Abstract
Background
Postpartum developmental delay has been proposed as an important
phenotype of human evolution which contributes to many human-specific
features including the increase in brain size and the advanced
human-specific cognitive traits. However, the biological processes and
molecular functions underlying early brain development still remain
poorly understood, especially in human and primates.
Results
In this paper, we comparatively and extensively studied dorsolarteral
prefrontal cortex expression data in human and chimpanzee to
investigate the critical processes or biological events during early
brain development at a molecular level. By using the dynamic network
biomarker (DNB) model, we found that there are tipping points around
3 months and 1 month, which are crucial periods in infant human and
chimpanzee brain development, respectively. In particular, we shown
that the human postnatal development and the corresponding expression
changes are delayed 3 times relative to chimpanzee, and we also
revealed that many common biological processes are highly involved in
those critical periods for both human and chimpanzee, e.g.,
physiological system development functions, nervous system development,
organismal development and tissue morphology. These findings support
that the maximal rates of brain growth will be in those two critical
periods for respective human and primates. In addition, different from
chimpanzee, our analytic results also showed that human can further
develop a number of advanced behavior functions around this tipping
point (around 3 months), such as the ability of learning and memory.
Conclusion
This work not only provides biological insights into primate brain
development at a molecular level but also opens a new way to study the
criticality of nonlinear biological processes based on the observed
omics data.
Keywords: Brain development, Gene expression, Bioinformatics, Tipping
point, Dynamic network biomarker
Background
The primate brain development was traditionally studied by
investigating the conserved biological processes and functions across
mammals [[31]1]. Genetic changes resulting in protein changes are
probably too few to account for the great phenotype differences between
humans and chimpanzees, prompting the hypothesis that changes in gene
expression are likely to drive major phenotypic differences between
humans and other primates [[32]2]. Human and chimpanzee also show a
number of significant differences in morphology and numerous cognitive
traits during development tendency [[33]3–[34]7]. Some detailed
comparisons related to gene expression of human and chimpanzee have
identified human accelerated regions [[35]8, [36]9] or conserved
noncoding sequences [[37]10]. The individual ontogenesis of human and
chimpanzee have mainly been compared in terms of skeletal morphology
but there are few studies conducted at a molecular level. Results from
these comparisons demonstrate that some human features may indeed be
explained by neoteny, e.g. small jaws [[38]11]. In human brain growth,
developmental retardation or neoteny has been identified and also the
brain developmental changes have been delayed comparing to other
primate species. Besides, there is a well-known evidence that human’s
infant brain develops sharply in the first 3 months in terms of
morphology. The infant structural growth rate changes approximately
from 1%/d to 0.4%/d at the end of 3 months [[39]12]. Generally, the
brain-growth rate of infant chimpanzee is three times as much as that
of human.
The transcriptome is dramatically remodeled during postnatal brain
development [[40]13]. However, the biological processes and biological
functions during early brain development in human and primates have not
yet been extensively studied so far. In particular, the brain
development can be considered as a nonlinear biological process, which
involves the gradual change and then drastic transition near the
tipping point. Thus, detecting the tipping point and further revealing
the related molecular functions as well as gene regulations are
important to understand the brain development as a nonlinear dynamical
process at a molecular level. In this paper, we investigate the
critical processes or events during early brain development at a
molecular level by extensively studying dorsolarteral prefrontal cortex
expression data in human and chimpanzee. For the first time, we
identified 3 months for human and 1 month for chimpanzee as their
respective tipping points during their infant brain development, based
on Dynamic Network Biomarker (DNB) theory [[41]14, [42]15]. In
addition, we found three times difference in terms of brain growth rate
between human and chimpanzee due to human slow postnatal development.
We also reveal many common biological processes involved in those key
periods for both human and chimpanzee, e.g., physiological system
development functions, nervous system development, organismal
development and tissue morphology, etc. Actually, many published works
have reported that the maximal rates of brain growth are 3 and 1 month
for human and chimpanzee respectively, which is consistent with our
analysis. Our analytic results also show that from around 3 months
(tipping point) to later, human rather than chimpanzee can further
develop a number of advanced behavior functions, e.g. the ability of
learning and memory. This work not only provides biological insights
into the brain development from a system viewpoint but also opens a new
way to study the criticality of nonlinear biological processes based on
DNB theory.
