| Literature DB >> 24719883 |
Chao Feng1, Min Fang2, Yu Xu3, Ting Hua3, Xue-Yuan Liu2.
Abstract
Late-life depression could be classified roughly as early-onset depression (EOD) and late-onset depression (LOD). LOD was proved to be associated with cerebral lesions including white matter hyperintensities (WMH) and silent brain infarctions (SBI), differently from EOD. However, it is unclear whether similar association is present between LOD and microbleeds which are also silent lesions. In this study, 195 patients of late-life depression were evaluated and divided into EOD, presenile-onset depression (POD), and LOD groups; 85 healthy elderly controls were enrolled as controls. Subjects were scanned by MRI including susceptibility weighted images to evaluate white matter hyperintensities (WMH), silent brain infarctions (SBI), and microbleeds. The severity of depression was evaluated with 15-item Geriatric Depression Scale. Psychosocial factors were investigated with Scale of Life Events and Lubben Social Network Scale. Logistic regression and linear regression were performed to identify the independent risk factors for depression. Results showed that LOD patients had higher prevalence of microbleeds than EOD, POD, and control patients. The prevalence of lobar microbleeds and microbleeds in the left hemisphere was the independent risk factor for the occurrence of LOD; a high number of microbleeds were associated with severe state of LOD, whereas life events and lack of social support were more important for EOD and POD. All these results indicated that Microbleeds especially lobar microbleeds and microbleeds in the left hemisphere were associated with LOD but not with EOD.Entities:
Mesh:
Year: 2014 PMID: 24719883 PMCID: PMC3955674 DOI: 10.1155/2014/682092
Source DB: PubMed Journal: Biomed Res Int Impact factor: 3.411
Demographic, neuropsychosocial, and radiological characteristics of all subjects.
| Control | EOD |
| POD |
| LOD |
| |
|---|---|---|---|---|---|---|---|
| Age, years | 72.25 ± 5.87 | 71.84 ± 4.95 | 0.669 | 73.06 ± 5.61 | 0.422 | 73.23 ± 4.78 | 0.236 |
| Female | 41 (48.2%) | 37 (64.9%) | 0.050 | 35 (64.8%) | 0.056 | 53 (63.1%) | 0.052 |
| Education, years | 4.25 ± 3.65 | 4.21 ± 4.18 | 0.956 | 3.56 ± 2.82 | 0.238 | 3.99 ± 3.64 | 0.645 |
| Hypertension | 52 (61.2%) | 37 (64.9%) | 0.652 | 33 (61.1%) | 0.994 | 59 (70.2%) | 0.215 |
| Diabetes | 24 (28.2%) | 12 (21.1%) | 0.335 | 16 (29.6%) | 0.860 | 29 (34.5%) | 0.378 |
| MMSE | 25.64 ± 2.68 | 25.33 ± 2.86 | 0.522 | 24.67 ± 2.64 | 0.038 | 24.39 ± 2.42 | 0.002 |
| LSNS | 36.11 ± 4.80 | 32.88 ± 4.32 | 0.000 | 33.46 ± 4.26 | 0.001 | 34.58 ± 5.23 | 0.050 |
| SLE | 0.74 ± 0.79 | 1.91 ± 1.20 | 0.000 | 1.69 ± 1.18 | 0.000 | 0.82 ± 0.79 | 0.511 |
| GDS | 2.36 ± 1.50 | 8.96 ± 1.77 | 0.000 | 9.09 ± 1.73 | 0.000 | 8.62 ± 1.96 | 0.000 |
| Grade of PWMH | 0.94 ± 0.92 | 1.14 ± 0.95 | 0.214 | 1.30 ± 1.06 | 0.038 | 1.56 ± 0.97 | 0.000 |
| Grade of DWMH | 0.86 ± 0.79 | 0.96 ± 0.82 | 0.441 | 1.06 ± 0.92 | 0.182 | 1.54 ± 0.94 | 0.000 |
| Prevalence of SBI | 28 (32.9%) | 17 (29.8%) | 0.696 | 25 (46.3%) | 0.114 | 47 (56.0%) | 0.003 |
| Prevalence of microbleeds in | |||||||
| Any region | 20 (23.5%) | 13 (22.8%) | 0.920 | 15 (27.8%) | 0.574 | 35 (41.7%) | 0.012 |
| Left hemisphere | 10 (11.8%) | 7 (12.3%) | 0.926 | 12 (22.2%) | 0.100 | 28 (33.3%) | 0.001 |
| Right hemisphere | 14 (16.5%) | 10 (17.5%) | 0.721 | 8 (14.8%) | 0.794 | 20 (23.8) | 0.234 |
| Infratentorial | 9 (10.6%) | 5 (8.8%) | 0.722 | 7 (13.0%) | 0.669 | 13 (15.5%) | 0.345 |
| Lobar | 10 (11.8%) | 8 (14.0%) | 0.690 | 11 (20.4%) | 0.167 | 27 (32.1%) | 0.001 |
| Deep | 14 (16.5%) | 11 (19.3%) | 0.665 | 9 (16.7%) | 0.976 | 22 (26.2%) | 0.123 |
EOD: early-onset depression; POD: presenile-onset depression; LOD: late-onset depression; MMSE: minimental state examination; LSNS: Lubben Social Network Scale; SLE: Scale of Life Events; GDS: Geriatric Depression Scale; PWMH: periventricular white matter hyperintensities; DWMH: deep white matter hyperintensities; SBI: silent brain infarction.
Figure 1Examples of microbleeds detected by SWI. The black arrows pointed to lobar and infratentorial microbleeds.
Logistic regressions about the determinants of LOD.
| OR (95% CI) |
| |
|---|---|---|
| Model 1 | ||
| Female | 1.390 (0.703–2.749) | 0.344 |
| Grade of PWMH | 1.141 (0.711–1.830) | 0.586 |
| Grade of DWMH | 1.866 (1.132–3.076) | 0.014 |
| Prevalence of SBI | 1.980 (0.999–3.924) | 0.050 |
| Prevalence of microbleeds in any region | 1.593 (0.750–3.383) | 0.225 |
| Model 2 | ||
| Prevalence of SBI | 1.969 (0.986–3.935) | 0.055 |
| Prevalence of microbleeds in the left hemisphere | 2.660 (1.122–6.309) | 0.026 |
| Model 3 | ||
| Prevalence of SBI | 1.916 (0.962–3.818) | 0.065 |
| Prevalence of lobar microbleeds | 2.502 (1.044–5.997) | 0.040 |
Results about sex and WMH in Models 2 and 3 were similar to those in Model 1 and thus were not shown here. Abbreviations were explained below Table 1.
Linear regression about the determinants of symptom severity in LOD.
|
|
| |
|---|---|---|
| Age | −0.082 ± 0.049 | 0.100 |
| Female | 0.058 ± 0.413 | 0.888 |
| Education year | −0.068 ± 0.057 | 0.238 |
| Hypertension | 0.082 ± 0.468 | 0.862 |
| Diabetes | −0.166 ± 0.447 | 0.712 |
| Degree of PWMH | −0.092 ± 0.289 | 0.752 |
| Degree of DWMH | 0.534 ± 0.262 | 0.045 |
| Prevalence of SBI | 0.036 ± 0.423 | 0.933 |
| Grade of microbleeds | 0.789 ± 0.196 | 0.000 |
| MMSE | 0.009 ± 0.093 | 0.924 |
| LSNS | 0.050 ± 0.046 | 0.281 |
| SLE | 0.266 ± 0.258 | 0.307 |
Abbreviations were explained below Table 1.