Age and the association between apolipoprotein E genotype and Alzheimer disease: A cerebrospinal fluid biomarker–based case–control study

Hana Saddiki; Aurore Fayosse; Emmanuel Cognat; Séverine Sabia; Sebastiaan Engelborghs; David Wallon; Panagiotis Alexopoulos; Kaj Blennow; Henrik Zetterberg; Lucilla Parnetti; Inga Zerr; Peter Hermann; Audrey Gabelle; Mercè Boada; Adelina Orellana; Itziar de Rojas; Matthieu Lilamand; Maria Bjerke; Christine Van Broeckhoven; Lucia Farotti; Nicola Salvadori; Janine Diehl-Schmid; Timo Grimmer; Claire Hourregue; Aline Dugravot; Gaël Nicolas; Jean-Louis Laplanche; Sylvain Lehmann; Elodie Bouaziz-Amar; the Alzheimer’s Disease Neuroimaging Initiative; Jacques Hugon; Christophe Tzourio; Archana Singh-Manoux; Claire Paquet; Julien Dumurgier

doi:10.1371/journal.pmed.1003289

. 2020 Aug 20;17(8):e1003289. doi: 10.1371/journal.pmed.1003289

Age and the association between apolipoprotein E genotype and Alzheimer disease: A cerebrospinal fluid biomarker–based case–control study

Hana Saddiki ¹, Aurore Fayosse ¹, Emmanuel Cognat ², Séverine Sabia ¹, Sebastiaan Engelborghs ^3,⁴, David Wallon ⁵, Panagiotis Alexopoulos ⁶, Kaj Blennow ^7,⁸, Henrik Zetterberg ^7,^8,⁹, Lucilla Parnetti ¹⁰, Inga Zerr ¹¹, Peter Hermann ¹¹, Audrey Gabelle ¹², Mercè Boada ¹³, Adelina Orellana ¹³, Itziar de Rojas ¹³, Matthieu Lilamand ², Maria Bjerke ¹⁴, Christine Van Broeckhoven ¹⁴, Lucia Farotti ¹⁰, Nicola Salvadori ¹⁰, Janine Diehl-Schmid ⁶, Timo Grimmer ⁶, Claire Hourregue ², Aline Dugravot ¹, Gaël Nicolas ⁵, Jean-Louis Laplanche ¹⁵, Sylvain Lehmann ¹⁶, Elodie Bouaziz-Amar ¹⁵; the Alzheimer’s Disease Neuroimaging Initiative¹, Jacques Hugon ², Christophe Tzourio ¹⁷, Archana Singh-Manoux ^1,¹⁸, Claire Paquet ², Julien Dumurgier ^1,^2,^*

Editor: Raquel C Gardner¹⁹

¹Université de Paris, Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Paris, France

²Cognitive Neurology Center, Lariboisiere—Fernand Widal Hospital, AP-HP, Université de Paris, Paris, France

³Department of Neurology, Universitair Ziekenhuis Brussel, Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium

⁴Department of Biomedical Sciences, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium

⁵Inserm U1245, Rouen University Hospital, Department of Neurology and CNR-MAJ, Normandy Center for Genomic and Personalized Medicine, Rouen, France

⁶Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Faculty of Medicine, Technical University of Munich, Munich, Germany

⁷Department of Psychiatry and Neurochemistry, University of Gothenburg, Mölndal, Sweden

⁸Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden

⁹Department of Neurodegenerative Disease, Institute of Neurology, University College London, UK Dementia Research Institute, London, United Kingdom

¹⁰Center for Memory Disturbances-Lab of Clinical Neurochemistry, Section of Neurology, University of Perugia, Italy

¹¹Department of Neurology, Clinical Dementia Center, University Medical Center Göttingen and German Center for Neurodegenerative Diseases, Göttingen, Germany

¹²Department of Neurology, Memory Research and Resources Centre, University of Montpellier, Montpellier, France

¹³Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurciències Aplicades, Universitat International de Catalunya, Barcelona, Spain

¹⁴VIB Center for Molecular Neurology, Institute Born-Bunge and Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium

¹⁵Department of Biochemistry and Molecular Biology, Lariboisière Hospital, APHP, Paris, France

¹⁶Department of Biochemistry, University of Montpellier, Montpellier, France

¹⁷Bordeaux Population Health Research Center, Team HEALTHY, UMR1219, University of Bordeaux, Inserm, Bordeaux, France

¹⁸Department of Epidemiology and Public Health, University College London, London, United Kingdom

¹⁹University of California San Francisco, UNITED STATES

No conflicts of interest with regards to this paper. Outside the submitted work, TG reported having received consulting fees from Actelion, Biogen, Eli Lilly, Iqvia/ Quintiles; MSD; Novartis, Quintiles, Roche Pharma, lecture fees from Biogen, Lilly, Parexel, Roche Pharma, and grants to his institution from Actelion and PreDemTech.

^✉

* E-mail: julien.dumurgier@inserm.fr

Roles

Hana Saddiki: Conceptualization, Supervision, Writing – original draft, Writing – review & editing

Aurore Fayosse: Conceptualization, Funding acquisition, Methodology, Writing – original draft, Writing – review & editing

Emmanuel Cognat: Conceptualization, Investigation, Validation, Writing – original draft, Writing – review & editing

Séverine Sabia: Methodology, Resources, Writing – original draft, Writing – review & editing

Sebastiaan Engelborghs: Methodology, Resources, Validation, Writing – review & editing

David Wallon: Resources, Validation, Writing – review & editing

Panagiotis Alexopoulos: Investigation, Resources, Validation, Writing – review & editing

Kaj Blennow: Investigation, Resources, Validation, Writing – original draft, Writing – review & editing

Henrik Zetterberg: Investigation, Resources, Writing – original draft, Writing – review & editing

Lucilla Parnetti: Investigation, Resources, Validation, Writing – review & editing

Inga Zerr: Investigation, Resources, Writing – review & editing

Peter Hermann: Investigation, Resources, Writing – review & editing

Audrey Gabelle: Investigation, Resources, Writing – review & editing

Mercè Boada: Investigation, Resources, Writing – review & editing

Adelina Orellana: Investigation, Resources, Writing – review & editing

Itziar de Rojas: Investigation, Resources, Writing – review & editing

Matthieu Lilamand: Investigation, Resources, Writing – review & editing

Maria Bjerke: Investigation, Resources, Writing – review & editing

Christine Van Broeckhoven: Investigation, Resources, Writing – review & editing

Lucia Farotti: Investigation, Resources, Writing – review & editing

Nicola Salvadori: Investigation, Resources, Writing – review & editing

Janine Diehl-Schmid: Investigation, Resources, Writing – review & editing

Timo Grimmer: Investigation, Resources, Writing – review & editing

Claire Hourregue: Investigation, Resources, Writing – review & editing

Aline Dugravot: Formal analysis, Investigation, Resources, Writing – review & editing

Gaël Nicolas: Investigation, Resources, Writing – review & editing

Jean-Louis Laplanche: Investigation, Resources, Writing – review & editing

Sylvain Lehmann: Investigation, Resources, Writing – review & editing

Elodie Bouaziz-Amar: Investigation, Resources, Writing – review & editing

Jacques Hugon: Investigation, Resources, Writing – original draft, Writing – review & editing

Christophe Tzourio: Investigation, Resources, Writing – original draft, Writing – review & editing

Archana Singh-Manoux: Investigation, Methodology, Resources, Supervision, Writing – original draft, Writing – review & editing

Claire Paquet: Investigation, Resources, Writing – original draft, Writing – review & editing

Julien Dumurgier: Conceptualization, Formal analysis, Investigation, Methodology, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

Raquel C Gardner: Academic Editor

PMCID: PMC7446786 PMID: 32817639

Abstract

Background

The ε4 allele of apolipoprotein E (APOE) gene and increasing age are two of the most important known risk factors for developing Alzheimer disease (AD). The diagnosis of AD based on clinical symptoms alone is known to have poor specificity; recently developed diagnostic criteria based on biomarkers that reflect underlying AD neuropathology allow better assessment of the strength of the associations of risk factors with AD. Accordingly, we examined the global and age-specific association between APOE genotype and AD by using the A/T/N classification, relying on the cerebrospinal fluid (CSF) levels of β-amyloid peptide (A, β-amyloid deposition), phosphorylated tau (T, pathologic tau), and total tau (N, neurodegeneration) to identify patients with AD.