Results
Expression pattern analysis of dorsolateral prefrontal cortex expression data
reveals smooth changes with drastic transitions during brain development
We first evaluate the general expression pattern in the dorsolarteral
prefrontal cortex (DLPFC) of three species, human, chimpanzee and
macaque. We cluster these samples according to their expression levels
by hierarchical clustering analysis. The samples are well separated
into three clusters according to their species. Relative to macaque
samples, chimpanzee is close to human in the resulting clusters in
terms of the distance (Additional file [43]1). Meanwhile, human and
chimpanzee also can be clustered into two different groups
(Fig. [44]1a). Therefore, human and chimpanzee brains are considered
very close but still different. Clearly, there are smooth changes with
drastic transitions during the period. In this work, we focus on the
analyses of infant brain development of human and chimpanzee, i.e.
focusing on the early / first year life stages of humans and
chimpanzees. In the principal component analysis (PCA) results of the
data, we can also find that two groups, i.e. human and chimpanzee, are
significantly separated (Fig. [45]1b). Next, we estimate when these
gene expression changes take place during human and chimpanzee brain
development and what the differences are between human and chimpanzee
among the whole gene expressions. We used Multi-dimensional scaling
(MDS) to evaluate the global changes of the whole samples in human and
chimpanzee gene expressions relative to the individual’s age. We find
that the most rapid changes or drastic transitions take place in the
first year for both species. As shown in Fig. [46]1, the slope of the
line for gene expressions is approximately 1 during the first year.
More than 55% changes happened in the first year. Furthermore, the
early trajectory of chimpanzee’s age-related gene expression changes is
in close proximity to that of human (Fig. [47]1c).
Fig. 1.
[48]Fig. 1
[49]Open in a new tab
Gene expression analysis of dorsolateral prefrontal cortex expression
data. a The clusters of the human and chimpanzee DLPFC dataset. b The
first 2 principle components of the two species’ expression data by
PCA. Each small dot represents the PC score along the top two principle
components for each sample and the numbers represent each sample’s age
in years. Blue represents chimpanzee samples and red represents human
samples. For both humans and chimpanzees, the samples of the
individuals’ ages (the most samples are included in circle) are
distributed on early life stages. c Multi-dimensional scaling (MDS)
plots show the first principal axes relative to the individual’s age in
years. Each point represents a sample
Dynamic network biomarkers identifies the tipping points during the infant
brain development
Recent research works show that there is a sudden change or a critical
transition during time evolution of many dynamic systems, such as
climate system [[50]16, [51]17], ecosystem [[52]18, [53]19], economics,
global finance [[54]20, [55]21] and biological system [[56]14]. Such a
change plays a critical role in the development of whole system, and
there will be a tipping point just before such drastic change or
transition of system states. Owing to the sudden change, the dynamical
features of biological system is from a state to another state through
a drastic transition or transformation (Fig. [57]2a). To detect the
tipping points during dynamic processes, a mathematical model, DNB
theory with three quantitative criteria [[58]14] was developed and has
been widely applied to investigate many diseases [[59]14, [60]15,
[61]22–[62]27] and biological processes [[63]24, [64]28, [65]29] based
on the observed data. In this work, DNB is firstly applied to find
whether or not there is a tipping point in the primate brain growth in
the first year (infant) and what biological functions are developed
(enriched) before and after such tipping point.
Fig. 2.
[66]Fig. 2
[67]Open in a new tab
Detecting the tipping points for the infant brain development of human
and chimpanzee. a Schematic illustration of the dynamical process from
a state to another with a drastic transition for a biological system. b
& c Detecting the tipping points during the infant brain development of
two species by dynamic network biomarkers. b There are 13 infant human
samples (age range from 0 to 0.9 years old). The two dots connected by
the black line are significantly higher than other dots, and the
corresponding time points involve 0.3. c There are 9 infant chimpanzee
samples (age range from 0 to 6.3 years old). The two dots connected by
the black line are significantly higher than other dots, and the
corresponding time points involve 0.1. b & c represent the composite
index of DNB (see [68]Methods, and CI in Eq. ([69]1))
To identify specific tipping points during the first year brain
development of human and chimpanzee, the gene expression data include
13 infant humans and 9 infant chimpanzees were used. According to the
three criteria of DNB for detecting tipping points [[70]14], we
analyzed all 17,429 genes. The composite index of the DNB suggests that
human’s DLPFC gene expression has a significant change around 3 months
(Fig. [71]2b) and around 1 month for chimpanzee (Fig. [72]2c).
