Odor identification impairment in carriers of ApoE-ɛ4 is independent of clinical dementia

Neurobiology of Aging 31 (2010) 567–577

Odor identification impairment in carriers of ApoE-ε4 is independent of clinical dementia Jonas K. Olofsson a,b,c,∗ , Steven Nordin a,d , Stefan Wiens b,c , Margareta Hedner b,c , Lars-Göran Nilsson b,c , Maria Larsson b,c a Department of Psychology, Umeå University, Umeå, Sweden Department of Psychology, Stockholm University, Stockholm, Sweden c Stockholm Brain Institute, Stockholm, Sweden Department of Psychology, San Diego State University, San Diego, USA

b d

Received 24 October 2007; received in revised form 7 May 2008; accepted 20 May 2008 Available online 10 July 2008

Abstract The ApoE gene is expressed in olfactory brain structures and is believed to play a role in neuronal regenerative processes as well as in development of Alzheimer’s disease (AD), the most common form of dementia. The ε4 allele has been reported to be associated with compromised odor identification ability in the elderly, and this deficit has been interpreted as a sign of pre-diagnostic AD. However, because it has not been demonstrated that the relationship between the ε4 allele and odor identification is mediated by dementia, it is possible that the ε4 allele may have an effect on odor identification over and above any effects of dementia. The present study investigated effects of ApoE-status on odor identification in a large, population-based sample (n = 1236) of adults (45–80 years), who were assessed for dementia at time of testing and 5 years later. The results showed that the ε4 allele was associated with an odor identification deficit among elderly participants (75–80). Critically, this effect remained after current and pre-diagnostic dementia, vocabulary, global cognitive status and health variables were partialled out. The present results suggest that the ApoE gene plays a role in olfactory functioning that is independent of dementia conversion within 5 years. © 2008 Elsevier Inc. All rights reserved. Keywords: ApoE; Odor identification; Olfaction; Aging; Alzheimer’s disease

1. Introduction Aging is associated with decreases in human olfactory abilities. This age-related impairment is observed across several olfactory domains, including detection sensitivity (Schiffman et al., 1976; Stevens and Cain, 1987), quality discrimination (Schiffman and Pasternak, 1979), and in more cognitively driven tasks such as odor identification (Doty et al., 1984; Larsson et al., 2004; Ship et al., 1996; Wysocki and Gilbert, 1989), odor recognition memory (Larsson and Bäckman, 1997, 1998a,b), and odor source memory (Gilbert ∗ Corresponding author. Present address: Department of Psychology, Stockholm University, SE-106 91 Stockholm, Sweden. Tel.: +46 8 163834; fax: +46 8 159342. E-mail address: [email protected] (J.K. Olofsson).

0197-4580/$ – see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.neurobiolaging.2008.05.019

et al., 2006). Evidence also suggests large individual differences in olfactory function in old age. The mechanisms are multi-factorial and include demographic (Ship et al., 1996; Ship and Weiffenbach, 1993), environmental (Corwin et al., 1995), cognitive (Larsson et al., 2004, 2005), and various health-related factors (Schiffman, 1983a,b). Research suggests that the human apolipoprotein E (ApoE) gene might affect age-related changes in olfactory function. ApoE is a plasma protein that is involved in lipid transport (Mahley, 1988). The gene for ApoE is located on chromosome 19 and carries three alleles; ε2, ε3, and ε4. The ApoE gene is expressed in the central nervous system, including the olfactory bulb and the olfactory epithelium (Nathan et al., 2007; Struble et al., 1999; Yamagishi et al., 1998), and has been proposed to play a role in lipid recycling during neuronal regenerative processes (Masliah et al., 1996; Nathan et al.,

