The authors have declared that no competing interests exist.
Conceived and designed the experiments: MPA SS. Performed the experiments: SS MPA. Analyzed the data: SS MPA. Contributed reagents/materials/analysis tools: MPA. Wrote the paper: MPA SS. Idea conceived by: MPA. Analysis done by: SS.
Increasing epidemiological studies in patients with psoriasis report the frequent occurrence of one or more associated disorders. Psoriasis is associated with multiple comorbidities including autoimmune disease, neurological disorders, cardiometabolic diseases and inflammatory-bowel disease. An integrated system biology approach is utilized to decipher the molecular alliance of psoriasis with its comorbidities. An unbiased integrative network medicine methodology is adopted for the investigation of diseasome, biological process and pathways of five most common psoriasis associated comorbidities. A significant overlap was observed between genes acting in similar direction in psoriasis and its comorbidities proving the mandatory occurrence of either one of its comorbidities. The biological processes involved in inflammatory response and cell signaling formed a common basis between psoriasis and its associated comorbidities. The pathway analysis revealed the presence of few common pathways such as angiogenesis and few uncommon pathways which includes CCKR signaling map and gonadotrophin-realising hormone receptor pathway overlapping in all the comorbidities. The work shed light on few common genes and pathways that were previously overlooked. These fruitful targets may serve as a starting point for diagnosis and/or treatment of psoriasis comorbidities. The current research provides an evidence for the existence of shared component hypothesis between psoriasis and its comorbidities.
Psoriasis is a chronic immune mediated skin disease. The disease presents itself with well circumscribed, red or silvery scaly plaques [
The occurrence of one or more disorders in association with a particular disease has recently gained interest in various medicinal divisions including dermatology [
The current work aims to decipher the shared component hypothesis between psoriasis and its five associated common comorbidities which includes myocardial infarction (MI), type II diabetes (T2DM), obesity, rheumatoid arthritis (RA) and Alzheimer’s disease (AD). The psoriasis associated comorbidities would be associated at the molecular level by common genes, proteins, biological processes and pathways. The network medicine approach has been utilized to construct individual diseasomes. The interactomes are explored to identify the biological processes and pathways linking psoriasis with its comorbidities.
Gene expression raw data (CEL files) were downloaded from NCBI GEO database [
Accession ID | Disease | Number of samples | Contributor |
---|---|---|---|
GSE4757 | Alzheimer’s disease | 20 | Barth AS |
GSE25724 | Type II diabetes | 13 | Dominguez V |
GSE3585 | Myocardial infarction | 12 | Barth AS |
GSE9624 | Obesity | 11 | Aguilera CM |
GSE48780 | Rheumatoid arthritis | 83 | Dennis G Jr |
GSE13355 | Psoriasis | 180 | Gudjonsson JE |
The microarray expression sets were processed individually in a similar way to remove bias. The raw files from different studies were processed using the bioconductor packages in R [
The association between psoriasis and its comorbidities was termed as “diseasome”. The two diseases were linked if they share the variations in similar set of genes. Proteins encoded by each differentially expressed gene were identified for the construction of the diseasome. The human proteome interactome was obtained based on the interactions reported by the HPRD server [
ProteinsDis1 Proteins and ProteinDis2 Proteinswere the proteins associated with disease1 and disease2 respectively. ProteinsDis1→Dis2 Proteinswere the proteins associated with disease1 that show interactions with the proteins associated with disease2 (vice versa for ProteinsDis2→Dis1 Proteins). ∩ was the intersection operator denoting the number of common proteins between the diseases and ∪ operatordenote the total number of proteins participating in both the disease categories. The sets represented within the vertical bars indicate their cardinality.
