
==== Front
Neuroreport
Neuroreport
NR
Neuroreport
0959-4965
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Lippincott Williams & Wilkins

39166393
NR-D-24-00214
00001
10.1097/WNR.0000000000002092
3
Cellular, Molecular and Developmental Neuroscience
Changes in gene expression due to aging in the hypothalamus of mice
Narukawa Masataka ab
Saito Yoshikazu bc
Kasahara Yoichi b
Asakura Tomiko bd
Misaka Takumi b
a Department of Food and Nutrition, Kyoto Women’s University, Kyoto
b Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo-ku, Tokyo, Japan
c Research Department, Toyo Institute of Food Technology, Kawanishi, Hyogo
d Department of Liberal Arts, The Open University of Japan, Chiba, Chiba, Japan
Correspondence to Masataka Narukawa, PhD, Department of Food and Nutrition, Kyoto Women’s University, 35 Kitahiyoshicho Imakumano Higashiyama-ku, Kyoto, Kyoto 605-8501, Japan Tel: +81 75 531 7131; e-mail: narukawa@kyoto-wu.ac.jp
16 10 2024
13 8 2024
35 15 987991
17 4 2024
29 6 2024
Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Aging generally affects food consumption and energy metabolism. Since the feeding center is located in the hypothalamus, it is a major target for understanding the mechanism of age-related changes in eating behavior and metabolism. To obtain insight into the age-related changes in gene expression in the hypothalamus, we investigated genes whose expression changes with age in the hypothalamus. A DNA microanalysis was performed using hypothalamus samples obtained from young (aged 24 weeks) and old male mice (aged 138 weeks). Gene Ontology (GO) analysis was performed using the identified differentially expressed genes. We observed that the expression of 377 probe sets was significantly altered with aging (177 were upregulated and 200 were downregulated in old mice). As a result of the GO analysis of these probe sets, 16 GO terms, including the neuropeptide signaling pathway, were obtained. Intriguingly, although the food intake in old mice was lower than that in young mice, we found that several neuropeptide genes, such as agouti-related neuropeptide (Agrp), neuropeptide Y (Npy), and pro-melanin-concentrating hormone (Pmch), all of which promote food intake, were upregulated in old mice. In conclusion, this suggests that the gene expression pattern in the hypothalamus is regulated to promote food intake.

aging
DNA microarray
hypothalamus
mice
neuropeptide
Japan Society for the Promotion of Science 10.13039/501100001691 19H02905 Masataka NarukawaJapan Society for the Promotion of Science 10.13039/501100001691 22H02292 Masataka NarukawaJapan Society for the Promotion of Science 10.13039/501100001691 23K23559 Masataka NarukawaJapan Society for the Promotion of Science 10.13039/501100001691 23K17575 Masataka NarukawaJapan Society for the Promotion of Science 10.13039/501100001691 23K17575 Tomiko AsakuraOPEN-ACCESSTRUE
SDCT
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pmcIntroduction

The health of older people has become an important social issue owing to the progressively aging populations in most developed countries. A balanced and nutritious diet is imperative for maintaining good health. Taste is a chemical sensation that primarily detects the nutrients present in food. The maintenance of taste sensation is important to ensure that older people have a balanced nutritional diet. Several reports have indicated that taste sensitivity gradually changes in an age-dependent manner in both humans and rodents [1–4]; for example, we have reported that old mice (over 100 weeks old) exhibited significant changes in their taste sensitivities for bitter and salty tastes [2,3]. However, the molecular mechanisms underlying this phenomenon remain unclear.

Generally, the brain shrinks, and changes occur at all levels, from chemicals to morphology, with age. It has been suggested that age-related changes in taste function are associated with changes in neuronal circuits [5]. Therefore, brain functions could be targeted to elucidate the molecular mechanisms underlying aging-dependent changes in taste sensitivity.

