AMGP61210S1064-7481(12)61210-X10.1097/00019442-199905000-00009American Association for Geriatric PsychiatryTABLE 1Comparison of demographics between the early-onset-of-depression (EOD) and the late-onset-of-depression (LOD) samples (Student's t-test and chi-square)Onset of DepressionTotal Group (TG) EOD and LOD (N = 245)EOD (n = 114)LOD (n = 131)PAge, years, mean ± SD75.28±7.1372.19±6.9477.96±6.170.001Length of stay, days, mean ± SD118.69±63.42125.75 ±60.52112.53±65.440.100Ham-D, baseline, mean ± SD19.89 ±6.8420.03 ±7.0919.76 ±6.630.759Ham-D, discharge, mean ± SD10.30±6.599.35 ±6.4911.28±6.580.048Sex, n (%)0.604 Male64 (26.1%)28 (24.6%)36 (27.5%) Female181 (73-9%)86 (75.4%)95 (72.5%)Level of education, n (%)0.062 No formal education7 (2.9%)1 (0.9%)6 (4.6%) Elementary, partial or complete90 (36.7%)36 (31.6%)54 (41.2%) High school or technical school, partial45 (18.4%)24 (21.1%)21 (16%.0) High school, complete68 (27.8%)34 (29.8%)34 (26.0%) College/University, partial10 (4.1%)6 (5.3%)4 (3.1%) College/University, complete20 (8.2%)10 (8.8%)10 (7.6%) Graduate studies, partial or complete5 (2.0%)3 (2.6%)2 (1.5%)DSM-IV diagnoses, n (%) Primary Axis I0.187  Major depression240 (98.0%)110 (96.5%)130 (99.2%)  Othera5 (2.0%)4 (3.5%)1 (0.8%) Axis II0.224  No diagnosis217 (88.6%)104 (91.2%)113 (86.3%)  Personality disorderb28 (11.4%)10 (8.8%)18 (13.7%)Note: EOD: onset <age 60; LOD: onset ≥age 60. SD = standard deviation.aincludes dysthymic disorder (TG: 0.4%; EOD: 0.9%), adjustment disorder (TG: 0.4%; EOD: 0.9%), delusional disorder (TG: 0.4%; EOD: 0.9%), bereavement (TG: 0.4%; EOD: 0.9%), and generalized anxiety disorder (TG: 0.4%; LOD: 0.8%).bincludes borderline personality disorder (TG: 0.8%; EOD: 0.9%; LOD: 0.8%), histrionic personality disorder (TG: 3-7%; EOD: 4.4%; LOD: 3.1%), narcissistic personality disorder (TG: 2.1%; EOD: 0.9%; LOD: 31%), dependent personality disorder (TG: 2.1%; EOD: 0.9%; LOD: 31%), avoidant personality disorder (TG: 0.4%; LOD: 0.8%), and “diagnosis deferred” (TG: 1.2%; LOD: 2.3%).TABLE 2Comparison of cognitive functioning between early-onset-of-depression (EOD) and late-onset-of-depression (LOD) groups (ANOVA)Total GroupOnset of DepressionEODLODPMini-Mental State Exam, baseline N/n/n229110119 Mean ± SD26.30 ±3-2627.01 ±2.4825.81 ±3-760.005Mini-Mental State Exam, discharge N/n/n1257154 Mean ± SD27.58 ±2.4527.96 ±2.3127.07±2.570.040Mattis Dementia Rating Scale, baseline N/n/n1919299 Mean ± SD124.07 ± 15.94127.47 ± 12.49120.91 ± 18.090.004Note:EOD: onset <age 60; LOD: onset ≥ 60. SD = standard deviation.The difference between MMSE scores at baseline and discharge was found to be statistically significant for the total group (t = −2.27; P<0.05) and the EOD group (t = − 2.98; P<0.05) but not for the LOD group (t =—0.19; P>0.05).TABLE 3Comparison of cognitive functioning between early-onset-of-depression (EOD) and late-onset-of-depression (LOD) groups with age and level of education as covariates (ANCOVA)Onset of DepressionEODLODPMini-Mental State Exam (MMSE), baseline n110119 Adjusted mean26.7927.370.271Mini-Mental State Exam (MMSE), discharge n7154 Adjusted mean27.5127.520.980Mattis Dementia Rating Scale (MDRS), baseline n9299 Adjusted mean127.72127.810.969Note:EOD: onset < age 60; LOD: onset ≥ age 60. Multivariate analysis of covariance revealed no significant difference between the two groups (EOD vs. LOD) with respect to performance on the MDRS and the MMSE (Wilks F[1,98] =0.98; P1>0.05).TABLE 4Comparison of cognitive functioning (per subscales of the MMSE and MDRS at baseline) between early-onset-of-depression (EOD) and late-onset-of-depression (LOD) groups, mean±SD (ANOVA)Total GroupOnset of DepressionEODLODPMini-Mental State Exam (MMSE), baseline Orientation956±0.909.76±0.54938± 1.100.002 Registration2.99±0.112.98±0.132.99±0.900.148 Calculation3.82± 1.553-90 ± 1.383-74 ± 1.700.381 Language7.24 ±0.847.40 ±0.787.10±0.960.006 Recall2.10±0.932.22 ±0.901.99±0.940.418 Construction0.70 ±0.480.75 ±0.440.66±0.510.131Mattis Dementia Rating Scale (MDRS), baseline Attention34.73 ±2.5835.03 ± 1.8134.44±3-ll0.232 Initiation and Perseveration30.88 ±5.7231.40±5.2630.38±6.110.318 Construction5.39± 1-325.57±0.985.21 ± 1.560.090 Conceptualization3305 ±5.5134.48 ±4.8731.70 ±5.740.001 Memory20.03 ±4.3320.92 ±3-6119-18±4.780.009Note:EOD: onset <age 60; LOD: onset ≥age 60. SD = standard deviation.TABLE 5Comparison of cognitive functioning (per the subscales of the MMSE and MDRS at baseline) between early-onset-of-depression (EOD) and late-onset-of-depression (LOD) groups, adjusted means, with age and level of education as