**E**ff**ects of Grape Polyphenols on the Life Span and Neuroinflammatory Alterations Related to Neurodegenerative Parkinson Disease-Like Disturbances in Mice**

**Maria A. Tikhonova 1,2, Nadezhda G. Tikhonova 3,\*, Michael V. Tenditnik 2, Marina V. Ovsyukova 2, Anna A. Akopyan 2, Nina I. Dubrovina 2, Tamara G. Amstislavskaya <sup>2</sup> and Elena K. Khlestkina 1,3**


Academic Editor: H.P. Vasantha Rupasinghe Received: 24 September 2020; Accepted: 9 November 2020; Published: 16 November 2020

**Abstract:** Functional nutrition is a valuable supplementation to dietary therapy. Functional foods are enriched with biologically active substances. Plant polyphenols attract particular attention due to multiple beneficial properties attributed to their high antioxidant and other biological activities. We assessed the effect of grape polyphenols on the life span of C57BL/6 mice and on behavioral and neuroinflammatory alterations in a transgenic mouse model of Parkinson disease (PD) with overexpression of the A53T-mutant human α-synuclein. C57BL/6 mice were given a dietary supplement containing grape polyphenol concentrate (GPC—1.5 mL/kg/day) with drinking water from the age of 6–8 weeks for life. Transgenic PD mice received GPC beginning at the age of 10 weeks for four months. GPC significantly influenced the cumulative proportion of surviving and substantially augmented the average life span in mice. In the transgenic PD model, the grape polyphenol (GP) diet enhanced memory reconsolidation and diminished memory extinction in a passive avoidance test. Behavioral effects of GP treatment were accompanied by a decrease in α-synuclein accumulation in the frontal cortex and a reduction in the expression of neuroinflammatory markers (IBA1 and CD54) in the frontal cortex and hippocampus. Thus, a GP-rich diet is recommended as promising functional nutrition for aging people and patients with neurodegenerative disorders.

**Keywords:** flavonoids; cognition; passive avoidance test; memory extinction; mice; microglia; neuroprotection

### **1. Introduction**

There is growing evidence that diets rich in polyphenols decrease the risk of chronic diseases such as obesity, diabetes, heart disease, and cancer [1–5]. Polyphenols are the most abundant group of biologically active molecules and natural antioxidants that can protect human cells from oxidative damage thereby reducing the risk of developing various degenerative diseases associated with oxidative stress. The main sources of polyphenols are fruits, tea, coffee, cacao, and grapes. These compounds are also found in vegetables and seeds of different crops, but in lower concentrations [6,7]. In plants,

polyphenols are secondary metabolites participating in plant protection from a wide range of biotic and abiotic stress factors [8,9].

Even with a standard diet, we consume about 1 g of polyphenols daily, which is 10 and 100 times higher than the daily doses of vitamins C and E (as well as carotenoids), respectively [10]. In addition to antioxidant activity, polyphenols depending on their chemical structure, manifest a wide range of biological activities, such as anti-inflammatory, capillary-strengthening, hepatoprotective, diuretic, antiallergic, antimicrobial and antitumor properties [5,11–13].

There is a special interest in reusing winemaking waste, such as grape seed, fruit skin or vine. These waste products are rich in polyphenols, specifically, catechins, quercetin, anthocyanins, proantocyanidins, phenolic acids, and resveratrol [14,15] having most of the activities described above [5,12,13], so they may be used to produce valuable extracts. Furthermore, the photoprotective effect of polyphenolic compounds extracted from red grapes was observed during in vitro human cell culture studies [7]. Red grapes effectively inhibit UV-A-induced synthesis of type III collagen both at the RNA and protein levels. This confirms the potential of grape polyphenols in slowing down the skin photoaging [7]. In addition, polyphenols can overcome the blood–brain barrier and produce a neuroprotective effect on the central nervous system [16,17]. Hence, the application of grape-derived polyphenols as an adjunctive treatment paradigm to prevent neuropathologies including such neurodegenerative disorders as Alzheimer and Parkinson diseases is widely discussed [18]. Parkinson disease (PD) is the second most common neurodegenerative disorder, placing huge economic and social burdens on societies all over the world. The main risk factor for the development of PD is aging. Current therapies for PD are symptomatic and limited they do not cope with the disease onset or progression as they do not address multiple overlapping mechanisms involved in the PD pathogenesis. Moreover, PD patients develop drug tolerance and suffer from serious side effects of the drugs due to uninterrupted long-term treatment. Nutritional supplementation with polyphenols is regarded as a promising prophylactic treatment for neurodegenerative disorders, as it potently and simultaneously targets inflammatory and oxidative pathways [18]. It is noteworthy that a recent study by Ben Youssef et al. [19] evidenced the neuroprotective effect of grape seed and skin extract on a mouse PD model induced by 6-OHDA neurotoxin through reducing apoptosis, oxidative stress, and inflammation. Pathological aggregation and accumulation of α-synuclein in neurons and Lewy bodies appear to play a core role in the pathogenesis of PD [20]. However, the potential impact of grape polyphenols on this mechanism is scantily studied.