Additional file [73]2 also shows that 3 and 1 month are the tipping
points of the infant human and chimpanzee respectively. By using the
DNB model, we got 371 dynamical network biomarker genes (DNBs)
(Fig. [74]3a, and Additional file [75]3) of human and 132 DNBs (Fig.
[76]3a, and Additional file [77]3) of chimpanzee. There is one gene
(TNFAIP3) overlapping the two specie-specific DNBs (Fig. [78]3a and
Additional file [79]3). Meanwhile, we obtained 341 significantly
differentially expressed genes (DEGs) around 3 months for human (Fig.
[80]3b, and Additional file [81]4) (ANOVA false discovery rate
(FDR) < 0.01 and fold-change > 2); and similarly, we detected 396
significant DEGs for chimpanzee (Fig. [82]3b, and Additional file
[83]4). There are 18 genes overlapping the two DEGs (Fig. [84]3b and
Additional file [85]4). Previous reports of these overlapping genes
relevant to the functions of brain, especially on brain development,
are listed in Table [86]1.
Fig. 3.
[87]Fig. 3
[88]Open in a new tab
The global gene expression changes during brain growth. a & b The pie
graphs of the DNBs and DEGs; a The DNBs of human and chimpanzee. The
yellow is the overlap (1 gene) of two groups; b The DEGs of human and
chimpanzee. The yellow is the overlap genes (18 genes) of two group
DEGs; c MDS plot shows that the first principal axis relative to the
individual’s age before 8 years old. Each point represents a sample,
i.e., the sample’s global expression analysis by using DNBs (371 human
genes and 132 chimpanzee genes); d The DEGs (341 human genes and 396
chimpanzee genes) are used to show the global expression tendency
relative to age
Table 1.
Overlapping DNBs/DEGs between human and chimpanzee
Type Entrez gene name Functions of brain development Other functions in
brain
RAET1E DEG retinoic acid early transcript 1E [[89]30]
LEFTY2 DEG left-right determination factor 2 [[90]31]
TUBB2B DEG tubulin beta 2B class IIb [[91]32]
PPM1J DEG Protein phosphatase Mg2+/Mn2+ dependent 1 J [[92]33]
CCDC182 DEG coiled-coil domain containing 182 [[93]34]
SIRPD DEG signal regulatory protein delta [[94]35]
OR5L2 DEG olfactory receptor family 5 subfamily L member 2 [[95]36]
FPR1 DEG formyl peptide receptor 1 [[96]37]
GPR34 DEG G protein-coupled receptor 34 [[97]38]
FCGRT DEG Fc fragment of IgG receptor and transporter [[98]39]
P2RY12 DEG purinergic receptor P2Y12 [[99]40]
AIF1 DEG allograft inflammatory factor 1 [[100]41]
SI DEG sucrase-isomaltase
OR10H2 DEG olfactory receptor family 10 subfamily H member 2
CD14 DEG CD14 molecule
PIK3CG DEG phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic
subunit gamma
RP11-1407O15.2 DEG RP11-407P15.2 protein-coding
TNFAIP3 DNB TNF alpha induced protein 3
[101]Open in a new tab
According to the DNB theory, DNBs may have strongly functional impacts
on biological processes at the tipping points. Next we examine whether
or not there are significantly differential expression changes during
the development of infant brain for DNBs. We find that the global
expression tendency of DNBs is significantly stronger than other genes.
Obviously, the relative growth rate of infant chimpanzee is much higher
than human (Fig. [102]3c) especially in the first year. There is the
similar tendency for the DEGs of the two groups (Fig. [103]3d). These
results suggest that DNBs and DEGs may play important roles around the
tipping points during the brain growth together. Therefore, by
analyzing DNBs and DEGs, we have shown a rapidly brain development
mechanism for the coordination of gene expression in infant chimpanzee
relative to infant human.
