The Israel Registry for Alzheimer’s Prevention (IRAP) Study: Design and Baseline Characteristics

Abstract

Background:

Family history of Alzheimer’s disease (AD) is associated with increased dementia-risk.

Objective:

The Israel Registry for Alzheimer’s Prevention (IRAP) is a prospective longitudinal study of asymptomatic middle-aged offspring of AD patients (family history positive; FH+) and controls (whose parents have aged without dementia; FH–) aimed to unravel the contribution of midlife factors to future cognitive decline and dementia. Here we present the study design, methods, and baseline characteristics.

Methods:

Participants are members of the Maccabi Health Services, 40–65 years of age, with exquisitely detailed laboratory, medical diagnoses and medication data available in the Maccabi electronic medical records since 1998. Data collected through IRAP include genetic, sociodemographic, cognitive, brain imaging, lifestyle, and health-related characteristics at baseline and every three years thereafter.

Results:

Currently IRAP has 483 participants [mean age 54.95 (SD = 6.68) and 64.8% (n = 313) women], 379 (78.5%) FH+, and 104 (21.5%) FH–. Compared to FH–, FH+ participants were younger (p = 0.011), more often males (p = 0.003) and with a higher prevalence of the APOE E4 allele carriers (32.9% FH+, 22% FH–; p = 0.040). Adjusting for age, sex, and education, FH+ performed worse than FH–in global cognition (p = 0.027) and episodic memory (p = 0.022).

Conclusion:

Lower cognitive scores and higher rates of the APOE E4 allele carriers among the FH+ group suggest that FH ascertainment is good. The combination of long-term historical health-related data available through Maccabi with the multifactorial information collected through IRAP will potentially enable development of dementia-prevention strategies already in midlife, a critical period in terms of risk factor exposure and initiation of AD-neuropathology.

Keywords

Alzheimer’s disease family history offspring risk factors

INTRODUCTION

Dementia constitutes a significant public health problem with 5–10% of people aged ≥65 suffering from this disorder and prevalence doubling every 5 years, reaching rates of 50% or higher at age ≥85 [1]. In recognition of the expected substantial increase in dementia prevalence in the decades to come, the World Health Organization (WHO) and the G8 called for strategies aimed at dementia prevention [2 –4]. Implementation of such strategies requires identification of populations at high risk [5] and understanding of the targetable mechanisms underlying dementia.

Late onset Alzheimer’s disease (LOAD) is the most common clinical form of dementia [6]. Current treatments approved for LOAD have marginal efficacy, and do not affect disease progression [7]. Numerous compounds, including those targeting amyloid plaques [8, 9] and neurofibrillary tangles [10], failed in clinical trials in symptomatic as well as in asymptomatic patients [11]. Several explanations have been suggested for these failures [12], including irrelevance of the amyloid hypothesis in LOAD, initiation of treatment at advanced stages of neuropathology, or the multifactorial nature of the disease [13], prevention of which requires treatments targeting several factors.

In addition to aging, the timing of clinical ex-pression of dementia has been associated with several factors, part of which are modifiable: genetic susceptibility; socio-demographic (e.g., education); medical (e.g., diabetes [14], hypertension, hypercholesterolemia [15]); psychological (e.g., depression [16], loneliness [17]); lifestyle (e.g., nutrition, physical and cognitive activities), and environmental (e.g., brain trauma [18]). Risk factor modification has been stipulated to have the potential to reduce approximately one third of AD dementia cases [4, 19]. Accordingly, studies implementing multi-domain risk factor modification demonstrated reduced risk for cognitive decline and dementia in specific high risk sub-populations [20, 21], i.e., those with a positive amyloid PET scan [20] or those with untreated hypertension [21], even in the presence of the Apolipoprotein E4 (APOE E4) allele, a well-established genetic risk factor for AD [22]. These results suggest that risk factor modification may have a beneficial effect in dementia prevention; however, this intervention should probably be personalized in terms of target populations, timing, and intensity.

