P-172

カニクイザルの体重，血液学的検査，血液生化学的検査の項目間相関について〇高橋 一彰，佐藤 順子，山本 大，比毛 則夫，高木 辰巳，石井 宏幸，岡村 隆之，大竹 誠司 株式会社LSIメディエンス

Relationship between Body Weight and Hematological and Biochemical Parameters in Cynomolgus Monkeys○Kazuaki TAKAHASHI, Junko SATO, Dai YAMAMOTO, Norio HIKE, Tatsumi TAKAKI, Hiroyuki ISHII, Takayuki OKAMURA, Seiji OTAKE LSI Medience Corporation
If you have any questions, please contact the following: takahashi.kazuaki@mg.medience.co.jp

Little has been reported on the relationship between body weight andclinical pathology parameters in toxicity studies using cynomolgus
monkeys. We have previously reported on the incidence of animals
showing body weight loss in toxicity studies in spite of being control
animals and the features of their results in hematology, biochemistry,and pathology [1]. In this study, we analyzed the relationship among
body weight, rate of change in body weight, hematology, andbiochemistry in control animals including animals showing body weightloss.
[1] A Decrease in Body Weight without a Decrease in Food
Consumption Observed in Cynomolgus Monkeys and Its Improvement.
The 46th Annual Meeting of the Japanese Society of Toxicology 2019.

Number ofanimals
95

Items (Abbreviation; Unit)
Rate of change in body weight (%)
Body weight (kg)

Table 1 Summary
statistics

95

Animals used: Cynomolgus monkeys in a control group (95 males and 95 females, 3 to 6 years old) in a 4-week toxicity study
Body weight: At the end of the 4-week dosing period
Rate of change in body weight: It was calculated according to the following formula.
Rate of change in body weight = {(body weight at the end of the study) – (body weight at the start of the study)} /(body weight at the start of the study) × 100
Hematology: Items listed in Table 1 were analyzed using CA-510 or XT-2000iV (Sysmex Corporation). PT and APTT were examinedusing plasma samples, and the other items were examined using blood samples anticoagulated with EDTA-2K.
Biochemistry: Items listed in Table 1 were analyzed using TBA-200FR (Canon Medical Systems Corporation) or Epalyzer 2 (Helena
Laboratories).
Statistical analysis: The Shapiro–Wilk’s test was used to check for normal distribution (Table 1) using statistical analysis system,EXSUS version 8.1.0 (CAC Croit Corporation, statistical analysis software: SAS 9.4, SAS Institute Japan Ltd.). Furthermore, data wereanalyzed by the Pearson correlation test for parametric tests or Spearman correlation tests for non-parametric analysis at asignificance level of p<0.05, 0.01, or 0.001. The correlations were classified according to the r value (Table 2a).

MaleStandard
StatisticalMean
deviation
distribution
2.93165.2604 Non-parametric95

33.9368

13.0586

Non-parametric

Alanine aminotransferase (ALAT; U/L)

95

57.3579

67.2403

Non-parametric95

52.0000

30.4976

Non-parametricNon-parametricLactate dehydrogenase (LDH; U/L)

68

280.4559

73.0104

Non-parametric68

266.4706

69.0491

Non-parametric

Hemoglobin concentration (HGB; g/dL)

95

13.30420.7839Parametric95

12.91370.9317

Non-parametric

Glutamate dehydrogenase (GLDH; U/L)

15

28.8000

18.9480

Parametric15

27.6000

19.9241

Parametric

Hematocrit (HCT; %)95

43.1274

2.7166

Non-parametric95

42.14112.8324

Non-parametric

Alkaline phosphatase (ALP; U/L)95

1699.0105 768.2146 Non-parametric95

790.3263 304.1855 Non-parametric

Mean corpuscular volume (MCV; fL)

95

78.02424.7347

Parametric95

79.2032

3.8819Non-parametric

γ-Glutamyl transpeptidase (γGT; U/L)

60

77.65

38.934

Non-parametric

60

57.1

Mean corpuscular hemoglobin (MCH; pg)