Advanced behavior related functions develop for human at the tipping point in
contrast to chimpanzee
We carried out analysis of both human’s DNBs and DEGs before and after
3 months with IPA (Ingenuity Pathway Analysis) [[104]42]. The most
significant physiological system development and function terms from
Disease and Function analysis are listed in Table [105]2. We also
conducted a network analysis by IPA. In the top-ranked networks, these
genes play an important role in Behavior (IPA disease and Function
Term, P-value = 1.02E-16~1.39E-6), including memory
(P-value = 1.39E-6), learning (P-value = 9.11E-9) and behavior
(P-value = 1.02E-16) (Table [106]3). Besides, these genes are also
abundant in the network related to Cell Morphology (IPA disease and
Function Term, P-value = 5.42E-16~2.26E-03). For DNBs in this network
(Fig. [107]4), i.e., FOS, JUN and EGR1 are regulated by many genes,
while SRF and NR3C1 regulate other genes in the network. The FOS gene
family consists of FOS, FOSB, FOSL1, and FOSL2. Leucine zipper proteins
are encoded by FOS and can dimerize with proteins of the JUN family.
FOS and JUN form the transcription factor complex AP-1. These proteins
have been identified as regulators of cell proliferation,
differentiation, and transformation. The protein encoded by EGR1
belongs to growth factor EGR family and functions as a transcriptional
regulator. Its target genes play a role in differentiation and
mutagenesis. Upstream analysis by IPA shows that FOS, JUN and EGR1 have
the same upstream regulator, growth factor EGF and transcription
regulator FOS. SRF encodes a ubiquitous nuclear protein and stimulates
cell differentiation and proliferation. NR3C1 encodes glucocorticoid
receptor and participates in inflammatory reactions, cell
differentiation and proliferation in target tissues [[108]43]. Based on
the analyses above, clearly these DNBs are related to Behavior in the
functional network, and they have strong co-function links with other
genes.
Table 2.
Top physiological system developments and functions enriched in human
DNBs and DEGs
Name P-value range Molecules
Tissue Morphology 3.23E-02 - 5.77E-06 43
Cardiovascular System Development and Function 8.72E-04 - 8.72E-04 5
Nervous System Development and Function 4.27E-02 - 8.72E-04 39
Organ Morphology 3.23E-02 - 8.72E-04 22
Organismal Development 3.94E-02 - 1.04E-03 23
[109]Open in a new tab
Table 3.
Top relevant diseases and biological Functions of the human DEGs and
DNBs network in Fig. [110]4
Diseases and Functions P-value range Molecules
Behavior 1.02E-16 - 1.39E-6 21
Behavior 1.02E-16 21
Learning 9.11E-9 10
Memory 1.39E-6 7
Cell Morphology 5.42E-16 - 2.26E-3 27
Morphology 5.42E-16 - 3.09E-7 25
Size 6.89E-11 12
hypertrophy 1.16E-10 - 2.26E-3 10
Sprouting 1.18E-10 11
Branching 1.32E-9 - 1.14E-6 10
depolarization 2.03E-7 5
Formation 4.52E-7 11
Neurogenesis 9.34E-7 9
[111]Open in a new tab
Fig. 4.
[112]Fig. 4
[113]Open in a new tab
Top networks and pathways of human DEGs and DNBs. Blue genes are DNBs,
red genes are the up-regulated genes along with time, and green genes
are the down-regulated genes. DNBs play a leading role in this network
Infants grow at the fastest rate at 3 months old, not only for their
height and weight but also for their brain development. The head
circumference will increase by about 1.25 cm during the third month.
Their behavior undergoes huge changes during this period. The Moro
reflex, which is developed in human evolution as a response to a sudden
loss of support, starts disappearing gradually at this period
[[114]44]. When the soles of infant feet touch a flat surface, they
will attempt to walk by placing one foot in front of the other: this
phenomenon is called as walking reflex or stepping reflex. This
behavior is present at birth and disappears around 10 weeks [[115]45].
At 3 months old, infants’ unconscious activities, such as Moro reflex
and Stepping reflect, disappears, meanwhile their behavior develops
more purposefully and steadily towards maturation. In addition, during
that period, hands begin to perform advanced functions and can open and
close consciously. They start staring at something that interests them
as well. Their Hand-eye coordination is also improving.
In a brief summary, our human DNBs and DEGs are found abundant in
Nervous System Development and Function, Cell Morphology and Behavior.
Nervous System Development and Cell Morphology support the fast brain
development, so that, infants become to develop the advanced behavior.
In the molecular level, we identify several DNBs as the hubs of the
network, which play critical roles in regulating the relevant
functional modules and pathways.
