Increased levels of plasma amyloid-beta are related to cortical thinning and cognitive decline in cognitively normal elderly subjects

Neurobiology of Aging 36 (2015) 2791e2797

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Increased levels of plasma amyloid-beta are related to cortical thinning and cognitive decline in cognitively normal elderly subjects Sandra Llado-Saz, Mercedes Atienza, Jose L. Cantero* Laboratory of Functional Neuroscience, Spanish Network of Excellence for Research on Neurodegenerative Diseases (CIBERNED), Pablo de Olavide University, Seville, Spain

a r t i c l e i n f o

a b s t r a c t

Article history: Received 7 May 2015 Received in revised form 14 June 2015 Accepted 17 June 2015 Available online 24 June 2015

Plasma levels of circulating amyloid-beta (Ab) peptides are of particular interest in Alzheimer’ disease, but little is known about cognitive and cortical correlates of peripheral Ab levels in normal aging. Here, we compared cognitive functioning, vascular risk factors, and patterns of cortical thickness between cognitively intact elderly subjects with low (N ¼ 60) and high (N ¼ 60) plasma Ab levels (cutoffs: 225 pg/mL and 23 pg/ mL for Ab1e40 and Ab1e42, respectively). Overall, subjects with high Ab levels showed lower cognitive performance and thinner cortex than those with low Ab levels. More specifically, subjects with high Ab1e40 showed bilateral thinning of the prefrontal cortex, poorer objective memory, slower processing speed, and lower nonverbal reasoning skills, whereas subjects with high Ab1e42 had thinner temporal lobe, poorer everyday memory, and increased levels of homocysteine. Overall, these results suggest that high plasma Ab levels in normal elderly subjects are associated with subclinical markers of vulnerable aging, which may be helpful at predicting different trajectories of aging in cognitively intact older adults. Ó 2015 Elsevier Inc. All rights reserved.

Keywords: Aging Plasma amyloid-beta Cognitive function Cortical thickness Homocysteine Alzheimer’s disease

1. Introduction The worldwide population >65 is rapidly increasing from 500 million people in 2006 to 1 billion by 2030 (National Institute of Aging, 2007), leading to important challenges for public health systems and to novel insights into the limits of human longevity (Christensen et al., 2009). However, the physiological decline is highly heterogeneous among individuals, pointing to the existence of different trajectories of aging associated with specific patterns of subclinical functional impairment in the late-life period (Lunney et al., 2003). This notion is strongly supported by evidence suggesting that aging-related chronic diseases evolve silently for decades, until the first symptoms are clinically detected (Lang et al., 2009), then it can be too late to slow or stop progression of the disease. Alzheimer’s disease (AD), the leading cause of dementia in the elderly, is a neurodegenerative disorder with insidious onset and progressive cognitive decline. At present, there is no cure for this disorder, although the impact can be lessened by delaying its onset (Lopez, 2011). Given that a substantial proportion of AD cases might be attributable to potentially modifiable risk factors (Norton et al.,

* Corresponding author at: Laboratory of Functional Neuroscience, Spanish Network of Excellence for Research on Neurodegenerative Diseases (CIBERNED), Pablo de Olavide University, Ctra. de Utrera Km 1, 41013eSeville, Spain. Tel.: þ34 954 977433; fax: þ34 954 349151. E-mail address: [email protected] (J.L. Cantero). 0197-4580/$ e see front matter Ó 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.neurobiolaging.2015.06.023

