Less agreeable, better preserved? A PET amyloid and MRI study in a community-based cohort

Journal Pre-proof Less agreeable, better preserved? A PET amyloid and MRI study in a communitybased cohort Panteleimon Giannakopoulos, M.D, Cristelle Rodriguez, M.S, Marie-Louise Montandon, Ph.D, Valentina Garibotto, M.D, Sven Haller, M.D, François R. Herrmann, M.D., MPh PII:

S0197-4580(20)30031-2

DOI:

https://doi.org/10.1016/j.neurobiolaging.2020.02.004

Reference:

NBA 10768

To appear in:

Neurobiology of Aging

Received Date: 18 November 2019 Revised Date:

7 February 2020

Accepted Date: 7 February 2020

Please cite this article as: Giannakopoulos, P., Rodriguez, C., Montandon, M.-L., Garibotto, V., Haller, S., Herrmann, F.R., Less agreeable, better preserved? A PET amyloid and MRI study in a communitybased cohort, Neurobiology of Aging (2020), doi: https://doi.org/10.1016/j.neurobiolaging.2020.02.004. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Elsevier Inc. All rights reserved.

CRedit Author statement

P. Giannakopoulos : conceptualization, methodology, formal analysis, writing-original draft, review and editing, supervision, funding acquisition C. Rodriguez : conceptualization, validation, investigation, writing-original draft M-L Montandon : methodology, formal analysis, validation, writing-original draft, review and editing V. Garibotto : Methodology, formal analysis, validation, writing-original draft S. Haller : conceptualization, methodology, formal analysis, writing-original draft F.R. Herrmann : methodology, formal analysis, validation, writing-original draft, review and editing, supervision

Less agreeable, better preserved? A PET amyloid and MRI study in a communitybased cohort

Panteleimon Giannakopoulos, M.D. a, b, Cristelle Rodriguez, M.S. a, b, Marie-Louise Montandon, Ph.D. a,b,c, Valentina Garibotto, M.D. d,e, Sven Haller, M.D. e,f,g, François R. Herrmann, M.D., MPh c

a Department of Psychiatry, University of Geneva, Geneva, Switzerland b Medical Direction, Geneva University Hospitals, Geneva, Switzerland c Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland d Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, Geneva University Hospitals, Geneva, Switzerland e Faculty of Medicine of the University of Geneva, Geneva, Switzerland f CIRD - Centre d’Imagerie Rive Droite, Geneva, Switzerland g Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden

Running title: Personality and brain aging

Correspondence address: Prof. Panteleimon Giannakopoulos Division of Institutional Measures Geneva University Hospitals 12 bis avenue de Rosemont 1208 Geneva - Switzerland Direct line

+41 22 305 5777

e-mail: [email protected]

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Abstract The relationship between personality profiles and brain integrity in old age is still matter of debate. We examined the association between Big Five factor and facet scores and MRI brain volume changes upon a 54-month follow-up in 65 elderly controls with three neurocognitive assessments (baseline, 18 and 54 months), structural brain MRI (baseline and 54 months), brain amyloid PET during follow-up, and APOE genotyping. Personality was assessed with the Neuroticism Extraversion Openness Personality Inventory-Revised. Regression models were used to identify predictors of volume loss including time, age, sex, personality, amyloid load, presence of APOE epsilon 4 allele and cognitive evolution. Lower agreeableness factor scores (and four of its facets) were associated with lower volume loss in hippocampus, entorhinal cortex, amygdala, mesial temporal lobe and precuneus bilaterally. Higher openness factor scores (and two of its facets) were also associated with lower volume loss in left hippocampus. Our findings persisted when adjusting for confounders in multivariable models. These data suggest that the combination of low agreeableness and high openness is an independent predictor of better preservation of brain volume in areas vulnerable to neurodegeneration.

Keywords: amyloid load, cognitive aging, cohort studies, personality, structural MRI

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1. Introduction Personality refers to enduring styles of thinking, feeling and acting characteristic of each individual (McCrae and Costa, 1997). Involved in medicine, psychology, sociology and, more recently, neurosciences, personality has been associated with morbidity and mortality (Bogg and Roberts, 2004), subjective well-being (DeNeve and Cooper, 1998), resilience and work adaption (Barrick and Mount, 1991), as well as interpersonal relationships (Malouff et al., 2010). The Big-Five/Five-Factor model used in this report is a widely applied taxonomic approach of personality based on the presence of five major factors (i.e., Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness). Among the scales developed according to the Big-Five/Five-Factor model (McAbee and Oswald, 2013), the Neuroticism Extraversion Openness Personality Inventory-Revised (NEO-PI-R), is a crossculturally validated instrument that assesses 30 facets, 6 for each of the five personality factors (Costa and Mccrae, 1992). Neuroticism refers to the predominance of negative traits including anxiety, hostility, and anger; Extraversion includes the proneness towards positive emotions and feelings such as warmth and enthusiasm; Openness, the personal inclination to experience and the appreciation of new situations and thoughts with a curious, imaginative and creative attitude, is defined along six facets that cover imagination (or fantasy), sense of aesthetics, emotions and feelings, but also proactive behaviors and actions to explore and experiment beyond habits and routines, as well as intellectual curiosity, and the disposition to negotiate and discuss social, political and religious values; Agreeableness, characterized by trustful, cooperative and altruistic tendencies, and finally Conscientiousness, is the predisposition to be reliable, resolute and well organized, and unwilling to deviate from rules and moral principles.

According to the Big Five model, personality traits are pervasive and enduring patterns of thoughts, feelings and behaviors, which are formed through childhood and increase in consistency throughout the lifespan with a peak after age 50 (Bazana and Stelmack, 2002). However, later studies challenged this viewpoint. Between 14 and 77 years and with the

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exception of Conscientiousness, the lifelong differential stability of personality is modest (Harris et al., 2016). In the same line, the rank-order stability of Extraversion, Openness, and Agreeableness may follow an inverted U-shaped function, reaching a peak between the ages of 40 and 60 and decreasing afterward, whereas Conscientiousness showed a continuously increasing rank-order stability across adulthood (Specht et al., 2011).