Chimpanzee acquires the ability of basic behaviors associated with survival
at the tipping point
By contrast, chimpanzee develops faster than human, which has been
observed in many research works [[116]13]. Actually, in this work we
find that chimpanzee reaches the tipping point (1 month old) earlier.
We also apply IPA analysis on chimpanzee DNBs and DEGs before and after
1 month old. The most significant physiological system development and
function terms from disease and function analysis are listed in
Table [117]4. Though chimpanzee DNBs and DEGs have few overlaps with
human DNBs and DEGs, their top physiological system development and
function terms are very similar, including nervous system development,
organismal development and tissue morphology. We can conclude that
chimpanzee experiences the basic brain development similar to human
beings at the tipping point. We further investigate the ability of
behaviors by the function analysis, i.e., the feeding
(P-value = 3.92E-02). Human has more advanced behavior ability at the
tipping point than chimpanzee, such as learning and memory, which are
the footstone of our cognitive competence.
Table 4.
Top physiological system developments and functions of chimpanzee DNBs
and DEGs
Name P-value range Molecules
Embryonic Development 3.92E-02 - 1.98E-02 2
Nervous System Development and Function 3.92E-02 - 1.98E-02 3
Organismal Development 3.92E-02 - 1.98E-02 2
Tissue Morphology 1.98E-02 - 1.98E-02 1
Behavior 3.92E-02 - 3.92E-02 1
[118]Open in a new tab
Discussion and conclusion
Human beings have had dramatic enlargement in brain size during the
evolution, and developed advanced cognitive ability. In this work, we
aim to reveal major biological events happening to infant human brain
in the development process. We applied the DNB theory to analyze the
tipping points based on the dorsolateral prefrontal cortex expression
data of both human and chimpanzee.
Generally, chimpanzee grows faster than human beings for the brain
development; they reach the tipping point around 1 month old, much
earlier than human. In contrast, human’s tipping point is around 3
months old, which has been reported as one of the golden age of brain
development [[119]12]. Then we carried out the differential gene
expression analysis around the tipping points, and conducted function
analysis on DEGs and DNBs with IPA. Chimpanzee and human have different
DEGs and DNBs, but their DEGs and DNBs are related to same
physiological system development functions, i.e., nervous system
development, organismal development and tissue morphology. These
functions support the fast development of brain at this time period.
However, human further obtains more advanced behavior functions at the
tipping point. Specifically, human infants have the ability of learning
and memory while chimpanzee infants do not. In the molecular level, we
identified several DNBs in the hubs of human top ranked network, which
play a critical role in regulating the modules and having the
functional impacts on the brain growth. They are of great importance
due to the related functions with cellular proliferation and
differentiation in common. This work not only provides biological
insights into the brain development at a molecular level but also opens
a new way to study the criticality of nonlinear biological processes
based on the observed omics data. As a future topic, in contrast to the
traditional correlation analysis, we will adopt the direct associations
[[120]12] between molecules to study the molecular mechanism of infant
brain development at the network level.
Methods
Data set preparation
All dorsolarteral prefrontal cortex (DLPFC) expression data sets from
the microarray experiments were downloaded from the National Center for
Biotechnology Information Gene Expression Omnibus (GEO) with the
accession numbers [121]GSE11512 (GC HG-U133 Plus2.0 experiments). The
data sets contain 44 human samples (ranging in age 0–80 years), 14
chimpanzee samples (ranging in age 0–44 years), and 9 macaque samples.
In each sampling period, there are 1 to 5 samples for gene expressions
(Additional file [122]5).
Clustering analyses of data sets
Before analyzing the two data sets, we transformed the original data by
using normalization method. In this way, the data of each sample is in
a uniform distribution which suits better for our statistical analysis.
One method of cluster algorithm is ‘clustergram()’ in MATLAB Library,
and the results are shown in Fig. [123]1a. Another one is PCA, and the
results are given in Fig. [124]1b. MDS is used to calculate a 1D
summary measure of global expression relative to the individual’s age
(Fig. [125]1c). The ‘pdist()’ function in MATLAB Library is used to
evaluate the distance between two samples, and the ‘mdscale()’ in
MATLAB Library is adopted to estimate the global expression of samples.
Dynamic network biomarkers (DNB) analysis
Based on the nonlinear dynamical theory, a system is near the critical
state if there is a dominant group of molecules, i.e. DNB. According to
the DNB theoretical analysis [[126]14], we proved that the following
generic properties hold when the infant brain biological system reaches
a critical time point.