Each region plays different functions in the brain. The hypothalamus is recognized as the central region for feeding regulation [6]. Recently, it has been reported that selective activation of agouti-related protein (AgRP) neurons in the hypothalamus alters taste sensitivity [7]. Thus, investigating the change in the hypothalamus due to aging might be useful to reveal the cause of age-related changes in taste function. In this study, we performed a DNA microanalysis using hypothalamus samples obtained from young and old mice to investigate the gene expression changes in the hypothalamus due to aging.

Materials and methods

Animals

The study population comprised male C57BL/6J mice (CLEA Japan, Tokyo, Japan). The animals were housed at The University of Tokyo Animal Care Facility and had ad libitum access to standard laboratory chow (CE-2, CLEA Japan) and distilled water. The surrounding temperature and humidity were maintained at 23 °C and 55%, respectively, with a 12-h/12-h light/dark cycle (lights switched on at 0800 h). We divided the mice into two age groups: the young group aged 24 weeks (n = 5) and the old group aged 138 weeks (n = 5). Mice of normal sizes and with typical feeding behaviors were used. All experiments were performed in accordance with protocols approved by The University of Tokyo Animal Care Committee (approval number: P10-457).

DNA microarray experiment

The blood was drawn from the inferior vena cava for young mice and old mice under anesthesia by intraperitoneal injection of sodium pentobarbital. The collected blood was stored overnight at 4 °C and the serum was separated by centrifugation. The sera were stored at −80 °C until use. The mice were sacrificed by cervical dislocation, and their whole hypothalamus was removed. It was frozen with liquid nitrogen and kept at −80 °C until analysis. The sampling was performed in the morning of the same day. Total RNA was isolated from the hypothalamus using ISOGEN (Nippon Gene, Tokyo, Japan) and then purified with an RNeasy mini kit (QIAGEN, Hilden, Germany). The quality and quantity of total RNA were determined by agarose gel electrophoresis and spectrophotometry, respectively. Samples were taken from these individual tissues, and then DNA microarray analysis was performed with the GeneChip WT PLUS Reagent Kit (Affymetrix, Santa Clara, California) according to the manufacturer’s instructions. In brief, first-strand cDNA was synthesized from 100 ng of purified total RNA, and second-strand cDNA was synthesized. Subsequently, cRNA was transcribed by using T7 RNA polymerase, and 2nd cycle single strand (ss) cDNA was synthesized. Then, the template RNA was removed. After fragmentation, biotinylated ss cDNA was added to an Affymetrix Mouse Clariom S Array (Thermo Fisher Scientific, Waltham, Massachusetts), which contains probes for over 20 000 mouse genes. Following hybridization at 45 °C for 16 h, the array was washed and labeled with phycoerythrin. Fluorescence signals were scanned using the GeneChip system. GeneChip Command Console software was used to convert the array images to the signal intensity of each probe (CEL files). All array data were submitted to the National Center for Biotechnology Information Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/, GEO Series ID GSE238128).

Testosterone measurement

Serum testosterone concentrations were measured in triplicate using Testosterone ELISA Kit (Cayman Chemical, Ann Arbor, Michigan) according to the manufacturer’s instructions.

Data analysis

The CEL files were quantified with a model-based expression index using the statistical language R and Bioconductor. Hierarchical clustering was performed using the ‘pvclust’ function in R. To identify differentially expressed genes (DEGs), the rank product method was applied to the qFARMs quantified data. Probe sets with a false discovery rate (FDR) < 0.05 were considered to have different expression levels (differentially expressed) between the two groups.

The gene annotation was downloaded from R software. Gene annotation enrichment analysis of the DEGs (FDR < 0.05) was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Gene Ontology (GO) terms with Benjamini-corrected P values < 0.01 were extracted.

Statistical analysis

The statistical significance of differences between the groups was analyzed by unpaired t test for body weight and food intake per body weight or Welch t test for the cumulative food intake and serum testosterone concentration using Prism 6 software (Graph Pad Software, San Diego, California). The data are expressed as the mean ± SEM. For all analyses, differences were considered to be significant at P < 0.05.