2014), the identification of noninvasive and easily measurable AD biomarkers is a priority for detecting at-risk individuals and developing target interventions able to prevent and reduce the prevalence of AD. According to the amyloid cascade hypothesis, the pathogenesis of AD involves an imbalance between the production and clearance of the amyloid b (Ab) peptide, especially the 42-aminoacid isoform (Ab1e42), which subsequently aggregates into plaques in the cerebral cortex (Hardy and Selkoe, 2002). Recent cerebrospinal fluid (CSF) (Shaw et al., 2009) and amyloid positron emission tomographic (PET) studies (Bourgeat et al., 2010; Pike et al., 2007) have shown that a third of the cognitively normal individuals have significant amyloid deposition. Although both CSF and amyloid PET biomarkers have proven diagnostic accuracy for preclinical and clinical stages of AD, they are not appropriate for screening studies because of the required invasive lumbar puncture and the cost and availability of amyloid PET biomarkers (Toledo et al., 2013). Consequently, there is a growing demand for minimally invasive procedures to obtain peripheral AD biomarkers in asymptomatic elderly subjects. Although plasma is a more accessible and less invasive source than CSF for estimating Ab levels in circulation, results from studies using plasma Ab as a diagnostic marker in AD are conflicting, and associations between plasma Ab levels and CSF Ab/PET amyloid plaque measurements are modest, which might be because of the different origin, distribution, and clearance mechanisms of Ab in

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plasma, CSF and PET (Roher et al., 2009; Toledo et al., 2013). However, further studies have shown that plasma concentrations of Ab1e40 and Ab1e42 are increased in familial AD with mutations in the presenilin or the amyloid precursor protein genes (Kosaka et al., 1997; Scheuner et al., 1996) as well as in patients with Down syndrome (Head et al., 2011; Schupf et al., 2001) and in first degree relatives of AD patients, who are at an increased risk of developing the disease (Ertekin-Taner et al., 2008). In spite of the ongoing research, little is known about cognitive and cerebral correlates of plasma Ab levels in cognitively intact older adults, which might be potentially useful in establishing surrogate markers of pathological aging before cognitive decline is objectively detected. Accumulated evidence suggests that soluble Ab oligomers precede plaque formation and constitute the principal instigators of synapse loss and neuronal injury in AD patients (Selkoe, 2008; Walsh and Selkoe, 2007; Zahs and Ashe, 2013). Furthermore, the association between higher cerebral Ab load and cortical thinning of AD regions reinforces the idea that increased Ab levels might lead to synaptic deficits and neuronal loss in asymptomatic elderly subjects (Villeneuve et al., 2014). Therefore, given that plasma enzyme-linked immunosorbent assays mainly detect soluble Ab, a straightforward prediction for the present study is that cognitively normal older adults with increased plasma Ab levels should also show worse cognitive functioning and thinner cortex than those with lower plasma Ab levels. To test this hypothesis, different domains of cognitive function, vascular risk factors, and structural brain changes were compared between normal elderly subjects with low and high plasma Ab levels (i.e., Ab1e40 and Ab1e42). Next, group differences were further assessed in cortical thickness. Finally, we have evaluated whether Ab-dependent changes in cortical thickness were associated with cognitive functioning. 2. Materials and methods 2.1. Subjects This study included 120 cognitively normal elderly subjects (mean: 68.9  3.7 years) from different research programs related to biomarkers of normal and pathological aging conducted in the Laboratory of Functional Neuroscience at Pablo de Olavide University (Seville). Participants were primarily recruited from senior citizen’s associations, screening programs, and hospital outpatient services. Subjects received neurological, neuropsychological, magnetic resonance imaging (MRI) and 18F-fludeoxyglucose-PET exams. All subjects showed normal cognitive performance relative to appropriate reference values for age and education. Individuals with medical conditions and/or history of conditions that may affect brain structure or function (e.g., stroke, coronary heart diseases, diabetes, head trauma, any neurodegenerative diseases, depression, hydrocephalus, intracranial mass, MRI infarcts, and use of psychoactive medication) were not allowed to participate in the study. All participants showed a global score of 0 (no dementia) in the Clinical Dementia Rating as well as normal independent functiondassessed with the Spanish version of the interview for deterioration in daily living activities (Böhm et al., 1998). Depression was excluded (scores  5) with the shorter version of the Geriatric Depression Scale (Yesavage et al., 1983). Subjects gave their informed consent before their inclusion in the study, which was approved by the Ethical Committee for Human Research at Pablo de Olavide University.

