# Association between herpes simplex virus infection and Alzheimer's disease biomarkers: analysis within the MAPT trial.

Morgane Linard, Isabelle Garrigue, Bruno Vellas, Nicola Coley, Henrik Zetterberg, Kaj Blennow, Nicholas James Ashton, Pierre Payoux, Anne-Sophie Salabert, Jean-François Dartigues, et al.

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Morgane Linard, Isabelle Garrigue, Bruno Vellas, Nicola Coley, Henrik Zetterberg, et al. Association between herpes simplex virus infection and Alzheimer's disease biomarkers: analysis within the MAPT trial. Scientific Reports, 2025, 15 (1), pp.2362. 10.1038/s41598-024-84583-x. hal-04965047

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Association between herpes simplex virus infection and Alzheimer's disease biomarkers: analysis within the MAPT trial

Morgane Linard<sup>1,3</sup>, Isabelle Garrigue<sup>2,3</sup>, Bruno Vellas<sup>4,5</sup>, Nicola Coley<sup>5,6</sup>, Henrik Zetterberg<sup>7,8,9,10,11,12</sup>, Kaj Blennow<sup>7,8,13,14</sup>, Nicholas James Ashton<sup>7,15,16,17</sup>, Pierre Payoux<sup>18,19</sup>, Anne-Sophie Salabert<sup>19,20</sup>, Jean-François Dartigues<sup>1,21</sup>, Joachim Mazere<sup>22,23</sup>, Sandrine Andrieu<sup>5,6</sup> & Catherine Helmer<sup>24</sup>

In vitro and animal studies have suggested that inoculation with herpes simplex virus 1 (HSV-1) can lead to amyloid deposits, hyperphosphorylation of tau, and/or neuronal loss. Here, we studied the association between HSV-1 and Alzheimer's disease biomarkers in humans. Our sample included 182 participants at risk of cognitive decline from the Multidomain Alzheimer Preventive Trial who had HSV-1 plasma serology and an amyloid PET scan. Plasma Aβ42/40 ratio, neurofilament light chain and p-tau181 were also available for a sub-sample of participants. Multivariate linear regressions were performed and stratified by APOE4 genotype. The median age was 74.0 years, 85.2% were infected with HSV-1. Infected participants tended to have a lower cortical amyloid load than uninfected participants (β = -0.08, p = 0.06), especially those suspected of reactivating HSV-1 most frequently (i.e. with a high anti-HSV-1 IgG level; n = 58, β = -0.09 p = 0.04). After stratification, the association was only significant in APOE4 carriers (n = 43, β = -0.21 p = 0.01). No association was found with the plasma biomarkers. The trend toward lower cortical amyloid load in HSV-1-infected participants was unexpected given the pre-existing literature and may be explained either by a modified immune response in HSV-1 infected subjects which could favour the clearance of amyloid deposits or by a selection bias.

<footnote n="1"><sup>1</sup>INSERM U1219 Bordeaux Population Health Research Center, University of Bordeaux, 146, rue Léo Saignat, 33076 Bordeaux Cedex, France. <sup>2</sup>CNRS, MFP, UMR 5234, University of Bordeaux, Bordeaux, France. <sup>3</sup>Virology Department, University Hospital of Bordeaux, Bordeaux, France. <sup>4</sup>Gérontopôle de Toulouse, Institut du Vieillissement, University Hospital of Toulouse, Toulouse, France. <sup>5</sup>INSERM, CERPOP, U1295, University of Toulouse, Toulouse, France. <sup>6</sup>Department of Clinical Epidemiology and Public Health, University Hospital of Toulouse, Toulouse, France. <sup>7</sup>Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden. <sup>8</sup>Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden. <sup>9</sup>Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK. <sup>10</sup>UK Dementia Research Institute at UCL, London, UK. <sup>11</sup>Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China. <sup>12</sup>Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA. <sup>13</sup>Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France. <sup>14</sup>Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, Neurodegenerative Disorder Research Center, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, People's Republic of China. <sup>15</sup>Institute of Psychiatry, Psychology and Neuroscience, King's College London, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK. <sup>16</sup>NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK. <sup>17</sup>Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway. <sup>18</sup>Nuclear Medicine Department, University Hospital of Toulouse, Toulouse, France. <sup>19</sup>INSERM ToNIC, U1214, University of Toulouse, Toulouse, France. <sup>20</sup>Radiopharmacy Department, University Hospital of Toulouse, Toulouse, France. <sup>21</sup>Memory Consultation, CMRR, University Hospital of Bordeaux, Bordeaux, France. <sup>22</sup>Nuclear Medicine Department, University Hospital of Bordeaux, Bordeaux, France. <sup>23</sup>CNRS, INCIA, UMR 5287, University of Bordeaux, Bordeaux, France. <sup>24</sup>INSERM, Bergonié Institute, BPH, U1219, CIC-P 1401, University of Bordeaux, Bordeaux, France. <sup>✉</sup>email: morgane.linard@gmail.com</footnote>
Different processes underlie the development of Alzheimer's disease (AD), including intracerebral accumulation of both amyloid β (Aβ) deposits and neurofibrillary tangles (NFTs) (secondary to hyperphosphorylation of the tau protein) and subsequent neuronal loss. The extent of these lesions can be estimated in vivo using neuroimaging methods, including quantification of amyloid and tau lesions by positron emission tomography (PET) scans and measurement of cerebral atrophy by magnetic resonance imaging (MRI)¹. Well-established cerebrospinal fluid (CSF) biomarkers of these processes also exist. More recently, promising blood-based assays of these biomarkers have also been developed²⁻⁵, including sensitive and specific assays for the 42 and 40 amino acid-long amyloid β proteins (Aβ42/40 ratio, reduced levels of which reflect Aβ plaque pathology), phosphorylated tau (p-tau, reflecting AD-related tau phosphorylation) and neurofilament light chain (NfL, reflecting neuroaxonal injury irrespective of its cause).

Nevertheless, the triggers of these processes remain insufficiently understood. Among the existing hypotheses, a growing number of studies suggest that inadequate immune control of neurotropic herpes simplex virus 1 (HSV-1) could be involved in the onset of AD⁶,⁷. In particular, several studies highlighted a link between HSV-1 and AD hallmarks. In vitro, HSV-1 inoculation leads to Aβ accumulation⁸⁻¹⁷, increased concentrations of p-tau and a reduction in neuronal viability¹⁶⁻²¹. In rodents, HSV-1 inoculation leads to intracerebral accumulations of Aβ⁹,²² and p-tau²²,²³ proportional to the number of viral reactivations²². Notably, Aβ deposits were found to colocalize with HSV-1 in the brains of mice²⁴. Moreover, several studies highlighted that Aβ possesses antimicrobial activity against several viruses, bacteria and fungi²⁴⁻²⁶ and could also play a protective role against various neurotoxic solutes²⁷, suggesting that the accumulation of Aβ deposits in the central nervous system (CNS) may be part of the brain's response to aggression. In humans, only rare studies exist investigating links between HSV infection and plasma amyloid biomarkers²⁸⁻³⁰, plasma NfL³⁰, CSF biomarkers³¹, or postmortem intracerebral lesions³²,³³, leading to less convincing results regarding the potential involvement of HSV-1 in AD.

