Comparative Lipidomic Analysis of Mouse and Human Brain with Alzheimer Disease*

  1. Gilbert Di Paolo‡§,2
  1. From the Departments of ‡Pathology and Cell Biology and
  2. **Neurology,
  3. §Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, New York 10032,
  4. the Life and Health Science Research Institute (ICVS), School of Health Sciences,
  5. the ‖Life and Health Science Research Institute/3B's (Biomaterials, Biodegradables and Biomimetics), Portuguese Government Associate Laboratory, University of Minho, 4710-057 Braga, Portugal,
  6. the ‡‡Department of Biochemistry, National University of Singapore, Singapore 117597, and
  7. the §§Department of Biological Sciences, National University of Singapore, Singapore 117543
  1. ↵1 To whom correspondence may be addressed: Centre for Life Sciences, 28 Medical Dr., 04-21 Singapore 117456. Tel.: 65-6516-6683; E-mail: guanghou_shui{at}nuhs.edu.sg.
  2. ↵2 To whom correspondence may be addressed: 630 West 168th St., P&S 12–510, New York, NY 10032. Tel.: 212-304-5500; E-mail: gil.dipaolo{at}columbia.edu.

Background: Lipid dyshomeostasis has been linked to Alzheimer disease (AD).

Results: Lipidomic analyses of brain tissue from AD patients reveal region-specific changes in multiple bioactive lipids, some of which are phenocopied in AD mouse models.

Conclusion: Lipid anomalies observed in AD may be linked to pathogenesis, including endolysosomal dysfunction.

Significance: This study highlights the hypothesis-generating potential of lipidomics and its applicability to other diseases.

 
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Abstract

Lipids are key regulators of brain function and have been increasingly implicated in neurodegenerative disorders including Alzheimer disease (AD). Here, a systems-based approach was employed to determine the lipidome of brain tissues affected by AD. Specifically, we used liquid chromatography-mass spectrometry to profile extracts from the prefrontal cortex, entorhinal cortex, and cerebellum of late-onset AD (LOAD) patients, as well as the forebrain of three transgenic familial AD (FAD) mouse models. Although the cerebellum lacked major alterations in lipid composition, we found an elevation of a signaling pool of diacylglycerol as well as sphingolipids in the prefrontal cortex of AD patients. Furthermore, the diseased entorhinal cortex showed specific enrichment of lysobisphosphatidic acid, sphingomyelin, the ganglioside GM3, and cholesterol esters, all of which suggest common pathogenic mechanisms associated with endolysosomal storage disorders. Importantly, a significant increase in cholesterol esters and GM3 was recapitulated in the transgenic FAD models, suggesting that these mice are relevant tools to study aberrant lipid metabolism of endolysosomal dysfunction associated with AD. Finally, genetic ablation of phospholipase D2, which rescues the synaptic and behavioral deficits of an FAD mouse model, fully normalizes GM3 levels. These data thus unmask a cross-talk between the metabolism of phosphatidic acid, the product of phospholipase D2, and gangliosides, and point to a central role of ganglioside anomalies in AD pathogenesis. Overall, our study highlights the hypothesis generating potential of lipidomics and identifies novel region-specific lipid anomalies potentially linked to AD pathogenesis.

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Introduction

Alzheimer disease (AD)3 is a debilitating neurodegenerative disorder that afflicts millions of adults worldwide and the main cause of late life dementia. Three outstanding neuropathological features were noted in the original analysis from Alois Alzheimer, namely senile plaques, neurofibrillary tangles, and lipid granule accumulation (1). Based on the available molecular and biochemical techniques of the ensuing years, plaques and neurofibrillary tangles were viewed as consistent features of the AD brain and thus more heavily studied than changes in brain lipid metabolism (1). It is now common knowledge that the major molecular component of senile plaques is aggregated amyloid-β (Aβ), which is generated from the amyloid precursor protein (APP) via the sequential cleavage of APP by β-secretase β-site APP cleavage enzyme 1 (BACE1) and the γ-secretase complex, which contains a catalytic component, presenilin 1 or 2 (PS1 or 2). Although rare autosomal dominant mutations in APP and PS1 or 2 lead to early-onset familial AD (FAD) (2), the majority of AD cases are classified as late onset AD (LOAD). A major risk factor for LOAD is the E4 allelic variant of ApoE, which encodes a protein involved in cholesterol metabolism and lipid transport (3). Importantly, a variety of genes have been recently linked to LOAD through genomewide association studies and are directly or indirectly connected to lipid metabolism or cellular membrane dynamics (4, 5).

