DHA in plasma and post-mortem human brain

Brain DHA

In primate, pig and rodent models, when n-3 intake is severely deficient for extended periods, brain DHA also decreases across all cell types and regions, in association with lower scores on cognitive and behavioural tests⁽ Reference Calon and Cole ^{25 ,} Reference Brenna and Diau ^{28 –} Reference Novak, Dyer and Innis ^{31 )}. AD is now widely associated with lower fish and DHA intake, so it would be logical that post-mortem brain samples of patients with a definitive diagnosis of AD also contained lower DHA. Indeed, in the hippocampus, which is central to memory processing and learning, AD patients reportedly do have lower DHA⁽ Reference Soderberg, Edlund and Kristensson ^{32 ,} Reference Lukiw, Cui and Marcheselli ^{33 )}. However, in the temporal and frontal cortices which are also affected in AD, DHA is almost always the same as in the controls (Fig. 1). Studies reporting lower DHA in the AD brain show that other fatty acids are also lower, particularly n-6 PUFA⁽ Reference Astarita, Jung and Berchtold ^{35 ,} Reference Corrigan, Horrobin and Skinner ^{41 ,} Reference Guan, Wang and Cairns ^{44 ,} Reference Prasad, Lovell and Yatin ^{46 )}. Thus, the effect of AD is not specific to DHA which is contrary to what would be expected if only n-3 fatty acid intake were deficient.

Fig. 1. Summary of the published literature on brain and blood DHA in Alzheimer's disease. The symbols represent the results of individual studies using each study's control group as the reference (100 %; dotted line). The papers from which these DHA data are obtained are as follows: A, Arsenault et al.⁽ Reference Arsenault, Matthan and Scott ^{34 )}; B, Astarita et al.⁽ Reference Astarita, Jung and Berchtold ^{35 )}; C, Boston et al.⁽ Reference Boston, Bennett and Horrobin ^{36 )}; D, Brooksbank et al.⁽ Reference Brooksbank and Martinez ^{37 )}; E, Cherubini et al.⁽ Reference Cherubini, Andres-Lacueva and Martin ^{38 )}; F, Conquer et al.⁽ Reference Conquer, Tierney and Zecevic ^{39 )}; G, Corrigan et al.⁽ Reference Corrigan, Van Rhijn and Ijomah ^{40 )}; H, Corrigan et al.⁽ Reference Corrigan, Horrobin and Skinner ^{41 )}; I, Cunnane et al.⁽ Reference Cunnane, Schneider and Tangney ^{42 )}; J, Fraser et al.⁽ Reference Fraser, Tayler and Love ^{43 )}; K, Guan et al.⁽ Reference Guan, Wang and Cairns ^{44 )}; L, Laurin et al.⁽ Reference Laurin, Verreault and Lindsay ^{45 )}; M, Prasad et al.⁽ Reference Prasad, Lovell and Yatin ^{46 )}; N, Selley et al.⁽ Reference Selley ^{47 )}; O, Skinner et al.⁽ Reference Skinner, Watt and Besson ^{48 )}; P, Söderberg et al.⁽ Reference Soderberg, Edlund and Kristensson ^{32 )}; Q, Tully et al.⁽ Reference Tully, Roche and Doyle ^{49 )}. F,T,P, frontal, temporal and/or parietal cortex; P-H, para-hippocampus; H, hippocampus; P-TFA, plasma total fatty acids; P-PL, plasma phospholipids; P-CE, plasma cholesteryl esters; RBC, red blood cells.

There are many potential methodological reasons for the observed lack of agreement between the apparently low DHA intakes in AD yet frequently normal DHA levels in the brain⁽ Reference Cunnane, Plourde and Pifferi ^{12 )}. Crucial among these are the ‘healthy’ controls against which the AD cases are compared as well as the very marked extent of regional brain atrophy associated with ageing regardless of the presence of neurological disease⁽ Reference Guan, Wang and Cairns ^{44 ,} Reference Svennerholm, Boström and Jungbjer ^{50 )}. Furthermore, the basis for classifying a patient as having AD, i.e. whether on clinical cognitive criteria or on neuropathological score, may not give consistent results since senile plaques are increasingly recognised as being present in a significant proportion of cognitively normal elderly persons⁽ Reference Aizenstein, Nebes and Saxton ^{51 –} Reference Duyckaerts and Hauw ^{53 )}. Hence, there is a risk that post-mortem samples from brain banks for which cognitive status is not known at the time of death could be misclassified if based solely on neuropathological scores. It also appears that membrane PL in the cortex can tenaciously retain DHA and that a more discrete and specific subcellular pool or membrane pool of DHA may have to be measured⁽ Reference Fraser, Tayler and Love ^{43 )}. Brain membrane DHA cycles rapidly between PL and free DHA via DHA-CoA⁽ Reference Umhau, Zhou and Carson ^{54 ,} Reference Chen, Green and Orr ^{55 )}, and the deteriorating efficacy of this process could theoretically contribute to the neurodegenerative processes. Thus, the key issue in relation to post-mortem tissue analysis is that the time to lipid extraction is rarely less than 4–5 h yet DHA turnover is on the order of minutes, if not seconds. Since the turnover of DHA towards resolvins and neuroprotectins are orders of magnitude lower than the amount of DHA in the brain NEFA pool, truly ‘physiological’ amounts of these products are extremely difficult to measure, especially in human subjects⁽ Reference Bazan, Molina and Gordon ^{23 ,} Reference Serhan and Petasis ^{56 )}. As also noted elsewhere, these and other issues severely constrain the validity and hence the utility of DHA measurements on human post-mortem brain samples⁽ Reference Cunnane, Chouinard-Watkins and Castellano ^{57 )}.

