation of rare loss-of-function variants in genes previously associated with ASD, including a de novo premature stop variant in the well-established ASD candidate gene RBFOX1. Furthermore, ASD cases were more likely to have two damaging missense variants in candidate genes than controls. Finally, gene-based rare variant association implicates genes functioning in excitatory neurotransmission and neurite outgrowth and guidance pathways including CACNAD2, KCNH7, and NRXN1. CONCLUSIONS: We find suggestive evidence that rare variants in synaptic genes are associated with ASD and that loss-of-function mutations in ASD candidate genes are a major risk factor, and we implicate damaging mutations in glutamate signaling receptors and neuronal adhesion and guidance molecules. Furthermore, the role of de novo mutations in ASD remains to be fully investigated as we identified the first reported protein-truncating variant in RBFOX1 in ASD. Overall, this work, combined with others in the field, suggests a convergence of genes and molecular pathways underlying ASD etiology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13229-015-0034-z) contains supplementary material, which is available to authorized users

Regional efforts to mitigate climate change in China: A multi-criteria assessment approach

The task of mitigating climate change is usually allocated through administrative regions in China. In order to put pressure on regions that perform poorly in mitigating climate changes and highlight regions with best-practice climate policies, this study explored a method to assess regional efforts on climate change mitigation at the sub-national level. A climate change mitigation index (CCMI) was developed with 15 objective indicators, which were divided into four categories, namely, emissions, efficiency, non-fossil energy, and climate policy. The indicators’ current level and recent development were measured for the first three categories. The index was applied to assess China’s provincial performance in climate protection based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Empirical results show that the middle Yangtze River area and southern coastal area perform better than other areas in mitigating climate change. The average performance of the northwest area in China is the worst. In addition, climate change mitigation performance has a negative linear correlation with energy self-sufficiency ratio but does not have a significant linear correlation with social development level. Therefore, regional resource endowments had better be paid much more attention in terms of mitigating climate change because regions with good resource endowments in China tend to perform poorly

A heuristic method for determining CO2 efficiency in transportation planning

Background CO2 emissions are generally considered the most important indicator to determine the global warming effects. Their evaluation in the case of a transportation infrastructure is generally not easy and could be achieved through a separate balance

Overview of systematic reviews of therapeutic ranges : methodologies and recommendations for practice

BACKGROUND: Many medicines are dosed to achieve a particular therapeutic range, and monitored using therapeutic drug monitoring (TDM). The evidence base for a therapeutic range can be evaluated using systematic reviews, to ensure it continues to reflect current indications, doses, routes and formulations, as well as updated adverse effect data. There is no consensus on the optimal methodology for systematic reviews of therapeutic ranges. METHODS: An overview of systematic reviews of therapeutic ranges was undertaken. The following databases were used: Cochrane Database of Systematic Reviews (CDSR), Database of Abstracts and Reviews of Effects (DARE) and MEDLINE. The published methodologies used when systematically reviewing the therapeutic range of a drug were analyzed. Step by step recommendations to optimize such systematic reviews are proposed. RESULTS: Ten systematic reviews that investigated the correlation between serum concentrations and clinical outcomes encompassing a variety of medicines and indications were assessed. There were significant variations in the methodologies used (including the search terms used, data extraction methods, assessment of bias, and statistical analyses undertaken). Therapeutic ranges should be population and indication specific and based on clinically relevant outcomes. Recommendations for future systematic reviews based on these findings have been developed. CONCLUSION: Evidence based therapeutic ranges have the potential to improve TDM practice. Current systematic reviews investigating therapeutic ranges have highly variable methodologies and there is no consensus of best practice when undertaking systematic reviews in this field. These recommendations meet a need not addressed by standard protocols

Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility

We analyzed genetic data of 47,429 multiple sclerosis (MS) and 68,374 control subjects and established a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 variants within the extended MHC. We used an ensemble of methods to prioritize 551 putative susceptibility genes that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we observed enrichment for MS genes in these brain-resident immune cells, suggesting that these may have a role in targeting an autoimmune process to the central nervous system, although MS is most likely initially triggered by perturbation of peripheral immune responses