Strong evidence now links AD with aberrant lipid homeostasis, in part for the following reasons (6, 7). First, neuronal lipid composition regulates the trafficking and/or activity of the key membrane-bound proteins controlling Aβ levels, including APP, BACE1, and presenilins. For instance, γ-secretase activity is regulated by membrane levels of cholesterol and sphingomyelin (SM) (8). Second, Aβ exerts its cytotoxic effects primarily by perturbing cellular membranes, in part by modulating the activity of phospholipases, such as PLA2 (9), PLC (10), and phospholipase D2 (PLD2) (11). Third, lipids, such as ganglioside GM1, modulate the pathogenic potential of Aβ by affecting its propensity to aggregate (12). It is thus clear that an in-depth analysis of brain lipid composition changes in AD would provide a basis for further investigation of cell signaling and metabolic pathways that are disrupted in AD. Advances in lipidomics, particularly electrospray ionization-mass spectrometry, have facilitated the precise profiling of lipid species within tissues, including low abundance lipid classes that participate in cell signaling and membrane trafficking (13). Several studies focusing on defined families of lipids have made use of this technology to analyze lipid composition from AD brain tissue, showing changes in plasmalogen phosphatidylethanolamine (pPE) (14), sulfatide (Sulf) (15), ceramide (Cer), galactosylceramide (GalCer), cholesterol (16), and alkylacylglycerophosphocholine (17). Our own study has shown that a specific molecular species of phosphatidic acid (PA) previously linked to neurodegeneration in the fly (18) accumulates in the forebrain of old Swedish APP (swAPP) mice (11).

In this study, we present the lipidomic analysis of postmortem brain tissue obtained from patients with LOAD, specifically regions that typically are either moderately (prefrontal cortex, PFC) or severely (entorhinal cortex, ERC) affected in AD as well as a control region (cerebellum, CRB) that is largely unaffected by this disorder (19, 20). We also provide the lipidome of forebrain tissue obtained from three commonly used transgenic mouse models of FAD, namely (i) PSEN1M146V (PS1) (21), (ii) the Swedish mutant of APPK670N,M671L (APP) (22), and (iii) PS1-APP double transgenic (23) lines. Using a combination of normal phase and reverse phase LC-MS approaches, we analyzed 26 different lipid subclasses including lysophospholipids, glycerophospholipids, sphingolipids, glycerolipids, and sterols, covering over 300 lipid species. Our data show that multiple lipid subclasses are dysregulated in both the human AD tissue and AD mouse models, uncovering novel lipid pathways that may be linked to abnormal cellular activity and thus potential targets for further studies.

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EXPERIMENTAL PROCEDURES

Annotation of Lipid Species

Glycerophospholipids, lysophospholipids, and diacylglycerol (DAG) were annotated as <lipid subclass> <total fatty acyl chain length>:<total number of unsaturated bonds>. Sphingolipids were annotated as <lipid subclass> <sphinogoid base residue>/<fatty acyl residue>. Triacylglycerol (TAG) was annotated as <TAG> <total fatty acyl chain length>:<total number of unsaturated bonds>/<fatty acyl residue>). Cholesterol ester (CE) was annotated <CE> − <fatty acyl residue>.

Human Brain Tissue

Frozen postmortem brain tissue samples were obtained from the New York Brain Bank at Columbia University Medical Center. Three different brain regions were sampled from different subjects: PFC, ERC, and CRB. Morphologically, each dissected region consisted predominantly of gray matter with minimal associated underlying white matter. AD was defined as “high probability of AD” based on NIA, National Institutes of Health-Reagan Institute (NIA-RI) criteria. Controls were free of major neuropathological diagnoses, and either did “not meet” or met “low probability of AD” by NIA-RI criteria. Further sample information, including a semiquantitative assessment of neuronal loss, neurofibrillary tangles, amyloid neuritic plaques, and Lewy body burdens, for the PFC and ERC, is presented in supplemental Dataset S3. On average, the ERC exhibited higher levels of pathology than the PFC in LOAD samples.

AD Mouse Models

A mixed population of wild-type, PS1, APP, and PS1-APP mice were described previously (21,–,24), aged between 9 and 11.5 months, were used for full lipidomics analysis in this study. An older group of wild-type and APP mice aged between 14 and 15 months were used for targeted PA analysis. SwAPP mice with the Pld2+/+ and Pld2−/− genotypes with an average age of 12 months were described before (11) and used to examine the changes in sphingolipids and cholesterol ester. All mice were sacrificed by cervical dislocation, the forebrain dissected immediately and frozen in liquid nitrogen before storage at −80 °C.

Analysis of Lipids Using High Performance Liquid Chromatography-Mass Spectrometry

Lipid extracts were prepared using a modified Bligh/Dyer extraction procedure, spiked with appropriate internal standards, and analyzed using an Agilent 1200 HPLC system coupled with an Applied Biosystem Triple Quadrupole/Ion Trap mass spectrometer (3200Qtrap). Further cross-lab validation of our approach can be found in our previous work (25). Separation of individual lipid classes of polar lipids by normal phase HPLC was carried out using a Phenomenex Luna 3μ silica column (inner diameter 150 × 2.0 mm) with the following conditions: mobile phase A (chloroform:methanol:ammonium hydroxide, 89.5:10:0.5), B (chloroform:methanol:ammonium hydroxide:water, 55:39:0.5:5.5); flow rate of 300 μl/min; 5% B for 3 min, then linearly changed to 30% B over 24 min and maintained for 5 min, and then linearly changed to 70% B over 5 min and maintained for 7 min. Then, the gradient was changed back to the original ratio over 5 min and maintained for 6 min for column re-equilibration. Multiple reaction monitoring transitions were set up for quantitative analysis of various polar lipids (26, 27). Individual lipid species were quantified by referencing to spiked internal standards. PC, 14:0/14:0; PE, 14:0/14:0; PS, 14:0/14:0; PA, 17:0/17:0; PG, 14:0/14:0; d31-PI, 18:1/16:0; C8-GluCer, C17-Cer, C12-Sulfatide, and C12-SM were obtained from Avanti Polar Lipids (Alabaster, AL). Dioctanoyl phosphatidylinositol (PI, 16:0-PI) was used for lysophosphatidylinositol quantitation and obtained from Echelon Biosciences, Inc. (Salt Lake City, UT).