subjectively and objectively. Subjective memory was evaluated with the Memory Functioning Questionnaire validated in Spanish population (Alarcon and Fernandez, 2008), and objective memory performance was assessed with the Free and Cued Selective Reminding Test, the Rey-Osterrieth Complex Figure Test (ROCFT), and the Visual Reproduction subtest (Wechsler Memory Scale, third edition). Executive functioning was evaluated with the Stroop test, the Trail Making Test, and the Tower of London. Language was assessed with the Boston Naming Test and the Token test, whereas processing speed was evaluated with the digit-symbol coding and the Symbol search subtests of the Wechsler Adult Intelligence Scale, third edition (WAIS-III), and nonverbal reasoning was assessed with the Matrix Reasoning subtest (WAIS-III). In addition, the global cognitive status was evaluated with the Spanish version of the Mini-Mental State Examination (Lobo et al., 1979). 2.3. Plasma Ab measurements Plasma Ab levels were determined by a double-antibody sandwich ELISA (human Ab1e40 and high sensitive Ab1e42, Wako Chemicals, Tokyo, Japan). Briefly, venous blood samples were collected after overnight fasting in 10-mL K2-ethylenediaminetetraacetic acide coated tubes (BD Diagnostics), and immediately centrifuged (3500 rpm) at 4  C for 5 minutes. Supernatant plasma was collected and aliquoted into 250-mL polypropylene tubes containing 8.32 mL of a protease inhibitor cocktail (cOmplete ULTRA Tablets mini, Roche). Plasma samples were stored at 80  C and thawed immediately before assay. Samples and standards were incubated overnight at 8  C with antibodies specific for Ab1e40 and Ab1e42 peptides, and the wells were read for absorption at 450 nm on a Victor 3 system (PerkinElmer, Waltham, MA, USA), according to the manufacturer’s instructions. Plasma Ab levels were measured in duplicate (50 mL), and the average of the 2 measurements (pg/mL) was used for statistical analyses. Both interassay and intra-assay coefficients of variation were <10%. The detection limit for these assays was 1.04 pg/mL for Ab1e40 and 0.54 pg/mL for Ab1e42. Subjects were split into low and high Ab groups (N ¼ 60 cases/ group) using the median value of Ab levels as the cutoff (median Ab1e40 ¼ 22,504 pg/mL; median Ab1e42 ¼ 2302 pg/mL). Accordingly, subjects with Ab values above the median were included in the high group, whereas those subjects with Ab values below the median were included in the low group. This classification was employed throughout the study to assess group differences in cognitive function and cortical integrity for each Ab peptide, separately. 2.4. Vascular risk factors Participants underwent standardized measurements for body mass index, waist-hip ratio, and for systolic and diastolic blood pressures. Fasting serum levels of total cholesterol, low-density lipoprotein, high-density lipoprotein, triglycerides, apolipoprotein B, and homocysteine (HCYS) were also obtained from each participant using standard enzymatic methods (A15 Random Access Analyzer, Biosystems, Spain). Apolipoprotein E polymorphisms were also determined with predesigned TaqMan genotyping assays (Applied Biosystem). 2.5. MRI acquisition and cortical thickness estimation

2.2. Neuropsychological assessment A neuropsychological battery covering memory, executive functioning, language, processing speed, and nonverbal reasoning was administered to all participants. Memory was assessed

Structural MR cerebral images were acquired on a whole-body Philips Achieva 3T scanner equipped with an 8-channel head coil. One high-resolution magnetization-prepared rapid gradient echoT1weighted anatomical sequence was obtained for each participant.

