Lifelong Exercise Mitigates Aging-Induced Clk2 Elevation and Attenuates Fatty Liver in Mice

Kim, In-Gyu; Baek, Kyung-Wan; Xiang, Ying-Ying; Won, Jong-Hwa; Kim, Ji Hyun; Kim, Ji-Seok; In-Gyu Kim; Kyung-Wan Baek; Ying-Ying Xiang; Jong-Hwa Won; Ji Hyun Kim; Ji-Seok Kim

doi:10.15857/ksep.2024.00409

Exerc Sci > Volume 33(4); 2024 > Article

Kim, Baek, Xiang, Won, Kim, and Kim: Lifelong Exercise Mitigates Aging-Induced Clk2 Elevation and Attenuates Fatty Liver in Mice

Original Article

Exerc Sci.. 2024; 33(4): 458-467.

Published online: Nov 30, 2024

DOI: https://doi.org/10.15857/ksep.2024.00409

Lifelong Exercise Mitigates Aging-Induced Clk2 Elevation and Attenuates Fatty Liver in Mice

In-Gyu Kim MS^1,^†

, Kyung-Wan Baek PhD^1,^2,^†

, Ying-Ying Xiang MS¹

, Jong-Hwa Won MS¹

, Ji Hyun Kim PhD^3,⁴

, Ji-Seok Kim PhD^1,^2,

¹Department of Physical Education, Gyeongsang National University, Jinju, Korea

²Research Institute of Pharmaceutical Sciences, Gyeongsang National University, Jinju, Korea

³Department of Food Science, Gyeongsang National University, Jinju, Korea

⁴Department of Food Science and Nutrition, Gyeongsang National University, Jinju, Korea

Corresponding author: Ji-Seok Kim Tel +82-55-772-2296 Fax +82-55-772-2299 E-mail kjs7952@gmail.com

†These authors contributed equally to this work.

*This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1A6A3A01011328, NRF-2019R1I1A3A01061144).

Received Aug 10, 2024 Revised Sep 03, 2024 Accepted Sep 04, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

PURPOSE

This study investigated how aging regulates the expression of Clk2 (Cdc2-like kinase 2) protein and genes in the liver, and how lifelong spontaneous exercise (LSE) affects this expression.

METHODS

Male C57BL/6 mice were housed under controlled conditions and divided into groups with (EXE) and without (CON) access to running wheels to investigate the effects of LSE on Clk2 expression in the liver. The mice were maintained until 99 weeks of age (Old-CON, n=7; Old-EXE, n=7), Young controls underwent the same experiment for 22 weeks and were sacrificed at the same time points as the aged mice (Young-CON, n=7; Young-EXE, n=7), and body composition was assessed using dual-energy X-ray absorptiometry. Liver tissue samples were collected 48 h after the final exercise session and Clk2 expression was analyzed. Histological evaluation of the liver was performed using hematoxylin and eosin staining, and non-alcoholic fatty liver disease (NAFLD) activity scores were calculated.

RESULTS

Aged mice that underwent LSE exhibited significantly higher bone mineral content (Old-CON vs. Old-EXE, p <.05), and lower hepatic Clk2 expression compared to sedentary aged controls (Old-CON vs. Old-EXE, p<.05). LSE also led to a reduction in the NAFLD activity score (Old-CON vs. Old-EXE, p<.05), indicating less liver fat accumulation.

CONCLUSIONS

Clk2 increases in the liver with aging. Additionally, LSE appears to contribute to the suppression of Clk2, thereby reducing hepatic lipid accumulation and the NAFLD activity score. However, further research is required to fully understand the direct relationship between Clk2, aging, and exercise.

