The Coherence Problem: Finding Meaning in GWAS Complexity
- 342 Downloads
Genome wide association studies (GWAS) for behavioral traits and psychiatric disorders have inspired both confident optimism and withering criticism. Although many recent findings from well powered GWAS have been replicated in independent data sets, the genes identified have pinned down few if any underlying causal mechanisms. Therefore, a key issue is whether or not the genes implicated by GWAS form a coherent story on their own and thus could in principle lead to insight into the biological mechanisms underlying the trait or disorder. We sketch here four scenarios for how genes may contribute to traits and disorders; genetic studies may help elucidate mechanisms under only two of our scenarios. We also describe here an approach to characterize, in an unbiased fashion, the molecular coherence of the gene sets implicated by GWAS of various behavioral and psychiatric phenotypes and we sketch how the four scenarios may be reflected in our molecular coherence measure.
KeywordsGWAS Psychiatric illness Molecular genetics Coherence Philosophy
This project was supported by a Genetics and Human Agency Award to KSK. This work is solely the responsibility of the authors and does not necessarily represent the official view of the funders (John Templeton Foundation).
Compliance with ethical standards
Conflict of interest
Mark A. Reimers, Carl Craver, Mikhail Dozmorov, Silviu-Alin Bacanu and Kenneth S. Kendler declare no conflicts of interest.
This article does not contain any studies with human participants performed by any of the authors.
Human and Animal Rights
This article does not contain any studies with human or animal subjects performed by any of the authors.
For this type of study formal consent is not required.
- Ball P (2010) Bursting the genomics bubble: column: muse. Nature 10(13-March-2010):1038–1145Google Scholar
- Kendler KS, Eaves LJ (2005) Psychiatric genetics, review of psychiatry, vol 24. American Psychiatric, ArlingtonGoogle Scholar
- Kendler KS, Neale M, Kessler L, Heath A, Eaves L (1993) A twin study of recent life events and difficulties. ArchGenPsychiatry 50(10):789–796Google Scholar
- Sekar A, Bialas AR, de Rivera H, Davis A, Hammond TR, Kamitaki N, Tooley K, Presumey J, Baum M, Van Doren V, Genovese G, Rose SA, Handsaker RE, Daly MJ, Carroll MC, Stevens B, McCarroll SA (2016) Schizophrenia risk from complex variation of complement component 4. Nature 530(7589):177–183CrossRefGoogle Scholar
- Skene NG, Bryois J, Bakken TE, Breen G, Crowley JJ, Gaspar HA, Giusti-Rodriguez P, Hodge RD, Miller JA, Muñoz-Manchado AB, O’Donovan MC, Owen MJ, Pardiñas AF, Ryge J, Walters JTR, Linnarsson S, Lein ES;, Sullivan PF, Hjerling-Leffler J, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium (2018) Genetic identification of brain cell types underlying schizophrenia. Nat Genet Jun 50(6):825–833CrossRefGoogle Scholar
- Sullivan PF, Agrawal A, Bulik CM, Andreassen OA, Borglum AD, Breen G, Cichon S, Edenberg HJ, Faraone SV, Gelernter J, Mathews CA, Nievergelt CM, Smoller JW, O’Donovan MC (2017) Psychiatric genomics: an update and an agenda. Am J Psychiatry 2017:appiajp201717030283Google Scholar
- Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, Kuhn M, Bork P, Jensen LJ von MC (2015) STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res 43(Database issue):D447–D452CrossRefGoogle Scholar
- Wade N (2010) A decade later, genetic map yields few new cures. New York Times, New YorkGoogle Scholar