ARCHIVAL REPORT

Small Vessel Disease, but Neither Amyloid Load nor Metabolic Deficit, Is Dependent on Age at Onset in Alzheimer’s Disease Marion Ortner, Alexander Kurz, Panagiotis Alexopoulos, Florian Auer, Janine Diehl-Schmid, Alexander Drzezga, Stefan Förster, Hans Förstl, Robert Perneczky, Christian Sorg, Behrooz H. Yousefi, and Timo Grimmer Background: There is controversy concerning whether Alzheimer’s disease (AD) with early onset is distinct from AD with late onset with regard to amyloid pathology and neuronal metabolic deficit. We hypothesized that compared with patients with early-onset AD, patients with late-onset AD have more comorbid small vessel disease (SVD) contributing to clinical severity, whereas there are no differences in amyloid pathology and neuronal metabolic deficit. Methods: The study included two groups of patients with probable AD dementia with evidence of the AD pathophysiologic process: 24 patients with age at onset ⬍60 years old and 36 patients with age at onset ⬎70 years old. Amyloid deposition was assessed using carbon-11–labeled Pittsburgh compound B positron emission tomography, comorbid SVD was assessed using magnetic resonance imaging, and neuronal metabolic deficit was assessed using fluorodeoxyglucose positron emission tomography. Group differences of global and regional distribution of pathology were explored using region of interest and voxel-based analyses, respectively, carefully controlling for the influence of dementia severity, apolipoprotein E genotype, and in particular SVD. The pattern of cognitive impairment was determined using z scores of the subtests of the Consortium to Establish a Registry for Alzheimer’s Disease Neuropsychological Assessment Battery. Results: Patients with late-onset AD showed a significantly greater amount of SVD. No statistically significant differences in global or regional amyloid deposition or neuronal metabolic deficit between the two groups were revealed. However, when not controlling for SVD, subtle differences in fluorodeoxyglucose uptake between early-onset AD and late-onset AD groups were detectable. There were no significant differences regarding cognitive functioning. Conclusions: Age at onset does not influence amyloid deposition or neuronal metabolic deficit in AD. The greater extent of SVD in lateonset AD influences the association between neuronal metabolic deficit and clinical symptoms.

Key Words: AD, age at onset, Alzheimer’s disease, amyloid load, metabolic deficit, small vessel disease

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ince Alois Alzheimer’s seminal publications (1,2) there has been continuing controversy concerning whether Alzheimer’s disease (AD) with early onset and AD with late onset represent variants of the same clinicopathologic entity or are separate brain diseases with distinct etiology, pathophysiology, and clinical symptoms (3,4). Although no qualitative pathologic or clinical differences have been identified, many studies

From the Departments of Psychiatry and Psychotherapy (MO, AK, PA, JD-S, HF, RP, CS, TG), Nuclear Medicine (SF), Diagnostic and Interventional Neuroradiology (FA) Klinikum rechts der Isar der Technischen Universität München, Munich, Germany; Pharmaceutical Radiochemistry (BHY), Faculties of Chemistry and Medicine, Technische Universität München, Garching, Germany; Department of Nuclear Medicine (AD), University Köln, Cologne, Germany; Neuroepidemiology and Ageing Research Unit (RP), School of Public Health, Faculty of Medicine, The Imperial College of Science, Technology, and Medicine, London; and West London Cognitive Disorders Treatment and Research Unit (RP), West London Mental Health Trust, London, United Kingdom. Address correspondence to Marion Ortner, M.D., Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Technische Universität München, Möhlstr. 26, 81675 München, Germany; E-mail: marion. [email protected]. Received Oct 2, 2013; revised Dec 30, 2013; accepted Jan 17, 2014.