Keywords: Liver, Aging, Exercise, Clk2

INTRODUCTION

Aging itself can lead to increased fat accumulation in the liver [1]. The decline in metabolic rate, increased insulin resistance, and the decrease in growth hormone and sex hormones associated with aging are well-known causes of hepatic fat accumulation [1]. Additionally, inflammation and oxidative stress in liver cells may increase with age, potentially causing cellular damage that leads to fat accumulation [2-4]. Despite these findings, the key molecular factors associated with age-related hepatic fat accumulation remain unidentified.

Cdc2-like kinase 2 (Clk2) is a protein kinase involved in various cellular functions, including cell cycle regulation. RNA splicing, and metabolic control [5]. Clk2 plays a crucial role in insulin signaling pathways and metabolic regulation [6]. Dysregulation of Clk2 can lead to insulin resistance, which may result in non-alcoholic fatty liver disease (NAFLD) [7]. Furthermore, Clk2 directly influences lipid metabolism within hepatocytes by modulating the splicing and expression of key genes involved in lipid synthesis, such as those encoding enzymes in the fatty acid synthesis pathway. Specifically, Clk2 can regulate the alternative splicing of sterol regulatory element-binding protein 1c (SREBP1c), a master regulator of lipogenesis, thereby affecting the overall lipid balance in the liver [8]. The activation of Clk2 can either promote or inhibit fatty acid synthesis, thereby influencing the formation of fatty liver [7,8].

Additionally, Clk2 is implicated in the regulation of cellular stress and inflammatory responses, which are critical factors in the pathogenesis of hepatic steatosis. The kinase may modulate these pathways by influencing the splicing of pre-mRNAs encoding components of the inflammatory and stress responses pathways, thereby linking metabolic and stress signaling in hepatocytes [9]. Due to these properties, Clk2 in thought to play a key role in age-related lipid accumulation in the liver.

Studies on Clk2 and aging, particularly in relation to the liver, have yielded several important findings. Aging can alter the expression and activity of Clk2 in the liver [9]. Research has shown that the expression of Clk2 is suppressed in aged mice [9]. Additionally, there have been studies suggesting that inhibiting Clk2 might reduce fatty liver disease and its associated complications [8]. These findings suggest that it is not merely the increase or decrease of Clk2 in the liver is important, but rather the appropriate level of expression and normal regulatory function. In the other words, proper regulation of Clk2 is crucial, and it cannot be definitively stated that either an increase or decrease in expression will produce specific outcomes. It is also important to note that the expression of Clk2 can vary depending on conditions and circumstances.

In summary, Clk2 is closely associated with fatty liver through various pathways related to hepatic fat accumulation. However, Clk2 interacts with multiple pathways, and its effects can vary depending on the condition of the cells or the state of other metabolic pathways. While there is some evidence suggesting that aging may alter the expression of Clk2 in the liver, this is likely the result of complex interactions among various factors. Therefore, more research is needed to clearly understand the relationship between aging and Clk2. Initial studies have explored how aging affects Clk2 expression and activity and how this might lead to metabolic changes such as fat accumulation in the liver. Nonetheless, it remains unclear how Clk2 expression changes during aging and how external factors like exercise might influence Clk2 expression in the aging process.

We intended to determine how aging regulates the expression of Clk2 in the liver and the influence of exercise on this regulation. We investigated the expression levels of Clk2 protein and mRNA in the livers of 99-week-old, extremely aged mice that had undergone lifelong spontaneous exercise (LSE).

METHODS

1. Animal care

The Animal Care Facility at the Pusan National University School of Medicine in Yangsan, Gyeongsangnam-do, conducted the experiments. Female C57BL/6 mice, aged 6 weeks upon arrival, were sourced from Samtako (Daejeon, Korea). These mice were kept in an environment with a temperature of 22-24°C, 50-60% relative humidity, and a 12-hour light/dark cycle. The mice had unrestricted access to a standard diet (AIN-93G, Dyets, Betheleham, PA, USA) and fresh water, both of which were replenished daily. Euthanasia was performed on all mice after deep anesthesia was induced using isoflurane. The study's intervention method did not inflict pain on the mice. To ensure the mice's well-being, new food and water were provided at least twice weekly, and bedding was changed at least once a week to maintain cleanliness. All animal procedures adhered to the ethical guidelines of the Institutional Animal Care and Use Committee of Pusan National University (approval number: PNU-2019-2448).

