Literature Mapping with PubAtlas — extending PubMed with a ‘BLASTing interface’ *

PubAtlas (www.pubatlas.org) is a web service and standalone program providing literature maps for the biomedical research literature. It accepts user-defined sets of terms (PubMed queries) as input, and permits ‘BLASTing’ of one set against another: for all terms x and y in these sets, deriving the results of the pairwise intersections x AND y. This all vs. all capability extends PubMed with a literature analysis interface. Correspondingly, the basic form of literature map that PubAtlas provides for exploring associations among sets of terms is an interactive tabular display, in heatmap/microarray format

Counterpoint. Early intervention for psychosis risk syndromes: Minimizing risk and maximizing benefit

Background: Malhi et al. in this issue critique the clinical high risk (CHR) syndrome for psychosis. Method: Response to points of critique. Results: We agree that inconsistency in CHR nomenclature should be minimized. We respectfully disagree on other points. In our view: a) individuals with CHR and their families need help, using existing interventions, even though we do not yet fully understand disease mechanisms; b) substantial progress has been made in identification of biomarkers; c) symptoms used to identify CHR are specific to psychotic illnesses; d) CHR diagnosis is not “extremely difficult”; e) the pattern of progression, although heterogenous, is discernible; f) “psychosis-like symptoms” are common but are not used to identify CHR; and g) on the point described as ‘the real risk,’ CHR diagnosis does not frequently cause harmful stigma. Discussion: Malhi et al.'s arguments do not fairly characterize progress in the CHR field nor efforts to minimize stigma. That said, much work remains in areas of consistent nomenclature, mechanisms of disease, dissecting heterogeneity, and biomarkers. With regard to what the authors term the “real risk” of stigma associated with a CHR “label,” however, our view is that avoiding words like “risk” and “psychosis” reinforces the stigma that both they and we mean to oppose. Moreover, patients and their families benefit from being given a term that describes what is happening to them

A phenome-wide examination of neural and cognitive function

This data descriptor outlines a shared neuroimaging dataset from the UCLA Consortium for Neuropsychiatric Phenomics, which focused on understanding the dimensional structure of memory and cognitive control (response inhibition) functions in both healthy individuals (130 subjects) and individuals with neuropsychiatric disorders including schizophrenia (50 subjects), bipolar disorder (49 subjects), and attention deficit/hyperactivity disorder (43 subjects). The dataset includes an extensive set of task-based fMRI assessments, resting fMRI, structural MRI, and high angular resolution diffusion MRI. The dataset is shared through the OpenfMRI project, and is formatted according to the Brain Imaging Data Structure (BIDS) standard

Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

These authors contributed equally: Gail Davies, Max Lam. These authors jointly supervised this work: Todd Lencz, Ian J. Deary

Multi-Trait analysis of gwas and biological insights into cognition: A response to hill (2018)

Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88) presented a critique of our recently published paper in Cell Reports entitled 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' (Lam et al., Cell Reports, Vol. 21, 2017, 2597-2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229-237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from 'inflation in the FDR [false discovery rate]', as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88), and are not 'more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence'. © The Author(s) 2018Â

Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets

Here, we present a large (n = 107,207) genome-wide association study (GWAS) of general cognitive ability (“g”), further enhanced by combining results with a large-scale GWAS of educational attainment. We identified 70 independent genomic loci associated with general cognitive ability. Results showed significant enrichment for genes causing Mendelian disorders with an intellectual disability phenotype. Competitive pathway analysis implicated the biological processes of neurogenesis and synaptic regulation, as well as the gene targets of two pharmacologic agents: cinnarizine, a T-type calcium channel blocker, and LY97241, a potassium channel inhibitor. Transcriptome-wide and epigenome-wide analysis revealed that the implicated loci were enriched for genes expressed across all brain regions (most strongly in the cerebellum). Enrichment was exclusive to genes expressed in neurons but not oligodendrocytes or astrocytes. Finally, we report genetic correlations between cognitive ability and disparate phenotypes including psychiatric disorders, several autoimmune disorders, longevity, and maternal age at first birth. Lam et al. conduct a large-scale genome-wide association study of cognitive ability, identifying 70 associated loci. Results provide biological insights into the molecular basis of individual differences in cognitive ability, as well as their relationship to psychiatric and other health-relevant phenotypes. © 2017 The Author(s

Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways

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. © 201

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

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. © 2021, The Author(s)