Evidence-Based Complementary and Alternative Medicine

Volume 2012 (2012), Article ID 670362, 21 pages

doi:10.1155/2012/670362

Research Article

Mechanism of Earthquake Simulation as a Prenatal Stressor Retarding Rat Offspring Development and Chinese Medicine Correcting the Retardation: Hormones and Gene-Expression Alteration

X. G. Zhang,¹ H. Zhang,¹ R. Tan,² J. C. Peng,³ X. L. Liang,¹ Q. Liu,¹ M. Q. Wang,⁴ and X. P. Yu⁵

¹The School of Nursing, Chengdu University of T.C.M., Chengdu 610075, China

²School of Biology and Engineering, Southwest Jiaotong University, Chengdu 610031, China

³Earthquake Emergency Security Center, Sichuan Provincial Seismological Bureau, Chengdu 610041, China

⁴Molecular Laboratory of T.C.M., Chengdu University of T.C.M., Chengdu 610075, China

⁵School of Humanity and Information Management, Chengdu Medical University, Chengdu 610075, China

Received 26 August 2012; Revised 3 October 2012; Accepted 5 October 2012

Academic Editor: Jang-Hern Lee

Copyright © 2012 X. G. Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

We aimed to investigate the mechanism of shaking as a prenatal stressor impacting the development of the offspring and Chinese medicines correcting the alterations. Pregnant rats were randomized into earthquake simulation group (ESG), herbal group (HG) which received herbal supplements in feed after shaking, and control group (CG). Findings revealed body weight and open field test (OFT) score of ESG offspring were statistically inferior to the CG and HG offspring. The corticosterone levels of ESG were higher than those of CG but not than HG. The dopamine level of ESG was slightly lower than that of the CG and of HG was higher than that of ESG. The 5-HT of ESG was higher than CG and HG. The growth hormone level of the ESG was significantly lower than ESG but not than CG. Gene expression profile showed 81 genes upregulated and 39 genes downregulated in ESG versus CG, and 60 genes upregulated and 28 genes downregulated in ESG versus HG. Eighty-four genes were found differentially expressed in ESG versus CG comparison and were normalized in ESG versus HG. We conclude that maternal shaking negatively affected physical and nervous system development, with specific alterations in neurohormones and gene expression. Chinese herbal medicine reduced these negative outcomes.

1. Introduction

Maternal effects have been demonstrated as an essential factor for offspring development in many species. Because of the long period of perinatal mother-infant interaction in mammals, the growth and development and variations of offspring are very likely to be influenced by maternal impacts, leaving long-term consequences for both psychological and physiological health [1]. Recent human studies have shown that long-lasting and a wide variety of prenatal stressors, from anxiety and partner relationship problems to natural disasters, increase the risk for a diverse range of adverse neurodevelopmental outcomes in the child, including impaired cognitive development and behavioral problems [2, 3]. Animal experiments have convincingly demonstrated that prenatal maternal stress affects pregnancy outcome and results in early programming of brain functions with permanent changes in neuroendocrine regulation, gene expression, and behavior in offspring [4]. Prenatal restraint stress in rats is a common experimental model of early stress known to have long-term behavioral and neurobiological consequences [5, 6]. PS modifies the plastic responses of the adult brain, including the circuitry of the hippocampus-hypothalamus- pituitary-adrenalaxis (HHPA), that participate in the neuroendocrine control of feeding and metabolism in adult life [7].

As a typical prenatal stress, shaking can significantly impact the psychological and intellectual development of fetus and birth outcomes [8] in human. Naturally, earthquake is a fierce shaking. Tan et al. [9] reported that rates of birth defects after an earthquake were significantly higher than those before earthquake, whose spectrum was dramatically altered after earthquake, with the markedly increased occurrences of ear malformations; meanwhile the ratio of preterm birth after earthquake was significant increased than that of before earthquake. Oyarzo et al. [10] reported that women exposed to the February 27th 2010 Chilean earthquake during her first trimester delivered smaller newborns and they were more likely diagnosed with early preterm delivery, preterm delivery, and PROM but were less likely diagnosed with intrauterine growth retardation and late delivery compared to those exposed at third trimester, indicating disasters such as earthquakes are associated to adverse perinatal outcomes that impact negatively the entire maternal-neonatal healthcare system. Like the other alterations induced by PS in behavior those in learning and their direction appears to be dependent on the intensity, duration, and timing of the maternal stress [11].

In Chinese medicine, PS from shaking or an analog of earthquake is considered as a factor which impairs kidney Qi (shen qi) [12]. As kidney is the root of earlier heaven (the congenital constitution), it governs reproduction and development and holds oriffice of labor, whence agility and emanates. Jin Kui Shen Qi Wan (JKSQW) is a typical herbal formula supplementing kidney Qi, which recovers the physiological functions of kidney [13].

The current study involves shaking as a prenatal stressor. A first goal was to establish that earthquake simulation led to significant delays in development. A second goal was to examine whether Chinese traditional medicine could be used to address these negative effects. Based on the above information, we hypothesized parental kidney is injured from PS derived from earthquake simulation on rats, traits are handed down to offspring, showing development retardation; JKSQW could recover the dysfunctions of kidney whose underlying mechanism could involve development, hormones and gene expression alterations.

2. Materials and Methods

2.1. Grouping

Forty-five Sprague-Dawley (SD) female rats (230 g~270 g) and 45 male rats (225 g~261 g) were involved in this research. The rats were housed in a room with a temperature of 22°C, 12 hour light/dark cycle and fed with food and water ad libitum. After a week of adaption housing, the female rats were mated with the male rats. Pregnancy was confirmed by vaginal plug test. Then the 34 pregnant rats were randomized into three groups, control group (CG) (), earthquake simulation with conventional chow group (ESG) (), and earthquake plus herbal group (HG) (), and they were housed under pregnant rat cages until the delivery. With this procedure, all the groups were transferred with equivalent stress during pregnancy. There was no statistical difference of gestation time detected or body weight of the first day of gestation (CG: , ESG: , and HG: , ANOVA test, (g)) in the three groups. After delivery, all the litters of the three groups were housed with their mothers until the 25th day after birth.

2.2. Earthquake Simulation

The ESG cages housing pregnant rats were manually shaken up and down 3 times to simulate an initial earthquake and then were shaken for 50 timesover the next 15 minutes to modulate an aftershock [14]. The shaking was performed twice a day until delivery. Severity of the shake was measured with a seism velometer (DX-6Y2, Cheng Du Mei Huan Tech. Co. Ltd.), showing 9.6~10.5 of seismic intensity, 950 m1050 mg of vertical peak ground accelerations (PGA), which was similar to the PGA (1080 mg) of Wenchuan earthquake, May 12, 2008, China.

2.3. Chinese Herbal Formula Feed

The feed of HG rats was supplemented with herbal medicine until delivery, which consisted of (Radix Rehmanniae Preparata (Shu Di Huang), Fructus Corni Officinalis (Shan Zhu Yu), Cortex Moutan Radicis (Mu Dan Pi), Rhizoma Dioscoreae Oppositae (Shan Yao), Sclerotium Poriae Cocos (Fu Ling), Rhizoma Alismatis Orientalis (Ze Xie), Radix Aconiti Lateralis Preparata (Zhi Fu Zi), and Cortex Cinnamomi Cassiae (Rou Gui)) bought from Tong Ren Tang Technologies, Co., Ltd. The pill of JKSQW was grinded and added to the conventional feed 0.5~0.6 g/d.