DHA homeostasis during ageing and apoE

We propose that even when collected under hypothetically ideal conditions (zero delay; perfectly matched, cognitively healthy controls, etc.), data obtained from single blood samples are too limited to fully understand possible changes in DHA metabolism due to genotype, ageing or neurodegenerative disease. However, isotopically labelled DHA is emerging as a useful tool to assess how the metabolism of DHA changes with age. Indeed, in a relatively simple study design, it was clear that the clearance of a 50 mg oral dose of uniformly carbon-13 labelled DHA (¹³C-DHA) from the blood over 1 month was much slower in healthy 76-year-old compared with 27-year-old adults⁽ Reference Plourde, Chouinard-Watkins and Vandal ^{67 )}. These results were similar to our earlier report that the increase in plasma DHA during a short-term treatment with fish oil was higher in healthy older persons⁽ Reference Vandal, Freemantle and Tremblay-Mercier ^{68 )}. ¹³C-DHA enrichment in plasma NEFA and TAG of older adults was most affected (four- to fivefold higher than in the young adults) but its enrichment in PL and CE ¹³C-DHA was also affected. The doubling of ¹³C-DHA enrichment in plasma PL and CE emerged only after about 7 d post-dose, suggesting slower DHA clearance through plasma lipid classes, i.e. an altered plasma ‘DHA wave’ in older adults (Fig. 2)⁽ Reference Plourde, Chouinard-Watkins and Vandal ^{67 )}.

Fig. 2. Delayed plasma clearance of carbon 13-labelled DHA (¹³C-DHA) during healthy ageing, adapted from Plourde et al.⁽ Reference Plourde, Chouinard-Watkins and Vandal ^{67 )}. Plasma ¹³C-DHA concentration was followed over 28 d after the oral administration of a single 50 mg dose of ¹³C-DHA in young (27 years; n 6) and elderly (76 years; n 6) participants. In older adults, plasma tracer concentration in NEFA and TAG was four to fivefold higher 4 h after giving the oral dose and about twofold higher 1–4 weeks later in phospholipids (PL) and cholesteryl esters (CE).

Clearly, therefore, healthy ageing seems to change DHA metabolism and, hence, homeostasis in human subjects. Notwithstanding the limited extent to which the kinetic behaviour of a tracer can be compared with a single plasma fatty acid measurement, the difference in ¹³C-DHA homeostasis in the elderly seems to reflect the results observed in two studies in which lower DHA was reported in plasma PL yet higher DHA was reported in plasma CE of AD patients⁽ Reference Corrigan, Van Rhijn and Ijomah ^{40 ,} Reference Cunnane, Schneider and Tangney ^{42 )}. The minimally invasive nature of this type of experiment makes it difficult to invoke a particular mechanism but one could speculate that the changing sensitivity of endothelial lipoprotein lipase could be involved in this age-associated difference in DHA homeostasis⁽ Reference Millar, Lichtenstein and Cuchel ^{69 )}.

ApoE4 carriers are at significantly higher risk of AD⁽ Reference Jack, Knopman and Jagust ^{70 ,} Reference Jack, Petersen and Xu ^{71 )}. It is now emerging that the apoE4 status also affects DHA metabolism in human subjects⁽ Reference Barberger-Gateau, Samieri and Feart ^{27 ,} Reference Chouinard-Watkins, Rioux-Perreault and Fortier ^{72 ,} Reference Plourde, Vohl and Vandal ^{73 )}. This interaction may help explain why the protective association of higher dietary intake of fish⁽ Reference Huang, Zandi and Tucker ^{74 ,} Reference Barberger-Gateau, Raffaitin and Letenneur ^{75 )} or higher erythrocyte total n-3 fatty acids⁽ Reference Whalley, Deary and Starr ^{65 )} is generally limited to non-carriers of apoE4. Measuring expired ¹³C-CO₂ after dosing with ¹³C-DHA permits the estimation of the whole body half-life of DHA in healthy older adults, which is of the order of 32 d in carriers of apoE4 and 140 d in non-carriers of apoE4 ⁽ Reference Chouinard-Watkins, Rioux-Perreault and Fortier ^{72 )}. Ageing seems not to affect the whole body half-life of DHA although the small sample size makes these results still somewhat preliminary⁽ Reference Plourde, Chouinard-Watkins and Vandal ^{67 )}.