The accumulation of AD-related brain pathology decades prior to clinical expression of LOAD [23 –25], combined with a consistently high dementia risk in late life for those who were exposed to lifestyle, metabolic, and cardiovascular risk factors for dementia in midlife [26], imply that midlife is a critical window of opportunities for prevention of LOAD.

Family history of AD (FH+) in a first degree relative is a well-known risk factor for AD, encapsulating genetic and environmental risk loads [27 –29]. Heritability of AD is extremely high, accounting for at least 53% [30, 31] of the cases. Offspring of LOAD patients are at particularly high risk for developing the disease [32 –35]. Although genetics are significant contributors to higher AD risk in those with FH+ [36, 37], the correlations between age at onset (AAO) of LOAD in parents and offspring [38] are modest compared to that observed in families with autosomal dominant forms of AD [39], suggesting that in addition to genetic predisposition, other factors may be involved in AAO of AD in individuals with FH. This assumption is supported by the associations of AD AAO with education [40], midlife insulin resistance [41], diabetes [42], lower regional brain volume [43], late life hypertension [38], and participation in cognitively stimulating activities [44]. Even the impact of the APOE E4 allele is affected by cardiovascular [45] and lifestyle [46] variables. Therefore, longitudinal investigations of middle-aged asymptomatic offspring of LOAD patients provides an opportunity to assess the interplay of genetic, medical, lifestyle, and environmental factors in this critical period, and could potentially lead to development of strategies for prevention of dementia-related neuropathology and cognitive decline.

We have established the Israel Registry for Alz-heimer Prevention (IRAP) study, aimed at examining the effect of multiple factors [sociodemographic, health-related (vascular, metabolic), lifestyle, neuroimaging, laboratory, and genetic] on cognitive functioning and decline in middle-aged (age range 40–65 years) offspring of LOAD patients, compared to controls (middle-aged offspring whose parents have aged (father ≥70 and mother ≥75 years old) without dementia. Here, we describe the design of the study, and the baseline characteristics of the first 513 participants recruited.

METHODS

The IRAP study is a collaboration between the Sheba Medical Center, Israel, and the Maccabi Healthcare Services (MHS), the second largest health maintenance organization in Israel, insuring a representative cross-section of two million residents. Comprehensive and complete clinical data have been collected for all MHS members in central databases since 1998. Each member has a unique and permanent identifier which is linked to all clinical and administrative data including medication purchases and laboratory results. There is minimal loss to contact and prompt death notification. Medical, laboratory, and pharmacy data are available for all IRAP participants through MHS datasets.

Participants

The study was approved by the Sheba Medical Center and MHS institutional review board (IRB) committees and all participants signed informed consent. Recruitment started in 2013.

Eligibility criteria

MHS membership, age at enrollment 40–65 years, fluency in Hebrew, with (FH+) or without (FH–) parental history of AD. FH–is defined as an offspring of a father who passed the age of 70 and a mother who passed the age of 75, who are currently (or were at time of death) cognitively normal. This control group definition is consistent with that of similar cohort studies, e.g., the Wisconsin Registry of Alzheimer’s Prevention (WRAP) [47], the Adult Children Study [48], and other cohorts [49].

Ideally, the ultimate controls would be offspring of people who have reached very old age without dementia as they would probably carry protective genetic and environmental factors [50]. However, this would have led to a control group that differs substantially from the group of offspring of people with dementia, primarily in terms of age and cardiovascular profile [51]. We therefore remained consistent with the criteria used in the above-mentioned studies. The main source of participant recruitment is through advertisements in the home page of the MHS website and participants’ word of mouth. Of 1,418 individuals who approached the study team, 905 were found ineligible for the study [260 were no longer interested in participation after receiving explanations about the study, 176 reported that they were not MHS members, 124 reported, prior to Dementia Questionnaire (DQ) administration, that their parents’ dementia history was not compatible with inclusion/exclusion criteria (e.g., stroke), in 81 cases individuals’ age or medical profile was not compatible with inclusion criteria, and 100 were lost to contact, leaving 677 participants who underwent the DQ. Of these, in 164, the DQ was incompatible with inclusion criteria’] (See Supplementary Figure 1 for details), leaving 513 active participants. Originally, siblings were included in the study; however, later on we decided to exclude them as their data may substantively confound results, especially of analyses including genetic components. We therefore stopped recruiting siblings and excluded those already recruited (n = 30) leaving 483 active participants in the study.