TAG, DAG, and CE were analyzed using a modified version of reverse phase HPLC-electrospray ionization-MS described previously (28). Briefly, separation of TAG and CE from polar lipids was carried out on an Agilent Zorbax Eclipse XDB-C18 column (inner diameter 4.6 × 150 mm) using an isocratic mobile phase chloroform, methanol, 0.1 m ammonium acetate (100:100:4) at a flow rate of 250 μl/min. TAG were calculated as relative contents to the spiked d5-TAG 48:0 internal standard (CDN isotopes), whereas cholesterol esters were normalized to corresponding d6-C18 cholesterol ester (CDN isotopes). DAG species were quantified using 4-methyl 16:0 diether DAG as an internal standard (Avanti Polar Lipids). Free cholesterol was analyzed by reverse phase HPLC atmospheric pressure chemical ionization MS, utilizing the same XDB-C18 column as above but with chloroform:methanol, 1:1 (v/v), as the mobile phase at a flow rate of 500 μl/min (29). The instrument was operated in the positive mode with a vaporizer temperature of 500 °C and corona current of 3 μA. Free cholesterol was quantified relative to spiked d6-cholesterol (CDN isotopes) internal standard.

Data Analysis and Presentation

Lipid levels for each sample were calculated by summing up the total number of moles of all lipid species measured by all three LC-MS methodologies, and then normalizing that total to mol %. The final data are presented as mean mol % with error bars showing mean ± S.E. All lipid species in the human samples and more than 98% of the lipid species measured in the mouse samples were found to have equal variance (data not shown). For the human samples, a two-tailed Student's t test was used for statistical analysis. The mouse data were analyzed by one-way analysis of variance followed by post hoc multiple comparisons Tukey range test as indicated accordingly. In all cases, *, p < 0.05; **, p < 0.01; ***, p < 0.001. For all bar graphs, error bars represent the mean ± S.E.

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RESULTS

Comparative Lipid Profiling of Postmortem Human Brain Tissue

Postmortem brain tissues obtained from both control and AD patients with similar average age, cold, and frozen postmortem intervals were used in our analysis (Table 1). Depending on brain region, ∼44–48% of the lipidome measured in our analysis was made up of free cholesterol (Fig. 1, supplemental Fig. S1A and Dataset S1A). The next largest group is comprised of the glycerophospholipids, the bulk of which is made up of phosphatidylcholine (PC) (14.4–17.5%), phosphatidylethanolamine (PE) (4.0–6.3%), and pPE (8.0–9.8%). Other glycerophospholipids of intermediate abundance are phosphatidylserine (PS) (2.5–4.2%), phosphatidylinositol (PI) (2.4%-2.8%), and ether PC (ePC) (1.3%). Very low abundance glycerophospholipids were also measured including lysophospholipids (0.84–1.12% total), PA (0.16–0.25%), phosphatidylglycerol (PG) (0.06–0.09%), and lyso-bisphosphatidic acid (LBPA) (0.013–0.025%). In addition, we also measured a wide array of sphingolipids such as SM (7.7–9.5%), Cer (1.0–1.3%), glucosylceramide (GluCer) (1.4–2.6%), GalCer (1.4–2.4%), ganglioside GM3 (0.050–0.083%), and Sulf (1.1–2.1%). Comparatively, glycerolipids such as DAG (0.33–0.62%) and TAG (0.05–0.10%) and sterol derivative CE (0.31–0.62%) make up a very small proportion of the entire lipidome. The detailed molecular distribution of the individual lipid species measured can be found in supplemental Figs. S2–S4 and Dataset S1B. The PFC and ERC had a similar fatty acyl chain profile, consisting mostly of medium (36C) and long (>38C) chain fatty acyls and with either monounsaturated or polyunsaturated fatty acids with 4 or 6 bonds (Fig. 3, A, B, D, and E). Surprisingly, the CRB exhibited a unique fatty acyl profile, with the highest proportion from medium-chain length (36C) and monounsaturated phospholipids (supplemental Fig. S1, B and C). However, all three brain regions are highly similar in terms of sphingolipid chain length, with the majority being long (>42C) or medium (36C) chain length (Fig. 3, C and F, and supplemental Fig. S1D).

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TABLE 1

Average age at time of death, cold, and frozen postmortem intervals of patients used in this study

FIGURE 1.
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FIGURE 1.

Postmortem human brain tissue lipid composition is altered in LOAD. Various lipid changes are seen in PFC (A) and ERC (B) tissues. Lipid subclasses are expressed as mean mol % of all lipid species measured with error bars indicating mean ± S.E. The sample size for each brain region analyzed is shown in Table 1. The absolute level of individual lipid species is presented in supplemental Dataset S1.