0006-3223/$36.00 http://dx.doi.org/10.1016/j.biopsych.2014.01.019

reported quantitative heterogeneity of early-onset AD and lateonset AD with regard to core features of the disease (neurofibrillary tangles, senile plaques, amyloid deposition, neuronal metabolic deficit, and pattern of cognitive symptoms). This heterogeneity is considered by DSM-IV, which treats earlyonset AD and late-onset AD as disease variants dependent on age of onset. Previous studies demonstrated more severe loss of neurons (5) and synapses (6) and higher neuritic plaque count in the frontal parietal lobe (6) in patients with early-onset AD. A more severe neuronal metabolic deficit (7,8) and an increased amyloid deposition (9,10) have been demonstrated in vivo in early-onset AD using the positron emission tomography (PET) tracers fluorodeoxyglucose (FDG) (11) (for neuronal metabolic deficit) and carbon-11–labeled Pittsburgh compound B ([11C]PiB) (12) (for amyloid deposition). With regard to pattern of cognitive symptoms, atypical presentations such as prominent language or visuospatial impairment (13,14) and more severe deficits in praxis and attention skills (13,14) were found to be more frequent in patients with early-onset AD. Patients with late-onset AD were reported to score significantly lower on memory and naming tests and orientation (13–15). Amyloid deposition, neuronal metabolic deficit, and cognitive functioning, which we use as indicators and consequences of AD pathology in the present study, are influenced by numerous factors, which need to be considered when comparing potential subgroups or variants of AD. Specifically, amyloid deposition (16), neuronal metabolic deficit (17), and cognitive functioning (18) are BIOL PSYCHIATRY 2014;]:]]]–]]] & 2014 Society of Biological Psychiatry

2 BIOL PSYCHIATRY 2014;]:]]]–]]] dependent on severity of dementia, which is a correlate of disease stage. Amyloid deposition (19) and neuronal metabolic deficit (20) are enhanced by the presence of the apolipoprotein E (APOE) ε4 allele. Another factor that significantly influences the manifestation and possibly the development of AD pathology is comorbid cerebrovascular lesions (CVL), in particular small vessel changes (21). The prevalence of comorbid CVL increases with age (22) and is a common histopathologic finding in patients with AD (23). In the presence of CVL, a lower density of amyloid plaques and neurofibrillary tangles is found at comparable dementia severity (24) suggesting that AD and CVL have additive effects on the development of clinical symptoms. The consequence of small vessel disease (SVD) can be assessed using magnetic resonance imaging (MRI); white matter hyperintensities (WMH) can be evaluated with fluid-attenuated inversion recovery (FLAIR) MRI, and lacunar infarcts can be evaluated with T1-weighted MRI (25). The extent of WMH is a risk factor for AD dementia (26). In patients with late-onset AD, WMH are more pronounced (27) and are associated with an increased rate of amyloid deposition (28). The above-mentioned parameters that influence amyloid deposition, neuronal metabolic deficit, and cognitive functioning were not consistently taken into account in previous studies comparing early-onset AD and late-onset AD. We hypothesized that early-onset AD and late-onset AD differ neither with regard to core features of AD pathology that are demonstrable in vivo (i.e., amyloid deposition and neuronal metabolic deficit) nor in terms of clinical symptoms when clinical severity, APOE genotype, and SVD are factored in. We compared the quantity and regional distribution of amyloid deposition, the degree and regional pattern of neuronal metabolic deficit, and the pattern of cognitive impairment between patients with early-onset AD and patients with late-onset AD, controlling for overall severity of dementia, APOE genotype, sex, and amount of SVD. Additionally, we assessed the relevance of controlling for SVD when comparing amyloid deposition and neuronal metabolic deficits between patients with early-onset AD and patients with late-onset AD because this was consistently not done in previous studies.

