德国亥姆霍兹联合会Na Cai等研究人员发现，最小表型分析对重度抑郁症会产生低特异性的全基因组关联信号。2020年3月30日，《自然—遗传学》杂志在线发表了这项成果。

Title: Minimal phenotyping yields genome-wide association signals of low specificity for major depression

Author: Na Cai, Joana A. Revez, Mark J. Adams, Till F. M. Andlauer, Gerome Breen, Enda M. Byrne, Toni-Kim Clarke, Andreas J. Forstner, Hans J. Grabe, Steven P. Hamilton, Douglas F. Levinson, Cathryn M. Lewis, Glyn Lewis, Nicholas G. Martin, Yuri Milaneschi, Ole Mors, Bertram Mller-Myhsok, Brenda W. J. H. Penninx, Roy H. Perlis, Giorgio Pistis, James B. Potash, Martin Preisig, Jianxin Shi, Jordan W. Smoller, Fabien Streit, Henning Tiemeier, Rudolf Uher, Sandra Van der Auwera, Alexander Viktorin, Myrna M. Weissman, Kenneth S. Kendler, Jonathan Flint

Issue&Volume: 2020-03-30

Abstract: Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD.

DOI: 10.1038/s41588-020-0594-5

Source: https://www.nature.com/articles/s41588-020-0594-5