95

24.0747

1.3633

Parametric95

24.2600

1.1526

Parametric

Creatine kinase (CK; U/L)89

80.0449

89.0468

Non-parametric89

96.5056

156.6775 Non-parametric

Mean corpuscular hemoglobin concentration (MCHC; g/dL)

95

30.88421.2529Non-parametric95

30.7568

1.3355

Non-parametric

Total bilirubin (mg/dL)

95

0.10950.0670Non-parametric95

0.14420.0725

Non-parametric

Reticulocyte ratio (%)

86

0.91350.5021

Non-parametric86

1.06780.4126

Non-parametricUrea nitrogen (mg/dL)

95

21.5674

6.5991

Non-parametric95

18.3495

3.7907

Non-parametric

Reticulocyte count (×10 /L)

54

51.3815

24.9188 Non-parametric54

57.8074

22.1574 Non-parametric

Creatinine (mg/dL)

95

0.84110.1519Non-parametric95

0.70740.1034

Non-parametric

Platelet count (PLT; ×103/μL)

95

390.3789

85.6238

Parametric95421.6211

83.4748 Non-parametric

Glucose (mg/dL)

95

85.0947

12.9353

Parametric95

80.7263

13.4001

ParametricProthrombin time (PT; sec)

95

9.06530.7236

Non-parametric95

8.56630.4741

Parametric

Total cholesterol (mg/dL)

95

107.2421

25.1425

Parametric95

117.1158

24.0619

Non-parametric

Activated partial thromboplastin time (APTT; sec)95

22.9295

1.8607

Parametric95

22.36211.8649ParametricPhospholipid (mg/dL)

70

154.1857

35.1701

Parametric70

165.7429

29.4548

ParametricWhite blood cell count (WBC; ×103/μL)

959.3411

3.4228Non-parametric95

8.39982.5239Non-parametric

Triglyceride (mg/dL)

95

36.842118.9587

Non-parametric95

34.8737

15.4440

Non-parametric

Lymphocyte (Lym; ×103/μL)

95

4.71882.2748Non-parametric953.95601.2879Non-parametricCalcium (Ca; mg/dL)

95

10.3568

0.4780Parametric95

10.02210.4532

Parametric

Neutrophil (Neu; ×10 /μL)

95

4.02482.2747

Non-parametric953.9545

1.9949Non-parametric

Inorganic phosphorus (IP; mg/dL)

84

4.87141.0802

Parametric84

4.66551.0382

Parametric

Eosinophil (Eos; ×103/μL)

950.17540.2576

Non-parametric95

0.13980.1106

Non-parametricSodium (Na; mmol/L)

95

150.8526

4.3929Non-parametric95

149.4737

3.1752

Non-parametric

Basophil (Baso; ×103/μL)

95

0.00480.0071

Non-parametric95

0.00380.0057

Non-parametric

Potassium (K; mmol/L)

95

5.05370.5506

Non-parametric95

4.75050.5080Non-parametric95

0.41720.2686

Non-parametric95

0.34670.1444

Non-parametric

Chlorine (Cl; mmol/L)

95

108.8105

3.6094

Non-parametric95

109.8421

2.3307

Non-parametric

Total protein (g/dL)

95

8.02110.5562

Parametric95

7.83580.4948Non-parametric

γGT

CK

ASAT

0.6198***0.7158***ALAT–

0.6077***0.5757***0.5147***0.547***

0.5526*0.5403*0.8120***0.46370.12550.75*-0.0772-0.0222-0.0712-0.0411-0.0494
0.039
0.0125-0.05190.02980.01540.14420.03680.03040.171
0.2437-0.0084
0.135
0.118

0.4408***0.3202**
0.2347*0.09970.3273**0.2427*0.3264
0.26670.03190.0952-0.0384-0.1326

–

γGT

–

CK

–

Total bilirubin

Totalbilirubin

Urea
nitrogen0.16470.13670.06940.03020.12180.081
0.0828-0.0726-0.1115-0.1244-0.09270.16760.08350.03040.2441*0.2256*0.2255*0.13450.226
0.16680.27090.4114-0.05230.0403-0.1677-0.1416-0.1237
0.0023-0.0796-0.2727**––

