Page 61 - Biennial Report 2018-20 Jun 2021

IL23 is responsible for causing autoimmune inflammatory diseases. Since psoriasis is an
autoimmune disease this data pointed towards the underlying cytokine pathways being
responsible for development of this disease.
Inflammation is a common underlying theme connecting atherosclerosis and psoriasis and
comorbidities to Type 2 Diabetes. In addition, lipids are involved along with lipoprotein particles
of different categories. However, one comorbidity may be associated with the heart, whereas
the other comorbidity may be associated with the skin. The principal mechanism of deteriorated
metabolic homeostasis leading to diabetic dyslipidemia associated comorbidity, such as
atherosclerosis and psoriasis, is hyper immune activation. Since the central regulator of immune
response is nuclear factor-kappa B (NF-kB), it was hypothesized to understand and address the
underlying cues through the NF-kB network pathway model first. The network model
development and simulation were performed on CellDesigner using inbuilt functions as
described in the literature. Pathway connections of the components having HGNC approved
symbol, were assembled using KEGG and reactome pathway databases according to preference
to annotations in reactome pathways. In silico overexpression or knockdown of the NF-kB system
regulators for inferring the biological significance through numerical output was used. Heuristic
trends were procured through which the differential effect of perturbations was inferred. It was
observed that in the instance of immune insufficiency, MAP3K14 and PIN1 activation leading to
increased NF-kB activity could be considered for potential therapeutics. In the case of hyper
immune-activation circumstance, activation of PIAS3, PPARG and PDLIM2 activation could
repress the NFKB1 complex activity; whereas activation of GSK3B and NLRP12 activation could
reduce the NFKB2 complex activity.

The genes implicated in diabetic dyslipidemia associated atherosclerosis were next identified.
Abstracts from PubMed using the keyword ‘type 2 diabetes’ were extracted first, while further
it was curated for ‘dyslipidemia’. 4993 dyslipidemia abstracts in 176403 diabetic abstracts were
obtained. They were used as the first corpus in text mining and manual curation of genes. In this
exercise, 31 common genes under atherosclerosis under diabetic dyslipidemia were identified,
viz., ADIPOQ, ALB, APOA1, APOA5, CAPN10, CETP, CRP, DPP4, EDN1, FABP2, FABP4, FABP5,
FGF21, HGF, KLF14, LEP, LPL, MIF, MOK, MPO, MTHFR, NOS3, NPY, PCSK9, PON1, PPARA, PPARG,
RETN, SIRT1, TCF7L2, and TNFRSF11B, respectively.

Subsequently, a network through CellDesigner 4.4 software was obtained. In this network,
cytokines IL23A, IL23R and IL12B were found to be linked through transcription factors STAT1,
STAT3 and STAT4.

The model captures the degradation of IkB/NFKBIA, proteolytic processing of p100 to p52 and
p105 to p50 and posttranslational modifications at different sites on p65/RELA, RELB,
p50/NFKB1, and p52/NFKB2 proteins. The network model was iteratively improved to eliminate
connection errors through cycles of simulation and comparison with experimental results
reported in literature. With the goal of identifying genes and miRNAs implicated in type 2
diabetic dyslipidemia associated atherosclerosis and psoriasis, 176403 abstracts containing type
2 diabetic keywords were retrieved through PubMed upto 12th February 2019 publication date.
4993 abstracts containing dyslipidemia were extracted and consecutively from this subset 659
atherosclerosis abstracts and 30 psoriasis abstracts were extracted.

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