非肥満型高血糖発症モデルマウスの作製方法
A non-obese diabetes mouse model born with small-for-gestational age
Nagano Nobuhiko

日本大学 医学部 医学科 小児科学 准教授 長野 伸彦
背景他の研究／技術との相違点
DOHaD説とは、“胎児期や生後直後の健康・栄養状態が、成人になってからの健康に影響を及ぼす”という考え方である。
（日本産婦人科医会の資料より）

Developmental Origins
of Health and Disease
の略。

方法・結果
Table 1. Summary of Results (n=7 each)Birth weight (g)Body weight at 8 weeks of age (g)Blood glucose (mg/dL）
IRI (µIU/mL)
HOMA-RFat mass (g)Lean body mass (g)Total cholesterol (mg/dL)
Total triglycerides (mg/dL)

Control
1.9 (1.5-2.1)
41.2 (36.2-42.0)

Ischemia
1.5 (1.3-1.6)
36.9 (32.7-38.2)

p-value
<0.05
<0.05

72.0 (58.0-91.0) 213 (147.0-272.0)
1.0 (0.2-2.7)
3.9 (0.4-8.9)
0.16 (0.04-0.58)
2.08 (0.15-3.33)
17.7 (16.2-20.9
16.6 (8.5-22.9)
22.6 (19.4-25.0)
19.1 (15.0-27.4)
100.7 (87.2-107.3) 97.5 (79.3-144.5)
32.9 (18.7-56.9) 89.6 (23.0-139.1)

<0.01
0.03
<0.01
0.95
<0.05
0.94
0.02

発明の名称：非肥満型高血糖発症
非ヒト哺乳動物の作製方法
出願番号：2020-116354
公開番号：2022-014160

Figure 1. Mitochondrial function (n=3 each)
Figure 2. Oxidative stress markers (n=3 each)

まとめ・実用化に向けて①子宮内虚血による低出生体重-高血糖発症モデル
マウスは、ヒトの実臨床に近い動物モデルである。
②子宮内で低栄養に曝露されその環境に適合するための体質変化とその後の糖尿病の発症（DOHaD説）を基礎実験で解析することを可能にした。
③本発明の動物モデルを用いれば、低出生体重児-非肥満型糖尿病の病態メカニズムを明らかにできる可能性がある。

こんな企業の方を探しています〇下記目的で本技術を活用していただける方，
低出生体重-糖尿病発症メカニズムの解明
低出生体重-糖尿病発症の予防・治療研究（例：栄養学的介入研究、投薬介入研究）〇栄養補助食品作成技術を持つ方〇糖尿病発症予防食品や医薬品を開発中の企業〇DOHaD分野への展開を考えている企業

日本大学産官学連携知財センター （NUBIC)〒102-8275 東京都千代田区九段南4-8-24 日本大学会館
Tel: 03-5275-8139 Fax: 03-5275-8328 E-mail: nubic@nihon-u.ac.jp

http://www.nubic.jp

太ってないのに糖尿病のモデルマウス

作りませんか？

非肥満型２型糖尿病の病態解明・予防法・治療法の研究開発に適切な動物モデル

biomedicines
ArticleA Non-Obese Hyperglycemic Mouse Model that Develops afterBirth with Low Birthweight
Daichi Katayama † , Nobuhiko Nagano † , Shoichi Shimizu , Kimitaka Nakazaki, Kengo Matsuda,
Wataru Tokunaga, Kazumasa Fuwa, Ryoji Aoki and Ichiro Morioka *Department of Pediatrics and Child Health, Nihon University School of Medicine, Tokyo 173-8610, Japan;
katayama.daichi@nihon-u.ac.jp (D.K.); nagano.nobuhiko@nihon-u.ac.jp (N.N.);
shimizu.shoichi@nihon-u.ac.jp (S.S.); nakazaki.kimitaka@nihon-u.ac.jp (K.N.);
matsuda.kengo@nihon-u.ac.jp (K.M.); tokunaga.wataru@nihon-u.ac.jp (W.T.);
fuwa.kazumasa@nihon-u.ac.jp (K.F.); aoki.ryoji@nihon-u.ac.jp (R.A.)* Correspondence: morioka.ichiro@nihon-u.ac.jp; Tel.: +81-3-3972-8111† These authors contributed equally to this work.