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2005, 2007). However, evidence is sparse regarding the influence of ApoE status on human olfactory function and its precise neurobiological function. An early study indicated that odor identification ability was impaired in a small sample of non-demented but cognitively impaired elderly ε4-carriers (n = 7) relative to a cognitively intact control group (Murphy et al., 1998). A recent study, however, failed to replicate this association in a cognitively intact sample of ε4-carriers versus controls (Handley et al., 2006). Also, when tested for episodic odor memory function, elderly ε4-carriers produced more false positive errors than controls, but no impairment was reported in overall odor recognition performance (Gilbert and Murphy, 2004a,b). Longitudinal data suggest that elderly ε4-carriers exhibit a larger performance decline in odor identification than controls (Calhoun-Haney and Murphy, 2005). Taken together, the findings suggest that elderly ε4-carriers might have olfactory impairments. The ε4 allele is strongly associated with sporadic Alzheimer’s disease (AD; Corder et al., 1993; Poirier et al., 1993). In AD patients, neuropathological alterations are found in olfactory brain regions that include the olfactory bulb (Esiri and Wilcock, 1984; Kovacs et al., 1999, 2001) and, consequently, AD patients show severe olfactory deficits (Doty et al., 1986, 1987; Larsson et al., 1999; Morgan and Murphy, 2002; Murphy et al., 1999; Nordin et al., 1997; Nordin and Murphy, 1998; Serby, 1986). Furthermore, in the pre-diagnostic phase of AD, cognitive function decreases substantially during the years preceding the diagnosis (Bäckman et al., 2005), and olfactory impairments have been observed in cognitively impaired elderly who received an AD diagnosis within the following 2 years (Bacon et al., 1998; Tabert et al., 2005). The ApoE-ε4 allele in combination with olfactory impairment is associated with larger subsequent cognitive decline over a 2-year interval, suggesting that odor identification deficits in ε4-carriers may be a marker for an impending dementia disease (Graves et al., 1999). Because ε4-carriers develop AD earlier and more likely than non-carriers, follow-up assessment of dementia is pivotal to investigate whether an olfactory deficit in ε4-carriers is mediated by an influence of pre-diagnostic dementia on olfactory function, or whether an olfactory deficit can occur over and above the effect of dementia (Bacon et al., 1998). Hence, if the ApoE-ε4 is associated with olfactory impairment because of processes leading to a dementia diagnosis the effect would be attenuated by controlling for effects of future dementia diagnoses. However, if the ApoE-ε4 is associated with olfactory impairment by mechanisms that are not strongly related to future dementia diagnoses, the effect of ApoEε4 would remain after effects of dementia are controlled for. The main aim of the present study was to investigate the potential differences in odor identification ability related to the ε4 allele in a population-based sample of adults for which health factors, cognitive ability, and dementia status were controlled statistically. Most previous studies on olfactory ability and the ε4 allele did not assess dementia

prospectively (Murphy et al., 1998; Handley et al., 2006). The present study improves on previous study designs by employing a 5-year follow-up interval to address the possible effect of pre-diagnostic dementia on the association between the presence of ApoE-ε4 and olfactory ability. Also, we evaluated whether potential deficits in odor identification ability associated with ApoE status are olfactory specific or may be linked to deficits in semantic memory (i.e. vocabulary) or general cognitive status. As previous work on ApoE and olfactory function typically lack adequate control tasks, this issue was of particular interest. The ability to identify odors draws on both sensory (i.e. detection and discrimination) and cognitive abilities. With regard to the latter, vocabulary correlates positively with odor identification performance, and partially predicts the aging-related deficit in odor identification ability (Larsson et al., 2004). Hence, olfactory identification deficits can be evaluated against a test of vocabulary to assess whether a deficit is odor-specific or reflects a general impairment in semantic memory (Handley et al., 2006; Larsson et al., 2004, 2006; Murphy et al., 1998). Previous studies have not investigated the role of age as a potential moderator of the association between ApoE-ε4 and olfactory ability. Instead, these studies compared elderly groups of ε4-carriers and non-carriers (Gilbert and Murphy, 2004a,b; Graves et al., 1999; Murphy et al., 1998). Thus, the possible interactions between age and ApoE genotype on olfactory performance are yet unknown. In the present work, age was modelled as a continuous variable, extending previous work by including younger cohorts. Also, earlier studies used samples that were screened or matched for health factors (e.g. neurological and psychiatric disorders), without taking these variables into consideration as independent variables in the statistical analyses (Gilbert and Murphy, 2004a,b; Handley et al., 2006; Murphy et al., 1998; Westervelt et al., 2005). This, however, was done in the present study. Furthermore, we assessed whether carriers of the ε2-allele differed from non-carriers in olfactory ability. In summary, we used a large population-based sample of adults to investigate the influence of ApoE gene status on odor identification and to address the possible mediating role of current and pre-diagnostic dementia, as well as demographic, cognitive and health variables on the association between ApoE gene status and odor identification.

