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Review
. 2019 Apr 3;102(1):91-103.
doi: 10.1016/j.neuron.2019.03.022.

Uncovering the Genetic Architecture of Major Depression

Andrew M McIntosh  1 , Patrick F Sullivan  2 , Cathryn M Lewis  3
Affiliations
Review

Uncovering the Genetic Architecture of Major Depression

Andrew M McIntosh et al. Neuron. .

Abstract

There have been several recent studies addressing the genetic architecture of depression. This review serves to take stock of what is known now about the genetics of depression, how it has increased our knowledge and understanding of its mechanisms, and how the information and knowledge can be leveraged to improve the care of people affected. We identify four priorities for how the field of MD genetics research may move forward in future years, namely by increasing the sample sizes available for genome-wide association studies (GWASs), greater inclusion of diverse ancestries and low-income countries, the closer integration of psychiatric genetics with electronic medical records, and the development of the neuroscience toolkit for polygenic disorders.

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Conflict of interest statement

Declaration of interests

AMM currently receives research support from the Sackler Trust and has received past support from Eli Lilly and Janssen within the last 3 years. PFS reports the following potentially competing financial interests. Current: Lundbeck (advisory committee, grant recipient). Past three years: Pfizer (scientific advisory board), Element Genomics (consultation fee), and Roche (speaker reimbursement). CML receives research support from Eli Lilly and RGA Re-insurance.

Figures

Figure 1:
Figure 1:
Differences between major depressive disorder and major depression (MD)
Figure 2:
Figure 2:
Recent progress in genome-wide loci discovery from GWAS studies
Figure 3:
Figure 3:
Characterising the genetic component of MD and understanding its biology
Figure 4:
Figure 4:
Our changing concept of depression
Figure 5:
Figure 5:
Clinical translation of genetic associations from GWAS studies
See this image and copyright information in PMC

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