covariates (ANCOVA)Onset of DepressionEODLODPMini-Mental State Exam (MMSE), baseline Orientation9.659.430.113 Registration2.973.000.072 Calculation3-673.870.440 Language7.307.190.378 Recall2.082.110.838 Construction0.710.690.748Mattis Dementia Rating Scale (MDRS), baseline Attention34.7034.940.471 Initiation and Perseveration30.6431.240.470 Construction5.415.410.997 Conceptualization33.6832.550.146 Memory20.2919.880.513Note:EOD: onset <age 60; LOD: onset ≥age 60. Multivariate ANCOVA revealed no significant difference between the two groups (EOD vs. LOD) with respect to performance on the subscales of the MDRS and the MMSE (Wilks F[1, 184] = 0.92; P>0.05).TABLE 6Chi-square comparison of the proportions of early-onset-of-depression (EOD) vs. late-onset-of-depression (LOD) patients with dementia as defined by a Mattis Dementia Rating Scale (MDRS) score <123Onset of DepressionTotal Group (N=191)EOD (n = 92)LOD (n = 99)PMDRS≥123115 (60.2%)63 (68.5%)52 (52.5%)0.025MDRS<12376 (39-8%)29 (31.5%)47 (47.5%)Note:EOD: onset <age 60; LOD: onset ≥age 60. Odds ratio (OR)= 1.96.TABLE 7Comparison of changes in Mini-Mental State Exam score for early-onset and late-onset (EOD and LOD) subgroups of the dementia population (MDRS< 123), mean ± SDMini-Mental State ExamAt BaselineAt DischargePTotal group (EOD and LOD; N=31)25.21 ±30125.50±3120.562Early-onset depression (EOD; n= 15)24.93 ±2.6725.50±3-270.468Late-onset depression (LOD; n = 16)25.44 ±3-482538±3-260.931Note:EOD: onset <age 60; LOD: onset ≥age 60; MDRS = Mattis Dementia Rating Scale; SD = standard deviation.We gratefully acknowledge the efforts of the Psychiatry Day Hospital staff at Baycrest Centre and Dr. A. Steingart, for creating and maintaining the database used in this study.Dr. Simard is supported by a grant from the Alzheimer's Society of Canada and the Kunin-Lunenfeld Applied Research Unit of Baycrest Centre. Dr. van Reekum is supported by the Kunin-Lunenfeld Applied Research Unit of Baycrest Centre.Regular ArticlesLate-Life Depression as a Possible Predictor of Dementia: Cross-Sectional and Short-Term Follow-Up ResultsRobertvan ReekumM.D., FRCPC*robert.vanreekum@utoronto.caMartineSimardPh.D.DianaClarkeB.Sc.Malcolm A.BinnsM.Sc.DavidConnM.B., FRCPCBaycrest Centre for Geriatric Care, North York, Ontario, Canada*Address correspondence to Dr. van Reekum, Department of Psychiatry, Baycrest Centre for Geriatric Care, 3560 Bathurst St., North York, Ontario, M6A 2E1 CanadaThe authors explored cognitive functioning of a group of elderly subjects with depression. The group as a whole, and, in particular, the late-onset group (LOD), demonstrated cognitive impairment on the Mattis Dementia Rating Scale (MDRS). Subgroup differences were significant at P=0.004. This between-group difference was not seen when age and level of education were controlled. In the LOD group, 47.5% (vs. 31.5% of the early-onset group [P=0.025]), scored below the cutoff for dementia. Age-at-onset status in a logistic regression model predicted MDRS category, and treatment of the depression had little effect on cognition. Results support the hypothesis that late-life depression, particularly LOD, is associated with cognitive impairment that may represent early AD.The era of new treatments for Alzheimer's disease (AD) and related disorders is upon us.1–4 Even greater hope, however, is presented by the possibility that this disorder may actually be prevented or delayed. This strategy will require the ability to predict an increased risk of future occurrence in individuals who do not currently meet the criteria for AD.5,6 One possible predictor of future AD may be late-life depression.Our understanding of the relationship between pre-AD depression and AD has evolved over the last two decades. The early studies of Wells7 and Caine8 suggested that the “pseudodementia” of late-life depression was reversible with treatment for the depression, and hence this group was not expected to develop dementia. Kral's9,10 naturalistic data suggested instead that late-life depression in the presence of cognitive impairment may be an early or “prodromal” sign of impending AD. Alexopoulos et al.11 followed a similar clinical group for approximately 34 months and found that “irreversible dementia” (i.e., DSM-III-R12 dementia in the absence of depression) occurred in 10 of 23 subjects with initially reversible dementia (43%) and in 4 of 34 subjects (12%; P<0.01) who were initially only depressed. The risk ratio was 4.69. Alexopoulos' data were more systematic than the earlier research and included a control group. However, the outcome assessment