Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2016 Apr 12.
Published in final edited form as: Alzheimers Dement. 2014 Jun 18;11(2):226–235. doi: 10.1016/j.jalz.2014.02.005

Association of fish oil supplement use with preservation of brain volume and cognitive function

Lori A Daiello a,b,*, Assawin Gongvatana c, Shira Dunsiger d, Ronald A Cohen c, Brian R Ott a,b, for the Alzheimer’s Disease Neuroimaging Initiative
PMCID: PMC4829435  NIHMSID: NIHMS775259  PMID: 24954371

Abstract

Objective

The aim of this study was to investigate whether the use of fish oil supplements (FOSs) is associated with concomitant reduction in cognitive decline and brain atrophy in older adults.

Methods

We conducted a retrospective cohort study to examine the relationship between FOS use during the Alzheimer’s Disease Neuroimaging Initiative and indicators of cognitive decline. Older adults (229 cognitively normal individuals, 397 patients with mild cognitive impairment, and 193 patients with Alzheimer’s disease) were assessed with neuropsychological tests and brain magnetic resonance imaging every 6 months. Primary outcomes included (1) global cognitive status and (2) cerebral cortex gray matter and hippocampus and ventricular volumes.

Results

FOS use during follow-up was associated with significantly lower mean cognitive subscale of the Alzheimer’s Disease Assessment Scale and higher Mini-Mental State Examination scores among those with normal cognition. Associations between FOS use and the outcomes were observed only in APOE ε4–negative participants. FOS use during the study was also associated with less atrophy in one or more brain regions of interest.

Keywords: Alzheimer’s disease, Brain atrophy, Cognition, Docosahexaenoic acid, Omega-3

1. Introduction

Fish oil is a rich source of eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and long-chain polyunsaturated omega-3 fatty acids (n-3 PUFAs). For increasing numbers seeking to augment their diets for cognitive health, factors such as convenience, cost, and concerns about long-term effects of methyl mercury may motivate the use of fish oil supplements (FOSs) to replace or augment dietary consumption of marine sources of n-3 PUFAs [1].

Although observational studies have generally reported better cognitive functioning or lower rates of incident Alzheimer’s disease (AD) in populations reporting greater dietary intake of fatty fish, but with few exceptions [2–8], the results of placebo-controlled trials of 3- to 24-month treatment with DHA or DHA + EPA have not supported these findings [9–12]. Treatment with n-3 PUFAs has been ineffective in controlled trials of mild-to-moderate AD [13–16]; however, there is some evidence that intervening in very mild AD or mild cognitive impairment (MCI) may be beneficial [8,14,17,18].

By the time that AD is clinically evident, years of cumulative neuropathology has already occurred, so it is not surprising that n-3 PUFA supplements do not benefit cognition in established dementia. If neuroprotective roles exist for DHA and EPA, then biological markers of neuro-degeneration such as cognitive performance and volumetric magnetic resonance imaging (MRI) measures should be relatively preserved in FOS users [19], particularly in those taking them prophylactically or early in the neuropathologic process.

The primary objective of this study was to examine the relationship between the use of FOSs and concomitant longitudinal brain structural changes, as well as cognition across the spectrum of aging and age-related neurodegeneration. Second, we sought to investigate associations between duration of FOS use and these outcomes. To accomplish these aims, we examined repeated standardized measurements of brain volume (BV) and cognition from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort [20,21].

2. Methods

2.1. Design

We conducted a retrospective cohort study of participants recruited into the ADNI from inception to August 2010. ADNI is a 5-year multicenter study launched in 2003 to assess changes of cognition, brain structure, and biomarkers in three groups of elderly individuals: normal controls, MCI, and AD [21]. Study methods are available at www.adniinfo.org.

Written consent was obtained from subjects before participation in the ADNI. This study protocol was reviewed and designated as exempt for human subjects research by the Rhode Island Hospital Institutional Review Board.

2.2. Participants

A total of 819 elderly participants (229 with normal cognition [NC], 397 MCI, and 193 AD), aged 55 to 90 years, were recruited into the ADNI from 50 clinical centers in the United States [22]. After screening and baseline visits, follow-up evaluations were conducted at 6-month intervals for up to 48 months for NC and MCI subgroups; AD participants were assessed at 6-month intervals for up to 24 months and at month 36. Results of comprehensive neuropsychological testing and brain MRI were documented for all participants at 6- to 12-month intervals. Ninety-five percent of the ADNI participants attended at least one postbaseline study visit, and 80% of the cohort had four or more follow-up assessments.

The analysis cohort consisted of 117 participants reporting FOS use at the initial study visit and during follow-up and 682 who did not report FOS use during the study. Eleven participants initiated FOS use during follow-up; this group was excluded from the analysis cohort because the duration of FOS use was brief (≤6 months) or supplements were initiated too late in the study to allow adequate time for follow-up. The unexposed cohort (n = 691) included participants who did not report FOS use during the study; nine were subsequently excluded because of missing outcome data.

2.3. Exposure classification

Information on FOS use was extracted from the ADNI concomitant medication file, a longitudinal record of medication use within the cohort. According to the protocol, subjects were queried about prescription and nonprescription drug uses at screening and subsequent study visits. For those with memory impairment, study partners assisted research staff with medication reconciliation. For each participant, we constructed the primary exposure variable, FOS use, defined as the presence or absence of any form of FOSs reported during the study visit. The FOS user status was ascertained at each visit, and the participant-reported date of initiation was designated as the first day of FOS exposure in the data set. Those using FOSs at consecutive visits were considered to be continuously exposed between visits. The duration of FOS exposure for each subject was estimated by subtracting the discontinuation date from the start date; for those who did not discontinue FOSs during the study, the date of the last visit was considered the final day of FOS exposure.

2.4. Outcomes

The primary outcome measures were the total scores at each visit for (1) the cognitive subscale of the 70-point Alzheimer’s Disease Assessment Scale (ADAS-cog) and the Mini-Mental State Examination (MMSE) and (2) cerebral cortex gray matter, ventricle, and hippocampus volumes from serial MRI. The secondary outcome measure was the estimated duration of FOS use.