Determination of parental AD status

Individuals who approach the study team undergo initial questioning about their age, MHS membership, and parental dementia. Then, medical records of proband parents of potential participants are provided to the study team and a DQ (details below) is administered telephonically prior to invitation of potential participants to the study site. All the medical history and diagnostic workup available is reviewed together with the DQ in order to reach a probable AD diagnosis (according to NINCDS-ADRDA criteria). Offspring of probands with partial information about dementia type or with dementia other than AD, are excluded from the study.

Normal cognition of the parents of FH–control participants is determined similarly to the AD pro-bands, i.e., through medical charts and a normal DQ.

Dementia Questionnaire

The DQ is a validated, informant-based instrument, to determine the likely presence of AD in parents of potential study volunteers [52 –54]. The DQ obtains information similar to that obtained from a medical records’ review using DSM-IV criteria. During DQ administration, offspring are asked about the type, course, and progression of dementia-related symptoms and about the presence or absence of co-morbid conditions that could explain or contribute to the symptoms in their parents. When administered to close family members, diagnostic classifications based on the DQ show a high sensitivity and specificity as well as a high degree of concordance with the outcomes of clinical and neuropathological diagnostic evaluations [52 –54]. The results are reviewed by a study physician prior to the offspring potential enrollment in the study.

FH+ and FH–individuals who are willing to participate in the study are invited to the Sheba Medical Center, where, after signing an informed consent form, they are recruited to the study.

Core IRAP assessments

All assessments are administered in Hebrew. Each IRAP participant completes an entry core assessment that includes demographics (age, sex, education, ethnic origin of parents, i.e., Azhkenazi versus non-Ashkenazi), vital signs (pulse and respiratory rates, blood pressure, and oximetry) and anthropometric measurements, neuropsychological testing, laboratory testing, and a detailed health and lifestyle history. Assessments are performed at baseline and at each follow visit, approximately 3 years apart.

Health history, psychological, and lifestyle assessments

Through the IRAP study, we collect information about demographic characteristics, past and current medical history, use of prescribed and over the counter (OTC) medications, family history of dementing disorders, risk factors for AD (e.g., head trauma), lifestyle (e.g., physical activity-frequency and graded level of exercise, smoking, nutritional habits using the Hebrew-modified version of the Harvard Food Frequency Questionnaire (FFQ) [55] and frequency of participation in mentally stimulating activities). A questionnaire examining social stressors (e.g., death of a partner, serious illness of a spouse, major financial problems, conflicts with children or grandchildren, etc.) to which participants have been exposed to in the year preceding IRAP assessments is administered at each visit. If participants answer that they have been exposed to such a stressor, they are further required to rate how stressful was this event for them (i.e., mildly stressful, stressful, very stressful). We also administer the Memory Functioning Questionnaire for assessment of Memory Complaints in Adulthood and Old Age [56] which comprehensively measure subjective cognitive impairment. This questionnaire assesses subjective memory problems, their functional consequences, and use of cognitive compensation strategies. Depressive symptoms are assessed using the Center for Epidemiologic Studies Depression scale (CES-D) [57] and anxiety symptoms are examined using the Beck Anxiety Inventory (BAI) [58]. Data on personality traits, number of languages spoken and sleep quality are also collected. The Hebrew abridged version of the Zarit Burden Interview [59] is administered to assess the burden experienced by participants due to caregiving for a parent with dementia. Additional questionnaires assess occupational history, and learning disabilities in participants and their relatives.