Our primary objective was thus to explore a potential association between HSV-1 and AD biomarkers. We primarily investigated the intracerebral amyloid load measured by PET, for which no study exists to date. We also investigated plasma biomarkers such as the Aβ42/40 ratio, NfL and p-tau181.

# Methods

## Design and participants

The Multidomain Alzheimer Preventive Trial (MAPT, NCT00672685) is a phase 3 multicenter randomized trial³⁴,³⁵ that aimed to assess the effect of long-term preventive interventions on cognitive decline in older adults. The 3-year interventions consisting of i) supplementation with omega-3 polyunsaturated fatty acids or ii) multidomain lifestyle interventions (nutritional advice, cognitive training, physical activity) plus placebo or iii) the combination of supplementation and lifestyle interventions. The interventions failed to demonstrate efficacy compared with the placebo group³⁵.

Between 2008 and 2011, 1 680 participants at risk of cognitive decline at 13 memory centers in France and Monaco were included in the study according to the following criteria: i) ≥70 years old, ii) living in the community and iii) meeting at least one of the following conditions: spontaneous memory complaint expressed to the general practitioner, limitation in one instrumental activity of daily living and walking speed <0.8 m/s. Participants with dementia, a Mini Mental State Examination (MMSE) <24, dependency for any basic activity of daily living or a disease compromising the subject's participation were not included. Each participant provided signed informed consent, and the study protocol was approved by the French Ethical Committee located in Toulouse (CPP SOOM II) and by the French Health Authority. All the methods were performed in accordance with the relevant guidelines and regulations.

Aiming to explore the associations between HSV-1 infection and biomarkers reflecting pathophysiological processes underlying AD, this secondary analysis included 182 participants with both an amyloid PET scan (performed once during the 3-year follow-up) and an anti-HSV-1 plasma serology (measured at baseline) (Fig. 1). Subsequently, assays of plasma biomarkers were performed in stored blood samples from some of these participants. A first subsample of 164 participants had available data for both the Aβ42/40 ratio and NfL (measured in samples collected at 12 months of follow-up). A second subsample of 138 participants had data for p-tau181 (measured twice, at baseline and 36 months of follow-up).

## Anti-HSV-1 serologies

The presence of anti-HSV-1 immunoglobulin G (IgG) in the blood was assessed using the LIAISON® HSV1 Type Specific IgG kit (details in Supplementary file 1). Of the 271 participants who underwent an amyloid PET scan in the MAPT trial, 183 had an available plasma sample at baseline for performing anti-HSV serologies. One subject was further excluded due to uninterpretable HSV data (Fig. 1).

## Biomarkers related to Alzheimer's disease

### Cortical amyloid load

In the MAPT trial, the cortical amyloid load was measured by [18F] florbetapir (AV45) PET³⁴,³⁶. Details regarding the inclusion criteria and the acquisition parameters are provided in Supplementary file 1. The timing of the PET was variable and could take place during the 3 years of follow-up of the trial.

A semiautomated quantitative analysis made it possible to estimate regional standard uptake value ratios (SUVR), corresponding to the ratio between the fixation of the tracer in the studied region and that in a reference region (the whole cerebellum in this study). Subsequently, a cortical-to-cerebellar SUVR was defined as the mean signal of six predefined AD-related cortical regions of interest (frontal, temporal, parietal, precuneus, anterior cingulate, and posterior cingulate). Cortical-to-cerebellar SUVR values were analyzed as both continuous and binary variables with an amyloid positivity threshold set at ≥1.17³⁷,³⁸. Additional analyses were also carried out on separate cortical areas (continuous variable).
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Study design and flow chart. The main sample of our study includes 182 subjects with both HSV-1 serology at baseline and amyloid PET scans that may have been performed throughout follow-up. Two subsamples were used to assess associations between HSV-1 infection and plasma biomarkers: i) a subsample of 164 subjects with dosages of Aβ42/40 ratio and NfL at 12 months and ii) a subsample of 138 subjects with two dosages of p-tau 181 at baseline and 36 months. HSV, herpes simplex virus; NfL, neurofilament light chain; PET, positron emission tomography; p-tau, phosphorylated-tau.</figcaption></figure>

### Plasma biomarkers

AD-related plasma biomarkers were measured using high-precision methods (details in Supplementary file 1)³⁹⁻⁴¹. In the first subset, 165 participants had both Aβ42/40 ratios (lower is worse) and NfL (pg/mL, higher is worse) measured at 12 months of follow-up. Among them, one subject with an NfL value four standard deviations above the sample mean was considered an outlier and further excluded. In a second subset, 142 participants had p-tau181 (pg/mL, higher is worse) obtained at both baseline and 36 months of follow-up. Among them, 2 participants were considered outliers, and 2 participants had p-tau181 values below the lower limit of detection (1.0 pg/mL) and were further excluded. In regression models, plasma biomarkers were used as continuous variables, and both NfL and p-tau181 were log-transformed to correct skewness.

### Statistical analyses

To examine associations between HSV-1 serostatus and AD biomarkers, univariate and multivariate linear regression models (or logistic regression models for the binary PET amyloid positivity variable) were performed on i) the presence of anti-HSV-1 IgG and ii) the level of anti-HSV-1 IgG (considered in terciles due to an upper limit of quantification). A higher level of IgG was interpreted as reflecting a higher frequency of HSV-1 reactivation over time. Analyses were adjusted for baseline age, sex, presence of at least one APOE4 allele and level of education. Sensitivity analyses were also performed adjusting for factors potentially associated with AD biomarkers but with a low probability of influencing HSV-1 serostatus: history of hypertension, diabetes or dyslipidemia at baseline, time from randomization to PET scan (only for cortical amyloid load), randomization arms (only for biomarkers measured postbaseline), and serum creatinine level at the time of biomarker measurement (for plasma biomarkers only)⁵,⁴²,⁴³. For linear models, normality of residuals and homoscedasticity were assessed using a histogram of residuals, a normal quantile-quantile plot of residuals and a plot of residuals versus predicted values.

Moreover, as suggested by previously published results from postmortem⁴⁴, epidemiological⁶,⁴⁵,⁴⁶ or animal studies⁴⁷,⁴⁸, we assumed that any association between HSV-1 and AD may be modulated by the APOE4 genotype.
Consequently, analyses were stratified by *APOE4* genotype regardless of the significance of the interactions between HSV-1 and APOE4 (see Supplemental Tables for p-values of HSV-1 × APOE4 interactions). In these models, due to the small sample sizes (particularly among *APOE4* carriers), we did not analyze the levels of anti-HSV-1 IgG in terciles.