Whether our personality impacts on brain structure is still a highly disputed issue. Both positive and negative associations between gray matter (Zigmond and Snaith) volumes in most neocortical areas and Extraversion were reported (Bjornebekk et al., 2013; Coutinho et al., 2013; DeYoung et al., 2010; Li et al., 2017). Various associations were also found between Extraversion, Neuroticism scores and amygdala volume (Cremers et al., 2011; Holmes et al., 2012; Koelsch et al., 2013; Lu et al., 2014; Mincic, 2015; Omura et al., 2005). Agreeableness scores were associated positively with left superior temporal gyrus volumes (Li et al., 2017), but also negatively with left superior parietal, inferior parietal, middle occipital and anterior cingulate cortex volumes (Coutinho et al., 2013; Irle et al., 2005). A negative association between Openness scores and cortical thickness and volume in left frontal and superior temporal gyrus was recently reported (Vartanian et al., 2018). Attempting a more holistic approach, Privado et al. (2017) postulated that variations in GM clusters were associated with temperamental traits (Extraversion and Neuroticism), whereas long-distance structural connections were related with the dimension of personality close to high-level cognitive processes (Openness). However, later analyses did not confirm this distinction. Using the sample of the Human Connectome Project, Riccelli and coworkers (Riccelli et al., 2017) performed the most complete study of the MRI correlates of NEO-PI factors postulating that most of them reflected the anatomical variability and brain maturation. In the same line, Gray and coworkers (Gray et al., 2018) obtained negative data analyzing 1105 cases from the same project further stressing the difficulty to identify reliable associations between personality and brain integrity in young age. Nostro and collaborators (Nostro et al., 2017) also reported negative data in a sample of 182 women. These authors found,

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however, a modest but significant association between GM volume and neuroticism, extraversion, and conscientiousness only in men. Longitudinal studies exploring the impact of personality in the annual rate of GM volume loss in adults are rare. An association between higher Openness scores and better preservation of GM volume was reported by Taki and collaborators in a 6-year follow-up of 274 community dwelling subjects (Taki et al., 2013)

Despite is relative stability over the adult lifespan, the association between personality factors and MRI findings may change in old age. Several lines of evidence indicate that the associations between volumetric MRI variables and personality are more consistent. Increased cortical thickness in right superior frontal and left medial frontal cortex was reported in cases with high levels of Extraversion (Wright et al., 2007). Elderly cases with high levels of Agreeableness displayed an increased volume of right orbitofrontal cortex whereas the associations between cortical volumes and Conscientiousness were more variable (Kapogiannis et al., 2013). Conversely, high levels of Neuroticism were related to lower thickness and GM volumes in frontotemporal cortices (Kapogiannis et al., 2013; Wright et al., 2007). In the same line, older subjects with lower openness scores displayed lower regional GM volumes (Kitamura et al., 2016),

The most challenging case concerns the effect of personality on aging-related changes in human brain. Is there a link between personality factors and the rate of brain tissue loss over time in areas known to be vulnerable in neurodegenerative process? To our knowledge, no studies addressed the impact of personality on longitudinally assessed GM volume changes in old age. Based on the above-mentioned observations in cross-sectional designs, we hypothesized that personality factors, and in particular openness, may accelerate or decelerate volume changes in areas early affected in the course of Alzheimer disease process such as the hippocampus, entorhinal cortex and mesial temporal lobe. We report here the results of a longitudinal analysis combining MRI data and

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PET amyloid documentation in a community-based series of cognitively preserved elderly individuals followed-up longitudinally for a mean duration of 54 months.

2.

Materials and Methods

2.1. Participants The study was approved by the local Ethics Committee and all participants gave written informed consent prior to inclusion. Individuals were selected from an ongoing cohort study on cognitively intact elders, as described previously (van der Thiel et al., 2018; Xekardaki et al., 2015; Zanchi et al., 2017a). All of the cases were recruited via advertisements in local newspapers and media. Exclusion criteria included psychiatric or neurologic disorders, sustained head injury, history of major medical disorders (neoplasm or cardiac illness), alcohol or drug abuse, regular use of neuroleptics, antidepressants or psychostimulants and contraindications to PET or MRI scans. To control for the confounding effect of vascular pathology on MRI findings, individuals with subtle cardiovascular symptoms, hypertension (non treated) and a history of stroke or transient ischemic episodes were also excluded from the present study. The initial cohort included 526 elderly white non Latinos of mixed European descent individuals living in Geneva and Lausanne catchment area. Due to the need

for

an

excellent

French

knowledge

(in

order

to

participate

in

detailed

neuropsychological testing) the vast majority of the participants were Swiss (or born in French-speaking European countries, 92%). Cases with three neurocognitive assessments at baseline, 18 months and 54 months, structural brain MRI at baseline and 54-months postinclusion, brain amyloid PET at follow-up and APOE status were considered. The sample 54months post-inclusion included 397 cases. As a sub-project of this cohort study, the NEO-PIR assessment was administrated randomly in 65 elderly controls: 41 women and 24 men, mean age: 74.2 ± 4.0 (mean ± SD) ranging from 73.2 to 89.3 years. These individuals formed the sample of the present report.

2.2. Personality assessment

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Personality features and dimensions were assessed at baseline using the French version of the NEO-PI-R (Costa and McCrae, 1992). Participants were asked to complete the 240-item self-report version of the NEO-PI-R questionnaire using a five-point like agreement scale. The NEO-PI-R assesses 30 facets, 6 for each of the five personality factors (Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness; see Supplementary Materials).

2.3. Neuropsychological assessment At baseline, all individuals were evaluated with an extensive neuropsychological battery described in details previously (Haller et al., 2017; Herrmann et al., 2019; Xekardaki et al., 2015; Zanchi et al., 2017b) . All individuals were also evaluated with the Clinical Dementia Rating scale (CDR) (Hughes et al., 1982). In agreement with the criteria of Petersen et al. (Petersen et al., 2001), participants with a CDR of 0.5 but no dementia and a score exceeding 1.5 standard deviations below the age-appropriate mean in any of the cognitive tests were classified as MCI and were excluded. Participants with neither dementia nor MCI were classified as cognitively healthy controls and underwent full neuropsychological assessment at follow-up, after a mean period of 18 and 54 months.

In the absence of consensus, the definition of groups within the normal range on the basis of neuropsychological criteria should avoid to include a priori hypotheses on the cognitive fate of cases with unstable cognitive performances. Among them, some cases progress at the first follow-up and remain stable or even improve their performance at the second follow-up. Others are stable at the first follow-up and progress later on (but may improve or remain stable at later time points). To resolve this difficult question, we calculated the number of tests with improved minus the number of tests with decreased performances resulting in a final continuous cognitive score for each time point. Change in cognition between inclusion and last follow-up was defined as the sum of the continuous cognitive scores at two followups. This new approach makes it possible to avoid a priori hypotheses regarding the

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longitudinal evolution of cognition in our cases. Cognitive trajectories were defined after summing the number of cognitive tests at follow-up with performances at least 0.5 standard deviation (SD) higher or lower compared with the first evaluation (Z-scores). Change in cognition between inclusion and last follow-up was defined as the sum of the continuous cognitive scores at two follow-ups as previously described (Herrmann et al., 2019). This variable was used in all subsequent regression models.