Postmortem AD Tissue Display Region-specific Differences in Lipid Metabolism

Overall, whereas the lipid profile of the CRB from AD patients was comparable with that of control subjects (supplemental Figs. S1 and S4), the lipid profiles of both PFC and ERC were affected by the disease (Fig. 1). In the PFC, the most striking change was observed for DAG, which showed an overall 1.8-fold increase in AD (Figs. 1A and 4, and supplemental Fig. S2 and Dataset S1). Although numerous species of DAG were up-regulated, a pool of DAG (38:4) believed to derive from the PLC-mediated cleavage of phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) and thus involved in signaling (30), was up-regulated by ∼2.1-fold (supplemental Fig. S2). Analysis of glycerophospholipids showed an overall decrease in the levels of lysophosphatidylcholine (LPC) and lyso ether PC (LPCe) (∼19 and ∼13%, respectively), but no changes in PC. There was a clear decrease in total PE (∼25%), including major PE species, 40:6, 38:6, and 38:4. Contrary to a previous report (14), lower pPE levels were not seen except for a slight decrease in a single species, PE, 38:6p. Specific pools of ePC, 34:0p, 34:1p, and 32:1e, were up-regulated, whereas PC 34:0e was down-regulated. In the overall fatty acyl distribution, there was a decrease in long-chain fatty acids (>40C) with a corresponding increase in short-chain fatty acids (34C) (Fig. 3, A and B). Sphingolipid metabolism was also perturbed in AD samples, with a ∼25% decrease in medium length species (Fig. 3C). Although medium length SM d18:0/20:0 and d18:1/20:0 were subtly down-regulated, long-chain species SM d18:1/22:1 and d18:1/26:1 were up-regulated. The overall Cer levels were increased by ∼33%, mostly due to the major Cer species d18:1/18:0. However, there was a clear metabolic shift toward an increase of simple glycosphingolipids GluCer (∼43%) and GalCer (∼32%), perhaps reflecting increased catabolism of Sulf (which were decreased by ∼25%) (see also Ref. 15).

The ERC tissue exhibited a different pattern of lipid alterations compared with the PFC (Figs. 1B and 4, supplemental Fig. S3 and Dataset S1). LBPA (also called bis(monoacylglyceryl)phosphate), a lipid that is synthesized primarily from PG and highly enriched in the endolysosomal system (31), was highly enriched in AD (∼1.8-fold), including numerous species such as 32:1, 34:3, 36:3, 36:1, and 38:5 (supplemental Fig. S3). This region also showed increased levels in multiple species of the polyunsaturated lipid pools including PC 38:4p, 40:5p, and PE 36:5, 38:5, and 36:3p. Unlike the PFC, AD-affected ERC also exhibited alterations in different subclasses of sphingolipids, specifically increases in SM and ganglioside GM3 (∼20 and ∼64%, respectively). Strikingly, whereas SM species with a shorter fatty acyl residue including d18:0/18:0, d18:1/16:1, and d18:1/18:0 were selectively enriched, GM3 enrichment was restricted mainly to those with longer chain fatty acyl residues such as d18:0/24:0, d18:1/22:0, and d18:1/24:0 (supplemental Fig. S3). The selective increase in higher abundance SM led to a modest boost in overall short-chain sphingolipids distribution (Fig. 3F). Last, levels of CE, i.e. lipids typically enriched in lipid droplets (31), were significantly higher in ERC with AD (∼1.7-fold), particularly in the form of CE-16:1, CE-16:0, and CE-18:1. Interestingly, select pools of TAG (e.g. TAG 56:7(22:6) and 56:5(18:1)), which are also enriched in lipid droplets (32), accumulated in AD-affected ERC (supplemental Fig. S3).

Comparative Lipid Profiling of FAD Mouse Models Forebrain Brain Tissue

To determine whether any of the lipid changes seen in LOAD are phenocopied in the brain of commonly used mouse models of FAD, we characterized the forebrain lipid composition of WT, PS1, APP, and PS1-APP mice within an age range (i.e. 9–11.5 months) where transgenic mice have been characterized for various biochemical, morphological, electrophysiological, and behavioral phenotypes. Although the PS1 mice exhibit subtly increased Aβ42 levels without noticeable pathology (21), the APP mice show significantly elevated Aβ levels and develop numerous plaques between 9 and 13 months (22). Comparatively, Aβ production is markedly increased in the PS1-APP mice, which begin developing a severe plaque burden by 6–7 months (23). Reflecting in part the severity of Aβ burden, synaptic and behavioral impairments are least apparent in the PS1 mice and highly exacerbated in the PS1-APP mice (23, 24).