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Acquisition parameters were empirically optimized for gray or white contrast (0.8 mm3 isotropic voxel resolution, no gap between slices, repetition time ¼ 11 ms, echo time ¼ 4.5 ms, flip angle ¼ 8 , acquisition time ¼ 9.1 minutes). Cortical thickness was estimated by using surface-based methods with analysis tools implemented in Freesurfer v5.3 (http://surfer. nmr.mgh.harvard.edu/), which have been previously validated against histological data (Rosas et al., 2002) and manual segmentation (Kuperberg et al., 2003; Salat et al., 2004). Cortical surfacee based analysis allows inflating the cortex, flattening the entire cortical hemisphere, and transforming the hemisphere into a surface-based coordinate system (Fischl et al., 1999). The main purpose of the cortical surface inflation (Fig. 1A) and flattening (Fig. 1B) is to provide an enhanced representation of the cortical hemisphere that retains much of the shape and metric properties of the original surface, including the visualization of the detailed topographic organization of cortical areas (Fig. 1C), as well as the distributed changes occurring across the entire hemisphere (Fig. 1B). The Freesurfer cortical thickness pipeline involves intensity normalization, registration to Talairach space, skull stripping, segmentation of white matter (WM), tessellation of the WM boundary, and automatic correction of topological defects. The tessellated surface is used for a deformable surface algorithm as the starting point to find the WM and then the pial boundary. For each point on the tessellated WM surface, the cortical thickness is calculated as the average of the distance from the WM surface to the closest point on the pial surface, and from that point back to the closest point on

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the WM surface (Fischl and Dale, 2000). Pial and/or WM boundaries were manually corrected on a slice-by-slice basis in each participant to increase the reliability of cortical thickness measurements. Special attention was paid to cortical regions at the border with CSF to avoid partial volume effects. Cortical thickness maps were finally smoothed using nonlinear spherical wavelet-based denoising schemes, which have demonstrated enhanced specificity and sensitivity at detecting local and global changes in cortical thickness (Bernal-Rusiel et al., 2008). 2.6. Statistical analyses All statistical analyses were performed with SPSS v21 (SPSS Inc. Chicago, IL, USA). We first assessed the normality assumption of all variables by using the Kolmogorov-Smirnov test. Demographic data, cognitive scores, vascular risk factors, and plasma Ab values were normally distributed, which allowed us to use parametric statistical tests. Supplementary Fig. 1 shows the normal distribution of plasma Ab values. Group differences in demographics were assessed with unpaired t tests, with the exception of gender that was assessed with the c2 test due to the categorical nature of this variable. A different multivariate analysis of covariance (MANCOVA) was used to assess group differences (Ab1e40 and Ab1e42, separately) in each cognitive domain (i.e., memory, executive functioning, language, processing speed, and nonverbal reasoning). The score of each test within each cognitive domain was introduced as a

Fig. 1. Patterns of cortical thinning in normal elderly subjects with increased plasma amyloid-beta (Ab) levels. (A) Significant patterns of cortical thinning were represented on inflated cortical surfaces. (B) Thickness changes were also displayed on flattened surfaces of the same cortical hemisphere to allow for a better representation of the significant change within the entire cortex. (C) Flattened cortical maps were zoomed and major cytoarchitectonic subdivisions of affected regions were delimited. Left panel (low > high Ab1e40). Abbreviations for the left orbitofrontal cortex (Hof et al., 1995): Al, anterolateral region; Am, anteromedial region; Fp, frontopolar region; L, left hemisphere; Mo, medial orbitofrontal region; Olf, Olfatory tubercle; Pl, posterolateral region; Pm, posteromedial region. Abbreviations for the right frontal pole (Bludau et al., 2014): B11, medial portion of ventral frontal lobe; cg, cingulate gyrus; fms, frontomarginal sulcus; Fp2, medial frontopolar area 2; mfg, middle frontal gyrus; R, right hemisphere; sfg, superior frontal gyrus. Right panel (low > high Ab1e42). Abbreviations for the right temporal lobe (Ding et al., 2009; McDonald et al., 2000): In, insula; iTC, inferior temporal cortex; TA, primary auditory cortex; TAp, polysensory cortex; TAr, rostral auditory cortex; TE, temporal area; TEd, temporal dorsal area; TG, temporopolar area; PI, parainsular cortex.

