OBJECTIVE

The results of the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications cohort study revealed a strong association between dyslipidemia and the development of diabetic retinopathy. However, there are no experimental data on retinal fatty acid metabolism in diabetes. This study determined retinal-specific fatty acid metabolism in control and diabetic animals.

RESEARCH DESIGN AND METHODS

Tissue gene and protein expression profiles were determined by quantitative RT-PCR and Western blot in control and streptozotocin-induced diabetic rats at 3–6 weeks of diabetes. Fatty acid profiles were assessed by reverse-phase high-performance liquid chromatography, and phospholipid analysis was performed by nano-electrospray ionization tandem mass spectrometry.

RESULTS

We found a dramatic difference between retinal and liver elongase and desaturase profiles with high elongase and low desaturase gene expression in the retina compared with liver. Elovl4, an elongase expressed in the retina but not in the liver, showed the greatest expression level among retinal elongases, followed by Elovl2, Elovl1, and Elovl6. Importantly, early-stage diabetes induced a marked decrease in retinal expression levels of Elovl4, Elovl2, and Elovl6. Diabetes-induced downregulation of retinal elongases translated into a significant decrease in total retinal docosahexaenoic acid, as well as decreased incorporation of very-long-chain polyunsaturated fatty acids (PUFAs), particularly 32:6n3, into retinal phosphatidylcholine. This decrease in n3 PUFAs was coupled with inflammatory status in diabetic retina, reflected by an increase in gene expression of proinflammatory markers interleukin-6, vascular endothelial growth factor, and intercellular adhesion molecule-1.

CONCLUSIONS

This is the first comprehensive study demonstrating diabetes-induced changes in retinal fatty acid metabolism. Normalization of retinal fatty acid levels by dietary means or/and modulating expression of elongases could represent a potential therapeutic target for diabetes-induced retinal inflammation.

Early diabetic retinopathy has been suggested to be a low-grade chronic inflammatory disease (1,3) with a number of inflammatory markers, such as vascular endothelial growth factor (VEGF) (4,5), intercellular adhesion molecule (ICAM)-1 (6,7), tumor necrosis factor (TNF)-α (8), and interleukin (IL)-6 (9), shown to be upregulated in diabetic retina. The individual molecular steps leading to inflammation in the retina are not well resolved but likely involve hyperglycemia and dyslipidemia associated with diabetes.

Dyslipidemia is a major metabolic disorder of diabetes, and the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications cohort study revealed that dyslipidemia was significantly associated with the development of diabetic retinopathy (10). Diabetic dyslipidemia is the result of an imbalance in the complex regulation of lipid uptake, metabolism, release by adipocytes, and clearance from circulation (11,12). Fatty acid metabolism perturbation in diabetes is an important part of diabetic dyslipidemia (13).

To understand the effects of diabetes on plasma and tissue fatty acid composition, two metabolic routes have to be considered: de novo lipogenesis and the polyunsaturated fatty acid (PUFA) remodeling Sprecher pathway (14). Saturated fatty acids (SRAs), monounsaturated fatty acids (MUFAs), and PUFAs are synthesized from dietary precursors (glucose, palmitic16:0, oleic18:1n9, linoleic18:2n6, α-linolenic18:3n3, eicosapentaenoic acid [EPA20:5n3], and docosahexaenoic acid [DHA22:6n3]) through a series of desaturation (Δ5-desaturase [Δ5D], Δ6-desaturase [Δ6D], or Δ9-desaturase [Δ9D]) and elongation (Elovl1–7) reactions. In the recent work by Agbaga et al. (15), the Sprecher pathway was expanded to include very-long-chain PUFAs (VLCPUFAs), up to 38 carbon fatty acids, in which elongation of shorter-chain fatty acids precursors is performed by Elovl4 (Fig. 1). Elovl4 has very limited tissue specificity. It is highly expressed in the retina (16,18), thymus, and skin (17), as well as at lesser levels in the brain (17,18) and testis (18). Elovl4 is not expressed in the liver (17,18). In human retina, Elovl4 was shown to be primarily expressed in the inner segment of photoreceptors extending to photoreceptor cell bodies in the outer nuclear layer (19). Moderate labeling was also observed in the ganglion cells (19). Elovl4 has received much attention recently, as an autosomal-dominant Stargardt-like macular dystrophy was linked to several dominant-negative mutations in Elovl4 (19,21). The role of VLCPUFAs produced by Elovl4 is not known, but because of their localization in retinal outer-segment membranes and their ability to span both leaflets of the lipid bilayer, they are suggested to play a role in stabilizing cellular membranes with high curvature, such as the rims of photoreceptor disks (15). Fatty acid desaturase enzymes are known to be inhibited in diabetes (22,24), and there is emerging information suggesting that certain elongases might also be affected (25). Thus, diabetes may result in reduced fatty acid remodeling and, consequently, lead to an accumulation of the substrates and depletion of the products. The elongases Elovl2 and Elovl6 are ubiquitously expressed in most tissues; however, retina expresses Elovl2 at a very high level. Elovl2 is involved in several steps of DHA22:6n3 biosynthesis (26). Retina has a unique fatty acid profile with one of the highest levels of long-chain PUFAs, especially DHA22:6n3, in the body (27). We have previously demonstrated that DHA22:6n3 has a pronounced anti-inflammatory effect on cytokine-induced activation of the nuclear factor (NF)-κB pathway and adhesion molecule expression in human retinal endothelial cells (HRECs) (28). Thus, perturbation of lipid metabolism in diabetes with a subsequent decrease in DHA22:6n3 could create proinflammatory conditions in the retina, potentially contributing to the development of diabetic retinopathy. The effect of diabetes on retinal fatty acid elongases and desaturases and diabetes-induced changes in retinal fatty acid remodeling has not been analyzed and represents one of the goals of this study.

FIG. 1.

De novo lipogenesis and PUFA remodeling pathways. Fatty acids are synthesized from glucose through de novo lipogeneses or converted from dietary palmitic16:0, oleic18:1n9, linoleic18:2n6, and α-linolenic18:3n3 acids to long-chain unsaturated fatty acids in vivo by a series of desaturation (Δ5-desaturase [Δ5D], Δ6-desaturase [Δ6D], or Δ9-desaturase [Δ9D]) and elongation (Elovl1–7) reactions. Fatty acids that accumulate in animal and human tissues are in solid boxes. Dietary linoleic18:2n6 and α-linolenic18:3n3 acids are obtained from plants, and EPA20:5n3 and DHA22:6n3 are rich in fish oil. A recent study demonstrated that Elovl4 is necessary for synthesis of C26 and C28 VLCPUFAs from 24:5n3 and 24:6n3 fatty acid precursors and suggests that Elovl4 is also required for synthesis of >C28 VLCPUFAs. There is no interconversion between n3, n6, and n9 fatty acids in animals.

FIG. 1.

De novo lipogenesis and PUFA remodeling pathways. Fatty acids are synthesized from glucose through de novo lipogeneses or converted from dietary palmitic16:0, oleic18:1n9, linoleic18:2n6, and α-linolenic18:3n3 acids to long-chain unsaturated fatty acids in vivo by a series of desaturation (Δ5-desaturase [Δ5D], Δ6-desaturase [Δ6D], or Δ9-desaturase [Δ9D]) and elongation (Elovl1–7) reactions. Fatty acids that accumulate in animal and human tissues are in solid boxes. Dietary linoleic18:2n6 and α-linolenic18:3n3 acids are obtained from plants, and EPA20:5n3 and DHA22:6n3 are rich in fish oil. A recent study demonstrated that Elovl4 is necessary for synthesis of C26 and C28 VLCPUFAs from 24:5n3 and 24:6n3 fatty acid precursors and suggests that Elovl4 is also required for synthesis of >C28 VLCPUFAs. There is no interconversion between n3, n6, and n9 fatty acids in animals.