Heart rate, blood pressure, and anthropometric measures

Heart rate, blood pressure and anthropometric measures are obtained by the study staff according to the Atherosclerosis Risk in Communities Study (ARIC) protocols [60]. Participants are instructed to sit for 10 minutes, and then have blood pressure readings obtained.

Anthropometric variables include body mass index (BMI) and waist-hip ratio (WHR). BMI is calculated as weight in kg divided by height square, in meters. Subjects’ weight and height are measured without shoes. Weight is measured with an electronic scale. Height is measured to the nearest centimeter using a wall-mounted ruler. Waist and hip circumferences are measured with an anthropometric tape to the nearest centimeter with the subject standing. Further details on blood pressure, waist and hip circumference measurements are available in the Supplementary Material.

Laboratory testing

Fasting blood samples (12-h overnight fast) for insulin levels are collected following vital signs’ measurement and processed in the Sheba Medical Center main laboratory. Samples are collected on the day of cognitive testing. Serum samples are kept in –80°C for future laboratory assessments of interest.

APOE4 genotyping

Blood samples are collected for APOE genotype and for future genetic and genomic studies. DNA is extracted and frozen in –80°C. APOE status is determined based on rs429358 and rs7412 SNPs genotypes [61] at LGC company, UK, using Kompetitive allele specific PCR (KASP) technology [62].

Neuropsychological assessment

IRAP participants complete the Mini-Mental State Examination (MMSE) and a comprehensive neuropsychological battery at baseline and at all follow up assessments. This battery includes tests assessing multiple cognitive functions. Factor analysis summarized the neuropsychological measures into four domains: 1) episodic memory [Rey Auditory Verbal Learning Test (RAVLT) immediate recall (sum of lists 1–5), RAVLT delayed recall (list 8), and RVLT recognition]; 2) executive functions (Trails making test A, Trails making test B, WAIS-III-Hebrew Block design, and Digit Symbol); 3) working memory and attention (digit span forward, digit span backward, and letter number sequencing), and 4) language (WAIS-III-Hebrew similarities, WAIS-III-Hebrew vocabulary, and the average of phonemic and animal fluency). The neuropsychological tests’ scores were transformed into Z scores (reversing scores representing time—Trails A and Trails B—so high scores represented good cognition) and averaged for each domain. An overall cognition measure averages the scores of all 4 domains.

Informant reported activities of daily living (ADL), instrumental activities of daily living (IADL), and Clinical Dementia Rating Scale (CDR) [63]

Starting at the first follow up visit, participants’ functional capacity in basic and instrumental ADL and the CDR, aimed to assess cognitive functional abilities, are administered to informants. These assessments are not performed at baseline due to participants’ relatively young age. Further details on these questionnaires is available in the Supplementary Material.

Clinical diagnoses of AD will follow the recommendations from the National Institute of Aging and Alzheimer’s Association Work Groups using available clinical and longitudinal cognitive data. All clinical diagnoses of AD will be made at the weekly consensus conferences by neurologists, geriatric psychiatrists, and neuropsychologists, with at least two types of expertise present in the conference.

Parental dementia status in the control group

At each follow up visit, the DQ will be administered to control participants regarding their living parents, to assess whether there was a change in their parents’ dementia status.

Data from MHS electronic patient records

In addition to the information collected as part of the IRAP study assessments, for each participant, relevant health history (including past and present medical diagnoses, laboratory values and medications) as registered in MHS since 1998, are provided from MHS. This includes data on diagnoses of heart disease, hypertension, hypercholesterolemia, diabetes, stroke, any neurological disorder, depression, anxiety, and panic disorder. Additionally, data on participants’ laboratory values are available for creatinine, C-reactive protein, total cholesterol, LDL and HDL cholesterol, glucose, Hemoglobin A1c (HbgA1c), insulin, triglycerides, thyroid stimulating hormone, albumin, vitamin B12, folic acid, vitamin D, and BMI.