Results

Changes in body weight and food intake

Figure 1 shows the body weight and food intake for 5 weeks before sampling. The body weight of the old mice was significantly higher than that of the young mice throughout the measurement period (Fig. 1a). However, the food intake relative to body weight of old mice was lower than that of young mice (Fig. 1b). The cumulative food intake in the old mice was significantly lower than that in the young mice (Fig. 1c). There was no significant difference in serum testosterone concentrations between young and old mice (Supplementary Figure 1, Supplemental digital content 1, http://links.lww.com/WNR/A778). Thus, we confirmed that old mice were heavier than young mice, but consumed less food.

Fig. 1 Changes in body weight and food intake. (a) Changes in body weight during the 6 weeks before sampling (19–24 weeks old for young mice and 133–138 weeks old for old mice). (b) Change in food intake per week (19–23 weeks for young mice and 133–137 weeks for old mice). (c) Comparison of the cumulative food intake. **, ***, and **** indicate P < 0.01, 0.001 and 0.0001, respectively (n = 5).

DNA microarray data quantification and detection of differentially expressed genes

To characterize the effect of aging on gene expression in the hypothalamus, we performed a hierarchical clustering analysis (Fig. 2). Hierarchical clustering analysis revealed that gene expression between young and old mice had distinct differences because a separate cluster was formed between young and old mice.

Fig. 2 Dendrogram of the hierarchical cluster analysis of passive ratios. au stands for ‘approximately unbiased’; it corresponds to the values on the left. bp stands for ‘bootstrap probability’; it corresponds to the values on the right.

For a comprehensive understanding of the effect of aging on the hypothalamus, we extracted DEGs using the rank products method. Statistical analysis of the GeneChip data revealed that the expression of 377 probe sets in the Mouse Clariom S Array was significantly altered during aging. Of the 377 probe sets altered in old mice, 177 were upregulated and 200 were downregulated.

Gene Ontology analysis

To gain insight into the effects of aging on the gene expression profiles, we examined which gene function categories were overrepresented among the DEGs. Accordingly, the extracted 377 probe sets were analyzed by gene annotation enrichment analysis using DAVID. GO terms with Benjamini-corrected P values of less than 0.01 were selected. The specific overrepresented GO terms were ‘neuropeptide signaling pathway’, ‘energy reserve metabolic process’, ‘cellular response to lipid’, ‘negative regulation of lipid biosynthetic process’, ‘positive regulation of lipid metabolic process’, ‘positive regulation of protein kinase B signaling’, ‘heat generation’, ‘aging’, ‘cell adhesion’, ‘homophilic cell adhesion via plasma membrane adhesion molecules’, ‘response to drug’, ‘response to amphetamine’, ‘response to nicotine’, ‘response to toxic substance’, ‘locomotory behavior’, and ‘ion transport’ (Table 1). The gene lists that constitute each GO term are shown in Supplementary Table 1, Supplemental digital content 2, http://links.lww.com/WNR/A779.

Table 1 Significantly enriched Gene Ontology (GO) terms found in 377 differentially expressed probe sets between young and old mice

GO ID	Category	GO term	Benjamini	
7218	Neuropeptide	Neuropeptide signaling pathway	1.59E-03	
6112	Metabolic process	Energy reserve metabolic process	4.61E-05	
71396		Cellular response to lipid	1.65E-03	
51055		Negative regulation of lipid biosynthetic process	1.95E-03	
45834		Positive regulation of lipid metabolic process	7.06E-03	
51897		Positive regulation of protein kinase B signaling	3.41E-03	
31649		Heat generation	8.81E-03	
7568	Aging	Aging	4.86E-05	
7155	Cell adhesion	Cell adhesion	5.78E-04	
7156		Homophilic cell adhesion via plasma membrane adhesion molecules	2.19E-03	
42493	Response to chemicals	Response to drug	6.33E-04	
1975		Response to amphetamine	1.95E-03	
35094		Response to nicotine	2.06E-03	
9636		Response to a toxic substance	4.95E-03	
7626		Locomotory behavior	1.95E-03	
6811	Ion transport	Ion transport	7.97E-03	