2.5. Brain imaging acquisition and processing

All participants received high-resolution structural brain MRI scans on 1.5-T scanners as specified by the ADNI protocol [23]. Multiple procedures to minimize cross-site variation were used during the study, including standardized MRI protocols and acquisition parameters and systematic phantom-based monitoring of instruments. Raw three-dimensional T1-weighted magnetization-prepared rapid acquisition gradient echo images were preprocessed (gradient warping, scaling, B1 correction, and N3 inhomogeneity correction). Acquisition, quality control, and preprocessing of ADNI MRI data are described at http://adni.loni.ucla.edu/research/protocols/mri-protocols. Segmentation of brain regions was performed on T1-weighted images using an automated set of algorithms implemented in FreeSurfer (https://surfer.nmr.mgh.harvard.edu). Specifically, raw imaging data were downloaded from ADNI by Dr. Anders Dale and colleagues at the Departments of Neurosciences and Radiology, University of California, San Diego. Phantom scans were used to correct for gradient nonlinearities, followed by image intensity normalization. Neuroanatomic labels are assigned to each voxel based on probabilistic information estimated from an atlas. Accuracy of this procedure has been shown to be comparable with that of manual labeling and sensitive to subtle changes in AD and normal aging. The volumes so acquired were uploaded to the ADNI Web site for access by investigators. For this study, volumetric measures in millimeter [2] were downloaded from ADNI for the cerebral cortex gray matter, ventricles, and hippocampus. These regions were selected based on their relevance to neuropathology of AD. Overall ventricular volume was derived by combining volumes for all ventricles for each brain. Likewise, bilateral hippocampal volumes were combined. Total intracranial volumes were used in accounting for variation in head sizes in all volumetric analyses.

2.6. Cognitive evaluation

The ADAS-cog consists of 11 items measuring memory, language, praxis, attention, and other aspects of cognitive functioning. Total scores range from 0 to 70, with higher scores indicating greater levels of impairment. The MMSE assesses seven cognitive domains, including attention, memory, and visual construction. Total scores range from 0 to 30 points, with higher scores indicating better cognitive function.

2.7. Potential confounders

Confounders were chosen a priori and represent the participant-level characteristics available in the data set that could be associated with the exposure and outcomes. Cognitive models controlled for age, gender, education, race, vascular risk factors, APOE ε4 carrier status, cholinesterase inhibitor (CHEI) use, and baseline cognitive diagnosis and cognitive test scores. BV models controlled for age, gender, vascular risk factors, education, APOE ε4 carrier status, CHEI use, intracranial volume, and baseline cognitive diagnosis and region of interest volumes (cerebral cortex gray matter/ventricle/hippocampus).

The potential effects of vascular risk factors on cognition and BV were summarized in the models with a cardiovascular (CV) risk score using the method by Carmichael et al. [24] for ADNI data. One point is assigned for a baseline diagnosis of CV disease, current tobacco use, hypertension, diabetes, and cerebrovascular accident or stroke; the CV risk score (range, 0–5) is the sum of these scores.

2.8. Statistical analysis

Baseline sociodemographics, duration of FOS use, and subgroup means for the outcomes (cognitive test scores and BVs) were compared using χ2 tests and one-way analyses of variance (ANOVAs). Using a series of longitudinal regression models implemented with generalized estimating equations (GEEs) [25,26] with robust standard errors (SEs), longitudinal changes for each outcome measure were assessed, as well as associations between time-varying FOS exposure (users vs. nonusers at each visit) and the outcomes in the analysis cohort and the cognitive subgroups. The effect of duration of FOS exposure on the outcomes was assessed similarly.

GEE models do not require a distributional form of the response variable (cognition and BVs in this study) and have been shown to provide unbiased estimates of the model parameters even in the case when the within-subject correlation structure is incorrectly specified [25,26]. A working autoregressive correlation structure was chosen to accommodate within-subject correlation. GEEs are used to model incomplete longitudinal data and assume the missing data are missing completely at random, an assumption that cannot be directly tested. No imputation of missing values was performed. Analyses were performed using Stata, version 10.0 (StataCorp, College Station, TX, USA), and SAS, version 9.2 (SAS Institute Inc, Cary, NC, USA), and the significance level was set a priori to α = 0.05.

2.9. Relationship between FOSs and the study outcomes

2.9.1. Primary analyses

In the analysis cohort, we simultaneously regressed the cognitive and BV outcomes at time t (t = 6, …, 48 months) on time and the use of FOSs at time t, while controlling for confounders (Section 2.7).

2.9.2. Secondary analyses

To further investigate associations between FOS use during follow-up and the cognitive and brain structural outcomes, we conducted several secondary analyses. All models controlled for cognitive group membership (except the within-group analyses of cognitive diagnosis) and other potential confounders as in the previous analyses.

2.9.3. APOE ε4 genotype

After stratifying the analysis cohort by the APOE ε4 carrier status, associations between FOS use and change over time in cognition and BV were evaluated.

2.9.4. Cognitive diagnosis

The analysis cohort was stratified by diagnostic group membership at study entry (NC, MCI, and AD), and the cognitive and BV analyses were repeated.

2.9.5. Duration of exposure

The effect of duration of FOS exposure was investigated using longitudinal models to regress cognitive and BV outcomes on participant-reported time on FOSs within the analysis cohort. Time on FOSs was defined as (1) duration of supplement use at baseline and (2) cumulative time on FOSs (duration of exposure at baseline + follow-up) in months. Duration variables were entered into the models as continuous variables, then in quartiles. All duration models were evaluated with and without the FOS use indicator variable.

2.9.6. Sensitivity analysis

Lifestyle factors (e.g., diet, exercise, and other health habits) are potential confounders of the association between FOSs and the outcomes; however, this information was not collected during ADNI. As such, we considered multivitamin use at baseline as a proxy for this information and repeated the previous analyses, controlling for use of multivitamin supplements.

3. Results

3.1. Participant characteristics

Baseline characteristics of the cohort are presented in (Table 1). The three cognitive subgroups were similar in age, gender distribution, and race/ethnicity. In comparison with participants without dementia at baseline, the MCI and AD groups were more cognitively impaired (lower MMSE scores and higher ADAS-cog scores) and had a higher proportion of APOE ε4 carriers. Mean cerebral cortex gray matter volume was not significantly different between the groups at baseline; however, NC subjects had smaller ventricles (P < .05) than those with AD and smaller hippocampus volumes than those observed in the MCI (P < .001) and AD (P < .001) groups.

Table 1.

