His primary areas of study are Genome-wide association study, Schizophrenia, Neuroscience, Bipolar disorder and Psychiatry. He combines subjects such as Major depressive disorder, Genetic association, Clinical psychology and Genetic architecture with his study of Genome-wide association study. His study in Schizophrenia is interdisciplinary in nature, drawing from both Psychosis, Cognition, Neuropsychology and Allele.
The concepts of his Neuroscience study are interwoven with issues in Voxel-based morphometry and Audiology. His Bipolar disorder study combines topics in areas such as Meta-analysis, White matter, Grey matter and Brain size. His work in Psychiatry tackles topics such as Cohort study which are related to areas like Cohort.
Andrew M. McIntosh mainly investigates Schizophrenia, Psychiatry, Genome-wide association study, Bipolar disorder and Major depressive disorder. The study incorporates disciplines such as Audiology, Psychosis, Grey matter, Temporal lobe and Neuroscience in addition to Schizophrenia. His Genome-wide association study research is multidisciplinary, incorporating elements of Biobank, Genetic association and Genetic architecture.
Andrew M. McIntosh works mostly in the field of Bipolar disorder, limiting it down to topics relating to White matter and, in certain cases, Diffusion MRI, as a part of the same area of interest. His work deals with themes such as Internal medicine, Clinical psychology and Heritability, which intersect with Major depressive disorder. Andrew M. McIntosh interconnects Neuroticism, Personality and Cognition in the investigation of issues within Clinical psychology.
Andrew M. McIntosh focuses on Major depressive disorder, Depression, Clinical psychology, DNA methylation and Genome-wide association study. His Major depressive disorder research integrates issues from Polygenic risk score, Bipolar disorder and Mood. His research in Clinical psychology intersects with topics in Cognition, Schizophrenia, Neuroimaging and Neuroticism.
His Schizophrenia research is multidisciplinary, relying on both Anorexia nervosa, Psychosis and Genetic variation. His work focuses on many connections between Genome-wide association study and other disciplines, such as Genetic association, that overlap with his field of interest in Meta-analysis. His work on Genetic architecture as part of general Genetics study is frequently linked to Trait, bridging the gap between disciplines.
Andrew M. McIntosh spends much of his time researching Depression, Genome-wide association study, Clinical psychology, Major depressive disorder and Mental health. His Depression research includes elements of Schizophrenia, Increased risk, Lateral ventricles and Age of onset. His Genome-wide association study study combines topics from a wide range of disciplines, such as Meta-analysis, Cohort study and Genetic association.
The Clinical psychology study combines topics in areas such as Neuroticism and Heritability. His research integrates issues of Orbitofrontal cortex, Oncology, Internal medicine, Risk factor and Brain aging in his study of Major depressive disorder. His biological study spans a wide range of topics, including Genetics and Disease.
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Biological insights from 108 schizophrenia-associated genetic loci
Stephan Ripke;Stephan Ripke;Benjamin M. Neale;Benjamin M. Neale;Aiden Corvin;James T. R. Walters.
Nature (2014)
Genome-wide association study identifies five new schizophrenia loci
Stephan Ripke;Alan R. Sanders;Kenneth S. Kendler;Douglas F. Levinson.
Nature Genetics (2011)
Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs
S. Hong Lee;Stephan Ripke;Stephan Ripke;Benjamin M. Neale;Benjamin M. Neale;Stephen V. Faraone.
Nature Genetics (2013)
Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression
Naomi R. Wray;Stephan Ripke;Stephan Ripke;Stephan Ripke;Manuel Mattheisen;MacIej Trzaskowski.
Nature Genetics (2018)
Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4
Pamela Sklar;Pamela Sklar;Stephan Ripke;Stephan Ripke;Laura J. Scott;Ole A. Andreassen.
Nature Genetics (2011)
Analysis of shared heritability in common disorders of the brain
Verneri Anttila;Verneri Anttila;Brendan Bulik-Sullivan;Brendan Bulik-Sullivan;Hilary K. Finucane;Raymond K. Walters;Raymond K. Walters.
Science (2018)
A mega-analysis of genome-wide association studies for major depressive disorder
Stephan Ripke;Naomi R Wray;Cathryn M Lewis;Steven P Hamilton.
Molecular Psychiatry (2013)
Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection
Antonio F. Pardiñas;Peter Holmans;Andrew J. Pocklington;Valentina Escott-Price.
Nature Genetics (2018)
Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions
David M. Howard;Mark J. Adams;Toni Kim Clarke;Jonathan D. Hafferty.
Nature Neuroscience (2019)
Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores
Bjarni J. Vilhjálmsson;Jian Yang;Hilary K. Finucane;Alexander Gusev.
American Journal of Human Genetics (2015)
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