extfieldsofstudy: Medicine Chemistry

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The subcellular localization of type I p21-activated kinases is controlled by the disordered variable region and polybasic sequences

p21-activated kinases (PAKs) are serine/threonine kinase effectors of the small GTPases Rac and Cdc42 and major participants in cell adhesion, motility, and survival. Type II PAKs (PAK4, -5, and -6) are recruited to cell–cell boundaries, where they regulate adhesion dynamics and colony escape. In contrast, the type I PAK, PAK1, does not localize to cell–cell contacts. We have now found that the other type I PAKs (PAK2 and PAK3) also fail to target to cell–cell junctions. PAKs contain extensive similarities in sequence and domain organization; therefore, focusing on PAK1 and PAK6, we used chimeras and truncation mutants to investigate their differences in localization. We observed that a weakly conserved sequence region (the variable region), located between the Cdc42-binding CRIB domain and the kinase domain, inhibits PAK1 targeting to cell–cell junctions. Accordingly, substitution of the PAK1 variable region with that from PAK6 or removal of this region of PAK1 resulted in its localization to cell–cell contacts. We further show that Cdc42 binding is required, but not sufficient, to direct PAKs to cell–cell contacts and that an N-terminal polybasic sequence is necessary for PAK1 recruitment to cell–cell contacts, but only if the variable region–mediated inhibition is released. We propose that all PAKs contain cell–cell boundary–targeting motifs but that the variable region prevents type I PAK accumulation at junctions. This highlights the importance of this poorly conserved, largely disordered region in PAK regulation and raises the possibility that variable region inhibition may be released by cellular signals.

survival (1)(2)(3). The founding member of the family (PAK1) was first identified in a screen for interactors of GTP-bound Cdc42/ Rac (4), and all six PAKs are now known to be Cdc42/Rac effectors (5)(6)(7)(8)(9)(10). PAKs have been categorized into two separate groups according to their sequence similarities, with PAK1, -2, and -3 in type I and PAK4, -5, and -6 in type II (11)(12)(13). All PAKs have a highly conserved Cdc42/Rac interactive binding (CRIB) domain near their N terminus and a well-conserved C-terminal kinase domain. In type I PAKs, formation of an autoinhibitory dimer is thought to limit kinase activity and be released after Cdc42/Rac binding to the CRIB domain induces a conformational change that releases the autoinhibition and activates the kinase autophosphorylation signaling cascade (14,15). In contrast, type II PAKs do not form a similar autoinhibitory dimer, and Cdc42/Rac binding is generally not considered to activate type II PAK kinase activity, although this remains somewhat controversial (2,16,17). Instead, type II PAK activity is regulated by intramolecular associations between the kinase domain and a pseudosubstrate sequence, located C-terminal to the CRIB domain (16 -18). It remains unknown how this interaction is released (2,11,16). Despite having little effect on kinase activity, GTPase binding is, however, important for regulating PAK function through control of PAK subcellular localization (19,20).
PAKs play crucial kinase-dependent and -independent roles in many cellular signaling pathways involved in adhesion, migration, and survival, and dysregulation of PAK function or expression contributes to a range of diseases including cancer (21). Unsurprisingly, given the sequence conservation in their kinase domains, type I and II PAKs share many substrates (e.g. ␤-catenin, paxillin, and BAD); however, type I-and type II-specific substrates have been reported (22). Both type I and type II PAKs have been implicated in cancer development, and notably, both PAK1 and PAK6 are linked to prostate cancer metastasis (21,23,24).
We and others previously showed that PAK6 localizes at cell-cell contacts in the DU145 prostate cancer cell line and that this localization, along with kinase activity, drives escape of DU145 cells from cell colonies (19,20). In cells expressing GFP-PAK6, we observed a significant increase in the percentage of cells escaping from colonies when compared with control GFP cells (19,20). In our study, we identified residues 1-48, containing an N-terminal polybasic motif and the CRIB domain, as the minimal sequence sufficient to direct PAK6 to cell-cell contacts. We also demonstrated that knockdown of Cdc42 blocked PAK6 localization at cell-cell contacts (20). Furthermore, we found that both kinase activity and localization to cell-cell contacts were necessary to drive colony escape (20). PAK6 has been reported to form a complex with ␤-catenin (19), and PAK6 can directly phosphorylate ␤-catenin in vitro (19). The phosphorylation state of ␤-catenin regulates adherens junction integrity, and phosphorylated ␤-catenin is released from E-cadherin, which results in decreased cell-cell adhesions (25). We hypothesize that PAK6 phosphorylation of adherens junction components, such as ␤-catenin (19), disrupts cell-cell contacts and favors cell escape from colonies (19,26). Notably, although we find that all type II PAKs target to cell-cell boundaries to varying extents, the type I PAK, PAK1, does not. This differential localization is surprising, considering that PAK1 contains an N-terminal polybasic sequence and a CRIB domain, and PAK1 and PAK6 have shared substrates and both contribute to cancer development. The question of what causes the differential PAK localization is the focus of this study.

