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Table 4 Network and pathway analysis showing the most likely candidate genes with functional relevance in autoimmunity

From: Novel and rare functional genomic variants in multiple autoimmune syndrome and Sjögren’s syndrome

Gene

Network algorithm (P value)

Network node

GeneGO ontology process

Processes P value

LRP1

Analyse network (3.03e−7)

PKC alpha (phosphorylation of the A2M receptor encoded by LRP1) (Figure 1)

Phagocytosis

7.596e−8

LRP1

Analyse network (3.03e−7)

PKC-alpha (phosphorylation of the A2M receptor encoded by LRP1) (Figure 1)

Regulation of phospholipase A2 activity

3.597e−13

LRP1

Analyse network (3.03e−7)

PKC-alpha (phosphorylation of the A2M receptor encoded by LRP1) (Figure 1)

Negative regulation of apoptosis

6.703e−21

LRP1

Shortest paths (N/A)

LRP1 (transcription regulation) IFN-gamma (Figure 2)

Response to lipopolysaccharide

7.616e−21

MICAL1

Analyse network (7.32e−10)

PKC-mu MICAL1 (Figure 3)

Negative regulation of apoptotic process

7.901e−15

MICAL1

Analyse network (7.32e−10)

PKC-mu MICAL1 (Figure 3)

Actin filament depolymerisation

2.34e−2

MICAL1

Analyse network (7.32e−10)

PKC-mu MICAL1 (Figure 3)

Negative regulation of cysteine type endopeptidase activity

5.403e−3

  1. The first P value is of the constructed network. This gives the probability of obtaining a certain number of genes obtained from a given network algorithm from the input list by random chance. Also given are the network nodes and their corresponding biological processes that may have functional importance in ADs.