Methods and findings

This case–control study included 1,593 white AD cases (55.4% women; mean age 72.8 [range = 44–96] years) with abnormal values of CSF biomarkers from nine European memory clinics and the American Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. A total of 11,723 dementia-free controls (47.1% women; mean age 65.6 [range = 44–94] years) were drawn from two longitudinal cohort studies (Whitehall II and Three-City), in which incident cases of dementia over the follow-up were excluded from the control population. Odds ratio (OR) and population attributable fraction (PAF) for AD associated with APOE genotypes were determined, overall and by 5-year age categories. In total, 63.4% of patients with AD and 22.6% of population controls carried at least one APOE ε4 allele. Compared with non-ε4 carriers, heterozygous ε4 carriers had a 4.6 (95% confidence interval 4.1–5.2; p < 0.001) and ε4/ε4 homozygotes a 25.4 (20.4–31.2; p < 0.001) higher OR of AD in unadjusted analysis. This association was modified by age (p for interaction < 0.001). The PAF associated with carrying at least one ε4 allele was greatest in the 65–70 age group (69.7%) and weaker before 55 years (14.2%) and after 85 years (22.6%). The protective effect of APOE ε2 allele for AD was unaffected by age. Main study limitations are that analyses were based on white individuals and AD cases were drawn from memory centers, which may not be representative of the general population of patients with AD.

Conclusions

In this study, we found that AD diagnosis based on biomarkers was associated with APOE ε4 carrier status, with a higher OR than previously reported from studies based on only clinical AD criteria. This association differs according to age, with the strongest effect at 65–70 years. These findings highlight the need for early interventions for dementia prevention to mitigate the effect of APOE ε4 at the population level.

In a case-control study using cerebrospinal fluid biomarkers, Hana Saddiki and colleagues investigate how age is related to the association between Apolipoprotein E genotype and Alzheimer's disease, among individuals with and without Alzheimer's disease in Europe and the US.

Author summary

Why was this study done?

The ε4 allele of apolipoprotein E (APOE) gene (APOE4) and increasing age are two of the most important known risk factors for developing Alzheimer disease (AD).
The recent development of diagnostic criteria based on biomarkers that reflect brain β-amyloid and tau lesions (β-amyloid deposition, pathologic tau, neurodegeneration [A/T/N] classification]) increases homogeneity in diagnosed cases.
The strength of association of AD with risk factors can be better determined using biomarker-based AD compared with AD diagnosis based only on clinical criteria because the latter are known to lack specificity as a result of difficulties in ruling out other causes of dementia.

What did the researchers do and find?

We compared the overall and age-specific association between APOE4 and AD using a case–control study that included 1,593 AD cases from memory clinics with positive cerebrospinal fluid biomarkers and 11,723 dementia-free controls drawn from two longitudinal cohort studies.
The use of a large number of cases and controls allows assessment of whether the association between APOE4 and AD is dependent on age.
Compared with controls, patients with AD were more likely to carry one APOE4 (odds ratio [OR] = 4.6) or two APOE4 (OR = 25.3). This association was significantly modified by age, with the strongest association seen between 65 and 70 years of age and weaker associations at the two tails of the age distribution.

What do these findings mean?

Incorporating biomarkers for diagnosis of AD identified an association with APOE4 that is apparently greater than has been previously reported using clinical diagnosis of the disease.
The impact of APOE4 on the risk of AD was strongest between the 65 and 70 years of age, earlier than the mean age at diagnosis in this study, which was 72.8 years.

Introduction

Apolipoprotein E (APOE) ε4 allele is the strongest known genetic risk factor for Alzheimer disease (AD) in the general population [1]. The three most common alleles of the APOE gene are ε2, ε3, and ε4; they encode for three isoform proteins differing in two single cysteine-to-arginine amino acid substitution at positions 112 and 158 [2]. The ε3 allele is the most common allele in the population and is used as the reference to estimate risk of AD. Current evidence suggests that ε4 heterozygote carriers have an overall 3-fold increased risk of AD, whereas ε4 homozygote carriers have up to a 15-fold increased risk [3]. Conversely, the ε2 allele is associated with nearly 50% lower risk of AD [4]. The mechanisms underlying the relationship between APOE ε4 and AD are thought to be complex [5], involving β-amyloid (Aβ) peptide clearance [6] as well as a direct role on neuronal death [7,8] and on phosphorylation of tau [9].

Beyond individual genetic susceptibilities, increasing age is the main risk factor of AD [10]. Rare before the age of 60, AD affects up to 20% of the population after 80 years [11]. Accordingly, the objective of the present study was to examine whether age modifies the association between APOE genotype and risk of AD. Indeed, much of the evidence in this domain is from studies undertaken before the 2000s, when the diagnosis of AD was based solely on clinical criteria. Diagnosis of AD based on clinical criteria is marked by poor overall specificity, ranging from 40% to 70% compared with neuropathologic examination [12], which can lead to misclassification bias in studies [13]. Furthermore, the rate of false-positive diagnosis of AD may be influenced by the APOE status and age of patients, as the proportion of some differential diagnoses, like frontotemporal dementia, is higher in younger patients, leading to differential misclassification bias and unpredictable effect when estimating the strength of associations in case–controls studies [14].

Tau and Aβ peptide biomarkers are now incorporated in the new research diagnostic criteria in order to increase the biological homogeneity in diagnosed AD cases [15,16], and the β-amyloid deposition, pathologic tau, neurodegeneration (A/T/N) classification has recently been proposed as an unbiased biological definition of the disease [17]. Therefore, the present study aims to examine the global and age-specific association of APOE status with AD risk using a case–control design based on data on AD cases from nine European memory centers and the American Alzheimer’s Disease Neuroimaging Initiative (ADNI) study [18], in which diagnosis were based both on clinical criteria [16] and on positive-biomarkers profile according to A/T/N classification [17]. Contrary to previous case–controls studies in which controls may have also included persons at a prodromal stage of AD, we chose a first control group drawn from two large European longitudinal cohorts: the Whitehall II study [19] and Three-City Study [20], in which prevalent and incident cases of dementia over the follow-up were excluded. Furthermore, the complementarity in terms of age of these two studies ensures a wide age range to match that of patients with AD. We also considered a second independent control group, recruited from individuals seen at the same memory clinics as the AD cases, who were characterized by a normal profile of cerebrospinal fluid (CSF) AD biomarkers.

Methods

This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (S1 STROBE Checklist). The study objectives and analysis plan were developed prior to data manipulation as an MSc internship project (S1 Text). The analyses undertaken in response to reviewers’ suggestions are presented in post hoc analyses.

Patients with AD

Data were drawn from nine memory centers in Europe (France [Paris, Rouen, Montpellier], Sweden [Gothenburg], Spain [Barcelona], Italia [Perugia], Belgium [Antwerp], and Germany [Göttingen and Munich]) and the ADNI study (see www.adni-info.org) [18]. Patients with AD included in the analyses were white and had a clinical diagnosis of probable AD [16], data on APOE genotype, and a positive-biomarkers profiles according to the A/T/N classification, and they are referred to as “CSF AD cases” in this study. Positivity of biomarkers profile was defined as abnormal values for CSF Aβ42 (A+) and CSF tau phosphorylated at threonine 181 (p-tau 181, T+), according to the reference values used in the memory centers. Assessment of CSF p-tau 181 was missing in one center (Gothenburg); biomarker positivity therefore relied only on CSF Aβ42 and CSF tau for this center. CSF Aβ40 was not measured, which precluded use of the amyloid ratio in the analyses. The number of patients included from each center as well as center-specific cutoffs of the CSF biomarkers are presented in S1 Table.

Controls

“Population controls” came from two large European cohort studies of community-dwelling people with a focus on cognitive aging: the Whitehall II study (United Kingdom) and the Three-City Study (France). Design and procedures of these studies have been reported previously [19,20]. Data on controls from these studies were drawn from the wave when APOE genotype was determined (baseline for Three-City Study, third clinical screening for Whitehall II). Both studies were complementary in terms of age of participants, as Whitehall II study included mainly middle-aged participants, and Three-City Study included persons 65 years or more at baseline. Therefore, controls less than 65 years old came from Whitehall II and those aged 65 years or more came from the Three-City Study. CSF biomarkers were not available in either of these studies. We excluded prevalent cases of dementia at measurement of APOE genotype and incident cases over the subsequent follow-up: 20 years in the Whitehall II study (168 incident cases) and 8 years in the Three-City Study (182 prevalent cases and 220 incident cases). In Whitehall II, dementia cases were ascertained based on linkage for all participants to electronic health records. Three registers (the national hospital episode statistics database, the Mental Health Services Data Set, and the mortality register) were used for dementia ascertainment by using ICD-10 codes F00-F03, F05.1, G30, and G31. In the Three-City Study, the detection of dementia cases was based on a three-step procedure at baseline and at each follow-up (neuropsychological evaluation, neurological examination, validation by an independent committee) as previously described [20]. Nonwhite participants were excluded in both studies.

We also used a second set of controls, identified as “CSF controls,” consisting of white individuals recruited at the memory centers with normal values for all CSF biomarkers (Aβ42, tau, p-tau 181). This population consisted mainly of patients assessed for cognitive disorders other than AD and/or persons referred to the memory clinic who turned out not to have AD.