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different dependent variable in the same MANCOVA to reduce the number of multiple comparisons. Age, gender, years of education, and/or Ab levels of the nontested peptide were introduced as covariates in previous analyses, provided that they accounted for significant variance in dependent variables (i.e., cognitive scores). If the MANCOVA reached significance, univariate F-tests (analyses of covariance) were used to identify those test scores that contributed to significant effects within a same cognitive domain. By using a previously validated hierarchical statistical model (Bernal-Rusiel et al., 2010), group differences in cortical thickness were assessed between subjects with low and high plasma Ab levels. An analysis of covariance was performed for each hemisphere, including group as the main factor (low and high Ab levels of each peptide, separately), and age, gender, Ab levels of the nontested peptide, and mean cortical thickness as nuisance variables. The significance threshold was set at p < 0.05 after correcting for multiple comparisons, with a cluster extent threshold of 90 vertices. 3. Results 3.1. Vascular risk factors Low and high Ab groups were statistically homogeneous in age, gender, education level, body mass index, waist-hip ratio, blood pressure, serum-lipid levels, and apolipoprotein E ε4 distribution, for both Ab1e40 and Ab1e42 comparisons. However, participants with high Ab1e42 showed higher levels of HCYS than those with low Ab1e42 (p < 0.02). Demographic and vascular risk factor for each Ab group (low and high Ab1e40 and Ab1e42) are shown in Table 1. 3.2. Neuropsychological results Table 2 shows significant changes in cognitive functioning for low and high Ab groups. It is worth noting that group differences in cognitive functioning are subclinical, revealing, therefore, effects that are below the cutoff value for clinical significance. In general, high Ab groups (Ab1e40 and Ab1e42) exhibited lower memory abilities than low Ab groups (Ab1e40: F10,108 ¼ 1.97, p < 0.04; Ab1e42: F4,113 ¼ 3.49, p < 0.01], although each Ab peptide affected different aspects of memory. Thus, older adults with high Ab1e40 showed lower scores on free recall (p < 0.02; Free and Cued Selective Reminding Test), immediate recall (p < 0.01; ROCFT), delayed recall (p < 0.003; ROCFT),

and visual declarative memory (p < 0.02; WMS), whereas high plasma levels of Ab1e42 significantly compromised self-perception of memory (0.001 < p < 0.009; Memory Functioning Questionnaire). Processing speed (0.001 < p < 0.02; WAIS) and nonverbal reasoning (p < 0.01; WAIS) were also significantly diminished in the high Ab1e40 group (MANCOVA for processing speed: F2,117 ¼ 5.39, p < 0.006; MANCOVA for nonverbal reasoning: F1,118 ¼ 6.22, p < 0.01). However, executive functioning and language did not differ between low and high Ab groups (neither Ab1e40 nor Ab1e42). 3.3. Cortical thickness Table 3 shows significant differences in cortical thickness between low and high Ab groups. Older adults with high Ab1e40 levels showed bilateral thinning of prefrontal cortex (PFC) compared with participants with low Ab1e40. These changes were restricted to the lateral orbitofrontal cortex in the left hemisphere and to the rostral middle frontal lobe in the right hemisphere (Fig. 1). We further found significant cortical atrophy of right anterior temporal regions in subjects with high Ab1e42 levels (Fig. 1). No significant changes were found in the opposite sense (i.e., thinner cortex in low Ab groups). Correlations between impaired cognitive domains and thinner cortical regions did not reach significance in any of the Ab peptides. 4. Discussion In this study, we have shown that cognitively normal elderly subjects with high concentrations of plasma Ab have lower cognitive performance, higher HCYS, and thinner cortex than those with low Ab levels. These results are Ab peptide-dependent. Thus, subjects with higher levels of Ab1e40 showed thinning of PFC accompanied by poorer memory, slower processing speed, and lower nonverbal reasoning skills; whereas individuals with higher levels of Ab1e42 had atrophy of the anterior temporal lobe, poorer selfperception of everyday memory, and increased levels of HCYS. Together, these results may contribute to clarify the role of plasma Ab levels in normal aging and enhance predictions of different trajectories of aging in asymptomatic older populations. 4.1. Cognitive functioning and plasma Ab levels in the elderly Previous research has shown that high plasma Ab levels are associated with increased cognitive impairment (Moon et al., 2011;

