A Synergistic Combination of DHA, Luteolin, and Urolithin A Against Alzheimer’s Disease

Introduction

Plants, the immobile life on earth, have the inherent ability to synthesize defensive secondary metabolites, commonly known as phytochemicals, to withstand attacks by different organisms such as pathogens, insects, and herbivores. These phytochemicals have proven bioactivity through modulating molecular targets in living beings (Efferth and Koch, 2011). These bioactive phytochemicals are used in traditional medicine in China and Sri Lanka, and Ayurveda in India. These medicine systems use herbal mixtures consisting of many different herbs to treat diseases (Thomas and Egon, 2011).

The unraveling of complex disease mechanisms in modern medicine by technological advancement has immensely contributed to a greater understanding of drug interactions and usage of drug combinations in therapeutic regimes. In combination drug therapies, the simultaneous action of drugs in low doses increases therapeutic efficacy and decreases toxicity effects and drug resistance (Sun et al., 2016). Combination drug therapies are widely researched in treating diseases such as cancer (De Kok et al., 2008), human immunodeficiency virus (HIV) infection (Moreno et al., 2019), and many other ailments. Furthermore, combining natural compounds is popularizing in dealing with medical conditions where there is a shortage of discovery and approval of new drugs, and the existing monotherapies have shown limited therapeutic efficacy (Patti et al., 2017; Santana-Gálvez et al., 2019).

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and is the second major cause of death in Australia. The classical AD brain is characterized by extracellular deposition of amyloid-β (Aβ) protein aggregates as senile plaques and intracellular neurofibrillary tangles (NFTs), composed of hyper-phosphorylated forms of the microtubule-associated protein Tau. Amyloid beta peptides are formed by the normal metabolic processing of amyloid precursor protein (APP). The predominant (90%) Aβ peptides are Aβ_1–40 and Aβ_1–42, respectively, with the latter being the most toxic (Selkoe, 2001; Murphy and Levine, 2010; Tiwari and Kepp, 2016).

It has been reported that by February 2020, there were 121 drugs studied in 136 AD therapeutic trials (Cummings et al., 2020). However, considering the past decade, many clinical trials have failed outright while the efficacy and effect size have been problematic in the ones that have indicated a positive outcome (Banik et al., 2015). There has been no new drug approved within the past 16 years until the controversial approval of the drug Aducanumab recently in 2021 (Rabinovici, 2021).

Due to the toxicity associated with the use of currently available drugs and their limited therapeutic effectiveness, the purposed drugs for AD are being repositioned as combinations (Cummings et al., 2019; Kabir et al., 2020). Considering the multifactorial nature of AD, combinations of therapeutic agents may be effective than monotherapies. One study reported that a drug combination of two approved drugs, acamprosate and baclofen synergistically protected rat cortical neurons and human brain-derived microvascular endothelial cells against Aβ oligomer-induced toxicity (Chumakov et al., 2015). Furthermore, this combination has alleviated cognitive deficits in an acute Aβ_25–35 peptide injection mouse model and a mutant APP transgenic mouse model (Chumakov et al., 2015). Many studies and clinical trials have been conducted for AD drug combinations, to name a few, the N-methyl-D-aspartate (NMDA) receptor antagonist Memantine with various Acetyl Cholinesterase inhibitors such as Memantine and Rivastigmine (Dantoine et al., 2006; Riepe et al., 2007), Memantine, and Donepezil (Tariot et al., 2004; Cummings et al., 2006) and Memantine and Galantamine (Simoni et al., 2012).

Prevention of AD has become an important consideration, particularly since disease-modifying treatment trials have proven unsuccessful. As AD is a complex multifactorial disorder, there may also be multiple ways to prevent or delay the onset of AD (Galvin, 2017). It suggests that prevention studies focusing on risk reduction and lifestyle modification by diet and exercise may be an alternative approach offering additional benefits. In the modulation of lifestyle, diet plays a major role. The Mediterranean diet (MeDi) plays an important role to reduce the risk for AD (Scarmeas et al., 2006; Panza et al., 2018). MeDi is characterized by a high intake of vegetables, fruits, unsaturated fatty acids (in the form of olive oil), fish, a low-to-moderate intake of dairy products such as cheese or yogurt, a low intake of meat, and poultry and a regular but moderate amount of red wine (Scarmeas et al., 2006). These vital food items in a typical MeDi are rich in bioactive components that are reported as potentially beneficial for cognitive performance in AD (Cremonini et al., 2019; Grodzicki and Dziendzikowska, 2020).

One rich source of polyphenols is pomegranate, which possesses many polyphenolic compounds such as ellagitannins (ETs) and flavonoids (Sreekumar et al., 2014). Punicalagin is the most abundant ET in pomegranate juice with a very low bioavailability (Cerda et al., 2003). In the lower digestive tract, punicalagins are converted by the gut microbiota into urolithin A (UA), which has a relatively higher bioavailability (Seeram et al., 2006; Espin et al., 2013). According to Hartman et al. (2006), mice treated with pomegranate juice had significantly less (∼50%) soluble Aβ₄₂ and amyloid deposition in the hippocampus as compared to control mice (Hartman et al., 2006). However, the anti-AD effects of pomegranate are due to UA (Yuan et al., 2016; Gong et al., 2019). Luteolin (LUT) is a prominent flavone compound in pomegranate peel (Van Elswijk et al., 2004; Chaudhari et al., 2014; Liu et al., 2017). It shows potent anti-inflammatory and antioxidant activities (Xia et al., 2014). It also inhibits BACE1 by suppressing the BACE1 promoter by NF-κB signaling (Zheng et al., 2015). Moreover, LUT has been reported to reduce zinc-induced Tau hyperphosphorylation in SH-SY5Y Cells (Zhou et al., 2012). Luteolin has also been shown to ameliorate neurotoxicity in an Aβ toxicity model that used Aβ_25–35 peptide in murine cortical neurons (Choi et al., 2014). Overall, there are only a limited number of studies carried out on the activity of these pomegranate-related polyphenols on the inhibition of Aβ_1–42 induced toxicity.

Omega-3 polyunsaturated fatty acids including docosahexaenoic acid (DHA) naturally occur in marine food sources such as fish and algae (Tocher, 2015; Peltomaa et al., 2017). An in vivo experiment carried out in mouse expressing human APP K670N-M671L (APPsw) transgenic mouse model (Tg2576) has shown that DHA treatment lowers Aβ₄₀ and Aβ₄₂ levels and Aβ plaque burden (Lim et al., 2005). Some in vitro experiments demonstrated that DHA decreases the BACE1 and γ-secretase activity and increases the α-secretase activity. It has been reported that DHA effectively reduced Aβ release by driving the amyloidogenic processing of APP toward non-amyloidogenic processing (Grimm et al., 2011). An in vitro study indicated that DHA reduced soluble Aβ oligomer levels and further inhibited formation of Aβ_1–42 fibrils (Hossain et al., 2009). Furthermore, another study showed that DHA reduced formation of Aβ oligomers and fibrils in the cerebral cortex of Aβ-infused rats (Hashimoto et al., 2009). However, the few studies that have investigated DHA on Aβ_1–42 induced toxicity need confirmation by a more thorough investigation.