To explore the significance of biological functions of the differentially expressed proteins in each disease [
The Jaccard coefficient measures the degree of similarity between the psoriasis comorbidities. Dis1 and Dis2 correspond to psoriasis and its comorbidities. Biological process (BP) of Dis1 and Dis2 represents the biological processes contributed by psoriasis and its individual comorbidity respectively, whereas pathways of Dis1 and Dis2 are the biological pathways in which the proteins associated with the comorbidities participate. The calculated measures were visualized as heat-maps constructed using gitools [
The differential expression analysis of psoriasis microarray data resulted in 507 differentially expressed genes (DEG) (113-upregulated; 394-downregulated), on submitting the differentially expressed genes of psoriasis transcriptome to DAVID server, around fourteen major disease categories were enriched (
Disease class | Disease | Genes involved | |
---|---|---|---|
Musculoskeletal Diseases | RA | 16 | PLAT, MMP9, TLR2, GGH, PTPN22, CXCR2, MMP1, MMP12, TYMS, IL12RB1, CCR5, CD274, IL1B, SERPINA1, FCGR3B, SELE |
Neoplasms | Esophageal cancer | 4 | TYMS, IL8, CXCR2, MMP1 |
Neoplasms | Stomach Neoplasms | 5 | TYMS, IL8, CXCR2, MMP1 |
Neoplasms | Leiomyoma | 3 | IL12RB1, IL8, IL1B |
Neoplasms | Oral cancer | 5 | IL8, MMP9, TGFA, CYP2E1, MMP1 |
Virus Diseases | Hepatitis C | 10 | IFI27, IL12RB1, CCR5, LDLR, IL19, IL1B, OAS1, CXCR2, MX1, IL20 |
Virus Diseases | Hepatitis B | 6 | CCR5, OAS3, OAS1, OAS2, MX1, STAT1 |
Otorhinolaryngologic Diseases | Hearing loss/deafness | 5 | PLAT, SLC26A4, GJB6, ESPN, GJB2 |
Bacterial Infections and Mycoses | Tuberculosis | 9 | IL12RB1, IL8, TLR2, PTPN22, IL1B, CXCR2, SERPINA1, CYP2E1, STAT1 |
Nervous System Diseases | Subarachnoid hemorrhage | 5 | MMP9, SERPINA3, IL1B, MMP12, MMP1 |
Nervous System Diseases | Multiple sclerosis | 15 | IL8, MMP9, CCR1, APOC1, PTPN22, CXCR2, OAS1, IL7R, CXCL10, CCR5, IL1B, CD24, MX1, FCGR3B, SELE |
Nervous System Diseases | AD | 3 | C3,CD14, DNM3 |
Digestive System Diseases | Pancreatitis, chronic | 5 | IL8, PRSS2, PRSS3, SERPINA3, IL1B |
Stomatognathic Diseases | Periodontitis | 9 | PLAT, CCR5, S100A8, MMP9, TLR2, IL1B, SERPINA1, FCGR3B, MMP1 |
Respiratory Tract Diseases | COPD | 7 | IL8, MMP9, SERPINA3, IL1B, SERPINA1, MMP12, MMP1 |
Respiratory Tract Diseases | Asthma | 15 | CYP2J2, MMP9, TLR2, CXCR2, EHF, IL12RB2, CCR5, CXCR4, FCGR1B, SERPINA3, FUT3, IL1B, SERPINA1, FUT2, SELE |
Cardiovascular Diseases | Atherosclerosis | 13 | PLAT, F12, CYP2J2, LDLR, CCR5, SELL, MMP9, APOC1, TLR2, IL1B, FCGR3B, SELE, MMP1 |
Cardiovascular Diseases | MI | 3 | JAK2, CD14, CCL1 |
Cardiovascular Diseases | Coronary artery disease | 7 | PLAT, CCR5, LDLR, MMP9, IL1B, SELE, MMP12 |
Digestive System Diseases | Cirrhosis; pancreatitis | 3 | IL8, IL1B, CYP2E1 |
Skin and Connective Tissue Diseases | Systemic lupus erythematosus | 9 | CCR5, IL8, CFB, TLR2, PTPN22, IL1B, CXCR2, FCGR3B, SELE |
Hemic and Lymphatic Diseases | Sarcoidosis; tuberculosis | 3 | IL12RB2, IL12RB1, MMP1 |
Nutritional and Metabolic Diseases | T2DM | 2 | IL12RB2, IL12RB1 |
Nutritional and Metabolic Diseases | Obesity | 5 | CXCL1, DPN, NAIP, PAPPA, IL24 |
#Number of genes enriched in each disease category; Diseases are classified based on the MeSH disease hierarchy
Independent meta-analysis was carried out for psoriasis and its co-morbidity using their respective microarray expression data. The aim of the meta-analysis was to identify the genes which were significantly upregulated and down regulated in diseased condition when compared with the normal samples [
The commonalities between the diseases were assessed based on their interaction patterns. The number of shared genes or proteins in the psoriasis diseasome ranged from 31 (MI) to 312 (T2DM) (
Yellow nodes—proteins involved in psoriasis, red nodes—common proteins shared by AD and psoriasis and blue nodes—indirect interactions.
