Biology subjects

Steen, V. M.

Publications and source records attributed to Steen, V. M..

8 recordsLinked to original sources

bioRxiv2020

Identifying Nootropic Drug Targets via Large-Scale Cognitive GWAS and Transcriptomics

BackgroundCognitive traits demonstrate significant genetic correlations with many psychiatric disorders and other health-related traits. Many neuropsychiatric and neurodegenerative disorders are marked by cognitive deficits. Therefore, genome-wide association studies (GWAS) of general cognitive ability might suggest potential targets for nootropic drug repurposing. Our previous effort to identify "druggable genes" (i.e., GWAS-identified genes that produce proteins targeted by known small molecules) was modestly powered due to the small cognitive GWAS sample available at the time. Since then, two large cognitive GWAS meta-analyses have reported 148 and 205 genome-wide significant loci, respectively. Additionally, large-scale gene expression databases, derived from post-mortem human brain, have recently been made available for GWAS annotation. Here, we 1) reconcile results from these two cognitive GWAS meta-analyses to further enhance power for locus discovery; 2) employ several complementary transcriptomic methods to identify genes in these loci with variants that are credibly associated with cognition; and 3) further annotate the resulting genes to identify "druggable" targets. MethodsGWAS summary statistics were harmonized and jointly analysed using Multi-Trait Analysis of GWAS [MTAG], which is optimized for handling sample overlaps. Downstream gene identification was carried out using MAGMA, S-PrediXcan/S-TissueXcan Transcriptomic Wide Analysis, and eQTL mapping, as well as more recently developed methods that integrate GWAS and eQTL data via Summary-statistics Mendelian Randomization [SMR] and linkage methods [HEIDI], Available brain-specific eQTL databases included GTEXv7, BrainEAC, CommonMind, ROSMAP, and PsychENCODE. Intersecting credible genes were then annotated against multiple chemoinformatic databases [DGIdb, KI, and a published review on "druggability"]. ResultsUsing 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. 26 genes were associated with general cognitive ability via SMR, 16 genes via STissueXcan/S-PrediXcan, 47 genes via eQTL mapping, and 68 genes via MAGMA pathway analysis. The use of the HEIDI test permitted the exclusion of candidate genes that may have been artifactually associated to cognition due to linkage, rather than direct causal or indirect pleiotropic effects. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging on our various transcriptome and pathway analyses, as well as available chemoinformatic databases, we identified 16 putative genes that may suggest drug targets with nootropic properties. DiscussionResults converged on several categories of significant drug targets, including serotonergic and glutamatergic genes, voltage-gated ion channel genes, carbonic anhydrase genes, and phosphodiesterase genes. The current results represent the first efforts to apply a multi-method approach to integrate gene expression and SNP level data to identify credible actionable genes for general cognitive ability.

genomics↗

bioRxiv2019

Functional analysis of evolutionary human methylated regions in schizophrenia patients

BackgroundRecent studies have implicated variations in DNA methylation in the aetiology of schizophrenia. Genome-wide scans in both brain and blood report differential methylated regions (DMRs) and positions (DMPs) between patients with schizophrenia and healthy controls. Previously, we reported that DMRs where human specific methylation (hDMR) has occurred over evolutionary time are enriched for schizophrenia-associated markers (SCZ_hDMR). However, it is unknown whether these human specific DMRs show variable methylation in patients with schizophrenia. MethodsUsing publicly available data, we investigate if human specific DMRs that harbour genetic variants associated with schizophrenia are differentially methylated between cases and controls. ResultsWe find statistically significant (p < 1e-4) methylation difference in schizophrenia associated human specific DMRs (SCZ hDMR) between brain samples of cases and controls. However, we fail to find evidence of similar differences in methylation in blood samples. ConclusionRegions that are evolutionarily important for human species and that are associated with schizophrenia, also show difference in methylation variation in the brain in patients with schizophrenia.

genomics↗

bioRxiv2019

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

Liability to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and 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 GWAS 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 demonstrating 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<5x10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs, and many of these have been validated by larger, more recent single-phenotype GWAS. 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. Further, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia, but also to the broader biological dimensions that are implicated in both general health outcomes and psychiatric illness.

genetics↗

bioRxiv2018

Comparison of three variant callers for human whole genome sequencing

Testing of patients with genetics-related disorders is in progress of shifting from single gene assays to gene panel sequencing, whole-exome sequencing (WES) and whole-genome sequencing (WGS). Since WGS is unquestionably becoming a new foundation for molecular analyses, we decided to compare three currently used tools for variant calling of human whole genome sequencing data. We tested DeepVariant, a new TensorFlow machine learning-based variant caller, and compared this tool to GATK 4.0 and SpeedSeq, using 30x, 15x and 10x WGS data of the well-known NA12878 DNA reference sample.\n\nAccording to our comparison, the performance on SNV calling was almost similar in 30x data, with all three variant callers reaching F-Scores (i.e. harmonic mean of recall and precision) equal to 0.98. In contrast, DeepVariant was more precise in indel calling than GATK and SpeedSeq, as demonstrated by F-Scores of 0.94, 0.90 and 0.84, respectively.\n\nWe conclude that the DeepVariant tool has great potential and usefulness for analysis of WGS data in medical genetics.