Methods and Materials Patient Recruitment and Inclusion and Exclusion Criteria Patients were recruited from the research outpatient unit for cognitive disorders at the Department of Psychiatry, Klinikum rechts der Isar, Technische Universitaet Muenchen, Munich, Germany. The patients had been referred for diagnostic evaluation of cognitive impairment by general practitioners, neurologists, psychiatrists, or other institutions and had undergone a standardized diagnostic procedure. The study protocol was approved by the medical faculty’s ethics committee and by radiation protection authorities. All patients provided written informed consent before any study-specific procedures were undertaken. The standard diagnostic work-up included an interview with the patient and an informant; psychiatric, neurologic, and physical examinations; neuropsychological evaluation including the MiniMental State Examination (MMSE) (29) and the Consortium to Establish a Registry for Alzheimer’s Disease Neuropsychological Assessment Battery (30); routine laboratory screening; and APOE genotyping. The severity of cognitive impairment was rated on the Clinical Dementia Rating (CDR) scale (31); the subscale scores were used to calculate the CDR sum of boxes (CDR SOB). Cranial www.sobp.org/journal

M. Ortner et al. MRI was performed to assess structural brain abnormalities. In addition to this, study participants underwent cranial FDG-PET to determine neuronal metabolic deficit and [11C]PiB-PET to assess brain amyloid deposition. All assessments were completed within a 3-months period in each patient. Study participants met the National Institute of Neurological and Communicative Disorders and Stroke and Alzheimer’s Disease and Related Disorders Association diagnostic criteria for probable AD (32). Additionally, patients were required to have AD typical FDG uptake on PET (33) to enhance the likelihood of underlying AD pathology (34) (i.e., hypometabolism in the temporoparietal and posterior cingulate cortex with relative sparing of the primary sensorimotor cortex on visual inspection). Participants also met the new National Institute on Aging and Alzheimer’s Association criteria of probable AD dementia with evidence of the AD pathophysiologic process (35). Patients with very mild to moderate dementia as defined by global CDR scale ratings of .5, 1, or 2 were included. The onset of symptoms was estimated from caregivers’ observations. Because these estimations are often imprecise, we sought to reduce misclassification by defining early-onset AD as an age of onset #60 years and lateonset AD as an age of onset $70 years (“onset groups”). Patients were not included in the study if they met diagnostic criteria for other neurologic or psychiatric disorders, including Parkinson’s disease, normal-pressure hydrocephalus, progressive nuclear palsy, or major depression. Patients were also excluded if they exhibited dilated perivascular spaces or any major abnormalities on MRI. The National Institute of Neurological Disorders and Stroke and the Association International pour la Recherché et l’Enseignement en Neurosciences criteria were used to exclude vascular dementia (36). Patients with other possible causes of cognitive impairment, such as psychotropic medication (e.g., antidepressants, antipsychotics), substance abuse, or major abnormalities in routine blood testing, were not enrolled. Findings on [11C]PiB-PET were not used as inclusion criteria. Laboratory Screen and APOE Genotyping Routine blood screening included a standard serologic chemistry group, complete blood cell count, blood glucose, vitamin B12 and folic acid levels, thyroid hormone levels, and serologic tests for syphilis and Lyme borreliosis. The APOE genotype was determined following a standardized protocol using a polymerase chain reaction–based assay, which simultaneously uses two distinct restriction enzymes (37). Brain Imaging Structural MRI, FDG-PET, and [11C]PiB-PET of the brain were performed using standard procedures as described previously (16). Patients underwent cranial MRI examination on a 1.5-tesla Siemens MAGNETOM Symphony (Siemens Healthcare, Erlangen, Germany) MRI scanner using a standardized imaging protocol that consisted of a three-dimensional T1 dataset (repetition time [TR] ¼ 1520 msec; echo time [TE] ¼ 3.93 msec; matrix ¼ 256  256; flip angle ¼ 151; 1-mm slices); axial T2-weighted turbo spin echo images (TR ¼ 4510 msec; TE ¼ 104 msec; 19 slices; voxel dimensions ¼ .6 mm  .5 mm  6.0 mm); coronal T1-weighted spin echo images (TR ¼ 527 msec; TE ¼ 17 msec; 19 slices; voxel dimensions ¼ .9 mm  .9 mm  6.0 mm); T2-weighted gradient echo images (TR ¼ 725; TE ¼ 29; 19 slices; voxel dimensions ¼ .7 mm  .7 mm  6.0 mm); and axial FLAIR images (TR ¼ 9000 msec; TE ¼ 105 msec; inversion time ¼ 2500 msec; 3-mm slices). A Siemens ECAT HR⫹ PET scanner (Siemens/CTI, Knoxville, Tennessee) was used to obtain FDG-PET images. The patients

