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A Meta-analysis of immune signaling pathways between human type 2 diabetic tissue and mouse bone repair

James McCauley

Seton Hall University, 400 South Orange Avenue, South Orange, NJ, USA

E-mail : bhuvaneswari.bibleraaj@uhsm.nhs.uk

Ashley Walsh

Seton Hall University, 400 South Orange Avenue, South Orange, NJ, USA

Justin F Bejar

Seton Hall University, 400 South Orange Avenue, South Orange, NJ, USA

Jason Ianni

Seton Hall University, 400 South Orange Avenue, South Orange, NJ, USA

Mannesah Georges

Seton Hall University, 400 South Orange Avenue, South Orange, NJ, USA

Zaneta Zachwieja

Seton Hall University, 400 South Orange Avenue, South Orange, NJ, USA

Robert Gray

Seton Hall University, 400 South Orange Avenue, South Orange, NJ, USA

Tinchun Chu

Seton Hall University, 400 South Orange Avenue, South Orange, NJ, USA

Jessica Cottrell

Seton Hall University, 400 South Orange Avenue, South Orange, NJ, USA

Sulie L. Chang

Seton Hall University, 400 South Orange Avenue, South Orange, NJ, USA

DOI: 10.15761/BRCP.1000202

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Abstract

Type II diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insulin insensitivity, hyperglycemia, and immune dysregulation. Recent findings have shown that T2DM has a significant impact on the skeletal system, including the impairment of the fracture healing process which commonly leads to non-union. Throughout the process, heterotypic interactions between different immune cells are required for the recruitment and differentiation of osteogenic cells vital for fracture repair. The purpose of this study was to compare inflammatory gene expression induced in T2DM with those occurring during fracture repair with a specific focus on immune cell expression. Using publicly available RNA-seq datasets and Ingenuity Pathway Analysis (IPA), we compared gene expression profiles of human diabetic and non-diabetic data to gene expression profiles of mice post-fracture. IPA core analysis of diabetic vs. non-diabetic immune gene expression revealed top canonical pathways (p-value < 1.0 x 10-6) involved in the Th1 Activation Pathway, Granulocyte Adhesion and diapedesis, and IL-7 Signaling, had an average activation z-score of -2.373, thus exhibiting a predicted inhibition when compared to non-diabetic controls. Additionally, top upstream inflammatory regulators such as TNF-α, IL-1B, and IL-6 also exhibited an average 3.5 log-fold reduction in expression. When examining gene expression in normal fracture repair, previous upstream inflammatory regulators exhibit an average 2.1 log-fold increase. Our results suggest that during fracture repair, the early immune response required for recruitment of osteogenic cells and repair is impaired in T2DM signaling.

Keywords

inflammation, type 2 diabetes, fracture, myeloid, ingenuity pathway analysis

Abbreviations

T2DM: Type 2 Diabetes Mellitus; MSCs: Mesenchymal Stem Cells.

Introduction

In type 2 diabetes mellitus (T2DM), the glucose homeostatic function of insulinis impaired which leads to negative physiological changes ] like failed bone healing. Inthe U.S. annually, 790,000 diabetic fractures do not heal properly each costing $30,000more in patient care Unfortunately, the connection between the immune system, T2DM,and fracture repair is stillunclear. After fracture, the acute inflammatory response recruits’ cells to supporthematoma formation, callus formation, and osteogenesis Recruited mesenchymal stem cells(MSCs) can differentiate into osteogenic cells required for the generation of the callus Thisstabilizes the fracture and acts as a scaffold for deposition of mature lamellar bone In diabetics,this process takes significantly longer. Hamon et al. observed that diabetic rats have increasedrates of non-union and lower bone mineral density at 12 weeks post-fracture when compared tonon-diabetics Roy et al. correlated these changes with declines in transcription factors suchas Dlx5 are inhibited under hyperglycemic conditions and required for osteogenicdifferentiation. This inhibition is thought to reduce MSC commitment, which depletes theavailable osteoprogenitor cells necessary for fracturerepair. Recent studies have shown that immune cells such as macrophages are also criticalfor fracture repair. Mouse macrophage ablation studies in fracture models show asignificant impairment in the fracture healing process These myeloid derived immune cellssecrete mediators which regulate processes like matrix synthesis and osteogenesis Similarimmune components are known to be dysregulated in TD2M Therefore, in this study weuse Ingenuity Pathway Analysis to compare human T2DM gene expression profiles with thoseof mice post-fracture to determine connections between immune dysregulation, T2DM, andfracture repair.