2.4. Body Weight Measurement

Body weight (g) was measured at the 1st (day 0), 5th (day 5), 10th (day 10), 15th (day 15), 20th (day 20), and 25th (day 25) days after delivery in order to evaluate the body development of the offspring.

2.5. Open Field Test (OFT)

A square board (90 cm × 90 cm) painted with yellow and white squares (15 cm × 15 cm). The offspring of 25 days old was placed in the center of the board. We counted how many squares the offspring had crawled across in two minutes. One score was given only when the four paws of an offspring were in one square.

2.6. Hormone Assay

Thirty offspring were randomly selected from the groups, ten for each. Blood sample was taken from arteria femoralis. ELISA (R&D Systems China Co., Ltd.) was employed to determine the serum level of corticosterone (DZE 30590), dopamine (DZE 30238), 5-HT (DZE 30326), and growth hormone (DZE 30549).

2.7. Gene Expression Profile Chip Experiments

2.7.1. RNA Extraction and Purification

Total RNA was extracted using TRIZOL Reagent (Cat no. 15596-018, technologies, Carlsbad, CA, US) following the manufacturer’s instructions and checked for a RIN number to inspect RNA integration by an Agilent Bioanalyzer 2100 (Agilent technologies, Santa Clara, CA, US). Qualified total RNA was further purified by RNeasy mini kit (Cat no. 74106, QIAGEN, GmBH, Germany) and RNeasy micro kit (Cat no. 74004, QIAGEN, GmBH, Germany) and RNase-Free DNase Set (Cat no. 79254, QIAGEN, GmBH, Germany) (Table 1).

Table 1: QC of RNA extraction and slides experiment (A sample is qualified only when 2100 RIN ≥ 7.0 and 28S/18S ≥ 0.7).

Group
QC of RNA

QC of slides

Con. (g/μL)
Vol. (μL)
Total (μg)
A260/A280
2100 Result
Result
CV (%)*
Detection rate (%)

RIN
28S/18S

ESG
0.168
50
8.41
1.88
9.4
1.7
Qualified
3.91
69.50

1.366
30
40.98
1.93
9.5
1.8
Qualified
4.85
62.96

0.246
50
12.29
1.90
9.4
1.7
Qualified
6.70
72.13

HG
0.134
50
6.69
1.81
9.4
1.8
Qualified
4.76
70.40

0.138
50
6.92
1.82
9.4
1.8
Qualified
4.90
72.30

0.372
50
18.58
1.86
9.5
1.6
Qualified
4.89
69.43

CG
0.185
50
9.27
1.91
9.4
1.7
Qualified
6.33
61.09

0.595
50
29.75
1.93
9.4
1.7
Qualified
5.70
70.68

0.355
25
8.87
1.85
9.3
1.6
Qualified
4.39
65.52

*CV = SD/Mean × 100%.

2.7.2. RNA Amplification and Labeling

Total RNA was amplified and labeled by Low Input Quick Amp Labeling Kit, One-Color (Cat no. 5190-2305, Agilent technologies, Santa Clara, CA, US), following the manufacturer’s instructions. Labeled cRNA were purified by RNeasy mini kit (Cat no. 74106, QIAGEN, GmBH, Germany).

2.7.3. Hybridization

Each slide was hybridized with 1.65 μg Cy3-labeled cRNA using Gene Expression Hybridization Kit (Cat no. 5188-5242, Agilent technologies, Santa Clara, CA, US) in Hybridization Oven (Cat no. G2545A, Agilent technologies, Santa Clara, CA, US), according to the manufacturer’s instructions. After 17 hours hybridization, slides were washed in staining dishes (Cat no. 121, Thermo Shandon, Waltham, MA, US) with Gene Expression Wash Buffer Kit (Cat no. 5188-5327, Agilent technologies, Santa Clara, CA, US), following the manufacturer’s instructions.

2.7.4. Data Acquisition

Slides were scanned by Agilent Microarray Scanner (Cat no. G2565CA, Agilent technologies, Santa Clara, CA, US) with default settings: dye channel: Green, Scan , PMT 100%, 10%, 16 bit. Feature Extraction software 10.7 (Agilent technologies, Santa Clara, CA, US) Raw data were normalized by Quantile algorithm, Gene Spring Software 11.0 (Agilent technologies, Santa Clara, CA, US) (Table 1).

2.7.5. Real-Time PCR

Primers of the four genes were designed with Primer Express 2.0 (Oebiotec, Shanghai, China) (Table 2). Reverse transcription was performed on PrimerScript RT reagent Kit (TaKaRa, DRR037A, Takara Biotechnology (Dalian) Co., Ltd. China). Total RNA (0.5 μg) was denatured at room temperatrue then mixed with the reagent in a final volume of 10 μL containing 50 μM oligo dT, 100 μM random primer, 0.5 mM dNTP and the manufacturer’s buffer and Enzyme Mix. The RT reaction was conducted for 15 min at 37°C, and 85°C for 5 s in ABI 9700. First-strand cDNA product was diluted in 100 μL distilled water in preparation for real-time PCR. qPCR was performed using SuperReal PreMix (SYBR Green) kit (TIANGEN, FP204, Tiangen Biotech (Beijing) Co., Ltd. Beijing, China). Briefly, 1 μL of diluted cDNA product was used for 40-cycle three-step PCR in a Roche HOLD CYCLE LightCycler 480 II.

Table 2: Primers and product length of the four targeted genes.

No.
Gene symbol
Forward primer
Reverse primer
Product

length

1
*ACTB
GCGTCCACCCGCGAGTACAA
ACATGCCGGAGCCGTTGTCG
118

2
Irf7
TGGCAGATGGAAGCTACC
GGCTATACAGGAACACGC
154

3
Ninj2
CCACCACCTTGGTCTTCATA
AGGCTGAAGTGGCTTTAG
152

4
Isca1
CCCGTTGCATCTTTACCAC
GTCTAAGCAAACCGCATGAA
151

5
Plxnc1
TGACCACTGCCACTTGAT
CTGAAGAGTTTCTCAAGCAC
159

*refers to internal control gene.

2.8. Statistical Analysis

The body development, behavioral test, and hormone level data were analyzed using a Statistical Package for the Social Sciences (SPSS) version 19.0. ANOVA for Repeated Measurement with Greenhouse-Geisser Adjustment was performed to analyze group differences in body weight. A nonparametric Mann-Whitney test was performed to analyze group differences on the OFT. Student’s -test was performed to analyze group differences in corticosterone, dopamine, 5-HT, and growth hormone. Alpha was set to.05 for all analyses.

3. Results

3.1. Body Development and Behavior Test

ANOVA for Repeated Measurement with Greenhouse-Geisser Adjustment (Mauchly’s , Approx. , , , ) showed a statistically significant difference of the body weight of the 6 observation time spots of offspring among CG, ESG, and HG offspring (body weight: , mean , , ; body , mean , , ). Generally, HG offspring was heavier than CG, which is heavier than ESG (Figure 1).

Figure 1: Mean plot of body weight. According to the ANOVA for Repeated Measurement, the body weight of ESG offspring were statistically all inferior to the CG offspring despite in Day 10 (). The body weight HG offspring were statistically superior to the ESG offspring despite in Day 5 (); The body weight HG in Day 15, Day 20 and Day 25 were statistically superior to the CG ().

A Mann-Whitney test showed significant difference between the three groups on the OFT (Mann-Whitney , Wilcoxon , , ) (Figure 2): the OFT scores of HG and CG were both significantly higher than those observed in the ESG.