2. Study design

The overall design of this study was previously detailed in our earlier publication [10]. Six-week-old C57BL/6 mice were acquired for an aging study. Half of these mice were housed in cages equipped with running wheels (Amazon, Changnyeong, Korea) (Old-EXE, n=7), while the other half were kept in cages without wheels (Old-CON, n=7). The mice were maintained until they reached 25 months of age (99 weeks old) for the aging study. For comparison, young mice at 6 weeks old were also bred under the same conditions for 16 weeks (Young-CON, Young-EXE, each n=7). To prevent immediate physiological effects on the experimental animals, the running wheels were removed from the cages of the Young-EXE and Old-EXE groups 48 hours before sacrifice. At the conclusion of the aging study, young mice were euthanized simultaneously at 22 weeks of age (Young mice=22 weeks old; Old mice=25 months old) (Fig. 1). Despite utilizing the same mice as in our previous study, we did not find any overlapping data. Additionally, we explicitly state that we used mouse liver tissue collected during prior research and affirm that this was not an instance of data salami slicing.

Fig. 1.

Study design.

3. Dual-energy X-ray absorptiometry

Body composition for all mice was measured utilizing a dual-energy X-ray absorptiometry (DXA) scanner (iNSiGHT VET DXA, OsteoSys, Seoul, Korea), a device well-established for its accuracy and reliability [11]. Prior to euthanasia, each anesthetized mouse was positioned prone on the scanner bed, with its limbs and tail extended outward. The scanning process involved the use of a flat panel detector along with a cone beam X-ray source, producing low-energy (60 kV/0.8 mA) and high-energy (80 kV/0.8 mA) X-rays. The obtained high-resolution images and the corresponding quantitative data were processed using the iNSiGHT software (Version 1.0.6; OsteoSys, Korea). Fig. 2 presents the DXA scan images of the mice along with the body composition data.

Fig. 2.

Comparison of body composition of mice measured dual-energy X-ray absorptiometry (DXA) and relative liver weight after sacrifice. (A) Representative DXA raw images for each group. (B) Analysis results of DXA images. All data are presented as the mean±standard deviation (SD). CON, control; EXE, exercise; NS, no significant; LWW, liver wet weight; BW, body weight. * p<.05, ** p<.01.

4. Sample collection

Sample tissue collection from experimental animals was performed 48 hours after the final exercise session to exclude any immediate physiological effects of exercise. To eliminate dietary influences, food was withheld for 10 hours prior to humane sacrifice. Mice were anesthetized with isoflurane inhalation, after which the skin from the abdomen to the neck was removed, and the liver was excised. The wet weight of the liver tissue in mice was measured immediately after dissection (Fig. 2B). Liver tissues for Western blotting and quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) were immediately placed in liquid nitrogen after liver excision and washing with 0.9% saline solution. These samples were stored at − 80°C until analysis. For histological analysis, the liver tissue was fixed in 10% formalin for 24 hours and then used to prepare paraffin blocks.