Citation: Katayama, D.; Nagano, N.;
Shimizu, S.; Nakazaki, K.; Matsuda,
K.; Tokunaga, W.; Fuwa, K.; Aoki, R.;
Morioka, I. A Non-Obese
Hyperglycemic Mouse Model that

Abstract: The number of low birthweight (LBW) infants weighing below 2500 g has not decreased inJapan. This study aimed to develop an adult non-obese hyperglycemic mouse model born with LBW
to study the pathogenesis. At 16.5 days of gestation, transient intrauterine ischemia (blocked bloodflow in both uterine arteries for 15 min) was performed in a subgroup of pregnant mice (group I).
Non-occluded dams were used as sham controls (group C). After birth, female pups in each groupwere weaned at 4 weeks of age and reared on the normal diet until 8 weeks of age (n = 7). Fastingblood glucose levels, serum immunoreactive insulin (IRI), and body composition were then measured.
Metabolite analyses was performed on the liver tissues. Birthweight was significantly lower in group
I compared with group C. Pups from group I remained underweight with low fat-free mass andshowed hyperglycemia with high serum IRI and homeostasis model assessment of insulin resistancelevels, indicating insulin resistance. Metabolite analyses showed significantly reduced adenosine
triphosphate and nicotinamide adenine dinucleotide production and increased lactic acid in group I.
The pathogenesis of our non-obese hyperglycemic mouse model may be due to increased myogenic
insulin resistance based on mitochondrial dysfunction and reduced lean body mass.

Develops after Birth with Low
Birthweight. Biomedicines 2022, 10,1642. https://doi.org/10.3390/
biomedicines10071642

Keywords: body composition; developmental origins of health and disease; homeostasis
model assessment of insulin resistance; immunoreactive insulin; metabolite analyses; myogenic
insulin resistanceAcademic Editor: Chrysi Koliaki
Received: 7 June 2022
Accepted: 7 July 2022
Published: 8 July 2022
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims inpublished maps and institutional affiliations.

Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

1. Introduction
Fetuses exposed to undernutrition by lean pregnant women with nutritional restrictions during pregnancy lose weight and acquire insulin resistance and a frugal constitutionthat easily accumulates energy-efficient fat through the adaptation of metabolic and endocrine mechanisms to the undernutrition environment in utero [1,2]. Low birthweight(LBW) infants are more likely to develop metabolic syndrome and lifestyle-related diseases such as type 2 diabetes mellitus, hyperlipidemia, and hypertension in adulthood(developmental origins of health and disease [DOHaD] theory) [3].
The total number of births in Japan is decreasing, yet the trend of LBW infants weighing
under 2500 g has not decreased [4]. The percentage of LBW infants in the total annual
number of births is 9.49%, which is higher than that of other countries (8.02% in the UnitedStates, 6.95% in the United Kingdom, 6.65% in Germany, 4.95% in China, and 8.38% in
Brazil) [5]. Therefore, it is very important to reduce adulthood health problems in LBW
infants for medical, economic, and social reasons.
It has been reported that a Japanese patient born with LBW developed type 2 diabetes
mellitus without being markedly obese at a young age [6]. Some diabetic patients in Japan