Some reports have investigated the combined effect of multi-targeting nutraceutical compounds in AD in vitro models (Espargaró et al., 2017). It has recently been shown in Tg2576 transgenic mice that a combination of food-derived compounds, EGCG, DHA, and α-lipoic acid exerted potent anti-inflammatory and neuroprotective effects (Sharman et al., 2019). However, similar studies targeting bioactive compound combinations against AD are still limited in the literature.

The objective of the present study was to investigate the compounds, DHA, LUT, and UA (Figure 1) in vitro for any nutraceutical combinations potentially effective against AD. The compounds were initially screened for their activity to inhibit Aβ_1–42-induced toxicity and were subsequently used to determine synergistic combinations in vitro that may be more potent in action against Aβ_1–42 compared to single compounds. For drug combinations, quantifying synergism and antagonism through CI calculations was performed by the third-generation computer software, “CompuSyn” written by Ting-Chao Chou and Nick Martin (MIT, MA, United States) in 2005 (ComboSyn, Inc., MA, United States).

FIGURE 1

Figure 1. The compounds of interest. The compounds investigated in the present study were, omega-3 polyunsaturated fatty acid, docosahexaenoic acid (DHA) and pomegranate-derived compounds: luteolin (LUT), urolithin A (UA).

Materials and Methods

Materials

cis-4,7,10,13,16,19-Docosahexaenoic acid (DHA: D2534), LUT (L9283), UA (SML1791), and dimethyl sulfoxide (DMSO) were obtained from Sigma Aldrich, United States. BE(2)-M17 cells (ATCC^® CRL2267™) were purchased from American Type Cell Culture Collection (ATCC, Manassas, VA, United States). All cell culture reagents including Dulbecco’s Modified Eagle Medium (DMEM), Ham’s F12 medium, Hank’s balanced salt solution (HBSS), fetal calf serum (FCS) and Trypsin-EDTA (0.5%) were purchased from GIBCO by Life Technologies (United States). Human Aβ_1–42 peptides were synthesized, purified and characterized by high pressure liquid chromatography (HPLC) and mass spectrometry (MS) by The ERI Amyloid Laboratories LLC, United States. Anhydrous DMSO was purchased from Molecular Probes by Life Technologies (United States). CellTiter 96^® AQueous One Solution Cell Proliferation assay (MTS: 3-(4,5-Dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) and CytoTox-ONE™ Homogeneous Membrane Integrity assay kits (Lactate dehydrogenase: LDH assay), and CellTiter-Glo luminiscent cell viability assay kits were purchased from Promega (Madison, WI, United States).

Cell Culture

Human neuroblastoma BE(2)-M17 cells were maintained in T75 culture flasks containing 15 mL of DMEM/F12 (1:1 ratio) growth media supplemented with 10% (v/v) FCS and placed in a humidified incubator with 5% CO₂/95% air at 37°C. Upon reaching about 80% confluency, the cells were sub-cultured on to fresh cell culture flasks. For all cell culture experiments, passage number did not exceed 30.

Preparation of Oligomeric Aβ_1–42

The oligomeric Aβ_1–42 was prepared according to the method of Stine et al. (2011) with some modifications (Stine et al., 2011). The detailed method used for Aβ_1–42 preparation is explained in our previous work (Jayatunga et al., 2021).

Aβ_1–42 Induced Toxicity/Lactate Dehydrogenase Assay

For Aβ_1–42 toxicity experiments, cells were plated in 96-well tissue culture microplates at a density of 1.5 × 10⁴ cells/well and incubated for 24 hours. The cell culture media was then replaced with treatment media (1% FCS) and the cells were pre-treated with different concentrations of the compounds, DHA, LUT, and UA (5 μM to 40 μM) for 24 hours. The cells were then treated with oligomeric 20 μM Aβ_1–42 with appropriate controls (vehicle-treatment: negative control; Aβ_1–42–treatement: positive control). The microplates were incubated in the humidified incubator with 5% CO₂/95% air for 72 h at 37°C. The percentage LDH release for all treatments were determined using LDH assay. LDH release results of Aβ_1–42-induced toxicity assays for the compounds DHA, LUT, and UA.

The% LDH release results of Aβ_1–42–induced toxicity assays for the compounds DHA, LUT, and UA were normalized according to the method used by Chumakov et al. (2015). As shown below, the vehicle and the Aβ_1–42 added treatments were considered as 1 and 0, respectively (Chumakov et al., 2015). The coded data were considered as the fractions affected (F_a) and used along with their respective concentrations (5 to 40 μM) as input for the computer program CompuSyn v.1.0.

Calculation of F_a - method adapted from Chumakov et al. (2015).

Preparation of Compound Solutions

The compounds DHA, LUT, and UA were dissolved in dimethylsulfoxide (DMSO) and 10 mM stock solutions were prepared from each. The stock solutions were frozen and working solutions were prepared using treatment media (DMEM/F12 supplemented with 1% FCS). Control solutions were used for all compounds at all concentrations.

Combination Studies

MTS Assay

Alternatively, all possible two-compound combinations (n = 75) for the compounds DHA, LUT, and UA (for the concentration range of 5 μM to 40 μM) were used for screening the combinations with the greatest efficacy to inhibit Aβ_1–42–induced toxicity. For that, BE(2)-M17 cells were maintained in DMEM/F12 medium supplemented with 10% FCS, in 5% CO₂ at 37°C. For Aβ_1–42 toxicity experiments, cells were plated in 96-well tissue culture microplates at a density of 1.5 × 10⁴ cells/well and incubated for 24 h. After replacing the media with treatment media, the cells were pre-treated with each two-compound combinations for 24 h. The cells were then treated with oligomeric 20 μM Aβ including controls for vehicle (negative control) and Aβ_1–42 (positive control). The microplates were incubated in a humidified incubator with 5% CO₂/95% air for 72 h at 37°C. Percentage cell viability for each combination was determined (N = 4) using the MTS assay.

Determination of Best Combinations by LDH Assay

The combinations with higher% cell viabilities were re-screened with the LDH assay. Percentage protection was calculated from the% LDH release for all compound combinations. The experiments consisted of all 3 compounds combining with each other at 5, 10, 20, and 40 μM concentrations. The coded data were considered as data of F_a and used along with their respective concentrations (doses) as input in the computer program CompuSyn v.1.0 for calculating CI values. Thirteen synergistic combinations were recognized by the CI values less than 1.

Validation of the Synergistic Two-Compound Combinations Using CellTiter Glo Assay

The synergistic combinations were further validated and confirmed by cellular ATP levels using the CelltiterGlo assay. Briefly, the BE(2)-M17 cells in DMEM/F12 medium supplemented with 10% FCS were seeded in 96-well tissue culture microplates at a density of 1.5 × 104 cells/well and were incubated at 37°C for 24 h. After the respective treatment of compounds and incubation at 37°C, cellular ATP levels were measured using CellTiter Glo ATP detection kit as per the manufacturer’s instructions (Promega). Briefly, cells were placed at RT for 30 min and then lysed by adding 100 μL of ATP-releasing reagent. The lysates were incubated with the luciferin substrate and luciferase enzyme in the dark for 10 min to stabilize the luminescence signal. The luminescence (RLU) was measured using a Perkin Elmer EnSpire multi-mode plate reader.

Prediction of a Potentially Synergistic Three-Compound Combination and Validation

Based on the validation data for the two-compound combinations, a new three-compound combination was predicted. This combination was repeated and confirmed as efficiently inhibiting Aβ_1–42-induced toxicity using MTS, LDH, and CellTiter Glo assays.