Urea nitrogen

Creatinine

Glucose-0.1274
0.1116-0.0352
0.02790.05630.0836-0.09530.20190.1048-0.0373-0.09080.0514-0.2883**
0.016
0.12030.0464
1 0.2436*
0.369***

0.0777-0.046-0.0602-0.0330.2564*0.1667-0.11650.44720.1961-0.0821-0.2221-0.04390.08640.1653-0.0639-0.2354*0.13560.123
0.02510.1009Creatinine–

Glucose–Totalcholesterol

Total
Phospholipid Triglyceridecholesterol-0.1245-0.2427*-0.1213-0.1883-0.0979-0.0472
0.3996-0.1326
0.0653-0.0165-0.01960.18580.0141-0.1289-0.0535
0.0252-0.1901-0.267**-0.1804-0.01410.08990.1076–-0.1011-0.1844-0.208-0.1967-0.1138-0.01830.7423-0.38020.0998-0.037-0.0870.0035-0.1225-0.1043
0.1122-0.0124-0.0734-0.1559-0.0595
0.17210.00630.2186
0.8965***0.8169***–

Table 2a Meaning of the Correlation Coefficient (r)r=0
No relationship0< | r | ≤0.2 No or negligible relationship0.2< | r | ≤0.4 Weak relationship0.4< | r | ≤0.7 Moderate relationship0.7< | r | ≤1.0 Strong relationshipNa

Non-parametric

0.4476

ALP

IP

26.54645.3333

GLDH

ALP

40.8947

95

LDH

–

95

Parametric

ALAT

GLDH

Aspartate aminotransferase (ASAT; U/L)

0.3961

Table 2 Correlation matrix of biochemical parameters–

Statistical
distribution

Mean

BiochemistryNon-parametric

Number ofanimals

Number ofanimals

Items (Abbreviation; Unit)

5.5402

Monocyte (Mono; ×10 /μL)Ca

0.3175

Statistical
distribution

FemaleStandard
Mean
deviation

95

3

Triglyceride

3.0495

Male
Standard
deviation

Red blood cell count (RBC; ×106/μL)

3

Phospholipid

95

Statistical
distribution
Parametric

Hematology

9

LDH

Number ofanimals
95

Parametric

0.6354

3.8474

FemaleStandard
Mean
deviation
3.70535.19440.07320.14590.07950.15470.2575*0.20590.16290.1991-0.3116**-0.0908-0.3497**-0.008-0.1226
0.12210.0295-0.2222*0.3838***0.2384*0.07680.0785-0.0520.19620.2247*0.09050.4475***0.2123
–

Ca

IP

Na

-0.0479-0.2256*
0.1316-0.0497-0.0680.0944-0.0097-0.1815
0.153-0.0949-0.0882
0.066-0.1635-0.07650.1406-0.0601-0.05410.13190.28650.2149-0.0530.0262-0.292-0.1096
0.0537-0.1010.2087*0.088
0.10190.01220.065
0.02050.1193-0.0178
0.035-0.12810.00190.06180.1321
0.0221
0.11340.0321
0.06810.04550.18830.01 2 0.3557***
0.0459-0.1304-0.3484**
0.06880.1177-0.4473***
0.09360.2066*0.03280.3319**0.0798-0.2001
0.4721***
0.09290.0141 1 0.1814
0.0974-0.15160.07430.09780.0768-0.0832
0.12150.1808-0.00030.08740.17150.06290.18950.2739*0.1737-0.0387-0.0597
0.0506
0.0312-0.1171
0.0412
3 0.2407*
0.4514***–0.04290.3083**0.0837–-0.0823
–

K

K

Cl

0.13650.18560.224*
0.04930.1216
0.1539-0.117-0.22-0.0410.0303-0.09-0.1828-0.20430.1403-0.07610.00070.133
0.03910.2793**0.11830.00930.2024*-0.126-0.1502-0.0966-0.02160.16790.10650.365***
0.353***
0.1005-0.04070.277**
0.3928***0.0642
0.0569-0.07690.08080.09780.0726-0.3822-0.0046
0.2369*-0.1297-0.08910.13040.059-0.1035
0.1073-0.09480.05140.09280.2165*0.3346***0.0841-0.0832
0-0.1540.2218-0.03890.11860.04540.0284-0.0845-0.1565-0.2178*
0.4511***0.5083***0.1485
0.131