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are non-obese and have a normal body mass index (BMI, 24.9 kg/m2 or less) [7]. Indeed,Japanese type 2 diabetes patients were less obese than those in Western countries [8].
Approximately 15% of Japanese children with type 2 diabetes are non-obese, which isa higher rate than that in other countries [9]. It is still unclear why there are so many
non-obese type 2 diabetes patients in Japan, and the scientific reasons are under research.
Animal models wherein obese type 2 diabetes develops after birth with LBW by aeutrophic (high fat) diet already exist [10]. However, there is no animal model wherein nonobese hyperglycemia develops after birth at LBW. The cause of non-obese type 2 diabetes
is thought to be insulin resistance due to fat accumulation in the liver and skeletal muscle
as visceral or ectopic fat [11]. In humans, the relationship between the development rateof type 2 diabetes and birth weight shows a U-shape [12], suggesting that future visceralfat accumulation occurs regardless of whether birthweight is high or low. However, themechanisms of insulin resistance and details of body composition are unclear in non-obese
type 2 diabetes that develops after birth at LBW.
The aims of this study were to develop a mouse model with non-obese hyperglycemia
that develops after birth at LBW and to clarify the pathogenetic mechanism of non-obese
hyperglycemia in our mouse model.
2. Materials and Methods
2.1. Study Design, Protocol, and Animal Model
This study was carried out in accordance with the ARRIVE guidelines, and the protocols were approved by the Nihon University Institutional Animal Care and Use Committee(protocol nos. AP18MED033-1 [5 July 2019] and AP20MED003-1 [3 April 2020]). ICR micestrains at 12 days of gestation were obtained from Sankyo Labo Service Corporation Inc.,Tokyo, Japan. All mice were fed a normal solid diet (moisture: 7.9%, crude fat: 5.1%, crude
protein: 23.1%, crude ash: 5.8%, crude fiber: 2.8%, and soluble solids: 55.3% (Oriental Yeast
Co., Ltd., Tokyo, Japan) and had access to water ad libitum.
The lower abdomen was incised under isoflurane inhalation anesthesia (induction 5%,
maintenance 2%) at 16.5 days of gestation. In the intrauterine ischemia (group I), maternal
mice were pre-warmed at 37.5 ◦ C on a hot plate, the uterine artery was exposed and bloodflow to the artery was blocked by a clip for 15 min to lead to fetus hypoxia and undernutrition(Figure 1a,b) [13]. The uterine artery was then unclipped, the were fetuses returned into theabdomen of the mother mice, and the abdomen was sutured. The controls (group C) only underwent a lower abdominal incision under similar anesthesia (sham control). Newborn pups
were reared under the care of their mothers; female pups from the two groups were weaned
at 4 weeks of age after birth and reared on a normal diet until 8 weeks of age (Figure 1c).
At birth and thereafter, the pups were weighed twice a week until 8 weeks of age. The
body weight gain plateaued at approximately 8 weeks of age. Eight-week-old mice represent
human adulthood [14]. At 8 weeks of age, body composition was measured, blood was drawn
from the heart, and the liver was removed after 12 h of fasting (Figure 1c,d). Fasting blood
glucose levels, serum immunoreactive insulin (IRI), body composition, and serum lipoprotein
levels were measured at 8 weeks of age. Metabolite analyses were performed on liver tissues
at 8 weeks of age. Results were compared between group I and C (n = 7 for each group).
2.2. Glucose Metabolism Markers
Blood glucose levels after 12 h of fasting were measured using a Stat Strip XP2 (Nipro
Corp., Osaka, Japan). Blood was then centrifuged at 3000 rpm for 5 min at room temperatureand the serum was stored at −20 ◦ C. Serum IRI levels were measured using a mouse/rat
total insulin (high sensitivity) assay kit (Immuno-Biological Laboratories Co., Ltd., Fujioka,
Gunma, Japan). Homeostasis model assessment of insulin resistance (HOMA-R) was
calculated using the human formula:
HOMA-R = fasting blood glucose (mg/dL) × IRI (µIU/mL)/405
since there is no formula for mice [15].

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Figure 1. Experimental procedures. (a) Uterine artery ligation in pregnant mice (ischemia for
15 min). (b) Body temperature control on a hot plate (37.5 ◦ C). (c) Study flow of this study. (d) Body
composition measurements using ImpediVETTM (Bioresearch center, Co., Ltd., Nagoya, Japan).

2.3. Body Composition Analyses
Body composition was measured using the bioelectrical impedance analysis method
using a body composition analyzer for laboratory animals (ImpediVETTM , Bioresearch
center, Co., Ltd., Nagoya, Japan) (Figure 1d) [15]. Bioelectrical impedance analysis is used
to estimate body composition (such as body fat percentage) by measuring the electricalresistance (bioimpedance) of biological tissues. Adipose tissue conducts almost no electricity, while muscle and other tissues that contain many electrolytes easily conduct electricity.
The ratio of fat to other tissues can be estimated by measuring electrical resistance [16]. Fatmass percentage and fat-free mass percentage were measured. Fat mass (g) (1) or fat-freemass (g) (2) were calculated using the following formula:(1) Fat mass (g) = eight-week-old body weight (g) × fat mass percentage/100(2) Fat-free mass (g) = eight-week-old body weight (g) × fat-free mass percentage/100
2.4. Serum Lipoprotein Levels
Cholesterol and triglyceride profiles in serum lipoproteins were analyzed using apreviously described gel-permeation high-performance liquid chromatography method(LipoSEARCH® ; Skylight Biotech, Akita, Japan) [17–19]. Cholesterol and triglyceride levelsof total- and major classes of lipoproteins (high density lipoprotein, HDL; low density
lipoprotein, LDL; very low-density lipoprotein, VLDL) were defined using component peakanalyses based on lipoprotein particle sizes using the Gaussian curve fitting technique [18].
2.5. Metabolite Analyses in Liver
Metabolites were extracted using the following methods: approximately 50 mg offrozen liver tissue from female mice (8 weeks of age, n = 3 each group) was placed in a
homogenization tube along with zirconia beads (5 mm ϕ and 3 mm ϕ). Next, 1500 µL of 50%
acetonitrile/Milli-Q water containing internal standards (H3304-1002, Human Metabolome
Technologies, Inc. (HMT), Tsuruoka, Yamagata, Japan) was added, followed by two cycles