was not blinded to initial status, and the two groups differed in terms of the severity of depression at baseline. Other research13,14 began to suggest that late-life depression confers a high risk for dementia even in the absence of objectively verifiable significant cognitive impairment.Jorm et al.'s15 initial analysis of pooled data from available case-control studies found a relative risk (RR) of 1.82 for developing AD in those with a pre-AD history of depression, and this finding was supported by Speck et al.16 These data appear to suggest that a lifetime history of depression is associated with increased risk of AD. However, when Jorm et al.15 analyzed data by subgroup, they found that the RR in the late-onset depression (LOD) subgroup (cutoff age not given) was 2.44, whereas that for the early-onset (EOD) group revealed no increased risk of AD (RR=1.01). Other data17–19 also suggest that it is the LOD subgroup, in particular, who are at increased risk of developing AD.One question that remains to be addressed is whether identified predictors of AD are simply markers for the disease, or whether they are signs of the disease process already at work, but not yet at the level of causing the classical signs and symptoms of AD. There is growing evidence20–22 that changes in the brain are occurring before the full expression of AD, suggesting that a “preclinical” or “prodromal” condition exists. Hence, it is at least possible that late-onset depression is an early manifestation of AD, rather than simply a marker of future disease onset.In summary, there is considerable preliminary evidence for an association between depression and subsequent onset of dementia, especially when the depression 1) occurs in elderly patients; 2) is associated with reversible cognitive impairment; and 3) has its first onset later in life. However, significant limitations to the data exist, given that most of the evidence is derived from naturalistic follow-up studies or case-control studies. We do not yet know the incidence of AD in these populations, and, therefore, larger populations of depressed elderly patients will ultimately need to be followed over long periods in an appropriate prospective cohort study. In the interim, cross-sectional and short-term follow-up data may be valuable if, in fact, late-life depression is an early manifestation of AD, because we might expect there to be early evidence of cognitive impairment even in this prodromal stage.The hypothesis behind the current research is that late-life depression, especially of late onset and/or with reversible cognitive impairment, is associated with dementia, and indeed is likely to be a prodromal feature of AD for a large subgroup of the LOD population. Corollaries of this hypothesis that may be addressed with cross-sectional data might include the following: 1) Cognitive impairment is likely to be frequent in elderly patients with depression and may be more frequent or more severe in those with LOD; 2) The cognitive impairment seen is likely to resemble that seen in early AD; and 3) Cognitive impairment in the LOD group, or in the group with cognitive impairment equivalent to those with dementia, may be less likely to improve with treatment for the depression than is the impairment in the EOD group. The objective for this research is to add to the available knowledge regarding the relationship between pre-AD depression and subsequent onset of AD, in the hope that these data will ultimately assist in developing clinical markers for predicting AD, which, in turn, will facilitate the testing of AD prevention strategies. This knowledge may also contribute to our understanding of the pathophysiology of AD and to our knowledge regarding the outcome of late-life depression.SUBJECTS AND METHODSSubjectsThe Department of Psychiatry at Baycrest Centre for Geriatric Care, in Toronto, Canada, offers a day hospital for treating elderly persons with depression and related disorders. Multidisciplinary treatment is provided, including medical and psychiatric care for mood disorders, and a host of therapies, in an intensive program lasting an average of 119 days. Clinical data at admission to and discharge from the program have been systematically collected for more than 10 years and coded onto a computerized database. This is the same database used by Steingart and Herrmann;19 however the sample is now much larger, and the current study did not enforce the requirement that subjects needed to have been previously hospitalized for depression.There were 667 possible subjects in the database, and, of