**7. Future trends and conclusion**

**6. Comparable chemicals**

**Term Overlap Adjusted** 

116 Bisphenol A Exposure and Health Risks

**Sch**

**ASD**

**AD**

MIR‐141, MIR‐200A

**BD**

**P‐value**

MIR‐368 3/40 0.0061 9.16 DLX1, MEF2C, BDNF

MIR‐191 2/29 0.0483 4.45 BDNF, FOXP1

MIR‐498 3/114 0.0232 6.98 MECP2, CRH, PAM MIR‐101 4/257 0.0232 6.83 APP, MAGI2, GNB1, FOS

MIR‐485‐3P 3/155 0.0336 5.97 CNR1, MAGI2, GNB1

MIR‐410 3/93 0.0317 6.41 NTRK2, SP4, NR3C1 MIR‐380‐3P 3/103 0.0317 6.27 SNAP25, BDNF, SP4

**Table 8.** miRNA for the BPA bi‐interacted genes in neurodevelopmental disorders.

MIR‐494 4/164 0.0251 6.71 SP4, GRIK2, CACNA1C, TAC1

MIR‐373 4/227 0.0483 5.01 GABRB3, DLG4, EN2, SOX9

**Combined score**

MIR‐485‐3P 7/155 0.0171 7.68 ADAMTS3, CNR1, NRXN1, MAGI2, GAD2, CPLX2,

MIR‐218 11/402 0.0171 7.60 KLF12, RELN, HTR7, NRXN1, MAGI2, GRIK2,

MIR‐380‐3P 5/103 0.0008 13.50 MEF2C, LRRTM3, BDNF, NRXN1, IL1RAPL1 MIR‐524 8/437 0.0009 12.82 DLX1, MEF2C, LRRTM3, PCDH9, IL1RAPL1,

MIR‐302C 5/243 0.0120 7.57 GABRB3, DLX1, PCDH9, TBL1X, FOXP1 MIR‐518C 4/149 0.0143 7.07 PCDH9, ITGB3, DNMT3A, NRXN2

MIR‐218 5/402 0.0232 7.15 MECP2, HTR7, MAGI2, GNB1, NPY1R

4/310 0.0325 6.07 MECP2, CNR1, DIXDC1, DRD2

**Genes**

NR3C1

TAC1, NR3C1, SLC6A1, RTN4, LGR4

TBL1X, SOX9, FOXP1

The CTD provides a way to group chemicals based upon their biological effects, instead of their physical or structural properties, which provides a novel way to view and classify genes and chemicals and will help advance testable hypotheses about environmental chemi‐ cal‐gene disease networks [61]. Comparable chemicals were curated for the possible shar‐ ing with many of the networks common to BPA in neurodevelopmental disorders (**Table 9**). Tetrachlorodibenzodioxin, benzo(a)pyrene, vehicle emissions and dibutyle phthalate, as the common environmental pollutants, were found interacting with 312, 269, 204 and 159 of the 403 BPA bi‐interacted genes in the NDs, respectively. Drugs such as valproic acid, acetaminophen,

With the existed data libraries (mainly CTD, GO, pathway, TFs and miRNA relate databases), bioinformatics softwares (Cytoscape, MCODE and Genemania) or web‐based tools (STRING, GEO, ArrayExpress, David and EnrichR), BPs, CCs, MFs, signal pathways and gene regula‐ tion in the BPA‐gene‐disease networks were presented. These data integration and curation yielded insight into the actions of BPA and provide a basis for developing hypotheses about the molecular mechanisms underlying the aetiology of the neurodevelopmental disorder ID, LD, Sch, ASD, AD and BD, although most of the other neurodevelopmental disorders showed no enough information to make a conclusion. The nervous system–related CCs such as neu‐ ron related, synapse related, dendrite and axon related are common in CC annotation; the commonly found MFs are neurotransmitter receptor binding or activity, signal transducer or receptor binding or activity; and the main commonly involved BPs include synaptic sig‐ nalling, cognition, learning or memory, behaviour, the development of nervous system and brain, and the regulation of the related BPs. Neuroactive ligand‐receptor interaction, dopami‐ nergic, glutamatergic and serotonergic synapse, monoamine transport, synaptic vesicle path‐ way may involve in the action of BPA in the neurodevelopmental disorders. Simultaneously, the BPA disease may share the common pathways with drug addictions (cocaine addiction, nicotine addiction and alcoholism), or other types of neurological diseases (Alzheimer's dis‐ ease, Rett syndrome and sudden infant death syndrome). Unique pathways might also con‐ tribute to the BPA action in different NDs like one carbon metabolism and detoxification of oxidative stress–related pathways in Down syndrome. Although GO and pathway results indicate some common characteristics, the predicted PPI molecular function clusters are quite different for each ND. In addition, some of the NDs share the same TFs and miRNAs, which indicate these disorders have the similar expression profiles. What needs to be emphasized that the BPA‐gene‐disease networks might be influenced by some of the comparable chemi‐ cals such as environmental pollutants, drugs, dietary pollutants or occupational exposure, which share the same interacted genes with BPA.

The integrated and curated biological processes and pathways shall shed light on the future studies to find the possible BPA interacted or influenced genes. This will contribute to com‐ plete the BPA‐disease networks, which surely help to screen the potential biomarker of BPA‐induced neurodevelopmental diseases. However, it should be noted that most of the evidences were from curation of the cell or animal experiments. Simultaneously, the biin‐ teraction mode for BPA‐gene interaction was adopted for the precise network. Therefore, the future study design should consider the human subjects. Given the sample shortage, the peripheral blood instead of the brain tissue should be preferred in the future. This will con‐ tribute to the clinical diagnosis or intervention. Finally, our results should be carefully inter‐ preted because the results might be changed with the increasing abundance of the enrichment of BPA bi‐interacted genes.
