Determinants of mesial temporal lobe volume loss in older individuals with preserved cognition: a longitudinal PET amyloid study

Journal Pre-proof Determinants of mesial temporal lobe volume loss in older individuals with preserved cognition: a longitudinal PET amyloid study Marie-Louise Montandon, François R. Herrmann, Valentina Garibotto, Cristelle Rodriguez, Sven Haller, Panteleimon Giannakopoulos PII:

S0197-4580(19)30429-4

DOI:

https://doi.org/10.1016/j.neurobiolaging.2019.12.002

Reference:

NBA 10728

To appear in:

Neurobiology of Aging

Received Date: 7 June 2019 Revised Date:

3 December 2019

Accepted Date: 5 December 2019

Please cite this article as: Montandon, M.-L., Herrmann, F.R., Garibotto, V., Rodriguez, C., Haller, S., Giannakopoulos, P., Determinants of mesial temporal lobe volume loss in older individuals with preserved cognition: a longitudinal PET amyloid study, Neurobiology of Aging (2020), doi: https:// doi.org/10.1016/j.neurobiolaging.2019.12.002. 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. © 2019 Published by Elsevier Inc.

Determinants of mesial temporal lobe volume loss in older individuals with preserved cognition: a longitudinal PET amyloid study

Marie-Louise Montandon a,b*, François R. Herrmann a*, Valentina Garibotto h, Cristelle Rodriguez b,g, Sven Haller c,d,e,f, Panteleimon Giannakopoulos b,g

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

*equally first authors

Running title: Mesial temporal lobe volume loss in aging

Correspondence address:

Prof. François Herrmann Division of Geriatrics, Department of Rehabilitation and Geriatrics Geneva University Hospitals Hôpital des Trois-Chêne 3, Chemin du Pont Bochet CH 1226 THONEX Switzerland Direct line

+41 22 305 6681

Fax office 1

+41 22 305 6115

[email protected]

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Abstract Mesial temporal lobe (MTL) is prominently affected in normal aging and associated with neurodegeneration in AD. Whether or not MTL atrophy is dependent on increasing amyloid load prior to the emergence of cognitive deficits is still disputed. We performed a 4.5-year longitudinal study in 75 older community dwellers (48 women, mean age: 79.3 years) including MRI at baseline and follow-up, PET amyloid during follow-up, neuropsychological assessment at 18 and 55 months, and APOE genotyping. Linear regression models were used to identify predictors of the MTL volume loss. Amyloid load was negatively associated with bilateral MTL volume at baseline explaining almost 10.5% of its variability. In multivariate models including time of follow-up as well as demographic variables (older age, male gender) this percentage exceeded 35%. The APOE4 allele independently contributed another 6%. Cognitive changes had a modest but still significant negative association with MTL volume loss. Our data support a multifactorial model including amyloid deposition, older age, male gender, APOE4 allele and slight decline of cognitive abilities as independent predictors of MTL volume loss in brain aging.

Keywords: mesial temporal lobe, amyloid load, structural MRI, APOE, cognitive changes, normal aging