Biomedicines 2022, 10, 1642

4 of 13of tissue homogenization using a bead shaker at 1500 rpm for 120 s at 4 ◦ C each (Shake
Master NEO, Bio Medical Science, Tokyo, Japan). The homogenate was centrifuged at
2300× g for 5 min at 4 ◦ C. The upper aqueous layer (400 µL) was centrifugally filteredat 9100× g for 120 min at 4 ◦ C using a Millipore 5-kDa cutoff filter (Human Metabolome
Technologies, Inc.) to remove macromolecules. Under vacuum, the filtrate was evaporated
to dryness and redissolved in 50 µL of Milli-Q water for the metabolome analysis.
Metabolome analyses were conducted using capillary electrophoresis time-of-flightmass spectrometry, as previously described [20,21]. Briefly, capillary electrophoresis timeof-flight mass spectrometry analysis was performed using an Agilent CE capillary electrophoresis system (Agilent Technologies, Inc., Santa Clara, CA, USA). The spectrometer
was scanned at 50–1000 m/z and peaks were extracted by integration software (Keio University, Tsuruoka, Yamagata, Japan) to obtain the following data; m/z, migration time, andpeak area [22]. The peaks were determined according to the metabolite database based on
their m/z values and migration times. Peak areas were normalized using internal standards
and sample volume, then relative levels of the metabolites were obtained.
Principal component analysis and hierarchical cluster analysis were performed, as
previously described [23]. Detected metabolites were plotted on metabolic pathway maps,
as previously described [24].
2.6. Statistical Analyses
Data are expressed as the mean ± standard error of the mean. Comparisons between
the two groups were performed with the Mann-Whitney U test or Welch’s t test as appropriate using JMP ver. 14 (SAS Institute, Cary, NC, USA). A p value < 0.05 was considered asignificant difference.
3. Results
3.1. Birth Weight and Changes in Body Weight Gain
Birthweight was significantly lower in group I (1.5 g) than that in group C (1.8 g)(p = 0.01) (Figure 2a). The mean body weights of groups I and C at 1, 2, 3, 4, 5, 6, 7, and8 weeks of age were: 4.7 and 7.2 g, p < 0.01; 7.3 and 9.7 g, p < 0.01; 14.0 and 15.5 g, p = 0.03;
22.1 and 26.1 g, p < 0.01; 30.5 and 34.1 g, p < 0.01; 33.2 and 36.3 g, p = 0.02; 33.9 and 37.9 g,
p < 0.05; and 35.5 and 40.2 g, p = 0.01, respectively. Group I had a LBW and was consistently
underweight thereafter, even at 8 weeks of age (Figure 2b).
3.2. Glucose Metabolism Markers
The mean fasting blood glucose level at 8 weeks of age was significantly higher ingroup I compared with group C (196.9 and 75.0 mg/dL, respectively) (p < 0.01). The
mean levels of IRI and HOMA-R were significantly higher in group I (3.9 µIU/mL and 1.9,
respectively) compared with group C (1.4 µIU/mL and 0.3, respectively) (p = 0.03, p < 0.01,
respectively; Figure 2c–e).
3.3. Body Composition
There was no significant difference between the mean fat mass of group I and group C(16.6 and 17.7 g, respectively) (p = 0.95, Figure 3a). Meanwhile, the mean fat-free mass was
significantly lower in group I than that of group C (19.1 and 22.6 g, respectively) (p = 0.01,
Figure 3b).
3.4. Serum Lipoprotein Levels
Mean total cholesterol, LDL cholesterol, VLDL cholesterol, and HDL cholesterol levels
were 104.4 mg/dL, 15.5 mg/dL, 10.7 mg/dL, and 77.6 mg/dL, respectively in group I and99.3 mg/dL, 16.5 mg/dL, 8.2 mg/dL, and 74.3 mg/dL, respectively in group C, with nosignificant differences between the two groups (Figure 3c–f). Total triglyceride level was
significantly higher in Group I (88.1 mg/dL) than that of group C (37.3 mg/dL) (p < 0.05;
Figure 3g).