Close modal

Reagents.

High-performance liquid chromatography (HPLC)-grade acetonitrile, acetic acid, methanol, chloroform, streptozotocin (STZ), and commonly used chemicals and reagents were from Sigma-Aldrich Chemical (St. Louis, MO).

Animals and induction of STZ-induced diabetes.

Male Sprague-Dawley rats weighing 237–283 g were made diabetic with a single intraperitoneal injection of 65 mg STZ per kg body wt. Body weight gains and blood glucose for the control and STZ-induced diabetic groups were monitored biweekly. At 3–6 weeks after STZ injection, the animals were killed and blood plasma, liver, and retina were recovered for analyses of fatty acid profiles and/or fatty acid elongase and desaturase expression levels. To isolate the retina, the optic nerve was cut out; the eye was opened; the coronary, cornea, and lens were discarded; and the retina was separated from choroid, washed in PBS, and frozen. Rats were maintained on Harlan-Teklad laboratory diet (no. 8,640) and water ad libitum. The fatty acid composition of the diet was analyzed by reverse-phase HPLC (RP-HPLC, see below) and found to be 16:0, 20.0%; 18:0, 1.8%; 18:1n9, 21.9%; 18:2n6, 50.8%; 18:3n3, 5.6%; 18:3n6, 0.1%; 20:4n6, 0.1%; 20:5n3, 0.4%; 22:5n3, 0.1%; and 22:6n3, 0.3%. Animal protocol was approved by the Michigan State University Institutional Animal Care and Use Committee. All experiments followed the guidelines set forth by the Association for Research in Vision and Ophthalmology Resolution on Treatment of Animals in Research.

RNA and protein isolation.

Rat tissues were homogenized in Trizol reagent (Invitrogen), and RNA was isolated according to manufacturer instructions. After adding chloroform, the upper aqueous phase was separated and RNA was precipitated with isopropyl alcohol, washed with 75% ethanol, and redissolved in RNase-free water. Proteins from the same samples were isolated by washing in Tris buffer (30 mmol/l Tris-HCl, pH 6.8, with 0.1% SDS) followed by concentration on Amicon-15 (Millipore) centrifugal filters. After concentration, protease/phosphatase inhibitor cocktail was added and samples were frozen until further analysis.

Real-time qRT-PCR.

Transcript-specific primers were designed using Primer3 software (available at http://frodo.wi.mit.edu/primer3/). First-strand cDNA was synthesized using the SuperScript II RNase H Reverse Transcriptase (Invitrogen, Carlsband, CA), and PCRs were performed in triplicate as previously described (25). Transcripts of interest were normalized to the abundance of cyclophilin mRNA. Rat gene–specific primers used in this study were Elovl4: GAAGTGGATGAAAGACCGAGA (sense) and GCGTTGTATGATCCCATGAA (antisense); Elovl7: TGGCGTTCAGCGATCTTAC and GATGATGGTTTGTGGCAGAG; IL-6: CCAGGAAATTTGCCTATTGA and GCTCTGAATGACTCTGGCTTT; VEGF A: GCTCTCTTGGGTGCACTGG and CACCACTTCATGGGCTTTCT; and ICAM-1: CCACCATCACTGTGTATTCGTT and ACGGAGCAGCACTACTGAGA. All other primers for rat elongases and desaturases were described previously (25).

Western blotting.

Protein concentration was determined by a Qubit fluorometer (Invitrogen), according to manufacturer's instructions, and equivalent amounts of protein were loaded on the SDS-polyacrylamide (10%) minigels for SDS-PAGE separation. The separated proteins were electrophoretically transferred to a nitrocellulose membrane (Bio-Rad, Hercules, CA), blocked for 30 min at room temperature, and probed with primary rabbit anti-Elovl4 (Abcam) and mouse anti-α tubulin (Sigma) antibody followed by fluorescent secondary antibody (Invitrogen). The blots were analyzed by the Licor Odyssey scanner and quantitated using Licor Odyssey software.

Total lipid extraction.

Total lipids from retina, blood plasma, and liver were extracted with chloroform-methanol (2:1, vol/vol), normalized to tissue weight, dried, and resuspended as previously described (29). Acidification of total lipid extracts was omitted, as low pH has been demonstrated to destroy acid-labile plasmalogen lipids (30), which are abundant in neural tissues. No significant decrease of recovery of abundant lipid classes was observed in the absence of pH modification (29). Blood plasma lipids were normalized to protein, as measured by Qubit assay. Erythrocyte total lipids were extracted from 100 mg of packed cells by a modified Rose and Oklander method (31). Briefly, lysed cells were combined with 6.8 ml of 80% 2-propanol, vortexed, and incubated for 1 h on ice with occasional mixing. Lipids were extracted twice by addition of 3.2 ml of 100% chloroform and 1-h incubation on ice, with phase separation after each chloroform addition achieved by centrifugation at 2,000g for 30 min. Acidification of the extraction mixture was omitted, as it was found that low pH destroys acid-labile plasmalogen lipids (30), which are abundant in neural tissues. No significant decrease of recovery of abundant lipid classes was observed in the absence of pH modification (29). Pooled lipid extracts were dried, resuspended, and stored as described above.

Lipid analysis by nano-electrospray ionization tandem mass spectrometry.

Lipid extracts were introduced to a triple-quadrupole mass spectrometer (Thermo Scientific model TSQ Quantum Ultra, San Jose, CA) for nano-electrospray ionization tandem mass spectrometry (nESI-MS/MS) analysis of lipid species as previously described (29). Identification of phospholipid species by precursor ion and neutral loss scan mode MS/MS was performed according to published methods (29,32). Assignment of phosphatidylcholine (GPCho) acyl substituents was achieved by negative ion mode analysis of corresponding GPCho [M+Cl] ions byproduct ion scan mode MS/MS, as well as by precursor ion scanning for m/z corresponding to specific deprotonated fatty acyl ions. Peak finding and correction for 13C isotope effects was performed using the Lipid Mass Spectrum Analysis (LIMSA) software version 1.0 peak model fit algorithm (33). Quantitative analysis of the relative changes in GPCho lipid abundances between control and diabetic samples was achieved by normalization of the peak area of each detected GPCho m/z to that of the GPCho(16:0/16:0) lipid present in each of the samples, after correction for 13C isotope contributions.

Tissue fatty acid analysis by RP-HPLC.

An aliquot of total lipids from tissues and blood fractions was saponified (0.4 N KOH in 80% methanol, 50°C for 1 h). Saponified fatty acids were acidified and extracted with diethyl ether (according to Wang et al. [25]) and stored in methanol containing 1 mmol/l butylated hydroxytoluene. Saponified free fatty acids were fractionated and quantitated by RP-HPLC using a YMC J-Sphere (ODS-H80) column and a sigmoidal gradient starting at 86.5% acetonitrile + acetic acid (0.1%) and ending at 100% acetonitrile + acetic acid (0.1%) over 50 min with a flow rate of 1.0 ml/min using a Waters 600 controller. Fatty acids were introduced to the HPLC by injection in methanol and detected using ultraviolet absorbance and evaporative light scatter as previously described (25). Authentic fatty acid standards (Nu-Chek Prep) were used to generate calibration curves for verification and quantification of fatty acids.

Statistical analysis.

Data are expressed as the means ± SD. Student's t test was used for comparing data obtained from independent samples. Significance was established at P < 0.05.

Body weight gain and blood glucose concentration of experimental animals.

As presented in Table 1, body weight gain was significantly slower in diabetic animals compared with control animals. Blood glucose levels were almost five times higher in diabetic animals compared with controls. As this was a short-term diabetes study, A1C levels were not measured.

