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Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents
被引:1
|作者:
Thng, Gladi
[1
]
Shen, Xueyi
[1
]
Stolicyn, Aleks
[1
]
Harris, Mathew A.
[1
]
Adams, Mark J.
[1
]
Barbu, Miruna C.
[1
]
Kwong, Alex S. F.
[1
,2
,3
]
Frangou, Sophia
[4
,5
]
Lawrie, Stephen M.
[1
]
McIntosh, Andrew M.
[1
]
Romaniuk, Liana
[1
]
Whalley, Heather C.
[1
]
机构:
[1] Univ Edinburgh, Royal Edinburgh Hosp, Div Psychiat, Kennedy Tower,Morningside Pk, Edinburgh, Midlothian, Scotland
[2] Univ Bristol, MRC, Integrat Epidemiol Unit, Bristol, Avon, England
[3] Univ Bristol, Bristol Med Sch, Dept Populat Hlth Sci, Bristol, Avon, England
[4] Univ British Columbia, Djavad Mowafaghian Ctr Brain Hlth, Vancouver, BC, Canada
[5] Icahn Sch Med Mt Sinai, Dept Psychiat, New York, NY 10029 USA
基金:
美国国家卫生研究院;
关键词:
Adolescents;
genetics;
imaging;
major depressive disorder;
CEREBRAL-CORTEX;
MATTER;
VARIABILITY;
STRESS;
D O I:
10.1192/j.eurpsy.2022.2301
中图分类号:
R749 [精神病学];
学科分类号:
100205 ;
摘要:
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 (beta = 0.099-0.281, P-FDR = 0.001-0.043) than MDD-PRS (beta = 0.056-0.152, P-FDR = 0.140-0.140). In adolescents, depressive symptoms were associated with MDD-PRS at baseline and follow-up (beta = 0.084-0.086, p = 1.38 x 10(-4)-4.77 x 10(-4)) but not with any MDD-RVIs (beta < 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.
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