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Transl Psychiatry. 2019 Aug 5;9(1):184. doi: 10.1038/s41398-019-0516-4.

Investigating the association between body fat and depression via Mendelian randomization.

Speed MS1,2,3,4,5, Jefsen OH3, Børglum AD4,5,6, Speed D1,4,5,7, Østergaard SD8,9,10,11,12.

Author information

1
Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.
2
Department of Affective Disorders, Aarhus University, Aarhus, Denmark.
3
Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
4
The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
5
Center for Genomics and Personalized Medicine, Aarhus, Denmark.
6
Department of Biomedicine and Center for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark.
7
Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark.
8
Department of Affective Disorders, Aarhus University, Aarhus, Denmark. soeoes@rm.dk.
9
Department of Clinical Medicine, Aarhus University, Aarhus, Denmark. soeoes@rm.dk.
10
The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark. soeoes@rm.dk.
11
Center for Genomics and Personalized Medicine, Aarhus, Denmark. soeoes@rm.dk.
12
Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark. soeoes@rm.dk.

Abstract

Obesity and depression are major public health concerns that are both associated with substantial morbidity and mortality. There is a considerable body of literature linking obesity to the development of depression. Recent studies using Mendelian randomization indicate that this relationship is causal. Most studies of the obesity-depression association have used body mass index as a measure of obesity. Body mass index is defined as weight (measured in kilograms) divided by the square of height (meters) and therefore does not distinguish between the contributions of fat and nonfat to body weight. To better understand the obesity-depression association, we conduct a Mendelian randomization study of the relationship between fat mass, nonfat mass, height, and depression, using genome-wide association study results from the UK Biobank (n = 332,000) and the Psychiatric Genomics Consortium (n = 480,000). Our findings suggest that both fat mass and height (short stature) are causal risk factors for depression, while nonfat mass is not. These results represent important new knowledge on the role of anthropometric measures in the etiology of depression. They also suggest that reducing fat mass will decrease the risk of depression, which lends further support to public health measures aimed at reducing the obesity epidemic.

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