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1. Introduction After age 35 years, a steady brain volume loss has been reported that increases from 0.2% to reach 0.5% annually at age 60. Over 60, the brain volume loss exceeds 0.5% annually (Hedman, et al., 2012). This atrophy rate is more than doubled in cases with mild Alzheimer disease (AD) (Fotenos, et al., 2005). However, not all brain areas are equally exposed to this process. Limbic regions, and in particular mesial temporal lobe (MTL) structures are prominently affected by the aging process and early stages of dementia, notably AD. The volume of MTL is already modulated in early life by negative events (Gerritsen, et al., 2015) but also engagement in enriching activities (Moored, et al., 2018). This area also undergoes an age-related decrease of its volume (Kurth, et al., 2019,Stoub, et al., 2012) as part of normative aging. Longitudinal studies conducted on cohorts of cognitively normal elders have reported that hippocampal atrophy often associated with changes of adjacent medial temporal substructures is already present at the pre-mild cognitive impairment (MCI) stages (Bernard, et al., 2014) Schroder and Pantel, 2016; (Smith, et al., 2012); (Schroder and Pantel, 2016,Smith, et al., 2007), up to 10 years before the diagnosis of dementia (Tondelli, et al., 2012). MTL volume loss was also reported in cases with subjective cognitive complaints (Chao, et al., 2010) (Jessen, et al., 2006) (Saykin, et al., 2006). It was initially thought that the morphological alterations in MTL become detectable in structural magnetic resonance imaging (MRI) only after the development of amyloid pathology (Younes, et al., 2014). Postmortem analyses suggested that tau pathology in the transentorhinal cortex is common by age 60, whereas spread to neocortical regions and worsening of cognition is usually associated with amyloid deposits (Hedden, et al., 2013). However, in a series of 1209 cognitively intact individuals aged 50 to 95, Jack and collaborators (Jack, et al., 2015) showed that hippocampal volume loss may occur before abnormal amyloid PET occurrence pointing to the relevance of preexisting structural deficits that are associated with aging and are independent on the current amyloid pathologydetermined definition of preclinical AD. Similar observations were reported by Edmonds and coworkers indicating that neurodegeneration alone was 2.5 times more common than

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amyloidosis alone among healthy individuals (Edmonds, et al., 2015). In the same line, using tau-specific and Aβ-specific positron emission tomography tracers, Maass and coworkers recently reported that MTL tau pathology is associated with episodic-memory performance and MTL atrophy in cognitively normal adults, independent of Aβ (Maass, et al., 2018).

In order to identify the participation of amyloid pathology in age-related MRI volume loss of MTL, we report here the results of a 4.5-year longitudinal study in a cohort of older community dwellers with PET amyloid documentation, neuropsychological follow-up after a mean period of 18 and 55 months and MRI scans performed at inclusion and last follow-up. Our results imply a significant deleterious effect of amyloid pathology but also indicate an independent association between MTL volume loss and older age, male gender, APOE epsilon 4 status and declining cognitive trajectories.

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 a large population-based longitudinal study on healthy aging that is still on going in the Geneva and Lausanne counties (van der Thiel, et al., 2018,Xekardaki, et al., 2015,Zanchi, et al., 2017). All of the cases were recruited via advertisements in local newspapers and media. The cohort included 526 older Caucasian white 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 55 months, brain amyloid PET information available during follow-up, structural brain MRI at baseline and 55-months post-inclusion and APOE status were considered. Exclusion criteria included psychiatric or neurologic disorders, sustained head injury, history of major medical disorders (neoplasm or cardiac illness), alcohol or drug

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abuse,

regular

use

of

neuroleptics,

antidepressants

or

psychostimulants

and

contraindications to PET or MRI. 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 final sample included 75 older controls: 48 women and 27 men, mean age: 79.3 ± 4.0 (mean ± SD) ranging from 68.6 to 90.0 years.

2.2. Neuropsychological assessment At baseline, all individuals were evaluated with an extensive neuropsychological battery, including the Mini-Mental State Examination (MMSE) (Folstein, et al., 1975), the Hospital Anxiety and Depression Scale (HAD (Zigmond and Snaith, 1983), and the Lawton Instrumental Activities of Daily Living (IADL (Barberger-Gateau, et al., 1992)). Cognitive assessment included (a) attention (Digit-Symbol-Coding (Wechsler, 1997), Trail Making Test A (Reitan, 1958), (b) working memory (verbal: Digit Span Forward (Wechsler, 1955)), visuospatial: Visual Memory Span (Corsi) (Milner, 1971), (c) episodic memory (verbal: RI-48 Cued Recall Test (Buschke, et al., 1997)), visual: Shapes Test (Baddley, et al., 1994), (d) executive functions (Trail Making Test B (Reitan, 1958), Wisconsin Card Sorting Test and Phonemic Verbal Fluency Test (Heaton, et al., 1993), (e) language (Boston Naming (Kaplan, et al., 1983), (f) visual gnosis (Ghent Overlapping Figures), (g) praxis: ideomotor (Schnider, et al., 1997), reflexive (Poeck, 1985), and constructional (Consortium to Establish a Registry for Alzheimer’s Disease (CERAD), Figures copy (Welsh, et al., 1994)). 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. (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 55 months.