TABLE 1

Body weight gain and blood glucose concentrations of experimental animals

nWeight gain (g/day)Blood glucose (mmol/l)
Control animals 4.05 ± 0.65 4.33 ± 0.29 
Diabetic animals 2.32 ± 0.89 20.80 ± 1.16 
nWeight gain (g/day)Blood glucose (mmol/l)
Control animals 4.05 ± 0.65 4.33 ± 0.29 
Diabetic animals 2.32 ± 0.89 20.80 ± 1.16 

Data are means ± SD.

Elongase and desaturase expression level in control and diabetic animals.

The gene expression levels of elongases and desaturases in control retinas were determined by quantitative RT-PCR and compared with the levels found in the livers of the same animals. Retinal-specific elongase, Elovl4, had the highest expression level among all the elongases in the retina and was not expressed in the liver. Retinas also had high levels of Elovl2 expression (Fig. 2,A). Livers exhibited higher levels of Elovl5 and Δ5-, Δ6-, and Δ9-desaturases than retina (Fig. 2 A), and the liver profile of all elongases and desaturases agreed with our previous study (25).

FIG. 2.

Expression levels of elongases and desaturases in retinas and livers of control and diabetic animals. Total RNA was extracted from retinas and livers of normal control (n = 4) and STZ-induced diabetic animals (n = 5) after 3–6 weeks of diabetes and analyzed by real-time PCR for elongases 1–7 (E1–7) and Δ5-, Δ6-, and Δ9-desaturase (D5D, D6D, and D9D) expression level. A comparison of the expression levels in retina (□) and liver () of normal control animals is presented in A. Diabetes-induced changes in liver elongase and desaturase expression levels are presented in B (□, control; ■, diabetes). Diabetes-induced changes in retinal expression levels are presented in C (□, control; ■, diabetes). A Western blot of diabetes-induced changes in retina Elovl4 protein level (lanes 1–4 control, lanes 5–8 diabetic), and quantification by ratiometric comparison to tubulin, are presented in D (□, control; ■, diabetes). Data are presented as means ± SD of five independent experiments. *Statistical significance at P < 0.05.

FIG. 2.

Expression levels of elongases and desaturases in retinas and livers of control and diabetic animals. Total RNA was extracted from retinas and livers of normal control (n = 4) and STZ-induced diabetic animals (n = 5) after 3–6 weeks of diabetes and analyzed by real-time PCR for elongases 1–7 (E1–7) and Δ5-, Δ6-, and Δ9-desaturase (D5D, D6D, and D9D) expression level. A comparison of the expression levels in retina (□) and liver () of normal control animals is presented in A. Diabetes-induced changes in liver elongase and desaturase expression levels are presented in B (□, control; ■, diabetes). Diabetes-induced changes in retinal expression levels are presented in C (□, control; ■, diabetes). A Western blot of diabetes-induced changes in retina Elovl4 protein level (lanes 1–4 control, lanes 5–8 diabetic), and quantification by ratiometric comparison to tubulin, are presented in D (□, control; ■, diabetes). Data are presented as means ± SD of five independent experiments. *Statistical significance at P < 0.05.

Close modal

In the liver, diabetes induced a 25% decrease in Elovl2 and a 33% decrease in Elovl6 expression, as well as an 85% decrease in Δ9-desaturase (Fig. 2,B) compared with controls. In the retina, diabetes induced a 40% reduction in Elovl4 and 50% reduction in Elovl2 expression levels (Fig. 2,C). There was no significant effect of diabetes on the retinal desaturases (Fig. 2,C). A decrease in Elovl4 protein level was confirmed by Western blot, as shown in Fig. 2 D.

Blood plasma fatty acid profiles of control and diabetic animals.

The control and diabetic blood plasma fatty acid profiles 3 weeks after STZ injection are presented in Table 2. There was a tendency toward higher total fatty acids level in diabetic versus control blood plasma. We observed changes in the plasma fatty acid profile consistent with inhibition of fatty acid remodeling in diabetes that leads to a lower end product–to–precursor fatty acid ratio. There was a decrease in two major end products of the PUFA synthesis pathway, arachidonic20:4n6 acid and DHA22:6n3, relative to their precursors, linoleic18:2n6 and α-linolenic18:3n3 acid, respectively (Table 2). As a result of these changes, we observed a decrease in unsaturation index (the number of double bonds per fatty acyl residue) and a decrease in long-chain–to–short-chain PUFA ratio in diabetic versus control animals (Table 2).

TABLE 2

Blood plasma fatty acid profiles of control (n = 4) and diabetic (n = 7) animals

Fatty acidsBlood plasma
P
Control animalsDiabetic animalsDifference
Total (nmol/mg protein) 2,262.55 ± 639.64 3,286.54 ± 766.69  0.0972 
Mole % of total fatty acids     
    16:0 (palmitic) 2.19 ± 1.17 3.70 ± 0.46 ↑ 0.0362* 
    18:0 (stearic) 2.25 ± 0.34 2.08 ± 0.40  0.5639 
    18:1n9 (oleic) 12.65 ± 1.03 13.43 ± 1.74  0.5126 
    18:2n6 (linoleic) 54.12 ± 2.31 57.44 ± 2.62  0.1207 
    18:3n3 (α-linolenic) 1.93 ± 0.32 2.71 ± 0.36 ↑ 0.0214* 
    18:3n6 (γ-linolenic) 0.31 ± 0.13 0.51 ± 0.37  0.4028 
    20:3n6 (dihomo-γ-linolenic) 0.84 ± 0.12 0.87 ± 1.15  0.9631 
    20:3n9 (mead) 0.52 ± 0.32 0.35 ± 0.30  0.4636 
    20:4n6 (arachidonic) 21.29 ± 2.70 15.90 ± 1.95 ↓ 0.0161* 
    20:5n3 (eicosapentaenoic) 0.53 ± 0.08 0.51 ± 0.03  0.7449 
    22:5n3 (docosapentaenoic) 0.84 ± 0.22 0.54 ± 0.04 ↓ 0.0235* 
    22:6n3 (docosahexaenoic) 2.78 ± 0.23 1.72 ± 0.25 ↓ 0.0010* 
Fatty acid ratios     
    Unsaturation index 61.58 ± 18.05 38.91 ± 5.56 ↓ 0.0342* 
    LCPUFAa/SCPUFAa 0.48 ± 0.06 0.33 ± 0.05 ↓ 0.0107* 
    20:4n6/18:2n6 0.40 ± 0.07 0.28 ± 0.04 ↓ 0.0232* 
    22:6n3/18:3n3 1.46 ± 0.17 0.64 ± 0.13 ↓ 0.0002* 
Fatty acidsBlood plasma
P
Control animalsDiabetic animalsDifference
Total (nmol/mg protein) 2,262.55 ± 639.64 3,286.54 ± 766.69  0.0972 
Mole % of total fatty acids     
    16:0 (palmitic) 2.19 ± 1.17 3.70 ± 0.46 ↑ 0.0362* 
    18:0 (stearic) 2.25 ± 0.34 2.08 ± 0.40  0.5639 
    18:1n9 (oleic) 12.65 ± 1.03 13.43 ± 1.74  0.5126 
    18:2n6 (linoleic) 54.12 ± 2.31 57.44 ± 2.62  0.1207 
    18:3n3 (α-linolenic) 1.93 ± 0.32 2.71 ± 0.36 ↑ 0.0214* 
    18:3n6 (γ-linolenic) 0.31 ± 0.13 0.51 ± 0.37  0.4028 
    20:3n6 (dihomo-γ-linolenic) 0.84 ± 0.12 0.87 ± 1.15  0.9631 
    20:3n9 (mead) 0.52 ± 0.32 0.35 ± 0.30  0.4636 
    20:4n6 (arachidonic) 21.29 ± 2.70 15.90 ± 1.95 ↓ 0.0161* 
    20:5n3 (eicosapentaenoic) 0.53 ± 0.08 0.51 ± 0.03  0.7449 
    22:5n3 (docosapentaenoic) 0.84 ± 0.22 0.54 ± 0.04 ↓ 0.0235* 
    22:6n3 (docosahexaenoic) 2.78 ± 0.23 1.72 ± 0.25 ↓ 0.0010* 
Fatty acid ratios     
    Unsaturation index 61.58 ± 18.05 38.91 ± 5.56 ↓ 0.0342* 
    LCPUFAa/SCPUFAa 0.48 ± 0.06 0.33 ± 0.05 ↓ 0.0107* 
    20:4n6/18:2n6 0.40 ± 0.07 0.28 ± 0.04 ↓ 0.0232* 
    22:6n3/18:3n3 1.46 ± 0.17 0.64 ± 0.13 ↓ 0.0002* 

Data are means ± SD.