5. Western blotting

Frozen liver tissues were homogenized using PRO-PREP^TM for cell/tissue (iNtRON Biotechnology, Seongnam, Korea) with tissue grinder pestle. The homogenate was then centrifuge at 13,000 rpm for 5 minutes at 4°C, and the supernatant was collected. Protein concentration was de-termined with a Bradford protein assay. Soluble protein (20 µg) was boiled in Laemmli buffer for 5 minutes at 95°C, loaded onto 12% SDS-polyacrylamide gel, and transferred to polyvinyl difluoride membranes (Immobilon^®-P, Merck Millipore, Darmstadt, Germany). The membranes were blocked in 5% (w/v) skim milk or 5% (w/v) bovine serum albumin for 1 hour and incubated with primary antibodies overnight at 4°C. The membranes incubated overnight were washed three times for 10 minutes each with TBS-T or PBS-T. The washed membranes were then incubated with the secondary antibody for 1 hour at room temperature. After this incubation, the membranes underwent three washing steps, followed by the removal of excess washing buffer. Enhanced che-miluminescence (#1705061, Bio-Rad Laboratories, Hercules, CA, USA) was the applied for a minute. The images of the membranes were captured using ChemiDoc^TM MP imaging system (Bio-Rad Laboratories, USA). The captured images were analyzed AlphaEaseFC (Alpha Inno-tech, San Leandro, CA, USA) program to quantify the expression intensity of the target proteins at the expected sizes (kDa) where the primary and secondary antibodies had bound. Primary antibodies Clk2 (#sc-393909, Santa Cruz Biotechnology, Santa Cruz, CA, USA), Akt1 (#ab89402, Abcam, Cambridge, MA, USA), pAkt1 (#ab81283, Abcam, USA), PGC-1α (#ab191838, Abcam, USA), and β-actin (#A300-491A, Bethyl Laboratories, Montgomery, TX, USA) were used, and the dilution rates for the antibodies for Western blotting, the dilution base buffer, and the blocking buffer were chosen according to the manufacturer's instructions. The secondary antibody was selected to match the host of the primary antibody. The secondary antibodies used were goat anti-rabbit IgG (#1706515, Bio-Rad Laboratories, USA) and goat anti-mouse IgG (#1706516, Bio-Rad Laboratories, USA).

6. Quantitative real-time reverse transcription polymerase chain reaction

qRT-PCR was performed to analyze the gene expression level of Clk2 (gene encoding Clk2), Ppargc1a (gene encoding PGC-1α), and Akt1 (gene encoding Akt1). A 100 mg sample of liver tissue was taken from the frozen mouse liver and placed into a 1.5 mL bead beater tube containing TRIZol^TM reagent (#15596018, Ambion, Carlsbad, CA, USA) and metal beads. The tissue was then homogenized using a bead beater (TissueLyser II, Qiagen, Hilden, Germany). The RNA extraction process followed the phenol-chloroform RNA extraction [11]. The concentration and purity of the extracted RNA were verified using a spectrophotometer (NanoDrop^TM 2000c, Thermo Fischer Scientific, Waltham, MA, USA). Complementary DNA (cDNA) was synthesized from RNA of the same concentration, using AccuPower^® RT Premix (#K-2041, Bioneer, Daejeon, Korea) with custom oligo dT (18-mers) primers (Macrogen, Seoul, Korea). To analyze gene expression, we mixed synthesized cDNA, forward and reverse primers, RNase free water, and Fast SYBR^® Green Master Master Mix (#4385612, Applied Biosystems, Foster City, CA, USA). The mixture was then distributed in triplicate into a MicroAmp^TM Fast Optical 96-Well Reaction Plate (#4346907, Applied Biosystems, USA). The mixed samples were distributed in triplicate into a 96-well plate. Actb and Ywhaz were used as a multiple internal control genes to normalize target genes expression levels between samples [12]. Amplification and analysis were performed using the StepOnePlus Real-Time PCR System (Applied Biosystems, USA). The primer sequences for each gene used in the qRT-PCR are listed in Table 1. The relative gene expression level was calculated using the 2^{–ΔΔ CT} method [13].

Table 1.