Ethics statement

Ethical clearance was obtained by the institutional review boards of all participating sites (European memory centers and ADNI study sites). Ethical approval for the Whitehall II study was obtained from the NHS London—Harrow Research Ethics Committee (reference number 85/0938). The study protocol of Three-City Study was approved by the Ethical Committee of Kremlin-Bicetre University Hospital. All participants provided written, informed consent.

CSF biomarkers assessment

For the European memory centres, CSF levels of Aβ42, total tau, and p-tau 181 were assessed with the commercially available sandwich ELISA INNOTEST, using the manufacturer’s procedures (Fujirebio Europe NV, formerly Innogenetics NV).

In the ADNI study, CSF collection and processing are described in detail at http://adni.loni.usc.edu/methods/. Briefly, CSF Aβ42, tau, and p-tau 181 levels were quantified using multiplex xMAP Luminex platform (Luminex Corporation, Austin, TX) with Innogenetics (INNO-BIA AlzBio3; Ghent, Belgium) immunoassay kit–based research-use-only reagents containing 4D7A3 monoclonal antibody for Aβ42, AT120 monoclonal antibody for tau, and AT270 monoclonal antibody for p-tau 181.

The center-specific CSF biomarker cutoffs used in clinical setting were provided by each participating center and are presented in S1 Table.

APOE genotyping

In the European memory centers, APOE genotype was determined using standard polymerase chain reaction and restriction enzyme digestion according to established standard protocols [21].

In the ADNI study, APOE genotypes were determined by using DNA extracted by Cogenics from a 3-mL aliquot of EDTA blood. Polymerase chain reaction amplification was followed by HhaI restriction enzyme digestion, resolution on 4% Metaphor Gel, and visualization by ethidium bromide staining [22].

In Whitehall II and the Three-City Study, two TaqMan assays (Rs429358 and Rs7412, Assay-On-Demand, Applied Biosystems) were used and run on a 7900HT analyzer (Applied Biosystems), and APOE genotypes were indicated by the Sequence Detection Software version 2.0 (Applied Biosystems) [23,24].

Covariates

Age in the analysis was set as age at CSF collection for AD cases and CSF controls and at blood collection for APOE genotyping in the population controls. As CSF biomarker assessment was performed as part of the AD diagnostic procedure, age at CSF collection was considered as a surrogate of age at diagnosis. Mini-Mental Status Examination (MMSE) score was taken from the date closest to the lumbar puncture for patients with AD and APOE determination in the population controls. Level of education was considered in three categories: no education to primary school, secondary school to high school, and baccalaureate or university degree.

In a subsample, data on the following cardiovascular risk factors were available: hypertension defined as systolic/diastolic blood pressure ≥140/90 mmHg or use of antihypertensive treatment; diabetes as fasting glycemia ≥1.26 g/L or use of antidiabetics drugs; and dyslipidemia as LDL cholesterol ≥1.9 g/L or use of lipid-lowering treatment.

Statistical analyses

Participant characteristics were examined in three groups: CSF AD cases, population controls, and CSF controls. Proportions were calculated for categorical variables, and means and standard deviations were computed for continuous variables. Comparison of CSF AD cases with both control groups was assessed using a χ² test or Student t test as appropriate. Comparison of mean CSF biomarker values between CSF AD cases and CSF controls were adjusted for memory centers using analysis of covariance. Cumulative percentage of CSF AD cases as a function of age (in 5-year age groups) were plotted according to the APOE ε4 status (0, 1, 2 alleles); median age in the three groups was compared using the nonparametric Brown–Mood median test. We then used logistic regression to estimate the odds ratio (OR) of AD according to APOE genotype, comparing the total population of CSF-determined AD cases to population controls first and then to CSF controls. The role of age in modifying the association between APOE genotype and AD was examined in analyses stratified by 5-year age group, ranging from <55 years to >85 years. The ε3/ε3 group was the reference, and analysis was undertaken in groups using ε4 status. The nonlinearity of associations with AD as a function of age was tested using an interaction term between age² and APOE.

Population attributable fraction (PAF) associated with APOE ε4 (one allele, two alleles) for AD was plotted as a function of 5-year age group. PAF reflects the fraction of AD cases related to the presence of the APOE ε4 allele, and its calculation is based on prevalence of APOE ε4 among CSF AD cases (PREV_Ɛ4) and the ORs associated with APOE ε4: PAF = PREV_Ɛ4 × (1 − 1/OR) [25]. ORs used for these estimations were those from the analysis comparing CSF AD cases to population controls.

We also examined whether sex and education affected the age-dependent association between APOE ε4 and AD using a triple interaction term in the logistic regression model. To ensure robustness of our findings, the analyses were repeated using controls defined by CSF biomarkers.

We conducted several post hoc analyses in response to peer review comments. First, as CSF p-tau 181 was missing for one of the centers (Gothenburg), we examined the impact of excluding data from this center on our findings. Second, we calculated the sensitivity and specificity of carrying ≥1 APOE ε4 to discriminate CSF AD from controls, and the corresponding area under receiver operating characteristic (ROC) curves (AUCs) were plotted as a function of age to compare with previous studies [26]. Third, we estimated the heterogeneity of the association between APOE and AD in the various centers by stratifying the analyses by memory center and weighting their effect by the sample size, as in a meta-analysis. We calculated the I² statistic to evaluate heterogeneity in these estimates [27]. Finally, we examined the impact of cardiovascular risk factors on the association between APOE genotype and AD. These analyses were based on a subsample of the population of CSF AD cases for whom these data were available and all population controls. Using logistic regression, we first report crude ORs, followed by analyses adjusted for sex and education and, finally, for hypertension, diabetes mellitus, and hypercholesterolemia.

All resulting p-values were two-tailed, and p ≤ 0.05 was considered statistically significant. Statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA) and STATA version 14.

Results

A total of 1,593 CSF AD cases, 11,723 population controls, and 805 CSF controls were included in the analyses; their characteristics are summarized in Table 1. Compared with CSF controls and population controls, CSF AD cases were older (72.8 versus 67.1 and 65.6 years), more likely to be women (55.4% versus 49.9% and 47.1%), and had a lower MMSE score (21.4 versus 25.6 and 27.5). CSF cases were also more likely to carry at least one APOE ε4 allele (46.7% versus 21.0% and 21.2%) or two ε4 alleles (16.6% versus 0.4% and 1.4%). The proportion of APOE ε4 carriers did not differ between population controls and CSF controls (respectively, 22.6% and 21.4%, p = 0.41).

Table 1. Characteristics of the study population: CSF-determined AD cases, CSF-determined controls, and population controls.

	CSF AD cases	CSF controls	Population controls
Characteristics	(N = 1,593)	(N = 805)	(N = 11,723)	p-Value^a	p-Value^b
Age, years, mean (SD)	72.8 (8.3)	67.1 (10.3)	65.6 (10.7)	<0.001	<0.001
Women, n (%)	883 (55.4)	402 (49.9)	5,525 (47.1)	0.011	<0.001
MMSE, mean (SD)^c	21.4 (5.9)	25.6 (4.4)	27.5 (1.8)	<0.001	<0.001
Education, n (%)^d				0.005	<0.001
Low	83 (6.8)	56 (9.3)	612 (5.2)
Medium	334 (27.3)	195 (32.4)	9,079 (77.4)
High	805 (65.9)	350 (58.2)	2,032 (17.3)
APOE genotype, n (%)				<0.001	<0.001
ε2/ε2	3 (0.2)	2 (0.2)	73 (0.6)
ε2/ε3	67 (4.2)	113 (14.0)	1,440 (12.3)
ε3/ε3	514 (32.3)	518 (64.3)	7,560 (64.5)
ε2/ε4	43 (2.7)	8 (1.0)	220 (1.9)
ε3/ε4	701 (44.0)	161 (20.0)	2,267 (19.3)
ε4/ε4	265 (16.6)	3 (0.4)	163 (1.4)
CSF biomarkers, pg/mL, mean (SD)
CSF Aβ42	357.4 (177.5)	803.6 (346.7)	—	<0.001^e
CSF tau	535.3 (400.4)	181.3 (88.7)	—	<0.001^e
CSF p-tau 181	83.2 (49.9)	35.0 (12.8)	—	<0.001^e

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^aComparison between CSF AD cases and CSF controls, χ² test or Student t test.

^bComparison between CSF AD cases and population controls, χ² test or Student t test.

^cMMSE data were missing for 108 CSF AD, 41 CSF controls, and 4,186 population controls.

^dEducation data were missing for 371 CSF AD and 204 CSF controls.

^eAnalyses on CSF biomarkers were adjusted for memory center and analysis of covariance.