2.4. Amyloid PET imaging Sixty-one

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F-Florbetapir- (Amyvid) and four

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F-Flutemetanol-PET (Vizamyl) data were

acquired on 2 different instruments (Siemens BiographTM mCT scanner and GE Healthcare Discovery PET/CT 710 scanner) of varying resolution and following different platform-specific acquisition protocols. The

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F-Florbetapir images were acquired 50 to 70 minutes after

injection and the 18F-Flutemetanol PET images 90 to 120 minutes after injection. PET images were reconstructed using the parameters recommended by the ADNI protocol aimed at increasing data uniformity across the multicenter acquisitions. More information on the different

imaging

protocols

can

be

found

on

the

ADNI

web

site

(http://adni.loni.usc.edu/methods/).

Amyloid positivity was visually assessed following standardized procedures approved by the European Medicinal Agency. Moreover, all scans were intensity normalized using the thalamus-pons as target region as described by (Lilja et al., 2018), and cortical standard uptake value rations (SUVR) were then calculated.

2.5. MR imaging At baseline, imaging data were acquired on a 3T MRI scanner (TRIO SIEMENS Medical Systems, Erlangen, Germany). The structural high-resolution T1-weighted anatomical scan was performed with the following fundamental parameters: 256x256 matrix, 176 slices, 1 mm isotropic, TR = 2.27 ms). At follow-up, high-resolution anatomical 3DT1 data were acquired

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(254x254 matrix, 178 slices, 1 mm isotropic, TR = 7.24 ms) on a 3T MR750w scanner (GE Healthcare, Milwaukee, Wisconsin). At both acquisition times, additional sequences (T2w imaging, susceptibility-weighted imaging, diffusion tensor imaging) were used to exclude incidental brain lesions. The average interval between baseline and follow-up imaging was 4.5 ± 0.6 years.

Automatic MR volumetry of both baseline and follow-up MRI was performed with the Combinostics cNeuro software package (https://www.cneuro.com), using the standard processing parameters. Our analysis included areas known to display early loss of volume in brain aging and Alzheimer disease (AD; mesial temporal lobe (MTL), hippocampus, entorhinal cortex and amygdala; (Yang et al., 2012) and precuneus (the earliest site of decreased perfusion in AD; (Miners et al., 2016). In order to examine the specificity of our findings, we also analysed the personality impact on the volume of four control areas (caudate nuclei, cerebellum, fusiform gyrus and thalamus). Volume loss was calculated as follows: (volume follow-up – volume baseline) / (volume baseline x time in years).

2.6. APOE status Whole blood samples were collected at baseline for all subjects for APOE genotyping. Standard DNA extraction was performed using either 9 ml EDTA tubes (Sarstedt, Germany) or Oragene Saliva DNA Kit (DNA Genotek, Inc., Ottawa, ON, Canada) which were stored at 20°C. APOE genotyping was done on the LightCycler (Roche Diagnostics, Basel, Switzerland) as described previously (Nauck et al., 2000). Subjects were divided according to their APOE epsilon 4 allele status (4/3 versus 3/3, 3/2 carriers).

2.7. Statistical analysis Demographic and neuropsychological data were compared between the two visits with paired t-test and Wilcoxon matched-pairs signed rank test. Mixed effects linear regression models were used to identify predictors of the brain volume loss (dependent variable)

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including time, sex, age, personality factors (and facets), mean SUVR, APOE genotyping and continuous cognitive score. The significance level was set at P < 0.05 but was corrected to P < 0.0075 for univariate testing and P<0.005 for multivariable testing by using the Benjamini-Hochberg method (Green and Diggle, 2007) which was applied on the 180 pvalues obtained for the 5 factors, both sides of the 9 brain regions studied, with simple and multiple regression models. The coefficient of determination (R2) was computed for each model. All statistics were performed with the STATA statistical software, Version 15.1 (StataCorp, College Station, Texas, 2017). The coefficients of determination were assessed according to Selya et al. (2012). (Selya et al., 2012).

3. Results 3.1. Descriptive data Demographic data show no sex-related differences in age, APOE epsilon 4 allele frequency, MMSE scores at baseline, and amyloid positivity. Men were significantly more educated than women (p=0.02). However, the continuous cognitive score (combined on the basis of two follow-ups) decreased in men (p=0.027) but remained fairly stable in women. According to the visual score, 73.2% of women and 50.0% of men were Aβ-negative. The mean SUVr varied between 0.5 and 0.7 (Table 1). This variable was used for subsequent regression analyses since it decreases the inter-rater variability that may substantially affect amyloid assessment in cognitively intact cases (Bullich et al., 2017; Mountz et al., 2015).

3.2. Personality factors and brain volume loss In mixed regression univariate models, lower Agreeableness scores were associated with better volume preservation (lower volume loss at 4.5 year follow-up compared to inclusion) in hippocampus, entorhinal cortex, amygdala, MTL and precuneus bilaterally (Table 2, Fig. 1). Importantly, for this single variable the percentage of explained variability for MRI volume loss ranged from 33.7% in MTL to 16% in right hippocampus. Following the left MTL, left entorhinal and left amygdala displayed the highest percentage of explained variability (26.3%

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and 25.7% respectively). The only other personality factor to be associated with brain volume loss in these areas was Openness but in an opposite sense (Table 2). The percentages of volume loss variability that could be attributed to this variable was between 22% for left amygdala and 28.4% for right hippocampus. In the right hemisphere, only MTL volume loss was associated with this variable explaining 26% of its variability. Among control areas, lower Agreeableness scores were associated with better volume preservation only in thalamus (Fig 1). When the more stringent Benjamini-Hochberg correction for multiple comparisons was used, the association between lower scores of Agreeableness and better volume preservation persisted in bilateral MTL, precuneus, entorhinal cortex and amygdala as well as left hippocampus. This was also the case for the association between Openness and lower volume loss in left hippocampus.