* There exists a group of molecules of human or chimpanzee, whose
average Pearson’s correlation coefficients (PCCs) of molecules
drastically increase in absolute value.
* The average PCCs of molecules between this group and any others
(i.e., between molecules inside this group and any other molecules
outside this group) drastically decrease in absolute value.
* The average standard deviations (SDs) of molecules in this group
drastically increase.
If all of these three conditions are satisfied simultaneously, we call
this group a dominant group of the system, which will play an important
role in early brain development.
Therefore, when a biological system approaches the tipping point; a
dominant group of genes appear among all genes. With the gene
expression data of all samples in one period, this dominant group can
be quantified by the following composite index (DNB model):
[MATH: CI≕S
Dd•PCCdPCCo :MATH]
1
where PCC[d] is the average Pearson’s correlation coefficient (PCC)
between the genes in the dominant group of the same time period in
absolute value; PCC[o] is the average PCC between the dominant group
and others of the same time period in absolute value; SD[d] is the
average standard deviations (SD) of the genes in the dominant group.
These three criteria together construct the composite index (CI)
[[127]14, [128]15, [129]24–[130]28, [131]46–[132]51]. The CI is
expected to reach the peak or increase sharply during the measured
periods when the system approaches the tipping point, thus indicating
the imminent transition.
We applied this DNB method to detect the tipping points during the
infant human and chimpanzee brain development. In each sampling period
of infant human and chimpanzee, there are 1–5 samples with gene
expression profiles. In order to increase the reliability of DNB
result, the slide window method is incorporated into DNB model to
process data. We calculate these three criteria of human and chimpanzee
(Additional file [133]2). In addition, the Matlab package of DNB and
the operation methods of DNB model are available at
[134]http://sysbio.sibcb.ac.cn/cb/chenlab/software.htm
Functional analysis
DNBs and DEGs for the two species are used for pathway enrichment
analysis by IPA [[135]42] (Additional file [136]6), and network
analysis is used to investigate the correlations of DNBs and DEGs in
IPA network analysis. All additional results are described in
Additional file [137]6 in this paper.
Supplementary information
[138]12864_2020_6465_MOESM1_ESM.jpg^ (656KB, jpg)
Additional file 1. Hierarchical cluster analysis of normalized DPLEC
datasets (Human, Chimpanzee, Monkey), based on 17,429 expressed genes.
The red represents human, the blue represents chimpanzee and the yellow
represents macaque.
[139]12864_2020_6465_MOESM2_ESM.jpg^ (739.1KB, jpg)
Additional file 2. Detecting the tipping points for the infant brain
development of human and chimpanzee. Detecting the tipping points for
two data sets, human (a, b, c, d) and chimpanzee (e, f, g, h). The
infant human contain 13 samples (age range from 0 to 0.9 years old).
The infant chimpanzee contains 9 samples (age range from 0 to 6.3 years
old). Subfigures a and e represent the composite index (see
[140]Methods, CI in Eq.([141]1)), Subfigures b and f represent the mean
SDs in the DNB of human and chimpanzee (see [142]Methods, SD in
Eq.([143]1)), Subfigures c and g represent PCCs in the DNB (see
[144]Methods, PCCd in Eq.([145]1)), Subfigures d and h are the PCCs
between the DNB and other molecules (see [146]Methods, PCCo in
Eq.([147]1)).The results of the figure show the effectiveness of the
DNB model by using our data sets and 3 and 1 month are the tipping
points of two species.
[148]12864_2020_6465_MOESM3_ESM.xls^ (15KB, xls)
Additional file 3. 371 DNBs of human and 132 DNBs of chimpanzee. There
are one gene which are overlaps of two parts DNBs.
[149]12864_2020_6465_MOESM4_ESM.xls^ (106.4KB, xls)
Additional file 4. The DEGs of human and chimpanzee around the tipping
point. The overlap genes between DNBs and DEGs of two species.
[150]12864_2020_6465_MOESM5_ESM.doc^ (20.4KB, doc)
Additional file 5. Sample Characteristics.
[151]12864_2020_6465_MOESM6_ESM.xls^ (1,011.5KB, xls)
Additional file 6. Detailed DNB genes and DEGs IPA analysis summary and
network analysis results.
Acknowledgements