–

Cl

–

Each cell shows correlation coefficient (upper: male, lower: female). *: p< 0.05 **: p< 0.01 ***: p< 0.001

17.1886

Non-parametric

2

Total
protein
0.0562-0.0447
0.1071-0.07
0.13170.12210.3373-0.1886-0.0237
0.0986-0.0372
0.03340.0821-0.0469
0.19750.1077-0.148-0.1274
0.2785**0.2882**0.04780.1167-0.0129
0.1953-0.0298
0.4159***-0.1105
0.04050.6049***0.4039***
0.214
0.185
0.3137**0.4572***0.18590.2368*-0.0328
0.0696

There were weak to moderate negative correlations between serum
urea nitrogen and inorganic phosphorus levels in males and females.
The serum urea nitrogen level reflected protein intake. These results
indicated that the intracellular glycolytic system is promoted andphosphorus is utilized in relatively well-nourished animals with theresult that inorganic phosphorus in the blood is taken up into the cells[3].
[3] Hayashi M. Recent findings in phosphate metabolism and etiology
of hypophosphatemia. J Jpn Soc Intensive Care Med. 2009;16:5-6.
3

1

There were weak to moderate positive correlations between serum creatinine and sodium levels as well as serum creatinine andchloride levels in males and females, and serum creatinine and potassium levels in males. There were weak positive correlations
between serum creatinine and total protein or urea nitrogen levels in males and females.
Serum creatinine levels are widely known as an indicator of renal function, and serum concentrations increase when glomerular
filtration rate is reduced [2]. In both males and females, serum creatinine levels did not deviate widely from the background data ofthe test facility (3 to 6 years old, mean ± 2SD: 0.56-1.14 mg/dL for males，0.49-0.97 mg/dL for females) and were considered to
be within the range of physiological variability. These results suggest that serum creatinine levels reflect renal function even within
the range of physiological variability, and animals with high serum creatinine levels tended to have higher serum electrolyte, total
protein, and urea nitrogen levels because of relatively low glomerular filtration volume.
[2] Andrew S. Levey, M.D., Ronald D. Perrone, M.D., andNicolaos E. Madias, M.D. SERUM CREATININE AND RENAL FUNCTION.
Annual Review of Medicine 1988; 39: 466-490.

The following correlations were found with respect to serum
electrolyte levels.
Statistical significances between IP and Ca (abbr.: IP-Ca) and IP-Cl
were judged to be incidental and “non-correlated” because they wereunisexual and the degree of correlation was weak.
Correlated: Na-Ca, Ca-K, Na-K, and Na-Cl
Non-correlated: Ca-Cl, K-Cl, IP-Na, IP-K, IP-Cl, and IP-Ca
Since Na+ and Cl- are ingested as dietary salt and lost in the form of
Na+ Cl-, it was considered that a correlation was observed between
Na-Cl. It is difficult to determine the mechanism of the difference
between the correlated and non-correlated parameters other than NaCl in this study alone, and further investigation is necessary.
The others
Ca-Total protein: Because much of the calcium is bound to proteins in
the blood.
Na-Total protein, Urea nitrogen-Triglyceride, and Phospholipid-Totalcholesterol: Reflect nutritional status.
Urea nitrogen-ASAT: It was considered to be incidental sincecorrelation was weak and it was not clearly related in the scatter plot.
Correlation between ASAT, ALAT, LDH, GLDH, and CK:
Because they are enzymes that are distributed in many organs of thebody, there is a correlation among them.