2. Materials and methods 2.1. Participants The present data were derived from the Betula study, a prospective population-based study of aging, cognition, and health (Nilsson et al., 1997, 2004). In Betula, extensive psychological testing and health assessments are conducted every 5 years. The present data were collected during the

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Table 1 Participant characteristics across ε4 allele subgroups Total N (m/f) Age (years; mean ± S.D.) Education (years; mean ± S.D.) Testing experience (one vs. two times) Current dementia (%) Pre-diagnostic dementia (%) Psychiatric disorder (%) Neurologic disorder (%) Cardiovascular symptoms (%) Diabetes (%) Allergy, asthma, eczema or intolerance (%) Ear/nose/throat disorder (%) Smoker (%) Solvent exposure, drug abuse or intoxication (%) Cold, congestion, flu, etc. (%) Head injury (%)

third wave of testing which occurred in 1998–2000, with additional information about dementia diagnoses obtained from the fourth wave of testing, conducted in 2003–2005. The data were obtained from two stratified independent random samples from the population of Umeå, a city with about 110,000 inhabitants, located in northern Sweden. Sample 1 was recruited during the first wave of Betula testing (1988–1990), whereas Sample 2 was recruited during the second wave (1993–1995). Thus, Sample 1 had been exposed to testing on two previous occasions (i.e. 5 and 10 years before the third wave of testing), whereas Sample 2 had one previous experience of these tests (i.e. 5 years before the third wave of testing). The potential effects related to previous experiences were controlled for by including this variation in the statistical analysis. Importantly, the odor identification test was included for the first time in the third wave of the Betula study, and had consequently not been previously experienced by any participant. At the third wave of data collection, 1268 individuals between 45 and 80 years of age completed the assessment of global cognitive status (MMSE), odor identification, vocabulary, and health questionnaires at the time of testing, and were thus considered active participants. Of those, DNA had been extracted and ApoE had been genotyped in 97.5% of the cases. This procedure yielded an effective sample of 1236 individuals. Several health variables were assessed through interviews and questionnaires. The participants’ demographic and health-related characteristics are provided in Table 1. Because our main aim was to investigate odor identification performance associated with the presence of the ε4 allele, Table 1 provides the characteristics of the groups of carriers and non-carriers of the ε4 allele. The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Faculty of Medicine and Odontology, Umeå University. All participants gave their informed consent.

ε4 = no

ε4 = yes

864 (466/398) 61.5 (11.3) 10.7 (4.0) 455/409 13 (1.5) 17 (2.0) 46 (5.3) 62 (7.2) 77 (8.9) 51 (5.9) 129 (14.9) 122 (14.1) 118 (13.7) 3 (0.3) 115 (13.3) 18 (2.1)

372 (206/166) 60.7 (10.8) 11.0 (4.0) 185/187 11 (3.0) 24 (6.5) 13 (3.5) 23 (6.2) 23 (6.2) 20 (5.4) 57 (15.3) 58 (15.6) 49 (13.2) 2 (0.5) 53 (14.2) 3 (0.8)

2.2. Procedure Details of the procedure have been previously reported (Nilsson et al., 1997, 2004). All participants were tested individually in two sessions, 1 week apart. The first session was conducted by a nurse, and included blood sampling and an extensive health examination. Participants filled out questionnaires about health factors and social factors, and performed a few cognitive tests. In the second session, participants performed a larger battery of psychological tests, of different cognitive domains (e.g. memory, perceptual speed). The sessions lasted for approximately 2 h each, and the psychological tests were administered by well-trained research assistants. 2.2.1. Olfactory and cognitive assessment The Betula study includes a version of the Scandinavian Odor Identification Test (SOIT) (Nordin et al., 1998). This version comprises 13 olfactory stimuli that are familiar to the Scandinavian population: pine-needle, juniper berry, violet, anise, clove, vanilla, almond (bitter), orange, cinnamon, lemon, lilac, tar, and apple. The odors are fairly strong in intensity and represent a wide range of odor qualities, such as floral, citrous, non-citrous fruity, sweet, woody, and spicy. Of the included odors, all except tar were natural etheric oils (Stockholm Ether and Essence Manufactory, Stockholm, Sweden). For each stimulus, participants were provided with a written list of four response alternatives where one represented the correct verbal label (see Bende and Nordin, 1997 for details). The stimulus order was randomized between participants by randomly assigning one out of ten different stimulus orders to each participant. The odors and their corresponding response alternatives were identical for all participants. To prevent effects of adaptation, there was a 30 s inter-stimulus interval between odor items. Demographic and cognitive correlates of this test have been reported in a previous study (Larsson et al., 2004). Odor identification performance is typically higher in women than men, in highly