M. Ortner et al. received 370 MBq FDG (time of exact dose injection was calculated by measuring radioactivity shortly before) at rest with eyes closed. The patients were positioned with the head parallel to the canthomeatal line within the gantry. Imaging with PET was performed 30 min after injection under standard resting condition (eyes closed in dimmed ambient light) as published previously (38). A sequence of one frame of 10 min and two frames of 5 min was started and later summed into a single frame. Each frame was evaluated to verify adequate count statistics and absence of head motion. Image data were acquired in three-dimensional mode with a total axial field of view of 15.5 cm. A transmission scan was acquired after completion of the emission scan for attenuation correction. The [11C]PiB-PET examination was performed on the same scanner and followed a standardized protocol (39). All patients were injected with 370 MBq [11C]PiB (time of exact dose injection was calculated by measuring radioactivity shortly before) at rest outside the scanner. The patients were placed in the scanner 30 min later. At 40 min after injection, three 10-min frames of data acquisition were started and later summed into a single frame (40–70 min). Each frame was evaluated to verify adequate count statistics and absence of head motion. Acquisition was carried out in three-dimensional mode, and a transmission scan was performed to allow for later attenuation correction. The [11C]PiB and FDG images were coregistered to the high-resolution MRI scans and normalized to the Montreal Neurological Institute space using the warping parameters of the MRI scans to obtain interindividually comparable images. Assessment of SVD The consequences of SVD that could be imaged—lacunes and subcortical WMH—were assessed and used as two independent variables and referred to as SVD in the subsequent analysis. Patients with multiple lacunar infarcts (more than three) or excessive WMH (⬎25% of total white matter) were not included in the study. The amount of lacunes was assessed on axial T1-weighted MRI images. The amount of subcortical WMH was assessed by visual inspection of axial FLAIR images using a standard semiquantitative score that takes number and size of the lesions into account (40) as demonstrated previously (28). The assessment of the WMH was conducted by an experienced neuroradiologist (FA) blinded to time point of examination, patient identification, and all clinical and other imaging data. The rater was trained in using the scale by rating 50 different FLAIR sequences randomly presented two times. Retest reliability was .959. Imaging Preprocessing Amyloid Deposition. A relative measure of global [11C]PiB uptake was obtained by calculating the cerebral-to-cerebellar vermis (C/cv) ratio to control for between-subjects differences in tracer uptake as demonstrated previously (16,41). For this purpose, two anatomic regions of interest were defined, one covering the entire cerebral gray matter and the other covering the cerebellar vermis as a reference region, using an established predefined template (42). Mean standard uptake volume values were calculated for 95% of voxels that showed the highest uptake values for each region of interest (43). The regional distribution of amyloid deposition was examined in a voxel-based manner using statistical parametric mapping version 8 (44). As a preprocessing method for these analyses, spatially normalized individual [11C]PiB images were quantitatively normalized to the cerebellar vermis and smoothed using a Gaussian kernel of 10 mm  10 mm  10 mm.