Primer sequences of genes for quantitative real-time reverse transcription polymerase chain reaction

Gene symbol	Forward primer (5' to 3')	Reverse primer (5' to 3')
Clk2	CGAAGAAGAAGTCGCTCC	TCCGCCGCCGCCTTGTCC
Ppargc1a	AATACCGCAAAGAGCACGAG	ACCAACGTAAATCACACGGC
Akt1	ATGAACGACGTAGCCATTGTG	TTGTAGCCAATAAAGGTGCCAT
Actb	CCAACCGTGAAAAGATGACC	CCAGAGGCATACAGGGACAG
Ywhaz	GAAAAGTTCTTGATCCCCAATG	GC TGTGACTGGTCCACAATTCCTT

7. Histological evaluation of liver tissue

Paraffin blocks were prepared for histological analysis. The fixed liver tissue was dehydrated and then embedded in paraffin. Three randomly selected lobes of the liver were embedded in the paraffin blocks. The paraffin-embedded tissue was sectioned into 5 µm thick slices using a microtome. The sliced tissue sections were spread on water at 40-45°C and then mounted onto microscope slides. For hematoxylin & eosin (H&E) staining, the slides underwent deparaffinization and hydration processes before being immersed in hematoxylin for 5 minutes to stain the nuclei. The slides were then rinsed in running tap water for 5 minutes to remove the dye. Subsequently, the slides were immersed in tap water for 1 minute for the bluing process. The cytoplasm and other extracellular structures were stained by immersing the slides in 1% eosin solution for 1 minute. The eosin dye was then washed off with running tap water. After dehydration with alcohol and clearing with xylene, a drop of mounting medium was placed on the tissue sections, and cover slips were applied to fix the tissue samples. The stained slides were observed under a microscope and images were captured. We calculated the NAFLD activity score by referring to previous studies [14-16].

8. Statistical analysis

Two-way ANOVA was performed for all the measurement variables that passed the normality test to determine whether there was an interaction between age and exercise. Post hoc test was performed by Sidak's multiple comparison test. All variables were checked for normality by the Shapiro-Wlik test, defined as normality distributed data at p >.05. Statistical power analysis was conducted to ensure that the study had sufficient power to detect meaningful effects using G*Power 3.1 (Hein-rich-Heine-Universität Düsseldorf, Düsseldorf, Germany), with a desired power level set at .80 and α=.05 [17]. GraphPad Prism 8.3.0 (GraphPad Software, La Jolla, CA, USA) was used for all statistical analysis and plot-ting graphs. Statistical significances were considered at p <.05.

RESULTS

1. Effects of aging and lifelong spontaneous exercise (LSE) on body composition in mice

Representative DXA images of each group of experimental mice taken before sacrifice are shown in Fig. 2A. Analysis of these DXA images revealed no significant differences in bone mineral density and bone area between groups (Fig. 2B). In terms of bone mineral content, there was no significant difference due to exercise in young mice (Young-CON vs. Young-EXE), but in aged mice, the Old-EXE had significantly higher bone mineral content compared to the Old-CON (p<.05) (Fig. 2B). Body fat percentage (p <.05), body weight (p <.01), and relative liver weight were significantly higher in the Old-CON compared to the Young-CON (p<.05) (Fig. 2B).

2. Effects of aging and LSE on the expression of Clk2 and related proteins in mouse liver

Western blotting images of each target protein are shown in Fig. 3A. Clk2 expression in the liver was significantly higher in the Old-CON compared to the Young-CON (p <.01) (Fig. 3B). Additionally, liver Clk2 expression was significantly lower in the Old-EXE compared to the Old-CON (p <.05) (Fig. 3B). PGC-1α expression in the liver was significantly higher in the Old-CON compared to the Young-CON (p <.05) (Fig. 3C). Phosphorylation of Akt1 was significantly higher in the Young-EXE compared to the Young-CON (p <.05) (Fig. 3D).

Fig. 3.

Comparison of Clk2 and related protein expression in mouse liver using Western blotting. (A) Images of Western blotting bands showing the results. (B) Clk2, (C) PGC-1α, (D) Akt1, graphs comparing protein expression levels based on the analysis of Western blotting band image density. All data are presented as the mean±SD. * p<.05, ** p<.01.