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Figure 2. Body weight and glucose metabolism markers. (a) Birthweight was measured on the firstday after birth. (b) Changes in weight gain from birth to 8 weeks of age (•: Ischemia, : Control).
(c) Fasting blood glucose levels. (d) Serum immunoreactive insulin levels. (e) Homeostasis model
Biomedicines 2022, 10, 0
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assessment of insulin resistance levels. Data are shown as the mean ± standard error of the mean(n = 7 per group). * p < 0.05, ** p < 0.01.

Figure 3. Cont.

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Figure 3. Body compositionand serum lipoprotein levels. (a) Fat mass. (b) Fat-free mass. (c) Total
Figure 3. Body composition and serum lipoprotein levels. (a) Fat mass. (b) Fat-free mass. (c) Totalcholesterol. (d) LDL
cholesterol.
(e) VLDL
cholesterol.
HDL cholesterol.
(g) Total(g)triglyceride.
cholesterol. (d) LDL
cholesterol.
(e) VLDL (f)cholesterol.
(f) HDL cholesterol.
Total triglyceride.
Data are shown as Datathe mean± standard
error
of the mean(nthe
= 7meanper (ngroup).
are shownas the mean
± standard
error of= 7 per HDL,
group).high-density
HDL, high-density
lipoprotein; LDL,
low-density
lipoprotein;
VLDL, very-low-density
lipoprotein.
lipoprotein; LDL, low-density
lipoprotein;
VLDL,
very-low-density
lipoprotein.

3.5. Liver Metabolite Analyses
A clear difference was found between group I and group C in the principal component
analysis and the heat map display of the hierarchical cluster analysis (n = 3 for each group,
Figure 4a,b; Supplementary Tables S1 and S2).

Figure 4. Metabolite analyses in liver tissue. (a) Principal component (PC) analysis. (b) Heat map
display of the hierarchical cluster analysis. n = 3 per group.

Comparative analysis of the tricarboxylic acid (TCA) cycle, respiratory chain, andglycolytic pathway between group I and C are shown in Figure 5a,b, and Supplementary
Table S3. Malic acid, fumaric acid, succinic acid, and citric acid were higher in group I thangroup C (p < 0.001, p < 0.001, p = 0.170, and p = 0.118, respectively; Figure 5c). Respiratory
chain analyses showed that nicotinamide adenine dinucleotide (NAD+ ) and adenosine
triphosphate (ATP) were significantly lower in group I than that of group C (p = 0.010 and
p = 0.031, respectively). Meanwhile, lactic acid in the glycolytic pathway was significantly

Biomedicines 2022, 10, 1642

7 of 13higher in group I than that in group C (p = 0.002). Representative oxidative stress markers
3-indoxylsulfuric acid, cysteine, and S-adenosylmethionine were significantly higher ingroup I than that in group C (p < 0.001, p < 0.05, and p < 0.01, respectively; Table 1).

Figure 5. Comprehensive comparative analysis between the ischemia and control groups for
the TCA cycle, respiratory chain, and glycolytic pathway. (a) TCA cycle and respiratory chain.
(b) Glycolytic pathway. (c) Important metabolites. Red and blue bars show group I and C, respectively.
ATP, adenosine triphosphate; NAD+ ; nicotinamide adenine dinucleotide; TCA, tricarboxylic acid;n = 3 per group.

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Table 1. Oxidative stress markers.
Comparative Analysis
Group I vs. C
Compound Name

Compound Name

Ratio †

p-Value k

Oxidative stress3-indoxylsulfuric acidCys
S-adenosylmethionine
Ergothioneine
N,N-dimethylglycine

2.0
3.0
1.7
0.7
0.9

<0.001
0.011
0.003
0.061
0.683

† The ratio of the detected mean values between the two groups. k Welch’s t-test.