these, 452 had a diagnosis of “major depressive episode or disorder” (as assessed by the attending psychiatrist per the DSM manuals appropriate to the time period). However, some of these records represented repeat admissions; after taking data from only the first admissions, there remained 331 subjects, and 264 subjects remained after we excluded those with a history of central nervous system disease, including dementia of any type (as diagnosed by the admitting psychiatrist). This was narrowed to 245 subjects for whom data on age at onset of first episode of depression were available. This represents the study sample; however, the sample size for some of the analyses is smaller because Mini-Mental State Exam (MMSE23) and Mattis Dementia Rating Scale (MDRS24) data were not available (largely because of the clinical nature of the database) for all subjects (n=229 for admission MMSE; n=125 for discharge MMSE; and n=191 for admission MDRS).MethodsThe measures of cognitive function used by the day hospital include the MMSE and the MDRS. The Hamilton Rating Scale for Depression (Ham-D)25 is used as a measure of the severity of depressive symptoms. All of these data, as well as demographic and other health-related data, are collected at admission into the program by the day hospital staff. The MMSE is collected at discharge as well as at admission. The MDRS is administered by a psychologist, and the other scales by healthcare professionals (nurse, social worker, or occupational therapist).The analyses used are described in the title of each table. All comparisons were evaluated for statistical significance, adjusting for multiple comparisons with the Bonferroni correction (0.05/number of comparisons in the table). For example, there are eight comparisons in Table 1; only those differences with P<0.006 would be accepted as significant.RESULTSTable 1 presents the demographic and clinical characteristics of the groups; it shows that the subjects are, on average, in their mid-70s, and 73.9% are women. Less than 20% of the group had more than high school training. A significant difference in age and a trend-level difference in level of education were found, with the LOD group being both older and less well educated. The clinical characteristics at admission that are relevant to depression in the two groups were similar, with no significant differences in length of stay, Ham-D score at admission, rate of major depression as the primary Axis I diagnosis (note that those subjects who had another Axis I disorder listed as the primary diagnosis received a diagnosis of depression as a secondary diagnosis), and frequency of Axis II diagnoses. However, there was a trend-level difference seen in Ham-D scores at discharge, with the LOD group having more symptoms at discharge (mean Ham-D=11.3) than the EOD group (mean Ham-D=9.4; P=0.05). Both groups averaged well below the cutoff score for depression (17) on the Ham-D at discharge.Table 2 presents the cognitive functioning of the study sample, and the EOD and LOD subgroups, as measured by the MMSE at admission and discharge and by the MDRS at admission. The LOD group shows lower functioning on the MMSE at baseline, and there is a trend-level difference in MMSE score at discharge; however the clinical significance of these small differences is questionable. The MDRS, on the other hand, shows a clinically and statistically significant difference of nearly seven points, with the LOD group averaging below the 123 cutoff score for dementia.24 As described in the note to the table, the change in MMSE from admission to discharge was statistically significant, at P<0.05 for the entire group and for the EOD group, but not for the LOD group. The magnitude of the differences was small for all groups, with the largest magnitude of average difference seen in the LOD group at just over one point. Because of the difference in age and level of education between the two groups, the EOD-vs.