Type II but not type I PAKs target to cell-cell contacts
We previously reported that PAK6, a type II PAK, targets to cell-cell contacts in DU145 prostate cancer cells, but PAK1, a type I PAK, does not (20). Furthermore, the other type II PAKs, PAK4 and PAK5, also target to cell-cell contacts, albeit PAK4 targeting is weak (19,20,27). Based on these data, we suggested that type I and type II PAKs exhibit differential targeting to cell-cell contacts. To test this hypothesis, we assessed localization of all three type I PAKs using N-terminal GFP-tagged PAK1, PAK2, and PAK3 in DU145 cells. Using immunofluorescent staining of ␤-catenin as a marker of cell-cell junctions, we showed that type I PAKs fail to target at cell-cell contacts and display a diffuse localization pattern much like the GFP control (Fig. 1A). In contrast, GFP-PAK6 clearly targets to cell-cell contacts (Fig. 1A). The lack of type I PAK targeting was not due to proteolysis, as immunoblotting confirmed that the GFPtagged PAKs were of the expected molecular weights (Fig. 1B). As described previously (20), we quantified cell-cell targeting using the JACoP plugin (28) on ImageJ to calculate a Mander's colocalization coefficient, the fraction of GFP signal colocalizing with ␤-catenin. The quantification confirmed that GFPtagged type I PAKs or GFP alone failed to colocalize with ␤-catenin, producing a low Mander's coefficient with very small S.D., whereas GFP-PAK6 exhibits a higher Mander's coefficient with a wider distribution probably due to the differences in total GFP-PAK6 expression level (Fig. 1C). Thus, we demonstrated that the type I and type II PAKs exhibit differential targeting to cell-cell contacts, but the molecular basis for this was unknown.
We have been unable to identify anti-PAK antibodies that allow immunofluorescent localization of endogenous PAK1 or PAK6. Therefore, to ensure that the differential targeting we observe is not solely a consequence of inserting an N-terminal GFP tag, we also compared PAK1 and PAK6 containing C-terminal mCherry. As shown in Fig. S1A and quantified by Mander's colocalization coefficient (Fig. S1B), PAK6-mCherry localized at cell-cell boundaries, whereas PAK1-mCherry did not. Furthermore, to examine whether the size of the tag influenced localization, we generated C-terminally Myc-tagged PAK1 and PAK6. Again, PAK1-Myc did not localize to cell-cell boundaries, whereas PAK6-Myc colocalized with ␤-catenin ( Fig. S1 (C and D)). We note that PAK6-Myc co-localized with ␤-catenin with an overall lower Mander's coefficient, and we suspect that this may reflect difficulties with accurate thresholding of images due to the higher background staining obtained with the anti-Myc tag antibody.
Having established that differential localization of PAK1 and PAK6 is independent of the site and size of the tag, we tested whether this trend also occurred in cells other than DU145. Our prior studies used the DU145 prostate cancer cell line, as these Figure 1. Type II but not type I PAKs target to cell-cell contacts. A, DU145 cells transiently expressing GFP-tagged type I PAKs (PAK1, PAK2, or PAK3) or PAK6 were plated on glass coverslips, fixed after 24 h, and stained with antibody to ␤-catenin. Scale bar, 10 m. B, 5 ϫ 10 6 DU145 cells transiently transfected with GFP-PAK constructs were lysed in buffer X lysis buffer, diluted in sample buffer, and immunoblotted (IB) for GFP. C, colocalization of GFP and GFP-PAKs with ␤-catenin was assessed by calculating the Mander's coefficient. At least 15 nonoverlapping frames from at least three independent transfections were used in the analysis. Mean Ϯ S.D. (error bars) is indicated. n.s., not significant; ****, p Ͻ 0.0001 in an ordinary one-way ANOVA test with Dunnett's correction for multiple comparisons.