Finally, given i) the time sequence of amyloid and tau lesions and ii) the suspected antimicrobial role of Aβ²⁵, we hypothesized that associations between HSV-1 and p-tau181 may depend on a preexisting amyloid pathology. Thus, analyses on p-tau181 measured at 36 months were also stratified on the cortical amyloid load (< or ≥ 1.17, measured during the follow-up).

All statistical tests were two-tailed, and the threshold for statistical significance was 5%. Analyses were performed with SAS software (version 9.4, SAS Institute).

## Results

In the main sample (Table 1), the median age was 74.0 years, 59.3% of participants were female, and 85.2% of the participants were infected by HSV-1. Participants with a cortical amyloid load above the positivity threshold of 1.17 represented 42.9% of the sample. The characteristics of the two subsamples with plasma biomarkers were broadly similar (Table 2). The median Aβ42/40 ratio was 0.113. As expected, the cortical-to-cerebellar SUVR and Aβ42/40 ratio were negatively correlated. The median NfL level was 76.8 pg/ml, and the median p-tau181 levels were 8.7 pg/ml and 9.1 pg/ml at baseline and 36 months, respectively. The p-tau181 levels were relatively stable between baseline and 36 months (median variation = 0.3 pg/ml). Amyloid-positive participants (according to PET) exhibited higher plasma levels of NfL (88.2 ± 37.3 versus 75.2 ± 26.7), p-tau181 at baseline (10.9 ± 3.8 versus 8.8 ± 4.2) and p-tau181 at 36 months (11.9 ± 5.1 versus 8.3 ± 3.9) than amyloid-negative participants.

Regarding the associations between anti-HSV1 serology and cortical amyloid load (univariate and multivariate analysis in Supplementary Table S1 and Fig. 2, respectively), participants infected by HSV-1 tended to have a lower cortical SUVR than uninfected participants (β = -0.08, p value = 0.06). Infected participants suspected to reactivate HSV-1 more frequently (those with an anti-HSV-1 IgG level in the 2 highest terciles) also had lower cortical SUVR (β = -0.10, p value = 0.03 for those in the 2nd tertile; β = -0.09, p value = 0.04 for those in the 3rd tertile) than uninfected participants. A similar trend (although not statistically significant) was

<table><caption>**Table 1.** Participant characteristics in the main sample (n = 182). MAPT trial. ¹Missing data for the level of education (n = 1) and APOE4 (n = 16). ²At the closest visit to PET scan. Abbreviations: CDR, Clinical dementia rating; IQR, interquartile range; MMSE, Mini Mental State Examination; PET, positron emission tomography; SUVR, standard uptake value ratio.</caption><thead><tr><th></th><th></th><th>Total<br>(N = 182)<br>N (%)</th><th>Cortical Aβ load &lt; 1.17<br>(N = 104)<br>N (%)</th><th>Cortical Aβ load ≥ 1.17<br>(N = 78)<br>N (%)</th></tr></thead><tbody><tr><td colspan="5"><strong>Characteristics at baseline</strong></td></tr><tr><td>Age (years)</td><td>Median [IQR]</td><td>74.0 [71.0-77.0]</td><td>74.0 [71.0-77.0]</td><td>72.5 [71.0-78.0]</td></tr><tr><td>Sex</td><td>Woman</td><td>108 (59.3)</td><td>62 (59.6)</td><td>46 (59.0)</td></tr><tr><td rowspan="3">Level of education<sup>1</sup></td><td>No diploma or primary school certificate</td><td>48 (26.5)</td><td>30 (28.8)</td><td>18 (23.4)</td></tr><tr><td>Secondary education</td><td>50 (27.6)</td><td>24 (23.1)</td><td>26 (33.8)</td></tr><tr><td>High school diploma or university level</td><td>83 (45.9)</td><td>50 (48.1)</td><td>33 (42.9)</td></tr><tr><td>APOE4<sup>1</sup></td><td>At least one allele</td><td>43 (25.9)</td><td>13 (14.1)</td><td>30 (40.5)</td></tr><tr><td rowspan="4">Randomization arm</td><td>Multidomain plus polyunsaturated fatty acids</td><td>49 (26.9)</td><td>36 (34.6)</td><td>13 (16.7)</td></tr><tr><td>Polyunsaturated fatty acids</td><td>43 (23.6)</td><td>23 (22.1)</td><td>20 (25.6)</td></tr><tr><td>Multidomain plus placebo</td><td>40 (22.0)</td><td>24 (23.1)</td><td>16 (20.5)</td></tr><tr><td>Placebo</td><td>50 (27.5)</td><td>21 (20.2)</td><td>29 (37.2)</td></tr><tr><td>MMSE</td><td>Median [IQR]</td><td>28 [27-29]</td><td>29 [28-29]</td><td>28 [27-29]</td></tr><tr><td rowspan="2">CDR</td><td>0</td><td>105 (57.7)</td><td>62 (59.6)</td><td>43 (55.1)</td></tr><tr><td>0.5</td><td>77 (42.3)</td><td>42 (40.4)</td><td>35 (44.9)</td></tr><tr><td>Anti-HSV-1 IgG</td><td>Positive</td><td>155 (85.2)</td><td>90 (86.5)</td><td>65 (83.3)</td></tr><tr><td colspan="5"><strong>Amyloid PET scan during the follow-up</strong></td></tr><tr><td rowspan="3">Age at PET scan (years)</td><td>Median [IQR]</td><td>75.0 [73.0-79.0]</td><td>76.0 [73.0-79.0]</td><td>74.0 [73.0-80.0]</td></tr><tr><td>&lt; 12 months</td><td>51 (28.0)</td><td>29 (27.9)</td><td>22 (28.2)</td></tr><tr><td>12-24 months</td><td>58 (31.9)</td><td>36 (34.6)</td><td>22 (28.2)</td></tr><tr><td rowspan="2">Time from randomisation to PET scan (months)</td><td>≥ 24 months</td><td>73 (40.1)</td><td>39 (37.5)</td><td>34 (43.6)</td></tr><tr><td>Median [IQR]</td><td>1.13 [1.05-1.29]</td><td>1.06 [1.02-1.10]</td><td>1.33 [1.25-1.43]</td></tr><tr><td>Cortical SUVR</td><td>Median [IQR]</td><td>78 (42.9)</td><td>-</td><td>-</td></tr><tr><td rowspan="2">MMSE at PET scan<sup>2</sup></td><td>Median [IQR]</td><td>29 [27-30]</td><td>29 [28-30]</td><td>28 [27-29]</td></tr><tr><td>0</td><td>101 (55.5)</td><td>57 (54.8)</td><td>44 (56.4)</td></tr><tr><td rowspan="2">CDR at PET scan<sup>2</sup></td><td>0.5</td><td>79 (43.4)</td><td>47 (45.2)</td><td>32 (41.0)</td></tr><tr><td>≥ 1</td><td>2 (1.1)</td><td>0 (0.0)</td><td>2 (2.6)</td></tr></tbody></table>
<table><caption>**Table 2.** Participant characteristics in subsamples 1 and 2 (n = 164 and 138). MAPT trial. ¹Missing data for the level of education (n = 1 for subsample 1 and 1 for subsample 2) and APOE4 (n = 13 for subsample 1 and 14 for subsample 2). ²12 months for subsample 1 and 36 months for subsample 2. Abbreviations: CDR, Clinical dementia rating; IQR, interquartile range; MMSE, Mini Mental State Examination; NfL, neurofilament light chain; p-tau181, phosphorylated tau 181.</caption><thead><tr><th></th><th></th><th>Subsample 1<br>Aβ42/40-NfL<br>(N=164)<br>N (%)</th><th>Subsample 2<br>p-tau181<br>(N=138)<br>N (%)</th></tr></thead><tbody><tr><td colspan="4"><strong>Characteristics at baseline</strong></td></tr><tr><td>Age (years)</td><td>Median [IQR]</td><td>73.0 [71.0-77.0]</td><td>73.0 [71.0-77.0]</td></tr><tr><td>Sex</td><td>Woman</td><td>97 (59.1)</td><td>84 (60.9)</td></tr><tr><td rowspan="3">Level of education<sup>1</sup></td><td>No diploma or primary school certificate</td><td>41 (25.2)</td><td>37 (27.0)</td></tr><tr><td>Secondary education</td><td>44 (27.0)</td><td>33 (24.1)</td></tr><tr><td>High school diploma or university level</td><td>78 (47.9)</td><td>67 (48.9)</td></tr><tr><td>APOE4<sup>1</sup></td><td>At least one allele</td><td>41 (27.2)</td><td>33 (26.6)</td></tr><tr><td rowspan="4">Randomization arm</td><td>Multidomain plus polyunsaturated fatty acids</td><td>46 (28.0)</td><td>39 (28.3)</td></tr><tr><td>Polyunsaturated fatty acids</td><td>38 (23.2)</td><td>31 (22.5)</td></tr><tr><td>Multidomain plus placebo</td><td>34 (20.7)</td><td>27 (19.6)</td></tr><tr><td>Placebo</td><td>46 (28.0)</td><td>41 (29.7)</td></tr><tr><td>MMSE</td><td>Median [IQR]</td><td>28 [28-29]</td><td>28 [28-29]</td></tr><tr><td rowspan="2">CDR</td><td>0</td><td>95 (57.9)</td><td>85 (61.6)</td></tr><tr><td>0.5</td><td>69 (42.1)</td><td>53 (38.4)</td></tr><tr><td>Anti-HSV-1 IgG</td><td>Positive</td><td>139 (84.8)</td><td>117 (84.8)</td></tr><tr><td colspan="4"><strong>Plasma biomarkers</strong></td></tr><tr><td>Aβ42/40 ratio at 12 months</td><td>Median [IQR]</td><td>0.113 [0.102-0.122]</td><td>-</td></tr><tr><td>NfL at 12 months (pg/ml)</td><td>Median [IQR]</td><td>76.8 [58.3-94.0]</td><td>-</td></tr><tr><td>p-tau181 at baseline (pg/ml)</td><td>Median [IQR]</td><td>-</td><td>8.7 [6.8-12.0]</td></tr><tr><td>p-tau181 at 36 months (pg/ml)</td><td>Median [IQR]</td><td>-</td><td>9.1 [6.6-11.9]</td></tr><tr><td>Variation of p-tau181 between 0 and 36 months (pg/ml)</td><td>Median [IQR]</td><td>-</td><td>0.3 [-1.4-2.2]</td></tr><tr><td>MMSE at 12 or 36 months<sup>2</sup></td><td>Median [IQR]</td><td>29 [27-30]</td><td>29 [28-29]</td></tr><tr><td rowspan="3">CDR at 12 or 36 months<sup>2</sup></td><td>0</td><td>87 (53.1)</td><td>76 (55.1)</td></tr><tr><td>0.5</td><td>75 (45.7)</td><td>60 (43.5)</td></tr><tr><td>≥1</td><td>2 (1.2)</td><td>2 (1.4)</td></tr></tbody></table>