Imaging

A subsample of participants from the IRAP study who complete baseline visit is randomly scanned for brain magnetic resonance imaging (MRI) and positron emission tomography-computed tomography (PET-CT) for amyloid-β (Aβ) brain deposition.

MRI acquisition

MRI scans are acquired on a 3 Tesla whole body MRI system (GE Signa HDxt, version 16 VO2) equipped with an eight-channel radio frequency head coil.

The MRI scanning session included both anatomical and functional imaging. Structural sequences include, T1-weighted imaging, T2-weighted-fluid-attenuated inversion recovery (T2-FLAIR), and diffusion weighted imaging (DWI). Functional sequences include a functional MRI (fMRI) scan during an n-back working memory task, and a resting-state functional connectivity scan. Further details of structural and functional MRI image acquisition are available in the Supplementary Material.

F18 Flutemetamol Aβ PET radiochemistry and acquisition

F18 Flutemetamol is synthesized at the Hadassah Cyclotron Radiochemistry Unit using previously published protocol. PET scans are performed at Sheba medical center on a Philips Vereos PET/CT scanner in 3D acquisition mode. A low-dose CT scan is performed for attenuation correction prior to all scans. Participants are injected with 4–5 millicuries (mCi) of [F18] Flutemetamol Vizamyl TM (GE Healthcare). Image acquisition begins 90-min post-injection and takes 20 min. Iterative reconstruction with weighted attenuation scatter is performed with a slice thickness of 2 mm, matrix size of 128×128 with pixel sizes of 2×2 mm.

F18 Flutemetamol Aβ PET preprocessing and interpretation

PET frames are co-registered onto their corresponding native space T1 weighted MRIs by SPM12. Standardized uptake value ratio (SUVR) maps are calculated using whole cerebellum as reference region as previously described [64]. Global cortical uptake value is calculated based on the weighted uptake in the frontal, temporal, parietal and posterior cingulate cortex. This value is then used as a measure of Aβ “cortical burden”.

Visual reads are performed following the official guidelines [65]. Readers are blinded to SUVR quantification and to all clinical information except age and sex.

Further information on Flutemetamol Aβ PET interpretation and preprocessing is available in the Supplementary Material.

Statistical analyses

For descriptive purposes, comparisons between FH groups (FH+∖FH–) in demographic, lifestyle, medical conditions variables and laboratory values, were done using χ² for categorical variables, and independent t-tests for continuous variables. For comparisons between the FH groups in overall cognition and the four cognitive domains (episodic memory, working memory and attention, executive functions, and language), independent t-tests were used (Model 1). We then adjusted for age, sex, and education using ANCOVAs (Model 2). Raw scores [mean (standard deviation (SD)] of each cognitive test are presented in Supplementary Table 1. Analyses were done with SPSS v. 24.

RESULTS

Four hundred and eighty-three IRAP participants [mean age 54.95 (SD = 6.68) and 64.8% (n = 313) women] were included in the analysis. Of these, 379 (78.5% of the IRAP sample) were FH+, and 104 (21.5%) were FH–. Of the FH+, 252 (66.5%) had maternal, 116 (30.6%) had paternal, and 11 (2.9%) had bi-parental AD family history.

Demographic, health, and lifestyle characteristics of IRAP sample by AD family history

Compared to FH–, the FH+ participants were younger (p = 0.011), more often males (p = 0.003), though both groups were female predominant (Table 1). FH groups did not differ in the prevalence of different APOE genotypes (p = 0.252) (Table 2); however, FH+ had almost 50% higher prevalence of the APOE E4 allele carriers compared to FH–(p = 0.040) (Table 1). The groups did not differ in years of education (Table 1), lifestyle variables, rates of subjective memory complaints or depression scores (Table 3). The mean CES-D score was below that considered to be potentially clinically significant in both groups (Table 3). Lastly, FH groups did not differ in rates of medical diagnoses or laboratory values (Table 4).

