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. 2021 Nov;26(11):6806-6819.
doi: 10.1038/s41380-021-01098-x. Epub 2021 Apr 16.

Association between body mass index and subcortical brain volumes in bipolar disorders-ENIGMA study in 2735 individuals

Sean R McWhinney  1 Christoph Abé  2 Martin Alda  1 Francesco Benedetti  3   4 Erlend Bøen  5 Caterina Del Mar Bonnin  6 Tiana Borgers  7 Katharina Brosch  8 Erick J Canales-Rodríguez  9 Dara M Cannon  10 Udo Dannlowski  7 Ana M Díaz-Zuluaga  11 Torbjørn Elvsåshagen  12   13   14 Lisa T Eyler  15   16 Janice M Fullerton  17   18 Jose M Goikolea  6 Janik Goltermann  7 Dominik Grotegerd  7 Bartholomeus C M Haarman  19 Tim Hahn  7 Fleur M Howells  20   21 Martin Ingvar  2 Tilo T J Kircher  8 Axel Krug  8   22 Rayus T Kuplicki  23 Mikael Landén  24   25 Hannah Lemke  7 Benny Liberg  2 Carlos Lopez-Jaramillo  11 Ulrik F Malt  5   26 Fiona M Martyn  10 Elena Mazza  3   4 Colm McDonald  10 Genevieve McPhilemy  10 Sandra Meier  1 Susanne Meinert  7 Tina Meller  8   27 Elisa M T Melloni  3   4 Philip B Mitchell  28 Leila Nabulsi  10 Igor Nenadic  8 Nils Opel  7 Roel A Ophoff  29   30 Bronwyn J Overs  17 Julia-Katharina Pfarr  8 Julian A Pineda-Zapata  31 Edith Pomarol-Clotet  9 Joaquim Raduà  2   6   32 Jonathan Repple  7 Maike Richter  7 Kai G Ringwald  8 Gloria Roberts  28 Raymond Salvador  9 Jonathan Savitz  23   33 Simon Schmitt  8 Peter R Schofield  17   18 Kang Sim  34   35 Dan J Stein  20   21   36 Frederike Stein  8 Henk S Temmingh  21 Katharina Thiel  7 Neeltje E M van Haren  37   38 Holly Van Gestel  1 Cristian Vargas  11 Eduard Vieta  6 Annabel Vreeker  37 Lena Waltemate  7 Lakshmi N Yatham  39 Christopher R K Ching  40 Ole Andreassen  12 Paul M Thompson  40 Tomas Hajek  41   42 ENIGMA Bipolar Disorders Working Group
Affiliations

Association between body mass index and subcortical brain volumes in bipolar disorders-ENIGMA study in 2735 individuals

Sean R McWhinney et al. Mol Psychiatry. 2021 Nov.

Abstract

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.

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Conflict of interest statement

PMT & CRKC received a grant from Biogen, Inc., for research unrelated to this manuscript. DJS has received research grants and/or consultancy honoraria from Lundbeck and Sun. LNY has received speaking/consulting fees and/or research grants from Abbvie, Alkermes, Allergan, AstraZeneca, CANMAT, CIHR, Dainippon Sumitomo Pharma, Janssen, Lundbeck, Otsuka, Sunovion, and Teva. TE received speaker’s honoraria from Lundbeck and Janssen Cilag. EV has received grants and served as consultant, advisor or CME speaker for the following entities (unrelated to the present work): AB-Biotics, Abbott, Allergan, Angelini, Dainippon Sumitomo Pharma, Ferrer, Gedeon Richter, Janssen, Lundbeck, Otsuka, Sage, Sanofi-Aventis, and Takeda.

Figures

Fig. 1
Fig. 1. Effect size of between-group volume differences in each region without adjusting for BMI (left), and after adjusting for BMI (right).
Statistically  significant group differences are denoted by asterisks. BMI slopes shown where significant (FDR-adjusted p < 0.05).
Fig. 2
Fig. 2. Changes in differences between BD and control individuals with versus without controlling for BMI.
Change in group effect size after controlling for BMI, shown in regions where both BD and BMI were significantly associated with regional volume.
Fig. 3
Fig. 3. The effect of diagnosis and BMI on ventricular volume.
Path (c) represents the direct effect of diagnosis, while (a) through (b) represents the indirect path of diagnosis through BMI. The adjusted effect of diagnosis on volume is shown after accounting for BMI (c′). We show unstandardized coefficients along with their 95% CI derived from bootstrap. Significant effects (p < 0.05) are marked by asterisks. In all effects, we controlled for the covariates age, sex, and data collection site, while those impacting volume additionally adjusted for hemisphere, ICV.

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References

    1. Hajek T, Slaney C, Garnham J, Ruzickova M, Passmore M, Alda M. Clinical correlates of current level of functioning in primary care-treated bipolar patients. Bipolar Disord. 2005;7:286–91. - PubMed
    1. Begley CE, Annegers JF, Swann AC, Lewis C, Coan S, Schnapp WB, et al. The lifetime cost of bipolar disorder in the US: an estimate for new cases in 1998. Pharmacoeconomics. 2001;19:483–95. - PubMed
    1. Kleinman L, Lowin A, Flood E, Gandhi G, Edgell E, Revicki D. Costs of bipolar disorder. Pharmacoeconomics. 2003;21:601–22. - PubMed
    1. Hajek T, Franke K, Kolenic M, Capkova J, Matejka M, Propper L, et al. Brain age in early stages of bipolar disorders or schizophrenia. Schizophr Bull. 2019;45:190–8. - PMC - PubMed
    1. Nunes A, Schnack HG, Ching CRK, Agartz I, Akudjedu NT, Alda M, et al. Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group. Mol Psychiatry. 2020;25:2130–43. - PMC - PubMed

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