Using positron emission tomography and the tracer, ¹¹C-DHA, human brain turnover of DHA has been estimated to be about 4 mg/d, giving rise to a half-life of brain DHA of about 2·5 years⁽ Reference Umhau, Zhou and Carson ^{54 )}. Hence, the half-life of brain DHA is much longer than its whole body half-life. Perhaps further assessments of the brain or whole body half-life of DHA could provide some insight into the current ineffectiveness of DHA supplements in AD despite the fact that these supplements typically supply several fold the brain's apparent daily turnover of DHA⁽ Reference Cunnane, Plourde and Pifferi ^{12 )}.

ApoE4 seems also to supress the plasma DHA response to a fish oil supplement⁽ Reference Plourde, Vohl and Vandal ^{73 )} and the metabolism of an oral dose of ¹³C-DHA⁽ Reference Chouinard-Watkins, Rioux-Perreault and Fortier ^{72 )}, an effect somewhat opposite to that observed with healthy ageing. For up to 28 d after a single oral dose of ¹³C-DHA, carriers of apoE4 have a slightly lower concentration of plasma ¹³C-DHA compared with non-carriers⁽ Reference Chouinard-Watkins, Rioux-Perreault and Fortier ^{72 )}. When the tracer is given both before and again after a 5-month period of DHA+EPA supplementation, the apoE4 carriers had a greater accumulation of the tracer in plasma after supplementation compared with the non-carriers, again suggesting slower clearance of DHA to and/or use by tissues (Fig. 3). Hence, two established risk factors for AD (ageing and apoE4) both significantly change DHA homeostasis but possibly in different ways.

Fig. 3. Plasma carbon 13-labelled DHA (¹³C-DHA) concentration over 28 d after a single oral dose of 40 mg ¹³C-DHA. Results expressed as means (sem) show the plasma ¹³C-DHA status (a) pre- (n 6) and (b) post- (n 4) supplementation of 5 months with 1·8 g/d EPA +1·4 g/d DHA in apoE ɛ4 carriers (apoE4+; ○) and non-carriers (apoE4-; ●).

Linking dietary and plasma DHA

Habitual DHA intake is commonly estimated to be <250 mg/d⁽ Reference Harris, Mozaffarian and Lefevre ^{76 –} Reference Meyer ^{78 )} but this is a difficult and laborious measurement and subject to high day-to-day variability depending on the frequency of fish or shellfish consumption. Hence, it would be useful if DHA intake and plasma DHA were highly correlated because plasma DHA measurement is now technically simple and reliable, so it could potentially be a surrogate for dietary DHA measurement. There is indeed a good positive correlation between dietary and plasma intake for DHA consumption, especially at DHA intakes towards 1000 mg/d, during which plasma DHA rises to a maximum of about 4 % in plasma total lipids. However, DHA always seems to be present in plasma, even when DHA intake is negligible; thus, vegans consuming no known dietary sources of DHA still have about 0·5 % DHA in plasma total lipids⁽ Reference Sanders, Hinds and Pereira ^{79 )}. The problem is that there are relatively few reports on which to build the relationship of dietary to plasma DHA. At DHA intakes between 0 and 50 mg/d, DHA is between 0·5 and 1·2 % of plasma total lipids, but the spread in these data is large⁽ Reference Cunnane, Chouinard-Watkins and Castellano ^{57 )}. A value of 0·5 % DHA in plasma total lipids therefore seems to be at or close to the lower limit possible of plasma DHA in healthy adults.

The AD cases we have studied had 1·0 % DHA in plasma total lipids, which empirically corroborates very low DHA intake, yet they had ‘normal’ DHA in the PL of brain cortical grey matter⁽ Reference Cunnane, Schneider and Tangney ^{42 )}. Plasma DHA does not rise in human subjects given EPA or α-linolenic acid supplements, even in vegans⁽ Reference James, Ursin and Cleland ^{80 –} Reference Horrobin, Fokkema and Muskiet ^{82 )}. The conundrum therefore is: how are plasma (or brain) DHA levels maintained when DHA intakes are very low to negligible? We speculate that with changes in DHA metabolism and homeostasis during age-related cognitive decline, the diet–plasma relation of DHA may shift, explaining why with lower DHA intake, a population with age-related cognitive decline appears to have the same plasma DHA concentration as healthy elderly even though the availability of DHA to the tissues may be reduced⁽ Reference Lopez, Kritz-Silverstein and Barrett Connor ^{83 )}. The lack of an established reference lipid class in blood (PL, CE, TAG or NEFA, erythrocytes, etc.) for DHA measurements relative to intake still hampers the extent to which plasma DHA data from various reports can be compared in relation to ageing, genotype and risk of cognitive decline. This area clearly needs further research but suffice it to say that it is becoming increasingly important to take into account changing DHA homeostasis in the study of ageing population, especially in a context of age-related cognitive decline or AD.