Table 1 Demographic and cardiovascular risk factors on the basis of plasma Ab levels Low Ab1e40 Ab (pg/mL) Age Gender (m/f) Education, y ApoE ε4 (yes/no) BMI (kg/m2) WHR Systolic BP (mmHg) Diastolic BP (mmHg) Total cholesterol (mg/dL) LDL cholesterol (mg/dL) HDL cholesterol (mg/dL) Triglycerides (mg/dL) ApoB (mg/dL) Homocysteine (mmol/L)

199.9  16 69.9  3.4 34/26 11.7  4.6 15/45 28.7  4 0.9  0.07 142  23 79  9 211  34 113  28 53  12 133  67 117  26 14.4  5.3

High Ab1e40 257.1  24 69.7  3.9 31/29 10.4  4.6 13/47 28.7  3 0.9  0.08 144  21 79  10 210  36 115  28 54  17 133  76 121  27 15.7  5.4

p 29*

10 0.7 0.6 0.09 0.7 0.9 0.7 0.7 0.8 0.8 0.7 0.7 0.8 0.4 0.2

Low Ab1e42

High Ab1e42

p

18.8  3 68.4  3.4 36/24 11  4.6 10/50 29  3.5 0.9  0.07 140  23 79  10 211  37 116  28 53  17 138  65 119  27 13.9  5.2

29.3  6 69.3  4 29/31 11.1  4.7 18/42 28.3  3.7 0.9  0.08 146  21 79  9 209  32 112  27 53  11 133  77 119  26 16.2  5.3

1020* 0.2 0.2 0.9 0.2 0.3 0.7 0.2 0.9 0.6 0.4 0.9 0.7 0.9 0.02*

Results are expressed as mean  standard deviation. Key: Ab, amyloid beta; ApoB, apolipoprotein B; ApoE ε4, apolipoprotein E epsilon 4; BMI, body mass index; BP, blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein; m/f, male/female; WHR, waist-hip ratio. * p < 0.05.

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Table 2 Group differences in cognitive functioning on the basis of plasma Ab levels. Low Ab1e40 Objective memory Free recall (FCSRT) Immediate (ROCFT) Delayed (ROCFT) Visual (WMS) Subjective memory Everyday (MFQ) Texts (MFQ) Past events (MFQ) Processing speed Digital-symbol (WAIS) Symbol search (WAIS) Nonverbal reasoning Matrix (WAIS)

7.1 20.2 20 43.3

   

1.8 4.9 5 3.1

High Ab1e40 6.3 17.7 17.1 41.8

   

1.7 5.5 5.6 3.4

p

Low Ab1e42

0.02a 0.01a 0.003a 0.02a

6.7 19.9 19.2 42.8

   

1.9 5 5.4 3

High Ab1e42 6.6 18.1 17.9 42.3

   

1.8 5.4 5.5 3.7

p 0.6 0.06 0.1 0.4

36.2  10.3 8.4  4.3 18.5  3.5

37.5  10.6 8.2  4.2 17.8  3.4

0.5 0.7 0.3

33.9  10.3 7.4  4 19  2.7

39.8  9.7 9.3  4.2 17.3  3.8

0.001a 0.009a 0.009a

53.8  12.9 27.5  5.7

48  14.3 23.5  7.3

0.02a 0.001a

51  14.2 25.6  6.7

50.6  13.6 25.4  6.8

0.9 0.8

11.7  5.4

9.4  4.8

0.01a

10.6  5.2

10.4  5.3

0.8

Results are expressed as mean  standard deviation. Key: Ab, amyloid beta; FCSRT, Free and Cued Selective Reminding Test; MFQ, Memory Functioning Questionnaire; ROCFT, Rey-Osterrieth Complex Figure Test; WAIS, Wechsler Adult Intelligence Scale, third edition; WMS, Wechsler Memory Scale, third edition. a Post hoc after the significant multivariate analysis of covariance (p < 0.05).