3. Effects of aging and LSE on the expression of Clk2 and related genes in mice liver

In the liver, the expression of the Clk2 and related genes (Ppargc1a, Akt1) showed no significant differences in young mice (Fig. 4). However, the expression levels of Clk2 and Akt1 genes were significantly lower on the Old-EXE compared to the Old-CON (p <.05) (Fig.4A and C). There were no significant differences in the expression of Ppargc1a even in aged mice (Fig. 4B).

Fig. 4.

Comparison of Clk2 and related gene expression in mouse liver using quantitative real-time reverse transcription polymerase chain reaction. (A) Clk2 expression levels, (B) Ppargc1a expression levels, (C) Akt1 expression levels, analyzed using multiple internal reference genes for comparison. All data are presented as the mean±SD. NS, no significant. * p<.05.

4. Effects of aging and LSE on histological changes in the liver of mice

Representative histological images of the liver from each group, stained with Hematoxylin & Eosin, are presented in Fig. 5A. Based on the stained images, the NAFLD activity score was significantly higher in the Old-CON compared to the Young-CON (p <.001). Additionally, the score was significantly lower in the Old-EXE compared to the Old-CON (p <.05) (Fig. 5B).

Fig. 5.

Comparison of hepatic lipid accumulation and non-alcoholic fatty liver disease activity score. (A) Representative images of the results of hematoxylin & eosin staining using paraffin sections. (B) Comparison of non-alcoholic fatty liver disease activity scores based on histological image analysis. All data are presented as the mean±SD. CON, control; EXE, exercise; NAFLD, non-alcoholic fatty liver disease. * p<.05, *** p<.001.

DISCUSSION

Numerous previous studies have demonstrated the benefits of LSE. In particular, animal studies have shown that LSE can compensate for defects in energy sensing caused by aging, thereby reducing the risk of mortality [10]. The finding that exercise can delay or improve defects in energy sensing implies that it may lower the incidence of chronic diseases across various tissues. While most studies focus on changes in energy sensing in skeletal muscle induced by exercise, it is well known that exercise regulates energy sensing through the activation of AMP-activated protein kinase (AMPK) [18,19]. Additionally, Clk2 has been identified as interacting with key metabolic pathways, such as AMPK and mTOR, which play crucial roles in cellular energy status and metabolic responses [20-22]. These interactions suggest that Clk2 could acts as a metabolic regulator, particularly in the context of aging-related metabolic changes. This suggests that similar mechanisms may also operate in other tissues, such as adipose tissue [23,24]. Therefore, it is perhaps unsurprising that LSE would have beneficial effects in the liver, one of the body's major metabolic organs. Nevertheless, it remains unclear how Clk2, a protein closely associated with hepatic fat accumulation, is affected by natural aging and whether LSE can influence its expression during aging.

In our study, we first investigated whether LSE induces changes in body composition (Fig. 2). Specifically, we examined whether aging and LSE result in distinct phenotypic changes. Our findings revealed that bone mineral content was significantly higher in the Old-EXE compared to the Old-CON (Fig. 2B), suggesting that prolonged exercise may contribute to the maintenance of bone health. Weight-bearing exercises, including lifelong activities such as walking, running, and resistance training, have been shown to positively influence bone mineral density and may help in the prevention of osteoporosis [25,26]. Given these findings, along with the fact the other aspects of body composition show no significant differences between the Old-CON and Old-EXE, it is evident that LSE is particularly effective in maintaining bone mineral density. Additionally, we confirmed that aging leads to increases in body weight (p<.01), body fat (p<.05), and relative liver weight (p<.05) (Fig. 2B). However, no significant differences were observed between the Old-CON and Old-EXE in terms of body weight, body fat, or liver mass, aligning with the established notion that without dietary control, dramatic changes in body fat, body weight, and liver mass cannot be maintained [27,28]. Nonetheless, the lower average values in the Old-EXE compared to the Old-CON warrant further attention (Fig. 2B). In particular, the increase in liver mass due to aging was attributed to the accumulation of hepatic fat. To address this hypothesis, we conducted histological evaluations of the liver (Fig. 5A). The results clearly showed that lipid accumulation in the liver occurs as a consequence of aging (Young-CON vs. Old-CON, p<.001) (Fig. 5B), as we had anticipated. Previous studies have well-documented that hepatic fat accumulation due to aging in inevitable [29-31]. Therefore, our findings also suggest that the observed increase in liver lipid accumulation and consequent liver weight gain is attributable to the aging process. Although LSE did not result in significant changes in body weight, body fat, or liver mass, we observed that the NAFLD activity score was significantly lower in the Old-EXE compared to the Old-CON (Fig. 5B). Although LSE did not cause dramatic phenotypic changes during the aging process, it seems to play a critical role in maintaining metabolic rate and physiological functions in the liver.