*P < 0.05.

†Long-chain PUFAs/short-chain PUFAs.

Liver fatty acid profiles of control and diabetic animals.

The control and diabetic liver fatty acid profiles 3 weeks after STZ injection are presented in Table 3. There was an increase in the linoleic acid18:2n6 level in the livers of diabetic versus control animals that led to a decrease in long-chain–to–short-chain PUFA ratio (Table 3). There were no other significant changes in liver fatty acid profiles in diabetic versus control animals. The liver unsaturation index and PUFA synthesis pathway end product–to–precursor ratios did not change in diabetic versus control animals (Table 3).

TABLE 3

Liver fatty acid profiles of control (n = 4) and diabetic (n = 7) animals

Fatty acidsLiver
P
Control animalsDiabetic animalsDifference
Total (nmol/mg protein) 1,762.82 ± 480.50 1,357.85 ± 241.19  0.1,542 
Mole % of total fatty acids     
    16:0 (palmitic) 26.73 ± 8.18 17.55 ± 3.25  0.0518 
    18:0 (stearic) 11.25 ± 3.74 12.64 ± 3.55  0.9706 
    18:1n9 (oleic) 3.11 ± 1.03 3.39 ± 1.04  0.4785 
    18:2n6 (linoleic) 33.14 ± 5.34 39.90 ± 2.71 ↑ 0.0161* 
    18:3n3 (α-linolenic) 0.49 ± 0.11 0.59 ± 0.11  0.2101 
    18:3n6 (γ-linolenic) 0.13 ± 0.14 0.09 ± 0.04  0.2173 
    20:3n6 (dihomo-γ-linolenic) 0.34 ± 0.04 0.43 ± 0.15  0.3942 
    20:3n9 (mead) 0.62 ± 0.24 0.51 ± 0.14  0.9340 
    20:4n6 (arachidonic) 19.87 ± 4.43 21.37 ± 2.50  0.4581 
    20:5n3 (eicosapentaenoic) 0.15 ± 0.03 0.15 ± 0.05  0.7777 
    22:5n3 (docosapentaenoic) 0.57 ± 0.15 0.44 ± 0.07  0.2388 
    22:6n3 (docosahexaenoic) 3.60 ± 0.92 2.94 ± 0.35  0.2294 
Fatty acid ratios     
    Unsaturation index 5.05 ± 1.82 6.56 ± 1.31  0.0911 
    LCPUFA/SCPUFA 0.74 ± 0.07 0.64 ± 0.02 ↓ 0.0123* 
    20:4n6/18:2n6 0.60 ± 0.07 0.53 ± 0.03  0.1211 
    22:6n3/18:3n3 7.74 ± 2.96 5.11 ± 1.05  0.0979 
Fatty acidsLiver
P
Control animalsDiabetic animalsDifference
Total (nmol/mg protein) 1,762.82 ± 480.50 1,357.85 ± 241.19  0.1,542 
Mole % of total fatty acids     
    16:0 (palmitic) 26.73 ± 8.18 17.55 ± 3.25  0.0518 
    18:0 (stearic) 11.25 ± 3.74 12.64 ± 3.55  0.9706 
    18:1n9 (oleic) 3.11 ± 1.03 3.39 ± 1.04  0.4785 
    18:2n6 (linoleic) 33.14 ± 5.34 39.90 ± 2.71 ↑ 0.0161* 
    18:3n3 (α-linolenic) 0.49 ± 0.11 0.59 ± 0.11  0.2101 
    18:3n6 (γ-linolenic) 0.13 ± 0.14 0.09 ± 0.04  0.2173 
    20:3n6 (dihomo-γ-linolenic) 0.34 ± 0.04 0.43 ± 0.15  0.3942 
    20:3n9 (mead) 0.62 ± 0.24 0.51 ± 0.14  0.9340 
    20:4n6 (arachidonic) 19.87 ± 4.43 21.37 ± 2.50  0.4581 
    20:5n3 (eicosapentaenoic) 0.15 ± 0.03 0.15 ± 0.05  0.7777 
    22:5n3 (docosapentaenoic) 0.57 ± 0.15 0.44 ± 0.07  0.2388 
    22:6n3 (docosahexaenoic) 3.60 ± 0.92 2.94 ± 0.35  0.2294 
Fatty acid ratios     
    Unsaturation index 5.05 ± 1.82 6.56 ± 1.31  0.0911 
    LCPUFA/SCPUFA 0.74 ± 0.07 0.64 ± 0.02 ↓ 0.0123* 
    20:4n6/18:2n6 0.60 ± 0.07 0.53 ± 0.03  0.1211 
    22:6n3/18:3n3 7.74 ± 2.96 5.11 ± 1.05  0.0979 

Data are means ± SD.

*P < 0.05.

†Long-chain PUFAs/short-chain PUFAs.

Retinal fatty acid profiles of control and diabetic animals.

Retina has a unique fatty acid profile, with the highest content of long-chain PUFAs in the body. In agreement with other studies, retinal profiles were very rich in DHA22:6n3 and arachidonic20:4n6 acid (Table 4). The levels of linoleic18:2n6 and α-linolenic18:3n3 acid in the retina were very low; thus we did not calculate the PUFA synthesis pathway end product–to–precursor ratios. Importantly, the retinas of diabetic animals had 28% less DHA22:6n3 compared with controls. As a result, we observed a decrease in unsaturation index, a decrease in long-chain–to–short-chain PUFA ratio, and a decrease in the n3-to-n6 PUFA ratio in the retinas of diabetic versus control animals (Table 4). Representative RP-HPLC chromatograms of saponified fatty acids from control and diabetic retina are presented in Fig. 3 A.