BIOL PSYCHIATRY 2014;]:]]]–]]] 3 Neuronal Metabolic Deficit. A relative measure of global FDG uptake was obtained similar to the [11C]PiB images with the exception that the pons was used as reference region. Regional neuronal metabolic deficit was analyzed in a voxel-based manner. As a preprocessing method for these analyses, spatially normalized individual FDG images were quantitatively normalized to the pons and smoothed using a Gaussian kernel of 10 mm  10 mm  10 mm. Statistical Analyses The groups of early-onset AD and late-onset AD patients were characterized using descriptive statistics. Group comparisons of all clinical variables were performed using t tests for continuous variables and χ2 tests for categorical variables. All analyses were calculated using IBM SPSS version 20 (IBM Deutschland GmbH, Ehningen, Germany) except voxel-based analyses using statistical parametric mapping version 8 (44). The global amount of amyloid deposition was compared between early-onset AD and late-onset AD using linear regression analysis with C/cv [11C]PiB uptake as dependent variable and onset group as independent variable. The regional distribution of amyloid deposition was compared between onset groups using voxel-based group comparisons of [11C]PiB images. In both calculations, the number of APOE ε4 alleles, the amount of SVD, CDR SOB, and sex were used as control variables. The severity of SVD was compared between early-onset AD and late-onset AD using a linear regression analysis that included SVD as dependent variable; onset group as independent variable; and number of APOE ε4 alleles, CDR SOB, and sex as control variables. The degree of global neuronal metabolic deficit was compared between early-onset AD and late-onset AD using a linear regression analysis with cerebral-to-pons (C/pons ratios) FDG uptake as dependent variable and onset group as independent variable. The regional distribution of neuronal metabolic deficit was examined between onset groups using voxel-based group comparison of FDG images. In both calculations, the number of APOE ε4 alleles, C/cv [11C]PiB uptake, SVD score, CDR SOB, and sex were used as control variables. To explore the relevance of considering SVD for the comparison between early-onset AD and late-onset AD, the latter analysis of regional distribution of neuronal metabolic deficit between onset groups was repeated without including SVD as a control variable. The pattern of cognitive impairment was compared between onset groups using analysis of variance with the z score of each Consortium to Establish a Registry for Alzheimer’s Disease Neuropsychological Assessment Battery subtest as dependent variable, onset group as factor, and CDR SOB as covariate. A significance threshold of .05 was applied for all linear regression analyses. For all voxel-based analyses and analysis of variance, a threshold of .05 corrected for multiple comparisons was applied.

Results The early-onset AD group consisted of 24 patients, and the late-onset AD group consisted of 36 patients. The two groups did not significantly differ in clinical severity and APOE ε4 genotype or MMSE raw score (Table 1). No significant differences of homogeneity of variance between the two groups were observed for C/pons ratios FDG uptake or C/cv [11C]PiB uptake (Levene’s test, p ¼ .567 and p ¼ .564, respectively) or for any region on voxelbased analyses of FDG and [11C]PiB images (F test, p ⬎ .05 and www.sobp.org/journal

M. Ortner et al.

4 BIOL PSYCHIATRY 2014;]:]]]–]]] Table 1. Demographics Variable

Early-Onset AD

Late-Onset AD

p Value

No. Patients Age at Onset (Years) Age at Examination (Years) Sex (Male/Female) CDR SOB MMSE Copies of APOE ε4 WMH Score No. Lacunes [11C]PiB Uptake Ratio FDG Uptake Ratio

24 54.5 ⫾ 4.14 (47–60) 58.4 ⫾ 5.21 (50–68) 12/12 4.02 ⫾ 2.098 (1.5–9.0) 23.4 ⫾ 4.83 (14–30) .8 ⫾ .72 (0–2) 2.7 ⫾ 3.31 (0–15) .0 ⫾ .00 (0–0) 1.86 ⫾ .338 (1.2–2.5) 1.28 ⫾ .122 (1.1–1.5)

36 74.4 ⫾ 3.82 (70–83) 76.5 ⫾ 4.27 (70–84) 22/14 4.14 ⫾ 3.447 (.5–14.0) 23.4 ⫾ 4.67 (8–28) .8 ⫾ .69 (0–2) 14.8 ⫾ 8.9 (0–32) .1 ⫾ .50 (0–3) 1.81 ⫾ .314 (1.0–2.4) 1.30 ⫾ .148 (1.1–1.7)