Violet nodes—proteins in psoriasis, red nodes—common proteins shared by MI and psoriasis and blue nodes—indirect interactions.
Green nodes—proteins involvement in psoriasis, red nodes—common proteins shared by T2DM and psoriasis and blue nodes—indirect interactions.
Pink nodes—proteins involved in psoriasis, red nodes—common proteins shared by obesity and psoriasis and blue nodes indicate indirect interactions.
Brown nodes—proteins involvement in psoriasis, red nodes—common proteins shared by RA and psoriasis and blue nodes—indirect interactions.
Number of proteins shared between psoriasis and its comorbidities. MCI shows the strength of association between psoriasis and its comorbidities. The association becomes stronger with the increasing number of shared genes and high MCI.
The deregulation of common set of genes either in similar or opposite direction can be an underlying cause for the comorbidities. To generate the molecular interpretation of the comorbidities, we compared the direction of dysregulation of the genes shared by psoriasis and its comorbidities with the help of meta-analysis (
(a) Proteins upregulated (b) proteins downregulated.
To identify the biological functions shared by the psoriasis and its comorbidities, a functional enrichment analysis was performed based on the BP. RA shared the highest number of overlapping BP with psoriasis. The list followed the order of T2DM, obesity, AD and MI starting from highest to lowest overlapping processes (
Each cell is colored according to the Jaccard correlation coefficient which represents the similarity between the comorbidities considering, (a) biological process and (b) biological pathways. The MI shares the highest JC in biological process with psoriasis and T2DM shares the highest JC in pathway annotation
We further investigated the pathways that were common between the psoriasis and its associated comorbidities (
The availability of enormous amount of information from various communities of science makes it essential to appropriately mine out and connect them in a systematic network which allows the creation of new hypothesis. This approach has a probable way to bring about new hypothesis that are not self-evident. In the current work, we adopted an integrative approach by combining the traditional gene expression analysis with the information derived from different databases with the help of bioinformatics.
The network medicine based investigation of five psoriasis comorbidities presented in this work reveals the existence of common genes/ proteins, biological process and pathways. In total, these observations highlight the shared component hypothesis of the psoriasis diseasome leading to the discovery of precise molecular connections between psoriasis and its comorbid diseases. The comorbidities occurring with psoriasis have a major impact in the nature of the disease. Yet the precise mechanisms were not evident. To our knowledge, this is the first study utilizing comprehensive and systematic bioinformatics strategy to investigate the shared component hypothesis [
The proposed network protocol not only provides a global analysis of the proteins but also presents a detailed view on specific proteins and their association with the comorbidity under the study. We noted the appearance of apolipoprotein E (ApoE) in psoriasis and AD. Lipid metabolism is the common term connecting both the disease. ApoE polymorphisms were shown to be associated with both the diseases disrupting the lipid metabolism. When the direction of regulation was considered the gene was downregulated in both the cases as established by the previous reports [
The findings of our work reveal that the psoriasis comorbidities are related at the molecular level that may contribute to their co-occurrences. In this context, the BP annotation identified several process of inflammation such as defence response and immune response which were enriched in all the comorbidities. The pathway annotation also revealed the presence of inflammatory pathways such as inflammation mediated by chemokines and cytokine signaling pathway, integrin signaling pathway and Wnt signaling pathway. The search for inflammatory links was carried out for all the diseases against published literatures.
The production of amyloid-β peptides can activate the innate immune response and evoke AD. Pattern recognition receptor (PRR) such as C1q is involved in complement cascade activation in the brain. The PPRs were also involved in the induction of pro-inflammatory signaling pathways in AD [
Psoriasis and its associated comorbidities highlight psoriasis as a paradigmatic disorder. The comprehensive network based approach investigated the shared component hypothesis existing between psoriasis with its associated co-morbidities. The findings suggest that the most prevalent psoriasis comorbidities were interlinked through common molecular connections which were evidenced by their shared biological functions and pathways. Significant overlap was observed in the biological process and pathways involved in inflammation in most of the comorbidities establishing a link between them. The work identified few associations in the biological processes and molecular pathways which were previously overlooked in majority of the diseases. The current research also shed light on few multimeric novel targets and pathways which can be targeted to offer diagnosis and/or cure for psoriasis along with its associated co-morbidities.
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The common biological processes between psoriasis and its comorbidities were highlighted.
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The common biological pathways between psoriasis and its comorbidities are highlighted.
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We thank VIT University for providing the computational facilities.