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educated than less educated individuals, and in younger than older individuals. The odor identification test shows low-tomoderate correlations with several cognitive tests, of which vocabulary and cognitive speed partially predict the agerelated deficit in odor identification performance. To control for cognitive influences on odor identification performance, two tests were used. Vocabulary is typically used as a measure of general knowledge, which is an aspect of semantic memory (Nyberg et al., 2003; Tulving, 1972, 1983). The vocabulary test used in the present study was a 30-item multiple-choice test, and participants were instructed to select a synonym for each target word out of five alternatives (Dureman and Sälde, 1959). The test was self-paced with a time limit of 7 min. The vocabulary test thus resembles the odor identification test in that both tests use a multiplechoice format of matching a stimulus to one of several verbal response alternatives. Also, the Mini-Mental State Examination (MMSE; Folstein et al., 1975) was used to control for general cognitive deficits that might indicate dementia. 2.2.2. Health assessment In the Betula study, determination of dementia diagnosis followed a procedure such that participants fulfilling one or several of the following criteria were referred to a specialist in neuropsychiatry: (a) suspected dementia signs observed by the staff conducting the Betula testing, (b) MMSE performance below 24, or (c) a decline of 3 or more points on the MMSE from the previous testing occasion. The psychiatrist evaluated the participants’ dementia status based on the Diagnostic and Statistical Manual of Mental Disorders, Revised Fourth Edition (DSM IV-R) (1994) (DSMMD, 1994). The medical records of all participants were provided for dementia classification. Participants could be identified as converting to a dementia disorder either at the third wave of testing (“current dementia”; n = 23), or at the fourth wave of testing (“pre-diagnostic dementia”; n = 42) in the Betula study. Differentiating dementia sub-types is intrinsically difficult without biological markers. For this reason, participants were only classified as being either demented or non-demented. However, according to the present dementia assessment, 77% of the demented participants were evaluated as having either AD or “AD and/or vascular dementia”. This indicates that AD was the most prevalent dementia category in this sample. Data for other health variables were obtained by interviews and questionnaires. The presence of neurological (e.g. multiple sclerosis) and psychiatric disease (e.g. depression and schizophrenia), cardiovascular problem (hypertension, stroke, or heart disease for which the participant is receiving medication), ear-nose-throat disorder, and type-II diabetes were included as dichotomous variables (yes versus no) if present within 5 years prior to testing. Current smoking was also included as a dichotomous variable in the analysis, as was self-reported conditions of the upper airways, such as cold, nasal congestion, flu, polyps, etc., if present at time

of testing. The prevalence of these conditions is reported in Table 1. In addition to the variables specified above, age, sex (female, male), number of years of formal education, and the variation in previous testing experience (one versus two times) were included in the analysis. 2.2.3. ApoE genotyping A polymerase chain reaction (PCR) was performed with 200 ng genomic DNA as template in a 25:1 reaction mixture containing 20 pmol of PCR primers APOEA (5 -TCCAAGGAGCTGCAGGCGGCA-3 ) and APOEB (5 -ACAGAATTCGCCCCGGCCTGGTACACTGCCA3 ; Wenham et al., 1991); 0.2 units (U) Taq DNA polymerase (Gibco BRL, Gaithersburg, MD, USA); 1.0 mM MgCl2 ; 75 mM Tris–HCI, pH 9.0; 20 mM (NH4 )2 SO4 ; and 10% DMSO. The PCR amplification consisted of 35 cycles of 30 s at 94 ◦ C, 30 s at 72 ◦ C, PCR products were digested with 5 units HhaI (Life Technologies, Portland, OR, USA) by incubating for 3 h at 37 ◦ C. Bands were separated on a 5% agarose gel and visualized on an ultraviolet transilluminator after ethidium bromide staining. Alternatively, electrophoresis was performed with ExcellGel gels (Pharmacia, acquired by Pfizer, NY, USA) and the MultiphorII electrophoresis system (Pharmacia/Pfizer), and the bands were visualized by silver staining. The genotype proportions for the present sample (n = 1236) were: 2/2, 0.003 (n = 4); 2/3, 0.122 (n = 151); 2/4, 0.028 (n = 35); 3/3, 0.574 (n = 709); 3/4, 0.250 (n = 309); and 4/4, 0.023 (n = 28). This genetic distribution is congruent with a previous population estimate (Eggertsen et al., 1993). In the present study, we wanted to assess whether having an ε2 or ε4 allele was associated with odor identification ability. Because of the small proportions of ε2 and ε4 homozygotes, the presence versus absence of at least one ε2-allele was coded in one dichotomous variable, and the presence versus absence of at least one ε4 allele was coded in another dichotomous variable. As a result of this dummy coding, the carriers of two ε3 alleles served as the control group because they had neither ε2 nor ε4. The variables regarding ApoE-status (ε2-allele carrier versus non-carrier, ε4 allele carrier versus non-carrier) were included in the analyses as main effects and as interactions with age. 3. Results Hierarchical regression analyses were performed because they allow assessment of the unique contribution of an independent variable in predicting a dependent variable after the effects of other independent variables have been partialled out. All statistical analyses were performed with the SPSS statistical software package (version 13.0 for Windows). Note that in all analyses, the interaction variables represent the residuals of the interaction effects after the main effects were partialled out. Thus, the ApoE-ε4 × age interaction does not correlate with either age or ApoE-ε4 status.