-LOD comparisons were repeated (Table 3; ANCOVAs) while controlling for these covariates; no significant differences remained, and the LOD group's mean adjusted MDRS score no longer remained in the dementia range.Table 4 shows that the groups differed significantly on the orientation subscale of the MMSE and on the conceptualization subscale of the MDRS. There were strong trend differences between the MMSE Language, and the MDRS Memory subscales and a weak trend difference on the construction subscale of the MDRS. For all of these comparisons, the LOD group was more impaired than the EOD group. These differences were not seen when age and level of education were covaried (Table 5).Table 6 shows that nearly 40% of the entire group scored below 123 on the MDRS. The two subgroups differed (P=0.025) in the frequency of scoring below this threshold, with the LOD group having a larger proportion of subjects (n=47, or 47.5%) scoring below threshold than the EOD group (n=29, or 31.5%). The odds ratio (OR) for this comparison was 1.96.Table 7 shows that all the MMSE scores for the groups with MDRS scores in the dementia range are about 25. There is very little change in these scores over the course of admission to the Day Hospital.Logistic regression analyses, with MDRS status (score greater than or less than 123) as dependent variable were also completed. The first analysis included all possible subjects in the database, including those with CNS disease (including dementia), those with and without an admitting diagnosis of depression, and those returning to the program for repeat treatment (maximum of four repeats); 667 possible subjects were available, but only 353 had complete data. Level of education (R=0.228; P<0.0001; OR: 0.60), age decile (R=0.176; P<0.0001; OR: 2.16), presence of CNS disease (R=0.144; P=0.0005; OR: 2.78), and age at onset of depression ([EOD or LOD] R=0.060; P=0.05; OR: 1.63) all entered the model. Severity of depression (Ham-D score greater than or less than 17) and gender did not enter the model. When this analysis was repeated in the absence of age and education as covariates, there were 356 possible subjects, and the model included only age at onset of depression (R=0.169; P=0.0001; OR: 2.44) and presence of CNS disease (R=0.026; P=0.026; OR: 1.79). A third logistic regression analysis controlled for age effects by creating a new dependent variable based on data from a community sample of elderly subjects,26 which suggested that the effects of age on MDRS score could be predicted by the equation X=MDRS score − 0.08 (age minus mean age of sample). In this analysis, 355 possible subjects were included (same criteria as that for the previous two regression analyses), and age-at-onset category (R=0.207; P<0.0001) and education level (R=0.203; P<0.0001) were the only two variables to enter the model.DISCUSSIONA number of potential selection biases exist in regard to the day hospital. Although Baycrest Centre's outpatient programs, such as the Day Hospital for Depression, are nondenominational, they tend to attract primarily members of the Jewish community. The day hospital is a tertiary-care treatment program for elderly patients with depression and related disorders, and of course this may further select the population. Also, the program is intensive, with an expectation of attendance at most of the 4-day-per-week activities.The program is geared to those who may best benefit from multidisciplinary treatment, with a strong emphasis on various psychotherapies, and therefore individuals who are felt by the team to have cognitive impairments that would prevent progress within the program are excluded. Despite this exclusion, some individuals who were felt to have relatively mild dementia have been admitted into the program; they were excluded, however, in this study (with the exception of the regression analyses).Other limitations of the study include its very brief period of follow-up, reliance on clinical diagnoses (including the admitting psychiatrist's lack of diagnosis of dementia in subjects who were included in the study and who clearly manifested some cognitive impairment), missing data, and post-hoc group formation. Despite these limitations, this group of Day Hospital for Depression attenders provided clinical, cross-sectional, and short-term follow-up data that are broadly supportive of the hypothesis that in some individuals, late-life depression is a prodrome of dementia. In particular, the MDRS mean score of 120.9 in the LOD group suggested that the LOD group as a whole was scoring in the range that is generally considered to be indicative of dementia, although age and education contribute to the low score.Although this study did not have a normal-comparison population, a healthy, community-dwelling elderly population scored much better on the MDRS than than did the LOD group in this study.27 Montgomery and Costa28 studied groups of healthy, community-dwelling elderly people (65 to 81 years old) and found that only 3 of 85 subjects had an MDRS score of 121 or less. When one considers the selection biases operating at the level of the Day Hospital admission criteria (cognitively well enough to benefit from the