Table 1

Demographic characteristics by FH group

Characteristic	FH+ (n = 379)	FH–(n = 104)	p
Demographic variable
Age, mean (SD)	54.55 (6.76)	56.423 (6.19)	0.011
Sex (% female)	233 (61.5%)	80 (76.9%)	0.003
Years of Education	16.39 (3.01)	16.80 (3.12)	0.220
APOE E4 carriers (%)	104 (32.9%)	22 (22%)	0.040
Ashkenazi	248 (62.6%)	59 (62.8%)	0.980

FH, family history of AD; SD, standard deviation.

Table 2

APOE genotype frequencies by family history

APOE genotype	FH+ N (%)	FH–N (%)	N (%)
E2/E2	1 (0.3%)	–	1 (0.2%)
E2/E4	10 (3.2%)	2 (2%)	12 (2.9%)
E2/E3	21 (6.6%)	12 (12%)	33 (7.9%)
E3/E3	190 (60.1%)	66 (66%)	256 (61.5%)
E3/E4	87 (27.5%)	19 (19%)	106 (25.5%)
E4/E4	7 (2.2%)	1 (1%)	8 (1.9%)
Total	316 (100%)	100 (100%)	416 (100%)

APOE, Apolipoprotein E; FH, family history of AD.

Table 3

Lifestyle and psychological characteristics by FH group

Characteristic	FH+ (n = 379)	FH–(n = 104)	p
Exercise frequency per month^a [mean (SD)]	3.04(1.311)	3.23 (1.16)	0.182
Reported consumption of alcoholic beverage in past month (% yes)	168 (44.7%)	47 (45.2%)	0.757
Reported smoking in the past month (% yes)	45 (12%)	11 (10.6%)	0.154
Reported subjective memory complaints (% yes)	230 (58.5%)	63 (60.6%)	0.602
Depression rating (CES-D)	11.01 (7.87)	9.83 (7.415)	0.179

FH, Family history of AD; CES-D, Center for Epidemiologic Studies Depression Scale; SD, standard deviation. ^aExercise frequency per month: 1 = never, 2≤ once per month, 3 = 1 to 4 times per month, 4≥ once per week.

Table 4

Medical characteristics by FH group

Characteristic	FH+	FH–	p
Medical diagnoses
Heart disease (%)	9 (2.4%)	3 (2.9%)	0.771
Hypertension (%)	114 (32.7%)	12 (25.5%)	0.324
Hyperlipidemia (%)	123 (32.8%)	32 (31.1%)	0.936
Type 2 Diabetes (%)	45 (12.9%)	9 (19.1%)	0.241
Stroke (%)	9 (2.4%)	1 (1%)	0.579
Depression (%)	28 (7.5%)	5 (4.9 %)	0.564
Anxiety or panic disorder (%)	26 (6.9%)	10 (9.7%)	0.344
Laboratory values/vitals (fasting)
Creatinine (mg/dl)	0.87 (0.16)	0.86 (0.19)	0.581
C-Reactive protein (mg/l)	2.92 (3.51)	3.44 (3.69)	0.223
Total cholesterol (mg/dl)	197.72 (27.07)	193.59(27.72)	0.352
LDL cholesterol (mg/dl)	119.96 (23.17)	114.18 (27.11)	0.135
HDL cholesterol (mg/dl)	52.91 (12.26)	53.94 (13.05)	0.610
Glucose (mg/dl)	96.70 (16.14)	95.93 (14.41)	0.770
Hb A1c (%)	5.76 (0.84)	5.70 (0.47)	0.740
Insulin (mU/l)	8.76 (6.49)	8.92 (7.60)	0.841
Triglyceride (mg/dl)	121.62 (52.49)	120.97 (62.85)	0.941
TSH (mU/L)	2.41 (1.37)	2.09 (1.12)	0.142
Albumin g/dl	4.33 (0.23)	4.29 (0.18)	0.302
Vitamin B12 (pg/ml)	392.26 (209.06)	382.25 (184.14)	0.682
Folic acid (ng/ml)	12.63 (6.07)	12.066 (4.96)	0.439
Vitamin D (ng/ml)	22.60 (8.44)	24.05 (8.11)	0.140
Body mass index (kg/m²)	26.23 (4.30)	26.43 (4.68)	0.693
Diastolic blood pressure (mmHg)	75.52 (6.08)	74.21 (6.68)	0.190
Systolic blood pressure (mmHg)	120.22 (11.11)	119.10 (10.6)	0.531