Methods

Literature search utilizing ingenuity pathway analysis

The Ingenuity Pathway Analysis (IPA, Qiagen, The Netherlands) Knowledge Basewas utilized to locate articles with RNA-seq and gene expression data related to diabetes,fracture repair, and myeloid cell activity. IPA’s BioProfiler function was used to search for specificgene functions and molecule activity while excluding drug and chemical markers. Theliterature search yielded only two studies, “Diabetic complications and dysregulated innate immunity”and “Transcriptomic signatures reveal immune dysregulation in human diabetic andidiopathic gastroparesis” that contained RNA-seq data that overlapped with our search criteriaand were used for subsequent meta-analysis and coreanalysis.

Comparison of gene expression in T2DM, non-diabetic, and acute fracture repair

First, the data were extrapolated and used to analyze transcriptome patterns ofhuman T2DM to non-diabetic and mouse non-diabetic unfractured to mouse non-diabeticpost-fracture with a specific focus on immune cell related gene expression andfunction. In Grover et al.’s study, gene expression data from smooth muscle wascompared between T2DM patients vs. non-diabetics controls Data were uploaded to IPA inExcel files and annotated prior to core analysis using IPA’s flexible file format. For data obtainedfrom Grover et al. 564 genes were inputted for analysis with 549 gene IDs successfully mappedand 15 gene IDs remaining unmapped and no additional cutoffs to fold-change in expression andp- values wereassigned.

In Bais et al.’s study, gene expression data was extracted at day 3 post-fracture, whichis established as part of the acute inflammatory phase of fracture repair in mice. For Bais etal. 16,505 genes were inputted for analysis with 13,454 gene IDs successfully mapped 3051gene IDs remaining unmapped. For this data set, cutoff values of -1.5 and +1.5 were implementedfor fold change in expression to reduce the analysis of genes inputted to 1998genes. Since both T2DM and fracture transcriptome represent sustained inflammatoryevents, these two datasets were compared to each other to find links between immunedysregulation, T2DM, and fracture repair that span both the mouse and humansystems.

Data IPA analysis

Predictions of the activation states of pathways and regulators was conductedthrough IPA’s z-scoring system. These z-scores act as a prediction model in which IPA canaccurately state if a specific pathway or molecule will be activated or inhibited based on geneexpression datasets uploaded to its core expression analysis feature. IPA can then compare theexpression patterns between these uploaded datasets and the existing datasets in the IPA KnowledgeBase. Any inconsistencies between the uploaded datasets and the IPA Knowledge Base willsubtract from the overall z-score while consistencies add to the z-score. A negative z-score isindicative of a predicted state of inhibition while a positive z-score represents a predicted stateof activation. When analyzing canonical pathways, the top 20 results (consisting of the lowest20 p-values) were selected for each category. For upstream regulators, the top 15 results(consisting of the lowest 15 p-values) wereselected.

Results

Canonical signaling pathways involved in T2DM dysregulation of the immune response

When the uploaded dataset from Grover et al. was uploaded to the IPA, IPA predicted the top 20 canonical pathways, based on lowest p-values, to be inhibited overall (Figure 1, blue- shaded bars). Immune and inflammatory signaling pathways such as the Th1 pathway, IL-7 pathway, and Granulocyte Adhesion and Diapedesis functions all exhibited an average negative z-score of -2.737 (Figure 1, Table 1).

Figure 1. Canonical signaling pathways involved in T2DM dysregulation of the immune response

Table 1. Z-scores and P-values of Top 7 Downregulated Canonical Pathways in T2DM

Pathway

Z-score value

p-value

TH2 Pathway

-2.11

2.22E-10

Granulocyte Adhesion and Diapedesis

-2.113

8.46E-09

STAT3

-1.414

1.31E-08

TH1 Pathway

-2.887

1.46E-07

Osteoathritis Pathway

-1

3.87E-07

iCOS-iCOSL Signaling T Helper Cells

-2.714

1.79E-06

IL-7 Signaling Pathway

-2.121

3.16E-06

Expression of Pro-inflammatory Mediators IL1-β and TNF-α are Significantly Inhibited in T2DM

In addition to top canonical pathways, IPA also predicted the activation states of similar upstream regulators using the same z-scoring system. In the T2DM dataset, inflammatory molecules TNF-α, IL-1β, and IL-6 were predicted to be inhibited with an average negative z-score of -5.952 (Table 1). Aside from cytokines, other endogenous inflammatory molecules such as prostaglandin E2 and leukotriene D4 were predicted to be inhibited with z-scores of -3.175 and -5.281, respectively (Table 2).