Population characteristics at baseline

Characteristics All (n = 819) NC (n = 229) MCI (n = 397) AD (n = 193) P value*
Age, y, mean ± SD 75.3 ± 6.9 76.0 ± 5.0 74.9 ± 7.5 75.5 ± 7.5 .14
APOE ε4 status, % (N)
 Carrier (+) 48.4 (400) 26.6 (61) 53.4 (212) 65.8 (127) <.0001
 Noncarrier (−) 51.2 (419) 73.4 (168) 46.6 (185) 34.2 (66) <.0001
Gender, %
 Female 41.8 48.0 35.5 47.2 .36
Race, % (N)
 Caucasian 93.0 (762) 91.7 (210) 93.5 (371) 93.8 (181) .94
CV risk score, mean ± SD 1.75 ± 1.11 1.67 ± 1.1 1.78 ± 1.1 1.77 ± 1.1 .44
Fish oil supplement use, % (N) 14.3 (117) 13.5 (31) 8.1 (32) 28 (54) <.0001
Duration of fish oil supplement use by cognitive subgroup, y, mean ± SD 6.0 ± 9.5 4.7 ± 7.6 2.7 ± 2.5 <.001
Cognition, mean ± SD
 MMSE 26.8 ± 2.7 27.8 ± 2.4 26.7 ± 2.4 25.7 ± 2.8 <.0001
 ADAS-cog 11.7 ± 6.4 6.2 ± 2.9 11.5 ± 4.4 18.6 ± 6.3 <.001
MRI volumetric comparisons
 Hippocampus volume (mm3) 6768.68 (1108.90) 6273.37 (1144.57) 6290.48 (1200.12) <.0001
 Ventricular volume (mm3) 43262.19 (24182.39) 45502.06 (23143.11) 49274.90 (28633.18) .04
 Cerebral cortex volume (mm3) 392689.40 (41706.61) 387538.93 (42602.97) 384431.73 (43391.82) .13
 Intracranial volume (mm3) 1460204.18 (139330.04) 1472862.07 (148113.38) 1441954.67 (154518.06) .07
Open in a new tab

Abbreviations: NC, cognitively normal controls; MCI, mild cognitive impairment; AD, Alzheimer’s disease; SD, standard deviation; APOE, apolipoprotein E; CV, cardiovascular; MMSE, Mini-Mental State Examination; ADAS-cog, Alzheimer’s Disease Assessment Scale—cognitive subscale.

*

Cognitive subgroup comparisons.

Within the ADNI cohort, 14.3% (n = 117) reported regular use of FOSs (NC, 13.5%; MCI, 8.2%; and AD, 30%) at the initial study visits. The proportion of ADNI participants using FOSs at baseline and at one or more subsequent study visits during follow-up was 95.7% (n = 112) at 12 months, 87.2% (n = 102) at 24 months, 64.9% (n = 76) at 36 months, 32.5% (n = 38) at 42 months, and 11.1% (n = 13) at the 48-month study visit. The number of FOS users assessed at each time point during the ADNI is shown in Table 2.

Table 2.

Numbers of participants using FOSs at baseline and during the ADNI

Study visit Normal cognition, attended assessment (n) Mild cognitive impairment, attended assessment (n) Alzheimer’s disease, attended assessment (n)
Baseline 31 32 54
Month 12 31 28 49
Month 24 28 24 42
Month 36 24 19 33
Month 42 10 16 12
Month 48 6 5 3
Open in a new tab

Abbreviations: FOS, fish oil supplement; ADNI, Alzheimer’s Disease Neuroimaging Initiative.

Most reported long-term FOS use before enrollment in the ADNI study; 11.1% reported FOS use exceeding 10-year duration and 59.8% reported 1 to 10 years of use. The remainder (29.8%) used FOSs for less than 12 months on entering the study. Those with NC at baseline reported the longest mean duration of use (6.0 years [standard deviation {SD}, 9.5 years]), followed by the MCI (4.7 years [SD, 7.6 years]) and AD (2.7 years [SD, 2.5 years]) groups. Duration of FOS use at study entry differed significantly between diagnostic groups [F (2, 816) = 10.87, P =.001]. Bonferroni post hoc comparisons indicated that FOS duration of use for the NC and MCI groups exceeded that reported by those with AD (NC vs. AD, M = 3.30, 95% CI, 1.57–5.03, P < .001; MCI vs. AD, M = 2.00, 95% CI, 0.443–3.56, P < .01). There was a trend toward statistical significance for greater years of FOS use in the NC versus MCI comparison (NC vs. MCI, M = 1.30, 95% CI, −0.1725 to 2.773, P = .06).

The majority (88.9%) of ADNI participants using FOSs at enrollment reported that supplements were primarily used for “general health,” whereas 2.7% cited “joint protection/arthritis” reasons. Few (4.3%) endorsed the use of FOSs for “memory/brain protection”; all had been diagnosed with a memory disorder at baseline (MCI, n = 3; AD, n = 2).

3.2. Primary analyses

3.2.1. Associations between FOS use and cognitive/BV outcomes in the ADNI cohort

In general, ADAS-cog scores increased over time (β = 0.05; SE, 0.01; P <.01) and MMSE scores decreased over time (β = −0.05; SE, 0.01; P =.02); however, significant associations between FOS use and both cognitive outcome measures were observed at follow-up (6–48 months; Table 3). Compared with nonusers, reported use of FOSs during follow-up was associated with lower mean ADAS-cog scores (β = −3.86; SE, 1.59; P = .02) and higher mean MMSE scores (β = 0.96; SE, 0.43; P =.02) at any given time in the study.

Table 3.

Covariate-adjusted parameter estimates for main effects of FOS use and time (ADNI analysis cohort)*

Outcome variable Group Main effect of time
Main effect of FOS use
Value SE P value Value SE P value
Cognitive outcomes
 ADAS-cog ADNI cohort 0.05 0.01 <.01 −3.86 1.59 .02
APOE ε4 (+) 0.08 0.02 <.01 −1.40 4.27 .74
APOE ε4 (−) 0.02 0.01 .07 −4.68 1.40 <.01
 MMSE ADNI cohort −0.05 0.01 .02 0.96 0.43 .02
APOE ε4 (+) −0.07 0.01 <.01 0.16 0.53 .76
APOE ε4 (−) −0.04 0.01 <.01 1.12 0.44 .01
Brain volume outcomes
 Hippocampus volume ADNI cohort −12.69 0.55 <.01 160.80 70.65 .02
APOE ε4 (+) −13.80 0.81 <.01 −34.68 111.24 .76
APOE ε4 (−) −11.78 0.72 <.01 232.15 39.62 <.01
 Ventricular volume ADNI cohort 234.77 9.61 <.01 −2330.46 1085.19 .03
APOE ε4 (+) 271.94 15.23 <.01 −2746.48 2105.34 .19
APOE ε4 (−) 201.37 11.43 <.01 −1786.25 1134.96 .12
 Cerebral cortex gray matter volume ADNI cohort −305.02 23.21 <.01 11904.12 4477.22 <.01
APOE ε4 (+) −357.89 32.72 <.01 5585.13 3131.46 .07
APOE ε4 (−) −258.52 32.08 <.01 14,988 4980.90 <.01
Open in a new tab