REPORT Whole-Exome Sequencing Links a Variant in DHDDS to Retinitis Pigmentosa

Increasingly, mutations in genes causing Mendelian disease will be supported by individual and small families only; however, exome sequencing studies have thus far focused on syndromic phenotypes characterized by low locus heterogeneity. In contrast, retinitis pigmentosa (RP) is caused by &gt;50 known genes, which still explain only half of the clinical cases. In a single, one-generation, nonsyndromic RP family, we have identified a gene, dehydrodolichol diphosphate synthase (DHDDS), demonstrating the power of combining whole-exome sequencing with rapid in vivo studies. DHDDS is a highly conserved essential enzyme for dolichol synthesis, permitting global N-linked glycosylation. Zebrafish studies showed virtually identical photoreceptor defects as observed with N-linked glycosylation-interfering mutations in the light-sensing protein rhodopsin. The identified Lys42Glu variant likely arose from an ancestral founder, because eight of the nine identified alleles in 27,174 control chromosomes were of confirmed Ashkenazi Jewish ethnicity. These findings demonstrate the power of exome sequencing linked to functional studies when faced with challenging study designs and, importantly, link RP to the pathways of N-linked glycosylation, which promise new avenues for therapeutic interventions. Retinitis pigmentosa (RP) refers to a large group of genetically heterogeneous retinal degenerative disorders characterized by early rod photoreceptor dysfunction followed by progressive rod and cone photoreceptor dysfunction and photoreceptor death (MIM 268000). Impaired night vision followed by impaired peripheral vision generally starts in adolescence to young adulthood, with subsequent impaired central vision in later life. We studied a family of Ashkenazi Jewish (AJ) origin in which three out of four siblings (two females and one male) were diagnosed with RP in their teenage years ( To identify the genetic cause of this likely recessive subtype of RP, we screened all genes known to harbor RP mutations and found that they were negative for mutations. Classic linkage approaches were not applicable because of the size of the nonconsanguineous family, so we performed whole-exome sequencing in the three affected siblings and one unaffected sibling (Whole Human Exome Capture kit, Roche). We produced approximately 10 gigabases (Gb) of paired-end 75 bp sequence reads per individual on the Illumina GAII platform. To test the overall quality of the sequence data, we compared the genotypes of variants found in the sequence data to variants derived from genotyping via a genome-wide SN

Classification of emissions trading scheme design characteristics

The analysis of existing emission trading schemes leads to the classification of their characteristics into four categories: (i) objectives, (ii) target groups, (iii) rules-influencing mechanisms and (iv) implementation network. This classification is applied for the design of a Hellenic emissions trading scheme and for exploring policy interactions between the Hellenic scheme and other Hellenic climate policy instruments. The results of this procedure confirm that the proposed classification facilitates the definition of the elementary Hellenic scheme characteristics and the specification of its distinctions from other national regimes. Conclusively the proposed classification systematizes and facilitates the integrated design of an emissions trading scheme. Copyright © 2003 John Wiley and Sons, Ltd and ERP Environment

A multi-criteria evaluation method for climate change mitigation policy instruments

This paper presents an integrated multi-criteria analysis method for the quantitative evaluation of climate change mitigation policy instruments. The method consists of: (i) a set of criteria supported by sub-criteria, all of which describe the complex framework under which these instruments are selected by policy makers and implemented, (ii) an Analytical Hierarchy Process (AHP) process for defining weight coefficients for criteria and sub-criteria according to the preferences of three stakeholders groups and (iii) a Multi-Attribute Theory (MAUT)/Simple Multi-Attribute Ranking Technique (SMART) process for assigning grades to each instrument that is evaluated for its performance under a specific sub-criterion. Arguments for the selected combination of these standard methods and definitions for criteria/sub-criteria are quoted. Consistency and robustness tests are performed. The functionality of the proposed method is tested by assessing the aggregate performances of the EU emission trading scheme at Denmark, Germany, Greece, Italy, Netherlands, Portugal, Sweden and United Kingdom. Conclusions are discussed. © 2007 Elsevier Ltd. All rights reserved