TABLE 4

Retinal fatty acid profiles of control (n = 4) and diabetic (n = 7) animals

Fatty acidsRetina
P
Control animalsDiabetic animalsDifference
Total (nmol/mg protein) 488.96 ± 17.64 460.32 ± 27.82  0.43 
n3 fatty acids 225.1 ± 4.23 166.34 ± 20.66 ↓ 0.0495* 
n6 fatty acids 38.67 ± 4.71 40.59 ± 3.9  0.7693 
Mole % of total fatty acids     
    16:0 (palmitic) 15.51 ± 0.8 18.32 ± 1.67  0.2046 
    18:0 (stearic) 18.61 ± 0.97 21.98 ± 2.  0.2046 
    18:1n9 (oleic) 10.58 ± 0.2 12.9 ± 0.77 ↑ 0.0441* 
    18:2n6 (linoleic) 0.44 ± 0.06 0.88 ± 0.05 ↑ 0.0051* 
    18:3n3 (α-linolenic) 0.24 ± 0.06 0.17 ± 0.02  0.3556 
    20:3n6 (dihomo-γ-linolenic) 0.11 ± 0.02 0.04 ± 0.01  0.0819 
    20:3n9 (mead) 0.97 ± 0.06 1.09 ± 0.2  0.6103 
    20:4n6 (arachidonic) 7.33 ± 0.75 7.9 ± 0.64  0.6004 
    20:5n3 (eicosapentaenoic) 0.04 ± 0.02 0.01 ± 0.01  0.2910 
    22:5n3 (docosapentaenoic) 0.47 ± 0.08 0.28 ± 0.05  0.1129 
    22:6n3 (docosahexaenoic) 45.37 ± 1.32 35.47 ± 2.71 ↓ 0.0305* 
Fatty acid ratios     
    Unsaturation index 20.77 ± 1.63 14.9 ± 2.57  0.1259 
    LCPUFA/SCPUFA 80.39 ± 4.86 42.53 ± 3.94 ↓ 0.0038* 
    % n3 fatty acids of total 46.12 ± 1.41 35.93 ± 2.77 ↓ 0.0306* 
Fatty acidsRetina
P
Control animalsDiabetic animalsDifference
Total (nmol/mg protein) 488.96 ± 17.64 460.32 ± 27.82  0.43 
n3 fatty acids 225.1 ± 4.23 166.34 ± 20.66 ↓ 0.0495* 
n6 fatty acids 38.67 ± 4.71 40.59 ± 3.9  0.7693 
Mole % of total fatty acids     
    16:0 (palmitic) 15.51 ± 0.8 18.32 ± 1.67  0.2046 
    18:0 (stearic) 18.61 ± 0.97 21.98 ± 2.  0.2046 
    18:1n9 (oleic) 10.58 ± 0.2 12.9 ± 0.77 ↑ 0.0441* 
    18:2n6 (linoleic) 0.44 ± 0.06 0.88 ± 0.05 ↑ 0.0051* 
    18:3n3 (α-linolenic) 0.24 ± 0.06 0.17 ± 0.02  0.3556 
    20:3n6 (dihomo-γ-linolenic) 0.11 ± 0.02 0.04 ± 0.01  0.0819 
    20:3n9 (mead) 0.97 ± 0.06 1.09 ± 0.2  0.6103 
    20:4n6 (arachidonic) 7.33 ± 0.75 7.9 ± 0.64  0.6004 
    20:5n3 (eicosapentaenoic) 0.04 ± 0.02 0.01 ± 0.01  0.2910 
    22:5n3 (docosapentaenoic) 0.47 ± 0.08 0.28 ± 0.05  0.1129 
    22:6n3 (docosahexaenoic) 45.37 ± 1.32 35.47 ± 2.71 ↓ 0.0305* 
Fatty acid ratios     
    Unsaturation index 20.77 ± 1.63 14.9 ± 2.57  0.1259 
    LCPUFA/SCPUFA 80.39 ± 4.86 42.53 ± 3.94 ↓ 0.0038* 
    % n3 fatty acids of total 46.12 ± 1.41 35.93 ± 2.77 ↓ 0.0306* 

Data are means ± SD.

*P < 0.05.

†Long-chain PUFAs/short-chain PUFAs.

FIG. 3.

Fatty acid analysis by RP-HPLC and comparative MS/MS analysis of GPCho lipids in control (n = 3) and diabetic (n = 3) animals at 3–6 weeks post-STZ injection. A: Identification and quantification of diabetes-induced changes in total retina saponified fatty acids. Top: RP-HPLC chromatogram of a mixture of authentic fatty acid standards. Middle: Control retina saponified fatty acids. Bottom: Diabetic retina saponified fatty acids. B: Ratiometric analysis of changes in GPCho lipid abundance (Abund.) between control (□) and diabetic (■) retina. GPCho species were detected by nESI-MS/MS using PI m/z 184 and further characterized as described in research design and methods.C: Ratiometric analysis of changes in GPCho lipid abundance between control and diabetic erythrocytes. Data are presented as means ± SD. *Statistical significance at P < 0.05.

FIG. 3.

Fatty acid analysis by RP-HPLC and comparative MS/MS analysis of GPCho lipids in control (n = 3) and diabetic (n = 3) animals at 3–6 weeks post-STZ injection. A: Identification and quantification of diabetes-induced changes in total retina saponified fatty acids. Top: RP-HPLC chromatogram of a mixture of authentic fatty acid standards. Middle: Control retina saponified fatty acids. Bottom: Diabetic retina saponified fatty acids. B: Ratiometric analysis of changes in GPCho lipid abundance (Abund.) between control (□) and diabetic (■) retina. GPCho species were detected by nESI-MS/MS using PI m/z 184 and further characterized as described in research design and methods.C: Ratiometric analysis of changes in GPCho lipid abundance between control and diabetic erythrocytes. Data are presented as means ± SD. *Statistical significance at P < 0.05.

Close modal

Retinal and erythrocyte phospholipid profiles of control and diabetic animals.

In agreement with saponified fatty acid profile data, nESI-MS/MS analysis of the retina lipid extracts of diabetic animals (n = 3) showed a significant (up to 34%) decrease in the abundance of glycerophospholipids containing DHA22:6n3 compared with the control animals (n = 3). For example, compare the abundance of the GPCho(18:0/22:6) and GPCho(22:6/22:6) lipids in the ratiometric analysis shown in Fig. 3,B. Similar decreases in the abundances of DHA22:6n3 containing lipids were also observed for glycerophosphoethanolamine and glycerophosphoserine lipids (data not shown). In contrast, an increase (37%) in the abundance of the linoleic18:2n6 acid–containing GPCho(16:0/18:2) lipid was observed for the same samples as shown in Fig. 3 B. In addition to known fatty acids identified by HPLC analysis, nESI-MS/MS analysis revealed several VLCPUFAs, primarily 32:6n3 and 34:6n3, esterified to GPCho in the retina. Interestingly, GPCho(32:6/22:6) was significantly decreased (24%) in diabetic retinas compared with controls, and there was a nonsignificant decrease (9%) of GPCho(34:6/22:6).

In erythrocyte lipid extracts, an increase in the abundance of linoleic18:2n6 acid–containing lipids, namely GPCho(16:0/18:2) and GPCho(18:0/18:2), was observed between the diabetic and control samples, consistent with the changes in retina lipids, as shown in Fig. 3 C. Erythrocytes had very low levels of DHA-containing phospholipid species, and there was no effect of diabetes on these species. There was no detectable GPCho(32:6/22:6) or GPCho(34:6/22:6) in the erythrocytes or in liver and blood plasma (data not shown).

Inflammatory marker expression in control and diabetic retinas.

As n3 PUFAs are known to have anti-inflammatory properties, we hypothesized that a decrease in n3 PUFAs would be associated with a proinflammatory state in diabetic retinas. As shown in Fig. 4, diabetic retinas had increased expression levels of several inflammatory markers including adhesion molecules (ICAM-1), cytokines (IL-6), and growth factors (VEGF).

FIG. 4.

Expression levels of inflammatory markers in retinas of control (□, n = 7) and diabetic (■, n = 7) animals. Total RNA was extracted from retinas of control and diabetic animals after 3–6 weeks of diabetes and analyzed by real-time PCR. Diabetes-induced changes in retinal ICAM-1, IL-6, and VEGF expression are shown. Data are presented as means ± SD of at least four independent experiments. *Statistical significance at P < 0.05.

FIG. 4.

Expression levels of inflammatory markers in retinas of control (□, n = 7) and diabetic (■, n = 7) animals. Total RNA was extracted from retinas of control and diabetic animals after 3–6 weeks of diabetes and analyzed by real-time PCR. Diabetes-induced changes in retinal ICAM-1, IL-6, and VEGF expression are shown. Data are presented as means ± SD of at least four independent experiments. *Statistical significance at P < 0.05.

