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Leveraging psychiatric and medical genetics to understand comorbid depression and obesity

  • Anna R. Docherty (a1)

Summary

Precision medicine in psychiatry is on the rise, and depression and obesity – two highly prevalent, comorbid and well-characterised phenotypes – are optimal targets for the approach. Add the bedrock susceptibility gene, FTO, and Riviera et al have identified a constellation of factors that could enhance clinical treatment of both disorders.

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References

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1 Sullivan, PF, Agrawal, A, Bulik, CM, Andreassen, OA, Borglum, AD, Breen, G, et al. Psychiatric genomics: an update and an agenda. bioRxiv 2017 (preprint 10 Mar, https://dx.doi.org/10.1101/115600).
2 Rivera, M, Locke, AE, Corre, T, Czamara, D, Wolf, C, Ching-Lopez, A, et al. Interaction between the FTO gene, body mass index and depression: meta-analysis of 13701 individuals. Br J Psychiatry 2017; 211: 70–6.
3 Luppino, FS, de Wit, LM, Bouvy, PF, Stijnen, T, Cuijpers, P, Penninx, BW, et al. Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry 2010; 67: 220–9.
4 Peng, S, Zhu, Y, Xu, F, Ren, X, Li, X, Lai, M. FTO gene polymorphisms and obesity risk: a meta-analysis. BMC Med 2011; 9: 71.
5 McGinty, EE, Bailer, J, Azrin, ST, Juliano-Bult, D, Daumit, GL. Interventions to address medical conditions and health-risk behaviors among persons with serious mental illness: a comprehensive review. Schizophr Bull 2016; 42: 96124.
6 Daumit, GL, Dickerson, FB, Wang, NY, Dalcin, A, Jerome, GJ, Anderson, CA, et al. A behavioral weight-loss intervention in persons with serious mental illness. N Engl J Med 2013; 368: 1594–602.
7 Teasdale, SB, Ward, PB, Rosenbaum, S, Samaras, K, Stubbs, B. Solving a weighty problem: systematic review and meta-analysis of nutrition interventions in severe mental illness. Br J Psychiatry 2017; 210: 110–8.
8 Krueger, RF, Tackett, JL, MacDonald, A. Toward validation of a structural approach to conceptualizing psychopathology: a special section of the Journal of Abnormal Psychology. J Abnorm Psychol 2016; 125: 1023–6.
9 Adkins, DE. Machine learning and electronic health records: a paradigm shift. Am J Psychiatry 2017; 174: 93–4.
10 Hoffmann, TJ, Ehret, GB, Nandakumar, P, Ranatunga, D, Schaefer, C, Kwok, PY, et al. Genome-wide association analyses using electronic health records identify new loci influencing blood pressure variation. Nat Genet 2017; 49: 5464.

Leveraging psychiatric and medical genetics to understand comorbid depression and obesity

  • Anna R. Docherty (a1)

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Leveraging psychiatric and medical genetics to understand comorbid depression and obesity

  • Anna R. Docherty (a1)
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