Okereke et al., 2009) and faster cognitive decline regardless of dementia status at follow-up (Cosentino et al., 2010), supporting the notion that increased plasma Ab levels may represent a broader marker of frailty in aging, perhaps not necessarily related to AD (Killiany, 2009). However, no studies to date have examined which cognitive domains are most impaired in elderly subjects with high Ab levels and whether these individuals show patterns of cortical atrophy not exclusively accounted by aging itself. Here, we found that subjects with high Ab1e40 levels had slower processing and impaired memory together with bilateral thinning of the PFC. Prefrontal regions are involved in information processing speed, which is critical to complete tasks rapidly and efficiently. In fact, structural and functional changes of the PFC have been associated with neuropsychological measures of processing speed in young (Glascher et al., 2009; Rypma et al., 2006) and older adults (Rosano et al., 2012). Therefore, high Ab1e40 levels in asymptomatic older adults might be a marker of accelerated aging, as revealed by slower processing, impaired memory, and integrity loss of the PFC. Perceived loss of memory ability is frequent in the elderly but its potential association with plasma Ab levels in normal aging remains elusive to date. The present study shows that subjective deficits of everyday memory are more evident in elderly subjects with high plasma levels of Ab1e42, who also exhibited a thinner right temporal lobe than the low Ab1e42 group. Recent evidence has shown that cognitively intact older individuals with subjective memory complaints presented increased AD-type brain pathology in regions of the medial temporal lobe (Kryscio et al., 2014), reductions of gray matter density in medial temporal regions similar to mild cognitive impairment (MCI) patients (Saykin et al., 2006), and aberrant patterns of functional connectivity in resting-state cortical networks (Hafkemeijer et al., 2013). Our study is the first to show that high plasma Ab1e42 levels are associated with worse perception of everyday memory and thinner temporal cortex, suggesting that

self-reported mnemonics in older adults with increased plasma Ab1e42 levels may be helpful at identifying persons for clinical monitoring who might benefit from earlier therapeutic opportunities. 4.2. Cortical correlates of plasma Ab levels in the elderly High levels of plasma Ab1e42 have been associated with faster decline in multiple cognitive domains in normal elderly subjects (Cosentino et al., 2010; Okereke et al., 2009) and conversion to MCI (Assini et al., 2004; Cammarata et al., 2009; Sóbow et al., 2005). Furthermore, recent studies have revealed that increased levels of plasma Ab1e42 are related to disrupted slow-wave sleep in MCI subjects (Sanchez-Espinosa et al., 2014), whereas decreased levels of plasma Ab1e42 are associated with enhanced interhemispheric functional connectivity in healthy elderly subjects (GonzalezEscamilla et al., 2014). However, studies of plasma Ab levels as potential biomarkers of AD have yielded contradictory results (e.g., Hansson et al., 2010; Lopez et al., 2008; Seppälä et al., 2010; Sundelöf et al., 2008; van Oijen et al., 2006), precluding the use of plasma Ab measurements in the clinical practice. The lack of consensus is likely because of a broad range of variability sources (demographic, clinical, and technical) that indeed affects plasma Ab measurements (Toledo et al., 2013). Despite the heterogeneity of results, plasma Ab levels remain a focus of interest in predicting the risk of later development of AD because it is a simple, inexpensive, and noninvasive biomarker, all of which are significant merits for population-based screening tools (Koyama et al., 2012). Combining plasma Ab measurements with surrogate imaging markers of AD may be useful for patient selection in clinical trials and detecting vulnerable elderly subjects at higher risk to develop AD or other chronic cerebral condition. Although the variability between studies precludes establishing plasma Ab cutoff values for

Table 3 Group differences in cortical thickness on the basis of plasma Ab levels. Cortical region (BA)

Low > high Ab1e40 Lateral orbitofrontal (BA47) Rostral middle frontal (BA10) Low > high Ab1e42 Middle temporal (BA21)

Hemisphere

Mean  SD thickness

CS (mm2)

p

Low

High

L R

2.55  0.14 2.47  0.22

2.47  0.14 2.37  0.19

1561 594

0.04 0.03

R

2.97  0.19

2.85  0.17

1326

0.0007

Key: Ab, amyloid beta; BA, Brodmann area; CS, cluster size; L, left; p, corrected p value; R, right; SD, standard deviation.