Abbreviations: Aβ, β-amyloid; AD, Alzheimer disease; APOE, apolipoprotein E; CSF, cerebrospinal fluid; MMSE: Mini-Mental State Examination; p-Tau 181, tau phosphorylated at threonine 181; SD, standard deviation

Fig 1 presents the cumulative proportion of CSF AD cases as a function of age and APOE ε4 status. The median age at AD diagnosis of non-ε4 carriers (75.2 years) was greater than that of one ε4 carriers (73.8 years, p = 0.016) and of ε4/ε4 carriers (70.3 years, p < 0.001). Compared with non-ε4 carriers, the cumulative percentage of AD cases in two ε4 carriers was higher starting at age 63.5 years, and in one ε4 carriers, the percentage was higher starting at 69.1 years.

The unadjusted association of APOE genotypes with AD is presented in Table 2. The presence of at least one ε4 allele was associated with an OR of 5.9 (95% confidence interval [CI] 5.3–6.6; p < 0.001) compared with non-ε4 carriers. Using ε3/ε3 as the reference, ε2 allele was associated with lower risk of AD (OR: 0.68 [0.53–0.88]; p = 0.003), whereas ε2/ε4 (OR: 2.9 [2.0–4.0]; p < 0.001), ε3/ε4 (OR: 4.5 [4.0–5.1]; p < 0.001), and ε4/ε4 (OR: 23.9 [19.3–29.6]; p < 0.001) were associated with greater risk of AD. Using CSF controls instead of population controls yielded similar findings (Table 2), as well as the exclusion of the center with missing data for CSF phosphorylated tau (see S2 Table).

Table 2. The ORs of AD according to APOE genotype.

CSF AD cases were compared with population controls and with CSF controls using logistic regression analysis.

	CSF AD cases versus population controls		CSF AD cases versus CSF controls
APOE genotype	OR (95% CI)	p-Value	OR (95% CI)^a	p-Value^a
0 ε4	1 (Ref)		1 (Ref)
≥1 ε4	5.9 (5.3–6.6)	<0.001	6.4 (5.2–7.7)	<0.001
0 ε4	1 (Ref)		1 (Ref)
1 ε4	4.6 (4.1–5.2)	<0.001	4.8 (3.9–5.8)	<0.001
2 ε4	25.4 (20.4–31.2)	<0.001	—	—
ε2/ε2, ε2/ε3	0.68 (0.53–0.88)	0.003	0.61 (0.44–0.85)	0.003
ε3/ε3	1 (Ref)		1 (Ref)
ε2/ε4	2.9 (2.0–4.0)	<0.001	—	—
ε3/ε4	4.5 (4.0–5.1)	<0.001	4.4 (3.6–5.4)	<0.001
ε4/ε4	23.9 (19.3–29.6)	<0.001	—	—

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OR could not be determined due to small numbers in the following CSF control categories: ε4/ε4 (n = 3) and ε2/ε4 (n = 8) categories.

Abbreviations: AD, Alzheimer disease; APOE, apolipoprotein E; CI, confidence interval; CSF, cerebrospinal fluid; OR, odds ratio; Ref, reference

The proportion of APOE ε4 carriers by 5-year age group is shown in Fig 2. In total, 28.9% of CSF AD cases <55 years at diagnosis carried one ε4 allele, and this rate increased progressively to 54.2% in the group aged 65–70 years and then progressively decreased to 28.1% in those over 85 years at AD diagnosis. Similarly, 8.9% of AD cases <55 years at diagnosis were homozygous ε4/ε4; this proportion climbed progressively to 29.3% in the group aged 60–65 years and then progressively decreased (3.7% in those ≥85 years). Among population controls, the proportion of APOE ε4 carriers was around 25% until 65 years old, 20% between 65 and 80 years old, and 15% after the age of 80 years. The distribution of APOE ε4 as a function of age was similar in population controls and CSF controls (χ² test, p = 0.42).

The PAF associated with the presence of at least one APOE ε4 allele for AD in the total population was 53%; the PAF by 5-year age categories is presented in Fig 3. PAF associated with at least one ε4 was highest in the group aged 65–70 years, at 69.7%. The PAF associated with one ε4 allele was also highest in the group aged 65–70 years, at 48.0%. The PAF of two ε4 alleles was highest in the group aged 60–65 years, at 28.4%. The importance of ε4 for AD was lower both at younger (<55 years, PAF: 14.2%) and older (>85 years, PAF: 22.6%) ages.

Fig 3 — AD, Alzheimer disease; *APOE*, apolipoprotein E.

Fig 4 shows the association of APOE genotype with AD as a function of 5-year age group, adjusted for sex and education. There was no evidence that the age-related association of APOE ε4 differed by sex (p = 0.77) or education (p = 0.61). The association of APOE ε4 genotype with AD was modified by age (p for interaction with age² < 0.001), with the strongest association in the 65–70 age group: one ε4 allele (OR: 10.7 [7.6–15.2]; p < 0.001), ε4/ε4 (OR: 64.2 [34.1–120.8]; p < 0.001). The protective association of APOE ε2 genotype for risk of AD was not affected by age (p for interaction = 0.72).

Post hoc analysis

Sensitivity and specificity of APOE ε4 to discriminate CSF AD from population controls was, respectively, 56% and 78% for heterozygotes and 31% and 98% for homozygotes, corresponding to an AUC of 0.70 (0.69–0.72, p < 0.001); similar results were found when comparing CSF AD cases with CSF controls (AUC = 0.70 [0.69–0.73], p < 0.001). The ability of APOE ε4 to discriminate AD from controls differed as a function of age (Fig 5) and was greatest in the group aged 65–69 years (AUC = 0.78 [0.75–0.80], p < 0.001) and poorer before 55 years (AUC = 0.55 [0.47–0.62], p = 0.32) and after 85 years (AUC = 0.61 [0.56–0.67], p = 0.001).

Fig 5 — AD, Alzheimer disease; *APOE*, apolipoprotein E; AUC, area under receiver operating characteristic curve; CI, confidence interval; CSF, cerebrospinal fluid.

We examined the heterogeneity in associations of one or more APOE ε4 with AD across the different memory centers using population controls as the comparison group. These results are shown in Fig 6. The I² statistic was 58%, corresponding to some heterogeneity between centers.

Fig 6 — AD, Alzheimer disease; *APOE*, apolipoprotein E; CI, confidence interval; OR, odds ratio.

The final analysis was on the subset of patients with AD (841 CSF AD cases) with data on cardiovascular risk factors. There were no significant differences between CSF AD cases with and without these data in term of age (p = 0.80) and APOE genotype (p = 0.67). Compared with general population controls (see S3 Table), CSF AD cases were more likely to have hypertension (p = 0.024), diabetes mellitus (p < 0.001), and hypercholesterolemia (p < 0.001). We examined the role of these risk factors in the association of APOE genotypes with AD without adjustment for age due to its role in modifying the association between APOE genotype and AD. Table 3 shows these results. Adjustment for sex and education (model 1) and for cardiovascular risk factors (model 2) had little impact on the estimates compared with the unadjusted model. S1 Fig shows similar findings in analyses stratified by age group.

Table 3. The ORs of AD in CSF AD cases compared with population controls: multivariable logistic regression analysis.

	Unadjusted		Model 1^a		Model 2^b
APOE	OR (95% CI)	p-Value	OR (95% CI)	p-Value	OR (95% CI)	p-Value
0 ε4	1 (Ref)		1 (Ref)		1 (Ref)
≥1 ε4	5.9 (5.1–6.8)	<0.001	6.0 (5.1–7.0)	<0.001	6.0 (5.1–7.0)	<0.001
0 ε4	1 (Ref)		1 (Ref)		1 (Ref)
1 ε4	4.7 (4.0–5.4)	<0.001	4.7 (4.0–5.6)	<0.001	4.7 (4.0–5.6)	<0.001
2 ε4	24.6 (19.0–31.7)	<0.001	25.7 (19.0–34.7)	<0.001	26.5 (19.5–36.1)	<0.001
ε2/ε2, ε2/ε3	0.55 (0.38–0.81)	0.002	0.54 (0.37–0.79)	0.002	0.53 (0.36–0.78)	0.001
ε3/ε3	1 (Ref)		1 (Ref)		1 (Ref)
ε2/ε4	2.5 (1.5–3.9)	<0.001	2.3 (1.4–3.9)	<0.001	2.3 (1.4–3.8)	0.001
ε3/ε4	4.5 (3.8–5.3)	<0.001	4.6 (3.8–5.4)	<0.001	4.6 (3.8–5.5)	<0.001
ε4/ε4	22.7 (17.6–29.4)	<0.001	23.7 (17.4–32.1)	<0.001	24.5 (18.0–33.4)	<0.001

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Analyses were performed on a subsample (N = 841 AD cases, 11,665 controls).

^aModel 1: adjustment for sex and education.

^bModel 2: model 1 + further adjustment for hypertension, diabetes, and hypercholesterolemia.