Statistical Analysis

All results were expressed as mean ± standard deviation (SD) from four (N = 4) independent experiments. Statistical significance was determined by one-way ANOVA and Tukey’s post hoc test in SPSS v25. Significance was defined as P < 0.05.

Results

Thirteen Synergistic Two-Compound Combinations Derived in silico

There were thirteen two-compound combinations that were determined to be synergistic based on their CI values, being less than 1 (Table 1). Table 1 summarizes the thirteen synergistic combinations (numbered as combinations 1-13) that belong to UA-DHA, LUT-DHA, and UA-LUT. The inferences on synergy with subtle definitions were based on the work of Chou and Talalay (1984).

TABLE 1

Table 1. In silico-derived synergistic two-compound combinations.

Two Best Synergistic Two-Compound Combinations Based on Validations for Relative ATP Levels

Based on the validation of results for all 13 synergistic combinations, the combination 2 (D₅U₅: DHA 5 μM and UA 5 μM) and 11 (L₅U₅: LUT 5 μM and UA 5 μM) were selected as the best combinations based on two reasons. First, their significantly higher relative ATP levels compared to both components in the combinations independently. Second, they both had the lowest possible concentrations used in this study. Relative ATP level of the cells was reduced to 51.9 + 7.0% of the control treatment after 72 h exposure to 20 μM Aβ_1–42 treatment. Pre-treatment with the combination 2 (D₅U₅) increased the cellular ATP levels to 71.3 + 7.9% (P < 0.001) (Figure 2).

FIGURE 2

Figure 2. Relative ATP levels for the combination 2 (D₅U₅) and its components. ATP levels for the combination 2 (D₅U₅) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle control, ***P < 0.001 vs. Aβ_1–42-treated control, ^#P < 0.05 vs. DHA 5 μM and ^$P < 0.05 vs. UA 5 μM.

Similarly, pre-treatment with the combination 11 (L₅U₅) increased the ATP levels to 99.6 ± 4.2% (P < 0.001) (Figure 3). In either case, the combinations gave significantly higher ATP levels against the Aβ_1–42-treated controls than the component compound concentrations (DHA, LUT, and UA 5 μM each). These results suggest that pre-treatment with these combinations effectively attenuated Aβ_1–42-induced toxicity.

FIGURE 3

Figure 3. Relative ATP levels for the combination 11 (L₅U₅) and its components. ATP levels for the combination 11 (L₅U₅) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs vehicle control, ***P < 0.001 vs. Aβ_1–42-treated control, ^###P < 0.001 vs. LUT 5 μM and UA 5 μM.

Prediction and Validation of a New Three-Compound Combination-D₅L₅U₅ (DHA 5 μM, LUT 5 μM, UA 5 μM)

Based on the two best combinations identified, namely 2 and 11, a new combination was predicted. This composed of all the three compounds, DHA, LUT, and UA, each at a concentration of 5 μM and namely, D₅L₅U₅. The predicted three-compound combination, D₅L₅U₅ was analyzed for its ability to inhibit Aβ_1–42-induced toxicity using MTS and LDH assays. The analysis of LDH results by the program CompuSyn v.1.0 determined the three-compound combination, D₅L₅U₅ as synergistic with a CI value of 0.01 (Table 2). Percentage cell viability of BE(2)-M17 cells was decreased to 46.0 ± 3.7% of control (P < 0.001) after 72 h of 20 μM Aβ_1–42 treatment, while pre-treatment with D₅L₅U₅ improved the cell viability to 103.6 ± 8.7% (P < 0.001) (Figure 4A). Additionally, 20 μM Aβ_1–42 treatment increased the release of LDH in the cells from 7.39 ± 0.04% (vehicle-treated cells) to 25.4 ± 0.5% (Aβ_1–42-treated cells) (P < 0.001) and the D₅L₅U₅ pre-treatment significantly reduced the LDH release to 7.3 ± 1.4% (P < 0.001) Figure 4B. Cells after treating with D₅L₅U₅ showed an intact morphology with visually reduced toxic effects and increased proliferation compared to Aβ_1–42-treated cells (Figure 5). These results together indicated that pre-treatment with the three-compound combination, D₅L₅U₅ attenuated Aβ_1–42-induced toxicity very effectively.

TABLE 2

Table 2. Predicted three-compound combination D₅L₅U₅ and its combination index derived by CompySyn v. 1.0.

FIGURE 4

Figure 4. The effect of D₅L₅U₅ on Aβ_1–42-induced toxicity. (A) % cell viability (B) % LDH release determined from MTS and LDH assays, respectively, with pre-treatment of D₅L₅U₅ in BE(2)-M17 cells for 24 h followed by incubation with 20 μM Aβ_1–42 for 72 h at 37°C. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^a,bP < 0.001 vs vehicle control, ***P < 0.001, ^###P < 0.001 vs. Aβ_1–42-treated control.

FIGURE 5

Figure 5. BE(2)-M17 cell morphology for vehicle-treated control, Aβ_1–42-treated control and the D₅L₅U₅ treatment. Comparison of cells for 20 μM Aβ_1–42-treatment with and without D₅L₅U₅ pre-treatment. The BE(2)-M17 cells are pre-treated with D₅L₅U₅ followed by exposure of 20 μM Aβ_1–42 for 72 h. Cell morphology was imaged using a Nikon phase-contrast microscope (X40).

Validation of the combinations 2 and 11 and the three-compound combination along with their single components. ATP level of BE(2)-M17 cells was decreased to 51.9 ± 7.0% of control (P < 0.001) after 72 h of 20 μM Aβ_1–42 treatment. Pre-treatment with the combination 2 (D₅U₅) increased the cellular ATP levels to 71.3 ± 7.9% (P < 0.001)while the combination 11 (L₅U₅) increased the ATP levels to 99.6 ± 4.2% which is a significantly increased ATP level (P < 0.001) compared to the combination 2 (D₅U₅). However, pre-treatment with the three-compound combination (D₅L₅U₅) resulted in the highest most ATP levels which amounted to 110.8 ± 4.2%. This ATP level is significantly higher compared to that of both combination 2 (D₅U₅) (P < 0.001) and 11 (L₅U₅) (P = 0.001) (Figure 6). These results reflect the previous data that the three-compound combination, D₅L₅U₅ attenuates Aβ_1–42-induced toxicity better than its two-compound combination counterparts, D₅U₅ and L₅U₅.

FIGURE 6

Figure 6. Comparison of the two-compound combinations D₅U₅, L₅U₅ and the three-compound combination D₅L₅U₅. ATP levels for the D₅U₅, L₅U₅, D₅L₅U₅ and their single components were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle control, ^&&&P < 0.001 vs. Aβ_1–42-treated control, ***P < 0.001, ^###P < 0.001 vs. D₅U₅ and ^$$P = 0.001 vs. L₅U₅.