Table 2 Intercorrelations among variables 1

1. Odor id. 2. Age 3. Sex 4. Education 5. Testing exp. 6. ApoE ε4 7. ApoE ε2 8. Vocabulary 9. MMSE 10. Diabetes 11. Neurologic 12. Psychiatric 13. Head injury 14. Chemical exp. 15. Allergy, etc. 16. ENT disorder 17. Cardiovascular 18. Smoking 19. Cold, flu, etc. 20. Current dem. 21. Pre-diagn. dem. 22. Age × ApoE ε2 23. Age × ApoE ε4

−.37 −.13 .27 −.05 −.03 −.00 .28 .18 −.16 −.05 .02 −.00 −.00 −.02 .04 −.10 .01 −01 −.15 −.14 −.01 −.07

2

−.05 −.55 .01 −.04 −.01 −.34 −.34 .17 −.01 −.04 .00 .00 −.02 .01 .26 −.12 −.06 .17 .22 .00 .00

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

.03 −.01 −.01 −.02 −.05 −.02 .05 .01 −.09 −.01 −.01 −.04 −.01 −.03 .01 .04 .00 −.01 −.01 .02

−.04 .03 .01 .52 .33 −.12 .01 .02 −.02 −.04 .02 .00 −.21 −.03 .09 −.11 −.10 −.01 −.01

−.27 .00 −.01 −.07 −.01 .03 −.02 −.02 −.02 .06 −.02 −.13 −.05 −.01 −.05 .03 .05 −.02

−.11 .03 −.02 −.01 −.02 −.04 −.05 .01 .01 .02 −.05 −.01 .01 .05 .12 −.05 .00

.05 .03 .04 −.00 .01 −.02 .04 .01 −.00 −.03 .02 −.01 .01 −.05 .00 −.05

.46 −.13 .01 .04 −.06 −.03 .02 .04 −.15 −.03 .04 −.20 −.08 −.02 −.01

−.08 .02 −.00 −.03 .01 .04 .03 −.10 .01 .03 −.36 −.17 −.00 −.03

.02 .01 .05 −.02 .04 .02 .16 −.01 .02 .04 .05 .03 −.02

.07 −.01 .03 −.01 .03 −.02 −.02 .02 −.02 .00 .04 −.01

.03 .11 .03 .03 .00 −.01 .00 −.00 .00 −.03 −.02

−.01 .05 .02 .03 .02 −.03 −.02 .05 −.03 .02

.04 .05 −.02 .01 −.03 −.01 −.01 −.01 −.01

.02 .10 −.01 .09 −.06 −.04 .05 −.03

−.03 .03 .12 −.04 −.01 −.01 −.04

−.00 −.02 .07 .03 −.01 −.04

.04 −.02 −.01 .00 .05

−.04 −.05 .03 .05

−.03 .01 −.05 .04 .14

22

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Variable

−.12

Correlations in bold are significant (two-tailed). For correlations that exceed an absolute value of 0.08, p < .01, and for correlations with absolute values between 0.06 and 0.08, p < .05.

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Fig. 1. Mean odor identification performance (±S.E.) as a function of ApoEε4 status in the different age cohorts. Left side: number of correctly identified odors; right side: standardized scores with the youngest cohort as reference.