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The subtle cognitive decline continuous score was defined and computed as follows. Most of the cognitive performances, discrete or continuous, cannot be linearly combined by adding the individual scores to a unique composite cognitive score. Thus, all values were converted to z scores. Subsequently, we summed the number of cognitive tests at follow-up with performances at least 0.5 standard deviation (SD) higher compared with the first evaluation, leading to the number of tests with improved performances (range, 0–14). Similarly, we summed the number of cognitive tests at follow-up with performances at least 0.5 SDs lower compared with the first evaluation, yielding the number of tests with decreased performances (range, 0–14). Finally, the number of tests with improved minus the number of tests with decreased performances results in a final continuous cognitive score. Change in cognition between inclusion and last follow-up was defined as the sum of the continuous cognitive scores at two follow-ups. This variable was used in all subsequent regression models.

2.3. Amyloid PET imaging All of the cases had

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F-Florbetapir- (Amyvid) or

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F-Flutemetanol-PET (Vizamyl) scans

acquired on 2 different instruments (66 cases with Siemens BiographTM mCT scanner and 9 cases with GE Healthcare Discovery PET/CT 710 scanner) of varying resolution and following different platform-specific acquisition protocols. There were no significant differences in clinical and demographic variables as well as MTL volume and Fazekas score at inclusion between the two PET scanner samples (Supplementary Table 1). The Florbetapir images were acquired 50 to 70 minutes after injection and the

18

F-

18

F-Flutemetanol

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 multicentre acquisitions. More information on the different imaging protocols for PET acquisition can be found on the ADNI web site (https://adni.loni.usc.edu/methods/).

All scans were intensity normalized using a modified Centiloid pons VOI created by Lilja et al. (2018). Cortical standard uptake value ratios (SUVR) were then calculated using the cortex

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as target region. Moreover, all scans were spatially normalized to the synthetic Aβ template developed by Lilja and coworkers (2018), which spans the whole range from Aβ-negative to Aβ-positive. The visual analysis of amyloid PET images was conducted by an independent, board-certified specialist in nuclear medicine, following the tracer-specific standardized operating procedures. They had to be classified as either typical Aβ-negative or Aβ-positive images.

2.4. 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 (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 4.4 ± 0.6 years. All of our cases were assessed with the same MRI scan. Since we performed a between-group analysis, potential scanner-related systematic bias should be canceled. Given the fact that MRI scan change is a usual phenomenon in the course of long follow-up, we carefully matched the MR sequences between both scanners. The software used contains algorithms to minimize scanner-related effects.

Automatic MR volumetry of both baseline and follow-up MRI was performed with the fully automated multi-atlas segmentation tool cNeuro (Combinostics Ltd, Tampere, Finland, https://www.cneuro.com/cmri/) as described by Lötjönen et al. (Lotjonen, et al., 2010) We focused on the estimated volume of left and right mesial temporal lobe, which was computed as a combination of amygdala, hippocampus, entorhinal cortex and parahippocampal gyrus (Fig. 1). MTL volume loss was calculated as follows: (volume baseline – volume follow-up) /

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(volume baseline x time in years). Given the relatively small sample size and in order to avoid multiple comparison biases, we did not perform separate MRI analysis of amygdala, hippocampal subdivisions and entorhinal cortex.

2.5. APOE status APOE status was assessed as described earlier (Zanchi, et al., 2017). Subjects were divided based on if they were a carrier of the APOE epsilon 4 allele (4/3 versus 3/3, 3/2 carriers).

2.6. Statistical analysis Demographic and neuropsychological data were compared between the two visits with paired t-test and Wilcoxon matched-pairs signed rank test. The significance level was set at P < 0.05 but was corrected to P < 0.0079 for multiple testing by using the BenjaminiHochberg method (Green and Diggle, 2007). Simple and multiple linear regression models were used to identify predictors of the MTL volume loss (dependent variable) including time, gender, age, mean SUVR, APOE genotyping and continuous cognitive score. Models with only the significant variables were built by a stepwise forward multivariate process to assess the added value of each variable in predicting MTL volume loss with the coefficient of determination (R-squared). All statistics were performed with the STATA statistical software, Version 15.1 (StataCorp, College Station, Texas, 2017).