Our multiple linear regression models revealed that the univariate associations regarding Agreeableness persisted in MTL, entorhinal cortex and amygdala bilaterally, as well as left precuneus and hippocampus (but not in control areas) when adjusting for all of the main factors known to impact on brain tissue loss in old age, namely male sex, APOE epsilon 4 allele, amyloid load, age, and continuous cognitive score changes at 4.5 year follow-up compared to inclusion (Fig. 1). The more powerful regression models were obtained in respect to MTL volumes with R square values of 0.61 (left) and 0.55 (Lupton et al.). In this particular area, male sex, age, amyloid load, APOE epsilon 4 allele and Agreeableness scores were all independent predictors of volume loss. In hippocampus and entorhinal cortex, amyloid load, APOE epsilon 4 allele and Agreeableness scores were all significant predictors and explained from 38% to 45% of volume loss variability. Not surprisingly, amygdala-related regression models did not retain amyloid load, but male sex, APOE epsilon 4 allele and Agreeableness scores explained 43.3% (left) and 42.1% (Lupton et al.) of volume loss variability. Even in precuneus where amyloid load and APOE epsilon 4 allele were not significant predictors, Agreeableness scores along with male sex explained 41% (left) and 40.4% (Lupton et al.) of volume loss variability. Lower Openness scores were

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associated with increased volume loss in left hippocampus and left precuneus. Male sex, older age, APOE epsilon 4 allele and Openness scores explained 48.7% of volume loss variability in this area. Multivariable models revealed a significant association between lower scores of Conscientiousness and better preservation of brain volumes in left precuneus (38.9% of volume loss variability). Age, male sex, amyloid load and APOE epsilon 4 allele were all independent predictors in these latter analyses. In multivariable models including Benjamini-Hochberg correction for multiple comparisons, the observed associations between Agreeableness and volume loss persisted in left MTL and precuneus. This was also the case for the association between Openness scores and volume loss in left hippocampus.

3.3 Agreeableness and openness facets: relationship to brain volume loss As for personality factors, the NEO-PI facets of agreeableness and openness have been also included in univariate and multivariable regression models (Table 3, supplementary material for the full data). We report here only the associations that persist after adjustment in multivariable models according to the corrected p value (Benjamini-Hochberg correction). They concerned only the left hemisphere. Among the different facets of agreeableness, compliance was the most frequently associated with increased volume loss. This association was found in MTL, hippocampus, entorhinal cortex and amygdala. Straightforwardness scores were negatively associated with volume loss in MTL and hippocampus. Altruism scores were associated with more severe volume loss in MTL and entorhinal cortex. Tendermindness scores were negatively associated with volume loss in entorhinal cortex. This was also the case for the association between modesty and volume loss in precuneus. The associations between openness facets and volume loss were more rare. Increased fantasy score were related to lower volume loss in left hippocampus. In all of the control areas, no association was found between NEO-PI personality facets and volume loss according to the stringent criteria used (agreement between univariate and multivariable models, corrected for multiple comparisons).

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4. Discussion Controlling for most of the already known determinants of volume loss in old age and in particular amyloid pathology, our data reveal a strong association between lower levels of Agreeableness and better MRI volume preservation in AD-related cortical areas in healthy controls upon a 54-month follow-up. Higher scores of Openness were also associated with lower volume loss in left hippocampus. The analysis of agreeableness and openness facets further confirmed their independent association with brain volume loss in areas known to be involved in AD-related neurodegenerative process such as the hippocampus, amygdala, entorhinal cortex, mesial temporal lobe and precuneus. Pointing further to the specificity of these observations, other NEO-PI factors (neuroticism, extraversion) were not related to the evolution of brain volumes over time. Moreover, volume changes in control areas were not related to personality factors.

Previous contributions addressing the impact of personality factors on brain integrity in normal aging are scarce. In 29 healthy elderly controls, Wright and collaborators (Wright et al., 2007) reported that the thickness of lateral prefrontal cortex but not amygdala volume were associated with Extraversion (positively) and Neuroticism (negatively). Two latter studies attempted to address the same issue in larger community-based samples. Kapogiannis and coworkers (Kapogiannis et al., 2013) analyzed MRI scans from 87 elderly individuals free of cardiovascular disease and reported that lower Neuroticism, higher Extraversion, higher Openness, higher Agreeableness and higher Conscientiousness were all associated with both lower and higher GM volumes mainly within frontal lobe subdivisions, insula and anterior cingulate cortex. Taki and collaborators (Kapogiannis et al., 2013) performed the only currently available study on the impact of personality factors on GM volume changes over time. Conceptually close to the present report, this investigation of 274 healthy community dwelling controls indicated that lower level of Openness was associated with more pronounced loss of GM volume in the right inferior parietal lobule. In a correlation

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cross-sectional analysis of 41 elderly controls, Kitamura et al. (Kitamura et al., 2016) also reported a positive association between Openness scores and GM volumes in old age.

One main methodological issue that may explain the ambiguity of the previous observations is the number of covariates that may influence brain integrity in old age. Although sex and age have been systematically used as confounders in previous studies, the determinants of GM volume loss in normal aging mainly include AD-related biomarkers and, in particular, APOE epsilon 4 allele and amyloid pathology. In order to isolate the independent effect of personality factors on GM volume loss, the present longitudinal study combines a long follow-up period with detailed assessment of cognitive trajectories, PET amyloid documentation and APOE genotyping. To be discussed, the associations between personality factors and MRI data should, first, correspond to a stringent criterion for multiple comparisons and, second, survive in a stepwise regression analysis taking into account all of the previously cited confounders. Of evidence, we cannot exclude that additional covariates may partly explain the observed associations. However, the method applied here has the merit to reveal only the more robust associations between personality and GM volume loss in normal aging.

The association between lower levels of Agreeableness and better structural preservation of limbic areas, MTL and precuneus is a highly intriguing finding. This relationship was present in AD-related limbic and neocortical areas and explained a surprisingly high percentage of GM volume loss variability, in particular in left MTL and hippocampus. The multivariable models showed that this association persisted after controlling for a series of independent predictors of GM volume loss such as amyloid load, APOE epsilon 4 allele, age and male sex. The concomitant consideration of these variables allowed for predicting more than 60% of GM volume loss variability in left MTL. The complementary analysis of agreeableness facets led to consistent observations. According to the ROIs, higher scores in straightforwardness,

