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Michael Gill

Researcher at Trinity College, Dublin

Publications -  905
Citations -  98983

Michael Gill is an academic researcher from Trinity College, Dublin. The author has contributed to research in topics: Population & Genome-wide association study. The author has an hindex of 121, co-authored 810 publications receiving 86338 citations. Previous affiliations of Michael Gill include University of Ottawa & University of Connecticut.

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Biological insights from 108 schizophrenia-associated genetic loci

Stephan Ripke, +354 more
- 24 Jul 2014 - 
TL;DR: Associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses.
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Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Shaun Purcell, +81 more
- 06 Aug 2009 - 
TL;DR: The extent to which common genetic variation underlies the risk of schizophrenia is shown, using two analytic approaches, and the major histocompatibility complex is implicate, which is shown to involve thousands of common alleles of very small effect.
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Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease

Jean-Charles Lambert, +215 more
- 01 Dec 2013 - 
TL;DR: In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer's disease.
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Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease

Denise Harold, +86 more
- 01 Oct 2009 - 
TL;DR: A two-stage genome-wide association study of Alzheimer's disease involving over 16,000 individuals, the most powerful AD GWAS to date, produced compelling evidence for association with Alzheimer's Disease in the combined dataset.
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Synaptic, transcriptional and chromatin genes disrupted in autism

Silvia De Rubeis, +99 more
- 13 Nov 2014 - 
TL;DR: Using exome sequencing, it is shown that analysis of rare coding variation in 3,871 autism cases and 9,937 ancestry-matched or parental controls implicates 22 autosomal genes at a false discovery rate of < 0.05, plus a set of 107 genes strongly enriched for those likely to affect risk (FDR < 0.30).