As the food intake of old mice was lower than that of young mice (Fig. 1b, c), we focused on the neuropeptide signaling pathway (Table 2). Among the food intake-promoting genes, the expression of agouti-related neuropeptide (Agrp), neuropeptide Y (Npy), and pro-melanin-concentrating hormone (Pmch) was upregulated due to aging. This finding suggests that the gene expression pattern in the hypothalamus is regulated to promote food intake.

Table 2 Differentially expressed genes related to neuropeptide signaling pathway that is altered in the old mice

Gene symbol	Gene name	Unigene	Gene expression	False discovery rate	
Glra3	Glycine receptor, alpha 3 subunit	Mm.307061	Up	3.09E-03	
Agrp	Agouti-related neuropeptide	Mm.441696	Up	5.43E-05	
Ecel1	Endothelin converting enzyme-like 1	Mm.140765	Down	2.31E-04	
Gpr165	G protein-coupled receptor 165	Mm.256065	Down	1.14E-02	
Gpr83	G protein-coupled receptor 83	Mm.4672	Down	3.72E-03	
Hcrt	Hypocretin	Mm.10096	Down	1.35E-04	
Npy	Neuropeptide Y	Mm.154796	Up	1.08E-04	
Ntsr2	Neurotensin receptor 2	Mm.281715	Down	8.07E-08	
Pmch	Pro-melanin-concentrating hormone	Mm.391436	Up	9.58E-04	
Ecrg4	Augurin precursor	Mm.50109	Down	2.44E-05	
Penk	Preproenkephalin	Mm.475097	Down	2.55E-03	

Discussion

Aging is a multifaceted and intricate process characterized by a gradual decline in physiological and behavioral deterioration. Brain aging alters the biological, chemical, and physical functions of neurons, resulting in memory loss, behavioral changes, diminished cognitive abilities, dementia, and weakened immune responses [8]. Recently, Hajdarovic et al. reported the effects of aging on the mouse hypothalamus by cell type, including neurons, astrocytes, and oligodendrocytes, using single-nucleus sequencing analysis [9]. The authors proposed that gene expression tends to become more variable with age in most cell types, which may be a factor in the cellular dysfunction in the aged hypothalamus. Therefore, to better understand the mechanism of brain aging, it is essential to gather a wide range of information on the alterations in gene expression that occur with aging.

Food consumption and energy metabolism are affected by aging [10,11]. As the feeding center is located in the hypothalamus, it is a key area to investigate the mechanisms underlying age-related alterations in eating behavior and metabolism. Additionally, taste is an important factor in food consumption. Taste sensitivity changes with aging [1–4]; however, the underlying mechanism is not well understood. Recently, it has been reported that the activation of AgRP neurons in the hypothalamus affects sensitivity to bitter and sweet tastes [7], suggesting that the activity of a network of hypothalamic neurons that controls appetite may also affect taste sensitivity. Therefore, to gain an understanding of the mechanisms underlying the age-related changes in taste sensitivity, we investigated age-related changes in gene expression in the hypothalamus.