⬍.001 ⬍.001 .302 .881 .965 .916 ⬍.001 .099 .682 .567

Values represent mean ⫾ SD (range), where appropriate. p values calculated from t tests for continuous variables and χ2 tests for categorical variables. APOE, apolipoprotein E; CDR SOB, Clinical Dementia Rating sum of boxes; [11C]PiB, carbon-11–labeled Pittsburgh compound B; FDG, fluorodeoxyglucose; MMSE, Mini-Mental State Examination; WMH, white matter hyperintensities.

p ⬎ .05, respectively). On visual analysis of the [11C]PiB scans, all patients showed AD-typical tracer uptake in the brain. In a few patients, tracer uptake was unevenly distributed and low in several areas. A [11C]PiB-negative scan was not demonstrated in any patient. There were no statistically significant differences between the onset groups with regard to global amyloid deposition in the linear regression analysis (model, p ¼ .26; coefficient onset group, p ¼ .50) and regional distribution of amyloid deposition in the voxel-based group comparisons (pcorrected ⬎ .05 at all voxels) when clinical severity, SVD, and sex were taken into account. The onset group was not significantly associated with the degree of global neuronal metabolic deficit in the linear regression analysis (model, p ¼ .028; coefficient onset group, p ¼ .32), controlling for number of APOE ε4 alleles, amyloid burden, SVD, clinical severity, and sex. Also, onset groups did not show statistically significant differences in neuronal metabolic deficit in any region in the voxel-based group comparisons (pcorrected ⬎ .05 at all voxels) when these control variables were included in the regression model. When this analysis was repeated without the SVD score, there was a significantly greater neuronal metabolic deficit in the right temporoparietal cortex in the early-onset AD group (pcorrected ⬍ 0.05) (Figure S1 in Supplement 1). Onset groups differed significantly in terms of the amount of WMH (higher in late-onset AD; model, p ⬍ .001; coefficient onset group, p ⬍ .001) when the number of APOE ε4 alleles, clinical severity, and sex were considered. The pattern of cognitive impairment was not significantly different between the onset groups when the overall severity of dementia was taken into account (Table S1 in Supplement 1).

Discussion The present study shows that the amount or distribution of amyloid deposition, the total or regional neuronal metabolic deficit, and the pattern of cognitive impairment are not significantly different in patients with early-onset AD versus patients with late-onset AD when clinical severity, APOE genotype, and SVD are taken into account. As expected, subcortical WMH were more frequent in patients with late-onset AD. The importance of taking clinical severity, APOE genotype, and SVD into account when comparing patients with early-onset AD and patients with late-onset AD is exemplarily demonstrated. When not controlling www.sobp.org/journal

for SVD, differences in regional neuronal metabolic deficits were observed between patients with early-onset AD and patients with late-onset AD. Our findings are at variance with most previous studies. Three previous studies found regions where patients with early-onset AD showed more [11C]PiB uptake than patients with late-onset AD. Rabinovici et al. (9) investigated [11C]PiB binding in 21 patients with early-onset AD and 18 patients with late-onset AD. Controlling for disease duration and severity, but not for APOE genotype or SVD, they found a small number of voxels (n ¼ 49) in the left fusiform gyrus with higher [11C]PiB binding in patients with early-onset AD. Choo et al. (10) matched 11 patients with early-onset AD and 11 patients with late-onset AD for severity, duration of illness, and APOE genotype but not for SVD. In this study, patients with early-onset AD exhibited significantly higher global [11C]PiB binding compared with patients with late-onset AD. However, 45% of subjects in the late-onset AD group were [11C]PiB-negative. Ossenkoppele et al. (15) found comparable global but increased parietal [11C]PiB uptake in 45 patients with early-onset AD compared with 46 patients with late-onset AD, controlling for education, MMSE raw score, and APOE genotype but not for SVD. Also, no correction for multiple comparisons was included. Four previous studies reported decreased regional FDG uptake in patients with early-onset AD. Kim et al. (8) found more regional neuronal metabolic deficits in 66 patients with early-onset AD than in 39 patients with late-onset AD, controlling for severity of disease. However, the analysis was not adjusted for SVD, APOE genotype, or multiple comparisons. Rabinovici et al. (9) investigated regional metabolic deficits of 18 patients with early-onset AD and 16 patients with late-onset AD who were matched for disease duration and clinical severity. Patients with early-onset AD showed significantly (pcorrect ⬍ .05) lower regional neuronal metabolism after controlling for age, education, and MMSE. However, SVD and APOE genotype were not taken into consideration. Mielke et al. (7) found significantly more regional neuronal metabolic deficits in 14 patients with early-onset AD compared with 24 patients with late-onset AD (pcorrect ¼ .02), but they did not control for severity of disease, APOE genotype, or SVD. A study by Ossenkoppele et al. (15) found no differences in global or regional FDG uptake between patients with early-onset AD and patients with late-onset AD after adjusting for education, MMSE, and APOE genotype but not for SVD.