The comprehensive lipid composition of the forebrain tissue of the different mice is shown in Fig. 2, supplemental Fig. S5 and Dataset S2. As with the case of the human AD tissue, free cholesterol levels occupied the bulk of the lipidome we measured. The remainder of the WT mouse forebrain lipidome is composed mainly of bulk glycerophospholipids such as PC (17.0%), PE (9.0%), pPE (9.3%), PS (3.3%), PI (3.2%), and to a lesser extent sphingolipids such as SM (5.0%), GluCer (1.8%), GalCer (1.3%), and Sulf (1.6%). Contributing about 2% of the lipidome are low abundance glycerophospholipids such as lysophospholipids (0.56% total), ePC (0.52%), PA (0.52%), PG (0.16%), LBPA (0.007%), sphingolipids including Cer (0.34%), and GM3 (0.069%), glycerolipids DAG (0.058%) and TAG (0.2%) and sterol derivative CE (0.33%). The majority of phospholipids found in the mouse forebrain carry long-chain fatty acyls composed of 38 or more total carbon lengths, whereas medium (36C) and short-chain (<34C) length fatty acyls are less abundant (Fig. 3G). Corresponding to the long fatty acyl chain length, the majority of the phospholipids are polyunsaturated with either 4 or 6 double bonds (Fig. 3H). Phospholipids with the monounsaturated bond are the third most abundant followed by fully saturated phospholipids. Similar to the human brain tissue profile, the majority of sphingolipid species are either long (>42C) or medium (36C) chain length (Fig. 3I).

FIGURE 2.
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FIGURE 2.

Effects of FAD transgene expression on mouse forebrain lipid composition. Aberrant lipid homeostasis is evident in different FAD mice. Lipid subclasses are expressed as mean mol % of all lipid species measured with error bars indicating mean ± S.E. (WT, n = 6; PS, n = 6; APP, n = 6; PS-APP, n = 6). Statistical significance shown here was assessed by one-way analysis of variance analysis. The absolute level of individual lipid species is presented in supplemental Dataset S2.

FIGURE 3.
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FIGURE 3.

Altered fatty acid composition of postmortem human brain tissue in the PFC and ERC regions and of forebrain derived from FAD mouse models. Independent analyses for changes in diacylglycerophospholipids (GP) and DAG chain length equal to the total number of carbon atoms in the sum of fatty acid moieties (A, D, and G), GP and DAG saturation equal to the total number of double bonds in the sum of fatty acid moieties (B, E, and H), sphingolipid (SL) chain lengths equal to the total number of carbon atoms in both long-chain base and fatty acid moieties (C, F, and I) are expressed as mol %.

Lipid Dysregulation in FAD Mouse Models

All three AD transgenic mouse models showed distinctive lipid profiles compared with the WT mice (Fig. 2, 4, supplemental Fig. S5 and Dataset S2). Fatty acyl chain remodeling was evident, with an overall decrease in long-chain phospholipid (C > 40), and a corresponding increase in medium- to short-chain phospholipids (C < 36) (Fig. 3G). Related to these changes, a decrease in fatty acyl chains carrying four polyunsaturated bonds was also replaced by an increase in monounsaturated and saturated fatty acyls (Fig. 3H). In the APP and PS1-APP mice but not the PS1 mice, there was a similar decrease in long-chain sphingolipids (C > 40) that was balanced by increases in short and medium length species (C = 36 to 38) (Fig. 3I).

FIGURE 4.
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FIGURE 4.

Comparative lipid profile of LOAD human samples versus FAD transgene expressing mouse forebrains. The heat maps show all lipid species measured and are organized according to phospholipids, sphingolipids, and neutral lipids classification. The PS, APP, and PS1-APP columns represent the normalized values of the individual lipid species of mutant mice compared with wild-type mice, whereas the PFC, ERC, and CRB columns represent the normalized values of the individual lipid species of LOAD patients compared with control patients for each tissue type. The color bars represent the log2 value of the ratio of each lipid species and only statistically significant changes are shown (p < 0.05). Statistical analysis for the mouse data is based on one-way analysis of variance and post hoc Tukey range test.

In the PS1 mutants, there was a significant decrease in PS (∼29%), PI (∼37%), PG (∼25%), and LBPA (∼29%) as well as in LPC (∼13%) and LPCe (∼20%). Individual PA pools were also highly dysregulated, with PA 34:1 and 36:1 having increasing trends, whereas other species such as PA 32:1, 34:2, and 38:4 were decreased significantly (supplemental Fig. S5). Various pools of the most abundant sphingolipid SM, such as SM d18:1/18:0, and long-chain SM d18:1/26:1 and d18:0/24:0, were selectively enriched. Unique to the PS1 mutant was an increase in long-chain GalCer species such as GalCer d18:1/24:1, d18:1/24:0, and d18:1/26:0, which could be attributed to the degradation of Sulf (∼17%) (supplemental Fig. S5). Contrary to an earlier study on PS1 mutant hippocampus (33), we found no increase in Cer.