Figure 2: Box plot of OFT in the comparison between CG, ESG, and HG. ESG showed less scores than CG () and HG ().

3.2. Hormone Levels

The corticosterone levels of CG was statistically lower than ESG and slightly than HG (Figure 3(a)). The dopamine level of ESG was slightly lower than the CG and of HG was significantly higher than the ESG (Figure 3(b)). The 5-HT of ESG showed a highest level and the CG lowest (Figure 3(c)). The growth hormone level of the HG was statistically higher than the CG and ESG (Figure 3(d)).

(a)

(b)

(c)

(d)

Figure 3: ELISA outcomes of corticosterone, dopamine, 5-HT, and growth hormone. (a) ANOVA test for the corticosterone showed in CG versus ESG, in CG versus HG, and in ESG versus HG. (b) ANOVA test for the dopamine showed in CG versus ESG, in CG versus HG, and in ESG versus HG. (c) ANOVA test for 5-HT showed in CG versus ESG, in CG versus HG, and in ESG versus HG. (d) ANOVA test for the growth hormone showed in CG versus ESG, in CG versus HG, and in ESG versus HG.

3.3. Gene Expression Profile

3.3.1. ESG versus CG

Gene expression profile showed 81 genes upregulated and 39 genes downregulated () in ESG versus CG comparison (Table 3 (see Supporting Information 1), Figure 4), among which 14 GO annotations were obtained including, ligase activity, regulation of metabolic process, positive regulation of metabolic process, cellular component assembly, membrane bounded organelle, biosynthetic process, cellular component biogenesis, and cellular response to stimulus. (Table 4 (Supporting Information 2)), and among which 12 KEGG pathways were annotated, including oocyte meiosis, vascular smooth muscle contraction, RIG-I-like receptor signaling pathway, long-term potentiation, ubiquitin mediated proteolysis, and long-term depression (Table 5).

Table 3: Differentially expressed genes in ESG versus CG, among which 39 genes were upregulated and 81 genes downregulated.