Discussion

Effective alternate approaches to AD drug development are critically needed as most of all clinical drug immunotherapy trials have failed to date (Anderson et al., 2017; Mehta et al., 2017). Thus, food-derived compounds warrant investigation being potential therapeutic agents (Thaipisuttikul and Galvin, 2012; Lange et al., 2019; Peng et al., 2021). These emerging alternative strategies using natural compounds hold promise for early intervention by targeting the prodromal phase of the disease (Lange et al., 2019). Considering the complexity and the multi-faceted nature of AD neuropathology, a combination of multiple therapeutic targets that can intervene several pathophysiological pathways is preferred. An advantage of combination therapy is where there is a disparity among the drugs of interest. For instance, if one drug has a desirable profile and the other gives undesirable side-effects at a selected dose, it may be possible to combine the two drugs by using different combination ratios, in obtaining a synergistic outcome (Chou, 2006, 2010).

In vitro studies are important as a starting point for drug combination studies. Even though in vitro and in vivo drug combination analyses follow the same principles, animal studies are more expensive, time consuming and often subjected to more variability of data. Although the latter is an essential next step in the evaluation process, initial investigations under in vitro conditions are a cost reduction and thereby, is the logical first step. Furthermore, in vitro studies are more flexible in liability considerations and in using death as an endpoint of toxicity (Chou, 2010). It is well known that in vitro data may not always predict in vivo results, and in vivo animal data may not always predict clinical results (Van Norman, 2020). However, drug combination studies strictly need an initial in vitro component as analyzing the effects of sub-optimal doses in vivo is not ethical. Therefore, it is recommended to initiate preclinical studies in cells before animal or human investigations (Chou, 2010). Reporting antagonistic drug combinations is equally important as it may hint on possible contraindications in vivo and thus avoid unnecessary preclinical and clinical trials (Chou, 2010). The current study used human neuroblastoma BE(2)-M17 cells for their relative convenience to use and ability to induce neuronal differentiation (Andres et al., 2013) that is required at next stages of this research work.

A synergistic three-compound combination (D₅L₅U₅) comprising of three nutraceutical compounds was identified in vitro from the present study. It was found to exert significantly higher ATP levels in the presence of Aβ_1–42 compared to the two two-compound combinations (D₅U₅ and L₅U₅) from which the three-compound combination was derived (Figure 6). This finding was aided by the Chou-Talalay method of drug combinations which is based on median-effect principle (Chou and Talalay, 1984). This method is widely used in drug combinations for cancer, where the goal is selective cytotoxicity. Opposingly, the context for AD is cytoprotection, which may be a reason for the sparse use of this method in the field of AD. The novelty of the present study lies on the fact that it adapted the Chou-Talalay method to screen nutraceutical combinations that inhibited Aβ_1–42–induced toxicity. The idea of prevention was explored in the current in vitro work by pre-treating with the compounds and the insult of Aβ_1–42 introduced secondarily. This implicates that the current results indicative of AD prevention rather than treatment. As mentioned earlier, combination index (CI) is a quantitative assessment of drug combinations which uses dose-effect data of single compounds and the combinations and statistically derived doses of single compounds that give the same effect as that of the combinations to calculate CI. Combination index equals 1 for additive effect, CI is less than 1 (CI < 1) for synergistic effects and higher than 1 (CI > 1) for antagonistic effects (Chou and Talalay, 1984). The predicted three-compound combination was shown to be synergistic based on its CI value calculated by CompuSyn v.1.0. Dose reduction is an important aspect in drug combinations. The validation studies on relative ATP levels confirmed that the combination itself significantly inhibited Aβ_1–42–induced toxicity compared to its constituents; DHA, LUT, and UA in equimolar doses (5 μM each) (Figure 6). The significance of the resulted combination is that it includes three neuroprotective compounds in relatively low concentrations (5 μM each) so that their multi-modes of actions are elicited without causing toxicity issues as observed for higher concentrations. Furthermore, dissolving these compounds in a single solvent (DMSO) was an added advantage that they could be combined within a single matrix without causing any solvent-based incompatibilities that may have resulted in cytotoxicity.

Polyphenolic conjugation is a novel strategy used to enhance the efficiency and biological activity of polyphenolic compounds (Cirillo et al., 2016). Similarly, fatty acid conjugation is reported to increase potency of therapeutic agents (Prakash et al., 2019). This technique is used in cancer drug therapy that anticancer drugs are conjugated with lipids such as DHA (lipid-drug conjugate) for targeted tumor therapy (Wang et al., 2012; Li et al., 2014; Irby et al., 2017). In fact, formation of fatty acid esters of polyphenols such as quercetin-3-O-glucoside have been shown beneficial for cell viability and survival of both human lung fibroblasts and human primary hepatocytes against H₂O₂-induced cytotoxicity (Warnakulasuriya et al., 2016). As DHA is a constitutive fatty acid in cell membranes, it may facilitate the passage of the conjugated polyphenols into cells increasing their bioavailability. In a similar manner, DHA in the three-compound combination may potentially conjugate with LUT and UA, leading to their increased bioavailability and thereby resulting in increased cell viability. All possible structures of DHA ester derivatives of LUT and UA and polyphenolic associations that may form during the cellular pre-treatment of the three-compound combination are shown in the Figure 7.

FIGURE 7

Figure 7. Predicted chemical conjugations for the three-compound combination, D₅L₅U₅. For the DHA-LUT-UA combination, four chemical conjugations are predicted as (i) DHA-LUT (ii) DHA-UA (iii) LUT-UA (iv) DHA-UA-LUT.

Meanwhile, mechanisms of inhibiting Aβ_1–42-induced toxicity by D₅L₅U₅ are yet unknown. However, modified mitochondrial dehydrogenase activity which is indicated by the MTS results (Figure 4A) as well as the relatively higher ATP levels for D₅L₅U₅ (Figure 6), are suggestive of profound beneficial effects on mitochondria. It can be hypothesized, further, that the exact mechanisms are similar to that of individual drugs in a combination (Chou, 2010). Considering the components of D₅L₅U₅, DHA is thought to exert protection to neuronal mitochondria. Multiple lines of evidence show that dietary n-3 PUFA, specifically DHA gives beneficial effects on mitochondrial membrane organization (Fan et al., 2003; Khairallah et al., 2012) and mitochondrial function (Mayurasakorn et al., 2016). DHA has shown to reduce ROS production in vitro and Ca²⁺-induced mitochondrial membrane permeabilization in neonatal C57BL/6J mice following hypoxia-ischemia-brain injury (Mayurasakorn et al., 2016). Manipulation of membrane phospholipids in the mitochondrial membrane such as increasing cardiolipin content is proposed to be the mechanism of many of the beneficiary effects of DHA (Pepe et al., 1999). Mitochondria determine cell survival through the opening of the mPTP, which occurs under conditions of cell stress, causing mitochondrial depolarization and triggering of cell death as well as mitophagy. It has recently been found that dietary supplementation with a mixture of DHA and EPA (70:30 ratio) increased DHA and EPA in cardiac mitochondrial phospholipids and the tolerance of isolated mitochondria to Ca²⁺-induced mPTP opening (O’Shea et al., 2009). Moreover, it has been shown that supplementation with DHA per se also delayed Ca²⁺-induced mPTP opening (Khairallah et al., 2010). Luteolin, the second component of D₅L₅U₅, is also widely appreciated in the literature for its mitoprotective activities. It has been shown to ameliorate mitochondrial damage in isoproterenol-induced myocardial infarction by maintaining lipid peroxidation metabolism due to its free radical scavenging, mitochondrial lipids, antioxidants and mitochondrial enzymes (Murugesan and Manju, 2013). It is thought to associate with up-regulation of autophagy (Hu et al., 2016; Cao et al., 2017) and improvement of mitochondrial biogenesis through inhibition of macrophage stimulating 1 protein (Hu et al., 2016). Interestingly, a growing body of evidence suggests that UA restores mitochondrial dysfunction by inducing mitophagy (Ryu et al., 2016; Andreux et al., 2019; Lin et al., 2020). Overall, further in vitro studies are warranted to identify the mechanisms of action of the synergistic three-compound nutraceutical combination for may be a steppingstone toward developing an advanced functional food for the prevention or co-treatment of AD.