In the current study, we assessed the effect of grape polyphenols on the life span of C57BL/6 mice and on behavioral and neuroinflammatory alterations in a transgenic mouse model of PD with overexpression of the A53T-mutant human α-synuclein.

#### **2. Results**

#### *2.1. Diet Tolerance and the E*ff*ects on Life Expectancy and Body Weight Gain*

In mice of the C57Bl/6 strain born and reared at the conventional animal facility, grape polyphenol concentrate (*GPC*) significantly influenced the cumulative proportion of surviving (*p* < 0.01; Figure 1A) and substantially augmented the average life span (*p* < 0.01; Figure 1B).

The last mouse in the experiment was a *GPC*-treated male who died at the age of 1031 days. Moreover, in two-year-old mice the general condition of *GPC*-treated animals appeared to be better than of the controls, including the state of their fur and eyes (Figure 1C). Mice of the B6.Cg-Tg (Prnp-SNCA\*A53T)23Mkle/J strain (further mut(PD)), a genetic model of PD, and control wild-type (WT) mice that had been born and reared under SPF conditions also endured the *GPC*-supplemented diet well. No significant difference was found between the groups in body weight gain after four months of the experiment (Figure 2).

**Figure 1.** The effect of dietary supplementation with *GPC* on the cumulative proportion of surviving (**A**), average life span (**B**), and general condition (**C**) in mice of the C57Bl/6 strain. The data are presented as a Kaplan–Meier diagram (**A**) or the means ± SEMs (**B**) of the values obtained in an independent group of animals (*n* = 8–15 per group). Statistically significant differences: \*\* *p* < 0.01 vs. controls. (**C**) photographs of control and *GPC*-treated mice at the age of two years.

**Figure 2.** Effects of the overexpression of A53T-mutant α-synuclein and dietary supplementation with *GPC* for four months on body weight gain in mice.The data are expressed as the means ± SEMs of the values obtained in an independent group of animals (*n* = 5–9 per group).

#### *2.2. Behavioral E*ff*ects*

#### 2.2.1. The Open Field Test

An open field test was performed to assess general locomotion, vertical locomotor and exploratory activity, anxiety, and emotionality in mice (Table 1).

**Table 1.** Effects of *GPC* supplementation and overexpression of α-synuclein (genetic Parkinson's disease (PD) model) on the behavior of mice in the open field test.


G—genotype factor, D—diet factor. Data are presented as the Mean ± S.E.M. of the values obtained in an independent group of animals (*n* = 5–9 per group). Statistically significant differences: && *p* < 0.01 vs. a WT + GPC group.

When testing a PD model, two-way ANOVA followed by an LSD post-hoc test revealed a significant effect of the genotype on the distance travelled. Mut(PD) mice had higher horizontal locomotion than WT mice, which is quite in line with previous studies on this PD model [21–23]. The other measured parameters were not significantly affected by the genotype factor or the diet factor or their interaction.

#### 2.2.2. The Passive Avoidance Test

We recorded a significant effect of the repeated measures (learning) factor (F(1, 28) = 96.4, *p* < 0.001) on the step-through latency when evaluating contextual memory retrieval in mice (Figure 3A).

Latency to enter a dark compartment during training (before the foot shock) did not differ significantly among the experimental groups. As evidence of learning and acquisition of the conditioned passive avoidance reaction on testing day, 24 h after receiving the foot shock, mice of all groups demonstrated increased step-through latencies, often ~10-times greater than latencies on the training day. However, memory extinction was influenced not only by the repeated measures (time) factor (F (11, 297) = 14.6, *p* < 0.001)) but also by the interactions between the genotype and diet factors (F (1, 27) = 6.03, *p* < 0.05) and between the repeated measures and diet factors (F (11, 297) = 3.9, *p* < 0.001) (Figure 3B). With exposure to the context in the absence of additional shocks, the fear response gradually diminishes which is called memory extinction [24]. In the WT control, WT + GPC, and mut(PD) control groups, the values of step-through latency remained significantly increased for seven, seven, and two days, respectively, compared to the training day. A significant decrease in step-through latency was observed to start from the 6th, 8th, and 4th day of the extinction phase

compared to the test day in WT control, WT + *GPC*, and mut(PD) control group, respectively. Hence, extinction was more pronounced in the mut(PD) control group. At the same time, the values of step-through latency stayed significantly increased for ten days of the extinction phase as compared to the training day in a mut(PD) + *GPC* group. We failed to observe a substantial reduction in step-through latency in mice of the mut(PD) + *GPC* group within ten days of the extinction phase. Thus, the mut (PD) mice demonstrated *GPC* enhanced memory reconsolidation and diminished memory extinction.