Abbreviations: AD, Alzheimer disease; APOE, apolipoprotein E; CI, confidence interval; CSF, cerebrospinal fluid; OR, odds ratio; Ref, reference

Discussion

In this large multicentric study that included 1,600 biomarker-positive AD cases, we showed that the association between APOE ε4 and AD is modified by age. The impact of ε4 was less pronounced before the age of 60, strongest between 65 and 70 years, and then declined progressively at older ages. APOE ε4 carriers were more likely to develop AD at younger ages, with a difference of 4.9 years for ε4/ε4 and 1.4 years for one ε4 carriers when compared with median age at AD diagnosis in non-ε4 carriers (75.2 years). The PAF associated with APOE ε4 for AD was 53% overall, but it varied strongly with age, following a bell-curve relationship that ranged from less than 20% in the youngest and the oldest age groups and reaching 70% between 65 and 70 years. The protective effect of APOE ε2 allele was unaffected by age. The association between APOE genotype and AD was first reported in 1993 [28], and age is thought to play a role in this association [29,30]. Our use of a large, multicentric study of patients with AD defined by the new A/T/N criteria allows the risk of misclassification bias to be addressed, as it can be critical in such analyses. A further advantage of our study is the use of population controls from two large longitudinal cohorts in which the follow-up allowed us to remove incident cases of dementia. Because this control group without clinical dementia may be positive on AD biomarkers, we also considered a second group of controls drawn from the same memory clinics as the AD cases. This group of controls had a normal CSF AD biomarker profile, and results using these two independent sets of controls were similar, suggesting that our findings are robust.

In our study, carrying at least one APOE ε4 allele was associated with a 5.9 (5.3–6.6; p < 0.001) higher OR of AD, compared with an OR of 3.3 (3.2–3.4; p < 0.001) reported by a recent meta-analysis of 46 case–control studies with 64,000 participants [31]. We found the overall PAF associated with one or more APOE ε4 allele to be 53%, compared with the 37% reported by the AlzGene meta-analysis [32]. Our estimates are higher than those previously reported from studies based on only clinical AD criteria [33] but are close to those reported when using neuropathology [34] or biomarker approaches for AD diagnoses [35,36]. Our results, along with recent findings from other studies, suggest that the impact of APOE ε4, particularly ε4 homozygotes, is underestimated in studies based exclusively on clinical criteria for AD diagnosis [37]. A possible explanation is the importance of APOE ε4 specifically for AD neuropathology [38]. Another explanation is linked to the key finding that the association between APOE ε4 and AD is mediated by age. Therefore, a single, overall OR may not be suitable; reporting age-specific ORs, as in our analyses, may facilitate comparison between studies.

Our findings have implications for several types of studies, e.g., epidemiological and genetic, aiming to reveal biological associations between environmental and genetic risk factors for AD, which generally are performed on clinically diagnosed patients and cognitively unimpaired controls, without biomarker data. Midlife vascular risk factors (obesity, smoking, diabetes, hypertension, and cardiac disease) have commonly been found to increase risk of cognitive decline and AD dementia defined using clinical criteria; population studies employing biomarkers show that such risk factors are associated with neurodegeneration but not brain amyloidosis [39]. Further, genome-wide association studies have identified loci associated with clinically defined AD, but when examined in autopsy cohorts, no associations were found with plaques or tangle pathology; instead, associations were found with cerebrovascular disease [40]. Thus, there is a need to reinvestigate possible associations between environmental and genetic risk factors for AD using biomarker-based studies to understand the biologic basis of such associations.

Causes of early-onset AD, before 65 years, remain poorly understood. Autosomal dominant mutations, affecting amyloid precursor protein (APP), presenilin-1 (PSEN1), or presenilin-2 (PSEN2) genes, are thought to be involved, but these mutations are rare, accounting for less than 10% of early-onset AD [1]. During this past decade, several genome-wide association studies have discovered around 30 risk loci of the disease, which are useful to identify novel insights into the neurobiology of the disease, but their contribution to explaining AD in the population is thought not to be substantial [10]. Conversely, recent efforts in whole-exome and whole-genome sequencing of large AD case–control series unraveled three major genes—sortilin-related receptor (SORL1); triggering receptor expressed on myeloid cells-2 (TREM2); and ATP-binding cassette, sub-family A, member 7 (ABCA7)—the rare coding variants of which significantly increase the risk of AD with moderate to high OR [41]. Interestingly, the ORs were higher in patients with early-onset AD [41], and some patients carried more than one strong risk factor, including APOE ε4, suggesting an oligogenic inheritance in some of these patients.

In our study, APOE ε4 did not play a strong role in risk of AD before the age of 60 years, whereas its role increased dramatically during the seventh decade to hit its peak by 70 years. Asymptomatic APOE ε4 carriers are a major target for potential disease-modifying drugs to prevent AD, and several clinical trials are currently ongoing on this population [42]. Our findings support the idea of an early intervention in this population, if and when available, before APOE ε4 carriers reach the age at which incidence of AD rises sharply.

Strengths and limitations

This study has several strengths, including the use of AD cases determined using CSF biomarkers for tau and Aβ; a large sample size, which allowed sufficient power to undertake analysis in 5-year age categories; as well as the use of two large population cohort studies with long follow-up data, allowing us to exclude incident cases of dementia. Furthermore, we were able to replicate findings using a further set of controls, consisting of persons with normal CSF biomarkers who were seen at the same memory centers as the AD cases. The distribution of APOE genotypes by age group was similar in the two sets of controls, and the associations with AD using the two types of controls were also similar.

This study needs to be considered in light of the following limitations. First, AD cases drawn from memory centers may not be representative of the general population of patients with AD, in particular patients who do not seek medical care. This may involve some selection bias, primarily due to sociodemographic factors like education or sex, but it is unlikely to be a source of major bias because APOE status is unlikely to affect the decision to consult at memory clinics. Second, data on cardiovascular risk factors or familial history were missing for a part of the CSF AD cases, and adjustment for these risk factors was possible only on a subsample. More-detailed data on a larger set of risk factors would be useful in future studies to better understand the mechanisms underlying the relationship between APOE and AD. Third, the overall ratio between AD cases and controls used in this study was around 1:7, which may lead to detection of nonpertinent associations due to an overpowered design. However, the value of a large sample size is the ability to examine the association between APOE and AD in age subgroups to show the manner in which age modifies this association [43]. Finally, these analyses were restricted to white populations because the APOE ε4 allele frequency as well as its association with AD risk may be strongly influenced by ethnicity and geographic region [44,45]. Further research using different population settings is needed to better understand these complex associations.

Conclusions

This study supports an association between APOE ε4 and the risk of AD evaluated using biomarkers of AD neuropathology, and the results suggest that the strength of this association varies by age. The effect of APOE ε4 on AD was less pronounced in both younger and older persons (less than 60 and more than 85 years) and was greatest between 65 and 70 years, with a population attributable risk of 70% in this group. These findings highlight the importance of early interventions, if and when available, to mitigate the effect of APOE ε4 on AD.

Supporting information

S1 STROBE Checklist. STROBE checklist for cohort studies.

STROBE, Strengthening the Reporting of Observational Studies in Epidemiology.

(DOCX)

Click here for additional data file.^{(22.6KB, docx)}

S1 Fig. Association of APOE genotype in CSF AD cases compared with population controls in a subsample with data on cardiovascular risk factors.

Genotype ε3/ε3 was used as reference. Associations between age and OR of AD were modeled using a quadratic term for age in the logistic regression model and adjusted for sex, education, hypertension, diabetes mellitus, and hypercholesterolemia. AD, Alzheimer disease; APOE, apolipoprotein E; CSF, cerebrospinal fluid; OR, odds ratio.

(TIF)

Click here for additional data file.^{(322.7KB, tif)}

S1 Table. Threshold levels used for defining abnormal values of CSF Aβ42, CSF tau, and CSF p-tau 181 in the memory centers that participated in the study.

Aβ, β-amyloid; CSF, cerebrospinal fluid; p-Tau 181, tau phosphorylated at threonine 181.

(DOCX)

Click here for additional data file.^{(16.5KB, docx)}

S2 Table. The odds ratios of AD in CSF AD cases compared with population controls before and after exclusion of the center with missing CSF phosphorylated tau.

AD, Alzheimer disease; CSF, cerebrospinal fluid.

(DOCX)

Click here for additional data file.^{(18.4KB, docx)}

S3 Table. Characteristics of the subsample used for the assessment of the association between APOE genotype and AD adjusted for cardiovascular risk factors.

AD, Alzheimer disease; APOE, apolipoprotein E.

(DOCX)

Click here for additional data file.^{(19.1KB, docx)}

S1 Text. Prospective analysis plan.