M. Ortner et al. Several studies that controlled for disease severity and multiple testing demonstrated differences between patients with earlyonset AD and patients with late-onset AD with regard to raw values of psychometric tests. Koss et al. (13) compared the performance on the Consortium to Establish a Registry for Alzheimer’s Disease Neuropsychological Assessment Battery of 98 patients with early-onset AD and 323 patients with late-onset AD and showed that patients with early-onset AD performed more poorly on praxis, whereas naming was more impaired in patients with late-onset AD. Smits et al. (14) compared 81 patients with early-onset AD and 91 patients with late-onset AD with comparable MMSE and Cambridge Cognitive Examination scores in regard to memory, language, visuospatial functioning, executive functioning, and attention. Patients with early-onset AD performed significantly worse on visuospatial functioning, executive functioning, and attention. Possible explanations for not detecting differences on neuropsychological tests in our study include the smaller sample size, the low sensitivity of the tests used, or the adjustment of test results to the appropriate normative data. Despite the fact that MMSE raw values were not significantly different between patients with early-onset AD and patients with late-onset AD, MMSE z scores were significantly different in an ANOVA controlled for disease severity; this may be a possible confounding factor in other studies that used the MMSE as an indirect marker of disease severity. The discrepancies between the present study and previous studies could be explained partly by the fact that to our knowledge this is the first study taking cerebrovascular comorbidity into account. In accordance with a previous study (27), we found a higher prevalence of WMH in patients with late-onset AD compared with patients with early-onset AD. The prevalence of WMH increases with age (22), and mixed pathology is a common finding in patients with AD (23). Because cerebral SVD contributes to the clinical symptoms of dementia in addition to and independently of changes typical of AD (21), fewer amyloid plaques and neurofibrillary tangles, lower amyloid deposition, and fewer metabolic deficits may be found at the same level of clinical severity in individuals who have both pathologies compared with patients who have AD with no comorbid SVD (24). If cerebrovascular admixture is not taken into account, studies comparing early-onset AD and late-onset AD are likely to demonstrate that AD pathology is more severe in the early-onset than in the late-onset cases. In this study, the statistically significant neuronal metabolic deficit in patients with early-onset AD disappeared after controlling for SVD. Patients with excessive WMH or multiple lacunar infarcts were excluded from this study. Including patients with pronounced vascular comorbidity might have accentuated the results. The present study is limited because the clinical diagnosis of AD was not confirmed by postmortem examination, and misclassification of patients as having AD might have influenced the strength of the associations. However, patients were enrolled only if they met both the National Institute of Neurological and Communicative Disorders and Stroke and Alzheimer’s Disease and Related Disorders Association diagnostic criteria for probable AD (32) and the National Institute on Aging and Alzheimer’s Association criteria of probable AD dementia with evidence of the AD pathophysiologic process by showing AD-typical findings on FDG-PET (35). Compared with previous PET studies that revealed significant differences between patients with early-onset AD and patients with late-onset AD, our study population was relatively large. However, subtle differences between both groups might have been overlooked.