4. Discussion
In clinical practice, patients born with LBW can develop type 2 diabetes without
significant postnatal obesity; however, animal models have not yet been developed. In
this study, we confirmed that our mouse model using intrauterine ischemia by transiently
blocking blood flow of uterine arteries in pregnant mice yields non-obese hyperglycemia inyoung adulthood after birth with LBW. Total cholesterol, LDL cholesterol, VLDL cholesterol,and HDL cholesterol levels were not significantly different from the controls. Reduced leanbody mass and mitochondrial dysfunction contributed to the increased myogenic insulin
resistance of non-obese hyperglycemia (Figure 6).

Figure 6. A theory for the pathogenesis of non-obese hyperglycemia after birth with low birthweightin our model.

4.1. Mice Model Born with LBWIntrauterine malnutrition, such as ligation of bilateral uterine arteries in pregnant
rats or food restriction of pregnant animals, can cause fetal growth restriction [25–28].
There are animal models that develop hyperglycemia with adulthood obesity [10] andthat remain underweight in adulthood but do not develop hyperglycemia [29]. However,this is the first animal model that develops hyperglycemia after birth with LBW without
developing adulthood obesity on a normal diet. Further studies are needed to investigate ifBiomedicines 2022, 10, 1642

9 of 13the pathogenesis of our mouse model is related to that of human non-obese type 2 diabetic
patients.
4.2. Myogenic Insulin ResistanceGroup I had significantly lower fat-free mass than that of group C, although there
was no difference in fat mass between the groups. This may be due to decreased muscle
mass in group I since this group was not obese. Patients born with LBW tend to have
low muscle mass in adulthood [30] and their basal metabolism is low [31] which leads tovisceral fat accumulation, decreased adiponectin secretion, and insulin resistance [32]. Our
animal model showed myogenic insulin resistance due to reduced muscle mass which isconsidered one of the causes of non-obese diabetes.
4.3. Mitochondrial Dysfunction
Mitochondria are the site of energy production such as ATP; therefore, mitochondrial dysfunction decreases ATP production. Lactic acid increases since ATP is produced
through anaerobic glycolysis [33]. NAD+ is one of the cofactors for energy production in
mitochondria and is also reduced by mitochondrial dysfunction [34]. In this study, group
I liver metabolite analyses showed decreased mitochondrial function through decreased
ATP production, increased lactic acid, and decreased NAD+ . In addition, 3-indoxylsulfuric
acid (an oxidative stress molecule) was significantly higher in group I compared with group
C. Ischemia and reperfusion produce oxidative stress, such as reactive oxygen species,
resulting in decreased mitochondrial function [35–38]; this suggests that the intrauterine
ischemia in the present model caused mitochondrial dysfunction by the same mechanism(Figure 7).

Figure 7. Mitochondria dysfunction by ischemia and reperfusion. ATP, adenosine triphosphate;mPTP, mitochondrial permeability transition pore; ROS, reactive oxygen species.