observed when using the binary PET amyloid positivity variable. Sensitivity analyses (Supplementary Table S1) found similar results. Stratified analyses seem to support a modifying effect of APOE4 (Supplementary Table S1). Among APOE4 carriers, the association between being infected by HSV-1 and having a lower cortical amyloid load seemed stronger (n = 43, β = -0.21, p value = 0.01), whereas the association was not statistically significant among APOE4 noncarriers (n = 122, β = -0.03, p value = 0.45). Complementary analyses carried out on different cortical areas considered separately show similar results (Supplemental Table S2).

Regarding the associations between anti-HSV-1 serology and plasma biomarkers (univariate and multivariate analysis in Supplementary Tables S3-4 and Fig. 2, respectively), no statistically significant association was found between either i) being infected or ii) the level of anti-HSV-1 IgG and any of the plasma biomarkers studied (Aβ42/40 ratio, NfL or p-tau181). Of note, compared with uninfected participants, those with anti-HSV-1 IgG in the first tercile tended to have a higher Aβ42/40 ratio (β = 0.007, p value = 0.06), but there was no significant association for the other terciles of anti-HSV-1 IgG levels. Sensitivity analyses (Supplementary Tables S3-4) found similar results. Analyses stratified on APOE4 (Supplementary Tables S3-4) did not support the existence of an interaction between HSV-1 and APOE4 for these biomarkers.

Although far from statistically significant, some results suggest that the existence of an underlying amyloid pathology might modulate the impact of HSV-1 on tau lesions. Indeed, among participants with a cortical amyloid load ≥ 1.17, infected participants tended to have increased levels of p-tau181 at 36 months (β = 0.14, p value = 0.37), whereas among participants with a cortical amyloid load < 1.17, infected participants tended to have decreased levels of p-tau181 (β = -0.24, p value = 0.28).