compliance

but

also

altruism

and

tender-mindedness

were

14

independently related to more pronounced GM volume loss. These observations shed a different light to the role of Agreeableness in old age. Traditionally, high Agreeableness in adult lifespan is considered a positive trait of personality being associated with increased subjective well-being (Strickhouser et al., 2017), better outcome in mental health treatments (Bucher et al., 2019), less disengagement coping (Carver and Connor-Smith, 2010) and less sexual aggressive behavior (Allen and Walter, 2018). However, the picture seems to be quite different in old age. Higher Agreeableness levels in this life period have been associated with poorer executive performance and neurocognitive functions (Davey et al., 2015; Maldonato et al., 2017; Ouanes et al., 2017) and medically unexplained symptoms (van Dijk et al., 2016). As a psychological construct, Agreeableness refers to the tendency of establishing interpersonal relationships without aggressiveness searching for social acceptance. Agreeable persons are more prone to avoid conflicts, adapt themselves to other’s commitments and adopt easily a majoritarian viewpoint. These qualities may, however, have a price in old age when the need for social adaption is less imperative. In agreement with the previously cited works, our observations point to a negative impact of higher Agreeableness on GM volumes in areas early affected in the course of neurodegeneration. One could argue that low level of neurocognitive performances in elderly persons with high Agreeableness scores (Maldonato et al., Clin Pract Epidemiol Ment Health. 2017;13:233-245) may partly explain the positive association between Agreeableness scores and brain volume loss. Although we cannot formally exclude this possibility, this is an unlikely scenario in the present cohort in the light of high MMSE scores and education levels. Moreover, in an earlier report, we found no association between Agreeableness and cognitive scores in our cohort (Rodriguez et al., 2016).

The association between higher Openness scores and GM volume preservation in hippocampus parallels the previous work by Taki and collaborators (Taki et al., 2013) who reported similar data on volume loss in right inferior parietal lobule. Several other contributions supported the beneficial effect of higher levels of Openness on brain integrity

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including GM volumes (Kitamura et al., 2016), as well as better preservation of white matter tracts connecting posterior and anterior brain regions and dorsolateral prefrontal cortex (Privado et al., 2017; Xu and Potenza, 2012). Increased functional connectivity within mesocortical networks has been also described in open people (Passamonti et al., 2015). The association between higher openness factor (and its facets of fantasy) scores and higher GM hippocampal volumes at follow-up contrasts with the negative data reported in the Human Connectome Project sample (Gray et al., 2018) suggesting that the beneficial effect of this personality factor on GM volumes concerns mainly and possibly exclusively older adults. Why this personality factor may protect brain integrity is still matter of intense debate. Higher levels of Openness promote cardiovascular adaption (O'Suilleabhain et al., 2018) but also systolic and diastolic blood pressure regulation under stress conditions (Lu et al., 2016) that may be participate to brain volume preservation in hippocampus, an area known to be particularly vulnerable to microvascular damage and deleterious stress effects (PearsonLeary et al., 2017). In the same line, Openness has been associated with reversion from mild cognitive impairment (MCI) to normal cognition (Sachdev et al., 2013). The present study suggests, however, that the positive role of Openness on brain structure preservation in old age should not be overestimated. Although present, it is confined to the hippocampus and its magnitude remains modest.

In conclusion, this combined PET amyloid-MRI study reveals, for the first time to our knowledge, a specific association between lower levels of Agreeableness, higher levels of Openness and lower volume loss in limbic areas, MTL and precuneus in normal aging. In the light of these findings, one could recommend the exploration of these personality factors as independent predictors of early structural changes in the course of brain aging. Some limitations should be considered when interpreting these observations. First, our cases are not representative of the whole spectrum of brain aging. Despite their recruitment in the community, they display no or very mild vascular pathology and relatively high level of education. We cannot thus exclude that the observed association may be no longer present

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when cases with mixed demographic profiles or pathologies are considered. Second, demographic, genetic and biological factors may often mask the association between GM volume loss and personality in old age. As an example, higher scores of Conscientiousness were related to higher volume loss in left MTL, precuneus and hippocampus only in multivariable models. We opted to discuss here only concordant observations for both types of regression models. Lastly, the combination of all significant predictors allows for explaining almost 60% of the GM volume loss variability. Although remarkably high in the light of the marked heterogeneity of normal aging and relatively small sample size, this percentage implies the presence of additional predictors that may contaminate the association between personality factors and MRI data. In this respect, the in vivo assessment of tau pathology as well as brain metabolism in larger elderly cohorts would be a useful complement, in the efforts to get better insight into the role of personality in age-related brain volume loss.

Disclosure statement The authors report no conflicts of interest.

Acknowledgements This project was supported by the Association Suisse pour la Recherche sur Alzheimer, the Schmidheiny foundation and the Swiss National Foundation (Grant No. 320030-169390).

Highlights

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Lower Agreeableness is associated with better preservation of limbic areas

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Aging-related hippocampal volume decrease is lower in elders with higher openness

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•

Personality impact on brain volume is independent of amyloid load and APOE genotype

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Table 1. Participant’s characteristics (clinical and demographic data, personality factors, amyloid load and APOE status).

Female

Male

Total

N

41

24

65

Age at Amy PET

74.1 ± 4.1

74.3 ± 4.0

74.2 ± 4.0

Education (year)

P

0.836 0.020

<9

9 (22.0%)

0 (0.0%)

9-12

20 (48.8%)

12 (50.0%) 32 (49.2%)

>12

12 (29.3%)

12 (50.0%) 24 (36.9%)

MMSE at baseline

28.4 ± 1.3

28.9 ± 1.0

Neuroticism (N)

78.0 ± 17.6

79.0 ± 21.1 78.4 ± 18.8

0.834

Extraversion (E)

99.8 ± 13.8

99.9 ± 17.7 99.8 ± 15.2

0.981

*

9 (13.8%)

28.6 ± 1.2

0.103

111.9 ± Openness (O)

112.1 ± 17.7

15.9

Agreeableness (A)

135.9 ± 14.7

120.5±18.7 130.2 ± 17.8

< 0.001 *

111.6 ± 17.2

117.5±14.3 113.8 ± 16.4

0.160

112.0 ± 16.9

0.972

Conscientiousness (C) Amyloid

0.059

Negative

30 (73.2%)

12 (50.0%) 42 (64.6%)

Positive

11 (26.8%)

12 (50.0%) 23 (35.4%)

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APOE4

0.775

Negative

33 (80.5%)

20 (83.3%) 53 (81.5%)

Positive

8 (19.5%)

4 (16.7%)

12 (18.5%)

cognition

-0.1 ± 3.7

-2.3 ± 3.6

-0.9 ± 3.8

0.027

Mean SUVr

0.6 ± 0.1

0.6 ± 0.1

0.6 ± 0.1

0.334

Change in *

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Table 2.

