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Héléna A. Gaspar
King's College London
60Publications
14H-index
815Citations
Publications 60
Newest
#1Jonathan R. I. Coleman (Centre for Mental Health)H-Index: 13
#2Julien Bryois (KI: Karolinska Institutet)H-Index: 13
Last.Greg Crawford (Duke University)H-Index: 2
view all 10 authors...
Variance in IQ is associated with a wide range of health outcomes, and 1% of the population are affected by intellectual disability. Despite a century of research, the fundamental neural underpinnings of intelligence remain unclear. We integrate results from genome-wide association studies (GWAS) of intelligence with brain tissue and single cell gene expression data to identify tissues and cell types associated with intelligence. GWAS data for IQ (N = 78,308) were meta-analyzed with a study comp...
#1Julien Bryois (KI: Karolinska Institutet)H-Index: 13
#2Nathan Skene (KI: Karolinska Institutet)H-Index: 10
Last.James Walters (Cardiff University)H-Index: 33
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Background Knowledge of the genetic basis of schizophrenia has markedly improved in the past five years with the discovery of more than 140 significantly associated loci. Several gene sets have been implicated in schizophrenia (e.g. RBFOX, FMRP, synaptic genes). Precise experimental modelling remains difficult as gene sets consist of hundreds of genes and the functional effect of perturbations are likely to be cell type dependent. One key that would allow to model schizophrenia and better unders...
#1Héléna A. Gaspar ('KCL': King's College London)H-Index: 14
#2Gerome Breen ('KCL': King's College London)H-Index: 53
Principal component analysis (PCA) is a standard method to correct for population stratification in ancestry-specific genome-wide association studies (GWASs) and is used to cluster individuals by ancestry. Using the 1000 genomes project data, we examine how non-linear dimensionality reduction methods such as t-distributed stochastic neighbor embedding (t-SNE) or generative topographic mapping (GTM) can be used to provide improved ancestry maps by accounting for a higher percentage of explained v...
#1Naomi R. Wray (UQ: University of Queensland)H-Index: 72
#2Stephan Ripke (Charité)H-Index: 66
Last.Till M. F. Andlauer (MPG: Max Planck Society)H-Index: 1
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Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved ...
#1Delilah ZabanehH-Index: 17
#2Eva KrapohlH-Index: 10
Last.Martha PutallazH-Index: 21
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We used a case–control genome-wide association (GWA) design with cases consisting of 1238 individuals from the top 0.0003 (~170 mean IQ) of the population distribution of intelligence and 8172 unselected population-based controls. The single-nucleotide polymorphism heritability for the extreme IQ trait was 0.33 (0.02), which is the highest so far for a cognitive phenotype, and significant genome-wide genetic correlations of 0.78 were observed with educational attainment and 0.86 with population ...
#1Héléna A. Gaspar ('KCL': King's College London)H-Index: 14
#2Zachary Gerring (QIMR: QIMR Berghofer Medical Research Institute)
Last.Gerome Breen ('KCL': King's College London)H-Index: 53
view all 6 authors...
The major depressive disorder (MDD) working group of the Psychiatric Genomics Consortium (PGC) has published a genome-wide association study (GWAS) for MDD in 130,664 cases, identifying 44 risk variants. We used these results to investigate potential drug targets and repurposing opportunities. We built easily interpretable bipartite drug-target networks integrating interactions between drugs and their targets, genome-wide association statistics and genetically predicted expression levels in diff...
#1Héléna A. Gaspar (NIHR: National Institute for Health Research)H-Index: 14
#2Gerome Breen (NIHR: National Institute for Health Research)H-Index: 53
Using successful genome-wide association results in psychiatry for drug repurposing is an ongoing challenge. Databases collecting drug targets and gene annotations are growing and can be harnessed to shed a new light on psychiatric disorders. We used genome-wide association study (GWAS) summary statistics from the Psychiatric Genetics Consortium (PGC) Schizophrenia working group to build a drug repositioning model for schizophrenia. As sample size increases, schizophrenia GWAS results show incre...
Objective:The authors conducted a genome-wide association study of anorexia nervosa and calculated genetic correlations with a series of psychiatric, educational, and metabolic phenotypes.Method:Following uniform quality control and imputation procedures using the 1000 Genomes Project (phase 3) in 12 case-control cohorts comprising 3,495 anorexia nervosa cases and 10,982 controls, the authors performed standard association analysis followed by a meta-analysis across cohorts. Linkage disequilibri...
#1Nathan Skene (KI: Karolinska Institutet)H-Index: 10
#2Julien Bryois (KI: Karolinska Institutet)H-Index: 13
Last.Ana B. Muñoz-Manchado (KI: Karolinska Institutet)H-Index: 9
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With few exceptions, the marked advances in knowledge about the genetic basis of schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. By applying knowledge of the cellular taxonomy of the brain from single-cell RNA sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. We found that the common-variant genomic results consistently mapped to pyramidal cells, medium spiny neurons (MSNs...
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