Abbreviations: FOS, Fish oil supplement; ADNI, Alzheimer’s Disease Neuroimaging Initiative; SE, Standard error; ADAS-cog, Alzheimer’s Disease Assessment Scale—cognitive subscale; APOE, Apolipoprotein E; MMSE, Mini-Mental State Examination; CVD, Cardiovascular disease.

*

Cognition models controlled for age, gender, education, race, CVD risk score, APOE ε4 carrier status, cholinesterase inhibitor use, and baseline scores. Brain volume models controlled for age, gender, CVD risk score, education, APOE ε4 carrier status, cholinesterase inhibitor use, and baseline intracranial volume.

Overall, mean hippocampus volume decreased significantly over time (β = −12.69; SE, 0.55; P <.01), as did cerebral cortex gray matter volume (β = −305.02; SE, 23.21; P <.01), whereas mean ventricular volume increased over time (β = 234.77; SE, 9.61; P <.01). Use of FOSs at any given time (t) during the study was associated with brain structural differences compared with those not reporting use of FOSs during follow-up: increased hippocampal volume at month t (β = 160.80; SE, 70.65; P =.02), decreased ventricular volume (β = −2330.46; SE, 1085.19; P =.03), and increased cerebral cortex gray matter volume (β = 11904.12; SE, 4477.22; P <.01).

3.3. Secondary analyses

3.3.1. Associations between FOS use and the APOE ε4 carrier status

Stratifying the analysis cohort by the APOE ε4 carrier status revealed that the association between FOSs and better cognitive scores (ADAS-cog and MMSE) remained significant only in the APOE ε4 (−) group. FOS use during the study was also associated with significantly higher mean hippocampus (β =232.15; SE, 39.62; P <.01) and cerebral cortex gray matter volumes (β = 14988.00; SE, 4980.90; P < .01) in APOE ε4 noncarriers; however, no association was found between FOS use and ventricular volume in the stratified sample.

3.3.2. Associations between FOS use and cognitive/BV outcomes in the cognitive subgroups

When the cohort was stratified by groups (NC, MCI, and AD), significant associations between FOS use during the study and cognition (ADAS-cog and MMSE) were observed only in those with baseline normal cognitive function (Table 4). In the fully adjusted model, mean ADAS-cog scores were lower at any given time t for FOS users at time t compared with nonusers (β = −7.01; SE, 1.56; P < .01). In addition, the mean MMSE score was higher among FOS users compared with nonusers (β = 1.94; SE, 0.28; P < .01). In the NC group, FOS use during follow-up was also associated with higher mean hippocampus (β = 299.39; SE, 46.97; P <.01) and cerebral cortex gray matter volumes (β = 18255.70; SE, 2561.43; P < .01) at any point in the study (Table 4). Brain imaging analyses within the MCI and AD groups revealed a significant positive association between FOS use during the study and mean cerebral cortex gray matter volumes in the MCI cohort and mean hippocampal volumes in the AD subgroup compared with FOS nonusers.

Table 4.

Covariate-adjusted parameter estimates for main effects of FOS use and time (cognitive subgroups)*

Outcome variable Group Main effect of time
Main effect of FOS use
Value SE P value Value SE P value
Cognitive outcomes
 ADAS-cog NC −0.01 0.01 .59 −7.01 1.56 <.01
MCI 0.08 0.02 <.01 −3.29 2.57 .20
AD 0.10 0.03 <.01 −4.58 3.04 .13
 MMSE NC −0.01 0.01 .05 1.94 0.28 <.01
MCI −0.07 0.01 <.01 0.68 0.62 .28
AD −0.08 0.01 <.01 0.88 0.46 .06
Brain volume outcomes
 Hippocampus volume NC −10.31 0.79 <.01 299.39 46.97 <.01
MCI −14.49 0.81 <.01 88.16 143.71 .54
AD −11.95 1.31 <.01 195.02 64.78 <.01
 Ventricular volume NC 161.50 11.20 <.01 −1051.43 740.31 .16
MCI 273.28 15.24 <.01 −2070.55 1621.73 .20
AD 265.56 22.48 <.01 −2831.05 2042.54 .17
 Cerebral cortex gray matter volume NC −218.29 35.51 <.01 18255.70 2561.43 <.01
MCI −350.57 34.98 <.01 17406.86 3994.45 <.01
AD −345.89 53.20 <.01 −1331.65 1675.79 .43
Open in a new tab

Abbreviations: FOS, Fish oil supplement; SE, Standard error; ADAS-cog, Alzheimer’s Disease Assessment Scale—cognitive subscale; MMSE, Mini-Mental State Examination; NC, Cognitively normal controls; MCI, Mild cognitive impairment; AD, Alzheimer’s disease.

*

Cognition models controlled for age, gender, education, race, CVD risk score, APOE ε4 carrier status, cholinesterase inhibitor use, and baseline scores. Brain volume models controlled for age, gender, CVD risk score, education, APOE ε4 carrier status, cholinesterase inhibitor use, and baseline intracranial volume.

3.3.3. Associations between duration of FOS use and cognitive/BV volume outcomes in the ADNI cohort

Estimated participant-reported time on FOSs (duration of supplement use before baseline and total time on FOSs [duration of exposure before study entry + follow-up]), in months, was entered into the cognitive and BV models, first with duration before baseline, then using total time on FOSs. No associations between duration of FOS exposure and any of the cognitive or BV outcomes were observed (data not shown).

3.4. Sensitivity analysis

Controlling for documented use of multivitamins at baseline in the cohort in analyses for the primary and secondary outcomes did not significantly change the parameter estimates in any of the cognitive and BV models.