Gene ID
values
Fold change
Gene symbol
Regulation

63847
0.007006
0.096204
Fxyd6
Downregulated

498145
0.003225
0.17368
LOC498145
Downregulated

316628
0.004414
0.274831
Asb1
Downregulated

360547
0.005836
0.320844
Sat2
Downregulated

301245
0.007067
0.331729
Yipf3
Downregulated

293023
0.009502
0.335662
Klhl25
Downregulated

288240
0.002174
0.344925
Hlcs
Downregulated

293180
0.007695
0.352823
Micalcl
Downregulated

316426
0.003961
0.363248
Spats2l
Downregulated

293624
0.008043
0.364195
Irf7
Downregulated

683788
0.007907
0.382175
LOC683788
Downregulated

293156
0.009012
0.413953
Lrtomt
Downregulated

25646
0.004102
0.429726
Otx1
Downregulated

290232
0.009311
0.430944
Tinf2
Downregulated

498353
0.002896
0.440115
Scfd2
Downregulated

362873
0.006203
0.440433
Plxnc1
Downregulated

309415
0.009479
0.458925
Fam189a2
Downregulated

113894
0.007725
0.463149
Sqstm1
Downregulated

303538
0.003261
0.465171
Dhx58
Downregulated

406196
0.001118
0.467157
Hcr
Downregulated

313917
0.005676
0.482298
Abhd1
Downregulated

292811
0.009904
0.48439
Ccdc123
Downregulated

290985
0.007918
0.491881
Isca1
Downregulated

405152
0.008771
0.516648
Olr1192
Downregulated

171355
0.005274
0.519609
Pou4f2
Downregulated

362943
0.000172
0.526926
Adck5
Downregulated

309161
0.001612
0.543788
Ccdc85b
Downregulated

361327
0.003693
0.596748
Prr16
Downregulated

24640
0.008865
0.602226
Pfkfb2
Downregulated

619573
0.006811
0.603084
Fam104a
Downregulated

116725
0.007447
0.653258
Ube2n
Downregulated

304342
0.005141
0.662423
Zscan21
Downregulated

192252
0.009069
0.671766
Dctpp1
Downregulated

114205
0.00295
0.677239
Crcp
Downregulated

311430
0.007769
0.689602
Mavs
Downregulated

287840
0.003671
0.716317
Fam100b
Downregulated

297109
0.006823
0.764608
MGC95152
Downregulated

295037
0.000491
0.788096
Mgst2
Downregulated

100360990
0.007759
0.815928
LOC100360990
Downregulated

501083
0.00564
1.179002
Pdcd6ip
Upregulated

299195
0.000513
1.189394
Coq6
Upregulated

81716
0.007768
1.20684
Ggcx
Upregulated

315023
0.008157
1.265746
Slc25a32
Upregulated

296753
0.009238
1.284846
Srpk2
Upregulated

299147
0.005455
1.304917
Ppp2r5e
Upregulated

361932
0.009554
1.307515
RGD1561393
Upregulated

288259
0.009614
1.31293
Gart
Upregulated

289522
0.002341
1.325268
Cox18
Upregulated

50688
0.002132
1.334825
Cacnb1
Upregulated

363171
0.000593
1.337206
Tmem42
Upregulated

114215
0.005997
1.352079
Insl3
Upregulated

315771
0.008317
1.369011
Herc1
Upregulated

360389
0.009442
1.375028
Zfp422
Upregulated

305923
0.008185
1.393988
Zdhhc20
Upregulated

24803
0.005163
1.399617
Vamp2
Upregulated

363210
0.001697
1.411325
Phf3
Upregulated

50561
0.001722
1.425023
Resp18
Upregulated

362367
0.005441
1.43527
Znrf2
Upregulated

170841
0.009557
1.458549
Mutyh
Upregulated

81678
0.003588
1.464706
Itpr2
Upregulated

502886
0.009395
1.466283
Foxj2
Upregulated

360868
0.009274
1.471063
Sft2d2
Upregulated

313757
0.005281
1.485264
RGD1565591
Upregulated

361109
0.000669
1.486251
Dcp1a
Upregulated

192210
0.008713
1.487999
Dnajc21
Upregulated

25262
0.008127
1.49478
Itpr1
Upregulated

311112
0.00906
1.533447
Fastkd1
Upregulated

64086
0.004012
1.55121
Csnk1g1
Upregulated

366693
0.007515
1.567923
Rbm25
Upregulated

690961
0.006894
1.577038
Cog2
Upregulated

292148
0.004257
1.589999
Eif3a
Upregulated

691918
0.002531
1.596744
LOC691918
Upregulated

362317
0.001503
1.599092
Krit1
Upregulated

54323
0.001154
1.610286
Arc
Upregulated

304813
0.005676
1.614358
Ppp1r12b
Upregulated

58983
0.00216
1.617294
Rabggta
Upregulated

361944
0.004739
1.617335
Elf2
Upregulated

314862
0.000215
1.618023
Dyrk2
Upregulated

29642
0.003006
1.62079
Slc38a2
Upregulated

291409
0.00357
1.622726
Zfp236
Upregulated

246282
0.001061
1.623318
Zfp91
Upregulated

362132
0.00226
1.626565
Epc2
Upregulated

303963
0.002236
1.631518
Dzip3
Upregulated

116670
0.006773
1.634179
Ppp1r12a
Upregulated

302670
0.004529
1.63737
Zrsr2
Upregulated

360993
0.006601
1.637448
Smek2
Upregulated

59319
0.001208
1.6438
Nyw1
Upregulated

287249
0.009286
1.659325
Cnot6
Upregulated

362132
0.007917
1.663529
Epc2
Upregulated

303511
0.004368
1.665157
Ikzf3
Upregulated

363210
0.008478
1.665263
Phf3
Upregulated

362096
0.00268
1.668933
Setx
Upregulated

316583
0.001117
1.700923
B3gnt7
Upregulated

362817
0.008175
1.701909
Cdk2
Upregulated

304157
0.009185
1.708222
Nrip1
Upregulated

314169
0.009008
1.729076
Fam179b
Upregulated

303919
0.007784
1.731828
Lrrc58
Upregulated

309523
0.005447
1.734164
Kif20b
Upregulated

291773
0.003136
1.741424
RGD1562997
Upregulated

314423
0.003545
1.743689
Bcl11b
Upregulated

362622
0.007916
1.756522
Ccdc21
Upregulated

497198
0.005781
1.770803
Impact
Upregulated

315804
0.00029
1.773739
Rfx7
Upregulated

363287
0.002339
1.775948
Hdac4
Upregulated

361688
0.00606
1.778637
Suv420h1
Upregulated

363555
0.002239
1.787221
Wfikkn1
Upregulated

304809
0.001337
1.791911
Kdm5b
Upregulated

498803
0.003675
1.797804
Otud1
Upregulated

64624
0.005484
1.803225
Cul5
Upregulated

304817
0.00381
1.807047
Ipo9
Upregulated

54311
0.008729
1.82334
Timm17a
Upregulated

25486
0.008651
1.8782
Myo9b
Upregulated

302612
0.006615
1.978189
Tspyl2
Upregulated

293765
0.003013
2.076238
Olr327
Upregulated

171347
0.007854
2.324322
Mat2a
Upregulated

685074
0.008629
2.417108
LOC685074
Upregulated

498211
0.007458
2.449546
RGD1560523
Upregulated

690043
0.004624
2.470614
Rnf168
Upregulated

171347
0.00179
2.47901
Mat2a
Upregulated

363083
0.007379
2.521284
Fbxl22
Upregulated

Table 4: Significant GO annotation of the 120 differentially expressed genes and the genes involved ().

GO Id
Name
Symbol
Hits
Total
Percent
Enrichment test value

GO: 0016874
Ligase activity
Ube2n, Hlcs

Gart, Herc1,
7
308
2.27%
0.0083

Cul5, Rnf168, Ggcx

GO: 0019222
Regulation of metabolic process
Sqstm1, Insl3, Ube2n, Pou4f2,

Otx1, Cnot6, Tinf2,

RGD1562997, Irf7,

Tspyl2, Nrip1,
28
2415
1.16%
0.0089

Zscan21, Jarid1b, Bcl11b, Dyrk2,

Mll1, Rfx7, Zfp422, Smek2, Suv420h1, Elf2, Cdk2, Hdac4, Impact,

Foxj2, Rasd1, Rnf168, Pfn2

GO: 0009893
Positive regulation of metabolic process
Sqstm1, Insl3, Ube2n,

Pou4f2, Tinf2,

Nrip1, Zscan21, Bcl11b
13
846
1.54%
0.0098

Dyrk2, Mll1, Cdk2

Hdac4, Rnf168

GO: 0022607
Cellular component assembly
Sqstm1, Xtp3tpa

Vamp2, Cox18, Tinf2, Eif3s10, RGD1562997
12
786
1.53%
0.0135

Srpk2, Mll1, Enth, Pfn2

GO: 0043227
Membrane-bounded organelle
Sqstm1, Crcp, Ube2n, Mutyh, Pou4f2, Vamp2

Itpr1, Otx1, Cnot6

Hlcs, Cox18, Tinf2

Isca1, Eif3s10

RGD1562997

Irf7, Srpk2, Ikzf3

Ppp2r5e, Yipf3

Tspyl2, Zrsr2, Nrip1

Zscan21, Kif20b

Visa, RGD1565591
55
5982
0.92%
0.025

Bcl11b, Dyrk2

Slc25a32, Mll1, Enth

B3gnt7, Zfp422, Setx

Suv420h1, Elf2, Phf3

Cdk2, Adck5, Hdac4 Hcr, LOC498145

Pdcd6ip, Foxj2, Rasd1, Resp18, Cul5

Cacnb1,Timm17a,

Arc, Rnf168, Cog2,

Itpr2, Ggcx

GO: 0014854
Response to inactivity
Hdac4
1
3
33.33%
0.0288

GO: 0009058
Biosynthetic process
Crcp, Insl3,Ube2n

Mat2a, Pou4f2, Otx1

Cnot6, Gart, Tinf2

Isca1, RGD1562997

Eif3s10, Irf7, Coq6

Tspyl2, Nrip1, Mll1
34
3379
1.01%
0.0291

Zscan21, Jarid1b

Bcl11b, Dyrk2, Rfx7

B3gnt7, Zfp422, Elf2

Suv420h1, Cdk2, Phf3

Hdac4, Impact, Foxj2

Rabggta, Rasd1

GO: 0044085
Cellular component biogenesis
Sqstm1, Xtp3tpa,

Vamp2, Cox18, Tinf2

RGD1562997, Eif3s10
12
883
1.36%
0.0299

Srpk2, Mll1, Enth, Pfn2

GO: 0014874
Response to stimulus involved in regulation of muscle adaptation
Hdac4
1
4
25.00%
0.0359

GO: 0043233
Organelle lumen
Sqstm1, Mutyh, Itpr1

Tinf2, RGD1562997

Srpk2, Tspyl2, Zrsr2
16
1360
1.18%
0.0416

Nrip1, Kif20b, Mll1

Zfp422, Setx, Cdk2

Hdac4, Resp18

GO: 0051716
Cellular response to stimulus
Ube2n, Mutyh, Dyrk2

Mll1, Setx, Cdk2,
8
528
1.52%
0.0422

Pdcd6ip, Rnf168

GO: 0016740
Transferase activity
Crcp, Mat2a, Pfkfb2

Gart, Mgst2, Srpk2

RGD1304822, Dyrk2
18
1612
1.12%
0.0483

Fastkd1, Mll1, B3gnt7

Suv420h1, Cdk2, Fgfr1l, RGD1560523

Rabggta, Csnk1g1

GO: 0031974
Membrane enclosed lumen
Sqstm1, Mutyh, Itpr1

Tinf2, RGD1562997

Srpk2, Tspyl2, Zrsr2

Nrip1, Kif20b, Mll1
16
1392
1.15%
0.0495

Zfp422, Setx, Cdk2,

Hdac4, Resp18

GO: 0031077
Postembryonic camera-type eye development
Bcl11b
1
6
16.67%
0.0499

Table 5: KEGG Pathway annotation of the 120 differentially expressed genes (, ) ( refers downregulation, refers upregulation).