**Figure 3.** Effects of the overexpression of A53T-mutant α-synuclein and dietary supplementation with *GPC* for four months on memory retrieval (**A**) and memory extinction (**B**) in mice in the passive avoidance test. The data are expressed as the means ± SEMs (**A**) or means (**B**) of the values obtained in an independent group of animals (*n* = 5–9 per group). Statistically significant differences: ˆ *p* < 0.05, ˆˆ *p* < 0.01, ˆˆˆ *p* < 0.001 compared to values of the same group on the training day; # *p* < 0.05, ## *p* < 0.01, ### *p* < 0.001 compared to values of the same group on the test day.

#### *2.3. Immunohistochemical Analysis*

First, we evaluated the accumulation of human α-synuclein in the mouse brain. We detected immunofluorescence against human α-synuclein only in the frontal cortex of seven-month-old transgenic mut(PD) mice (Figure 4B). Both the genotype (F (1, 8) = 35.2, *p* < 0.001) and diet (F (1, 8) = 7.5, *p* < 0.05) factors had a significant effect on α-synuclein accumulation in the 2nd layer of the frontal cortex (Figure 4A).

**Figure 4.** Effects of the overexpression of A53T-mutant α-synuclein and dietary supplementation with *GPC* for four months on α-synuclein accumulation (**A**,**B**) and expression of the microglial marker IBA1 (**C**,**D**) or inflammatory marker CD54 (**E**,**F**) in the frontal cortex of mice. (**A**,**C**,**E**): quantitative results. The data are expressed as the means ± SEMs of the values obtained in an independent group of animals (*n* = 3 per group). Statistically significant differences: \*\* *p* < 0.01, \*\*\* *p* < 0.001 vs. WT controls; \$ *p* < 0.05, \$\$ *<sup>p</sup>* <sup>&</sup>lt; 0.01 vs. mut (PD)controls. (**B**) <sup>α</sup>-synuclein immunoreactivity in the frontal cortex. (zoom: 100×; bar: 100 μm.) (**D**) IBA1 immunoreactivity in the frontal cortex. (zoom: 200×; bar; 50 μm.) (**F**) CD54 immunoreactivity in the frontal cortex. (zoom: \200×; bar: 50 μm).

Dietary supplementation with *GPC* significantly reduced the accumulation of human α-synuclein in the frontal cortex of mut(PD) mice (*p* < 0.01). Indices of neuroinflammation (microglial marker IBA1, Figure 4C; inflammatory marker CD54, Figure 4D) were also increased in the frontal cortex of transgenic mut(PD) mice, while *GPC* treatment significantly suppressed them back to the levels of WT mice. Similar effects on the expression of the inflammatory markers were recorded in the hippocampus (Figure 5; Supplementary Materials: Figure S1).

The diet factor (F (1, 8) = 23.5, *p* < 0.01) produced a significant effect on the expression of IBA1 in the CA1 hippocampal area. The parameter was markedly decreased in both WT (*p* < 0.05) and mut(PD) (*p* < 0.01) mice by *GPC* supplementation (Figure 5A). The expression of CD54 was significantly influenced by the diet factor (F(1, 8) = 5.6, *p* < 0.05) in the CA3 hippocampal area (Figure 5E) and by the genotype factor (F(1, 8) = 11.96, *p* < 0.01), diet factor (F(1, 8) = 13.1, *p* < 0.01), and interaction between the factors (F(1, 8) = 6.8, *p* < 0.05) in the dentate gyrus of the hippocampus (Figure 5F). Dietary supplementation with *GPC* significantly reduced the CD54 expression in the CA3 area (*p* < 0.05) and dentate gyrus (*p* < 0.01) in mut(PD) mice.

**Figure 5.** Effects of the overexpression of A53T-mutant α-synuclein and dietary supplementation with *GPC* for four months on the expression of the microglial marker IBA1 (**A**–**C**) or inflammatory marker CD54 (**D**–**F**) in the hippocampus (**A,D** in the CA1 area; **B**,**E** in the CA3 area; **C**,**F** in the dentate gyrus) in mice. The data are expressed as the means ± SEMs of the values obtained in an independent group of animals (*n* = 3 per group). Statistically significant differences: \* *p* < 0.05, \*\* *p* < 0.01 vs. WT controls; \$ *p* < 0.05, \$\$ *p* < 0.01 vs. mut(PD) controls.

#### **3. Discussion**