Similar to the other transgenic mice, the APP mutant showed decreased levels of PS (∼33%), PI (∼41%), PG (∼25%), LBPA (∼43%), and LPE (∼20%) with an overall increase in PC (∼10%). A decrease in various molecular species of PA (e.g. 32:1 and 34:2) was also observed. These data are in contrast to the specific increase of PA 34:2 seen in a different strain of Swedish APP transgenic mice that were also older in age (11). To determine whether this was an age-related phenomenon, we conducted a targeted PA analysis of 14–15-month-old APP mice of the same genetic background and found that PA 34:2, and to a lower extent other molecular species of PA, were indeed elevated in these mice relative to 9–11-month-old APP mice (supplemental Fig. S6). Similar to the PS1 mutant, an increase in SM was observed in APP mice, reflecting the selective accumulation of medium-chain length SM d18:1/18:1, d18:1/18:0, and d18:0/18:0. This may have resulted from either increased catabolism of GluCer and/or Sulf, both of which showed significant decreases (∼10 and 26%, respectively). Finally, the APP mice showed a trend for increasing total levels of GM3 and CE as represented by specific molecular pools such as GM3 d18:1/18:0 and CE-22:6 (supplemental Fig. S5).

The PS1-APP mutant forebrain was the most severely affected, reflecting the additive or synergistic effects of the two transgenes. Similar to both the PS1 and APP mice, there was a major loss of lipids from the PS (∼28%), PI (∼37%), PG (∼25%), and LBPA (∼29%) subclasses and a slight increase in overall PC levels. Unlike the single transgenics, PS1-APP mice showed a decrease in pPE 34:2, 36:2, 36:1, and 36:0 as well as an increase in lysophospholipids, such as lyso-PS (LPS) (∼17%), lyso-PA (LPA) (∼21%), and lyso-PE (LPE) (∼16%). The changes in sphingolipid profile, specifically an increase in SM pools such as SM d18:1/18:0 and other long-chain species, and significant decrease in total Sulf (∼17%), also resemble the changes of the other two mutants. However, two groups of lipid alterations were prominent in the PS1-APP mice. First, there was an enrichment of GM3 (∼1.7-fold), particularly with major species GM3 d18:0/18:0, d18:1/18:0, and d18:1/20:0 (supplemental Fig. S5). Second, total CE levels was highly enriched (∼4.3-fold), with a dramatic increase (∼11-fold) for specific species, such as CE-22:6 (supplemental Fig. S5).

PLD2 Ablation Causes Normalization of GM3 Levels

Lipidomics can be harnessed to identify lipid pathways that are specific to perturbations made to different biological systems (34, 35). Combining our current data set with pharmacological treatments or genetic models that affect pathophysiological phenotypes of AD may identify bona fide targets of the disease. We recently reported that swAPP transgenic mice lacking PLD2, which hydrolyzes PC to generate PA, are protected from the synaptotoxic and memory-impairing actions of Aβ in vitro and in vivo (11). This protection occurs despite the production of high amounts of Aβ indicating that the toxic effects of Aβ may be neutralized. To understand the molecular basis of this protection, we conducted a targeted lipidomic analysis of the forebrain of these mice, which were slightly older than those used in Figs. 2⇑–4 (see “Experimental Procedures”). Although most sphingolipid classes appear to be unaltered in the mutant mice, profound alterations were observed for GM3 and CE (Fig. 5A). In the Pld2−/− only mice, most molecular species of GM3 were slightly reduced in the forebrain. In contrast, expression of the swAPP transgene alone produced a significant increase in GM3 and CE, similar to the PS1-APP animals (Fig. 2). Most importantly, when swAPP expression and PLD2 ablation were combined, GM3 but not CE levels were normalized, suggesting that ganglioside metabolism may be correlated to the pathogenicity associated with the swAPP model and its rescue in the Pld2−/− background (Fig. 5B).

FIGURE 5.
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FIGURE 5.

PLD2 ablation normalizes GM3 levels in an AD mouse model expressing Swedish APP transgene. A, the overall sphingolipid and cholesterol ester levels, and B, individual GM3 species in the forebrain of these mouse models are presented as mean mol % with error bars indicating mean ± S.E. (WT, no Tg, n = 8; KO, no Tg, n = 6; WT, APP, n = 5; KO, APP, n = 6).

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DISCUSSION

In the present study, we conducted an in-depth lipidomic analysis of AD brain tissue that covered over 300 lipid species from 26 lipid subclasses. We observed that different regions of the human brain undergo heterogeneous changes in lipid metabolism in AD-affected patients. Although the CRB lipid profile was largely unaffected, significant changes were observed in the diseased PFC and ERC (Fig. 1 and supplemental Fig. S1). Between these two tissues, the PFC seemed to carry more severe lipid alterations, with decreased levels of LPC, LPCe, and PE and elevated levels of Cer, GluCer, GalCer, and DAG. In contrast, the ERC only showed significant increases in LBPA, SM, GM3, and CE levels. However, there were also numerous changes to individual lipid species in different subclasses, suggesting that fatty acid carbon chain specificity may play an important role in AD pathogenesis (Fig. 4 and supplemental Figs. S2 and S3). In the PFC, this included various molecular species from the ePC, SM, Sulf, and CE, whereas ERC displayed variability in ePC, PE, and TAG. Importantly, the differences in lipid signatures suggest that these two subregions encounter different aspects or stages of AD pathogenesis, as supported by functional and pathological analyses (19, 20). As expected, neuronal loss was more obvious in the ERC than in the PFC (supplemental Dataset S3). Because neuronal loss is typically associated with gliosis, the lipidome of regions undergoing significant neuronal loss, such as the ERC, may reflect in part changes in the neuron/glia ratio.