Name
Symbol
Total
Percent
Enrichment

test value
value

Oocyte meiosis
Itpr1↑ Ppp2r5e↑
116
0.0345
0.0008
0.0048

Cdk2↑

Vascular smooth muscle contraction
Ppp1r12a↑
128
0.0313
0.0011
0.0048

Itpr1↑

Ppp1r12b↑

RIG-I-like receptor signaling pathway
Irf7↓ Dhx58↓
64
0.0469
0.0016
0.0048

Mavs↓

Long-term potentiation
Ppp1r12a↑ Itpr1↑
72
0.0417
0.0022
0.0049

Itpr2↑

Ubiquitin mediated proteolysis
Ube2n↓ Herc1↑
132
0.0227
0.0111
0.0176

Cul5↑

Cytosolic DNA-sensing pathway
Irf7↓ Mavs↓
49
0.0408
0.0131
0.0176

Biotin metabolism
Hlcs↓
3
0.3333
0.0135
0.0176

RNA degradation
Cnot6↑ Dcp1a↑
61
0.0328
0.0196
0.0223

Long-term depression
Itpr1↑ Itpr2↑
69
0.029
0.0245
0.0245

Ubiquinone and other terpenoid-quinone biosynthesis
Coq6↑
7
0.1429
0.0269
0.0245

Phosphatidylinositol signaling system
Itpr2↑ Itpr1↑
77
0.026
0.0299
0.0247

Gap junction
Itpr2↑ Itpr1↑
87
0.023
0.0371
0.0281

GnRH signaling pathway
Itpr1↑ Itpr2↑
99
0.0202
0.0467
0.0326

Figure 4: Heat map of the differently expressed genes. R2_1_NS, R2_2_NS, and R2_3_NS refer to ESG and R4_1_NS, R4_2_NS, R4_3_NS to CG.

3.3.2. ESG versus HG

Gene expression profile showed 60 genes upregulated and 28 genes downregulated () in ESG versus CG (Table 6 (Supporting Information 3), Figure 5), among which five GO annotations were obtained including protein complex localization, cellular component assembly, cellular component biogenesis, anatomical structure formation, and organelle lumen (Table 7), and among which 5 KEGG pathways were annotated, including cell cycle, Jak-STAT signaling pathway, Type II diabetes mellitus, One carbon pool by folate, and insulin signaling pathway (Table 8).

Table 6: Differentially expressed genes in ESG versus HG, among which 60 genes were upregulated and 28 genes downregulated.

Gene ID
values
Fold change
Symbol
Remark

287881
0.006042
0.220799
Dysfip1
Downregulated

25405
0.004824
0.344631
Ccng1
Downregulated

24237
0.003207
0.40894
C6
Downregulated

313219
0.003811
0.410283
Zfp189
Downregulated

287343
0.008194
0.499299
Olr1454
Downregulated

293156
0.008272
0.508908
Lrtomt
Downregulated

405143
0.009972
0.5345
Olr803
Downregulated

116724
0.000512
0.546672
Epb4.1l3
Downregulated

313917
0.00383
0.578297
Abhd1
Downregulated

83681
0.004251
0.581219
Cish
Downregulated

301346
0.007628
0.609505
Sema4c
Downregulated

315346
0.003519
0.619843
Itga5
Downregulated

56825
0.009009
0.625224
Cym
Downregulated

690810
0.007066
0.637375
Adat1
Downregulated

313982
0.009162
0.653927
RGD1561890
Downregulated

363285
0.004745
0.660307
Scly
Downregulated

316090
0.003533
0.683347
Fam198a
Downregulated

24513
0.003494
0.687818
Ivd
Downregulated

303384
0.007792
0.703077
Mmp28
Downregulated

246074
0.009445
0.718762
Scd1
Downregulated

500011
0.008188
0.726294
RGD1563091
Downregulated

362943
0.004839
0.735253
Adck5
Downregulated

500420
0.008119
0.744282
LOC500420
Downregulated

399489
0.006413
0.763541
E2f1
Downregulated

311716
0.004912
0.77549
Col20a1
Downregulated

113894
0.007846
0.78406
Sqstm1
Downregulated

266609
0.005228
0.798742
Bles03
Downregulated

246766
0.00514
0.821038
Ggta1
Downregulated

288518
0.008613
1.136098
RGD1311660
Upregulated

499430
0.008063
1.148146
Lrrc20
Upregulated

317399
0.000156
1.156541
Ddx21
Upregulated

306182
0.00808
1.160148
Ipo5
Upregulated

301038
0.00729
1.178184
Ubp1
Upregulated

310806
0.006399
1.178549
Cdc14a
Upregulated

287954
0.003091
1.181263
Dgcr8
Upregulated

260321
0.008611
1.181875
Fkbp4
Upregulated

305828
0.006609
1.182203
Socs4
Upregulated

64161
0.005932
1.183779
Pi4ka
Upregulated

290679
0.009165
1.186593
Ints10
Upregulated

298429
0.006198
1.188777
Rad54l
Upregulated

474154
0.005077
1.190852
Rbm4b
Upregulated

288717
0.006268
1.196619
Srrd
Upregulated

296312
0.004568
1.197256
RGD1311066
Upregulated

312640
0.005739
1.198178
Tmem111
Upregulated

83624
0.009311
1.200882
Ppig
Upregulated

288778
0.001749
1.22319
Pa2g4
Upregulated

362851
0.004166
1.224723
Cd320
Upregulated

308404
0.006579
1.227818
Irf2bp1
Upregulated

363760
0.005704
1.237527
Arl6
Upregulated

296076
0.007529
1.238081
Srp14
Upregulated

291787
6.57E–05
1.242186
Rbbp8
Upregulated

500727
0.00344
1.246021
Cdca4
Upregulated

306587
0.008906
1.255527
Tcta
Upregulated

29541
0.000917
1.259108
Nthl1
Upregulated

360855
0.004605
1.26267
Smg7
Upregulated

362317
0.008649
1.284527
Krit1
Upregulated

313757
0.004801
1.294664
RGD1565591
Upregulated

499370
0.009663
1.326682
Itprip
Upregulated

288259
0.009472
1.335197
Gart
Upregulated

29704
0.002213
1.349013
Pacsin1
Upregulated

84472
0.006393
1.366251
Ilf3
Upregulated

363210
0.006023
1.388566
Phf3
Upregulated

680451
0.005563
1.419061
Nrbp2
Upregulated

311112
0.001699
1.426768
Fastkd1
Upregulated

54323
0.001608
1.4509
Arc
Upregulated

309136
0.006405
1.452428
Oraov1
Upregulated

363169
0.005748
1.472567
Toag1
Upregulated

29642
0.004937
1.475875
Slc38a2
Upregulated

305461
0.004104
1.475879
Fam53a
Upregulated

304813
0.00934
1.481691
Ppp1r12b
Upregulated

680006
0.007932
1.484512
Mad1l1
Upregulated

304474
0.001635
1.497221
Pitpnm2
Upregulated

115768
0.009088
1.509009
Zfp37
Upregulated

301513
0.001268
1.512431
Rqcd1
Upregulated

363273
0.009331
1.521116
Cops7b
Upregulated

293511
0.008749
1.533752
Znf688
Upregulated

245966
0.004372
1.544613
Tmem150a
Upregulated

291409
0.003844
1.552189
Zfp236
Upregulated

84607
0.007931
1.552588
Socs2
Upregulated

306344
0.007778
1.569477
Arrdc2
Upregulated

309828
0.006302
1.584851
Tspyl4
Upregulated

501095
0.009284
1.589281
Rftn1
Upregulated

81531
0.008017
1.606129
Pfn2
Upregulated

293152
0.007896
1.613085
Art2b
Upregulated

497040
0.006162
1.71037
Prss36
Upregulated

171454
0.009816
1.850404
Nacc1
Upregulated

363827
0.00216
1.948295
LOC363827
Upregulated

364361
0.001905
4.479744
RGD1563700
Upregulated

Table 7: Significant GO Annotation of the 5 differentially expressed genes and the genes included ().