4. Discussion

This retrospective cohort study is the first to examine the potential association of ongoing FOS use with conservation of BV and cognition across the spectrum of normal aging and neurodegeneration. After adjusting for potential confounders, use of FOSs during the ADNI was associated with less cerebral cortex gray matter and hippocampal atrophy and better performance on the ADAS-cog and MMSE, on average, compared with nonusers; these results were observed in the entire ADNI cohort, for those without a dementia diagnosis at baseline, and in the APOE ε4 (−) group.

Our findings in the cognitively normal group complement those of other recent observational studies that have investigated the relationship between cognitive function, brain atrophy, and n-3 PUFA levels in nondemented elderly. Bowman et al. [27] used principal component analysis to identify associations between plasma nutrient biomarker patterns and cognition, as well as total cerebral volume and percentage of white matter hyperintensities (WMHs) in the Oregon Brain Aging Study cohort. Another cross-sectional study contrasted quartiles of red blood cell n-3 PUFA concentrations for middle-aged and elderly participants in the Framingham study [28] and reported that the lowest levels of DHA and DHA + EPA were associated with lower total brain and greater WMH volumes, as well as greater cognitive deficits in multiple domains. Samieri et al. [29] reported that higher baseline plasma levels of EPA, but not DHA, were associated with less regional gray matter atrophy in the right amygdala and sections of the right hippocampal and parahippocampal areas over 4 years in a subgroup of elders participating in the French Three-City Study.

Not surprisingly, we did not find support for cognitive benefits associated with FOS use during the study in the AD subgroup in this observational study; these results are consistent with outcomes of well-designed randomized controlled trials of DHA in dementia populations. The null association for FOS use during follow-up and the cognitive outcomes in the MCI subgroup is discordant with results of controlled trials of DHA in this at-risk population [8,14,17,18]. The relationships of FOS use with preserved cerebral cortex gray matter volume in MCI and hippocampus volume in AD have not been previously reported. In contrast, an 18-month clinical trial of DHA in AD patients failed to show any effect on MRI volumes [13]. We may have been able to demonstrate hippocampal volume differences in FOS users with AD if the exposure overlapped a critical period for neuroprotection, including the prodromal phase, when FOS use may have its greatest effects. However, these analyses must be interpreted cautiously because of the potential influence of reverse causation because participants may have initiated FOS use to treat clinical symptoms of neurodegeneration.

Currently, there is limited understanding of how certain factors, such as timing and duration of exposure, might moderate n-3 PUFAs’ neuroprotective and cognitive effects. Although a number of prospective cohort studies have identified positive associations between consumption of fatty fish and better cognitive health in long-term follow-up, the effects of supplemented fish oils or DHA have been studied in controlled trials for much shorter periods, up to 18 months in populations with dementia or MCI and 24 months in the cognitively normal elderly [9,16]. The predominance of ADNI participants using FOSs for unusually long periods was unexpected but provided a unique opportunity to study multiple clinical outcomes during long periods of exposure to supplemented n-3 PUFAs. Those reporting 10 or more years of FOS use would have initiated the supplements during midlife, a potentially important time for interventions aimed at preventing age-related cognitive decline. Of note, surrogate markers of preclinical AD (e.g., memory deficits, smaller whole brain and regional BVs, and cerebrospinal fluid and brain amyloid imaging) are observed in APOE ε4 carriers, as early as midlife [30,31].

Middle age may be a particularly significant period for the potential role of n-3 PUFA in cognitive aging. Two recent observational studies support this theory [32,33]; both reported positive associations between higher concentrations of DHA or total n-3 PUFAs + DHA and better cognitive function in subjects aged 44 to 64 years. One of the studies [32] examined the effect of APOE ε4 and determined that the association between the n-3 PUFA status and cognitive performance over 4 years of follow-up was significant only in the APOE ε4 (−) group. It is unclear whether n-3 PUFAs are ineffective in counteracting the deleterious effects of APOE ε4 in the brain or if adequate levels of long-chain fatty acids before, or during middle age, might mitigate early neurodegenerative processes in at-risk individuals. Intervening with DHA supplements in nondemented APOE ε4 carriers in late life may have questionable benefits, based on recent studies that indicate significant impairment of DHA homeostasis in this group [34,35]. Compared with noncarriers, those who are APOE ε4 (+) achieve lower than expected plasma levels in response to an oral dose of DHA and have marked decrements in whole-body clearance [36].

Thus, accumulating evidence points to APOE as the most important moderator of n-3 PUFA effectiveness in the aging brain [4,13,32,34,35,37]. The relationship between APOE genotype and PUFA-mediated neuroprotection has been investigated in a number of epidemiologic studies of older adult populations; most have reported associations of better cognitive effectiveness in APOE ε4 non-carriers [4,32,37,38]. We found similar results in the subgroup analysis of the entire study cohort, stratified by the APOE ε4 carrier status.

This study is the first to report an association between FOS use and brain structural changes in all three cognitive diagnostic groups; these findings may suggest a potential role for FOSs by reducing neurodegeneration over time. The neuroprotective activities of n-3 PUFAs may be largely mediated through vascular effects; however, other mechanisms have been proposed, including the activities of neuroprotectin D1 (NPD1), a potent lipid mediator synthesized from DHA during periods of oxidative stress [39]. In animal models, NPD1 mitigates AD-related neurodegeneration through downregulation of inflammatory signaling pathways, modulation of amyloid precursor protein cleavage, and removal of apoptotic cells and may play an important role in preventing or slowing progression of dementia [40,41].

Our inability to demonstrate a significant association between duration of FOS use with the cognitive or BV outcomes contradicts the results of the analyses in which exposure was characterized as time-varying FOS use. Although one explanation might be a true lack of a biologic relationship between the length of the exposure and study outcomes, this reasoning seems unlikely given the putative neuroprotective mechanisms ascribed to DHA and the lengthy duration of FOS exposure, particularly among those with NC at baseline. However, it seems more plausible that the null association may be related to the presence of unmeasured confounding. Because the ADNI data set lacked data on factors such as lifestyle and nutrition (fatty fish consumption) or a biologic measure of the n-3 PUFA status, we were unable to consider this information in the analyses [42]. Those who were FOSs exposed for shorter durations may have had long-term exposures to other forms of n-3 PUFAs. In this scenario, the short- and long-term users may have similar levels of exposure, leading to attenuated differences between the two groups. Because individuals who routinely use nutritional supplements generally report better health habits, we conducted sensitivity analyses, controlling for use of vitamin supplements in the models for the primary and secondary outcomes; however, the results were not informative of between-group differences.