Close modal

The association of dyslipidemia with the development of diabetic retinopathy has been underscored by the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications cohort study (8). Despite this evidence, the experimental data on diabetes-induced changes in lipid profile and lipid metabolism in the retina are not available. This is the first comprehensive study to analyze retinal-specific fatty acid profiles and metabolism and to compare them to liver and blood plasma in control and diabetic animals.

In this study utilizing STZ-induced diabetic rats, we found a decreased level of DHA22:6n3, the major retinal long-chain PUFA, in diabetic retina. This finding confirmed earlier studies showing a decrease in relative percentage of DHA22:6n3 in the diabetic retina (34,35). In addition to DHA22:6n3, VLCPUFAs including 32:6n3 and 34:6n3 were detected as substituents of retina GPCho. VLCPUFAs were not detected in lipid classes other than GPCho and were only detected in retina. Three weeks of diabetes reduced retinal levels of 32:6n3-GPCho compared with controls. As a result of these changes, the diabetic retina had a lower unsaturation index and lower long-chain–to–short-chain PUFA ratio. Moreover, there was a shift toward n3 PUFA–deficient, n6 PUFA–rich, profile in the diabetic retina.

In general, n6 PUFAs induce, while n3 PUFAs inhibit, inflammation, and the relative amount of these PUFAs plays an important role in the regulation of immunity (36). Our previous studies indicated that treatment of a cell type affected by diabetic retinopathy, HRECs, with n6 PUFA leads to a lipoxygenase-dependent increase in ICAM-1/vascular cell adhesion molecule-1 expression (37). Conversely, we have demonstrated that DHA22:6n3 inhibited cytokine-induced activation of the NFκB signaling pathway and adhesion molecule expression in HRECs (28). Thus, a decrease in the n3-to-n6 PUFA ratio in the diabetic retina observed in this study would create proinflammatory conditions potentially contributing to the development of diabetic retinopathy. Indeed, previous studies demonstrated an upregulation in a number of inflammatory markers in the retina early in diabetes: VEGF (4,5), ICAM-1 (6,7), TNF-α (8), and IL-6 (9). ICAM-mediated leukostasis was detected within 1 week of diabetes in rats (38,39). VEGF was shown to increase ICAM expression in retinas of nondiabetic mice (40), and vitreal VEGF levels were found to be correlated with that of IL-6 and severity of diabetic retinopathy in diabetic patients (41).

In this study, we chose a cytokine (IL-6), a growth factor (VEGF), and an adhesion molecule (ICAM-1) as readout of an inflammatory status in the retinas of diabetic animals with decreased n3/n6 PUFAs. mRNA levels of all three markers were elevated in diabetic retinas compared with controls.

Importantly, diabetes induced the most pronounced changes in the retinal fatty acid profile, whereas liver fatty acid profile was only slightly affected, indicating that the disruption of retinal fatty acid metabolism in diabetes might not simply be a result of altered liver metabolism. Moreover, VLCPUFA-containing phospholipids detected in the retina were not present in the liver or erythrocyte total lipids. The fatty acid profile in a particular peripheral tissue depends on two factors: 1) the profile in circulation due to the diet and liver metabolism and 2) the ability of a local tissue to remodel fatty acids. Retina has a unique fatty acid profile characterized by one of the highest levels of DHA22:6n3 in the body and by the presence of VLCPUFAs (27,42). While the expression level of retinal desaturases was relatively low compared with retinal elongases, it has been reported that retina can synthesize DHA22:6n3 from α-linolenic18:3n3 acid and EPA20:5n3 (43). Although retina may obtain additional DHA22:6n3 by uptake from the circulation, changes in the retinal fatty acid profiles of diabetic animals did not mirror changes observed in liver and plasma fatty acid profiles. Thus, a retina-specific decrease in DHA22:6n3 in diabetes is likely to be due to changes in retinal fatty acid metabolism.

To determine the effect of diabetes on retinal fatty acid metabolism, we analyzed the level of fatty acid elongase and desaturase gene expression in control and diabetic animals. Retinas had a very high expression level of the retinal-specific elongase, Elovl4, as well as high expression levels of long-chain PUFA elongase Elovl2. Δ5-, Δ6-, and Δ9-desaturase levels were low compared with the liver expression levels. The high levels of Elovl4 and Elovl2 and low levels of desaturases suggest that the retina is preferentially involved in production of very-long-chain fatty acids and exhibits a low level of de novo lipogenesis. The retinal elongase expression profile that we observed likely explains the high level of long-chain PUFAs in the retina compared with liver and blood plasma levels. Elovl2 elongates C20–22 fatty acids (44,46). Elovl4 was recently shown to be involved in VLCPUFA synthesis with substrate specificity for C26–36 fatty acids (15). The role of VLCPUFAs is not known. Because of their specific presence in tissues with high membrane curvature and their ability to span both leaflets of the lipid bilayer, VLCPUFAs are suggested to play the role of an anchor stabilizing high curvature cellular membranes (15). In the retina, VLCPUFAs are mainly present in the rod outer-segment membrane (15), where they are suggested to play a role in stabilizing the rims of photoreceptor disks. This specific localization might explain low abundance of VLCPUFAs in the total retinal lipids extracted in this study. At the same time, specific localization suggests that VLCPUFAs might play an important role in photoreceptor function. This study provides the first direct evidence that a significant decrease in Elovl4 in diabetic retina is indeed associated with a decrease in VLCPUFA (i.e., 32:6n3) synthesis. Despite lower abundance, diabetes-induced decrease in 32:6n3 containing GPCho (24%) was similar to the decrease in DHA22:6n3 containing GPChos (15–34%). Elovl4 protein expression in diabetic retina was inhibited to a higher degree (73%) compared with mRNA expression (40%), suggesting control of Elovl4 expression at both transcriptional and translational levels. Although decrease of VLCPUFAs is most likely to arise from Elovl4 loss, another plausible explanation could be that this reduction was due to reduction in VLCPUFA precursor lipids, EPA20:5n3, and/or DHA22:6n3. This possibility can be tested in the future by determining whether downregulation of VLCPUFAs in diabetes persists in animals supplemented with high-EPA20:5n3/DHA22:6n3 diet.

Another possibility could be that high level of reactive oxygen species in diabetic retina leads to degradation of a highly oxidation-prone DHA molecule. Previous studies using the same STZ-induced diabetic model of similar duration, however, did not find oxidized DHA products in diabetic retina (47).

Several Elovl4 gene mutations have been recently identified in pathogenesis of another retinal disease, Stargardt-like macular dystrophy (19,21). Stargardt-like macular dystrophy is an autosomal-dominant disorder due to a dominant-negative effect of the mutated Elovl4 on wild-type protein (19). As Elovl4 is highly expressed in the photoreceptors (19,21), it is not surprising that mutant Elovl4 transgenic mice are characterized by lipofuscin accumulation, abnormal electrophysiology, and photoreceptor degeneration (20). Although photoreceptors are not the primary site of diabetic retinopathy, several abnormalities in neural retina have been associated with the development of diabetic retinopathy (48,49). The decrease in Elovl4 observed in this study would not be expected to have as dramatic an effect on photoreceptor viability as the dominant-negative mutation in Elovl4. However, the reduction in Elovl4 in diabetic retina could be responsible for more subtle changes in photoreceptor/RPE cell function that could lead to metabolic changes in the whole retina and eventually contribute to the pathology characteristic of diabetic retinopathy.