3. Results Demographic data show no gender-related differences in age, APOE epsilon 4 allele frequency, MMSE scores at baseline, and amyloid load. Men were significantly more educated than women (p=0.003). However, the continuous cognitive score (combined on the basis of two follow-ups) decreased in men but remained fairly stable in women (p=0.001) According to the visual score, 72.9% of women and 51.9% of men were Aβ-negative (p=0.012). The mean SUVr varied between 0.5 and 0.7 (Table 1). This variable was used for

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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).

In univariate models, amyloid load was negatively associated with bilateral MTL volume at baseline explaining almost 10.5% of its variability (Fig. 2). As expected, at 4.5-year follow-up, a significant but still modest decrease of MTL volume was observed bilaterally (respectively 0.44 cm3 and -0.38 cm3 of right and left MTL volume loss). Multivariate models predicting MTL volume loss with amyloid, age at baseline and gender increased the percentage of explained variability to 43% (left hemisphere) and 35% (right hemisphere). In these models, amyloid load, older age at baseline and male gender were all independent predictors of MTL volume loss. Education was not related to MTL volume loss and was not included in multivariate regression models. The addition of APOE epsilon 4 allele as co-regressor increased the percentage of variability explained by the model to 49% and 41% (left and right hemisphere respectively). Importantly, changes in the continuous cognitive score had a modest but still significant negative association with MTL volume bilaterally. The simultaneous assessment of demographic variables, APOE status, and neuropsychological parameters accounts for 40% of left MTL volume loss variability (compared to 11% explained by amyloid load alone) and 35% of right MTL volume loss variability (compared to 10% explained by amyloid load alone) (Table 2). Adding Fazekas score (data not shown) did not change the results as it was not significantly different between the two gender groups.

4. Discussion Our data show that the deleterious effect of amyloid deposition on MTL integrity is significant, persists after controlling for demographic variables and presence of APOE epsilon 4 allele but remains of modest magnitude in healthy elders. Older age at baseline, male gender, APOE epsilon 4 allele and type of cognitive trajectories are all independent predictors of MTL volume loss in this population. The present findings also reveal that the concomitant

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consideration of these parameters explain almost 50% of MTL volume loss variability in normal aging.

The impact of amyloid deposition on MTL volume in normal aging remains a controversial issue. In older controls, MTL atrophy over time has been associated with decreased CSF Aβ42, increased neocortical PIB retention, and presence of naturally occurring anti-amyloid β autoantibodies (Hsu, et al., 2015,Pettigrew, et al., 2017) (Kimura, et al., 2017). Depending on the characteristics of the sample, the effect size was, however, small with moderate sensitivity and low specificity for AD (for review see (Pettigrew, et al., 2017)). Moreover, negative data were also reported raising further doubts about the deleterious impact of amyloid accumulation on MTL integrity (Chetelat, et al., 2013,Guzman, et al., 2013,Whitwell, et al., 2013). Our data in a cohort of highly educated community-based older individuals without significant vascular pathologies reveal that amyloid load, measured as mean SUVR with thalamus-pons normalization, has an independent but modest negative association with MTL volume. Our regression models show that this single parameter explains 10 to 11% of MTL volume variability in normal aging. When MTL volume loss over the three-year follow-up period was considered, amyloid accumulation persisted as negative predictor in agreement with previous CSF observations (Kimura, et al., 2017,Pettigrew, et al., 2017). However, the impact of amyloid deposition on MTL volume loss was much weaker compared to that of older age and male gender. The progressive loss of MTL grey matter with advanced age has been well documented mainly in cases that develop MCI or AD 3-4 years later (Bernard, et al., 2014,Schroder and Pantel, 2016,Smith, et al., 2012,Smith, et al., 2007). Our data show that the MTL volume loss is also present in older cases that remained within the normal range at a 4.5-year follow-up. Besides older age, male gender was also related to increased MTL volume loss in the present series. This finding parallels the observation of lower volumes over time in men in the left thalamus, right caudate nucleus, and right precuneus in healthy controls. Intriguingly, men had strikingly worst cognitive trajectories at follow-up time points compared to women. Although their neuropsychological performances remained