(DOCX)

Click here for additional data file.^{(18.8KB, docx)}

Acknowledgments

Some of the data used in preparation of this article were obtained from the ADNI database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. The Three-City Study is conducted under a partnership agreement between the Institut National de la Santé et de la Recherche Médicale (INSERM), the Victor Segalen-Bordeaux II University, and the Sanofi-Synthélabo Company.

Abbreviations

Aβ: β-amyloid
ABCA7: ATP-binding cassette, sub-family A, member 7
AD: Alzheimer disease
ADNI: American Alzheimer’s Disease Neuroimaging Initiative
APOE: apolipoprotein E
APP: amyloid precursor protein gene
A/T/N: β-amyloid deposition, pathologic tau, neurodegeneration
AUC: area under ROC curve
CI: confidence interval
CSF: cerebrospinal fluid
MMSE: Mini-Mental Status Examination
OR: odds ratio
PAF: population attributable fraction
PSEN1: presenilin-1 gene
PSEN2: presenilin-2 gene
p-Tau 181: tau phosphorylated at threonine 181
ROC: receiver operating characteristic
SORL1: sortilin-related receptor
STROBE: Strengthening the Reporting of Observational Studies in Epidemiology
TREM2: triggering receptor expressed on myeloid cells-2

Data Availability

Data coming from the European memory clinics used in this study are freely available at: https://figshare.com/articles/CSF_biomarkers_data_pdf/12030084. The Whitehall-II Study is managed by the Department of Epidemiology and Public Health of the University College of London (UCL). The list of the principal investigators of the study can be shown here: https://www.ucl.ac.uk/epidemiology-health-care/research/epidemiology-and-public-health/research/whitehall-ii/people/principal-investigators. Data coming from the Whitehall-II Study can be made freely available to interested researchers upon request: https://www.ucl.ac.uk/epidemiology-health-care/research/epidemiology-and-public-health/research/whitehall-ii/data-sharing. Contact information: whitehall2@ucl.ac.uk. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a longitudinal multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimers disease. The principal investigator is Pr Michael W. Weiner, Professor of Radiology, Medicine, Psychiatry, and Neurology at the University of California San Francisco. Data coming from the ADNI study can be made freely available to interested researchers upon request: http://adni.loni.usc.edu/data-samples/access-data/. Contact information: adni-study@usc.edu. The 3-City Study is managed by the INSERM Unit U708, Université Victor Segalen, Bordeaux, France. The principal investigators are Pr Jean-François Dartigues and Pr Christophe Tzourio. Data coming from the 3-City Study can be made freely available to interested researchers upon request: http://www.three-city-study.com/the-three-city-study.php. Contact information: E3C.U708@inserm.fr.

Funding Statement

The authors received no specific funding for this work.

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PLoS Med. doi: 10.1371/journal.pmed.1003289.r001

Decision Letter 0

Louise Gaynor-Brook

17 Feb 2020

Dear Dr. Dumurgier,

Thank you very much for submitting your manuscript "Age modifies the association between Apolipoprotein E genotype and Alzheimer’s disease: a multicountry cerebrospinal fluid biomarker-based case-control study." (PMEDICINE-D-19-04199) for consideration at PLOS Medicine.

Your paper was discussed among the editorial team, evaluated by an academic editor with relevant expertise, and sent to independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of these reviews, we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to invite you to submit a revised version that fully addresses the reviewers' and editors' comments. You will appreciate that we cannot make a decision about publication until we have seen the revised manuscript and your response, and we expect to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

We hope to receive your revised manuscript by Mar 09 2020 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see http://journals.plos.org/plosmedicine/s/submission-guidelines#loc-methods.

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

Please let me know if you have any questions. Otherwise, we look forward to receiving your revised manuscript in due course.

Sincerely,

Richard Turner PhD, for Louise Gaynor-Brook, MBBS PhD

Associate Editor, PLOS Medicine

rturner@plos.org

-----------------------------------------------------------

Requests from the editors:

Please adapt the title so that it is not declarative. We suggest "Age and the association between apolipoprotein E genotype and Alzheimer’s disease: a cerebrospinal fluid biomarker-based case-control study.

In the abstract and elsewhere, please add p values alongside CI where available.

Please add summary demographic details for study participants to the abstract.

Please add a new final sentence to the "methods and findings" subsection of your abstract, which should summarize the study's main limitations.

Please begin the sentence at line 86 with "In this study, we found that ..." or similar.

After the abstract, we will need to ask you to add a new and accessible "author summary" section in non-identical prose. You may find it helpful to consult one or two recent research papers published in PLOS Medicine to get a sense of the preferred style.

Early in the methods section of your main text, please state whether the present study had a protocol or prespecified analysis plan, and if so attach the relevant document(s) as an attachment, referred to in the text. please highlight analyses that were not prespecified.

At line 345 and any other instances, please avoid claims of "the first" or similar, and where these are needed please add "to our knowledge", for example.

Where study limitations are summarized (at line 412), we suggest crafting a dedicated paragraph and providing a fuller discussion.

In the reference list, please adapt citations so that, where appropriate, six rather than five authors' names are listed, followed by "et al.".

For reference 21, please make the journal name "BMJ".

Please adapt the attached STROBE checklist so that individual items are referred to by section (e.g., "Methods") and paragraph number rather than by page or line numbers, as the latter generally change in the event of publication. Please refer to this in the methods section of your main text.

Comments from the reviewers:

*** Reviewer #1:

Thank you for the opportunity to review this very interesting and compelling study by Saddikki and colleagues on exploring the association between the APOE e genotype and dementia. This retrospective study used brought together a consortia of AD patients and non-AD controls from Whitehall II 3-City to determine the effect size of association between APOE e4 allele (one/two copies) and AD, provide PAFs by age-stratum. The author did find an significant association (with stronger effects seen in the homozygotes) with the effect modified by age. The effect sizes were much higher than previously reported in published evidence, however it has been well-established from previous meta-analysis and case-control studies that APOE genotypes are associated strongly with AD. The case control design is an appropriate design for this analysis and the statistical analysis was simple and straightforward.

However, my major comments regards on controls selection, imbalance between cases and controls which will require some form of covariate adjustment or propensity score matching as the effect sizes of unadjusted ORs may be overestimated.

Specific comments related to this:

1) The authors utilised two large community dwelling cohorts to source controls from in the UK and France with APOE genotyping with 11,724 controls. The ratio between AD cases and controls is therefore approx. 1:7. Previous evidence has suggested that ORs for APOE genotypes are order of magnitude of > 3. I'm surprised the authors did not report a sample size calculation based on expected detection to get a sense of the minimum ratio of controls to cases. I mention this because it's likely the study is overpowered. While larger number of controls may seem obviously better, there may have been an opportunity to do a more sophisticated selection technique to account for selection and indication bias (which the authors themselves discuss as a limitation) given set a large number of controls. Authors clarification and comment on this aspect would be useful here.

2) Related the above comment then, I bring up the control selection because in Table 1, there are significant imbalances in age, gender, MMSE, education, CSF biomarkers (P < 0.001) and these are just the covariates that were reported. I would venture to guess that there are quite few more covariates captured. In the subsequent analysis of the logistic regression models (Table 2), there was no indication any covariate adjustments were made. In fact, there seems to be no consideration of prior history vascular conditions (for instance APOE genotypes are associated with familial hypercholesterolaemia and atherosclerosis - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505295/). Reporting crude ORs is good but what would improve the analysis and be more convincing if adjusted analyses could also be provided to account for confounders.

3) One method that could help deal with residual confounding is a the use of propensity scores adjustment (https://www.sciencedirect.com/science/article/pii/S1476927116300135) - creating a regression model (based on distribution of all the covariates) and then using the score to adjust during the model. This does not necessarily need to be done if simple covariate adjustment, considering confounding factors such as vascular comorbidities was taken into account. Barring that, covariate adjustment in adjusted model should be considered.

4) An early study with similar design (https://www.sciencedirect.com/science/article/pii/0895435696001953) showed similar results but looked at the sensitivity and specificity of E4 genotypes and found that the sensitivity was 0.52 /specificity was 0.74 for heterozygotes and homozygotes 0.23 sensitivity/0.99 specificity. The authors concluded that it was significant risk factors but as a diagnostic marker for AD would miss many true cases and misclassify many normal as AD. Can the authors show what the sensitivity and specificity of the biomarker is in their sample and whether or not they believe it has additional added value over and beyond the clinical assessment. Ideally you want to perform a ROC analyses but understand this may be not in the scope of the study analysis.

Apart from these issues above, the study reveals that the effect sizes were similar but perhaps there conclusion from their crude ORs that the associations between APOE genotypes and AD is much greater than previously reported may actually decrease when consideration of better control selection and covariate adjustment is taken into account. It would be advisable for the authors to consider these issues prior to consideration for publication.