## Discussion

### Main findings

Regarding the cortical amyloid load measured by PET, our analyses found intriguing results suggesting that participants infected by HSV-1 (and particularly those suspected to reactivate HSV-1 more frequently) tended to have a lower cortical amyloid load than uninfected participants. Moreover, after stratification on the APOE4 genotype, the association between being infected with HSV-1 and a lower intracerebral amyloid load was only
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Association between HSV-1 serostatus and Alzheimer's disease biomarkers: Multivariate regression models. MAPT trial. *To examine associations between HSV-1 serostatus and AD biomarkers, multivariate linear regression models (or logistic regression models for the binary PET amyloid positivity variable) were performed on either i) the presence of anti-HSV-1 IgG (IgG+) or ii) the level of anti-HSV-1 IgG considered in terciles (T1, T2 and T3 corresponding to 1st, 2nd and 3rd tertiles, respectively). In both cases, the reference category was the absence of anti-HSV-1 IgG (IgG-). Analyses were adjusted for baseline age, sex, presence of at least one APOE4 allele and level of education. The results are presented in the form of β (and their 95% confidence intervals in the figure), standard deviations and p values for the linear regressions or adjusted odds ratios and their 95% confidence intervals, as well as p values for logistic regressions. §in pg/ml, log transformed. Abbreviations: aOR, adjusted odds ratio; CI, confidence interval; HSV-1, herpes simplex virus 1; IgG, immunoglobulin G; NfL, neurofilament light chain; p-tau181, phosphorylated tau 181; std, standard deviation; SUVR, standard uptake value ratio; T1, T2 and T3, 1st, 2nd and 3rd tertiles, respectively.</figcaption></figure>

statistically significant in *APOE4* carriers. Conversely, no association was found between either i) being infected by HSV-1 or ii) the level of anti-HSV-1 IgG (suggested to reflect the frequency of viral reactivation) and any of the plasma biomarkers studied (Aβ42/40 ratio, NfL or p-tau181).

## Comparison to previous literature

Our study investigated the association between HSV-1 serostatus and intracerebral amyloid load measured by PET, but previous results exist on intracerebral amyloid load measured postmortem. Olsson et al.³³ highlighted that among HSV-1-infected participants, 32.4% had intracerebral amyloid deposits compared with 10.5% of uninfected participants, and 39.0% had NFTs compared with 25.0% of uninfected participants. Nevertheless, after adjusting for age, the associations were not statistically significant (p value = 0.2 and 0.8, respectively), and no significant association was found concerning the level of anti-HSV IgG.

Regarding plasma biomarkers, three studies reported results consistent with ours. Féart et al.²⁸ found no association between the levels of anti-HSV IgG and the levels of plasma Aβ40, Aβ42 or the Aβ42/40 ratio and no interaction between HSV serostatus and APOE4. Note that a significant association was nevertheless found between anti-HSV IgM (marker of recent viral reactivation) and lower levels of plasma Aβ40 or Aβ42 but not with the Aβ42/40 ratio. Lopatko et al.²⁹ found no significant association between the presence or levels of plasma anti-HSV-1 IgG and levels of plasma Aβ40 or Aβ42, whether in AD or in healthy participants. Duggan et al.³⁰ highlighted no significant association between a history of symptomatic infections with HSV-1, HSV-2 or varicella zoster virus (11.8% of their study sample) and Aβ42/40 ratio or NfL levels and no interaction with APOE4.

Recently, Goldhardt et al.³¹ published results on the presence of an intrathecal synthesis of anti-HSV IgG (reflecting viral reactivations within the CNS): the CSF-to-serum antibody index was positively correlated with
CSF p-tau and t-tau among AD patients, and this association was modulated by the CSF Aβ42/40 ratio (with stronger associations among participants with low ratios). Notably, in the same study, no association was found between plasma anti-HSV-1 serology and CSF biomarkers.

## Interpretation

Our results suggest that participants infected by HSV-1 (and particularly i) those suspected to reactivate HSV-1 more frequently and ii) APOE4 carriers) tend to have a lower cortical amyloid load than uninfected participants. This result is unexpected given the various studies showing that HSV-1 inoculation leads to Aβ accumulation in vitro and in animals.

Two possible explanations for these associations should be considered. Firstly, HSV-1 infection may lead to changes in the immune response within the CNS, promoting the clearance of amyloid deposits. Secondly, these results may reflect a selection bias related to the exclusion of subjects with dementia in the MAPT trial. Indeed, under the hypothesis of a role of Aβ in the brain's defense, diffuse amyloid deposits may accumulate secondary to various attacks of the CNS (including from HSV-1 but not restricted to it). Such a pro-inflammatory environment could in turn trigger HSV-1 reactivation within neurons and, as suggested in vitro and in animals, could lead to subsequent appearance of NFTs whose topographic sequence⁴⁹ seems consistent with HSV-1 tropism for the temporal cortex and its ability to spread to other brain regions following neural networks. (Notably, although far from statistically significant, the fact that among amyloid-positive participants, those infected by HSV-1 had increased levels of p-tau181 at 36 months compared with noninfected participants might argue in favor of this hypothesis.) Overall, if HSV-1 infection promotes progression to dementia only among those with a pre-existing amyloid pathology (while infected subjects with no amyloid pathology would remain asymptomatic), including only participants with no or few objectifiable cognitive symptoms could have led to the selection of infected subjects with fewer underlying amyloid pathology.

The absence of an association between HSV-1 serostatus and any of the plasma biomarkers studied may argue against an AD-promoting effect of HSV-1. Nevertheless, the absence could also be due to insufficient statistical power, the use of plasma biomarkers of AD suffering from large overlaps between groups, or the inclusion of participants at early stages of the disease. Moreover, conversely to the search for an intrathecal synthesis of anti-HSV1 antibodies, plasma serologies do not provide information on the reactivation of HSV-1 within the CNS.

## Limitations

We investigated the association between HSV-1 serostatus and several AD biomarkers, which has been relatively understudied in this context: i) intracerebral amyloid load measured by PET and ii) plasma p-tau181, Aβ42/40 ratio and NfL. However, this approach results in the main limitation of our study: anti-HSV-1 serologies were performed only for participants with an available amyloid PET, thus limiting the statistical power of the analyses.

This study benefited from serologies specific to HSV-1, leading to an estimated seroprevalence close to that usually found in the elderly population⁵⁰. However, plasma serologies are imperfect markers of the frequency of viral reactivations and do not provide information regarding the existence of reactivations within the CNS (unlike intrathecal assays). In addition, while serology was performed at inclusion, amyloid PET scans could have been performed throughout follow-up. If we anticipate a very minimal number of seroconversions between the two measurement points (given that primary HSV-1 infection occurs most of the time in childhood or adolescence), anti-HSV-1 antibody levels could have varied during this period and thus biased the analyses. Nevertheless, given the slow and progressive evolution of amyloid lesions over several years, we anticipate little impact from such variations occurring on the scale of a few months.

With respect to AD biomarkers, florbetapir PET scans provide an accurate estimate of the intracerebral amyloid load⁵¹. It should be noted that, although a key component of AD, it does not represent a biomarker with good specificity, given that a significant proportion of “amyloid-positive” individuals remain cognitively healthy¹,⁵². The plasma Aβ42/40 ratio, although estimated using a high-precision assay based on immunoprecipitation and mass spectrometry methods³⁹, suffers from large overlaps between amyloid PET + and PET- participants⁵³. Plasma NfL levels were measured using a third generation electrochemiluminescence-based assay. Although less efficient than fourth-generation single molecule array (Simoa) technology²,⁵⁴, this method allows sensitive detection of NfL in the blood², which is well correlated with CSF NfL levels⁵⁵. Nevertheless, increased levels of NfL are not AD-specific and rather reflect the presence of neuroaxonal injury irrespective of its cause². Conversely, plasma p-tau181 has been shown to differentiate AD from other neurodegenerative diseases with good accuracy⁵⁶⁻⁵⁸. Levels of plasma p-tau 181 are also increased along the AD continuum⁵³,⁵⁸ (this from the preclinical stage) and exhibit good correlation with CSF levels, tau PET and neuropathology⁵⁷,⁵⁸.