In addition, misclassification bias is an important consideration in observational studies that rely on self-reported exposures. Inaccurate recall of details of remote exposures is not an infrequent occurrence; in this study, nondifferential misclassification of exposure duration in the cognitively impaired subgroups may have contributed to the lack of association between FOS duration and the outcomes. ADNI procedures did not require verification of medication use beyond self-report, so these possibilities cannot be eliminated.

Our findings should be evaluated within the context of several other limitations. The first, and the most important, is the possibility that the associations between FOS exposure during the study and the outcomes might be explained by reverse causation (also known as protopathic bias). Because the study population included prevalent users of FOSs, including those with MCI and AD, it is possible that preclinical or subtle cognitive changes were determinants of FOS exposure in these subgroups. Compared with the NC group, AD participants were more than twice as likely to report FOS use, and the duration of exposure (mean, 2.7 years) suggests initiation of supplements could have been coincident with established neurodegenerative processes.

We investigated participant-reported reasons for FOS use and found that few endorsed using FOSs for cognitive benefits. The majority used FOSs for “general health”; however, these participants may have initiated FOSs to treat or prevent multiple conditions, including cognition.

Second, unique aspects of this study cohort may limit the generalizability of our results; ADNI participants are better educated, have higher premorbid intelligent quotients, and are less racially and ethnically diverse than the general elderly population [22].

5. Conclusion

Effective and safe interventions to prevent or delay the onset and treat AD are urgently needed. At present, increasing numbers of older adults use FOSs for cognitive health, without evidence for effectiveness. Although a causal effect of FOS use on cognition and brain atrophy cannot be concluded from our results, they highlight the need for future research on the effects of long-term FOS use on cognitive aging and dementia prevention in middle-aged and older adults.

RESEARCH IN CONTEXT.

  1. Systematic review: Although observational studies have generally reported positive associations between higher quantities of fish consumption and lower rates of cognitive decline or incident Alzheimer’s disease (AD) in nondemented elderly, with few exceptions, the results of randomized, double-blind, placebo-controlled trials of 3- to 24-month treatment with docosahexaenoic acid (DHA) have not supported these findings. Additionally, DHA as a treatment for cognitive impairment in dementia has been shown to be generally ineffective in placebo-controlled trials in mild-to-moderate AD; however, there is some evidence that intervening in very mild AD or in mild cognitive impairment (MCI) may be beneficial.

  2. Interpretation: This retrospective cohort study examines relationships between reported use of DHA (in the form of fish oil supplements [FOSs]) during ADNI and longitudinal changes in cognitive performance and brain volume in normal controls, MCI, and AD subjects. The innovation of this report is the (1) investigation of cognitive and brain structural outcomes associated with FOS use for durations exceeding those used in randomized clinical trials and (2) analysis of longitudinal outcomes in the population stratified by APOE ε4 genotype—a potential moderator of DHA cognitive effects that has not been available in a number of previous observational studies and controlled trials.

  3. Future directions: The effects of long-term FOS use on sensitive biomarkers of cognitive aging should be studied in randomized controlled trials of middle-aged or older adults.

Acknowledgments

Dr. Daiello was supported by K08 HS017735 from the Agency for HealthCare Research and Quality (AHRQ). Dr. Gongvatana was supported by R00AA020235, P01AA019072, and R01NS080655 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Dr. Dunsiger was supported by R03 CA153942 and R01 CA155381 from the National Cancer Institute; R01 NR011295 from the National Institute of Nursing Research; R01HL109116, R01 CA159954, 5T32HL076134, and R01 HL064342 from the National Heart, Lung and Blood Institute; R01AT006948 from the National Center for Complementary and Alternative Medicine; R01 DA021729 and R34 DA031057 from the National Institute on Drug Abuse; and R18 DK075371 from the National Institute of Diabetes and Digestive and Kidney Diseases. Dr. Cohen received support from the National Institutes of Health, including R01 HL089311, U01 CA1503878, R34 DA031057-02, P01 AA019072, R01 NS036524, R01 HL084178, R01 DA020725, R56 DK075119, and R01 MH074368. Dr. Ott received research support from Pfizer, Janssen, Baxter, Eli Lilly, and Avid pharmaceutical companies. He received speaking honorarium and travel expenses from the Alzheimer’s Association. He also received research support from ADNI as a site principal investigator.

Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (National Institutes of Health grant U01 AG024904). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Abbott; Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Amorfix Life Sciences Ltd; AstraZeneca; Bayer HealthCare; BioClinica, Inc; Biogen Idec, Inc; Bristol-Myers Squibb Company; Eisai Inc; Elan Pharmaceuticals, Inc; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc; GE Healthcare; Innogenetics, N.V.; IXICO Ltd; Janssen Alzheimer Immunotherapy Research & Development, LLC; Johnson & Johnson Pharmaceutical Research & Development LLC; Medpace, Inc; Merck & Co, Inc; Meso Scale Diagnostics, LLC; Novartis Pharmaceuticals Corporation; Pfizer Inc; Servier; Synarc Inc; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of California, Los Angeles. This research was also supported by NIH grants P30 AG010129 and K01 AG030514.

Footnotes

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative database (adni.loni.ucla.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.ucla.edu/wpcontent/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.