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within the normal range, they declined slightly but continuously during the 3 year follow-up period pointing to the need to consider sexual dimorphism when interpreting both cognitive trajectories and brain volume loss in the initial phases of brain aging (Skup, et al., 2011). Last but not least, APOE4 genotype explains only 8% of MTL volume variability. In healthy older controls, the APOE4 effect on brain structure remains unclear. Decreased GM volume in the caudate nuclei and the right cingulate gyrus as well as posterior cingulate cortex were found (Barnaure, et al., 2017,Farpour-Lambert, et al., 2009). However, negative data were also reported (Chen, et al., 2015,Lupton, et al., 2016) (Habes, et al., 2016). As for amyloid deposition, our data show that although statistically significant, the effect of APOE4 on MTL volume loss remains of low magnitude.

Taking together, these data allow for defining the relative contribution of the various determinants of MRI volumetric changes in MTL. Besides amyloid load, older age, male gender, and APOE4 genotype are independently associated with MTL volume loss. In the absence of a longer follow-up, we cannot exclude that some of our cases could develop clinically overt cognitive decline at later time points. Importantly, the careful assessment of neuropsychological performances (inclusion, 18 months, 55 months) makes it possible to define cognitive trajectories within the normal range in our sample. This variable was independently associated with increased MTL volume loss after controlling for demographic variables, APOE4 genotype and amyloid accumulation pointing to the possible relationship between slight but continuous decrement of cognitive performances prior to the mild cognitive impairment state and MTL volume loss. Our observations parallel a recent report by Albert and collaborators (Albert, et al., 2018) who postulated that the combination of six independent measures (hippocampal and entorhinal cortex volume, cognitive tests score, APOE4 allele, amyloid load and phosphorylated tau) predict the progression from normal cognition to the onset of MCI in a cohort of cognitively intact elders. Among these parameters and as reported by Pontecorvo and coworkers (Pontecorvo, et al., 2017), MTL lobe volumetric changes are mostly related to aging process whereas the development of tau

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pathology and subsequent loss of grey matter beyond the MTL may be dependent on amyloid accumulation.

Two methodological considerations should be taken into account when interpreting these data. First, in order to examine the global changes in limbic areas known to be particularly vulnerable to the degenerative process and remain close to routine clinical settings, we opted for analysing MTL volumes in toto without reference to hippocampal subdivisions, entorhinal cortex and amygdala. Second, all together the demographic, genetic and imaging parameters taken into account explain almost 50% of the variability in MTL volume. Local tau pathology has not been assessed in the present study and may represent an additional determinant of grey matter changes in MTL in the absence of significant vascular pathology (Iaccarino, et al., 2018). However, the association between tau pathology and MTL volume loss in cognitively preserved individuals is by far not established with two recent studies leading to negative or ambiguous data (Aschenbrenner, et al., 2018) (Shigemoto, et al., 2018). Moreover, tau accumulation in MTL is reported to be quite low (less than 0.5% per year) in cognitively preserved cases even in the presence of increased amyloid load (Jack, et al., 2018). Whether such low level of tau pathology determines the loss of grey matter in MTL remains to be elucidated. Future longitudinal studies in large community-based cohorts combining repeated PET amyloid and tau imaging and ad hoc MRI segmentation of the MTL may provide new insights into the origin of volume loss in this area long before the clinical expression of cognitive decline in old age.

Disclosure statement The authors report no conflicts of interest.

Acknowledgements This project was funded in part by a grant of the Swiss National Science Foundation SNF 3200B0-1161193 and SPUM 33CM30-124111, and an unrestricted grant from the

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Association pour la Recherche sur l’Alzheimer, Geneva, Switzerland.

