TY - JOUR
T1 - Person-based similarity in brain structure and functional connectivity in bipolar disorder
AU - Doucet, Gaelle E.
AU - Glahn, David C.
AU - Frangou, Sophia
N1 - Funding Information:
This work was supported by the National Institutes of Health (NIH) ( R01MH104284 ; R01MH113619 ; R01MH116147 ; R01AG050345 ; R01MH078143 ; R01MH106324 ; R03AG064001 ; P20GM130447 ).
Funding Information:
This work was supported by the National Institutes of Health (NIH) (R01MH104284; R01MH113619; R01MH116147; R01AG050345; R01MH078143; R01MH106324; R03AG064001; P20GM130447). The data that support the findings of this study are available from the corresponding author upon reasonable request. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. GED and SF designed the study; GED analyzed the data and wrote the first draft of the manuscript; SF provided data of the discovery sample; DCG provided data of the replication samples; all authors interpreted the results and approved the final version of the manuscript.
Publisher Copyright:
© 2020
PY - 2020/11/1
Y1 - 2020/11/1
N2 - BACKGROUND: Bipolar disorder shows significant variability in clinical presentation. Here we adopt a personalized approach to quantify the brain structural and functional similarity of each individual patient to other patients and to healthy individuals. METHODS: Brain morphometric and resting-state functional connectivity measures from two independent samples of patients with bipolar disorder and healthy individuals (total number of participants=215) were modeled as single vectors to generated individualized morphometric and connectivity profiles. These profiles were then used to compute a person-based similarity indices which quantified the similarity in neuroimaging profiles amongst patients and between patients and health individuals. RESULTS: The morphometric and connectivity profiles of patients showed within-diagnosis similarity which was comparable to that observed in healthy individuals. They also showed minimal deviance from those of healthy individuals; the correlation between the profiles of patients and healthy individuals was high (range: 0.71–0.94, p<10−5). The degree of similarity between imaging profiles was associated with IQ (for cortical thickness) and age (functional integration) rather than clinical variables. Patients who were prescribed lithium, compared to those who were not, showed greater similarity to healthy individuals in terms of network integration (t = 2.2, p = 0.03). LIMITATIONS: We focused on patients with Bipolar disorder, type I only. CONCLUSIONS: High inter-individual similarity in neuroimaging profiles was observed amongst patients with bipolar disorder and between patients and healthy individuals. We infer that brain alterations associated with bipolar disorder may be nested within the normal biological diversity consistent with the high prevalence of mood symptoms in the general population.
AB - BACKGROUND: Bipolar disorder shows significant variability in clinical presentation. Here we adopt a personalized approach to quantify the brain structural and functional similarity of each individual patient to other patients and to healthy individuals. METHODS: Brain morphometric and resting-state functional connectivity measures from two independent samples of patients with bipolar disorder and healthy individuals (total number of participants=215) were modeled as single vectors to generated individualized morphometric and connectivity profiles. These profiles were then used to compute a person-based similarity indices which quantified the similarity in neuroimaging profiles amongst patients and between patients and health individuals. RESULTS: The morphometric and connectivity profiles of patients showed within-diagnosis similarity which was comparable to that observed in healthy individuals. They also showed minimal deviance from those of healthy individuals; the correlation between the profiles of patients and healthy individuals was high (range: 0.71–0.94, p<10−5). The degree of similarity between imaging profiles was associated with IQ (for cortical thickness) and age (functional integration) rather than clinical variables. Patients who were prescribed lithium, compared to those who were not, showed greater similarity to healthy individuals in terms of network integration (t = 2.2, p = 0.03). LIMITATIONS: We focused on patients with Bipolar disorder, type I only. CONCLUSIONS: High inter-individual similarity in neuroimaging profiles was observed amongst patients with bipolar disorder and between patients and healthy individuals. We infer that brain alterations associated with bipolar disorder may be nested within the normal biological diversity consistent with the high prevalence of mood symptoms in the general population.
KW - Bipolar disorder
KW - Inter-individual correlation
KW - Magnetic resonance imaging, normative modeling
KW - Resting-state
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U2 - 10.1016/j.jad.2020.06.041
DO - 10.1016/j.jad.2020.06.041
M3 - Article
C2 - 32697714
AN - SCOPUS:85088021531
SN - 0165-0327
VL - 276
SP - 38
EP - 44
JO - Journal of Affective Disorders
JF - Journal of Affective Disorders
ER -