PAK1 variable region inhibits cell-cell contact targeting
cells are known to express PAK1 and PAK6 (20). When GFP-PAK1 or GFP-PAK6 was transiently expressed in HeLa or U2OS cells, GFP-PAK6 robustly co-localized with ␤-catenin at cell-cell boundaries, whereas GFP-PAK1 did not (Fig. S1 (E and F)). Differential PAK targeting is thus not restricted to DU145 cells.

The variable region contributes to the PAK1 localization difference
The domain architecture of PAK proteins is well-conserved with an N-terminal unstructured region that often contains a polybasic motif, followed by a CRIB domain, a central poorly conserved region of variable length that is believed to be largely unstructured (which we term the variable region), and a C-terminal highly conserved kinase domain ( Fig. 2A). We have pre-viously demonstrated that PAK6 targeting to cell-cell contacts depends on the Cdc42-binding CRIB domain and the N-terminal residues containing the polybasic sequence (20). The conservation between PAK isoforms allowed us to use chimeras to investigate the domains responsible for the differential targeting between PAK1 and PAK6. We first generated chimeric constructs swapping the N-terminal and CRIB domains ( Fig. 2A). Using fluorescent microscopy with ␤-catenin as a marker for cell-cell junctions, we showed that a construct containing the N-terminal and CRIB domains from PAK6 (residues 1-51) plus the PAK1 variable region (residues 108 -248) and PAK1 kinase domain (residues 249 -553), which we term GFP-611, efficiently targets to cell-cell contacts (Fig. 2B). This was consistent with our prior data showing that the minimal sequence needed for PAK6 cell-cell contact targeting is the N-terminal

PAK1 variable region inhibits cell-cell contact targeting
plus CRIB regions (20). However, more surprisingly, the converse chimera, GFP-166, containing the N-terminal and CRIB regions from PAK1 (residues 1-107) and the variable region (residues 52-382) and kinase domain (residues 383-681) from PAK6, also localizes at ␤-catenin-positive cell-cell boundaries (Fig. 2B). All chimeras were expressed at the correct molecular weight (Fig. 2C), and calculation of Mander's coefficients from many fields in independent transfections showed comparable targeting of GFP-611 and GFP-166 chimeras and of GFP-PAK6, all of which are significantly higher than the PAK1 control (Fig. 2D).
Knowing that the GFP-166 chimera targets to cell-cell contacts when having the variable region and kinase domain from PAK6, we set out to investigate which of these two regions facilitates targeting. We therefore generated additional PAK1 chimeras containing the PAK6 kinase domain (GFP-116) and the PAK6 variable domain (GFP-161) (Fig. 2E). As expected, given the highly conserved PAK kinase domains, swapping only the kinase domain had no impact on targeting (Fig. 2F), and GFP-116 co-localization with ␤-catenin was not significantly different from PAK1 control (Fig. 2H). Because GFP-166 is a targeting construct, this suggested that the variable region is likely to be responsible. Indeed, when we transiently transfected the GFP-161 construct, containing the PAK6 variable region, it targeted to cell-cell boundaries (Fig. 2F) at levels comparable with the GFP-166 chimera (Fig. 2H). Immunoblot of the lysates showed that all constructs were expressed at the expected molecular weight; however, GFP-161 was consistently less well-expressed (Fig. 2G). Notably, this reduction in expression did not alter our results, as we selected cells with comparable expression levels for imaging and analysis. For completeness, we also generated a complementary set of PAK6 chimeras, containing PAK1 kinase domain (GFP-661), variable region (GFP-616), or both (GFP-611) (Fig. 2I). Knowing that the N-terminal regions and CRIB domain are minimal essential domains for PAK6 targeting to cell-cell contacts (20), we were not surprised to find that all of these chimeras localized to cellcell contacts (Fig. 2, J and L). Collectively, our results with these chimera sets establish that the variable region of PAK6 enables PAK1 targeting to cell-cell contacts, whereas the presence of the PAK1 variable region and/or the kinase domain cannot stop PAK6 from localizing to the cell-cell boundaries.