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the different diagnostic groups, Ab values used in the present study to split groups are in agreement with other studies performed with nondemented elderly subjects (Metti et al., 2013; Pesaresi et al., 2006; Sepälä et al., 2010; Yaffe et al., 2011; van Oijen et al., 2006). However, few studies have specifically validated this hypothesis in the context of AD (Devanand et al., 2011; Rembach et al., 2014; Sotolongo-Grau et al., 2014) and none of them have combined structural brain changes with plasma Ab levels to assess differences in normal elderly subjects. Structural MRI changes are considered reliable markers of early neurodegeneration in asymptomatic elderly subjects (Dickerson et al., 2011; Lampert et al., 2013; Smith et al., 2007; Tondelli et al., 2012). In fact, different studies have shown that decreased gray-matter volume of anteromedial temporal lobe (Smith et al., 2007; Tondelli et al., 2012) and PFC (Tondelli et al., 2012) precedes clinical signs of AD in asymptomatic older adults. The thickness of the cortex is of major relevance for our purpose as it follows the normal aging process and has shown comparable loads of insoluble Ab and tau in cortical regions vulnerable to AD pathology in both MCI and asymptomatic AD subjects (Iacono et al., 2014). Additional evidence has further shown that thinning of the temporal lobe begins as long as 11 years before onset of cognitive impairment, suggesting that cortical thickness is extremely sensitive to neurodegenerative changes occurring decades before clinical AD symptoms appear (Pacheco et al., 2015). Disclosure statement The authors have no conflicts of interest to disclose. Acknowledgements This work was supported by the Spanish Ministry of Economy and Competitiveness (SAF2011-25463 to Jose L. Cantero, PSI201455747-R to Mercedes Atienza), the Regional Ministry of Innovation, Science and Enterprise, Junta de Andalucia (P12-CTS-2327 to Jose L. Cantero), and CIBERNED (grant number CB06/05/1111 to Jose L. Cantero). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.neurobiolaging. 2015.06.023. References Alarcon, D., Fernandez, C., 2008. Validación de la versión abreviada en español del Cuestionario de Funcionamiento de la Memoria (CFM) en una población mayor de 55 años. Anales de Psicologia 24, 320e326. Assini, A., Cammarata, S., Vitali, A., Colucci, M., Giliberto, L., Borghi, R., Inglese, M.L., Volpe, S., Ratto, S., Dagna-Bricarelli, F., Baldo, C., Argusti, A., Odetti, P., Piccini, A., Tabaton, M., 2004. Plasma levels of amyloid beta-protein 42 are increased in women with mild cognitive impairment. Neurology 63, 828e831. Bernal-Rusiel, J.L., Atienza, M., Cantero, J.L., 2008. Detection of focal changes in human cortical thickness: spherical wavelets versus Gaussian smoothing. Neuroimage 41, 1278e1292. Bernal-Rusiel, J.L., Atienza, M., Cantero, J.L., 2010. Determining the optimal level of smoothing in cortical thickness analysis: a hierarchical approach based on sequential statistical thresholding. Neuroimage 52, 158e171. Bludau, S., Eickhoff, S.B., Mohlberg, H., Caspers, S., Laird, A.R., Fox, P.T., Schleicher, A., Zilles, K., Amunts, K., 2014. Cytoarchitecture, probability maps and functions of the human frontal pole. Neuroimage 93 (Pt 2), 260e275. Böhm, P., Peña-Casanova, J., Aguilar, M., Hernandez, G., Sol, J.M., Blesa, R., NORMACODEN Group, 1998. Clinical validity and utility of the interview for deterioration of daily living in dementia for Spanish-speaking communities. Int. Psychogeriatr. 10, 261e270. Bourgeat, P., Chételat, G., Villemagne, V.L., Fripp, J., Raniga, P., Pike, K., Acosta, O., Szoeke, C., Ourselin, S., Ames, D., Ellis, K.A., Martins, R.N., Masters, C.L., Rowe, C.C., Salvado, O., AIBL Research Group, 2010. Beta amyloid burden in the

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