Conclusion

The present study identified a synergistic three-compound combination, D₅L₅U₅ that inhibits Aβ_1–42-induced toxicity in vitro. This compound combination consisted of nutraceuticals: DHA, luteolin and Urolithin A each in 5 μM concentration, and Chou-Talalay method of drug combinations was used to derive it. Further in vitro and in vivo investigations are required to determine the mechanisms of action and validate this synergistic three-compound combination in the journey toward identifying an advanced functional food for the prevention or co-treatment of AD.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s.

Author Contributions

RM and DJ designed the study. DJ carried out all experiments and wrote the manuscript. EH closely supervised the experiments. RM, EH, GV, MG, and WF reviewed the manuscript intensively. EH, RM, MG, and WF edited the manuscript. All authors have read and agreed to the final version of this manuscript.

Funding

Edith Cowan University funding was provided to RM.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

Edith Cowan University is acknowledged for the award of Edith Cowan University postgraduate research scholarship (ECUPRS) for DJ.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnagi.2022.780602/full#supplementary-material

Supplementary Figure 1 | Relative ATP levels for the combination 1 (D₅U₁₀) and its components. ATP levels for the combination 1 (D₅U₁₀) and its components were determined using the CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle control, ^***P < 0.001 vs. Aβ_1–42-treated control, ^#P < 0.05 vs. DHA 5 μM and UA 5 μM.

Supplementary Figure 2 | Relative ATP levels for the combination 1 (D₁₀U₁₀) and its components. ATP levels for the combination 3 (D₁₀U₁₀) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle-treated control, ^***P < 0.001 vs. Aβ_1–42-treated control, DHA 5 μM and UA 5 μM.

Supplementary Figure 3 | Relative ATP levels for the combination 1 (D₁₀U₅) and its components. ATP levels for the combination 3 (D₁₀U₅) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle control, ^***P < 0.001 vs. Aβ_1–42-treated control, DHA 10 μM and UA 5 μM.

Supplementary Figure 4 | Relative ATP levels for the combination 1 (D₂₀L₅) and its components. ATP levels for the combination 4 (D₂₀L₅) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle-treated control, ^***P < 0.001 vs. Aβ_1–42-treated control, DHA 10 μM.

Supplementary Figure 5 | Relative ATP levels for the combination 1 (D₁₀L₂₀) and its components. ATP levels for the combination 6 (D₁₀U₅) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle-treated control, ^***P < 0.001 vs. Aβ_1–42-treated control, DHA 10 μM and UA 5 μM.

Supplementary Figure 6 | Relative ATP levels for the combination 1 (D₅L₁₀) and its components. ATP levels for the combination 6 (D₅L₁₀) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle control, ^***P < 0.001 vs. Aβ_1–42-treated control, DHA 5 μM.

Supplementary Figure 7 | Relative ATP levels for the combination 7 (D₁₀L₁₀) and its components. ATP levels for the combination 7 (D₁₀L₁₀) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle control, ^***P < 0.001 vs Aβ_1–42-treated control, DHA 10 μM.

Supplementary Figure 8 | Relative ATP levels for the combination 9 (D₂₀L₁₀) and its components. ATP levels for the combination 9 (D₂₀L₁₀) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle control, ^***P < 0.001 vs. Aβ_1–42-treated control, DHA 20 μM.

Supplementary Figure 9 | Relative ATP levels for the combination 10 (D₁₀L₅) and its components. ATP levels for the combination 10 (D₁₀L₅) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs vehicle control, ^***P < 0.001 vs. Aβ_1–42-treated control, DHA 10 μM.

Supplementary Figure 10 | Relative ATP levels for the combination 12 (L₂₀U₅) and its components. ATP levels for the combination 12 (L₂₀U₅) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle control, ^***P < 0.001 vs. Aβ_1–42-treated control, LUT 20 μM and UA 5 μM.

Supplementary Figure 11 | Relative ATP levels for the combination 13 (L₁₀U₅) and its components. ATP levels for the combination 13 (L₁₀U₅) and its constituents were determined using CellTiter Glo assay. Data are expressed as mean ± SD from four (N = 4) independent experiments. Differences are significant at ^aP < 0.001 vs. vehicle control, ^***P < 0.001 vs. Aβ_1–42-treated control, LUT 10 μM and UA 5 μM.

References

Anderson, R. M., Hadjichrysanthou, C., Evans, S., and Wong, M. M. (2017). Why do so many clinical trials of therapies for Alzheimer’s disease fail? Lancet 390, 2327–2329.

Google Scholar

Andres, D., Keyser, B. M., Petrali, J., Benton, B., Hubbard, K. S., Mcnutt, P. M., et al. (2013). Morphological and functional differentiation in BE(2)-M17 human neuroblastoma cells by treatment with Trans-retinoic acid. BMC Neurosci. 14:49. doi: 10.1186/1471-2202-14-49

PubMed Abstract | CrossRef Full Text | Google Scholar

Andreux, P. A., Blanco-Bose, W., Ryu, D., Burdet, F., Ibberson, M., Aebischer, P., et al. (2019). The mitophagy activator urolithin A is safe and induces a molecular signature of improved mitochondrial and cellular health in humans. Nat. Metab. 1, 595–603. doi: 10.1038/s42255-019-0073-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Banik, A., Brown, R. E., Bamburg, J., Lahiri, D. K., Khurana, D., Friedland, R. P., et al. (2015). Translation of pre-clinical studies into successful clinical trials for Alzheimer’s disease: what are the roadblocks and how can they be overcome? J. Alzheimer’s Dis. 47, 815–843. doi: 10.3233/JAD-150136

PubMed Abstract | CrossRef Full Text | Google Scholar

Cao, Z., Zhang, H., Cai, X., Fang, W., Chai, D., Wen, Y., et al. (2017). Luteolin promotes cell apoptosis by inducing autophagy in hepatocellular carcinoma. Cell Physiol. Biochem. 43, 1803–1812. doi: 10.1159/000484066

PubMed Abstract | CrossRef Full Text | Google Scholar

Cerda, B., Llorach, R., Ceron, J. J., Espin, J. C., and Tomas-Barberan, F. A. (2003). Evaluation of the bioavailability and metabolism in the rat of punicalagin, an antioxidant polyphenol from pomegranate juice. Eur. J. Nutr. 42, 18–28. doi: 10.1007/s00394-003-0396-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Chaudhari, S. M., Patel, K. Y., and Badole, S. L. (2014). “Chapter 106 - Punica granatum (Pomegranate Fruit): in Cancer Treatment,” in Polyphenols in Human Health and Disease, eds R. R. Watson, V. R. Preedy, and S. Zibadi (San Diego, CA: Academic Press), 1393–1400.