References

  • 1.Laditka JN, Laditka SB, Tait EM, Tsulukidze MM. Use of dietary supplements for cognitive health: results of a national survey of adults in the United States. Am J Alzheimers Dis Other Demen. 2012;27:55–64. doi: 10.1177/1533317511435662. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.van Gelder BM, Tijhuis M, Kalmijn S, Kromhout D. Fish consumption, n-3 fatty acids, and subsequent 5-y cognitive decline in elderly men: the Zutphen Elderly Study. Am J Clin Nutr. 2007;85:1142–7. doi: 10.1093/ajcn/85.4.1142. [DOI] [PubMed] [Google Scholar]
  • 3.Barberger-Gateau P, Jutand MA, Letenneur L, Larrieu S, Tavernier B, Berr C. Correlates of regular fish consumption in French elderly community dwellers: data from the Three-City study. Eur J Clin Nutr. 2005;59:817–25. doi: 10.1038/sj.ejcn.1602145. [DOI] [PubMed] [Google Scholar]
  • 4.Huang TL, Zandi PP, Tucker KL, Fitzpatrick AL, Kuller LH, Fried LP, et al. Benefits of fatty fish on dementia risk are stronger for those without APOE epsilon4. Neurology. 2005;65:1409–14. doi: 10.1212/01.wnl.0000183148.34197.2e. [DOI] [PubMed] [Google Scholar]
  • 5.Schaefer EJ, Bongard V, Beiser AS, Lamon-Fava S, Robins SJ, Au R, et al. Plasma phosphatidylcholine docosahexaenoic acid content and risk of dementia and Alzheimer disease: the Framingham Heart Study. Arch Neurol. 2006;63:1545–50. doi: 10.1001/archneur.63.11.1545. [DOI] [PubMed] [Google Scholar]
  • 6.Barberger-Gateau P, Letenneur L, Deschamps V, Peres K, Dartigues JF, Renaud S. Fish, meat, and risk of dementia: cohort study. BMJ. 2002;325:932–3. doi: 10.1136/bmj.325.7370.932. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Yurko-Mauro K. Cognitive and cardiovascular benefits of docosahexaenoic acid in aging and cognitive decline. Curr Alzheimer Res. 2010;7:190–6. doi: 10.2174/156720510791050911. [DOI] [PubMed] [Google Scholar]
  • 8.Sinn N, Milte CM, Street SJ, Buckley JD, Coates AM, Petkov J, et al. Effects of n-3 fatty acids, EPA v. DHA, on depressive symptoms, quality of life, memory and executive function in older adults with mild cognitive impairment: a 6-month randomised controlled trial. Br J Nutr. 2011:1–12. doi: 10.1017/S0007114511004788. [DOI] [PubMed] [Google Scholar]
  • 9.Sydenham E, Dangour AD, Lim WS. Omega 3 fatty acid for the prevention of cognitive decline and dementia. Sao Paulo Med J. 2012;130:419. doi: 10.1590/S1516-31802012000600013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.van de Rest O, Geleijnse JM, Kok FJ, van Staveren WA, Dullemeijer C, Olderikkert MG, et al. Effect of fish oil on cognitive performance in older subjects: a randomized, controlled trial. Neurology. 2008;71:430–8. doi: 10.1212/01.wnl.0000324268.45138.86. [DOI] [PubMed] [Google Scholar]
  • 11.Dangour AD, Whitehouse PJ, Rafferty K, Mitchell SA, Smith L, Hawkesworth S, et al. B-vitamins and fatty acids in the prevention and treatment of Alzheimer’s disease and dementia: a systematic review. J Alzheimers Dis. 2010;22:205–24. doi: 10.3233/JAD-2010-090940. [DOI] [PubMed] [Google Scholar]
  • 12.Stough C, Downey L, Silber B, Lloyd J, Kure C, Wesnes K, et al. The effects of 90-day supplementation with the omega-3 essential fatty acid docosahexaenoic acid (DHA) on cognitive function and visual acuity in a healthy aging population. Neurobiol Aging. 2012;33:e821–3. doi: 10.1016/j.neurobiolaging.2011.03.019. [DOI] [PubMed] [Google Scholar]
  • 13.Quinn JF, Raman R, Thomas RG, Yurko-Mauro K, Nelson EB, Van Dyck C, et al. Docosahexaenoic acid supplementation and cognitive decline in Alzheimer disease: a randomized trial. JAMA. 2010;304:1903–11. doi: 10.1001/jama.2010.1510. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Chiu CC, Su KP, Cheng TC, Liu HC, Chang CJ, Dewey ME, et al. The effects of omega-3 fatty acids monotherapy in Alzheimer’s disease and mild cognitive impairment: a preliminary randomized double-blind placebo-controlled study. Prog Neuropsychopharmacol Biol Psychiatry. 2008;32:1538–44. doi: 10.1016/j.pnpbp.2008.05.015. [DOI] [PubMed] [Google Scholar]
  • 15.Terano T, Fujishiro S, Ban T, Yamamoto K, Tanaka T, Noguchi Y, et al. Docosahexaenoic acid supplementation improves the moderately severe dementia from thrombotic cerebrovascular diseases. Lipids. 1999;34(Suppl):S345–6. doi: 10.1007/BF02562338. [DOI] [PubMed] [Google Scholar]
  • 16.Mazereeuw G, Lanctot KL, Chau SA, Swardfager W, Herrmann N. Effects of omega-3 fatty acids on cognitive performance: a meta-analysis. Neurobiol Aging. 2012;33:e1417–29. doi: 10.1016/j.neurobiolaging.2011.12.014. [DOI] [PubMed] [Google Scholar]
  • 17.Freund-Levi Y, Eriksdotter-Jonhagen M, Cederholm T, Basun H, Faxen-Irving G, Garlind A, et al. Omega-3 fatty acid treatment in 174 patients with mild to moderate Alzheimer disease: OmegAD study: a randomized double-blind trial. Arch Neurol. 2006;63:1402–8. doi: 10.1001/archneur.63.10.1402. [DOI] [PubMed] [Google Scholar]
  • 18.Lee LK, Shahar S, Chin AV, Yusoff NA. Docosahexaenoic acid-concentrated fish oil supplementation in subjects with mild cognitive impairment (MCI): a 12-month randomised, double-blind, placebo-controlled trial. Psychopharmacology (Berl) 2013;225:605–12. doi: 10.1007/s00213-012-2848-0. [DOI] [PubMed] [Google Scholar]
