Stratifying major depressive disorder by polygenic risk for schizophrenia in relation to structural brain measures

Abstract

BackgroundSubstantial clinical heterogeneity of major depressive disorder (MDD) suggests it may group together individuals with diverse aetiologies. Identifying distinct subtypes should lead to more effective diagnosis and treatment, while providing more useful targets for further research. Genetic and clinical overlap between MDD and schizophrenia (SCZ) suggests an MDD subtype may share underlying mechanisms with SCZ.MethodsThe present study investigated whether a neurobiologically distinct subtype of MDD could be identified by SCZ polygenic risk score (PRS). We explored interactive effects between SCZ PRS and MDD case/control status on a range of cortical, subcortical and white matter metrics among 2370 male and 2574 female UK Biobank participants.ResultsThere was a significant SCZ PRS by MDD interaction for rostral anterior cingulate cortex (RACC) thickness (β = 0.191, q = 0.043). This was driven by a positive association between SCZ PRS and RACC thickness among MDD cases (β = 0.098, p = 0.026), compared to a negative association among controls (β = −0.087, p = 0.002). MDD cases with low SCZ PRS showed thinner RACC, although the opposite difference for high-SCZ-PRS cases was not significant. There were nominal interactions for other brain metrics, but none remained significant after correcting for multiple comparisons.ConclusionsOur significant results indicate that MDD case-control differences in RACC thickness vary as a function of SCZ PRS. Although this was not the case for most other brain measures assessed, our specific findings still provide some further evidence that MDD in the presence of high genetic risk for SCZ is subtly neurobiologically distinct from MDD in general.

Automated classification of depression from structural brain measures across two independent community‐based cohorts

“…In UK Biobank, T1‐weighted imaging data was collected at one site (Cheadle) with a 3T scanner (Siemens Skyra), following the standard and freely available UK Biobank imaging and quality control protocols (Alfaro‐Almagro et al, 2018; Smith, Alfaro‐Almagro, & Miller, 2018; UK Biobank, 2014). Brain morphometric measures for N = 10,109 T1‐weighted scans were derived locally with FreeSurfer version 5.3 and quality controlled (Supplementary section S1.1.3; Harris et al, 2019; Neilson et al, 2019; Ritchie et al, 2018). After quality control, measures for N = 8,959 participants were included.…”

ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing

“…Larger samples and meta-analytic approaches represent good strategies to overcome issues associated with small sample sizes. Large-scale data collection initiatives with harmonized assessments (including neuroimaging), such as the population-based UK Biobank study (N = 500,000) 15 , are yielding key insights into brain mechanisms involved in MDD (e.g., Howard et al 16 ; Shen et al 17 ; Harris et al 18 ). However, recruiting large samples is not always feasible because of limited access to patient populations at any one site or limited availability of scanning facilities and the financial costs of scanning hundreds or even thousands of participants.…”

Phenotypic and genetic associations between anhedonia and brain structure in UK Biobank

“…However, the influence of potential confounding factors associated with brain abnormalities in psychiatric disorders has often been neglected. Most previous studies on PRS for MDD and schizophrenia did not consider those factors [54,69,70], and this was the case in prior PRS-anhedonia analyses [6]. Our sensitivity analyses controlled for childhood traumatic events, adulthood traumatic events, medication use, depressed mood, Townsend social deprivation index, education qualification, body mass index, current tobacco use and alcohol intake frequency.…”