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Highlights

•

Amyloid load has a low magnitude deleterious effect on MTL volume loss in brain aging

•

Older age, male gender and APOE status are independent predictors of MTL volume loss

•

Slight but continuous decrement of cognition prior to MCI reflect worst MTL integrity

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Table 1. Clinical and demographic data, and Amyloid and APOE status.

Gender N Age at Amy PET Education (year) <9 9-12 >12 MMSE at baseline Fazekas at 1st MRI 0 1 2 3 Amyloid Negative Positive APOE4 Negative Positive Change in cognition Mean SUVR

Female 48 79.3 ± 4.0

Male 27 79.4 ± 4.0

Total 75 79.3 ± 4.0

p Value

11 (25%) 19 (43.2%) 14 (31.8%) 28.6 ± 1.2

0 (0%) 12 (52.2%) 11 (47.8%) 28.2 ± 2.2

11 (16.4%) 31 (46.3%) 25 (37.3%) 28.4 ± 1.6

21 (46.7%) 13 (28.9%) 9 (20.0%) 2 (4.4%)

10 (38.5%) 10 (38.5%) 5 (19.2%) 1 (3.8%)

31 (43.7%) 23 (32.4%) 14 (19.7%) 3 (4.2%)

35 (72.9%) 13 (27.1%)

14 (51.9%) 13 (48.1%)

49 (65.3%) 26 (34.7%)

0.067

40 (83.3%) 8 (16.7%) 0.1 ± 3.6 0.6 ± 0.1

23 (85.2%) 4 (14.8%) -2.0 ± 3.6 0.6 ± 0.1

63 (84%) 12 (16%) -0.6 ± 3.7 0.6 ± 0.1

0.821

0.892 0.003

0.198 0.727

0.001 0.070

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Table 2. Univariate and multiple linear regression models predicting the mesial temporal lobe volume loss (dependent variable) with the significant variables obtained by stepwise backward selection process and adjusted for the main confounders (mean cortical SUVr values, gender, age, APOE, change in continuous cognitive score/CCS). The coefficient unit is in cm3. Coeff: regression coefficient, CI: confidence interval; R2 : Coefficient of determination, F : F statistics Model 1: mean cortical SUVr; Model 2: Model 1 + Time + Gender + Age; Model 3: Model 2 + APOE4; Model 4: Model 3 + Change in continuous cognitive score

Region Left mesial temporal lobe Mean cortical SUVr Time Gender Age APOE4 Change in CCS 2 R F

Coeff.

Model 1 95% CI

p

Coeff.

Model 2 95% CI

p

Coeff.

Model 3 95% CI

p

Coeff.

-3.31

-5 - -1.61

<0.001

-2.54 -0.44 0.97 -0.06

-4.02 - -1.05 -0.63 - -0.25 0.59 – 1.34 -0.1 - -0.02

0.001 <0.001 <0.001 0.004

-2.88 -0.46 0.97 -0.05 0.69

-4.3 - -1.47 -0.65 - -0.27 0.61 - 1.32 -0.09 - -0.02 0.36 - 1.02

<0.001 <0.001 <0.001 0.007 <0.001

<0.001

0.43 116.77

<0.001

0.49 99.27

-2.60 -0.49 1.11 -0.05 0.85 0.06 0.53 86.42

Region Right mesial temporal lobe Mean cortical SUVr Time

Coeff.

95% CI

p

Coeff.

-3.08

-5.08 - 1.07

0.003

-2.46

0.11 15.07

-0.38

Gender

0.74

Age

-0.06

95% CI

-4.4 - 0.53 -0.57 - 0.19 0.35 1.12 -0.09 - 0.02

p

Coeff.

0.013

-2.80

<0.001

-0.40

<0.001

0.74

0.003

-0.05

APOE4

0.67

95% CI

-4.69 - 0.9 -0.59 - 0.21 0.37 1.10 -0.09 - 0.02 0.29 1.04

p

Coeff.