GO ID
Name
Symbol
Hits
Total
Percent
Enrichment test value

GO: 0031503
Protein complex localization
Fkbp4
1
5
20.00%
0.0309

GO: 0022607
Cellular component assembly
Sqstm1, Nacc1, Ivd, Fkbp4, Tspyl4, Itga5, Pfn2
8
786
1.02%
0.0548

GO: 0044085
Cellular component biogenesis
Sqstm1, Nacc1, Ivd, Fkbp4, Tspyl4, Itga5, Pfn2
8
883
0.91%
0.0926

GO: 0010926
Anatomical structure formation
Sqstm1, Nacc1, Ivd, Fkbp4, Ubp1, Tspyl4, Itga5, Pfn2
9
1049
0.86%
0.0993

GO: 0043233
Organelle lumen
Sqstm1, Nacc1, Ivd, Fkbp4, Pa2g4, Ints10, Nthl1, Ddx21, E2f1, Rbm4b, Ppig
11
1360
0.81%
0.0994

Table 8: KEGG Pathway annotation of the 120 differentially expressed genes () ( refers downregulation, refers upregulation).

Name
Symbol
Total
Percent
Enrichment test

value
value

Cell cycle
Cdc14a↑
132
0.0227
0.0044
0.0067

E2f1↓

Mad1l1↑

Jak-STAT signaling pathway
Socs4↑
149
0.0201
0.0062
0.0067

Cish↓

Socs2↑

Type II diabetes mellitus
Socs4↑
53
0.0377
0.008
0.0067

Socs2↑

One carbon pool by folate
Gart↑
17
0.0588
0.0429
0.0158

Insulin signaling pathway
Socs4↑
140
0.0143
0.0471
0.0158

Socs2↑

Figure 5: Heat map of the differently expressed genes. R2_1_NS, R2_2_NS, and R2_3_NS refer to ESG and R3_1_NS, R3_2_NS, R3_3_NS to HG.

No genes were found, which were significantly differently expressed simultaneously in ESG versus CG and ESG versus HG. However, 8,426 genes were found no statistical difference in HG versus CG () among which 84 were found also presented in the differently expressed genes in ESG versus HG (Table 9 (Supporting Information 4)).

Table 9: The 84 genes differently expressed in ESG and normalized in HG (the value and fold change of ESG versus CG ).

Gene ID

Fold change
Symbol
Description

287443
0.0414
2.0120
Acap1
ArfGAP with coiled-coil, ankyrin repeat, and PH domains 1

316628
0.0044
0.2748
Asb1
Ankyrin repeat and SOCS box-containing 1 (Asb1), mRNA

307970
0.0397
0.3289
Atxn1l
PREDICTED: similar to Ataxin-1 (Spinocerebellar ataxia type 1 protein homolog)

304127
0.0266
0.4310
Bach1
BTB and CNC homology 1, basic leucine zipper transcription factor 1

94342
0.0368
0.4621
Bat3
HLA-B-associated transcript 3, transcript variant 2,

308588
0.0241
0.4679
Car11
Carbonic anhydrase-related XI protein

81780
0.0349
2.6298
Ccl5
Chemokine (C-C motif) ligand 5

25405
0.0303
0.3845
Ccng1
Cyclin G1

362217
0.0393
0.4273
Cenpb
PREDICTED: centromere protein B

314004
0.0237
0.3330
Cmpk2
Cytidine monophosphate (UMP-CMP) kinase 2, mitochondrial, nuclear gene encoding mitochondrial protein

24273
0.0401
0.4750
Cryaa
Crystallin, alpha A

361729
0.0183
0.4488
Cybasc3
Cytochrome b, ascorbate dependent 3

308942
0.0369
0.3530
Dennd5a
DENN/MADD domain containing 5A

360583
0.0296
0.4192
Dhrs11
Dehydrogenase/reductase (SDR family) member 11

362293
0.0203
0.4955
Dnajb6
DnaJ (Hsp40) homolog, subfamily B, member 6

81655
0.0336
0.4654
Dync1li2
Dynein, cytoplasmic 1 light intermediate chain 2

59117
0.0343
0.3116
Eif2c2
Eukaryotic translation initiation factor 2C, 2

497983
0.0476
0.4848
Fam117a
Family with sequence similarity 117, member A

363083
0.0074
2.5213
Fbxl22
F-box and leucine-rich repeat protein 22

29292
0.0293
0.4455
Ftl
Ferritin, light polypeptide

54281
0.0281
0.3897
Furin
Furin (paired basic amino acid cleaving enzyme)

25172
0.0185
0.3991
Gata1
GATA binding protein 1

293267
0.0274
0.3516
Hbe1
Hemoglobin, epsilon 1

94164
0.0175
0.4161
Hbg1
Hemoglobin, gamma A

498008
0.0335
2.2484
Hexim1
Hexamethylene bis-acetamide inducible 1

365895
0.0417
0.3894
Hipk1
Homeodomain interacting protein kinase 1

288240
0.0022
0.3449
Hlcs
PREDICTED: holocarboxylase synthetase (biotin-(proprionyl-Coenzyme A-carboxylase (ATP-hydrolysing)) ligase)

293624
0.0080
0.3642
Irf7
Interferon regulatory factor 7

290985
0.0079
0.4919
Isca1
Iron-sulfur cluster assembly 1 homolog (S. cerevisiae)

298693
0.0462
0.3402
Isg15
ISG15 ubiquitin-like modifier

25118
0.0351
2.9262
Itga1
Integrin, alpha 1

300317
0.0493
0.4873
Kctd17
Potassium channel tetramerisation domain containing 17

25110
0.0410
2.6060
Klrd1
Killer cell lectin-like receptor, subfamily D, member 1

245955
0.0120
0.4700
Lgals3bp
Lectin, galactoside-binding, soluble, 3 binding protein

25476
0.0214
0.4406
Lgals9
Lectin, galactoside-binding, soluble, 9

100365370
0.0172
0.4588
LOC100365370
PREDICTED: nuclear LIM interactor-interacting factor 2-like

498145
0.0213
0.3006
LOC498145
Similar to RIKEN cDNA 2810453I06

679596
0.0155
0.4814
LOC679596
PREDICTED: similar to GABA(A) receptor-associated protein like 2

684112
0.0121
0.4067
LOC684112
PREDICTED: similar to KIAA0999 protein

293156
0.0090
0.4140
Lrtomt
Leucine rich transmembrane and 0-methyltransferase domain containing

294241
0.0443
0.2072
Ly6g6c
Lymphocyte antigen 6 complex, locus G6C

117558
0.0498
0.3267
Mylk2
Myosin light chain kinase 2

85482
0.0360
0.4205
Nbn
Nibrin

366998
0.0309
0.4486
Nfe2
Nuclear factor, erythroid derived 2

59115
0.0355
0.3302
Ninj2
Ninjurin 2

245980
0.0238
0.4878
Nr2f6
Nuclear receptor subfamily 2, group F, member 6

287328
0.0292
0.4931
Olr1439
Olfactory receptor 1439

287520
0.0498
0.4482
Olr1516
Olfactory receptor 1516

366104
0.0175
0.4251
Olr541
Olfactory receptor 541

246294
0.0120
0.3491
Optn
Optineurin

362973
0.0467
0.4896
Parvb
Parvin, beta

24649
0.0147
0.3899
Pim1
Pim-1 oncogene

64534
0.0423
2.1733
Pim3
Pim-3 oncogene

301173
0.0478
0.3759
Plcl2
Phospholipase C-like 2

310674
0.0473
0.4134
Plekho1
Pleckstrin homology domain containing, family O member 1