In conclusion, a decrease in the expression level of retinal fatty acid elongases Elovl2 and Elovl4 and concomitant decrease in the major n3 PUFA, DHA22:6n3, as well as the VLCPUFA32:6n3, results in an increased n6-to-n3 PUFA ratio in the diabetic retina that likely creates a proinflammatory state contributing to the development of diabetic retinopathy. Increasing the gene expression of fatty acid elongases in the retina represents a potential therapeutic strategy for modulating fatty acid metabolism and altering the pathogenesis of diabetic retinopathy.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

This work was supported by grants from the Juvenile Diabetes Research Foundation (2-2005-97 [to J.V.B.]), the National Institutes of Health (EY-016077 [to J.V.B.], R01RR025386 [to G.E.R. and J.V.B.], and DK 43220 [to D.B.J.]), and MAES MICL02163 (to J.V.B.).

No potential conflicts of interest relevant to this article were reported.

1
Schroder
S
,
Palinski
W
,
Schmid-Schonbein
GW
:
Activated monocytes and granulocytes, capillary nonperfusion, and neovascularization in diabetic retinopathy
.
Am J Pathol
1991
;
139
:
81
100
2
Miyamoto
K
,
Khosrof
S
,
Bursell
SE
,
Rohan
R
,
Murata
T
,
Clermont
AC
,
Aiello
LP
,
Ogura
Y
,
Adamis
AP
:
Prevention of leukostasis and vascular leakage in streptozotocin-induced diabetic retinopathy via intercellular adhesion molecule-1 inhibition
.
Proc Natl Acad Sci U S A
1999
;
96
:
10836
10841
3
Adamis
AP
:
Is diabetic retinopathy an inflammatory disease?
Br J Ophthalmol
2002
;
86
:
363
365
4
Yang
LP
,
Sun
HL
,
Wu
LM
,
Guo
XJ
,
Dou
HL
,
Tso
MO
,
Zhao
L
,
Li
SM
:
Baicalein reduces inflammatory process in a rodent model of diabetic retinopathy
.
Invest Ophthalmol Vis Sci
2009
;
50
:
2319
2327
5
Sone
H
,
Kawakami
Y
,
Okuda
Y
,
Sekine
Y
,
Honmura
S
,
Matsuo
K
,
Segawa
T
,
Suzuki
H
,
Yamashita
K
:
Ocular vascular endothelial growth factor levels in diabetic rats are elevated before observable retinal proliferative changes
.
Diabetologia
1997
;
40
:
726
730
6
Nozaki
M
,
Ogura
Y
,
Hirabayashi
Y
,
Saishin
Y
,
Shimada
S
:
Enhanced expression of adhesion molecules of the retinal vascular endothelium in spontaneous diabetic rats
.
Ophthalmic Res
2002
;
34
:
158
164
7
Al-Shabrawey
M
,
Rojas
M
,
Sanders
T
,
Behzadian
A
,
El-Remessy
A
,
Bartoli
M
,
Parpia
AK
,
Liou
G
,
Caldwell
RB
:
Role of NADPH oxidase in retinal vascular inflammation
.
Invest Ophthalmol Vis Sci
2008
;
49
:
3239
3244
8
Joussen
AM
,
Poulaki
V
,
Mitsiades
N
,
Kirchhof
B
,
Koizumi
K
,
Dohmen
S
,
Adamis
AP
:
Nonsteroidal anti-inflammatory drugs prevent early diabetic retinopathy via TNF-alpha suppression
.
FASEB J
2002
;
16
:
438
440
9
Gustavsson
C
,
Agardh
CD
,
Hagert
P
,
Agardh
E
:
Inflammatory markers in nondiabetic and diabetic rat retinas exposed to ischemia followed by reperfusion
.
Retina
2008
;
28
:
645
652
10
Lyons
TJ
,
Jenkins
AJ
,
Zheng
D
,
Lackland
DT
,
McGee
D
,
Garvey
WT
,
Klein
RL
:
Diabetic retinopathy and serum lipoprotein subclasses in the DCCT/EDIC cohort
.
Invest Ophthalmol Vis Sci
2004
;
45
:
910
918
11
Coppack
SW
,
Evans
RD
,
Fisher
RM
,
Frayn
KN
,
Gibbons
GF
,
Humphreys
SM
,
Kirk
ML
,
Potts
JL
,
Hockaday
TD
:
Adipose tissue metabolism in obesity: lipase action in vivo before and after a mixed meal
.
Metabolism
1992
;
41
:
264
272
12
Weinstock
PH
,
Levak-Frank
S
,
Hudgins
LC
,
Radner
H
,
Friedman
JM
,
Zechner
R
,
Breslow
JL
:
Lipoprotein lipase controls fatty acid entry into adipose tissue, but fat mass is preserved by endogenous synthesis in mice deficient in adipose tissue lipoprotein lipase
.
Proc Natl Acad Sci U S A
1997
;
94
:
10261
10266
13
Julius
U
:
Influence of plasma free fatty acids on lipoprotein synthesis and diabetic dyslipidemia
.
Exp Clin Endocrinol Diabetes
2003
;
111
:
246
250
14
Sprecher
H
,
Chen
Q
:
Polyunsaturated fatty acid biosynthesis: a microsomal-peroxisomal process
.
Prostaglandins Leukot Essent Fatty Acids
1999
;
60
:
317
321
15
Agbaga
MP
,
Brush
RS
,
Mandal
MN
,
Henry
K
,
Elliott
MH
,
Anderson
RE
:
Role of Stargardt-3 macular dystrophy protein (ELOVL4) in the biosynthesis of very long chain fatty acids
.
Proc Natl Acad Sci U S A
2008
;
105
:
12843
12848
16
Lagali
PS
,
Liu
J
,
Ambasudhan
R
,
Kakuk
LE
,
Bernstein
SL
,
Seigel
GM
,
Wong
PW
,
Ayyagari
R
:
Evolutionarily conserved ELOVL4 gene expression in the vertebrate retina
.
Invest Ophthalmol Vis Sci
2003
;
44
:
2841
2850
17
Umeda
S
,
Ayyagari
R
,
Suzuki
MT
,
Ono
F
,
Iwata
F
,
Fujiki
K
,
Kanai
A
,
Takada
Y
,
Yoshikawa
Y
,
Tanaka
Y
,
Iwata
T
:
Molecular cloning of ELOVL4 gene from cynomolgus monkey (Macaca fascicularis)
.
Exp Anim
2003
;
52
:
129
135
18
Zhang
XM
,
Yang
Z
,
Karan
G
,
Hashimoto
T
,
Baehr
W
,
Yang
XJ
,
Zhang
K
:
Elovl4 mRNA distribution in the developing mouse retina and phylogenetic conservation of Elovl4 genes
.
Mol Vis
2003
;
9
:
301
307
19
Grayson
C
,
Molday
RS
:
Dominant negative mechanism underlies autosomal dominant Stargardt-like macular dystrophy linked to mutations in ELOVL4
.
J Biol Chem
2005
;
280
:
32521
32530
20
Karan
G
,
Lillo
C
,
Yang
Z
,
Cameron
DJ
,
Locke
KG
,
Zhao
Y
,
Thirumalaichary
S
,
Li
C
,
Birch
DG
,
Vollmer-Snarr
HR
,
Williams
DS
,
Zhang
K
:
Lipofuscin accumulation, abnormal electrophysiology, and photoreceptor degeneration in mutant ELOVL4 transgenic mice: a model for macular degeneration
.
Proc Natl Acad Sci U S A
2005
;
102
:
4164
4169
21
Zhang
K
,
Kniazeva
M
,
Han
M
,
Li
W
,
Yu
Z
,
Yang
Z
,
Li
Y
,
Metzker
ML
,
Allikmets
R
,
Zack
DJ
,
Kakuk
LE
,
Lagali
PS
,
Wong
PW
,
MacDonald
IM
,
Sieving
PA
,
Figueroa
DJ
,
Austin
