Elsevier

Journal of Affective Disorders

Volume 222, November 2017, Pages 63-70
Journal of Affective Disorders

Research paper
Corpus callosum macro and microstructure in late-life depression

https://doi.org/10.1016/j.jad.2017.06.063Get rights and content

Highlights

  • Corpus callosum morphology is largely preserved in late-life depression.

  • MRI measures discriminate between late (>55 yrs) and early onset of depression.

  • Psychosis and depression score not associated with corpus callosum structure in LLD.

  • WMH burden influences dMRI metrics and should be accounted for.

  • Alterations in callosal microstructure unlikely due to partial volume effects.

Abstract

Background

Differences in corpus callosum (CC) morphology and microstructure have been implicated in late-life depression and may distinguish between late and early-onset forms of the illness. However, a multimodal approach using complementary imaging techniques is required to disentangle microstructural alterations from macrostructural partial volume effects.

Methods

107 older adults were assessed: 55 currently-depressed patients without dementia and 52 controls without cognitive impairment. We investigated group differences and clinical associations in 7 sub-regions of the mid-sagittal corpus callosum using T1 anatomical data, white matter hyperintensity (WMH) quantification and two different diffusion MRI (dMRI) models (multi-tissue constrained spherical deconvolution, yielding apparent fibre density, AFD; and diffusion tensor imaging, yielding fractional anisotropy, FA and radial diffusivity, RD).

Results

Callosal AFD was lower in patients compared to controls. There were no group differences in CC thickness, surface area, FA, RD, nor whole brain or WMH volume. Late-onset of depression was associated with lower FA, higher RD and lower AFD. There were no associations between any imaging measures and psychotic features or depression severity as assessed by the geriatric depression scale. WMH volume was associated with lower FA and AFD, and higher RD in patients.

Limitations

Patients were predominantly treatment-resistant. Measurements were limited to the mid-sagittal CC. dMRI analysis was performed on a smaller cohort, n=77. AFD was derived from low b-value data.

Conclusions

Callosal structure is largely preserved in LLD. WMH burden may impact on CC microstructure in late-onset depression suggesting vascular pathology has additional deleterious effects in these patients.

Introduction

Late-life depression (LLD)1 is a common, debilitating, and increasingly important disorder in the context of global ageing (Ferrari et al., 2013, Garcia-Pena et al., 2013). Its aetiology is poorly understood, in part due to the heterogeneous character of the illness. For example, LLD encompasses both patients whose depression continues from earlier adulthood (early onset - EOD) and those with a first episode after the age of 55–60 years old (late-onset, LOD)(Alexopoulos et al., 1988). This distinction is associated with differences in clinical presentation, such as a more severe course and family history in EOD, compared to greater medical comorbidity in LOD (Naismith et al., 2012). Regardless of age of onset, LLD is frequently associated with differential treatment response compared to younger patients (Aizenstein et al., 2014) and more pronounced age-related changes such as impaired executive function (e.g. in memory and processing speed)(Mackin et al., 2014), atrophy and increased cardiovascular burden (Aizenstein et al., 2014). Magnetic resonance imaging (MRI) assessment of the latter has consistently found that LLD patients have increased white matter hyperintensities (WMH) (Wang et al., 2014) which are assumed to reflect a spectrum of neuropathological changes associated with small vessel disease (Wardlaw et al., 2015). Both vascular burden and WM changes may be central to LLD pathology (Alexopoulos et al., 1997, Naismith et al., 2012, Valkanova and Ebmeier, 2013, Wen et al., 2014) thus motivating further characterisation of WM structural alterations in the illness using multimodal MRI measures.

The CC comprises more than a hundred million topographically arranged axons and forms the greatest inter-hemispheric WM network in the human brain. As such, it forms a critical component of brain function, supporting higher-order processing throughout the entire cortex, from prefrontal systems through to the visual system (Schmahmann and Pandya, 2006; Tomasch, 1954). It is hypothesised that the calibre and density of callosal axons reflect the functional capacity of the brain regions they connect and thus the tissue composition of the CC is heterogenous to reflect functional specialisation (Aboitiz et al., 1992). Given the functional anatomy of the CC, regional structural changes in the CC might therefore contribute to the impaired cognition, emotional regulation and psychomotor dysfunction that characterises depression.