## Conclusion

Our results suggest that participants infected by HSV-1 (and particularly i) those suspected to reactivate HSV-1 more frequently and ii) APOE4 carriers) tended to have a lower cortical amyloid load (measured by PET) than uninfected participants. These results are unexpected given the pre-existing literature suggesting accumulation of amyloid deposits secondary to HSV-1 virus inoculation in vivo or in animals. Two possible explanations for these associations should be considered, either a modified immune response in HSV-1 infected subjects promoting the clearance of amyloid deposits or a selection bias related to the exclusion of participants with baseline dementia in the MAPT trial. Moreover, the absence of a statistically significant association between HSV-1 serostatus and any of the plasma biomarkers studied (Aβ42/40 ratio, NfL or p-tau181) may be partly explained by methodological limitations. Overall, discrepancies between these results and those obtained in vitro, in animals or in humans when analyzing intrathecal synthesis of anti-HSV IgG will require additional investigations, especially at different stages of the disease and in larger samples benefiting from CSF samples or PET imaging.
## Data availability

The datasets used and/or analysed during the current study are available from the MAPT data sharing committee on reasonable request (nicola.coley@inserm.fr).

Received: 19 April 2024; Accepted: 24 December 2024

Published online: 18 January 2025

## References

1. Chételat, G. et al. Amyloid imaging in cognitively normal individuals, at-risk populations and preclinical Alzheimer's disease. *NeuroImage Clin.* **2**, 356-365 (2013).

2. Khalil, M. et al. Neurofilaments as biomarkers in neurological disorders. *Nat. Rev. Neurol.* **14**, 577-589 (2018).

3. Mielke, M. M. et al. Plasma and CSF neurofilament light: Relation to longitudinal neuroimaging and cognitive measures. *Neurology* **93**, e252-e260 (2019).

4. Wang, X., Sun, Y., Li, T., Cai, Y. & Han, Y. Amyloid-β as a blood biomarker for Alzheimer's disease: A review of recent literature. *J. Alzheimers Dis.* **73**, 819-832 (2020).

5. Mielke, M. M. et al. Performance of plasma phosphorylated tau 181 and 217 in the community. *Nat. Med.* **28**, 1398-1405 (2022).

6. Linard, M. et al. Interaction between APOE4 and herpes simplex virus type 1 in Alzheimer's disease. *Alzheimers Dement.* **16**, 200-208 (2020).

7. Itzhaki, R. F. Corroboration of a major role for herpes simplex virus type 1 in Alzheimer's disease. *Front. Aging Neurosci.* https://doi.org/10.3389/fnagi.2018.00324 (2018).

8. Shipley, S. J., Parkin, E. T., Itzhaki, R. F. & Dobson, C. B. Herpes simplex virus interferes with amyloid precursor protein processing. *BMC Microbiol.* https://doi.org/10.1186/1471-2180-5-48 (2005).

9. Wozniak, M. A., Itzhaki, R. F., Shipley, S. J. & Dobson, C. B. Herpes simplex virus infection causes cellular β-amyloid accumulation and secretase upregulation. *Neurosci. Lett.* **429**, 95-100 (2007).

10. De Chiara, G. et al. APP processing induced by herpes simplex virus type 1 (HSV-1) yields several APP fragments in human and rat neuronal cells. *PLoS ONE* **5**, e13989 (2010).

11. Piacentini, R. et al. HSV-1 promotes Ca2+-mediated APP phosphorylation and Aβ accumulation in rat cortical neurons. *Neurobiol. Aging* **32**(2323), e13-2323.e26 (2011).

12. Santana, S., Recuero, M., Bullido, M. J., Valdivieso, F. & Aldudo, J. Herpes simplex virus type I induces the accumulation of intracellular β-amyloid in autophagic compartments and the inhibition of the non-amyloidogenic pathway in human neuroblastoma cells. *Neurobiol. Aging* **33**(430), e19-430.e33 (2012).

13. Civitelli, L. et al. Herpes simplex virus type 1 infection in neurons leads to production and nuclear localization of APP intracellular domain (AICD): implications for Alzheimer's disease pathogenesis. *J. Neurovirol.* **21**, 480-490 (2015).

14. Piacentini, R. et al. Herpes Simplex Virus type-1 infection induces synaptic dysfunction in cultured cortical neurons via GSK-3 activation and intraneuronal amyloid-β protein accumulation. *Sci. Rep.* **5**, 15444 (2015).

15. Bourgade, K. et al. Protective effect of amyloid-β peptides against herpes simplex virus-1 infection in a neuronal cell culture model. *J. Alzheimers Dis.* **50**, 1227-1241 (2016).

16. Powell-Doherty, R. D., Abbott, A. R. N., Nelson, L. A. & Bertke, A. S. Amyloid-β and p-tau anti-threat response to herpes simplex virus 1 infection in primary adult murine hippocampal neurons. *J. Virol.* **94**, e01874-19. https://doi.org/10.1128/JVI.01874-19 (2020).

17. Cairns, D. M. et al. A 3D human brain-like tissue model of herpes-induced Alzheimer's disease. *Sci. Adv.* **6**, eaay8828 (2020).

18. Zambrano, Á. et al. Neuronal cytoskeletal dynamic modification and neurodegeneration induced by infection with herpes simplex virus type 1. *J. Alzheimers Dis.* **14**, 259-269 (2008).

19. Wozniak, M. A., Frost, A. L. & Itzhaki, R. F. Alzheimer's disease-specific tau phosphorylation is induced by herpes simplex virus type 1. *J. Alzheimers Dis.* **16**, 341-350 (2009).

20. Lerchundi, R. Tau cleavage at D421 by caspase-3 is induced in neurons and astrocytes infected with herpes simplex virus type 1. *J. Alzheimeraposs Dis.* https://doi.org/10.3233/JAD-2010-101386 (2011).

21. Álvarez, G., Aldudo, J., Alonso, M., Santana, S. & Valdivieso, F. Herpes simplex virus type 1 induces nuclear accumulation of hyperphosphorylated tau in neuronal cells. *J. Neurosci.* *Res.* **90**, 1020-1029 (2012).

22. De Chiara, G. et al. Recurrent herpes simplex virus-1 infection induces hallmarks of neurodegeneration and cognitive deficits in mice. *PLOS Pathog.* **15**, e1007617 (2019).

23. Martin, C. Inflammatory and neurodegeneration markers during asymptomatic HSV-1 reactivation. *J. Alzheimers Dis.* https://doi.org/10.3233/JAD-171106 (2014).