CP
,
Gould
RJ
,
Ayyagari
R
,
Petrukhin
K
:
A 5-bp deletion in ELOVL4 is associated with two related forms of autosomal dominant macular dystrophy
.
Nat Genet
2001
;
27
:
89
93
22
Brenner
RR
:
Hormonal modulation of delta6 and delta5 desaturases: case of diabetes
.
Prostaglandins Leukot Essent Fatty Acids
2003
;
68
:
151
162
23
Nakamura
MT
,
Nara
TY
:
Gene regulation of mammalian desaturases
.
Biochem Soc Trans
2002
;
30
:
1076
1079
24
Rimoldi
OJ
,
Finarelli
GS
,
Brenner
RR
:
Effects of diabetes and insulin on hepatic delta6 desaturase gene expression
.
Biochem Biophys Res Commun
2001
;
283
:
323
326
25
Wang
Y
,
Botolin
D
,
Xu
J
,
Christian
B
,
Mitchell
E
,
Jayaprakasam
B
,
Nair
MG
,
Peters
JM
,
Busik
JV
,
Olson
LK
,
Jump
DB
:
Regulation of hepatic fatty acid elongase and desaturase expression in diabetes and obesity
.
J Lipid Res
2006
;
47
:
2028
2041
26
Meyer
A
,
Kirsch
H
,
Domergue
F
,
Abbadi
A
,
Sperling
P
,
Bauer
J
,
Cirpus
P
,
Zank
TK
,
Moreau
H
,
Roscoe
TJ
,
Zahringer
U
,
Heinz
E
:
Novel fatty acid elongases and their use for the reconstitution of docosahexaenoic acid biosynthesis
.
J Lipid Res
2004
;
45
:
1899
1909
27
Anderson
RE
:
Lipids of ocular tissues: IV. A comparison of the phospholipids from the retina of six mammalian species
.
Exp Eye Res
1970
;
10
:
339
344
28
Chen
W
,
Esselman
WJ
,
Jump
DB
,
Busik
JV
:
Anti-inflammatory effect of docosahexaenoic acid on cytokine-induced adhesion molecule expression in human retinal vascular endothelial cells
.
Invest Ophthalmol Vis Sci
2005
;
46
:
4342
4347
29
Lydic
TA
,
Busik
JV
,
Esselman
WJ
,
Reid
GE
:
Complementary precursor ion and neutral loss scan mode tandem mass spectrometry for the analysis of glycerophosphatidylethanolamine lipids from whole rat retina
.
Anal Bioanal Chem
2009
;
394
:
267
275
30
Murphy
EJ
,
Stephens
R
,
Jurkowitz-Alexander
M
,
Horrocks
LA
:
Acidic hydrolysis of plasmalogens followed by high-performance liquid chromatography
.
Lipids
1993
;
28
:
565
568
31
Rose
H
,
Oklander
M
:
An improved method for the extraction of lipids from human erythrocytes
.
J Lipid Res
1965
;
6
:
428
443
32
Han
X
,
Gross
RW
:
Shotgun lipidomics: electrospray ionization mass spectrometric analysis and quantitation of cellular lipidomes directly from crude extracts of biological samples
.
Mass Spectrom Rev
2005
;
24
:
367
412
33
Haimi
P
,
Uphoff
A
,
Hermansson
M
,
Somerharju
P
:
Software tools for analysis of mass spectrometric lipidome data
.
Anal Chem
2006
;
78
:
8324
8331
34
Futterman
S
,
Sturtevant
R
,
Kupfer
C
:
Effect of alloxan diabetes on the fatty acid composition of the retina
.
Invest Ophthalmol
1969
;
8
:
542
544
35
Hegde
KR
,
Varma
SD
:
Electron impact mass spectroscopic studies on mouse retinal fatty acids: effect of diabetes
.
Ophthalmic Res
2009
;
42
:
9
14
36
Harbige
LS
:
Fatty acids, the immune response, and autoimmunity: a question of n-6 essentiality and the balance between n-6 and n-3
.
Lipids
2003
;
38
:
323
341
37
Chen
W
,
Jump
DB
,
Grant
MB
,
Esselman
WJ
,
Busik
JV
:
Dyslipidemia, but not hyperglycemia, induces inflammatory adhesion molecules in human retinal vascular endothelial cells
.
Invest Ophthalmol Vis Sci
2003
;
44
:
5016
5022
38
Joussen
AM
,
Poulaki
V
,
Qin
W
,
Kirchhof
B
,
Mitsiades
N
,
Wiegand
SJ
,
Rudge
J
,
Yancopoulos
GD
,
Adamis
AP
:
Retinal vascular endothelial growth factor induces intercellular adhesion molecule-1 and endothelial nitric oxide synthase expression and initiates early diabetic retinal leukocyte adhesion in vivo
.
Am J Pathol
2002
;
160
:
501
509
39
Joussen
AM
,
Murata
T
,
Tsujikawa
A
,
Kirchhof
B
,
Bursell
SE
,
Adamis
AP
:
Leukocyte-mediated endothelial cell injury and death in the diabetic retina
.
Am J Pathol
2001
;
158
:
147
152
40
Lu
M
,
Perez
VL
,
Ma
N
,
Miyamoto
K
,
Peng
HB
,
Liao
JK
,
Adamis
AP
:
VEGF increases retinal vascular ICAM-1 expression in vivo
.
Invest Ophthalmol Vis Sci
1999
;
40
:
1808
1812
41
Funatsu
H
,
Yamashita
H
,
Shimizu
E
,
Kojima
R
,
Hori
S
:
Relationship between vascular endothelial growth factor and interleukin-6 in diabetic retinopathy
.
Retina
2001
;
21
:
469
477
42
Fliesler
SJ
,
Anderson
RE
:
Chemistry and metabolism of lipids in the vertebrate retina
.
Prog Lipid Res
1983
;
22
:
79
131
43
Delton-Vandenbroucke
I
,
Grammas
P
,
Anderson
RE
:
Polyunsaturated fatty acid metabolism in retinal and cerebral microvascular endothelial cells
.
J Lipid Res
1997
;
38
:
147
159
44
Moon
YA
,
Shah
NA
,
Mohapatra
S
,
Warrington
JA
,
Horton
JD
:
Identification of a mammalian long chain fatty acyl elongase regulated by sterol regulatory element-binding proteins
.
J Biol Chem
2001
;
276
:
45358
45366
45
Jakobsson
A
,
Westerberg
R
,
Jacobsson
A
:
Fatty acid elongases in mammals: their regulation and roles in metabolism
.
Prog Lipid Res
2006
;
45
:
237
249
46
Leonard
AE
,
Pereira
SL
,
Sprecher
H
,
Huang
YS
:
Elongation of long-chain fatty acids
.
Prog Lipid Res
2004
;
43
:
36
54
47
Sunada
S
,
Kiyose
C
,
Kubo
K
,
Takebayashi
J
,
Sanada
H
,
Saito
M
:
Effect of docosahexaenoic acid intake on lipid peroxidation in diabetic rat retina under oxidative stress
.
Free Radic Res
2006
;
40
:
837
846
48
Barber
AJ
,
Lieth
E
,
Khin
SA
,
Antonetti
DA
,
Buchanan
AG
,
Gardner
TW
:
Neural apoptosis in the retina during experimental and human diabetes: early onset and effect of insulin
.
J Clin Invest
1998
;
102
:
783
791
49
Gardner
TW
,
Antonetti
DA
,
Barber
AJ
,
LaNoue
KF
,
Nakamura
M
:
New insights into the pathophysiology of diabetic retinopathy: potential cell-specific therapeutic targets
.
Diabetes Technol Ther
2000
;
2
:
601
608