PAK1 variable region inhibits PAK1 from targeting to cell-cell junctions
Our data provide the first evidence that the variable region plays a role directing the localization of PAKs to cell-cell contacts. We considered two alternative hypotheses to explain this effect: the PAK6 variable region may be sufficient to drive the chimera to junctions, or removing the PAK1 variable region may release an inhibitory process that keeps PAK1 away from cell-cell boundaries. To distinguish these two possibilities, we generated PAK1 truncation constructs to delete the kinase domain (GFP-PAK1⌬Cat) or both the kinase domain and the variable region (GFP-PAK1(1-107)). If there is an inhibitory effect mediated solely by the variable region, we expect to see the construct targeting to cell-cell contacts only when we remove the variable region. Supporting our inhibition hypoth-esis, we observed that whereas GFP-PAK1⌬Cat occasionally displayed increased membrane targeting, it did not colocalize with ␤-catenin, but upon the removal of the variable region, the truncation mutant GFP-PAK1(1-107) robustly localized at cell-cell boundaries (Fig. 3A). Whereas all truncation constructs were expressed at the correct size (Fig. 3B), Mandar's coefficient analysis showed significantly more GFP-PAK1(1-107) colocalizing with ␤-catenin compared with GFP-PAK1 and GFP-PAK1⌬Cat. These data suggest that the variable region of PAK1 prevents targeting to cell-cell contacts. Notably, we also made truncations deleting the kinase domain and variable regions of PAK2 and PAK3, and, similar to what we observed for PAK1, whereas full-length PAK2 and PAK3 do not target to junctions, GFP-PAK2(1-108) and GFP-PAK3(1-109) target very well (Fig. 3D). We note that some of the truncation mutants appeared to also localize to the nucleus, and we hypothesize that this is due to their smaller size compared with full-length PAKs. GFP is also sometimes observed in the nucleus. Nonetheless, these constructs support the conclusion that the N-terminal and CRIB domain regions of type I PAKs can target to cell-cell boundaries, and the variable region inhibits targeting.
We next investigated potential mechanisms by which the PAK1 variable region might inhibit accumulation of PAK1 at cell-cell contacts. Whereas the function of the variable region is unclear, and it is largely unstructured in PAK1 crystal structures (29), a binding site for the PIX family of nucleotide exchange factors lies in the PAK1 variable region (30,31), and PIX binding is proposed to either directly regulate PAK kinase activity or modulate PAK activity by recruiting it to focal adhesions (31,32). Notably, PIX does not bind to PAK6, and a PAK1 P191G/R192A double mutant has been shown to disrupt PIX binding (30). We therefore investigated whether PIX binding to PAK is responsible for the inhibitory effect of cell-cell boundary targeting. Using fluorescent microscopy, we showed that, like GFP-PAK1, GFP-PAK1 (P191G/R192A) fails to target to cell-cell contacts (Fig. 4, A and B), suggesting that PIX binding does not alter PAK1. We therefore attempted to identify additional binding partners of the PAK1 variable region. We generated GST-tagged constructs of the PAK1 variable region (VR), and the variable region with P191G/R192A mutations (VR-GA), expressed these proteins in Escherichia coli and purified them by GSH affinity chromatography. The purified GSTtagged proteins were loaded on GSH beads and used to pull down binding partners from DU145 cell lysates. Coomassie staining of bound proteins revealed two bands of molecular mass ϳ100 kDa, clearly visible in the GST-VR lane only when mixed with DU145 lysates and absent from GST control lanes (Fig. 4C). As the binding of both of bands was abolished in the P191G/R192A double mutant, we anticipated the ϳ90 kDa band to be ␤-PIX, and we confirmed this by immunoblotting with anti-␤-PIX antibodies (Fig. 4D). To identify the upper band, we excised the band and analyzed it by MS. This indicated it to be the known PIX binding partner GIT1 or GIT2, GTPaseactivating proteins for ADP-ribosylation factor small GTPbinding proteins (33). Immunoblotting with anti-GIT antibodies confirmed our mass spectrometry result (Fig. 4D). However, as the P191G/R192A double mutation did not impact PAK1

PAK1 variable region inhibits cell-cell contact targeting
targeting to cell-cell contacts (Fig. 4A), we concluded that PIX and GIT were not inhibiting PAK1 targeting. No other variable region binding partners were evident from our pulldown assays, raising the possibility that the variable region may inhibit PAK1 targeting by altering PAK1 conformation rather than through binding proteins.
Structural studies have shown that unstimulated PAK1 exists as a trans-inhibited dimer where the kinase domain of one PAK1 molecule is inhibited through interactions with the regulatory portion of the other PAK1 molecule and vice versa (14,29). The regulatory portions include the inhibitory switch (residues 87-136) and the kinase inhibitor segment (residues 137-149), and together they bind the C-lobe of the kinase domain, stabilizing its inactive conformation (29). The inhibitory switch region overlaps with the CRIB domain and the start of the variable region, whereas the kinase inhibitor segment lies in the variable region. Conformational changes in these regions are associated with PAK1 activation and conceivably influence targeting to cell-cell contacts. However, deletion of the kinase domain (GFP-PAK1⌬Cat), which would disrupt dimer formation, did not support localization to cell-cell contacts (Fig. 3A). Furthermore, a truncation mutant (GFP-PAK1(1-149)) that includes the entire inhibitory switch and the kinase inhibitor segment colocalized with ␤-catenin (Fig. 4, E and F) at levels comparable with that seen for GFP-PAK1(1-107), suggesting that residues from 115 to the end of the variable region suppress targeting through a yet to be determined mechanism.