0.004

-2.52

<0.001

-0.43

<0.001

0.87

0.005

-0.05

0.001

0.82

Change in CCS R

2

<0.001

0.06 0.10

0.003

0.35

<0.001

0.41

<0.001

0.45

95% CI

-4.17 - 0.88 -0.63 - 0.23 0.53 1.21 -0.08 - 0.01 0.44 1.21 0.00 0.12

Model 4 95% CI -3.87 - -1.32 -0.67 - -0.31 0.73 – 1.49 -0.08 - -0.01 0.51 - 1.19 0.01 - 0.12

p <0.001 <0.001 <0.001 0.013 <0.001 0.031 <0.001

p

0.003 <0.001 <0.001 0.018 <0.001 0.045 <0.001

24

F

9.37

67.35

57.6

49.64

25

Supplementary Table 1. Clinical, demographic and MRI data at inclusion according to the type of PET scanner

tomo GE Healthcare N=9

Siemens N=66

Total N=75

7 (77.8%) 2 (22.2%) 78.7 ± 3.3

41 (62.1%) 25 (37.9%) 79.4 ± 4.1

48 (64.0%) 27 (36.0%) 79.3 ± 4.0

0.5667

1 (12.5%) 4 (50.0%) 3 (37.5%) 28.22 ± 3.23

10 (16.9%) 27 (45.8%) 22 (37.3%) 28.4 ± 1.6

11 (16.4%) 31 (46.3%) 25 (37.3%) 28.4 ± 1.9

0.6836

P

Gender 0= female 1= male Female Male Age at Amy PET NSC 1 2 3 MMSE score

0.4750

APOE 4 No Yes

0.6300

3

MTL volume left [mm ] 3 MTL volume left [mm ] Fazekas score 0 1 2 3

7 (77.8%) 2 (22.2%)

56 (84.8%) 10 (15.2%)

63 (84.0%) 12 (16.0%)

9.45 ± 1.08 9.49 ± 1.21

9.42 ± 0.99 9.42 ± 0.99 9.56 ± 0.92 9.55 ± 0.95

0.8591 0.4854 0.1129

6 (75.0%) 1 (12.5%) 1 (12.5%) 0 (0.0%)

25 (39.7%) 22 (34.9%) 13 (20.6%) 3 (4.8%)

31 (43.7%) 23 (32.4%) 14 (19.7%) 3 (4.2%)

26

FIGURES LEGEND Fig. 1. Illustration of the structural segmentation from 3DT1 images showing the medial temporal lobe defined as a combination of the amygdala, hippocampus, entorhinal cortex and parahippocampal gyrus (outlined in red). Fig. 2. Representative slices of 3DT1 MRI showing significant differences in medial temporal lobe atrophy (A versus B) as a function of the absence (C) or presence (D) of significant amyloid load.

27

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Author Contributions Section

Conceived the study: FRH, SH, PG; recruited: CR, MLM, SH; neuropsychology supervising: CR, MLM, PG; imaging: MLM, VG, SH; data preparation: CR, MLM, FRH; analyzed the data: FRH, CR, SH, VG, MLM, PG; manuscript writing: FRH, CR, SH, VG, MLM, PG.

Dear Madame, Please find here our manuscript entitled « Determinants of mesial temporal lobe volume loss in elderly individuals with preserved cognition: a longitudinal PET amyloid stud» by Marie-Louise Montandon, François R. Herrmann, Valentina Garibotto, Cristelle Rodriguez, Sven Haller, Panteleimon Giannakopoulo

Address of the corresponding author Prof. François Herrmann Division of Geriatrics, Department of internal medicine, rehabilitation and geriatrics Geneva University Hospitals Hôpital des Trois-Chêne 3, Chemin du Pont Bochet CH 1226 THONEX Switzerland Direct line

+41 22 305 6681

E-mail [email protected] All authors have contributed to the work, agree with the presented findings, and the work has not been published before nor is being considered for publication in another journal. No animal subjects were involved in this study. The work was approved by the Geneva’s state ethical committee This work was supported in part by Swiss National Foundation Grant SNF 3200B0-1161193 and SPUM 33CM30-124111 and by the Association pour la recherche sur Alzheimer (unrestricted grant). The authors have no conflict of interest to report. Sincerely yours.

François Herrmann