  • 19.Landau SM, Harvey D, Madison CM, Koeppe RA, Reiman EM, Foster NL, et al. Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiol Aging. 2011;32:1207–18. doi: 10.1016/j.neurobiolaging.2009.07.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Swaminathan S, Kim S, Shen L, Risacher SL, Foroud T, Pankratz N, et al. Genomic copy number analysis in Alzheimer’s disease and mild cognitive impairment: an ADNI study. Int J Alzheimers Dis. 2011;2011:729478. doi: 10.4061/2011/729478. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Mueller SG, Weiner MW, Thal LJ, Petersen RC, Jack CR, Jagust W, et al. Ways toward an early diagnosis in Alzheimer’s disease: the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Alzheimers Dement. 2005;1:55–66. doi: 10.1016/j.jalz.2005.06.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Petersen RC, Aisen PS, Beckett LA, Donohue MC, Gamst AC, Harvey DJ, et al. Alzheimer’s Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology. 2010;74:201–9. doi: 10.1212/WNL.0b013e3181cb3e25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Jack CR, Jr, Bernstein MA, Fox NC, Thompson P, Alexander G, Harvey D, et al. The Alzheimer’s Disease Neuroimaging Initiative (ADNI): MRI methods. J Magn Reson Imaging. 2008;27:685–91. doi: 10.1002/jmri.21049. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Carmichael O, Schwarz C, Drucker D, Fletcher E, Harvey D, Beckett L, et al. Longitudinal changes in white matter disease and cognition in the first year of the Alzheimer Disease Neuroimaging Initiative. Arch Neurol. 2010;67:1370–8. doi: 10.1001/archneurol.2010.284. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Zeger SL, Liang KY. Longitudinal data analysis for discrete and continuous outcomes. Biometrics. 1986;42:121–30. [PubMed] [Google Scholar]
  • 26.Zeger SL, Liang KY, Albert PS. Models for longitudinal data: a generalized estimating equation approach. Biometrics. 1988;44:1049–60. [PubMed] [Google Scholar]
  • 27.Bowman GL, Silbert LC, Howieson D, Dodge HH, Traber MG, Frei B, et al. Nutrient biomarker patterns, cognitive function, and MRI measures of brain aging. Neurology. 2012;78:241–9. doi: 10.1212/WNL.0b013e3182436598. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Tan ZS, Harris WS, Beiser AS, Au R, Himali JJ, Debette S, et al. Red blood cell omega-3 fatty acid levels and markers of accelerated brain aging. Neurology. 2012;78:658–64. doi: 10.1212/WNL.0b013e318249f6a9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Samieri C, Maillard P, Crivello F, Proust-Lima C, Peuchant E, Helmer C, et al. Plasma long-chain omega-3 fatty acids and atrophy of the medial temporal lobe. Neurology. 2012;79:642–50. doi: 10.1212/WNL.0b013e318264e394. [DOI] [PubMed] [Google Scholar]
  • 30.Rowe CC, Ellis KA, Rimajova M, Bourgeat P, Pike KE, Jones G, et al. Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Neurobiol Aging. 2010;31:1275–83. doi: 10.1016/j.neurobiolaging.2010.04.007. [DOI] [PubMed] [Google Scholar]
  • 31.Rodrigue KM, Kennedy KM, Devous MD, Sr, Rieck JR, Hebrank AC, Diaz-Arrastia R, et al. β-Amyloid burden in healthy aging: regional distribution and cognitive consequences. Neurology. 2012;78:387–95. doi: 10.1212/WNL.0b013e318245d295. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Whalley LJ, Deary IJ, Starr JM, Wahle KW, Rance KA, Bourne VJ, et al. n-3 Fatty acid erythrocyte membrane content, APOE varepsilon4, and cognitive variation: an observational follow-up study in late adulthood. Am J Clin Nutr. 2008;87:449–54. doi: 10.1093/ajcn/87.2.449. [DOI] [PubMed] [Google Scholar]
  • 33.Muldoon MF, Ryan CM, Sheu L, Yao JK, Conklin SM, Manuck SB. Serum phospholipid docosahexaenoic acid is associated with cognitive functioning during middle adulthood. J Nutr. 2010;140:848–53. doi: 10.3945/jn.109.119578. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Cunnane SC, Chouinard-Watkins R, Castellano CA, Barberger-Gateau P. Docosahexaenoic acid homeostasis, brain aging and Alzheimer’s disease: can we reconcile the evidence? Prostaglandins Leukot Essent Fatty Acids. 2013;88:61–70. doi: 10.1016/j.plefa.2012.04.006. [DOI] [PubMed] [Google Scholar]
  • 35.Hennebelle M, Plourde M, Chouinard-Watkins R, Castellano CA, Barberger-Gateau P, Cunnane SC. Ageing and apoE change DHA homeostasis: relevance to age-related cognitive decline. Proc Nutr Soc. 2013:1–7. doi: 10.1017/S0029665113003625. [DOI] [PubMed] [Google Scholar]
  • 36.Chouinard-Watkins R, Rioux-Perreault C, Fortier M, Tremblay-Mercier J, Zhang Y, Lawrence P, et al. Disturbance in uniformly 13C-labelled DHA metabolism in elderly human subjects carrying the apoE epsilon4 allele. Br J Nutr. 2013;110:1751–9. doi: 10.1017/S0007114513001268. [DOI] [PubMed] [Google Scholar]
  • 37.Barberger-Gateau P, Raffaitin C, Letenneur L, Berr C, Tzourio C, Dartigues JF, et al. Dietary patterns and risk of dementia: the Three-City cohort study. Neurology. 2007;69:1921–30. doi: 10.1212/01.wnl.0000278116.37320.52. [DOI] [PubMed] [Google Scholar]
  • 38.Beydoun MA, Kaufman JS, Satia JA, Rosamond W, Folsom AR. Plasma n-3 fatty acids and the risk of cognitive decline in older adults: the Atherosclerosis Risk in Communities Study. Am J Clin Nutr. 2007;85:1103–11. doi: 10.1093/ajcn/85.4.1103. [DOI] [PubMed] [Google Scholar]
  • 39.Calandria JM, Mukherjee PK, de Rivero Vaccari JC, Zhu M, Petasis NA, Bazan NG. Ataxin-1 poly(Q)-induced proteotoxic stress and apoptosis are attenuated in neural cells by docosahexaenoic acid-derived neuroprotectin D1. J Biol Chem. 2012;287:23726–39. doi: 10.1074/jbc.M111.287078. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Lukiw WJ, Bazan NG. Inflammatory, apoptotic, and survival gene signaling in Alzheimer’s disease. A review on the bioactivity of neuroprotectin D1 and apoptosis. Mol Neurobiol. 2010;42:10–6. doi: 10.1007/s12035-010-8126-4. [DOI] [PubMed] [Google Scholar]
  • 41.Zhao Y, Calon F, Julien C, Winkler JW, Petasis NA, Lukiw WJ, et al. Docosahexaenoic acid-derived neuroprotectin D1 induces neuronal survival via secretase- and PPARgamma-mediated mechanisms in Alzheimer’s disease models. PLoS One. 2011;6:e15816. doi: 10.1371/journal.pone.0015816. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Morris MC. Nutritional determinants of cognitive aging and dementia. Proc Nutr Soc. 2012;71:1–13. doi: 10.1017/S0029665111003296. [DOI] [PubMed] [Google Scholar]

RESOURCES