1,288 research outputs found

    Comparison of the King’s and MiToS staging systems for ALS

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    Objective: To investigate and compare two ALS staging systems, King’s clinical staging and Milano-Torino (MiToS) functional staging, using data from the LiCALS phase III clinical trial (EudraCT 2008-006891-31). Methods: Disease stage was derived retrospectively for each system from the ALS Functional Rating Scale-Revised subscores using standard methods. The two staging methods were then compared for timing of stages using box plots, correspondence using chi-square tests, agreement using a linearly weighted kappa coefficient and concordance using Spearman’s rank correlation. Results: For both systems, progressively higher stages occurred at progressively later proportions of the disease course, but the distribution differed between the two methods. King’s stage 3 corresponded to MiToS stage 1 most frequently, with earlier King’s stages 1 and 2 largely corresponding to MiToS stage 0 or 1. The Spearman correlation was 0.54. There was fair agreement between the two systems with kappa coefficient of 0.21. Conclusion: The distribution of timings shows that the two systems are complementary, with King’s staging showing greatest resolution in early to mid-disease corresponding to clinical or disease burden, and MiToS staging having higher resolution for late disease, corresponding to functional involvement. We therefore propose using both staging systems when describing ALS

    Characterization of single gene copy number variants in schizophrenia

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    Background Genetic studies of schizophrenia have implicated numerous risk loci including several copy number variants (CNVs) of large effect and hundreds of loci of small effect. In only a few cases has a specific gene been clearly identified. Rare CNVs affecting a single gene offer a potential avenue to discovering schizophrenia risk genes. Methods CNVs were generated from exome-sequencing of 4,913 schizophrenia cases and 6,188 controls from Sweden. We integrated multiple CNV calling methods (XHMM and ExomeDepth) to expand our set of single-gene CNVs and leveraged two different approaches for validating these variants (qPCR and Nanostring). Results We found a significant excess of all rare CNVs (deletions p=0.0004, duplications p=0.0006) and single-gene CNVs (deletions p=0.04, duplications p=0.03) in schizophrenia cases compared to controls. An expanded set of CNVs generated from integrating multiple approaches showed a significant burden of deletions in 11/21 gene-sets previously implicated in schizophrenia and across all genes in those sets (p=0.008), although no tests survived correction. We performed an extensive validation of all deletions in the significant set of voltage-gated calcium channels among CNVs called from both exome-sequencing and genotyping arrays. In total, 4 exonic, single-gene deletions validated in cases and none in controls (p=0.039), of which all were identified by exome-sequencing. Conclusions These results point to the potential contribution of single-gene CNVs to schizophrenia, that the utility of exome-sequencing for CNV calling has yet to be maximized and single-gene CNVs should be included in gene focused studies using other classes of variation

    Fine-mapping of lipid regions in global populations discovers ethnic-specific signals and refines previously identified lipid loci

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    Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies

    Memory in Microbes: Quantifying History-Dependent Behavior in a Bacterium

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    Memory is usually associated with higher organisms rather than bacteria. However, evidence is mounting that many regulatory networks within bacteria are capable of complex dynamics and multi-stable behaviors that have been linked to memory in other systems. Moreover, it is recognized that bacteria that have experienced different environmental histories may respond differently to current conditions. These “memory” effects may be more than incidental to the regulatory mechanisms controlling acclimation or to the status of the metabolic stores. Rather, they may be regulated by the cell and confer fitness to the organism in the evolutionary game it participates in. Here, we propose that history-dependent behavior is a potentially important manifestation of memory, worth classifying and quantifying. To this end, we develop an information-theory based conceptual framework for measuring both the persistence of memory in microbes and the amount of information about the past encoded in history-dependent dynamics. This method produces a phenomenological measure of cellular memory without regard to the specific cellular mechanisms encoding it. We then apply this framework to a strain of Bacillus subtilis engineered to report on commitment to sporulation and degradative enzyme (AprE) synthesis and estimate the capacity of these systems and growth dynamics to ‘remember’ 10 distinct cell histories prior to application of a common stressor. The analysis suggests that B. subtilis remembers, both in short and long term, aspects of its cell history, and that this memory is distributed differently among the observables. While this study does not examine the mechanistic bases for memory, it presents a framework for quantifying memory in cellular behaviors and is thus a starting point for studying new questions about cellular regulation and evolutionary strategy

    Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics

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    Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.Peer reviewe

    Pleiotropic meta-analysis of cognition, education, and schizophrenia differentiates roles of early neurodevelopmental and adult synaptic pathways

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    Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected (“concordant”) direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive (“discordant”) relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10−8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms—early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways—that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness

    Rare coding variants in ten genes confer substantial risk for schizophrenia

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    Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, PPeer reviewe
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