genomics↗

bioRxiv2018

Genetic control of variability in subcortical and intracranial volumes

Sensitivity to external demands is essential for adaptation to dynamic environments, but comes at the cost of increased risk of adverse outcomes when facing poor environmental conditions. Here, we apply a novel methodology to perform genome-wide association analysis of mean and variance in nine key brain features (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, intracranial volume and cortical thickness), integrating genetic and neuroanatomical data from a large lifespan sample (n=25,575 individuals; 8 to 89 years, mean age 51.9 years). We identify genetic loci associated with phenotypic variability in cortical thickness, thalamus, pallidum, and intracranial volumes. The variance-controlling loci included genes with a documented role in brain and mental health and were not associated with the mean anatomical volumes. This proof-of-principle of the hypothesis of a genetic regulation of brain volume variability contributes to establishing the genetic basis of phenotypic variance (i.e., heritability), allows identifying different degrees of brain robustness across individuals, and opens new research avenues in the search for mechanisms controlling brain and mental health.

neuroscience↗

bioRxiv2018

Analysis of differentially methylated regions in primates and nonprimates provides support for the evolutionary hypothesis of schizophrenia

IntroductionThe persistence of schizophrenia in human populations separated by geography and time led to the evolutionary hypothesis that proposes schizophrenia as a by-product of the higher cognitive abilities of modern humans. To explore this hypothesis, we used here an evolutionary epigenetics approach building on differentially methylated regions (DMRs) of the genome.\n\nMethodsWe implemented a polygenic enrichment testing pipeline using the summary statistics of genome-wide association studies (GWAS) of schizophrenia and 12 other phenotypes. We investigated the enrichment of association of these traits across genomic regions with variable methylation between modern humans and great apes (orangutans, chimpanzees and gorillas; primate DMRs) and between modern humans and recently extinct hominids (Neanderthals and Denisovans; non-primate DMRs).\n\nResultsRegions that are hypo-methylated in humans compared to great apes show enrichment of association with schizophrenia only if the major histocompatibility complex (MHC) region is included. With the MHC region removed from the analysis, only a modest enrichment for SNPs of low effect persists. The INRICH pipeline confirms this finding after rigorous permutation and bootstrapping procedures.\n\nConclusionThe analyses of regions with differential methylation changes in humans and great apes do not provide compelling evidence of enrichment of association with schizophrenia, in contrast to our previous findings on more recent methylation differences between modern humans, Neanderthals and Denisovans. Our results further support the evolutionary hypothesis of schizophrenia and indicate that the origin of some of the genetic susceptibility factors of schizophrenia may lie in recent human evolution.

genomics↗

bioRxiv2017

Large-Scale cognitive GWAS Meta-analysis Reveals Tissue-Specific Neural Expression and Potential Nootopic Drug Targets

Neurocognitive ability is a fundamental readout of brain function, and cognitive deficits are a critical component of neuropsychiatric disorders, yet neurocognition is poorly understood at the molecular level. In the present report, we present the largest genome-wide association studies (GWAS) of cognitive ability to date (N=107,207), and further enhance signal by combining results with a large-scale GWAS of educational attainment. We identified 70 independent genomic loci associated with cognitive ability, 34 of which were novel. A total of 350 genes were implicated, and this list showed significant enrichment for genes associated with Mendelian disorders with an intellectual disability phenotype. Competitive pathway analysis of gene results implicated the biological process of neurogenesis, 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 analysis revealed that the implicated genes were strongly expressed in neurons, but not astrocytes or oligodendrocytes, and were more strongly associated with fetal brain expression than adult brain expression. Several tissue-specific gene expression relationships to cognitive ability were observed (for example, DAG1 levels in the hippocampus). Finally, we report novel genetic correlations between cognitive ability and disparate phenotypes such as maternal age at first birth and number of children, as well as several autoimmune disorders.

genomics↗

bioRxiv2017

Human-specific methylated regions are enriched in schizophrenia

BackgroundOne explanation for the persistence of schizophrenia despite the reduced fertility of patients is that it is a by-product of recent human evolution. This hypothesis is supported by evidence suggesting that recently-evolved genomic regions in humans are involved in the genetic risk for schizophrenia. Using summary statistics from genome-wide association studies (GWAS) of schizophrenia and 11 other phenotypes, we tested for enrichment of association with GWAS traits in regions that have undergone methylation changes in the human lineage compared to Neanderthals and Denisovans, i.e. human-specific differentially methylated regions (DMRs). We used analytical tools that evaluate polygenic enrichment of a subset of genomic variants against all variants.\n\nResultsSchizophrenia was the only trait in which DMR SNPs showed clear enrichment of association that passed the genome-wide significance threshold. The enrichment was not observed for Neanderthal or Denisovan DMRs. The enrichment seen in human DMRs is comparable to that for genomic regions tagged by Neanderthal Selective Sweep markers, and stronger than that for Human Accelerated Regions. The enrichment survives multiple testing performed through permutation (n=10,000) and bootstrapping (n=5,000) in INRICH (p<0.01). Some enrichment of association with height was observed at the gene level.\n\nConclusionsRegions where DNA methylation modifications have changed during recent human evolution show enrichment of association with schizophrenia and possibly with height. Our study further supports the hypothesis that genetic variants conferring risk of schizophrenia co-occur in genomic regions that have changed as the human species evolved. Since methylation is an epigenetic mark, potentially mediated by environmental changes, our results also suggest that interaction with the environment might have contributed to that association.

genetics↗