FH, family history of AD; LDL, low density lipoprotein; HDL, high density lipoprotein; HbA1c, hemoglobin A1c; TSH, thyroid stimulating hormone.

Cognitive performance of IRAP sample by AD family history

The scores [mean (SD)] of all cognitive tests are presented in Supplementary Table 1. In an unadjusted analysis, FH+ performed worse than FH–in overall cognition (p = 0.048) and episodic memory (p = 0.009) (Table 5, Model 1). After adjustment for age, sex, and education, overall cognition (p = 0.027) and episodic memory (p = 0.022) remained lower in FH+ compared to FH–(Table 5, Model 2).

Table 5

Cognitive factors by AD family history (z scores)

Model	Cognitive factor	FH+ (n = 379)	FH–(n = 104)	F	p
I: Unadjusted	Overall cognition	–0.015 (0.51)	0.096 (0.51)	3.916	0.048
	Episodic memory	–0.053 (0.87)	0.198 (0.87)	6.793	0.009
	Working memory and attention	0.008 (0.82)	0.024 (0.81)	0.032	0.858
	Language	–0.007 (0.76)	0.115 (0.76)	2.099	0.148
	Executive functions	–0.009 (0.49)	0.048 (0.48)	1.150	0.284
II: Adjusted for age, sex, and education	Overall cognition	–0.017 (0.47)	0.101 (0.48)	4.927	0.027
	Episodic memory	–0.043 (0.80)	0.163 (0.81)	5.307	0.022
	Working memory and attention	–0.005 (0.80)	0.069 (0.80)	0.682	0.409
	Language	–0.005 (0.74)	0.106 (0.74)	1.782	0.183
	Executive functions	–0.014 (0.45)	0.068 (0.45)	2.698	0.101

FH, family history of AD.

DISCUSSION

The IRAP study joins ongoing studies examining longitudinally offspring of AD patients. Among these are the WRAP study [47], the Adult Children Study at the Knight Alzheimer’s Disease Research Center (ADRC) at Washington University in Saint Louis [66] and the Health Brain Project [67]. Our study enables characterization of participants beyond cognitive, brain imaging, genetic and lifestyle factors by having for each participant, their detailed health history since 1998 from MHS medical records, which more accurately reflect the natural dynamics of health over time. Availability of such data together with the wealth of data collected through the IRAP provides an opportunity to develop more accurate personalized dementia prevention strategies in the future.

FH+ IRAP participants were younger and more often male compared to FH–; however, their poorer performance in the cognitive domains of episodic memory and global cognition remained significant after adjusting for these factors.

Family history of AD, even beyond first degree relatives, is robustly associated with increased risk for AD [68, 69]. Consistent with previous studies in similar populations, we found poorer cognitive function in FH+ IRAP participants, specifically in the domain of episodic memory, the first cognitive domain to be affected by AD [70, 71]. Given that our initial analyses were performed on cross-sectional data, the longitudinal component of IRAP is expected to shed light on the trajectories of cognitive decline in these asymptomatic high-risk individuals.