Table 2. Predicted activation states of inflammatory genes in type 2 diabetics

Upstream Regulator

Molecule Type

Predicted Activation State

Activation z-score

p-value of overlap

TNF

Cytokine

Inhibited

-6.036

9.84E-61

IL1β

cytokine

Inhibited

-6.451

2.83E-46

beta-estradiol

chemical - endogenous

Inhibited

-4.474

2.8E-40

PDGF BB

complex

Inhibited

-7.094

6.1E-40

TGFB1

growth factor

Inhibited

-4.843

1.29E-39

prostaglandin E2

chemical - endogenous

Inhibited

-3.175

5.51E-39

IFNG

cytokine

Inhibited

-4.492

1.5E-34

leukotriene D4

chemical - endogenous

Inhibited

-5.281

1.66E-34

GPER1

G-protein coupled receptor

Inhibited

-5.202

1.05E-33

NR3C1

nuclear receptor

Inhibited

-2.549

4.16E-33

IL2

cytokine

Inhibited

-4.739

1.52E-28

IGF1

growth factor

Inhibited

-4.599

1.56E-28

CD40LG

cytokine

Inhibited

-4.404

2.23E-28

HGF

growth factor

Inhibited

-4.95

2.44E-28

IL6

cytokine

Inhibited

-5.371

1.96E-25

Canonical signaling pathways involved in early fracture repair in non-diabetic conditions

Gene expression from early fracture repair in non-diabetic conditions were uploaded to IPA’s core expression analysis feature. The top 20 canonical pathways from this expression dataset reveal varied states of pathway inhibition (blue shaded bars) and ac Pathway and the LPS/IL-1 Mediated Inhibition of RXR Function with an average z-score of 2.745 (Figure 2, Supplemental Table 3). Clear bars are indicative of a z-score of 0 and thus have no difference in activity while gray shaded bars, such as Atherosclerosis signaling, indicate that no general prediction pattern was available from IPA’s z-scoring system.

Figure 2. Canonical signaling pathways involved in early fracture repair in non-diabetic conditions

Figure 3. Predicted activity of downstream TNF-α signaling targets in type II diabetes

Table 3. Z-Scores and P-values for Top 7 regulated canonical pathways in non-diabetic fracture healing

 

Z-score value

p-value

GP6 Signaling Pathway

2.887

5.40E-05

Osetoarthritis Pathway

1.604

8.93E-05

LPS/IL-1 Inhibiition of RXR Function

3.783

1.65E-04

Inhibition of Matrix Metalloproteases

-0.816

2.15E-04

Apelin Liver Signaling Pathway

2

2.25E-03

Gαs Signaling

1.134

-2.84E-03

Dermatan Sulfate Biosynthesis (Late Stage)

-1.342

-3.57E-03

Table 4. Predicted activation states of inflammatory genes in non-diabetic fracture healing

Upstream Regulator

Molecule Type

Predicted Activation State

Activation z-score

p-value of overlap

TGFB1

growth factor

Activated

5.235

91.94E-16

FGF2

growth factor

Activated

2.25

6.93E-14

BMP2

growth factor

Activated

3.484

1.71E-12

CD44

other

Activated

2.373

8.23E-11

TNF

cytokine

Activated

2.908

2.11E-10

KRAS

enzyme

Inhibited

-2.154

7.27E-10

SPP1

cytokine

Activated

2.174

1.88E-09

SMAD7

transcription regulator

Inhibited

-2.284

2.67E-09

RXRB

ligand-dependent nuclear receptor

Inhibited

-2.236

3.12E-09

RUNX2

transcription regulator

Activated

2.391

5.48E-09

IGF1

growth factor

Activated

3.239

1.01E-08

P38 MAPK

group

Activated

3.325

2.66E-08

Jnk

group

Activated

3.413

3.05E-08

IL1β

cytokine

Activated

3.311

3.09E-08

IL1α

cytokine

Activated

4.221

8.15E-08

Expression of pro-inflammatory mediators IL1-β and TNF-α is upregulated early during fracture repair in non-diabetic conditions

Gene expression data sets pertaining to fracture repair in non-diabeticconditions uploaded to IPA’s core analysis predicted inflammatory molecules IL-1α, IL1-β, and TNF-αto be activated in early fracture repair with respective z-scores of 3.311, 4.221, and 2.908 (). Additionally, genes related directly to the initiation and progression of fracture repair, BMP2and RUNX2, were also predicted to be activated early during fracture repair innon-diabetic conditions (respective z-scores of 3.484 and2.391).