24. Eimer, W. A. et al. Alzheimer's disease-associated β-amyloid is rapidly seeded by herpesviridae to protect against brain infection. *Neuron* **99**, 56-63.e3 (2018).

25. Gosztyla, M. L., Brothers, H. M. & Robinson, S. R. Alzheimer's amyloid-b is an antimicrobial peptide: A review of the evidence. *J. Alzheimer's Dis.* https://doi.org/10.3233/JAD-171133 (2018).

26. Moir, R. D., Lathe, R. & Tanzi, R. E. The antimicrobial protection hypothesis of Alzheimer's disease. *Alzheimers Dement.* **14**, 1602-1614 (2018).

27. Robinson, S. R. & Bishop, G. M. Ab as a bioflocculant: implications for the amyloid hypothesis of Alzheimer's disease. *Neurobiol. Aging* https://doi.org/10.1016/S0197-4580(01)00342-6 (2002).

28. Féart, C. et al. Association between IgM anti-herpes simplex virus and plasma amyloid-beta levels. *PLoS ONE* **6**, e29480 (2011).

29. Lopatko Lindman, K. et al. Plasma amyloid-β in relation to antibodies against herpes simplex virus, cytomegalovirus, and chlamydophila pneumoniae. *J. Alzheimers Dis. Rep.* **5**, 229-235 (2021).

30. Duggan, M. R. et al. Herpes viruses in the baltimore longitudinal study of aging: associations with brain volumes, cognitive performance, and plasma biomarkers. *Neurology* https://doi.org/10.1212/WNL.0000000000201036 (2022).

31. Goldhardt, O. et al. Herpes simplex virus alters Alzheimer's disease biomarkers - A hypothesis paper. *Alzheimers Dement. J. Alzheimers Assoc.* https://doi.org/10.1002/alz.12834 (2022).

32. Wozniak, M., Mee, A. & Itzhaki, R. Herpes simplex virus type 1 DNA is located within Alzheimer's disease amyloid plaques. *J. Pathol.* **217**, 131-138 (2009).

33. Olsson, J. et al. HSV presence in brains of individuals without dementia: the TASTY brain series. *Dis. Model. Mech.* **9**, 1349-1355 (2016).

34. Vellas, B. et al. MAPT study: a multidomain approach for preventing Alzheimer's disease: design and baseline data. *J. Prev. Alzheimers Dis.* **1**, 13-22 (2014).

35. Andrieu, S. et al. Effect of long-term omega 3 polyunsaturated fatty acid supplementation with or without multidomain intervention on cognitive function in elderly adults with memory complaints (MAPT): a randomised, placebo-controlled trial. *Lancet Neurol.* **16**, 377-389 (2017).

36. Payoux, P. et al. Cognitive and functional patterns of nondemented subjects with equivocal visual amyloid PET findings. *Eur. J. Nucl. Med. Mol. Imaging* **42**, 1459-1468 (2015).
37. Fleisher, A. S. Using positron emission tomography and florbetapir F 18 to image cortical amyloid in patients with mild cognitive impairment or dementia due to Alzheimer disease. *Arch. Neurol.* **68**, 1404 (2011).

38. Lilamand, M. et al. Brain amyloid deposition is associated with lower instrumental activities of daily living abilities in older adults. Results from the MAPT study. *J. Gerontol. A. Biol. Sci. Med. Sci.* **71**, 391–397 (2016).

39. Schindler, S. E. et al. High-precision plasma β-amyloid 42/40 predicts current and future brain amyloidosis. *Neurology* **93**, e1647–e1659 (2019).

40. Karikari, T. K. et al. Blood phosphorylated tau 181 as a biomarker for Alzheimer's disease: a diagnostic performance and prediction modelling study using data from four prospective cohorts. *Lancet Neurol.* **19**, 422–433 (2020).

41. Raffin, J. et al. Associations between physical activity, blood-based biomarkers of neurodegeneration, and cognition in healthy older adults: The MAPT study. *J. Gerontol. A. Biol. Sci. Med. Sci.* **76**, 1382–1390 (2021).

42. Syrjanen, J. A. et al. Associations of amyloid and neurodegeneration plasma biomarkers with comorbidities. *Alzheimers Dement.* **18**, 1128–1140 (2022).

43. Lau, W. L. et al. Kidney function is not related to brain amyloid burden on PET imaging in the 90+ study cohort. *Front. Med.* **8**, 671945 (2021).

44. Itzhaki, R. F. et al. Herpes simplex virus type 1 in brain and risk of Alzheimer's disease. *Lancet* **349**, 241–244 (1997).

45. Lövheim, H. et al. Herpes simplex virus, APOE ε4, and cognitive decline in old age: Results from the betula cohort study. *J. Alzheimers Dis.* **67**, 211–220 (2019).

46. Linard, M. et al. Herpes simplex virus, early neuroimaging markers and incidence of Alzheimer's disease. *Transl. Psychiatry* **11**, 414 (2021).

47. Burgos, J. S., Ramirez, C., Sastre, I., Bullido, M. J. & Valdivieso, F. ApoE4 is more efficient than E3 in brain access by herpes simplex virus type. *Genet. Nerv. Syst. Dis.* **14**, 3 (2003).

48. Burgos, J. S., Ramirez, C., Sastre, I. & Valdivieso, F. Effect of apolipoprotein E on the cerebral load of latent herpes simplex virus type 1 DNA. *J. Virol.* **80**, 5383–5387 (2006).

49. Braak, H. & Del Tredici, K. Alzheimer's pathogenesis: is there neuron-to-neuron propagation?. *Acta Neuropathol.* (Berl.) **121**, 589–595 (2011).

50. Looker, K. J. et al. Global and regional estimates of prevalent and incident herpes simplex virus type 1 infections in 2012. *PLOS ONE* **10**, e0140765 (2015).

51. Choi, S. R. et al. Correlation of amyloid PET ligand florbetapir F 18 binding with Aβ aggregation and neuritic plaque deposition in postmortem brain tissue. *Alzheimer Dis. Assoc. Disord.* **26**, 8–16 (2012).

52. Jansen, W. J. et al. Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis. *JAMA* **313**, 1924–1938 (2015).

53. Karikari, T. K. et al. Blood phospho-tau in Alzheimer disease: analysis, interpretation, and clinical utility. *Nat. Rev. Neurol.* **18**, 400–418 (2022).

54. Kuhle, J. et al. Comparison of three analytical platforms for quantification of the neurofilament light chain in blood samples: ELISA, electrochemiluminescence immunoassay and Simoa. *Clin. Chem. Lab. Med.* **54**, 1655–1661 (2016).

55. Mattsson, N., Andreasson, U., Zetterberg, H. & Blennow, K. Alzheimer's disease neuroimaging initiative. Association of plasma neurofilament light with neurodegeneration in patients with Alzheimer disease. *JAMA Neurol.* **74**, 557–566 (2017).