Because mouse models are used extensively to study AD pathogenesis, we set out to define whether specific changes in lipid metabolism in brain tissue with LOAD are phenocopied by mouse models of FAD and if these pathways can be targeted for further studies. Granted, this type of comparative analysis faces inherent challenges, including species-specific differences and disease etiology (i.e. FAD versus LOAD), and are thus not expected to be a perfect model for studying LOAD. With these caveats in mind, we observed dramatic lipid changes in all three transgenics that were not seen in humans. Specifically, a variety of anionic phospholipids and sphingolipids, such as Sulf, were decreased in transgenic models. Furthermore, genotype-specific lipid changes were observed and in several cases, the alterations present in the PS1-APP mice reflected an additive or synergistic effect of bigenic FAD gene expression. For instance, PS1-APP mice exhibited a striking elevation of CE and GM3, which was present to a lower extent in the APP mice and virtually absent from PS1 mice (Fig. 2 and supplemental Fig. S5).

Our analysis points to dysregulation of specific lipids potentially involved in key anomalies seen in AD including synaptic dysfunction and neurotransmission deficits (36). For instance, DAG metabolism, which is highly aberrant in diseased PFC, has been implicated in a number of synaptic processes including the regulation of dendritic spine morphology, plasticity, and neurotransmitter release (37). Importantly, overactivation of PKC, a target of DAG, interferes with PFC-regulated working memory (38), a key feature of AD. DAG accumulation in the PFC likely occurs through Aβ-stimulated hydrolysis of PI(4,5)P2 by PLC (10), based on the specific accumulation of polyunsaturated DAG 38:4 (supplemental Fig. S2), a primary metabolite of PI(4,5)P2 (30). Compounding this effect may be the loss of DAG kinase activity because synaptic targeting of DAG kinase depends on PSD95, whose levels are decreased in AD-affected brain tissue (11, 37). Furthermore, aberrant accumulation of sphingolipids in the PFC may also contribute to dysregulation of synaptic vesicle fusion and trafficking of NMDA receptors (39). This may reflect the fact that Aβ42 activates neutral sphingomyelinase, which produces Cer (8), and that sphingolipid enzymes are significantly altered in this tissue (40). Overall, our data suggest that aberrant DAG and sphingolipid metabolism are likely to participate in synaptic dysfunction in diseased PFC.

Another important observation is the LBPA increase in diseased ERC. LBPA is enriched specifically within late endosomes, where it plays a role in the biogenesis of multivesicular bodies (41). The enrichment of LBPA is thus consistent with a dysfunction of the late endosomes/multivesicular bodies. Aberrant endosomes have been previously reported in Down syndrome and AD (42) and growing evidence, most recently through genome wide association (4, 5) and gene expression (43) studies, indicates that defects in the endolysosomal pathway are linked to AD. An emerging hypothesis in the field is that defects in the endolysosomal pathway can affect amyloidogenesis, as organelles along this pathway contain high levels of APP as well as functionally active pools of BACE1 and γ-secretase (44, 45). Additionally, lysosomal defects alter the clearance of autophagosomes, which are double-membrane organelles of the autophagy pathway that mediate the elimination of protein aggregates, including Tau (45). Notwithstanding other possible functional implications (see below), the ERC accumulation of SM, GM3, and CE adds strong support to the endolysosomal dysfunction hypothesis. Indeed, SM and GM3 traffic within and between the plasma membrane and endosomes (46), whereas intracellular CE, normally found in lipid droplets, has also been detected in late endosomes (47). Of particular relevance, the accumulation of SM and gangliosides impairs lysosomal degradation of APP-CTFs, which enhances amyloidogenesis (48). A likely secondary implication of SM and GM3 accumulation is the propensity for ganglioside-enriched membrane microdomains at the cell surface and in endosomes to seed Aβ oligomerization (12). Taken together, the overall lipid profile changes seen in the ERC of AD patients suggest a pathogenic cascade that is reminiscent of lipid traffic jams described in lipid storage diseases such as Niemann-Pick types A and C (49).

Although lipid changes in FAD models are in most aspects vastly different from the LOAD samples, our lipidomic analysis suggest that the APP and PS1-APP mice are likely suitable models to study the role of ganglioside (GM3) and CE accumulation in AD, particularly because these anomalies are also observed in the ERC of AD patients (Fig. 4). A key question is whether the reversal of these lipid changes can ameliorate the AD-relevant phenotypes of the transgenic models, including enhanced amyloidogenesis. A partial answer, as well as an important “proof of concept” validation of our analysis, is that the pharmacological inhibition and genetic ablation of acyl-coenzyme A:cholesterol acyltransferase 1, a CE-synthesizing enzyme, lower Aβ production and improves memory related tasks in transgenic models of AD (32). Our own studies suggest that the protective role of PLD2 ablation in APP transgenic mice may be related to gangliosides, as suggested by the normalization of GM3 levels to those found in control mice (Fig. 5). This raises important questions about how PLD and its product PA are related to ganglioside metabolism and perhaps endolysosomal dysregulation in AD (11, 50). Additionally, because PLD2 ablation mitigates the signaling, but not the biogenesis of Aβ (11), we hypothesize that the GM3 elevation observed in the APP models (which is corrected in the Pld2 knock-out) occurs downstream of Aβ. Interestingly, the normalization of GM3 levels in the FAD mouse lacking PLD2 occurs independently of CE, suggesting that CE elevation in FAD mice may not be driven by increased Aβ signaling per se. Overall, our data suggest that there are multiple ways to relieve lipid traffic jams that may be detrimental to neural cells in AD pathogenesis.