High Cdc42 binding is necessary for targeting
Previously, we showed that Cdc42 binding to the PAK6 CRIB domain is important to recruit PAK6 to cell-cell boundaries, as CRIB domain mutations as well as Cdc42 knockdown blocked PAK6 localization, with the caveat that knockdown cells exhibit disrupted cell-cell junctions (20). We therefore investigated whether the differential targeting of different PAKs are correlated with their ability to bind Cdc42. We bacterially purified GST-tagged Cdc42, a nucleotide-binding defective mutant T17N as negative control, and a constitutively active binding mutant Q61L as positive control. All of the Cdc42 constructs encompassed residues 1-177 but lacked the C-terminal prenylation motif to facilitate expression and purification. We used these proteins in pulldown experiments with lysates from DU145 cells transiently transfected with either GFP-PAK1 or GFP-PAK6. As expected based on our prior studies (20), Cdc42 pulled down GFP-PAK6, and binding was specific as the T17N mutant inhibited binding (Fig. 5A). The activating Q61L mutant also bound GFP-PAK6 at levels comparable with the WT Cdc42. Notably, whereas we also observed specific GFP-PAK1 binding to Cdc42, GFP-PAK1 bound Cdc42 substantially less well than GFP-PAK6 (Fig. 5A). We repeatedly observed on average 3 times more PAK6 than PAK1 binding to Cdc42 (Fig.  5B), consistent with the notion that PAKs that target to junctions bind better to Cdc42 (Fig. 5, A and B). To ensure that the Cdc42 binding differences are not due to any variation in expression levels of GFP-PAK1 or GFP-PAK6, we generated binding curves by serially diluting the amount of GFP-PAK input lysate with untransfected lysates to ensure that total protein levels were the same while decreasing the amount of GFP-PAK present in the lysate. When we plotted the amount of PAK versus the amount of PAK bound to WT Cdc42, we see a robust difference between GFP-PAK1 and GFP-PAK6 at most input concentrations (Fig. 5C), confirming that PAK1 binds less well to Cdc42. We have been unable to purify full-length bacterially expressed PAK6 to confirm this result quantitatively, but experiments assessing binding of GST-Cdc42 to GFP-PAK1 or GFP-PAK6 affinity-purified from cell lysates using anti-GFP nanotrap beads (34) supported the conclusion that Cdc42 binds to GFP-PAK6 much better than GFP-PAK1 or GFP (Fig. S2).
We next tested our gain-of-function GFP-PAK1(1-107) truncation construct, and this also showed on average a 2.5-fold increased Cdc42 binding over full-length PAK1 (Fig. 5, D and  E). We further confirmed the specificity of this interaction by showing that a double H83L/H86L) mutation in the Cdc42binding site in the PAK1 CRIB domain (PAK1 HHLL) abolished binding to Cdc42 (Fig. 5D). Importantly, this also inhibited the ability of GFP-PAK1(1-107) to target to cell-cell junctions (Fig. 5, F and G).