program) and the study's exclusion (with the exception of the regression analyses) of individuals with a clinical diagnosis of dementia or other CNS illness, these data become even more compelling.However, the need for analyses controlling for age and level of education was suggested by the evidence that MDRS subscale scores correlate with age and educational level in normal, community-dwelling subjects.27 The analyses that controlled for these factors (Table 3) eliminated the differences between the LOD and EOD groups, and this, of course, weakens support for the hypothesis that the LOD group, in particular, is made up of a large proportion of individuals with prodromal AD. However, in this sample, the LOD group were both older (by more than 5 years (P=0.001) and tended to be less well educated (P=0.06; Table 1), suggesting that age, education, and age at onset of depression are related. Given that the incidence of AD varies with age,29 it may be that another of the effects of age on the sample is to increase the incidence of prodromal AD, and it follows that this would have the greatest effect in the LOD group. If so, then controlling for age would have the effect of masking the impact that a greater frequency of prodromal dementia would have in creating differences between the groups.Similarly, although the lower educational level in the LOD group would be expected to drag down the MDRS score, it may also be predicted that the lower educational level of the LOD group would affect those with prodromal AD, vs. the impact in the EOD group who have prodromal AD, if their higher education “compensates” for neuronal damage.30 Hence both age and education may have opposing effects on cognitive assessments in the groups as a whole (i.e., they may have caused the apparent differences in MMSE and MDRS scores between groups) vs. their effects in the subgroup of subjects who were dementing (i.e., in these subjects the effects of age and education are true effects that would be expected to be masked if age and education are covaried).Ultimately, knowledge about the diagnostic status of the subjects (i.e., with or without dementia) would be needed to address this issue. Because these data are unavailable, we report both the covaried and non-covaried analyses herein. However, it is notable that the differences on the MDRS as a function of age and education, in a population without dementia, as reported by Schmidt et al.,27 are small. The mean MDRS score in the group age 50–59 years was 141.8, and that in the group age 70–79 was 140.8 (SDs approximately 3.0). Those with 4–9 years of education had a mean MDRS score of 140.2, and those with college or university education scored 142.3 (SD=4.2 and 1.7, respectively). Hence, the effects of age and education in normal elderly subjects are relatively small, and this suggests that the effects of age and education in the current sample are likely to be weak unless they are associated with a third factor, such as onset of prodromal dementia. Neither of the subgroups reported on by Schmidt et al.26 scored in the low range seen in the LOD group in this study.To further assess the contributions of age, education, and age at onset of depression on MDRS scores in this study, logistic regression analyses were completed (not tabulated; see Results). The analysis showed that for the entire available data-set, age decile, education level, presence of CNS disease (including dementia), and age at onset of depression (EOD or LOD) all entered the model. When the analysis was repeated in the absence of age and education as covariates, age-at-onset category was the strongest predictor of MDRS status, and the magnitude of R was similar to that found for age in the first analysis. Finally, a third logistic regression analysis controlling for age, using Schmidt et al.'s data,27 again showed that age at onset of depression was the strongest predictor of MDRS status. These analyses suggest that age-at-onset independently contributes to the likelihood of scoring below the cutoff score for dementia of 123 on the MDRS.The nature of the cognitive impairments seen in the LOD group, as compared with the EOD group and as assessed by the subscales of the MMSE and MDRS (when age and level of education were not controlled for [Table 3]), also supports the hypothesis that the LOD group is made up of a large proportion of individuals with prodromal AD. These impairments are seen in individuals who do not have AD, but have subtle cognitive impairment on testing and who are at risk for developing AD in follow-up. Several studies20,31–37 