Inhibition of upstream inflammatory mediator TNF-α results in general suppression of downstream transcription factors involved in inflammation and enhancement of osteogenesis

IPA’s mechanistic network feature for reduced TNF-α activity in T2DM revealsan overall suppression of downstream signaling targets (). The signaling networksscores predicted activation states of downstream targets based on the z-scores of upstreamregulators seen in table 1. The downstream network shows that all downstream signaling are predictedto have suppressed or inhibited activity under hyperglycemic conditions. Some of thesetargets include transcription factors involved in inflammation (NF-kβ) and transcriptionfactors implicated in the enhancement of osteogenesis(STAT3).

Discussion and conclusion

The immune response plays a significant role in the process of fracture repair and itis often dysregulated in T2DM. These inflammatory responses are driven by immunesignaling pathways and the release of cytokines at the fracture site Our analysis shows asignificant dysregulation and suppression of canonical immune signaling pathways in T2DM includingthe Th1, granulocyte adhesion and diapedesis, and TNF-α regulation which all play a significantrole in host inflammatory responses (). The Th1 response requires high levels of inflammation and causes a strongcell-mediated immune response The Th1 response is important to macrophage activation, whichis essential to fracture repair We hypothesize that a reduction in Th1 signaling activityin T2DM could reduce available macrophages at the fracture site contributing to impairedfracture repair. Inflammatory cytokines TNF-α and IL-6 were also predicted to be inhibited inT2DM and activated post-fracture (). Interestingly, TNF-α and IL-6 are both secreted byTh1 cell subsets, which in turn activate macrophages Thus, a decrease in theseinflammatory cytokines could be related to the decrease in the Th1 pathway response and a reductionof macrophage activity at the fracture site. In addition to the Th1 pathway, thegranulocyte adhesion and diapedesis pathway is vital for myeloid cells such as macrophages andneutrophils to reach the fracture site and continue to promote this necessary inflammation. A reductionin this activity would result in reduced myeloid cell persistence at the fracture site, diminishingthe inflammatory response

Our data shows that in T2DM, inflammatory cytokines important for fracture repairare down regulated significantly (i.e. IL-1β and TNF, Comparing Table 1 to Table 2, z-score >-2). IL-1β functions during early fracture repair to recruit the necessary osteogenic cells andis consistent with IPA analysis of the post-fracture data set which shows activation ofIL-1β (). When IL1-β deficient mice were given IL-1β during fracture repair, fracturerepair improved when compared to controls Interestingly, other studies have shown IL-1βcan also be a potent inhibitor of chondrogenesis and an activator of osteogenesis In thissense, our findings could indicate that suppression of IL-1β in T2DM impairs the earlyinflammatory response and decreases osteoblast bonedeposition. TNF-α also plays a significant role in fracture healing by promoting MSCrecruitment and differentiation to osteoclast [22]. Data has shown that treatment with low doses ofTNF-α can enhance the rate of callus mineralization and fracture healing in rodent fracture modelsTranscription factors downstream of TNF-α such as NF-kβ and STAT3 were also predicted tobe suppressed in our signaling network (). NF-kβ and STAT3 activation are essentialfor osteoclasts and osteoblasts function During early fracture repair osteoclasts assist incallus reabsorption while osteoblasts deposition mature bone. STAT3 deficient mice afterfracture have impaired bone formation with reduced numbers of osteoblasts and increasedosteoclasts . It is hypothesized that a reduction of these mediators in T2DM could reduce theMSC number at the fracture site and negatively affect osteoprogenitor recruitment andfunction.

Overall, our data suggests that inflammatory pathways and molecules necessaryduring the early stages of fracture repair are suppressed in T2DM. Our IPA analysis providesinsight into which signaling pathways and transcription targets are important when elucidatingthe connection between the immune system, T2DM, and bonerepair.