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Diabetes development is strongly associated with mitochondrial dysfunction in skeletal muscle and liver; therefore, mitochondrial dysfunction can cause insulin resistance [39].
The clinical features of mitochondrial diabetes include short stature and non-obesity [40].
The development of mitochondrial diabetes is at a relatively young age (in the 30s), andthe maternal inheritance of diabetes mellitus is 59%; therefore, not all cases are maternallyinherited. Mitochondrial diabetes varies from insulin deficiency to insulin resistance. It isthought that autoimmune mechanisms are less likely to be involved. Other reports demonstrated a link between insulin resistance and mitochondrial dysfunction in the elderly [41]and mitochondrial dysfunction in a close relative of a diabetic patient [41]. Furthermore,
type 2 diabetic patients have decreased expression of mitochondrial respiratory chain complexes or mitochondrial metabolism-related genes compared with healthy controls [42,43]
while continuous physical activity improves insulin resistance and mitochondrial dysfunction in type 2 diabetic patients and obese individuals [44]. In addition, decreased
mitochondrial DNA in peripheral blood cells correlates with insulin resistance [45] suggesting that quantitative or qualitative mitochondrial decline may be involved in thedevelopment of non-obese type 2 diabetes. Mitochondrial dysfunction causes muscle
atrophy [46] and may be associated with insulin resistance due to reduced muscle mass
which is the cause of non-obese type 2 diabetes.
4.4. Other Pathogeneses
As other pathogeneses, increased insulin clearance [47], decreased pancreatic β-cellfunction [48], and enlarged fat cells [49] have been reported in the cause of non-obese type2 diabetes. It is necessary to study if these causes exist in this model using biochemical,
genetic, and histopathological analyses.
4.5. Limitations
There were several limitations in this study. First, there was a small number of animals
due to ethical issues. Second, only female mice were included because many male micedied due to the intrauterine ischemia. The results of male mice showed a similar trend;
however, the relationship was not as significant as those of females. Fewer male mice usedin the experiments may have contributed to a less significant difference. Mitochondria arematernally inherited and may be more likely to appear as a female phenotype; however,further studies are needed using large sample sizes in both sexes. Third, visceral fat
accumulation was not assessed by any imaging. Fourth, intrauterine ischemia is a cause of
LBW at birth, but not of all LBW causes. Finally, since the equation of HOMA-R generally
use is for humans, it is necessary to verify whether the results of this formula really
represent insulin resistance in mice.
5. Conclusions
This mouse model showed non-obese hyperglycemia in young adulthood after birthwith LBW due to transient intrauterine ischemia. A pathogenetic mechanism may involve
increased myogenic insulin resistance by mitochondrial dysfunction. In the future, using
this model, preventive and therapeutic strategies for non-obese hyperglycemia will be
studied, such as the use of growth hormone, whey protein, or Chinese medicine, andnon-invasive insulin therapy [50].
6. Patents
A method for producing a mouse model that develops non-obese type 2 diabetic inyoung adulthood after birth with LBW due to transient intrauterine ischemia was lodged
with the Japanese Patent Office on 6 July 2020, by Nobuhiko Nagano, Ichiro Morioka,
Shoichi Shimizu, and Daichi Katayama (application number: 2020-116354).

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Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/biomedicines10071642/s1, Table S1: principal component score;
Table S2: metabolites and principal component score; Table S3: comparative analysis.
Author Contributions: Conceptualization, D.K., N.N. and I.M.; methodology, D.K., N.N., S.S. andK.N.; formal analysis, D.K., N.N. and I.M.; investigation, D.K., N.N., S.S., K.N., K.M., W.T., K.F.
and R.A.; data curation, N.N. and I.M.; writing—original draft preparation, D.K., N.N. and I.M.;
writing—review and editing, S.S., K.N., K.M., W.T., K.F. and R.A.; visualization, D.K., N.N. and I.M.;
supervision, I.M.; funding acquisition, N.N., S.S., K.F. and R.A. All authors have read and agreed tothe published version of the manuscript.
Funding: This research was supported by the Nihon University Research Grant (2021), Nihon
University School of Medicine Alumni Association’s 60th anniversary fund research grant (2020), theGrants-in-Aid for Young Scientists (grant number: 19K20194, 22K15908, 22K15446, and 22K17839)
and Scientific Research (C) (grant number: 21K11582) of JSPS KAKENHI, the Japanese Society
for Pediatric Endocrinology Future Development Grant supported by Novo Nordisk Pharma Ltd.,
Kawano Masanori Memorial Public Interest Incorporated Foundation for Promotion of Pediatrics(2022), and the Japan Agency for Medical Research and Development (grant number: JP20fk0108137).
Institutional Review Board Statement: This study was carried out in accordance with the ARRIVE
guidelines and the protocols were approved by the Nihon University Institutional Animal Care and
Use Committee (protocol nos. AP18MED033-1 [5 July 2019] and AP20MED003-1 [3 April 2020]).
Informed Consent Statement: Not applicable.
Data Availability Statement: The data that support the findings of this study are available from thecorresponding author upon reasonable request.
Acknowledgments: We thank Tatsuhiko Urakami (Department of Pediatrics and Child Health,
Nihon University School of Medicine) for important and grateful advice for the pathogenesis of
hyperglycemia; and Tomoo Okada (Department of Nutrition and Life Sciences, Kanagawa Instituteof Technology) for technical support for conducting experimental procedures.
Conflicts of Interest: The authors declare no conflict of interest in this study.

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