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Genetic effects influencing risk for major depressive disorder in China and Europe

Overview of attention for article published in Translational Psychiatry, March 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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34 X users

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Title
Genetic effects influencing risk for major depressive disorder in China and Europe
Published in
Translational Psychiatry, March 2017
DOI 10.1038/tp.2016.292
Pubmed ID
Authors

T B Bigdeli, S Ripke, R E Peterson, M Trzaskowski, S-A Bacanu, A Abdellaoui, T F M Andlauer, A T F Beekman, K Berger, D H R Blackwood, D I Boomsma, G Breen, H N Buttenschøn, E M Byrne, S Cichon, T-K Clarke, B Couvy-Duchesne, N Craddock, E J C de Geus, F Degenhardt, E C Dunn, A C Edwards, A H Fanous, A J Forstner, J Frank, M Gill, S D Gordon, H J Grabe, S P Hamilton, O Hardiman, C Hayward, A C Heath, A K Henders, S Herms, I B Hickie, P Hoffmann, G Homuth, J-J Hottenga, M Ising, R Jansen, S Kloiber, J A Knowles, M Lang, Q S Li, S Lucae, D J MacIntyre, P A F Madden, N G Martin, P J McGrath, P McGuffin, A M McIntosh, S E Medland, D Mehta, C M Middeldorp, Y Milaneschi, G W Montgomery, O Mors, B Müller-Myhsok, M Nauck, D R Nyholt, M M Nöthen, M J Owen, B W J H Penninx, M L Pergadia, R H Perlis, W J Peyrot, D J Porteous, J B Potash, J P Rice, M Rietschel, B P Riley, M Rivera, R Schoevers, T G Schulze, J Shi, S I Shyn, J H Smit, J W Smoller, F Streit, J Strohmaier, A Teumer, J Treutlein, S Van der Auwera, G van Grootheest, A M van Hemert, H Völzke, B T Webb, M M Weissman, J Wellmann, G Willemsen, S H Witt, D F Levinson, C M Lewis, N R Wray, J Flint, P F Sullivan, K S Kendler

Abstract

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30-40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 34 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 175 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 174 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 16%
Student > Master 23 13%
Student > Bachelor 22 13%
Student > Ph. D. Student 20 11%
Student > Doctoral Student 9 5%
Other 28 16%
Unknown 45 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 22 13%
Medicine and Dentistry 21 12%
Psychology 17 10%
Neuroscience 15 9%
Agricultural and Biological Sciences 10 6%
Other 32 18%
Unknown 58 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 December 2017.
All research outputs
#2,034,096
of 23,845,863 outputs
Outputs from Translational Psychiatry
#787
of 3,388 outputs
Outputs of similar age
#39,838
of 310,227 outputs
Outputs of similar age from Translational Psychiatry
#29
of 95 outputs
Altmetric has tracked 23,845,863 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,388 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.2. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 310,227 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.