Google Scholar

Choi, S. M., Kim, B. C., Cho, Y. H., Choi, K. H., Chang, J., Park, M. S., et al. (2014). Effects of flavonoid compounds on beta-amyloid-peptide-induced neuronal death in cultured mouse cortical neurons. Chonnam. Med. J. 50, 45–51. doi: 10.4068/cmj.2014.50.2.45

PubMed Abstract | CrossRef Full Text | Google Scholar

Chou, T. C. (2006). Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies. Pharmacol. Rev. 58, 621–681.

Google Scholar

Chou, T. C. (2010). Drug combination studies and their synergy quantification using the Chou-Talalay method. Cancer Res. 70, 440–446.

Google Scholar

Chou, T. C., and Talalay, P. (1984). Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors. Adv. Enzyme Regul. 22, 27–55.

Google Scholar

Chumakov, I., Nabirotchkin, S., Cholet, N., Milet, A., Boucard, A., Toulorge, D., et al. (2015). Combining two repurposed drugs as a promising approach for Alzheimer’s disease therapy. Sci. Rep. 5:7608.

Google Scholar

Cirillo, G., Curcio, M., Vittorio, O., Iemma, F., Restuccia, D., Spizzirri, U. G., et al. (2016). Polyphenol conjugates and human health: a perspective review. Crit. Rev. Food Sci. Nutr. 56, 326–337. doi: 10.1080/10408398.2012.752342

PubMed Abstract | CrossRef Full Text | Google Scholar

Cremonini, A. L., Caffa, I., Cea, M., Nencioni, A., Odetti, P., and Monacelli, F. (2019). Nutrients in the prevention of Alzheimer’s disease. Oxid. Med. Cell. Longev. 2019:9874159.

Google Scholar

Cummings, J., Lee, G., Ritter, A., Sabbagh, M., and Zhong, K. (2020). Alzheimer’s disease drug development pipeline: 2020. Alzheimers Dement. Transl. Res. Clin. Intervent. 6:e12050.

Google Scholar

Cummings, J. L., Schneider, E., Tariot, P. N., and Graham, S. M. (2006). Behavioral effects of memantine in Alzheimer disease patients receiving donepezil treatment. Neurology 67:57.

Google Scholar

Cummings, J. L., Tong, G., and Ballard, C. (2019). Treatment combinations for Alzheimer’s disease: current and future pharmacotherapy options. J. Alzheimers Dis. 67, 779–794.

Google Scholar

Dantoine, T., Auriacombe, S., Sarazin, M., Becker, H., Pere, J.-J., and Bourdeix, I. (2006). Rivastigmine monotherapy and combination therapy with memantine in patients with moderately severe Alzheimer’s disease who failed to benefit from previous cholinesterase inhibitor treatment. Int. J. Clin. Pract. 60, 110–118. doi: 10.1111/j.1368-5031.2005.00769.x

PubMed Abstract | CrossRef Full Text | Google Scholar

De Kok, T. M., Van Breda, S. G., and Manson, M. M. (2008). Mechanisms of combined action of different chemopreventive dietary compounds: a review. Eur. J. Nutr. 47(Suppl. 2), 51–59.

Google Scholar

Efferth, T., and Koch, E. (2011). Complex interactions between phytochemicals. The multi-target therapeutic concept of phytotherapy. Curr. Drug Targets 12, 122–132. doi: 10.2174/138945011793591626

PubMed Abstract | CrossRef Full Text | Google Scholar

Espargaró, A., Ginex, T., Vadell, M. D. M., Busquets, M. A., Estelrich, J., Muñoz-Torrero, D., et al. (2017). Combined in vitro cell-based/in silico screening of naturally occurring flavonoids and phenolic compounds as potential anti-alzheimer drugs. J. Nat. Prod. 80, 278–289. doi: 10.1021/acs.jnatprod.6b00643

PubMed Abstract | CrossRef Full Text | Google Scholar

Espin, J. C., Larrosa, M., Garcia-Conesa, M. T., and Tomas-Barberan, F. (2013). Biological significance of urolithins, the gut microbial ellagic Acid-derived metabolites: the evidence so far. Evid. Based Complement. Alternat. Med. 2013:270418. doi: 10.1155/2013/270418

PubMed Abstract | CrossRef Full Text | Google Scholar

Fan, Y. Y., Mcmurray, D. N., Ly, L. H., and Chapkin, R. S. (2003). Dietary (n-3) polyunsaturated fatty acids remodel mouse T-cell lipid rafts. J. Nutr. 133, 1913–1920. doi: 10.1093/jn/133.6.1913

PubMed Abstract | CrossRef Full Text | Google Scholar

Galvin, J. E. (2017). Prevention of Alzheimer’s disease: lessons learned and applied. J. Am. Geriatr. Soc. 65, 2128–2133.

Google Scholar

Gong, Z., Huang, J., Xu, B., Ou, Z., Zhang, L., Lin, X., et al. (2019). Urolithin A attenuates memory impairment and neuroinflammation in APP/PS1 mice. J. Neuroinflam. 16:62. doi: 10.1186/s12974-019-1450-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Grimm, M. O., Kuchenbecker, J., Grosgen, S., Burg, V. K., Hundsdorfer, B., Rothhaar, T. L., et al. (2011). Docosahexaenoic acid reduces amyloid beta production via multiple pleiotropic mechanisms. J. Biol. Chem. 286, 14028–14039. doi: 10.1074/jbc.M110.182329

PubMed Abstract | CrossRef Full Text | Google Scholar

Grodzicki, W., and Dziendzikowska, K. (2020). The role of selected bioactive compounds in the prevention of alzheimer’s disease. Antioxidants 9:229.

Google Scholar

Hartman, R. E., Shah, A., Fagan, A. M., Schwetye, K. E., Parsadanian, M., Schulman, R. N., et al. (2006). Pomegranate juice decreases amyloid load and improves behavior in a mouse model of Alzheimer’s disease. Neurobiol. Dis. 24, 506–515. doi: 10.1016/j.nbd.2006.08.006

PubMed Abstract | CrossRef Full Text | Google Scholar

Hashimoto, M., Shahdat, H. M., Katakura, M., Tanabe, Y., Gamoh, S., Miwa, K., et al. (2009). Effects of docosahexaenoic acid on in vitro amyloid beta peptide 25-35 fibrillation. Biochim. Biophys. Acta 1791, 289–296.

Google Scholar

Hossain, S., Hashimoto, M., Katakura, M., Miwa, K., Shimada, T., and Shido, O. (2009). Mechanism of docosahexaenoic acid-induced inhibition of in vitro Aβ1–42 fibrillation and Aβ1–42-induced toxicity in SH-S5Y5 cells. J. Neurochem. 111, 568–579.

Google Scholar

Hu, J., Man, W., Shen, M., Zhang, M., Lin, J., Wang, T., et al. (2016). Luteolin alleviates post-infarction cardiac dysfunction by up-regulating autophagy through Mst1 inhibition. J. Cell Mol. Med. 20, 147–156. doi: 10.1111/jcmm.12714

PubMed Abstract | CrossRef Full Text | Google Scholar

Irby, D., Du, C., and Li, F. (2017). Lipid-drug conjugate for enhancing drug delivery. Mol. Pharm. 14, 1325–1338.