have demonstrated that impairments in memory, including impairments in orientation, are associated with subsequent onset of AD. Similarly, data also exist showing that language and abstract reasoning (“conceptualization” on the MDRS) deficits are present in mild stages of AD and/or predict future onset of AD.31,32,34,36,38 It is also interesting to note that the cognitive deficits found in this study are most suggestive of left frontal-temporal dysfunction, and this is congruent with the left frontal-temporal hypometabolism reported in a previous positron emission tomography (PET) study of AD patients with depression.39The proportion of subjects who scored below the MDRS cutoff for dementia, according to the manual for the scale,26 was large, at nearly 40%, and largest in the LOD subgroup, at nearly 50% (47.5%), which differed from the EOD group, at 31.5%. This finding suggests that nearly half of the LOD group are functioning at a cognitive level that is typical for early dementia. Age and education differences between the EOD and LOD group are likely to contribute to the observed difference in proportion. The OR of 1.96 suggests that those scoring below cutoff for dementia were nearly twice as likely to have LOD than EOD.Finally, the data describing the effects of treatment for depression on cognition (as assessed by pre–post-treatment MMSE scores [Table 2]) show that although the cognitive impairment seen for the groups as a whole improved somewhat (but at a statistically insignificant level for the LOD group), the improvement was modest, suggesting that not all of the impairment seen is “reversible.” This appeared to be the case to an even greater extent for those subjects who had more severe impairment (i.e., scored below the dementia cutoff score on the MDRS [Table 7]), given that even smaller-magnitude improvements were seen in these subjects than were seen for the full groups in Table 2.Interestingly, the LOD group, with initial MDRS less than 123, actually demonstrated a very small, statistically insignificant, decline in cognitive functioning as measured by the MMSE over the course of their treatment. Of course, the MMSE is limited in its sensitivity and scope of cognitive assessment, and this limitation may well have limited the ability of the data to demonstrate change. Nonetheless, the psychometric qualities of the MMSE have been reviewed by Thompson et al.40 as being adequate for research purposes “as a brief screening instrument to detect cognitive impairment” (p.302), and Nelson et al.41 reviewed the evidence that the MMSE can record cognitive improvement, when it exists, upon treatment for depression. Hence, the lack of change on the MMSE in the LOD group, particularly those scoring positive for dementia on the MDRS at admission, suggests that this group did not improve cognitively with treatment for the depression, and this finding is again consistent with the hypothesis that subjects in this group are already evidencing prodromal dementia.Overall, the results of this study, in combination with the available literature, suggest that LOD may well represent prodromal AD for at least some of the individuals assessed. A reasonable hypothesis is that the presence of particular cognitive impairments at a severe enough level in those with LOD may identify a subgroup of the LOD population who are at even greater risk of having prodromal AD. The nature of cognitive testing done in the early studies on late-life depression is relatively limited, and the MMSE and the MDRS are not the equivalent of a reasoned and thorough neuropsychological assessment. Hence, another limitation of the current data is that we do not know with any certainty which cognitive markers, when combined with LOD, are most likely to be predictive of AD. Hence, a reasonable approach for future studies would be to combine the data regarding cognitive predictors of AD20,31–38 with the data on LOD. It is likely that those individuals with LOD and persistent memory, language, and conceptualization impairments are at very high risk for the development of AD. Furthermore, it may be that this risk is even greater in those with other signs of CNS disease13 and in those with APO-E ϵ4 alleles (especially those homozygous for this allele).Clearly, a prospective cohort study examining this hypothesis will ultimately be required, but it is hoped that the data presented here will stimulate interest in such a study and that it will help to shape the nature of the cohorts and the testing paradigms used. 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