As mentioned earlier, LSE seems to aid in preserving metabolic rate or energy sensing capability during aging. This process likely results from interactions between Clk2 and other metabolic pathways, such as AMPK and PGC-1α, which regulate mitochondrial biogenesis and fatty acid oxidation [20,32]. Notably, our study revealed a significant increase in Clk2 protein expression due to aging, and LSE appeared to help prevent this age-related increase in Clk2 expression. Interestingly, we also found that Clk2 increased along with PGC-1α (Fig. 3B and C), which is known to generally rise in conjunction with the development of fatty liver. Specifically, it has been reported that PGC-1α expression increases in fatty liver conditions, promoting fatty acid oxidation and gluconeogenesis, potentially exacerbating hepatic insulin resistance [33]. PGC-1α plays a pivotal role in regulating mitochondrial function and oxidative stress responses, both of which are critical in the development of hepatic steatosis and insulin resistance [34,35]. Therefore, aging seems to induce hepatic fat accumulation through the activation of PGC-1α/Clk2 pathway. While LSE did not suppress PGC-1α expression, it appeared to inhibit hepatic fat accumulation by suppressing Clk2 (Fig. 3C). This possibility is further supported by the fact that Clk2 expression was significantly lower in the Old-EXE compared to the Old-CON when analyzing gene expression (p <.05) (Fig. 4A). Moreover, given that the expression of Ppargc1a and Akt1 did not align with protein expression (Fig. 4B and C), it seems that LSE specifically affects Clk2 gene and protein expression. Expanding on this, Clk2 could be interpreted as a protein that responds more specifically to exercise.

This study has newly identified that both PGC-1α and Clk2 increase in the liver due to aging. Additionally, it was newly revealed that LSE can significantly contribute to the suppression of PGC-1α and Clk2. However, it is important to note that Clk2 is not the sole contributor to hepatic fat accumulation associated with aging. Furthermore, it remains unclear whether the suppression of Clk2 thought LSE is a precursor to the reduction of hepatic lipids. Further research is needed to investigate the specific interactions between Clk2, AMPK, and other metabolic regulators in the context of aging and exercise, as well as to determine whether these findings can be generalized to human populations. Future research in needed to address these questions and provide further insights into these mechanisms.

CONCLUSION

PGC-1α and Clk2 increase in the liver as a result of aging. Additionally, LSE appears to contribute to suppressing of Clk2, thereby reducing hepatic lipid accumulation. However, further research is needed to fully understand the direct relationship between Clk2, aging, and exercise.

Conflict of Interest

The authors declare that they do not have conflict of interest.

AUTHOR CONTRIBUTIONS

Conceptualization: IG Kim, KW Baek; Data curation: IG Kim, YY Xiang, JH Won; Formal analysis: IG Kim, KW Baek, YY Xiang, JW Won; Funding acquisition: KW Baek; Methodology: IG Kim, KW Baek, JH Kim; Project administration: KW Baek, JS Kim; Visualization: IG Kim, KW Baek, JH Won; Writing - original draft: IG Kim, KW Baek; Writing - review & editing: KW Baek.

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