*** Reviewer #2:

In this work Saddiki and colleagues aimed to assess the association between AD and APOE genotype in groups of patients based on age-specific increments. In this confirmatory study the studied subjects were included from 9 different European centers, and the ADNI. The rationale for the study is based on previous studies assessing associations between APOE genotype and AD in patients diagnosed based on clinical criteria rather than evidence of AD pathology as assessed by available biomarkers - hence the authors speculated that the previously reported strong association between APOE and AD is an underestimation due to imprecise clinical diagnosis. Results are in line with previous studies reporting a strong association between APOE4 and AD and which is modified by age - less pronounced effect in younger and older individuals. The main take-home is that the association between AD and a homozygous APOE4 genotype is stronger than that reported in previous studies which were based on clinical AD diagnosis without the use of CSF biomarkers. This is an interesting study which is largely confirming previous studies hence novelty is limited yet the take-home message is of importance. This reviewer has several major concerns which need to be addressed before this work can be accepted for publication:

Major:

- The studied subjects were assessed in various different memory clinics which according to the supplementary information used locally-defined CSF biomarker cut-offs which at least for Abeta varied dramatically. Given the variation in AD risk between subjects in different geographical locations (most probably due to impact of environment factors like diet, sun exposure etc) the authors are asked to include a table specifying the number of subjects included from each European center so that the effect of each location on the results can be assessed. This is important especially since the results may be biased by results from specific populations in which amyloid-beta pathology (which is driven mainly by presence of the APOE4 allele both in patients and controls) was more/less pronounced as assessed by CSF AD biomarkers.

- Subjects from one of the centers lacked CSF p-tau and amyloid-beta40, the authors need to explain how this affected the A/T/N classification - if incomplete data this reviewer suggests to remove the subjects from that center from the study unless there is a strong rationale to as why to keep them in.

- The authors should address the p-tau cut-off employed in Antwerpen if it is not a typographical error

- More information about the controls should be provided. It is widely known that many cognitive controls exhibit altered CSF AD biomarkers with no impact on clinical parameters - the authors need to discuss this aspect

- Included subjects are described as Caucasian, the authors need to state whether ethnicity was self-reported by the study subjects or assessed by the examining physician only by the appearance of skin color. By tradition ethnicity has not been routinely logged in some European countries (contrary to for example the USA) - since the authors explicitly state that the study was performed on Caucasians they need to comment on this assessment.

- The authors do not give a proper rationale to as why non-Caucasians were excluded from the study

Minor:

- The authors should explain the A/T/N classification abbreviation in the abstract

- References are lacking to the methodologies used to assess APOE genotype (M&M)

- The authors need to explain the term 'CSF AD cases'

- There are several language errors (typos) which need to be corrected

- The statistical method used to assess group differences should be described in the text and figure legends

*** Reviewer #3:

In this manuscript Saddiki and colleagues use the rigorous A/T/N framework to re-evaluate risk of AD and APOE genotype. They use a case control design (1,599 cases and 801 controls and 11,724 controls) and calculated odds ratios and population attributable fraction (PAF) for AD association with APOE genotypes and age. They report OR of having AD is 4.6 with one E4 copy and 25.4 with two copies. They report highest PAF (69.7) between ages 65-70, and significantly weaker PAF at the tails of the age distributions. They find a modest effect of sex with females showing a stronger effect of E4 on AD risk. They conclude that E4 confers even greater risk that previously appreciated in a cohort rigorously defined using A/T/N biomarker criteria

This is a nice study in which the authors make a strong case for the use of the A/T/N framework in order to reduce misclassification noise from clinical diagnosis. They show that APOE effects on AD risk may be stronger than previously known, vary across aging, and disproportionately affect women. This is an important study and substantially contributes to our understanding of the two most well-known risk factors for AD- age and APOE. The strengths of the study include biomarker-based diagnosis rather than clinical diagnosis for the primary contrasts (CSF AD vs CSF controls) and the relatively large sample size of all participant groups. The comparison of the CSF AD and the population control cohort is really an extension of the CSF AD vs CSF control group since the population cohort was not defined using the A/T/N criteria. However, this is not really a weakness or significant limitation, but inferences about the CSF AD vs population controls should be made with this caveat. A more concerning limitation is the exclusion of non-Caucasian participants. The risk for AD is different for Caucasian and non-Caucasians and this is something that can be addressed in future studies.

I have a few additional comments:

1) Because participants were all Caucasian, other risk factors for AD which are over represented in non-Caucasian populations including vascular and metabolic factors may be under represented here. APOE risk for AD may be overstated in this study because these other risk factors were underrepresented. The authors should state this as a limitation of the study, or alternately qualify all of the findings as applying to Caucasians.

2) Its misleading to call the comparison between the CSF AD and CSF controls "secondary analyses" (line 166-168. The "cleaner" control group here is the CSF controls because they were identified by the more rigorous criteria (A/T/N). Further, its not entirely clear how the CSF controls were recruited and under what conditions. The authors state they came from the memory centers (line 168) but other than stating they were required to have normal A/T/N values its not clear who these participants were. Were non-Caucasian excluded from this group? Were they spouses or siblings of the CSF AD participants? A little more detail on how these CSF controls were included in the study would be helpful to understand whether they are comparable to the population control group.

3) The authors might consider minimizing the notion that they "…ensured that the controls didn't include very early stage of dementia" (lines 347-349). To be fair, they did exclude prevalent and incident AD in their population controls through clinical evaluations which does minimize misclassification, but a major premise of this study is that biomarker diagnosis is superior to clinical diagnosis through reducing misclassification bias. Only the 801 CSF control participants met this scrutiny, the 11,724 population controls did not.

4) Table 1 presents a single p value for what is presumably a students t-test for the continuous variables age and MMSE, but there are three groups (CSF AD, CSF controls, population controls). The authors need to clarify which comparison the p value reflects or provide p values for all group comparisons.

4) Sentences on Lines 123-125 and 349-352 are awkwardly written.

***

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. 2020 Aug 20;17(8):e1003289. doi: 10.1371/journal.pmed.1003289.r002

Author response to Decision Letter 0

25 Mar 2020

Attachment

Submitted filename: Response to reviewers.docx

Click here for additional data file.^{(511.9KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1003289.r003

Decision Letter 1

Caitlin Moyer

20 May 2020

Dear Dr. Dumurgier,

Thank you very much for submitting your revised manuscript "Age and the association between apolipoprotein E genotype and Alzheimer’s disease: a cerebrospinal fluid biomarker-based case-control study." (PMEDICINE-D-19-04199R1) for consideration at PLOS Medicine.

Your paper was re-evaluated by a senior editor and discussed among all the editors here. It was also sent back to two of the original reviewers, and was seen by a statistical reviewer. We apologize for the delayed decision on your revised submission, and will ensure that subsequent reviews will be faster. The original statistical reviewer (Reviewer 1) was not available to re-review the revised version of the manuscript. Therefore, we recruited an additional statistical expert to evaluate the study (Reviewer 4). The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by Reviewer 4. In your revision, please do address the comments of the statistical reviewer (Reviewer 4), particularly their question regarding the use of covariates vs. propensity score matching (also brought up initially by Reviewer 1, point 3), and their question about why age was analyzed both as a categorized and continuous variable.

We expect to receive your revised manuscript by May 27 2020 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

We look forward to receiving your revised manuscript.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Requests from the editors:

1. Title: Please include the study population in the title.

2. Abstract (and throughout): Please replace "Caucasian" with "white" throughout the paper.

3. Table 1: Please define abbreviation for MMSE in the legend.

4. S1 Text: Thank you for including your analysis plan. You note that: “The analyses undertaken were proposed as an MSc internship project advertised via various university channels in November 2018.” Is there any version of the document that incorporates this explanation, or the date, to note that these analyses were pre-specified?

Comments from the reviewers:

Reviewer #2: The authors have nicely addressed my comments and those of the other reviewers. I have no further concerns.

Reviewer #3: In this revised version of their manuscript, Saddiki and colleagues have made changes that address most of the reviewers concerns. I think this is a strong study which will contribute to the field. The major limitation in my mind is still the restriction to Caucasian participants. Future studies will need to address this finding in more diverse populations.

Reviewer #4: I confine my remarks to statistical aspects of this paper.

The general approach is fine. I do have a couple of questions and issues to resolve before I can recommend publication.

My main question is why the authors chose to add covariates rather than do some form of matching (either by particular values of variables or by propensity score). While it isn't necessarily wrong to use covariates, I think matching is more common.

Lines 274-279 I am confused as to why both these were done - I would not have done the analysis with categorized age. Categorizing independent variables is almost always a mistake. But then the authors also did he analysis with age as continuous and added a quadratic term. So, what was the first analysis for? (Also, the authors could explore use of a spline method and see if it does much better than just the quardratic).

Figs. 2 and 3 - Stacked bar charts are not a good method (see the work of William S. Cleveland) It would be better to use a line graph with 3 lines in each panel of fig 2 and 2 lines in fig. 3.