Indeed, there is some evidence to suggest CC changes may reflect both trait abnormalities of depression (Yamada et al., 2015), be mood-state dependent (van Uden et al., 2015; Walterfang et al., 2009) or reflect specific features of the illness such as psychosis (Sarrazin et al., 2015) and the time of disease-onset (Kemp et al., 2013). The latter is of most relevance to our study of LLD patients and several studies deserve highlighting. In a 10-year follow-up study, Cyprien et al. (2014) found a smaller CC to be predictive of incident depression in a 10-year period in women, but not men. Hahn et al. (2014) investigated callosal subregions in LOD patients and found a smaller anterior and posterior CC in patients, which correlated with cognitive measures, but not depression severity or illness duration. Similarly, in a morphometry study including both EOD and LOD patients, Ballmaier et al. (2008) found callosal thinning in both the genu and splenium, which correlated with memory and attention functioning only in the LOD group. Notably, the LOD group also had a thinner CC compared to the EOD group suggesting structural differences could discriminate between LLD subtypes. Studies applying diffusion tensor imaging (DTI) report mixed results with both no group-level differences (or not surviving multiple comparisons correction) in CC microstructure in patients (Colloby et al., 2011, Nobuhara et al., 2006) as well as localised differences in the CC (Mettenburg et al., 2012, Reppermund et al., 2014). Interestingly, Alexopoulus et al. (Alexopoulos et al., 2008) related CC deficits to poor treatment response in LLD.

What differentiates our study from previous investigations and which adds to new knowledge about LLD, is the combined analysis of both T1-weighted structural MRI (sMRI) data and diffusion MRI (dMRI) data using two different modelling approaches. Because WM appears homogeneous on T1-weighted scans, it is not possible to reliably perform region-of-interest (ROI) studies specific to most WM fibre bundles, therefore most studies investigate either regional morphometric analysis of sMRI data, or regional microstructural analysis of diffusion MRI data. When studies do apply both modalities they typically perform a voxel-based analysis (VBA) (including tract-based spatial statistics,TBSS) of both data types and compare the results e.g.(Mettenburg et al., 2012; Sexton et al., 2012a). However, by doing so, such studies cannot assess the relationship between macro and microstructural features in exactly the same regions (e.g. they are confounded by differences associated with image processing). This is particularly important in dMRI analysis, where partial volume contamination can significantly confound the estimated parameters (Alexander et al., 2001; Raffelt et al., 2012; Vos et al., 2011). Combining complementary sMRI and dMRI measures in the same well-defined region enables a more complete understanding of structural changes at different length scales.

Presently, the most widely used dMRI measures are FA, mean (MD), radial (RD) and axial diffusivity (AD), derived from the simple 6-parameter diffusion tensor imaging (DTI) model (Basser et al., 1994). In this approach, each voxel is assigned a unique degree of uni-directional anisotropy that is assumed to reflect the dominant underlying axonal architecture. DTI metrics such as FA reflect local changes in bundle composition, which may be caused by either microstructural alterations such as axon loss or reduced membrane integrity, or architectural changes such as increased axon dispersion and the presence of multiple fibre populations (Basser and Pierpaoli, 1996; Concha, 2014). In contrast to DTI, constrained spherical deconvolution (CSD) assumes constant anisotropy along fibres (Tournier et al., 2007). This means that CSD and DTI offer alternative and complementary methods to investigate WM, with CSD improving upon the tensor model by being more directly related to the measured diffusion-weighted signal and being more fibre bundle specific (Tournier et al., 2008). For example, CSD yields the fibre orientation distribution function (FOD) from which parameters relating to partial volume fractions (the relative space in the voxel attributed to a certain compartment) can be derived, and that are assumed to reflect fibre density. The “apparent fibre density” (AFD) measure (Raffelt et al., 2012) has been shown to correlate well with histological descriptions, and has successfully been applied in a number of studies examining WM abnormalities in clinical populations (Farquharson et al., 2014, Raffelt et al., 2012, Scheck et al., 2015, Vaughan et al., 2013), but not yet to study depression.