Finally, our study suggests that AD is associated with a more general perturbation of membrane properties. The length and degree of saturation are important determinants of many membrane characteristics including membrane thickness, fluidity, local curvature, and molecular packing, which in turn regulate the activities of membrane-bound enzymes (51). Intramembrane proteolysis is likely to be exquisitely regulated by membrane thickness, with major implications for γ-secretase-mediated cleavage of APP (52). Interestingly, FAD mouse forebrains and to a lower extent diseased PFC and ERC, exhibited a relative increase in short-chain lipids that was accompanied by a reduction in polyunsaturated phospholipids (Fig. 3). Similar results have been described in synaptosomal and detergent-resistant membranes due to aging (53) and AD (54). It is well known that long-chain polyunsaturated phospholipids display an aversion to highly ordered lamellar microdomains, whereas short-chain monounsaturated or saturated phospholipids interact favorably with sphingolipids and cholesterol in lipid rafts (6, 55). These features thus point to an increased propensity of membranes from the AD-affected brain to form lipid rafts, which may have consequences on the amyloidogenic processing of APP (6, 7).

A fundamental challenge in understanding a complex disease using a systems based approache, such as lipidomics, is the identification of pathophysiologically relevant changes among a myriad of changes. Here, we have capitalized on the exquisite sensitivity of LC-MS to characterize the lipidome of brain tissue from AD-affected humans and commonly used FAD mouse models. We describe novel region-specific lipid changes in human AD tissue that may contribute to AD etiology. We also identified overlaps in lipid dysregulation between mice and humans, suggesting that the FAD mouse model may be suitable for the study of specific aspects of AD-associated lipid dysregulation. Our data thus provides a frame of reference for lipids that can be targeted for therapeutic interrogation either through pharmacological or enzymatic manipulations, to improve learning and memory in the context of AD. In particular, PLD2 isoform-specific inhibitors (56) may prove to be valuable therapeutic agents in AD and thus require further evaluation. Our study also provides further incentive to systematically analyze the various animal models of AD available in the biomedical community as well as to expand these types of profiling to other AD-vulnerable brain regions, so that a better understanding of AD-linked lipid dysfunction can be achieved.

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Acknowledgments

We thank Dr. J. P. Vonsattel, Director of the New York Brain Bank for neuropathological expertise, Drs. O. Arancio and E. Levy for supplying a subset of the mouse models, Dr. Rong Cheng for advising on statistical analysis, K. S. Robinson and Dr. Z. M. Lasiecka for critically reading this manuscript, and Drs. D. E. Berman, L. B. McIntire, and T. W. Kim for helpful discussions.

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Footnotes

  • ↵* This work was supported, in whole or in part, by National Institutes of Health Grants R01 HD05547 (to G. D. P.) and P50 AG008702 (to M. Shelanski), and a Lejeune Foundation grant (to G. D. P.), National Research Foundation–Competitive Research Programme Grant R-183-000-218-281, Biomedical Research Council Grant R-183-000-234-305, and National University of Singapore–Life Sciences Institute (SLING) Grant R-711-000-021-133 (to M. R. W.).

  • ↵Graphic This article contains supplemental Figs. S1–S6 and Datasets S1–S3.

  • ↵3 The abbreviations used are:

    AD
    Alzheimer disease
    APP
    amyloid precursor protein
    BACE1
    β-secretase β-site APP cleavage enzyme 1
    PLD2
    phospholipase D2
    FAD
    familial AD
    PS1 and PS2
    presenilin 1 and 2
    LOAD
    late onset AD
    SM
    sphingomyelin
    pPE
    plasmalogen phosphatidylethanolamine
    PLC
    phospholipase C
    PA
    phosphatidic acid
    PFC
    prefrontal cortex
    ERC
    entorhinal cortex
    CRB
    cerebellum
    DAG
    diacylglycerol
    TAG
    triacylglycerol
    CE
    cholesterol ester
    PI
    phosphatidylinositol
    PC
    phosphatidylcholine
    PE
    phosphatidylethanolamine
    PS
    phosphatidylserine
    PG
    phosphatidylglycerol
    LBPA
    lysobisphosphatidic acid
    LPC
    lysophosphatidylcholine
    LPCe
    lyso ether PC
    Sulf
    sulfatide
    PI(4,5)P2
    phosphatidylinositol 4,5-bisphosphate
    GM1
    ceramide-N-tetrose-N-acetylneuraminic acid
    GM3
    ceramide-lactose-N-acetylneuraminic acid.

  • Received June 20, 2011.
  • Revision received November 29, 2011.
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  1. First Published on December 1, 2011 doi: 10.1074/jbc.M111.274142 The Journal of Biological Chemistry 287, 2678-2688.
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