Fig. 1 shows mean odor identification performance across age for people with either no ApoE-ε4 allele or at least one ApoE-ε4 allele. The number of participants in each age group varied between 115 and 174. The proportion of ε4-carriers among age groups varied between 23.9 and 32.0%. The distribution of ε4-carriers was similar across age-groups, χ2 (7, n = 1236) = 4.23, p = .753. Odor identification performance decreased most strongly in older participants with ApoEε4. However, this finding might be accounted for by effects of other variables. Table 2 shows zero-order correlations of odor identification with gene status, demographic, cognitive, and health-related variables, and the interactions of age with ApoE-ε4 and ApoE-ε2. Odor identification performance was lower for men and correlated negatively with diabetes, cardiovascular symptoms, neurological disorders, current dementia, and pre-diagnostic dementia. In contrast, odor identification correlated positively with education, MMSE and vocabulary scores. To address the possibility that the ApoE-ε4 × age interaction might be mediated by other variables, a hierarchical regression analysis was performed. In the hierarchial regression analysis, demographic variables were entered in the first block (age, sex, education, previous test experience). In the second block, the genetic factors ApoE-ε2 and ApoE-ε4 were entered as main effects. The third block included the vocabulary test and MMSE to control for individual differences in knowledge and general cognitive status. Block four included health-related variables. Current and pre-diagnostic dementia statuses were then entered in separate blocks. The two final blocks in the analysis included the genetic interactions with age: ApoE-ε2 × age and ApoEε4 × age, because we wanted to investigate the contribution of the ApoE-ε4 × age interaction to the criterion measure over and above the contribution of the other variables in the model. Since the ε2-allele has not been investigated before in the context of olfactory abilities and aging, and since the probability of having ε2 is negatively correlated with the probability of having ε4 (see Table 2), we wanted to con-

trol specifically for possible effects of ApoE-ε2 × age before entering the ApoE-ε4 × age in the statistical model. Results are shown in Table 3. Of the demographic variables in the first block, younger age, female sex and higher education predicted better identification performance. In the second block, there were no main effects of the ε2 and ε4 alleles on odor identification. In the third block, higher vocabulary score contributed to higher odor identification performance, but there was no unique influence of MMSE. Of the health-related variables that were entered in the fourth block, diabetes and neurological disorders had negative influences on odor identification performance. In the fifth and sixth blocks, dementia statuses contributed to the variance in odor identification, confirming that odor identification ability is compromised in individuals who are demented or who will become demented within the next 5 years. In the last block of the analysis, the interaction of age and ApoE groups investigated whether a unique influence on odor identification remained after potential confounds were partialled out. Table 3 shows that the ApoEε4 × age interaction was significant (β = −0.056; p = .033). Because this interaction was entered last in the analysis, its effect on odor identification cannot be mediated by the other variables. In sum, although several demographic, cognitive, and health variables affected odor identification, the present results suggest that there was a unique effect of the ApoE-ε4 × age interaction on odor identification . In total, predictor variables accounted for 21.3% of the explanatory variance in odor identification performance. Although these findings suggest an independent effect of ApoE-ε4 × age on odor identification, it is possible that this effect may be partly accounted for by interactions of ApoEε4 with current and prospective dementia. To address this question, a second hierarchical regression analysis was performed on only the two oldest cohorts (75–80 years). These groups were selected because they showed the strongest effect of ApoE-ε4 (Fig. 1), as confirmed by independentsamples t-tests (p < .05). The sample of 75–80 year old adults (n = 249) consisted of 62 ε4-carriers (5 with current dementia and 13 with pre-diagnostic dementia) and 187 non-carriers (6 with current dementia and 6 with pre-diagnostic dementia). The hierarchical regression analysis included the same variables as before, in addition to interactions of ApoE-ε4 with current and prospective dementia. As shown in Table 4, results showed that ApoE-ε4 retained a significant negative relationship with odor identification. The results confirm that the effect of ApoE-ε4 on odor identification in the 75–80 age range is not driven by individuals that receive a dementia diagnosis within a 5-year period after olfactory assessment.

4. Discussion The present study used the largest sample to date to study associations between ApoE status and olfactory func-

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573

Table 3 Hierarchal regression analysis for predicting odor identification (N = 1236)

1. Demographics Age Sex (0 = m, 1 = f) Education Testing experience

R2 change

R2

.165

.165

2. Genetics ApoE-ε4 ApoE-ε2

.002

3. Cognition Vocabulary MMSE

.020

4. Health Diabetes Neurological disorder Psychiatric disorder Head injury Chemical exposure Allergy, asthma, etc. ENT disorder Cardiovascular symptoms Smoking Cold, congestion, flu, etc.

