TY - JOUR
T1 - Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents
AU - Thng, Gladi
AU - Shen, Xueyi
AU - Stolicyn, Aleks
AU - Harris, Mathew A.
AU - Adams, Mark J.
AU - Barbu, Miruna C.
AU - Kwong, Alex S.F.
AU - Frangou, Sophia
AU - Lawrie, Stephen M.
AU - McIntosh, Andrew M.
AU - Romaniuk, Liana
AU - Whalley, Heather C.
N1 - Funding Information:
Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council [HR03006] and is currently supported by the Wellcome Trust (216767/Z/19/Z). Genotyping of the Generation Scotland samples was carried out by the Genetics Core Laboratory at the Edinburgh Clinical Research Facility, University of Edinburgh, Scotland and was funded by the Medical Research Council UK and the Wellcome Trust (Wellcome Trust Strategic Award “STratifying Resilience and Depression Longitudinally” (STRADL) Reference 104036/Z/14/Z).
Funding Information:
A.M.M. previously received research grant support from The Sackler Trust, as well as speaker fees from Illumina and Janssen. No potential conflicts of interest are reported for the other authors.
Funding Information:
The RVI_func() function was developed at the Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, supported by an NIH R01 EB015611 grant. We would like to thank all of the participants for their time and effort taking part in the studies, the research assistants, clinicians and technicians for their help in data collection, and Laura De Nooij, Rebecca Madden, and Claire Green for their help with the QC of the FreeSurfer data in GS-Imaging.
Funding Information:
Data used in the preparation of this article were also obtained from the Adolescent Brain Cognitive Development (ABCD) Study ( https://abcdstudy.org ), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children aged 9–10 and follow them over 10 years into early adulthood. The ABCD Study is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal-partners.html . A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/ . ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators.
Publisher Copyright:
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PY - 2022/7/28
Y1 - 2022/7/28
N2 - Background Major depressive disorder (MDD) is a polygenic disorder associated with brain alterations but until recently, there have been no brain-based metrics to quantify individual-level variation in brain morphology. Here, we evaluated and compared the performance of a new brain-based 'Regional Vulnerability Index' (RVI) with polygenic risk scores (PRS), in the context of MDD. We assessed associations with syndromal MDD in an adult sample (N = 702, age = 59 ± 10) and with subclinical depressive symptoms in a longitudinal adolescent sample (baseline N = 3,825, age = 10 ± 1; 2-year follow-up N = 2,081, age = 12 ± 1). Methods MDD-RVIs quantify the correlation of the individual's corresponding brain metric with the expected pattern for MDD derived in an independent sample. Using the same methodology across samples, subject-specific MDD-PRS and six MDD-RVIs based on different brain modalities (subcortical volume, cortical thickness, cortical surface area, mean diffusivity, fractional anisotropy, and multimodal) were computed. Results In adults, MDD-RVIs (based on white matter and multimodal measures) were more strongly associated with MDD (β = 0.099-0.281, PFDR = 0.001-0.043) than MDD-PRS (β = 0.056-0.152, PFDR = 0.140-0.140). In adolescents, depressive symptoms were associated with MDD-PRS at baseline and follow-up (β = 0.084-0.086, p = 1.38 × 10-4-4.77 × 10-4) but not with any MDD-RVIs (β < 0.05, p > 0.05). Conclusions Our results potentially indicate the ability of brain-based risk scores to capture a broader range of risk exposures than genetic risk scores in adults and are also useful in helping us to understand the temporal origins of depression-related brain features. Longitudinal data, specific to the developmental period and on white matter measures, will be useful in informing risk for subsequent psychiatric illness.
AB - Background Major depressive disorder (MDD) is a polygenic disorder associated with brain alterations but until recently, there have been no brain-based metrics to quantify individual-level variation in brain morphology. Here, we evaluated and compared the performance of a new brain-based 'Regional Vulnerability Index' (RVI) with polygenic risk scores (PRS), in the context of MDD. We assessed associations with syndromal MDD in an adult sample (N = 702, age = 59 ± 10) and with subclinical depressive symptoms in a longitudinal adolescent sample (baseline N = 3,825, age = 10 ± 1; 2-year follow-up N = 2,081, age = 12 ± 1). Methods MDD-RVIs quantify the correlation of the individual's corresponding brain metric with the expected pattern for MDD derived in an independent sample. Using the same methodology across samples, subject-specific MDD-PRS and six MDD-RVIs based on different brain modalities (subcortical volume, cortical thickness, cortical surface area, mean diffusivity, fractional anisotropy, and multimodal) were computed. Results In adults, MDD-RVIs (based on white matter and multimodal measures) were more strongly associated with MDD (β = 0.099-0.281, PFDR = 0.001-0.043) than MDD-PRS (β = 0.056-0.152, PFDR = 0.140-0.140). In adolescents, depressive symptoms were associated with MDD-PRS at baseline and follow-up (β = 0.084-0.086, p = 1.38 × 10-4-4.77 × 10-4) but not with any MDD-RVIs (β < 0.05, p > 0.05). Conclusions Our results potentially indicate the ability of brain-based risk scores to capture a broader range of risk exposures than genetic risk scores in adults and are also useful in helping us to understand the temporal origins of depression-related brain features. Longitudinal data, specific to the developmental period and on white matter measures, will be useful in informing risk for subsequent psychiatric illness.
KW - Adolescents
KW - genetics
KW - imaging
KW - major depressive disorder
UR - http://www.scopus.com/inward/record.url?scp=85135771994&partnerID=8YFLogxK
U2 - 10.1192/j.eurpsy.2022.2301
DO - 10.1192/j.eurpsy.2022.2301
M3 - Article
C2 - 35899848
AN - SCOPUS:85135771994
SN - 0924-9338
VL - 65
JO - European Psychiatry
JF - European Psychiatry
IS - 1
M1 - e44
ER -