In this study, our aims were threefold: to identify (1) potential global and regional structural differences in the CC associated with LLD, (2) any association between macro and microstructural differences and white matter lesion burden and (3) any associations between structural differences, depression sub-types and depressive symptomatology. We hypothesised that depression would be associated with regional callosal thinning and a reduced callosal area in anterior and posterior divisions of the CC, with reduced FA, increased RD and decreased AFD mirroring these changes. Moreover we hypothesised that CC structure would be adversely affected by increasing WM lesion load, depression severity and the presence of psychotic features.

Section snippets

Participants

We included 55 currently depressed patients with LLD and 52 age- and gender-matched healthy control participants without current or previous depressive illness, nor cognitive impairment as assessed by formal clinical rating scales. Two additional participants were excluded prior to analysis due to incidental radiological findings of an arteriovenous malformation and frontal lobe lesion respectively. Patients were recruited from the Old Age Psychiatry Department of the University Psychiatric

Structural differences in the whole corpus callosum

The median AFD across the whole mid-sagittal corpus callosum was reduced in patients compared to controls (F(1,73)=4.307, p=0.042, η2=0.057). We did not detect any statistically significant group differences in whole mid-sagittal callosal thickness or area, nor differences in any DTI measure between patients and controls. Whilst there were no differences in total WMH volume between patients and controls, in either the whole cohort (t(104)=−0.983, p=0.328) nor dMRI sub-sample (t(75)=−0.383,

Discussion

In this study we found that CC macrostructure was preserved in LLD. There was some evidence to suggest that microstructure was altered throughout the CC, and that in our study AFD was more sensitive than DTI metrics for detecting these differences. Moreover dMRI measures appeared to discriminate between late and early-onset depression, whilst no association was found between CC structure and psychosis and depression severity.

These results are largely consistent with the extant literature, as

Limitations

Our study applied a multimodal assessment of the CC in a relatively large sample, and is the first to report AFD changes in depression. Nevertheless, there are some limitations that should be noted. 1) The dMRI and patient sub-group analyses contained fewer participants than the total sample and should be interpreted with due caution. Notably, our positive findings were only present when applying more complex ANCOVA models rather than t-tests, which could be interpreted in terms of a lack of

Conclusion

Late-life depression is associated with subtle, microstructural changes in the corpus callosum, which are unrelated to psychosis or depression severity, and are more pronounced in patients with a late-onset of LLD. Combining anatomical and diffusion data provides greater insight into structural MRI changes than using either technique in isolation.

Conflicts of interest

None.

Contributors

Louise Emsell, Christopher Adamson, Filip Bouckaert, Pascal Sienart and Mathieu Vandebulcke designed the study. Filip Bouckaert, Francois-Laurent De Winter, Katarzyna Adamczuk and Rik Vandenberghe recruited the participants and collected the imaging and clinical data. Thibo Billiet, Daan Christiaens, Stefan Sunaert and Marc Seal performed and managed the MRI image processing. Louise Emsell and Mathieu Vandenbulcke managed the literature searches, performed the statistical analyses and wrote the

Role of funding sources

This work was supported by the Foundation for Alzheimer Research (RV., SAO-FRMA 09013, 11020, 13007), KU Leuven (RV., OT/08/056, OT/12/097), FWO (Research Foundation Flanders; KA and MV., G.0746.09), and IWT (Innovation by Science and Technology; DC., SB121013). The funding bodies had no involvement in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

Study limitations

Patients were predominantly treatment-resistant. Measurements were limited to the mid-sagittal corpus callosum and dMRI analysis was performed on a smaller cohort, n=77. AFD was derived from low b-value data.

Acknowledgements

The authors would like to thank Dr Kristof Vansteenlandt for providing statistical advice and Dr Donald Tournier for advice regarding the AFD measurement and its interpretation. An abstract based on this work was presented at the 24th Annual Meeting of the International Society for Magnetic Resonance Imaging in Medicine, 7th–13th May 2016, Singapore.

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