.013

5. Current dementia 6. Pre-diagnostic dementia 7. ApoE-ε2 × age 8. ApoE-ε4 × age

.006 .004 .000 .003

β

p

−.318 −.152 .098 −.042

.001*** .001*** .001*** .002** .105

.167 −.048 −.014

.174 .066 .587

.171 −.014

.001*** .001*** .649

−.080 −.053 −.015 .009 .004 −.032 .041 .020 −.027 −.030

.025* .003** .042* .567 .722 .868 .220 .113 .468 .306 .247

−.082 −.066 −.015 −.056

.003** .014* .988 .033*

.187

.200

.206 .210 .210 .213

Note: The interaction variables represent the residuals of the interaction effects after the main effects were partialled out. The β weights are the standardized regression coefficients at each step. MMSE = Mini Mental State Examination; ENT = ear–nose–throat. * p < .05. ** p < .01. *** p < .001.

tion. In the population-based sample of participants aged 45–80 years, results showed that in participants aged 75–80 years, carriers of the ε4-allele had an olfactory impairment. Importantly, this negative influence of the ε4 allele was present after controlling for vocabulary and general cognitive status. This pattern of findings suggests that the ε4 allele exerts a negative influence on the olfactory system in elderly individuals. Current and pre-diagnostic cases of dementia were assessed; whereas dementia influenced olfactory ability, dementia did not mediate the effect of ApoE-ε4 × age. This suggests that, contrary to previous assumptions (Murphy et al., 1998), the odor identification deficit in non-demented ε4carriers might be independent of subsequent development of dementia within 5 years. Little is known about the neurobiological mechanisms underlying the odor identification deficit in elderly, non-demented ApoE-ε4-carriers. It is difficult to exclude the possibility that the negative effects of ε4 might be related to processes leading to a dementia diagnosis several years after assessment. However, olfactory deficits are most pronounced shortly before diagnosis (Bacon et al., 1998). It is therefore unlikely that the association between the ε4 allele and odor identification ability in the present sample would be more strongly linked to a dementia diagnosis after more than

5 years than within 5 years after baseline assessment. However, neuropathological alterations might occur in olfactory brain structures in ε4-carriers without leading to a dementia diagnosis. A recent study (Wilson et al., 2007) showed that in an elderly sample, a measure of amyloid plaques and neurofibrillary tangles in the medial temporal lobe obtained during autopsy accounted for 12% of the variance in previous olfactory identification performance. Interestingly, this association was not attenuated by controlling for dementia diagnosis, suggesting that AD-related neuropathology might impair olfactory function in the elderly without leading to a dementia diagnosis. Thus, in the context of the present findings, the ApoE-ε4 might be involved in an accumulation of neuropathology in olfactory structures that impairs odor identification without resulting in a dementia diagnosis. Furthermore, ApoE has been proposed to be involved in lipid recycling, which is an important feature of neurogenesis (Masliah et al., 1996). The peripheral olfactory system and the hippocampus are main sites of adult neurogenesis (Altman, 1969; Kaplan and Hinds, 1977). Aging is associated with a decreased neurogenesis in these structures (Enwere et al., 2004; Kuhn et al., 1996). Although peripheral olfactory structures are difficult to study in humans in vivo, studies

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Table 4 Hierarchal regression analysis for predicting odor identification in older adults (75–80 years; N = 249) R2 change

R2

1. Demographics Sex (0 = m, 1 = f) Education Testing experience

.046

.046

2. Cognition Vocabulary MMSE

.030

3. Health Diabetes Neurological disorder Psychiatric disorder Head injury Allergy, asthma, etc. ENT disorder Cardiovascular symptoms Smoking Cold, congestion, flu, etc.

.083

4. Current dementia 5. ApoE-ε4 × current dementia 6. Pre-diagnostic dementia 7. ApoE-ε4 × pre-diagn. dementia 8. ApoE-ε2 9. ApoE-ε4

.016 .000 .011 .008 .002 .028

β

p

−.126 .183 −.073

.009** .051 .005** .251

.076 .138 .086 −.255 .021 −.106 .014 −.016 .039 .128 −.052 .000

.008** .001*** .733 .090 .826 .790 .528 .040* .400 .995

−.146 −.017 −.110 .093 .046 −.192

.033* .782 .075 .131 .456 .004**

.159

.175 .175 .186 .194 .196 .224

.021* .059 .215

Note: The interaction variables represent the residuals of the interaction effects after the main effects were partialled out. The β weights are the standardized regression coefficients at each step. From the health variables, chemical exposure was excluded because nobody had been exposed. MMSE = Mini Mental State Examination; ENT = ear–nose–throat. * p < .05. ** p < .01. *** p < .001.