BIOL PSYCHIATRY 2014;]:]]]–]]] 5 A strength of the present study is that we tried to reduce the likelihood of misclassifying patients using restrictive cutoffs (age of onset #60 years for early-onset AD and $70 years for lateonset AD, respectively) because the variable age of onset often depends on the sometimes unreliable memory of caregivers. In addition, we included all known factors that influence the association between AD pathology and clinical symptoms and adequately controlled for multiple testing. In conclusion, we found no differences between patients with early-onset AD and patients with late-onset AD in regard to global and regional cerebral amyloid burden measured by [11C]PiB-PET and in regard to neuronal metabolic deficits measured by [18F] FDG-PET after correcting for multiple comparisons and controlling for clinical severity, APOE genotype, SVD, and sex. Patients with late-onset AD had significantly more subcortical WMH, which made a small but significant contribution in addition to AD pathology on clinical severity. Our results are in accordance with the intention of the American Psychiatric Association to abolish the differentiation of AD into early-onset AD and late-onset AD in DSM-V. This work was supported in part by the German Research Foundation (Deutsche Forschungsgemeinschaft) (Grant No. HE 4560/1-2 to AD and Grant Nos. DR 445/3-1 and DR 445/4-1 to AD and AK), and by a grant from the Kommission für Klinische Forschung (KKF-grant) for clinical research of the Technische Universität München (to AD and TG). We thank Dr. Victoria Kehl from the Department of Statistics and Epidemiology for her statistical advice. Presented at the Alzheimer’s Association International Conference, July 18, 2012, Vancouver, British Columbia, Canada. The authors report no biomedical financial interests or potential conflicts of interest. Supplementary material cited in this article is available online at http://dx.doi.org/10.1016/j.biopsych.2014.01.019. 1. Alzheimer A (1906): Über einen eigenartigen schweren Erkrankungsprozeß der Hirnrinde. Neurologisches Centralblatt 1129–1136. 2. Alzheimer A (1907): Über eine eigenartige Erkrankung der Hirnrinde. Allgemeine Zeitschrift für Psychiatrie und Pschisch-Gerichtliche Medizin 146–148. 3. Kraepelin E (1910): Psychiatrie: Ein Lehrbuch für Studierende und Ärzte. II. Band Klinische Psychiatrie. 1. Teil, 8th ed. Leipzig: Barth Verlag. 4. Katzman R (1976): The prevalence and malignancy of Alzheimer disease. A major killer. Arch Neurol 33:217–218. 5. Tagliavini F, Pilleri G (1983): Neuronal counts in basal nucleus of Meynert in Alzheimer disease and in simple senile dementia. Lancet 1: 469–470. 6. Bigio EH, Hynan LS, Sontag E, Satumtira S, White CL (2002): Synapse loss is greater in presenile than senile onset Alzheimer disease: Implications for the cognitive reserve hypothesis. Neuropathol Appl Neurobiol 28:218–227. 7. Mielke R, Herholz K, Grond M, Kessler J, Heiss WD (1992): Differences of regional cerebral glucose metabolism between presenile and senile dementia of Alzheimer type. Neurobiol Aging 13:93–98. 8. Kim EJ, Cho SS, Jeong Y, Park KC, Kang SJ, Kang E, et al. (2005): Glucose metabolism in early onset versus late onset Alzheimer’s disease: An SPM analysis of 120 patients. Brain 128:1790–1801. 9. Rabinovici GD, Furst AJ, Alkalay A, Racine CA, O’Neil JP, Janabi M, et al. (2010): Increased metabolic vulnerability in early-onset Alzheimer’s disease is not related to amyloid burden. Brain 133:512–528. 10. Choo IH, Lee DY, Kim JW, Seo EH, Lee DS, Kim YK, et al. (2011): Relationship of amyloid-beta burden with age-at-onset in Alzheimer disease. Am J Geriatr Psychiatry 19:627–634.

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