Association between brain region volume change by side and personality

dimensions assessed with univariate and multiple mixed linear regression, adjusted for time, sex, APOE4, amyloid and change in cognition. The random intercept is the participant’s id and the age is the random slope. P-values are uncorrected. The Benjamini-Hochberg threshold is p =

0.0075 for the univariate and p = 0.005 for the multivariable analysis

(significant associations after correction are in Bold).

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Supplementary material

Table 3. Association between brain region volume change by side and facets of Agreeableness and Openness assessed with multiple mixed linear regression, adjusted for time, sex, APOE4, amyloid and change in cognition. The random intercept is the participant’s id and the age is the random slope. P-values are uncorrected. The Benjamini-Hochberg threshold is 0.010 for the left and .00083 for the right side (see text for details).

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FIGURE LEGEND Fig. 1. Radar plot showing the univariate and multivariable regression coefficients of the 5 major personality traits (N: Neuroticism, E: Extraversion, O: Openness, A-: Agreeableness with a reversed scale, C: Conscientiousness) associated with brain volume loss in 9 brain regions. Red line: Left side; Blue line: right side. Red circle: left side P < 0.05; Blue square: right side P < 0.05.

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Left Side Univariate Brain region

Personality dimensions

Medial temporal lobe

Neuroticism Extraversion Openness Agreeableness Conscientiousness Neuroticism Extraversion Openness Agreeableness Conscientiousness Neuroticism Extraversion Openness Agreeableness Conscientiousness Neuroticism Extraversion Openness Agreeableness Conscientiousness Neuroticism Extraversion Openness Agreeableness Conscientiousness Neuroticism Extraversion Openness Agreeableness Conscientiousness Neuroticism Extraversion Openness Agreeableness Conscientiousness Neuroticism Extraversion Openness Agreeableness Conscientiousness

Hippocampus

Entorhinal area

Amygdala

Precuneus

Caudate

Fusiform gyrus

Thalamus proper

Coeff (95% CI)

-0.001 (-0.013,0.011) 0.012 (-0.002,0.027) 0.016 (0.003,0.029) -0.026 (-0.037,-0.015) -0.005 (-0.018,0.009) 0.001 (-0.003,0.005) 0.005 (-0.001,0.010) 0.009 (0.004,0.013) -0.007 (-0.011,-0.003) -0.003 (-0.008,0.002) -0.002 (-0.006,0.002) 0.002 (-0.003,0.006) 0.003 (-0.002,0.007) -0.007 (-0.011,-0.004) -0.000 (-0.005,0.004) -0.001 (-0.002,0.001) 0.001 (-0.001,0.003) 0.002 (0.000,0.003) -0.003 (-0.004,-0.002) 0.000 (-0.002,0.002) -0.011 (-0.027,0.006) 0.007 (-0.013,0.028) -0.005 (-0.024,0.013) -0.035 (-0.050,-0.020) -0.008 (-0.026,0.011) -0.000 (-0.005,0.005) 0.004 (-0.002,0.010) 0.003 (-0.002,0.008) -0.004 (-0.009,0.001) -0.002 (-0.008,0.003) -0.010 (-0.021,0.002) 0.004 (-0.011,0.018) 0.009 (-0.004,0.022) -0.007 (-0.020,0.005) -0.003 (-0.016,0.011) -0.000 (-0.008,0.007) 0.005 (-0.004,0.013) 0.004 (-0.003,0.012) -0.012 (-0.019,-0.005) -0.001 (-0.009,0.007)

Right side Multiple

p

0.817 0.098 0.014 0.000 0.511 0.657 0.098 0.000 0.002 0.198 0.269 0.497 0.227 0.000 0.878 0.300 0.185 0.046 0.000 0.779 0.200 0.474 0.561 0.000 0.411 0.916 0.168 0.258 0.140 0.392 0.111 0.616 0.184 0.239 0.709 0.946 0.304 0.272 0.001 0.858

Coeff (95% CI)

-0.003 (-0.012,0.007) 0.005 (-0.007,0.017) 0.010 (-0.000,0.020) -0.017 (-0.026,-0.007) -0.009 (-0.019,0.001) 0.001 (-0.003,0.005) 0.003 (-0.002,0.008) 0.007 (0.002,0.011) -0.005 (-0.010,-0.001) -0.004 (-0.009,0.000) -0.002 (-0.006,0.001) -0.000 (-0.004,0.004) 0.001 (-0.003,0.005) -0.005 (-0.008,-0.001) -0.002 (-0.005,0.002) -0.001 (-0.002,0.000) 0.000 (-0.001,0.002) 0.001 (-0.000,0.002) -0.002 (-0.003,-0.000) -0.000 (-0.002,0.001) -0.010 (-0.024,0.004) 0.003 (-0.015,0.021) -0.005 (-0.021,0.010) -0.022 (-0.037,-0.007) -0.015 (-0.030,-0.000) -0.000 (-0.005,0.005) 0.002 (-0.004,0.008) 0.002 (-0.003,0.007) -0.001 (-0.006,0.004) -0.003 (-0.008,0.002) -0.009 (-0.019,0.001) 0.001 (-0.012,0.015) 0.008 (-0.004,0.020) 0.005 (-0.006,0.017) -0.008 (-0.020,0.003) -0.000 (-0.007,0.006) 0.002 (-0.006,0.010) 0.004 (-0.003,0.011) -0.006 (-0.012,0.001) -0.004 (-0.011,0.003)

Univariate p

Coeff (95% CI)

0.587 0.391 0.055 0.001 0.065 0.692 0.276 0.003 0.016 0.066 0.140 0.969 0.580 0.008 0.350 0.169 0.665 0.143 0.014 0.755 0.154 0.740 0.502 0.005 0.050 0.979 0.471 0.412 0.676 0.210 0.080 0.863 0.175 0.370 0.171 0.879 0.559 0.302 0.115 0.278

0.005 (-0.007,0.018) 0.016 (0.001,0.031) 0.013 (0.000,0.027) -0.023 (-0.034,-0.011) -0.001 (-0.015,0.013) 0.002 (-0.002,0.007) 0.006 (0.001,0.012) 0.006 (0.001,0.011) -0.005 (-0.010,-0.001) -0.001 (-0.006,0.004) 0.001 (-0.003,0.005) 0.002 (-0.003,0.007) 0.001 (-0.003,0.005) -0.007 (-0.011,-0.004) -0.000 (-0.004,0.004) 0.000 (-0.001,0.002) 0.001 (-0.000,0.003) 0.001 (-0.001,0.003) -0.003 (-0.004,-0.001) 0.000 (-0.001,0.002) -0.008 (-0.025,0.009) 0.012 (-0.009,0.033) -0.001 (-0.020,0.018) -0.030 (-0.047,-0.013) -0.006 (-0.025,0.014) -0.000 (-0.005,0.005) 0.005 (-0.001,0.011) 0.005 (-0.000,0.010) -0.002 (-0.007,0.003) -0.003 (-0.009,0.002) -0.007 (-0.020,0.006) 0.001 (-0.015,0.017) 0.007 (-0.007,0.021) -0.015 (-0.029,-0.002) -0.003 (-0.018,0.011) -0.001 (-0.008,0.006) 0.004 (-0.005,0.013) 0.005 (-0.003,0.013) -0.011 (-0.018,-0.003) 0.002 (-0.006,0.010)