Through GO analysis, we confirmed that 11 genes classified as neuropeptide signaling pathways were among the DEGs between young and old mice (Table 2 and Supplementary Table 1, Supplemental digital content 2, http://links.lww.com/WNR/A779). Of these, Agrp [12], Npy [13], and Pmch [14], which stimulate food consumption, were included, and their expression levels were upregulated in old mice. Additionally, the expression levels of other food intake-related genes, such as insulin-like growth factor 2 (Igf2) and dopamine receptor D (Drd) 1 and 2, decreased in old mice (Supplementary Table 1, Supplemental digital content 2, http://links.lww.com/WNR/A779). It is known that central administration of Igf2 can reduce food intake [15]. It has also been proposed that activation of Drd1 and Drd2 in the lateral hypothalamus suppresses feeding behavior [16]. These findings demonstrated that old mice have gene expression patterns that promote food intake. However, because old mice consumed less food than young mice (Fig. 1b, c), there was a contradictory relationship between eating behavior and gene expression. As one of the reasons, Klotho (KI) may be involved. Klotho (KI)-treated mice are known to have elevated energy expenditure [17], and this expression was also decreased in old mice (Supplementary Table 1, Supplemental digital content 2, http://links.lww.com/WNR/A779). Central KI is known to suppress Npy/AgRP neuronal activity and regulate metabolism [18]. Therefore, the downregulation of KI may be the cause of the upregulation of Npy and AgRP with aging. There was no significant difference in the expression of peptidergic factors that promote or suppress food intake, such as pro-opiomelanocortin-alpha (Pomc), brain-derived neurotrophic factor (Bdnf), corticotropin-releasing hormone (Crh), and galanin (Gal) [19], between young and old mice.

As mentioned previously, metabolic function decreases with aging. This was also supported by the GO analysis results, which identified terms related to metabolic processes, such as energy reserve metabolic processes and heat generation (Table 1 and Supplementary Table 1, Supplemental digital content 2, http://links.lww.com/WNR/A779). Major urinary protein 1 (Mup1), which is commonly included in these terms, is a member of the lipocalin family, and its expression is decreased in old mice (Supplementary Table 1, Supplemental digital content 2, http://links.lww.com/WNR/A779). Mup1 acts as a regulator of gluconeogenesis and lipogenesis in the liver [20] and improves energy expenditure and glucose tolerance by promoting mitochondrial function [21]. Furthermore, the expression of KI was also decreased in old mice (Supplementary Table 1, Supplemental digital content 2, http://links.lww.com/WNR/A779). These results are consistent with the fact that metabolism declines with aging. Testosterone levels are known to affect dietary food intake [22]. Therefore, we measured serum testosterone levels and found no significant differences between old and young mice. It is also known that leptin levels affect testosterone concentrations [23]. When blood leptin levels were measured in young and old mice, we found that there was no significant difference in serum leptin levels [2].

The expression of Agrp increased in old mice (Table 2 and Supplementary Table 1, Supplemental digital content 2, http://links.lww.com/WNR/A779). Bitter taste sensitivity is known to be reduced in old mice [2]. In contrast, a decrease in sensitivity to bitter taste has been observed in mice with activated AgRP neurons [7]. Thus, the changes in bitter taste sensitivity observed in old mice may be partly explained by the AgRP neuron-mediated effects. Furthermore, the activation of AgRP neurons also leads to increased sweet taste sensitivity. No significant changes in sweet taste sensitivity were observed in old mice, suggesting that factors other than AgRP may also be involved in the age-related changes in taste sensitivity.

In this study, we identified genes whose expression changes with age in the hypothalamus. We believe that our results provide useful information for understanding the mechanisms of age-related changes in taste sensitivities, as well as brain aging.

Acknowledgements

We thank Dr. Shinji Okada (The University of Tokyo) for the technical advice on the analysis of microarray data.

Supported in part by a Grant-in-Aid for Scientific Research (B) 19H02905, 22H02292, and 23K23559 to M.N. and for Challenging Research Exploratory 23K17575 to M.N. and T.A. from the Japan Society for the Promotion of Science.

Animal experiments were performed in accordance with protocols approved by the University of Tokyo Animal Care Committee (approval number: P10-457). Every attempt was made to reduce animal suffering, discomfort, and the total number of animals needed to obtain reliable results.

Conflicts of interest

There are no conflicts of interest.

Supplementary Material

Supplemental Digital Content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's website, www.neuroreport.com.
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