Google Scholar

Jayatunga, D. P. W., Hone, E., Fernando, W. M. A. D. B., Garg, M. L., Verdile, G., and Martins, R. N. (2021). Mitoprotective effects of a Synergistic Nutraceutical Combination: basis for a prevention strategy against Alzheimer’s Disease. Front. Aging Neurosci. (in press).

Google Scholar

Kabir, M. T., Uddin, M. S., Mamun, A. A., Jeandet, P., Aleya, L., Mansouri, R. A., et al. (2020). Combination drug therapy for the management of Alzheimer’s disease. Int J Mol Sci 21:3272.

Google Scholar

Khairallah, R. J., Kim, J., O’Shea, K. M., O’connell, K. A., Brown, B. H., Galvao, T., et al. (2012). Improved mitochondrial function with diet-induced increase in either docosahexaenoic acid or arachidonic acid in membrane phospholipids. PLoS One 7:e34402. doi: 10.1371/journal.pone.0034402

PubMed Abstract | CrossRef Full Text | Google Scholar

Khairallah, R. J., Sparagna, G. C., Khanna, N., O’Shea, K. M., Hecker, P. A., Kristian, T., et al. (2010). Dietary supplementation with docosahexaenoic acid, but not eicosapentaenoic acid, dramatically alters cardiac mitochondrial phospholipid fatty acid composition and prevents permeability transition. Biochim. Biophys. Acta 1797, 1555–1562.

Google Scholar

Lange, K. W., Guo, J., Kanaya, S., Lange, K. M., Nakamura, Y., and Li, S. (2019). Medical foods in Alzheimer’s disease. Food Sci. Hum. Wellness 8, 1–7.

Google Scholar

Li, S., Qin, J., Tian, C., Cao, J., Fida, G., Wang, Z., et al. (2014). The targeting mechanism of DHA ligand and its conjugate with Gemcitabine for the enhanced tumor therapy. Oncotarget 5, 3622–3635. doi: 10.18632/oncotarget.1969

PubMed Abstract | CrossRef Full Text | Google Scholar

Lim, G. P., Calon, F., Morihara, T., Yang, F., Teter, B., Ubeda, O., et al. (2005). A diet enriched with the omega-3 fatty acid docosahexaenoic acid reduces amyloid burden in an aged Alzheimer mouse model. J. Neurosci. 25, 3032–3040. doi: 10.1523/JNEUROSCI.4225-04.2005

PubMed Abstract | CrossRef Full Text | Google Scholar

Lin, J., Zhuge, J., Zheng, X., Wu, Y., Zhang, Z., Xu, T., et al. (2020). Urolithin A-induced mitophagy suppresses apoptosis and attenuates intervertebral disc degeneration via the AMPK signaling pathway. Free Radic. Biol. Med. 150, 109–119. doi: 10.1016/j.freeradbiomed.2020.02.024

PubMed Abstract | CrossRef Full Text | Google Scholar

Liu, H., Zeng, Z., Wang, S., Li, T., Mastriani, E., Li, Q.-H., et al. (2017). Main components of pomegranate, ellagic acid and luteolin, inhibit metastasis of ovarian cancer by down-regulating MMP2 and MMP9. Cancer Biol. Ther. 18, 990–999. doi: 10.1080/15384047.2017.1394542

PubMed Abstract | CrossRef Full Text | Google Scholar

Mayurasakorn, K., Niatsetskaya, Z. V., Sosunov, S. A., Williams, J. J., Zirpoli, H., Vlasakov, I., et al. (2016). DHA but not EPA emulsions preserve neurological and mitochondrial function after brain hypoxia-ischemia in neonatal mice. PLoS One 11:e0160870. doi: 10.1371/journal.pone.0160870

PubMed Abstract | CrossRef Full Text | Google Scholar

Mehta, D., Jackson, R., Paul, G., Shi, J., and Sabbagh, M. (2017). Why do trials for Alzheimer’s disease drugs keep failing? A discontinued drug perspective for 2010-2015. Expert Opin. Investig. Drugs 26, 735–739. doi: 10.1080/13543784.2017.1323868

PubMed Abstract | CrossRef Full Text | Google Scholar

Moreno, S., Perno, C., Mallon, P., Behrens, G., Corbeau, P., Routy, J.-P., et al. (2019). Two-drug vs. three-drug combinations for HIV-1: do we have enough data to make the switch? HIV Med. 20, 2–12.

Google Scholar

Murphy, M. P., and Levine, H. III (2010). Alzheimer’s disease and the amyloid-beta peptide. J. Alzheimers Dis. 19, 311–323.

Google Scholar

Murugesan, M., and Manju, V. (2013). Luteolin promotes mitochondrial protection during acute and chronic periods of isoproterenol induced myocardial infarction in rats. Egypt. Heart J. 65, 319–327.

Google Scholar

O’Shea, K. M., Khairallah, R. J., Sparagna, G. C., Xu, W., Hecker, P. A., Robillard-Frayne, I., et al. (2009). Dietary omega-3 fatty acids alter cardiac mitochondrial phospholipid composition and delay Ca2+-induced permeability transition. J. Mol. Cell Cardiol. 47, 819–827.

Google Scholar

Panza, F., Lozupone, M., Solfrizzi, V., Custodero, C., Valiani, V., D’introno, A., et al. (2018). “Chapter 9 - Contribution of Mediterranean Diet in the Prevention of Alzheimer’s Disease,” in Role of the Mediterranean Diet in the Brain and Neurodegenerative Diseases, eds T. Farooqui and A. A. Farooqui (Cambridge, MA: Academic Press), 139–155.

Google Scholar

Patti, A. M., Toth, P. P., Giglio, R. V., Banach, M., Noto, M., Nikolic, D., et al. (2017). Nutraceuticals as an important part of combination therapy in dyslipidaemia. Curr. Pharm. Des. 23, 2496–2503.

Google Scholar

Peltomaa, E., Johnson, M. D., and Taipale, S. J. (2017). Marine cryptophytes are great sources of EPA and DHA. Mar. Drugs 16:3. doi: 10.3390/md16010003

PubMed Abstract | CrossRef Full Text | Google Scholar

Peng, Y., Tao, H., Wang, S., Xiao, J., Wang, Y., and Su, H. (2021). Dietary intervention with edible medicinal plants and derived products for prevention of Alzheimer’s disease: a compendium of time-tested strategy. J. Funct. Foods 81:104463.

Google Scholar

Pepe, S., Tsuchiya, N., Lakatta, E. G., and Hansford, R. G. (1999). PUFA and aging modulate cardiac mitochondrial membrane lipid composition and Ca2+ activation of PDH. Am. J. Physiol. 276, H149–H158. doi: 10.1152/ajpheart.1999.276.1.H149

PubMed Abstract | CrossRef Full Text | Google Scholar

Prakash, T. P., Mullick, A. E., Lee, R. G., Yu, J., Yeh, S. T., Low, A., et al. (2019). Fatty acid conjugation enhances potency of antisense oligonucleotides in muscle. Nucleic Acids Res. 47, 6029–6044.

Google Scholar

Rabinovici, G. D. (2021). Controversy and progress in Alzheimer’s disease — FDA approval of aducanumab. N. Engl. J. Med. 385, 771–774.

Google Scholar

Riepe, M. W., Adler, G., Ibach, B., Weinkauf, B., Tracik, F., and Gunay, I. (2007). Domain-specific improvement of cognition on memantine in patients with Alzheimer’s disease treated with rivastigmine. Dement. Geriatr. Cogn. Disord. 23, 301–306.