Multiple p

0.378 0.032 0.048 0.000 0.894 0.332 0.027 0.011 0.024 0.736 0.754 0.477 0.629 0.000 0.994 0.765 0.137 0.199 0.000 0.597 0.364 0.253 0.894 0.000 0.571 0.948 0.119 0.074 0.519 0.222 0.287 0.892 0.344 0.026 0.648 0.776 0.434 0.243 0.004 0.638

Coeff (95% CI)

0.004 (-0.006,0.013) 0.008 (-0.004,0.021) 0.005 (-0.005,0.016) -0.013 (-0.023,-0.002) -0.005 (-0.016,0.005) 0.002 (-0.002,0.006) 0.005 (-0.001,0.010) 0.004 (-0.001,0.009) -0.004 (-0.009,0.001) -0.002 (-0.007,0.003) -0.000 (-0.003,0.003) 0.000 (-0.004,0.004) -0.001 (-0.004,0.003) -0.005 (-0.008,-0.001) -0.002 (-0.005,0.002) 0.000 (-0.001,0.001) 0.001 (-0.001,0.002) 0.000 (-0.001,0.002) -0.002 (-0.003,-0.000) 0.000 (-0.001,0.002) -0.008 (-0.022,0.006) 0.011 (-0.007,0.029) -0.001 (-0.018,0.015) -0.014 (-0.030,0.002) -0.014 (-0.030,0.002) 0.000 (-0.005,0.005) 0.003 (-0.003,0.009) 0.003 (-0.002,0.009) 0.001 (-0.005,0.006) -0.004 (-0.009,0.001) -0.006 (-0.017,0.006) -0.002 (-0.017,0.013) 0.006 (-0.008,0.019) -0.004 (-0.017,0.010) -0.009 (-0.022,0.004) -0.002 (-0.008,0.004) 0.002 (-0.006,0.010) 0.004 (-0.003,0.011) -0.003 (-0.010,0.004) -0.001 (-0.008,0.006)

p

0.421 0.168 0.334 0.016 0.324 0.338 0.102 0.086 0.132 0.526 0.915 0.980 0.711 0.006 0.371 0.847 0.467 0.916 0.011 0.858 0.253 0.236 0.880 0.095 0.089 0.942 0.404 0.208 0.773 0.113 0.330 0.799 0.405 0.585 0.182 0.504 0.674 0.304 0.336 0.720

Left Side Univariate Brain region

Personality dimensions

Medial temporal lobe Neuroticism Extraversion Openness Agreeableness Conscientiousness Hippocampus Neuroticism Extraversion Openness Agreeableness Conscientiousness Entorhinal area Neuroticism Extraversion Openness Agreeableness Conscientiousness Amygdala Neuroticism Extraversion Openness Agreeableness Conscientiousness Precuneus Neuroticism Extraversion Openness Agreeableness Conscientiousness Caudate Neuroticism Extraversion Openness Agreeableness Conscientiousness Fusiform gyrus Neuroticism Extraversion Openness Agreeableness Conscientiousness Thalamus proper Neuroticism Extraversion Openness Agreeableness Conscientiousness

Right side Multiple

Coeff (95% CI)

p

Coeff (95% CI)

-0.001 (-0.013,0.011) 0.012 (-0.002,0.027) 0.016 (0.003,0.029) -0.026 (-0.037,-0.015) -0.005 (-0.018,0.009) 0.001 (-0.003,0.005) 0.005 (-0.001,0.010) 0.009 (0.004,0.013) -0.007 (-0.011,-0.003) -0.003 (-0.008,0.002) -0.002 (-0.006,0.002) 0.002 (-0.003,0.006) 0.003 (-0.002,0.007) -0.007 (-0.011,-0.004) -0.000 (-0.005,0.004) -0.001 (-0.002,0.001) 0.001 (-0.001,0.003) 0.002 (0.000,0.003) -0.003 (-0.004,-0.002) 0.000 (-0.002,0.002) -0.011 (-0.027,0.006) 0.007 (-0.013,0.028) -0.005 (-0.024,0.013) -0.035 (-0.050,-0.020) -0.008 (-0.026,0.011) -0.000 (-0.005,0.005) 0.004 (-0.002,0.010) 0.003 (-0.002,0.008) -0.004 (-0.009,0.001) -0.002 (-0.008,0.003) -0.010 (-0.021,0.002) 0.004 (-0.011,0.018) 0.009 (-0.004,0.022) -0.007 (-0.020,0.005) -0.003 (-0.016,0.011) -0.000 (-0.008,0.007) 0.005 (-0.004,0.013) 0.004 (-0.003,0.012) -0.012 (-0.019,-0.005) -0.001 (-0.009,0.007)

0.817 0.098 0.014 0.000 0.511 0.657 0.098 0.000 0.002 0.198 0.269 0.497 0.227 0.000 0.878 0.300 0.185 0.046 0.000 0.779 0.200 0.474 0.561 0.000 0.411 0.916 0.168 0.258 0.140 0.392 0.111 0.616 0.184 0.239 0.709 0.946 0.304 0.272 0.001 0.858

-0.003 (-0.012,0.007) 0.005 (-0.007,0.017) 0.010 (-0.000,0.020) -0.017 (-0.026,-0.007) -0.009 (-0.019,0.001) 0.001 (-0.003,0.005) 0.003 (-0.002,0.008) 0.007 (0.002,0.011) -0.005 (-0.010,-0.001) -0.004 (-0.009,0.000) -0.002 (-0.006,0.001) -0.000 (-0.004,0.004) 0.001 (-0.003,0.005) -0.005 (-0.008,-0.001) -0.002 (-0.005,0.002) -0.001 (-0.002,0.000) 0.000 (-0.001,0.002) 0.001 (-0.000,0.002) -0.002 (-0.003,-0.000) -0.000 (-0.002,0.001) -0.010 (-0.024,0.004) 0.003 (-0.015,0.021) -0.005 (-0.021,0.010) -0.022 (-0.037,-0.007) -0.015 (-0.030,-0.000) -0.000 (-0.005,0.005) 0.002 (-0.004,0.008) 0.002 (-0.003,0.007) -0.001 (-0.006,0.004) -0.003 (-0.008,0.002) -0.009 (-0.019,0.001) 0.001 (-0.012,0.015) 0.008 (-0.004,0.020) 0.005 (-0.006,0.017) -0.008 (-0.020,0.003) -0.000 (-0.007,0.006) 0.002 (-0.006,0.010) 0.004 (-0.003,0.011) -0.006 (-0.012,0.001) -0.004 (-0.011,0.003)