Previous studies have demonstrated that at least one APOE E4 allele is found in 56%, and two alleles in 11% of AD cases [69, 72], and that the frequency of the allele in adult children of AD patients, exceeds that of the general population, which generally ranges between 15 to 20% [73]. Thus, the significantly higher rates of the APOE E4 allele carriers among FH+ IRAP participants are in line with earlier reports, though we observed somewhat lower rates compared to the WRAP study (45% in FH+ versus 19% in FH [74]). APOE E4 frequency was 36.8% in AD patients and 8.2% among controls in a study of Hispano-Americans [75], and 4.5% in cases and 3.5% in controls [76] in a study of the Israeli Arab population. The variability in the frequency of this allele can be attributed to geographical and ethnic differences, with the highest frequency rates reported in Northern Europe (61.3%) compared to southern Europe (40.5%) or Asia (41.9%) [72].

The younger age of the FH+, has also been observed by some [77, 78] (e.g., the WRAP study [77]), but not all [79, 80] studies of AD offspring (e.g., Knight ADRC [81]). This observation could potentially be related to their commitment to participation in research due to personal experience, referral to the study from clinics where their parents are treated or may arise from their awareness to change in their own cognitive functions. The latter may be possible given that we found worse performance in episodic memory among FH+, and especially in light of the awareness of the devastating ramifications of AD that research participants will have observed in their parents. However, it is important to note that objective measures of subjective cognitive complaints did not differ between FH groups in the IRAP study.

In accordance with previous studies [78 , 82], a higher rate of women participated in the IRAP study, especially in the FH–group. Caregivers of dementia patients are usually women [83], commonly daughters [83 –85] and daughters-in-law [86]. Moreover, the negative impact of AD on family members’ health, well-being, and working hours [86] is more prominent in women [87], potentially explaining female predominance in the FH+ group. The female predominance in the FH–group may be explained by the higher availability of women whose’ retirement age in Israel is earlier compared to that of men (62 versus 67) and potentially by high rates of daughters in law committed to the treatment of their parents in law who suffer from dementia [86].

In IRAP FH+ participants, maternal AD was present in the majority of cases (66.5%), consistent with the higher risk for AD in women [33]. Maternal family history appears to confer increased risk for dementia compared to paternal history, as well as increased susceptibility of AD-related brain areas to neurodegeneration, as evidenced by prominent regional atrophy and hypometabolism among cognitively unimpaired individuals with maternal AD compared to individuals with paternal AD or no parental history of AD [88–90]. It will be important to follow the offspring of AD-affected mothers in IRAP, to determine age of AD dementia onset, as well as determine if maternal family history confers a faster progression of the AD-related disease process.

The IRAP study has some limitations. In Israel, 12 years of education is compulsory by law. Thus, IRAP participants are highly educated, limiting the generalization of the results to less educated populations. Additionally, adjudication of dementia status in the probands is done based on medical charts and the DQ rather than a direct clinical assessment or neuropathology-based diagnosis. Although not ideal, the DQ has good sensitivity and specificity compared to neuropathology [52 –54] which combined with the probands’ medical chart, provides good diagnostic accuracy. Moreover, the lower cognitive scores and the higher rates of APOE E4 carriers among the FH+ group suggest that the ascertainment of AD in the probands is good. That said, we cannot rule out that probands of some IRAP cases may have had other types of dementia. Although the study does not have any exclusion criteria by race, ethnicity, or religion, the eligibility criteria requiring Hebrew speaking and living in the Tel Aviv area is a limitation as the sample is not representative of the whole Israeli population.

The IRAP study has numerous strengths. IRAP participants are followed longitudinally allowing examination of socio-demographic, genetic, brain imaging, health, and lifestyle-related factors contributing to their cognitive trajectories. In addition to the wealth of data collected through IRAP assessments, the availability of long term medical and laboratory data through MHS, provides an exceptional opportunity to identify patterns in these factors that contribute to increases (or decreases) in dementia risk and their interaction with other genetic and non-genetic characteristics.

Footnotes

ACKNOWLEDGMENTS

We thank the Bader Philanthropies, The LeRoy Schecter Foundation, and Dr. Marina Nissim for their kind grants that support the IRAP study.

Authors’ disclosures available online ().

The supplementary material is available in the electronic version of this article: .

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