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Michel G. Nivard

Researcher at VU University Amsterdam

Publications -  190
Citations -  13443

Michel G. Nivard is an academic researcher from VU University Amsterdam. The author has contributed to research in topics: Genome-wide association study & Medicine. The author has an hindex of 43, co-authored 158 publications receiving 9063 citations. Previous affiliations of Michel G. Nivard include University of Tartu & Public Health Research Institute.

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Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression

Naomi R. Wray, +262 more
- 26 Apr 2018 - 
TL;DR: A genome-wide association meta-analysis of individuals with clinically assessed or self-reported depression identifies 44 independent and significant loci and finds important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia.
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Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

Aysu Okbay, +216 more
- 01 Jun 2016 - 
TL;DR: In this paper, the authors conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n= 161,460), and neuroticism(n = 170,911).
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Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Phil Lee, +606 more
- 12 Dec 2019 - 
TL;DR: Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes.
Posted ContentDOI

Unraveling the polygenic architecture of complex traits using blood eQTL metaanalysis

Urmo Võsa, +100 more
- 19 Oct 2018 - 
TL;DR: It is observed that cis-eQTLs can be detected for 88% of the studied genes, but that they have a different genetic architecture compared to disease-associated variants, limiting the ability to use cis- eZTLs to pinpoint causal genes within susceptibility loci.