Peter Flom

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. 2020 Aug 20;17(8):e1003289. doi: 10.1371/journal.pmed.1003289.r004

Author response to Decision Letter 1

26 May 2020

Attachment

Submitted filename: Response to reviewers.docx

Click here for additional data file.^{(34.4KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1003289.r005

Decision Letter 2

Caitlin Moyer

2 Jul 2020

Dear Dr. Dumurgier,

Thank you very much for re-submitting your manuscript "Age and the association between Apolipoprotein E genotype and Alzheimer’s disease: a cerebrospinal fluid biomarker-based case-control study on white older adults." (PMEDICINE-D-19-04199R2) for review by PLOS Medicine.

I have discussed the paper with my colleagues and it was also seen again by one reviewer. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

Our publications team (plosmedicine@plos.org) will be in touch shortly about the production requirements for your paper, and the link and deadline for resubmission. DO NOT RESUBMIT BEFORE YOU'VE RECEIVED THE PRODUCTION REQUIREMENTS.

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.

We expect to receive your revised manuscript within 1 week. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Jul 09 2020 11:59PM.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

------------------------------------------------------------

Requests from Editors:

1.Title: We appreciate your willingness to revise your title; please remove “on white older adults” from the title.

2.Data availability statement: The Data Availability Statement (DAS) requires revision. For each data source used in your study: if the data are owned by a third party but freely available upon request, please note this and state the owner of the data set and contact information for data requests (web or email address). Note that a study author cannot be the contact person for the data.

Please revise your statement to include the relevant contact information for requesting data access for the ADNI Study, 3-City Study and Whitehall II Study, and please note that the contact cannot be one of the authors of the manuscript.

Please also update the link for the Whitehall-II study, as it does not seem to work: https://www.ucl.ac.uk/epidemiology-health-care/research/epidemiology-and-publichealth/research/whitehall-ii

3. Abstract: Line 84: Please replace "subject" with participant, patient, individual, or person.

4. Abstract: Conclusions: Please revise the first sentence to better reflect on the study’s findings: “In this study, we found that AD was associated with APOE ε4 carrier status, with a higher OR than previously reported for associations between AD diagnosis and biomarker status.” or similar.

5. Author summary: “What did the researchers do and find?”: We suggest removing the word “strongly” from the third bullet point, and replacing with “significantly”

6. Author summary: “What do these findings mean?”: We suggest revising the first bullet point to: “Incorporating biomarkers for diagnosis of AD identified an association with APOE4 that is apparently greater than has been previously reported using clinical diagnosis of the disease.” or similar, as the objective of the study does not seem to be to compare associations between this and other studies.

7. Introduction: Line 163: Please replace "subject" with participant, patient, individual, or person.

8. Methods: Line 194: “Term” should be “terms”

9. Results: Line 317: Please revise this sentence to “The proportion of APOE ε4 carriers…”

10. Results: Line 366: Please revise this sentence to “There was no evidence that the age-related association of APOE ε4 differed by sex…”

11. Discussion: Line 434 and 438: Please spell out the word “two” rather than “2” here.

12. Discussion: Line 447: Should “biomarkers” be “biomarker” here?

13. Discussion: Line 452: Please revise to avoid implying causality“...AD is strongly dependent on age at diagnosis.” to “...AD is mediated by age at diagnosis.” In addition, would it be more appropriate to delete “at diagnosis” because your study only indirectly associated age at CSF study with time of diagnosis?

14. Discussion: Line 457 and 460: Why is “AD” in quotations here? Please remove the quotes if not necessary.

15. Discussion: Conclusions paragraph: Please revise the first sentence of the conclusions paragraph to better reflect your study’s findings. “This study supports an association between APOE ε4 and the risk of AD evaluated using biomarkers of AD neuropathology, and the results suggest that the strength of this association varies by age.”

16. Figure 1: Please change “allele” to “alleles”. Please change the X axis to read “Age at CSF testing” or similar. In the legend, please explain the dashed horizontal line at 50.

17. Figure 2: Please provide an X axis label.

18. Figure 6: Please include an X axis label indicating the values are OR and 95% CIs.

19. Supporting information Figure 1: In the title, there should be a space between CSF and AD.

20. Supplementary table 1: Is it possible to elaborate in the legend, or use a more specific term than “cut-off” as it isn’t quite clear exactly what it means.

Comments from Reviewers:

Reviewer #4: The authors have addressed my concerns and I now recommend publication

Peter Flom

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. 2020 Aug 20;17(8):e1003289. doi: 10.1371/journal.pmed.1003289.r006

Author response to Decision Letter 2

15 Jul 2020

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PLoS Med. doi: 10.1371/journal.pmed.1003289.r007

Decision Letter 3

Caitlin Moyer

22 Jul 2020

Dear Dr Dumurgier,

On behalf of my colleagues and the academic editor, Dr. Raquel C. Gardner, I am delighted to inform you that your manuscript entitled "Age and the association between Apolipoprotein E genotype and Alzheimer’s disease: a cerebrospinal fluid biomarker-based case-control study." (PMEDICINE-D-19-04199R3) has been accepted for publication in PLOS Medicine.

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PROFILE INFORMATION

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Thank you again for submitting the manuscript to PLOS Medicine. We look forward to publishing it.

Best wishes,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 STROBE Checklist. STROBE checklist for cohort studies.

STROBE, Strengthening the Reporting of Observational Studies in Epidemiology.

(DOCX)

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S1 Fig. Association of APOE genotype in CSF AD cases compared with population controls in a subsample with data on cardiovascular risk factors.

(TIF)

Click here for additional data file.^{(322.7KB, tif)}

S1 Table. Threshold levels used for defining abnormal values of CSF Aβ42, CSF tau, and CSF p-tau 181 in the memory centers that participated in the study.

Aβ, β-amyloid; CSF, cerebrospinal fluid; p-Tau 181, tau phosphorylated at threonine 181.

(DOCX)

Click here for additional data file.^{(16.5KB, docx)}

S2 Table. The odds ratios of AD in CSF AD cases compared with population controls before and after exclusion of the center with missing CSF phosphorylated tau.

AD, Alzheimer disease; CSF, cerebrospinal fluid.

(DOCX)

Click here for additional data file.^{(18.4KB, docx)}

S3 Table. Characteristics of the subsample used for the assessment of the association between APOE genotype and AD adjusted for cardiovascular risk factors.

AD, Alzheimer disease; APOE, apolipoprotein E.

(DOCX)

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S1 Text. Prospective analysis plan.

(DOCX)

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Data Availability Statement

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PERMALINK

Age and the association between apolipoprotein E genotype and Alzheimer disease: A cerebrospinal fluid biomarker–based case–control study

Hana Saddiki

Aurore Fayosse

Emmanuel Cognat

Séverine Sabia

Sebastiaan Engelborghs

David Wallon

Panagiotis Alexopoulos

Kaj Blennow

Henrik Zetterberg

Lucilla Parnetti

Inga Zerr

Peter Hermann

Audrey Gabelle

Mercè Boada

Adelina Orellana

Itziar de Rojas

Matthieu Lilamand

Maria Bjerke

Christine Van Broeckhoven

Lucia Farotti

Nicola Salvadori

Janine Diehl-Schmid

Timo Grimmer

Claire Hourregue

Aline Dugravot

Gaël Nicolas

Jean-Louis Laplanche

Sylvain Lehmann

Elodie Bouaziz-Amar

Jacques Hugon

Christophe Tzourio

Archana Singh-Manoux

Claire Paquet

Julien Dumurgier

Roles

Abstract

Background

Methods and findings

Conclusions

Author summary

Why was this study done?

What did the researchers do and find?

What do these findings mean?

Introduction

Methods

Patients with AD

Controls

Ethics statement

CSF biomarkers assessment

APOE genotyping

Covariates

Statistical analyses

Results

Table 1. Characteristics of the study population: CSF-determined AD cases, CSF-determined controls, and population controls.

Fig 1. Cumulative proportion of CSF AD cases as a function of age and APOE ε4 status.

Table 2. The ORs of AD according to APOE genotype.

Fig 2. APOE ε4 prevalence in CSF AD cases and population and CSF controls as a function of age group.

Fig 3. Population attributable fraction of APOE ε4 for AD by 5-year age group.

Fig 4. Association of APOE genotype in CSF-determined AD cases compared with population controls.

Post hoc analysis

Fig 5. Analysis of the AUC in function of age for at least one APOE ε4 carrying versus none to discriminate CSF AD from population controls.

Fig 6. Association between APOE ε4 carrying and AD stratified by center, using general population group as controls.

Table 3. The ORs of AD in CSF AD cases compared with population controls: multivariable logistic regression analysis.

Discussion

Strengths and limitations

Conclusions

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Louise Gaynor-Brook

Roles

Author response to Decision Letter 0

Decision Letter 1

Caitlin Moyer