362873
0.0062
0.4404
Plxnc1
Plexin C1

362248
0.0215
0.4759
Procr
Protein C receptor, endothelial

309381
0.0286
2.2397
Pyroxd2
Pyridine nucleotide-disulphide oxidoreductase domain 2

171452
0.0460
0.3652
Rab3il1
RAB3A interacting protein

56820
0.0334
0.1273
Ramp3
Receptor (G protein-coupled) activity modifying protein 3

498659
0.0473
7.0377
RatNP-3b
Defensin RatNP-3 precursor

296408
0.0259
0.4348
RGD1311378
Similar to RIKEN cDNA 2010011I20

501644
0.0175
0.4259
RGD1561055
PREDICTED: similar to Ferritin light chain 2 (Ferritin L subunit 2) (Ferritin subunit LG)

65190
0.0454
0.3257
Rsad2
Radical S-adenosyl methionine domain containing 2

24974
0.0165
0.4619
RT1-A2
RT1 class Ia, locus A2 (RT1-A2)

414779
0.0105
0.4766
RT1-CE2
RT1 class I, locus CE2 (RT1-CE2)

266758
0.0163
2.6183
Sec11c
SEC11 homolog C (S. cerevisiae)

313057
0.0446
0.4886
Serinc2
Serine incorporator 2

498546
0.0120
0.1863
Serp2
Stress-associated endoplasmic reticulum protein family member 2

360636
0.0484
0.4722
Slc25a39
Solute carrier family 25, member 39 (Slc25a39)

192208
0.0472
0.3469
Slc38a5
Solute carrier family 38, member 5 (Slc38a5)

300191
0.0457
0.4485
Slc48a1
Solute carrier family 48 (heme transporter), member 1

64630
0.0330
0.4620
Snap23
Synaptosomal-associated protein 23

314251
0.0353
0.4407
Sptb
Spectrin, beta, erythrocytic

113894
0.0230
0.4367
Sqstm1
Sequestosome 1, transcript variant 1, mRNA

501146
0.0449
0.3749
Stradb
STE20-related kinase adaptor beta

24851
0.0449
0.3944
Tpm1
Tropomyosin 1, alpha

303167
0.0390
0.3720
Trim58
Predicted: tripartite motif-containing 58

362087
0.0450
0.3958
Ubac1
UBA domain containing 1

295704
0.0234
0.3510
Ube2l6
Ubiquitin-conjugating enzyme E2L 6

310633
0.0316
0.3751
Ubqln4
Ubiquilin 4

289229
0.0240
0.3468
Vangl2
Vang-like 2

24874
0.0262
2.6865
Vhl
Von Hippel-Lindau tumor suppressor

298765
0.0209
2.4995
Zfp36l2
Zinc finger protein 36, C3H type-like 2

3.3.3. RT-PCR Validation

Irf7, Ninj2, Plxnc1, and Isca1 were filtered to validate with RT-PCR according to the set that the flag value of the expression profile chip ≠ , or , expression value ≥6 from the GO and KEGG annotation. As showed in Figure 6(a), Irf7, Ninj2, and Isca1 were significantly hypoexpressed in ESG (); however, the gene expression of Plxnc1 did not match the RT-PCR validation; in Figure 6(b), the four genes were not significantly hypoexpressed in HG versus CG (), and the RT-PCR validation showed an obviously reduced ΔΔCt values compared with those in Figure 6(a). The gene expression profile chip outcomes showed a favorable match with the RT-PCR result.

(a) Relationship of rt-PCR and gene expression (ESG versus CG)

(b) Relationship of rt-PCR and gene expression (HG versus CG (no change))

Figure 6: RT-PCR validation of the selected four genes from gene expression profile chips, that is, Irf7, Ninj2, and Plxnc1, and Isca1. indicates the target genes were hyperexpressed in ESG/HG comparing with CG while indicates the target genes were hypoexpressed in ESG/HG comparing with CG. indicates the target genes were hyperexpressed in ESG/HG comparing with CG while indicates the target genes were hypoexpressed in ESG/HG comparing with CG.

4. Discussion

Substantial evidence from preclinical laboratory studies indicates that PS affects the hormonal and behavioral development of offspring. PS has been found to alter baseline and stress-induced responsivity of the HPA axis and levels and distribution of regulatory neurotransmitters, such as norepinepherine, dopamine, serotonin, and acetylcholine and to modify key limbic structures and to retard intrauterine growth [15]. In this study, ESG demonstrated differences from CG on body weight, hormone levels, and gene expressions, and HG differed from the ESG group on body weight, hormone levels, and gene expressions. From the perspective of Chinese medicine, once parental kidney is injured from PS, manifestations are handed down to offspring, showing development retardation and OFT performance reduction. JKSQW is a typical herbal formula for kidney qi supplementing, which recovers the physiological functions of kidney. In this study, the body weight and OFT performance were improved by JKSQW, supporting the effectiveness of Chinese herb remedy in rodents in lab [13].

Experimentally, PS in animal models mal-programs offspring physiology, resulting in increasing the likelihood of disorders of HPA axis activity and anxiety-related behaviors in adulthood [16]. PS increases plasma levels of corticosterone and corticotrophin releasing hormone in the mother and fetus, which may contribute to insulin resistance and behavior disorders in their offspring that include attention and learning deficits, generalized anxiety and depression [17]. We demonstrated that the serum corticosterone of ESG were significantly higher than CG and slightly higher than HG, which was in accordance with previous reports [18–20]. Animal studies indicate that PS can affect the activity of the placental barrier enzyme 11-βHSD2 (11β-hydroxysteroid dehydrogenase type 2), which metabolizes corticosterone [2, 17]. 5-HT level of ESG was significantly higher than CG and HG. Alterations in activity of the central 5-HT system play an essential role in many of these behavioral aberrations due to PS [21, 22]. During pregnancy, the 5-HT system has a fundamental role in the fetus’ development of the central nervous system, and 5-HT neurotransmission is involved in the activation and feedback of HPA axis throughout life [23]. Huang et al. [14] reported that levels of 5-HT were higher in rat hippocampus and hypothalamus of fetuses in the CUS group, that is, chronic unpredictable stress maternally performed than in the controls. Increased 5-HT signaling increases the expression of key transcription factors, notably nerve growth factor induced protein A, which binds to and regulates activation of the GR promoter [24]. No difference of the dopamine level between ESG and CG were obtained, indicating earthquake may not alter the offspring dopamine. Interestingly JKSQW in HG significantly elevated the dopamine level of ESG. Carboni et al. [25] reported prenatal catecholamine stimulation was obtained by amphetamine or nicotine. We observed that PS did not change dopamine. No difference of the hormone level between ESG and CG were obtained, indicating earthquake may not impact on the growth hormone of offspring. Interestingly, however, JKSQW in HG significantly elevated the dopamine level of ESG, which might be explained by the function of kidney that governs development. Shen and Cai [26] reported that growth hormone genes were downregulated in a kidney-qi deficiency rat model and Chinese formula supplementing kidney qi could correct the downregulation. Mak et al. [27] found that chronic kidney disease in children was associated with dramatic changes in the growth hormone and insulin-like growth factor (IGF-1) axis, resulting in growth retardation. Yang and Li [28] reported that JKSQW could recover the downregulated growth hormone genes (Somatotropin precursor, NM-008117) in a kidney-yang deficiency rat model. Researches of the neurobiological mechanisms underlying the interaction between PS and adult mental disorders suggest the involvement of multiple neurotransmitter systems [29, 30]. Findings of the hormones alterations suggest manual earthquake is a liable model modulating the fear from natural earthquake involving development retardation and neurotransmitter systems disorder. Meanwhile, from the perspective of Chinese medicine, kidney function is disturbed by the earthquake and recovered by JKSQW.