Google Scholar

Ryu, D., Mouchiroud, L., Andreux, P. A., Katsyuba, E., Moullan, N., Nicolet-Dit-Félix, A. A., et al. (2016). Urolithin A induces mitophagy and prolongs lifespan in C. elegans and increases muscle function in rodents. Nat. Med. 22, 879–888. doi: 10.1038/nm.4132

PubMed Abstract | CrossRef Full Text | Google Scholar

Santana-Gálvez, J., Cisneros-Zevallos, L., and Jacobo-Velázquez, D. A. (2019). A practical guide for designing effective nutraceutical combinations in the form of foods, beverages, and dietary supplements against chronic degenerative diseases. Trends Food Sci. Technol. 88, 179–193.

Google Scholar

Scarmeas, N., Stern, Y., Tang, M.-X., Mayeux, R., and Luchsinger, J. A. (2006). Mediterranean diet and risk for Alzheimer’s disease. Ann. Neurol. 59, 912–921.

Google Scholar

Seeram, N. P., Henning, S. M., Zhang, Y., Suchard, M., Li, Z., and Heber, D. (2006). Pomegranate Juice Ellagitannin Metabolites Are Present in Human Plasma and Some Persist in Urine for Up to 48 Hours. J. Nutr. 136, 2481–2485. doi: 10.1093/jn/136.10.2481

PubMed Abstract | CrossRef Full Text | Google Scholar

Selkoe, D. J. (2001). Alzheimer’s disease: genes, proteins, and therapy. Physiol. Rev. 81, 741–766.

Google Scholar

Sharman, M. J., Gyengesi, E., Liang, H., Chatterjee, P., Karl, T., Li, Q. X., et al. (2019). Assessment of diets containing curcumin, epigallocatechin-3-gallate, docosahexaenoic acid and alpha-lipoic acid on amyloid load and inflammation in a male transgenic mouse model of Alzheimer’s disease: are combinations more effective? Neurobiol. Dis. 124, 505–519. doi: 10.1016/j.nbd.2018.11.026

PubMed Abstract | CrossRef Full Text | Google Scholar

Simoni, E., Daniele, S., Bottegoni, G., Pizzirani, D., Trincavelli, M. L., Goldoni, L., et al. (2012). Combining galantamine and memantine in multitargeted, new chemical entities potentially useful in Alzheimer’s disease. J. Med. Chem. 55, 9708–9721. doi: 10.1021/jm3009458

PubMed Abstract | CrossRef Full Text | Google Scholar

Sreekumar, S., Sithul, H., Muraleedharan, P., Azeez, J. M., and Sreeharshan, S. (2014). Pomegranate fruit as a rich source of biologically active compounds. Biomed. Res. Int. 2014:686921.

Google Scholar

Stine, W. B., Jungbauer, L., Yu, C., and Ladu, M. J. (2011). Preparing synthetic Abeta in different aggregation states. Methods Mol. Biol. 670, 13–32.

Google Scholar

Sun, W., Sanderson, P. E., and Zheng, W. (2016). Drug combination therapy increases successful drug repositioning. Drug Discov. Today 21, 1189–1195.

Google Scholar

Tariot, P. N., Farlow, M. R., Grossberg, G. T., Graham, S. M., Mcdonald, S., Gergel, I., et al. (2004). Memantine treatment in patients with moderate to severe Alzheimer disease already receiving DonepezilA randomized controlled trial. JAMA 291, 317–324.

Google Scholar

Thaipisuttikul, P., and Galvin, J. E. (2012). Use of medical foods and nutritional approaches in the treatment of Alzheimer’s disease. Clin. Pract. 9, 199–209.

Google Scholar

Thomas, E., and Egon, K. (2011). Complex interactions between phytochemicals. The multi-target therapeutic concept of phytotherapy. Curr. Drug Targets 12, 122–132.

Google Scholar

Tiwari, M. K., and Kepp, K. P. (2016). β-Amyloid pathogenesis: chemical properties versus cellular levels. Alzheimers Dement. 12, 184–194. doi: 10.1016/j.jalz.2015.06.1895

PubMed Abstract | CrossRef Full Text | Google Scholar

Tocher, D. R. (2015). Omega-3 long-chain polyunsaturated fatty acids and aquaculture in perspective. Aquaculture 449, 94–107.

Google Scholar

Van Elswijk, D. A., Schobel, U. P., Lansky, E. P., Irth, H., and Van Der Greef, J. (2004). Rapid dereplication of estrogenic compounds in pomegranate (Punica granatum) using on-line biochemical detection coupled to mass spectrometry. Phytochemistry 65, 233–241. doi: 10.1016/j.phytochem.2003.07.001

PubMed Abstract | CrossRef Full Text | Google Scholar

Van Norman, G. A. (2020). Limitations of animal studies for predicting toxicity in clinical trials: part 2: potential alternatives to the use of animals in preclinical trials. JACC Basic Transl. Sci. 5, 387–397. doi: 10.1016/j.jacbts.2020.03.010

PubMed Abstract | CrossRef Full Text | Google Scholar

Wang, J., Luo, T., Li, S., and Zhao, J. (2012). The powerful applications of polyunsaturated fatty acids in improving the therapeutic efficacy of anticancer drugs. Expert Opin. Drug Deliv. 9, 1–7. doi: 10.1517/17425247.2011.618183

PubMed Abstract | CrossRef Full Text | Google Scholar

Warnakulasuriya, S. N., and Ziaullah Rupasinghe, H. P. V. (2016). Long chain fatty acid esters of Quercetin-3-O-glucoside attenuate H₂O₂-induced acute cytotoxicity in human lung fibroblasts and primary hepatocytes. Molecules 21, 452–452. doi: 10.3390/molecules21040452

PubMed Abstract | CrossRef Full Text | Google Scholar

Xia, F., Wang, C., Jin, Y., Liu, Q., Meng, Q., Liu, K., et al. (2014). Luteolin protects HUVECs from TNF-alpha-induced oxidative stress and inflammation via its effects on the Nox4/ROS-NF-kappaB and MAPK pathways. J. Atheroscler. Thromb. 21, 768–783. doi: 10.5551/jat.23697

PubMed Abstract | CrossRef Full Text | Google Scholar

Yuan, T., Ma, H., Liu, W., Niesen, D. B., Shah, N., Crews, R., et al. (2016). Pomegranate’s neuroprotective effects against Alzheimer’s disease are mediated by urolithins, its ellagitannin-gut microbial derived metabolites. ACS Chem. Neurosci. 7, 26–33.

Google Scholar

Zheng, N., Yuan, P., Li, C., Wu, J., and Huang, J. (2015). Luteolin reduces BACE1 expression through NF-kappaB and through estrogen receptor mediated pathways in HEK293 and SH-SY5Y Cells. J. Alzheimers Dis. 45, 659–671. doi: 10.3233/JAD-142517

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhou, F., Chen, S., Xiong, J., Li, Y., and Qu, L. (2012). Luteolin reduces zinc-induced tau phosphorylation at Ser262/356 in an ROS-dependent manner in SH-SY5Y cells. Biol. Trace Elem. Res. 149, 273–279. doi: 10.1007/s12011-012-9411-z

PubMed Abstract | CrossRef Full Text | Google Scholar