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Editorial Information

Editor-in-Chief

Cory J. Xian
University of South Australia

Article Type

Research Article

Publication history

Received: February 05, 2020
Accepted: February 23, 2020
Published: February 26, 2020

Copyright

©2020 McCauley J. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Citation

McCauley J, Walsh A, Bejar JF, Ianni J, Georges M, et al. (2020) A Meta-analysis of immune signaling pathways between human type 2 diabetic tissue and mouse bone repair. Biomed Res Clin Prac 5: DOI: 10.15761/BRCP.1000202

Corresponding author

Sulie L. Chang

Seton Hall University, 400 South Orange Avenue, South Orange, NJ, USA

E-mail : bhuvaneswari.bibleraaj@uhsm.nhs.uk

Figure 1. Canonical signaling pathways involved in T2DM dysregulation of the immune response

Figure 2. Canonical signaling pathways involved in early fracture repair in non-diabetic conditions

Figure 3. Predicted activity of downstream TNF-α signaling targets in type II diabetes

Table 1. Z-scores and P-values of Top 7 Downregulated Canonical Pathways in T2DM

Pathway

Z-score value

p-value

TH2 Pathway

-2.11

2.22E-10

Granulocyte Adhesion and Diapedesis

-2.113

8.46E-09

STAT3

-1.414

1.31E-08

TH1 Pathway

-2.887

1.46E-07

Osteoathritis Pathway

-1

3.87E-07

iCOS-iCOSL Signaling T Helper Cells

-2.714

1.79E-06

IL-7 Signaling Pathway

-2.121

3.16E-06

Table 2. Predicted activation states of inflammatory genes in type 2 diabetics

Upstream Regulator

Molecule Type

Predicted Activation State

Activation z-score

p-value of overlap

TNF

Cytokine

Inhibited

-6.036

9.84E-61

IL1β

cytokine

Inhibited

-6.451

2.83E-46

beta-estradiol

chemical - endogenous

Inhibited

-4.474

2.8E-40

PDGF BB

complex

Inhibited

-7.094

6.1E-40

TGFB1

growth factor

Inhibited

-4.843

1.29E-39

prostaglandin E2

chemical - endogenous

Inhibited

-3.175

5.51E-39

IFNG

cytokine

Inhibited

-4.492

1.5E-34

leukotriene D4

chemical - endogenous

Inhibited

-5.281

1.66E-34

GPER1

G-protein coupled receptor

Inhibited

-5.202

1.05E-33

NR3C1

nuclear receptor

Inhibited

-2.549

4.16E-33

IL2

cytokine

Inhibited

-4.739

1.52E-28

IGF1

growth factor

Inhibited

-4.599

1.56E-28

CD40LG

cytokine

Inhibited

-4.404

2.23E-28

HGF

growth factor

Inhibited

-4.95

2.44E-28

IL6

cytokine

Inhibited

-5.371

1.96E-25

Table 3. Z-Scores and P-values for Top 7 regulated canonical pathways in non-diabetic fracture healing

 

Z-score value

p-value

GP6 Signaling Pathway

2.887

5.40E-05

Osetoarthritis Pathway

1.604

8.93E-05

LPS/IL-1 Inhibiition of RXR Function

3.783

1.65E-04

Inhibition of Matrix Metalloproteases

-0.816

2.15E-04

Apelin Liver Signaling Pathway

2

2.25E-03

Gαs Signaling

1.134

-2.84E-03

Dermatan Sulfate Biosynthesis (Late Stage)

-1.342

-3.57E-03

Table 4. Predicted activation states of inflammatory genes in non-diabetic fracture healing

Upstream Regulator

Molecule Type

Predicted Activation State

Activation z-score

p-value of overlap

TGFB1

growth factor

Activated

5.235

91.94E-16

FGF2

growth factor

Activated

2.25

6.93E-14

BMP2

growth factor

Activated

3.484

1.71E-12

CD44

other

Activated

2.373

8.23E-11

TNF

cytokine

Activated

2.908

2.11E-10

KRAS

enzyme

Inhibited

-2.154

7.27E-10

SPP1

cytokine

Activated

2.174

1.88E-09

SMAD7

transcription regulator

Inhibited

-2.284

2.67E-09

RXRB

ligand-dependent nuclear receptor

Inhibited

-2.236

3.12E-09

RUNX2

transcription regulator

Activated

2.391

5.48E-09

IGF1

growth factor

Activated

3.239

1.01E-08

P38 MAPK

group

Activated

3.325

2.66E-08

Jnk

group

Activated

3.413

3.05E-08

IL1β

cytokine

Activated

3.311

3.09E-08

IL1α

cytokine

Activated

4.221

8.15E-08