We found 81 genes upregulated and 39 genes downregulated in ESG versus CG, from which 14 significant GO and 12 KEGG pathways were annotated, indicating diversified and complicated physiological and psychological impacts on offspring left by the prenatal earthquake as a prenatal stress, for example, long-term depression and long-term potentiation. Mychasiuk et al. [31] reported that significant gene expression level changes in 558 different genes, associated with overrepresentation of 36 biological processes and 34 canonical pathways indicating prenatal stress did not have to be experienced by the mother herself to influence offspring brain development. Among the GO annotations Itpr1 and Itpr2 appeared in almost all the affected pathways. In nonexcitable cells, the inositol 1,4,5-trisphosphate receptor (IP3R) is an intracellular Ca2C channel, which plays a major role in Ca2C signalling. Three isoforms of IP3R have been identified (IP3R-1, IP3R-2, and IP3R-3) and most cell types express different proportions of each isoform [31]. IP3Rs play major roles in agonists-induced intracellular Ca2C release and also in store operated Ca2C entry, a process whereby the depletion of intracellular Ca2C store causes the opening of Ca2C channels in the plasma membrane [32]. The intracellular elevations induced by BDNF required a signaling pathway consistent with the activation of the Trk-IP3R cascade, which was also necessary for the activation of the membrane conductance IBDNF [33, 34]. Amaral and Pozzo-Miller [35] reported that Trk receptors, IP3Rs, full intracellular stores and influx are all required for BDNF-induced elevations and membrane currents. Opposing influences of mBDNF and proBDNF on long-term potentiation and long-term depression might contribute to the dichotomy of BDNF actions on behaviors mediated by the brain stress and reward systems [36, 37]. Twelve KEGG pathways were annotated, including oocyte meiosis, vascular smooth muscle contraction, RIG-I-like receptor signaling pathway, long-term potentiation, ubiquitin mediated proteolysis, and long-term depression, Titterness and Christie [38] prenatal ethanol and prenatal stress produce sex-specific alterations in synaptic plasticity in the adolescent hippocampus. Calpains, which belong to a family of at least 14 members of calcium-dependent cysteine proteases and are involved in apoptosis are implicated in a wide range of physiological functions including cell motility, differentiation, signal transduction, including cell survival pathways, cell cycle progression, regulation of gene expression, and long-term potentiation [39, 40]. Yang et al. [41] reported that prenatal stress (10 unpredictable, 1 s, 0.8 mA foot shocks per day during gestational days 13–19) impaired long-term potentiation (LTP) but facilitated long-term depression (LTD) in hippocampal CA1 region in slices of the prenatal stressed offspring (5 weeks old). Proteolysis by the ubiquitin-proteasome pathway has attained prominence as a new molecular mechanism which regulates varied important functions of the nervous system, including development of synaptic connections and synaptic plasticity through control of axonal growth, axonal and dendritic pruning, and regulation of synaptic size and number [42].

We found 60 genes upregulated and 28 genes downregulated in HG versus ESG, from which five significant GO and five KEGG pathways were annotated, indicating diversified cellular biological process and signaling pathways. Interestingly, Socs 2 and Socs 4 of Socs (suppressors of cytokine signaling) family appeared in three of the KEGG pathways. SOCS family consists of eight structurally similar proteins (SOCS-1 to SOCS-7 and CIS), which have been implicated as potential inhibitors of tissue growth during both prenatal and postnatal life [43] and their actions clearly now extend to other intracellular pathways, they remain key negative regulators of cytokine and growth factor signaling [44]. Cytokine-mediated JAK/STAT signaling, that is, Janus kinase/signal transducers and activators of transcription, controls a number of vital biologic responses, including immune function, cellular growth, differentiation, and hematopoiesis [45]. The SOCS Family—The SOCS proteins were identified as STAT target genes that directly antagonize STAT activation, resulting in a classic “feedback loop” [46]. PS in rats induced lifespan reduction of neurogenesis in the dentate gyrus and produced impairment in hippocampal-related spatial tasks through blocking the increase of learning-induced neurogenesis [47]. Previous research reported that male rats exposed to stress in utero are characterized by a decrease in hippocampal cell proliferation, and consequently neurogenesis, from adolescence to senescence [48]. PS has been reported to alter cytokine levels. Coussons-Read et al. [49] reported that stress-related neural immune interactions may contribute to pregnancy complications and poor outcome. Collier et al. [50] found that PS changed typical proinflammatory cytokines including tumor necrosis factor (TNF)-α, and interleukin (IL)-6. As mentioned above, JKSQW recovered the dysfunction of kidney due to fear from earthquake, which could be supported by gene profile experiment outcome. In other words, cytokine conduction pathways, for example, JAK/STAT are involved in the prenatal kidney deficiency, and key molecules like Socs-2 and Socs-4 are the regulating targets of Chinese medicine treatment. The underlying mechanism that JKSQW improves development and behavior might attribute to the upregulation of Socs-2 and Socs-4 which suppress the pathway of JAK/STAT, resulting in reduction certain cytokines’ secretion. diabetes is considered as Xiao-ke in Chinese medicine, whose major pattern is kidney deficiency. JKSQW plays an important role in the composition of prescriptions treating Diabetes in Chinese medicine [51]. Promisingly, our findings revealed insulin related pathways were involved in the outcome of herbal intervention in HG, supporting the hypnosis that JKSQW recovery the dysfunction of kidney.

Four genes (Irf7, Ninj2, Plxnc1, and Isca1) were validated with RT-PCR, showing a favorable match (75%) between the gene expression profile chip and RT-PCR result. It is reported that all elements of IFN responses, whether the systemic production of IFN in innate immunity or the local action of IFN from plasmacytoid dendritic cells in adaptive immunity, are under the control of Irf7 [52]. Hannah et al. [53] reported that induction of pattern recognition receptors (PRRs; Tlr7 and Rig-I), expression of antiviral genes (Myd88, Visa, Jun, Irf7, Ifnbeta, Ifnar1, Jak2, Stat3, and Mx2), and production of Mx protein was elevated in the lungs of intact females compared with intact males. Ninjurin2 (Ninj2) is a transmembrane protein that mediates cell-to-cell and cell-to-extracellular matrix interactions during development, differentiation, and regeneration of the nervous system [54]. Recently, Ninj2 was reported to be a vascular susceptibility gene and associated with Alzheimer’s disease risk [55].

In conclusion, together with our own recent data, the findings of this body of work demonstrate the earthquake as a prenatal stressor during the pregnancy could negatively retard the body and nervous system development, and Chinese herbal remedy could correct the retardation, which could attribute to neurohormones alteration and altered gene expression profile. The gene pathways involved have been tied to signaling pathway, long-term potentiation, ubiquitin mediated proteolysis, and long-term depression relating to disruptions from prenatal stress; Jak-STAT signaling pathway could play a key role in improving the function of JKSQW. This study demonstrates that negatively prenatal experiences have the ability to significantly retard offspring developmental and immunity trajectories, which can be corrected by Chinese herbal remedy.

Conflict of Interests

The authors declare no conflict of interests.

Acknowledgments

This study was under the support of National Science Funds of China with the Grant no. 81072719. The authors thank Sheri L. Johnson, Ph.D. and Zeyiad Elias, Ph.D. USA for English editing.

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