in mice have suggested that the ApoE is necessary for efficient neuronal regeneration in olfactory structures, and that the ε4 allele is associated with regenerative failure (Nathan et al., 2002, 2005). The present data do not allow us to infer precise neurobiological mechanisms underlying the present observations. Speculatively, the observed olfactory impairment in elderly, non-demented carriers of the ε4 allele might be accounted for by either neuropathology in olfactory CNS structures that is not strongly related to a dementia diagnosis, a regenerative failure in the peripheral olfactory system in humans, or a combination of these two factors. As this issue is of importance for determining the role of olfaction in early detection of dementia, studies relating olfactory function to precise neurobiological mechanisms in the elderly are warranted. The present results indicate that the negative effect of the ApoE-ε4 on odor identification ability was only prevalent among the elderly individuals (75–80 years), whereas the gene exerted no influence on performance among the younger participants. This finding is in line with previous reports showing various negative effects of ε4 in elderly participants (Deary et al., 2002; Murman et al., 1996; Nilsson et al., 2006; Riley et al., 2000), and that the ε4-allele is a significant predictor of decreased longevity (Smith, 2002). While other studies on the subject have employed short post-test screening ranges for dementia or none at all (Bacon

et al., 1998; Graves et al., 1999; Murphy et al., 1998), the present study used a 5-year follow-up period. This, in combination with the standardized procedure for detecting demented participants within the Betula study (see methods section), improved our ability to classify participants as demented or non-demented at time of testing. The potential impact of several demographic and health variables on odor identification were assessed in the present study. The results replicate previous observations of female gender and high education being associated with higher performance in olfactory and semantic tasks (Larsson et al., 2000, 2004; Nilsson et al., 1997; Öberg et al., 2002). Also, the analyses showed that type-II diabetes exerted a significant negative influence on olfactory proficiency, corroborating previous findings (Nilsson et al., 2002; Uren et al., 1990; Weinstock et al., 1993). One limitation of the present study is that the self-reported dichotomous health variables might have yielded less reliable assessments than biological and clinical data. The lack of biological markers also impaired a differentiation between dementia sub-types. However, the psychiatric assessment indicated that AD was present in most demented individuals. Also, we note that previous testing experience was associated with better MMSE performance. This suggests influences of practise and/or attrition, i.e. low-performing persons discontinue participation more frequently than high-

J.K. Olofsson et al. / Neurobiology of Aging 31 (2010) 567–577

performing persons. This is a common finding in longitudinal studies, and has also been documented previously in the Betula project (Rönnlund et al., 2005). However, the odor identification test was novel to all participants, and the variation in previous testing experience did not influence our main finding of an age by ApoE-ε4 interaction effect on odor identification. In summary, the present findings indicate that (1) the ApoE-ε4 allele is associated with olfactory processing deficits specifically in elderly adults (75–80 years). Also (2) the ε4-related deficit is specific to the olfactory system and is not due to a deficit in word knowledge or general cognitive ability. Furthermore (3) current and pre-diagnostic dementia influences olfactory functioning. However (4) the effects of dementia do not mediate the effect of ApoE-ε4 on odor identification performance in the elderly. This suggests a more complex relationship between ApoE-ε4, olfactory ability, and dementia than what has been previously assumed. Overall, the present results suggest that the ApoE gene plays a significant role for the integrity of the olfactory system in non-demented, elderly individuals (Nathan et al., 2004, 2005, 2007; Struble et al., 1999). Conflict of interest The authors confirm that we have no conflict of interest.

Acknowledgements The Betula Study is funded by the Bank of Sweden Tercentenary Foundation (1988-0082:17), Swedish Council for Planning and Coordination of Research (D1988-0092, D1989-0115, D1990-0074, D1991-0258, D1992-0143, D1997-0756, D1997-1841, D1999-0739 and B1999-474), Swedish Council for Research in the Humanities and Social Sciences (F377/1988–2000), and the Swedish Council for Social Research (1988–1990: 88-0082 and 311/1991–2000). The authors acknowledge the contribution to this paper of the VIB—Department of Molecular Genetics at the University of Antwerp, Antwerpen, Belgium, and Rolf Adolfsson at the Department of Psychiatry, Umeå University, to the APOE genotyping of Betula individuals. Also, the authors thank Birgitta Törnkvist at the Department of Statistics, Umeå University, for valuable consultation, and six anonymous reviewers for helpful comments.

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