56. Ding, X. et al. Ultrasensitive assays for detection of plasma tau and phosphorylated tau 181 in Alzheimer's disease: a systematic review and meta-analysis. *Transl. Neurodegener.* **10**, 10 (2021).

57. Morrison, M. S. et al. Ante-mortem plasma phosphorylated tau (181) predicts Alzheimer's disease neuropathology and regional tau at autopsy. *Brain J. Neurol.* **145**, 3546–3557 (2022).

58. Janelidze, S. et al. Plasma P-tau181 in Alzheimer's disease: relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer's dementia. *Nat. Med.* **26**, 379–386 (2020).

## Acknowledgements

The present study was supported by the Fondation Plan Alzheimer (AAP 2016). The MAPT trial was supported by grants from the Gérontopôle of Toulouse, the French Ministry of Health (PHRC 2008, 2009), Pierre Fabre Research Institute (manufacturer of the omega-3 supplement), ExonHit Therapeutics SA, and Avid Radiopharmaceuticals Inc. The promotion of this study was supported by the University Hospital Center of Toulouse. The data sharing activity was supported by the Association Monegasque pour la Recherche sur la maladie d'Alzheimer (AMPA) and the INSERM-University of Toulouse III UMR 1295 (CERPOP) Research Unit. The measurement of plasma amyloid-β was supported by institutional gift funds (R.J. Bateman, PI) and National Institute on Aging grants NIH R56AG061900 and RF1AG061900 (R.J. Bateman, PI). The measurement of plasma NfL were supported by institutional funds from Saint Louis University. The measurement of p-tau were supported by the Swedish Alzheimer Foundation (#AF-968270), Hjärnfonden, Sweden (#ALZ2022-0006), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-965240), and the Alzheimer's Association 2021 Zenith Award (ZEN-21-848495). The funders had no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript. The authors wish to thank Randall Bateman and Yan Li (Department of Neurology, Washington University School of Medicine, Saint Louis, USA) for the αβ42/40 assays, and John Morley, Andrew D. Nguyen and Geetika Aggarwal (Division of Geriatric Medicine, School of Medicine, Saint Louis University, Saint Louis, USA) for the NfL assays. In addition, the authors would like to thank all the members of the MAPT/DSA Study Group: MAPT Study Group: Principal investigator: Bruno Vellas (Toulouse); Coordination: Sophie Guyonnet; Project leader: Isabelle Carrié; CRA: Lauréane Brigitte; Investigators: Catherine Faisant, Françoise Lala, Julien Delrieu, Hélène Villars; Psychologists: Emeline Combrouze, Carole Badufle, Audrey Zueras; Methodology, statistical analysis and data management: Sandrine Andrieu, Christelle Cantet, Christophe Morin; Multidomain group: Gabor Abellan Van Kan, Charlotte Dupuy, Yves Rolland (physical and nutritional components), Céline Caillaud, Pierre-Jean Ousset (cognitive component), Françoise Lala (preventive consultation). The cognitive component was designed in collaboration with Sherry Willis from the University of Seattle, and Sylvie Belleville, Brigitte Gilbert and Francine Fontaine from the University of Montreal. Co-Investigators in associated centres: Jean-François Dartigues, Isabelle Marcet, Fleur Delva, Alexandra Foubert, Sandrine Cerda (Bordeaux); Marie-Noëlle-Cuffi, Corinne Costes (Castres); Olivier Rouaud, Patrick Manckoundia, Valérie Quipourt, Sophie Marilier, Evelyne Franon (Dijon); Lawrence Bories, Marie-Laure Pader, Marie-France Basset, Bruno Lapoujade, Valérie Faure, Michael Li Yung Tong, Christine Malick-Loiseau, Evelyne Cazaban-Campistron (Foix); Françoise Desclaux, Colette Blatge (Lavaur); Thierry Dantoine, Cécile Laubarie-Mouret, Isabelle Saulnier, Jean-Pierre Clé-
ment, Marie-Agnès Picat, Laurence Bernard-Bourzeix, Stéphanie Willebois, Iléana Désormais, Noëlle Cardin-
aud (Limoges); Marc Bonnefoy, Pierre Livet, Pascale Rebaudet, Claire Gédéon, Catherine Burdet, Flavien Terra-
col (Lyon), Alain Pesce, Stéphanie Roth, Sylvie Chaillou, Sandrine Louchart (Monaco); Kristel Sudres, Nicolas
Lebrun, Nadège Barro-Belaygues (Montauban); Jacques Touchon, Karim Bennys, Audrey Gabelle, Aurélia Ro-
mano, Lynda Touati, Cécilia Marelli, Cécile Pays (Montpellier); Philippe Robert, Franck Le Duff, Claire Ger-
vais, Sébastien Gonfrier (Nice); Yannick Gasnier and Serge Bordes, Danièle Begorre, Christian Carpuat, Khaled
Khales, Jean-François Lefebvre, Samira Misbah El Idrissi, Pierre Skolil, Jean-Pierre Salles (Tarbes). MRI group: Carole Dufouil (Bordeaux), Stéphane Lehéricy, Marie Chupin, Jean-François Mangin, Ali Bouhayia (Paris); Michèle Allard (Bordeaux); Frédéric Ricolfi (Dijon); Dominique Dubois (Foix); Marie Paule Bonceour Martel (Limoges); François Cotton (Lyon); Alain Bonafé (Montpellier); Stéphane Chanalet (Nice); Françoise Hugon (Tarbes); Fabrice Bonneville, Christophe Cognard, François Chollet (Toulouse). PET scans group: Pierre Pay-
oux, Thierry Voisin, Julien Delrieu, Sophie Peiffer, Anne Hitzel, (Toulouse); Michèle Allard (Bordeaux); Michel
Zanca (Montpellier); Jacques Monteil (Limoges); Jacques Darcourt (Nice). Medico-economics group: Laurent
Molinier, Hélène Derumeaux, Nadège Costa (Toulouse). Biological sample collection: Bertrand Perret, Claire
Vinel, Sylvie Caspar-Bauguil (Toulouse). Safety management : Pascale Olivier-Abbal. DSA Group: Sandrine An-
drieu, Christelle Cantet, Nicola Coley.

Author contributions

BV and SA contributed to the conception of the MAPT trial. ML and CH contributed to the design of the study. IG, KB, HZ, NJA, PP and ASS contributed to the acquisition of the data. ML performed statistical analysis and wrote the first draft of the manuscript. ML, IG, BV, NC, HZ, KB, NJA, PP, ASS, JFD, JM, SA and CH participated in the interpretation of the data, commented on previous versions of the manuscript, and approved the final manuscript.

Funding

Fondation Plan Alzheimer (AAP 2016).

Declarations

Competing interests

The authors declare no competing interests.

Additional information

**Supplementary Information** The online version contains supplementary material available at https://doi.org/10.1038/s41598-024-84583-x.

Correspondence and requests for materials should be addressed to M.L.

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