Michel G. Nivard

Michel G. Nivard

Auto-generated profile, based on publicly available information

Michel G. Nivard

Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
26 April 2018 in Nature Genetics
Verified
Journal Article
Open access
PDF file
NWNaomi R. Wray
Naomi R. Wray
SRStephan Ripke
Stephan Ripke
MMManuel Mattheisen
Manuel Mattheisen
MTMaciej Trzaskowski
Maciej Trzaskowski
EBEnda M. Byrne
Enda M. Byrne
EQEqtlgen
Eqtlgen
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 in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

2 September 2021 in Nature Genetics
Verified
Journal Article
Closed access
PDF file
UVUrmo Võsa
Urmo Võsa
ACAnnique Claringbould
Annique Claringbould
HWHarm-Jan Westra
Harm-Jan Westra
MBMarc Jan Bonder
Marc Jan Bonder
PDPatrick Deelen
Patrick Deelen
LFLude Franke
Lude Franke

1 December 2019 in Cell
Verified
Journal Article
Closed access
PLPhil H. Lee
Phil H. Lee
VAVerneri Anttila
Verneri Anttila
HWHyejung Won
Hyejung Won
YFYen-Chen A. Feng
Yen-Chen A. Feng
JRJacob Rosenthal
Jacob Rosenthal
JSJordan Smoller
Jordan Smoller

8 April 2019 in Nature Human Behaviour
Verified
Journal Article
Closed access
PDF file
AGAndrew D. Grotzinger
Andrew D. Grotzinger
MRMijke Rhemtulla
Mijke Rhemtulla
RVRonald de Vlaming
Ronald de Vlaming
SRStuart J. Ritchie
Stuart J. Ritchie
TMTravis T. Mallard
Travis T. Mallard
ETElliot M. Tucker-Drob
Elliot M. Tucker-Drob

18 April 2016 in Nature Genetics
Verified
Journal Article
Open access
PDF file
LSLifeLines Cohort Study
LifeLines Cohort Study
AOAysu Okbay
Aysu Okbay
BBBart M L Baselmans
Bart M L Baselmans
JNJan-Emmanuel De Neve
Jan-Emmanuel De Neve
PTPatrick Turley
Patrick Turley
DCDavid Cesarini
David Cesarini
Daniel Benjamin, Meike Bartels, Philipp Koellinger and colleagues report a genome-wide association meta-analysis of subjective well-being, depressive symptoms and neuroticism. The study leverages a large sample size together with genetic correlations between the phenotypes to identify, with high confidence, loci associated with each phenotype. Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.

14 January 2019 in Nature Genetics
Verified
Journal Article
Open access
PDF file
RLRichard Karlsson Linnér
Richard Karlsson Linnér
PBPietro Biroli
Pietro Biroli
EKEdward Kong
Edward Kong
SMS. Fleur W. Meddens
S. Fleur W. Meddens
RWRobbee Wedow
Robbee Wedow
JBJonathan P. Beauchamp
Jonathan P. Beauchamp
Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated (\(\left| {\hat r_{\mathrm{g}}} \right|\) ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.