Univariate p

0.587 0.391 0.055 0.001 0.065 0.692 0.276 0.003 0.016 0.066 0.140 0.969 0.580 0.008 0.350 0.169 0.665 0.143 0.014 0.755 0.154 0.740 0.502 0.005 0.050 0.979 0.471 0.412 0.676 0.210 0.080 0.863 0.175 0.370 0.171 0.879 0.559 0.302 0.115 0.278

Multiple

Coeff (95% CI)

p

Coeff (95% CI)

p

0.005 (-0.007,0.018) 0.016 (0.001,0.031) 0.013 (0.000,0.027) -0.023 (-0.034,-0.011) -0.001 (-0.015,0.013) 0.002 (-0.002,0.007) 0.006 (0.001,0.012) 0.006 (0.001,0.011) -0.005 (-0.010,-0.001) -0.001 (-0.006,0.004) 0.001 (-0.003,0.005) 0.002 (-0.003,0.007) 0.001 (-0.003,0.005) -0.007 (-0.011,-0.004) -0.000 (-0.004,0.004) 0.000 (-0.001,0.002) 0.001 (-0.000,0.003) 0.001 (-0.001,0.003) -0.003 (-0.004,-0.001) 0.000 (-0.001,0.002) -0.008 (-0.025,0.009) 0.012 (-0.009,0.033) -0.001 (-0.020,0.018) -0.030 (-0.047,-0.013) -0.006 (-0.025,0.014) -0.000 (-0.005,0.005) 0.005 (-0.001,0.011) 0.005 (-0.000,0.010) -0.002 (-0.007,0.003) -0.003 (-0.009,0.002) -0.007 (-0.020,0.006) 0.001 (-0.015,0.017) 0.007 (-0.007,0.021) -0.015 (-0.029,-0.002) -0.003 (-0.018,0.011) -0.001 (-0.008,0.006) 0.004 (-0.005,0.013) 0.005 (-0.003,0.013) -0.011 (-0.018,-0.003) 0.002 (-0.006,0.010)

0.378 0.032 0.048 0.000 0.894 0.332 0.027 0.011 0.024 0.736 0.754 0.477 0.629 0.000 0.994 0.765 0.137 0.199 0.000 0.597 0.364 0.253 0.894 0.000 0.571 0.948 0.119 0.074 0.519 0.222 0.287 0.892 0.344 0.026 0.648 0.776 0.434 0.243 0.004 0.638

0.004 (-0.006,0.013) 0.008 (-0.004,0.021) 0.005 (-0.005,0.016) -0.013 (-0.023,-0.002) -0.005 (-0.016,0.005) 0.002 (-0.002,0.006) 0.005 (-0.001,0.010) 0.004 (-0.001,0.009) -0.004 (-0.009,0.001) -0.002 (-0.007,0.003) -0.000 (-0.003,0.003) 0.000 (-0.004,0.004) -0.001 (-0.004,0.003) -0.005 (-0.008,-0.001) -0.002 (-0.005,0.002) 0.000 (-0.001,0.001) 0.001 (-0.001,0.002) 0.000 (-0.001,0.002) -0.002 (-0.003,-0.000) 0.000 (-0.001,0.002) -0.008 (-0.022,0.006) 0.011 (-0.007,0.029) -0.001 (-0.018,0.015) -0.014 (-0.030,0.002) -0.014 (-0.030,0.002) 0.000 (-0.005,0.005) 0.003 (-0.003,0.009) 0.003 (-0.002,0.009) 0.001 (-0.005,0.006) -0.004 (-0.009,0.001) -0.006 (-0.017,0.006) -0.002 (-0.017,0.013) 0.006 (-0.008,0.019) -0.004 (-0.017,0.010) -0.009 (-0.022,0.004) -0.002 (-0.008,0.004) 0.002 (-0.006,0.010) 0.004 (-0.003,0.011) -0.003 (-0.010,0.004) -0.001 (-0.008,0.006)

0.421 0.168 0.334 0.016 0.324 0.338 0.102 0.086 0.132 0.526 0.915 0.980 0.711 0.006 0.371 0.847 0.467 0.916 0.011 0.858 0.253 0.236 0.880 0.095 0.089 0.942 0.404 0.208 0.773 0.113 0.330 0.799 0.405 0.585 0.182 0.504 0.674 0.304 0.336 0.720

Univariate

Multivariate

N

Amygdala

N

C

E

A-

0 .06 .13

C

O

E

A-

N

Entorhinal area

E

A-

C

O

E

A-

N

Hippocampus

E

A-

O

E

A-

E

A-

O

E

A-

E

A-

O

E

A-

E

A-

O

E

A-

E

A-

O

E

A-

E

A-

O

E

A-

E

A-

0 .06 .13

O

N

C 0 .06 .13

O

C

N

Thalamus proper

0 .06 .13

N

C 0 .06 .13

O

C

N

Fusiform gyrus

0 .06 .13

N

C 0 .06 .13

O

C

N

Cerebellum exterior

0 .06 .13

N

C 0 .06 .13

O

C

N

Caudate

0 .06 .13

N

C 0 .06 .13

O

C

N

Precuneus

0 .06 .13

N

C 0 .06 .13

O

C

N

Medial temporal lobe

0 .06 .13

N

C 0 .06 .13

O

N

C 0 .06 .13

0 .06 .13

O

C

E

A-

0 .06 .13

O

Less agreeable, better preserved? A PET amyloid and MRI study in a communitybased cohort, Panteleimon Giannakopoulos, Cristelle Rodriguez, Marie-Louise Montandon, Valentina Garibotto, Sven Haller, François R. Herrmann.

Highlights •

Lower Agreeableness is associated with better preservation of limbic areas

•

Aging-related hippocampal volume decrease is lower in elders with higher openness

•

Personality impact on brain volume is independent of amyloid load and APOE genotype