Table 3 Correlation matrix of the rate of change in body weight, body weight at the end of the 4-week dosing period, hematological, and biochemical parameters
Rate of change
in body weight

Body
weight0.01490.1489Body weight

–

RBC

HGB

HCT

MCV

MCH

0.08250.06020.0816-0.0959

0.008
0.2548*0.2335*0.00930.18190.2684**0.20030.03150.12280.12520.088
0.1354-0.08460.18160.144
0.1013Retiulocyte Reticulocyte
ratio
count
-0.2964**0.17180.18480.01940.05310.08640.09230.12190.0074-0.05240.0009-0.0826
MCHC

Total
5
bilirubin
Rate of change -0.3013** -0.3106**-0.0144-0.1395
0.2177*0.18360.0878-0.1254
in body weight 0.2093*
0.19290.01770.17930.07810.0082-0.1594
0.1249-0.3299**-0.0617-0.238-0.004-0.0449
0.0758-0.2874**
0.0416
Body weight
0.13280.125-0.0902
0.0360-0.2679**
0.0566-0.1593-0.0137
Each cell shows correlation coefficient (upper: male, lower: female). *: p< 0.05 **: p< 0.01 ***: p< 0.001
ASAT

ALAT

LDH

GLDH

ALP

γGT

CK

PLT

PT

APTT

WBC

Lym

Neu

Eos

Baso

Mono

-0.14020.0029-0.2223-0.0683-0.0353-0.2129*0.1317-0.08890.0349-0.1285-0.1306-0.05130.2512*-0.073-0.1243
0.15540.3901***
0.111-0.03620.14620.001-0.1972-0.1998
0.118

0.2102*-0.0184
0.16490.0903-0.0994
0.06030.16580.05140.2157*0.1002
0.04
0.14

Ca

IP

Na

K

Cl

-0.0924
0.07240.2534*0.04420.2953**0.15320.1536-0.1521-0.0892
0.01210.05590.2312*-0.2548*-0.0353
0.14270.07030.0288-0.1199-0.07120.1121Urea
Creatinine
nitrogen-0.142-0.1021-0.0433 4 -0.1087-0.1674 0.5287***-0.05540.2331*

Glucose0.1805-0.0329-0.2509*
0.0772

Total
Phospholipid Triglyceridecholesterol
0.112
0.0719-0.1104
0.08620.13520.2318*-0.2377*-0.2256-0.1804
0.1281
0.061-0.0323

Total
protein-0.2158*-0.06820.3544***0.02984There were moderate positive correlations in males and weak positive correlations in females between body weight andserum creatinine levels. Creatinine is the final metabolite of creatine phosphate, and in humans, about 94% of thecreatine in the body is distributed in muscles, suggesting that it may be a biomarker for the progression of amyotrophic
lateral sclerosis [4]. These results suggest that the serum creatinine level was also proportional to skeletal muscle mass incynomolgus monkeys and may be a biomarker of skeletal muscle mass. The degree of correlation was stronger in males
than in females, possibly because males had more skeletal muscle mass than females.
[4] Mitsumoto H and Saito T. A prognostic biomarker in amyotrophic lateral sclerosis. Clinical Neurology 2018;58:729-736.

5

There were weak negative correlations in males between the rate of change in body weight and ASAT or ALAT.
We found that animals with a rate of change in body weight of less than 0% and ASAT or ALAT of 100 U/L or more hadlost weight in spite of their feeding status (in-house data), suggesting that catabolism of skeletal muscle proteins is
promoted to compensate for the deficit energy [5] and ASAT and ALAT distributed in the skeletal muscle leaked into theblood. The absence of a similar trend in females may be due to their originally low skeletal muscle mass.
[5] Ishibashi I. Enteral Nutrition and Optimal Dosage in the Early Invasive Period. The Japanese Journal of SURGICALMETABOLISM and NUTRITION 2016; 50-2: 105-109.
●This presentation clarifies the degree of the correlation between each test item in cynomolgus monkeys. The correlation between the basic test items will serve as a reference whenabnormal values are found during the measurement.
●Males with larger body weight have higher basal creatinine levels in their blood, which should be kept in mind when assessing toxicity.
●In this presentation, since the population of animals was a control group, it is necessary to examine the relevance of each test item after administration of compounds such as
nephrotoxicants and hepatotoxicants in order to better understand the degree of the correlation between each test item.