A polybasic motif is necessary for PAK1 targeting once the inhibition from the variable region is released
The preceding data show that Cdc42 binding is required for PAK1 targeting to cell-cell contacts and that targeting constructs bind high levels of Cdc42; however, they do not establish whether strong Cdc42 binding is sufficient to target PAKs to cell-cell contacts. As the CRIB domain is the minimal Cdc42binding domain, we generated GFP-tagged PAK1 CRIB domain (amino acids 74 -107) and performed pulldown experiments with GST-Cdc42 proteins. As expected, GFP-PAK1 CRIB bound strongly and specifically to Cdc42 at levels comparable with GFP-PAK6 and higher than full-length GFP-PAK1 (Fig.  6A). However, GFP-PAK1 CRIB failed to target to cell-cell contacts when transiently transfected into DU145 cells (Fig.  6B). Comparison with GFP-PAK1(1-107), which includes the N-terminal region plus the CRIB and targets effectively to cellcell contacts (Fig. 6C), suggests that the N-terminal region plays a role in GFP-PAK1(1-107) targeting. The N-terminal region of PAK6 (amino acids 1-10) is also important for PAK6 targeting (20), but this region is much longer in PAK1. Whereas PAK6 has a polybasic lysine-rich motif adjacent to CRIB domain, the PAK1 N-terminal region contains a polybasic stretch of four lysines more N-terminal from the CRIB domain and a KEKE sequence adjacent to the CRIB domain corresponding to the position of the PAK6 polybasic motif. To test the importance of the PAK1 N-terminal polybasic region, we first generated a construct containing PAK1 CRIB and 10 amino acids upstream, GFP-PAK1(64 -107), a size equivalent to the PAK6 N-terminal region. PAK1(64 -107) failed to target to cell-cell boundaries, indicating that the sequence prior to CRIB is important and that a KEKE sequence is not sufficient to help the CRIB construct localize to junctions (Fig. 6, D, H, and  I). To ensure that the N-terminal GFP tag, positioned close to the polybasic motif, was not interfering in targeting, we confirmed our results using C-terminal mCherry-tagged constructs (Fig. S3). We subsequently mutated the four lysines (residue numbers 48 -51) in the polybasic stretch of PAK1(1-107) to alanines to investigate the importance of the polybasic motif. Figure 5. High Cdc42 binding is necessary for targeting. A, pulldown of GFP-tagged PAK1 or PAK6 from transiently transfected HEK293T cell lysates by bacterially purified GST-Cdc42, GST-Cdc42 T17N, or GST-Cdc42 Q61L. Samples were immunoblotted (IB) for GFP, and 3% input is shown. Ponceau staining was used to assess equal bead loading. B, PAK binding was quantified from four independent experiments (mean Ϯ S.D. (error bars)). *, p Ͻ 0.05 in a paired, two-tailed Student's t test. C, representative binding curve of GFP-tagged PAK1 or PAK6 pulled down by GST-Cdc42. Input amounts were serially diluted with untransfected 293T cell lysates. D and E, Cdc42 binding of GFP-tagged PAK1, PAK1(1-107), or constructs containing inactivating H83L/H86L double mutations in the PAK1 CRIB domain (HHLL) was assessed as in A and quantified as in B from seven independent experiments. ***, p Ͻ 0.001. F, DU145 cells on glass coverslips were transiently transfected with GFP-tagged PAK1 mutants, and 24 h later, cells were fixed and stained for ␤-catenin. Scale bar, 10 m. G, GFP-PAK colocalization with ␤-catenin was assessed by calculating the Mander's coefficient. At least 20 nonoverlapping frames from at least three independent transfections were used in the analysis. Mean Ϯ S.D. is indicated. ****, p Ͻ 0.0001 in an unpaired, two-tailed Student's t test.

PAK1 variable region inhibits cell-cell contact targeting
Whereas GFP-PAK(1-107) targets robustly to cell-cell contacts, when the lysines are mutated to alanines, targeting is abolished (Fig. 6, E, H, and I), supporting the importance of the polybasic region for targeting. To confirm the relationship between an intact polybasic region and targeting to cell-cell boundaries, we fused the PAK6 N terminus and the PAK1 CRIB domain and showed that this efficiently targeted to cell-cell contacts (Fig. 6, F, H, and I). However, this substitution in the context of full-length PAK1 was insufficient to trigger localization to cell-cell contacts (Fig. 6, F-I), consistent with the inhibitory action of the variable region of PAK1 identified above. We therefore conclude that PAK1 targeting to cell-cell contacts requires both the polybasic motif and the Cdc42-binding CRIB domain but that it is inhibited by the variable region between the CRIB and the kinase domains. Release from the variable region inhibition is therefore likely to be a key step in directing PAK1 to cell-cell contacts (Fig. 6, F-I).

Discussion
PAKs play key roles in cell adhesion, cytoskeletal organization, and cell motility (1). However, despite conserved domain organization and extensive sequence and structural similarity in their Rac and Cdc42-binding CRIB domains and their kinase domains, type II PAKs (PAK4, PAK5, and PAK6) co-localize with ␤-catenin at cell-cell contacts, whereas PAK1 does not (20,27,35,36). Here, we extend these observations to show that none of the type I PAKs localize at cell-cell contacts in DU145 cells, and we use truncation mutations and PAK1/PAK6 chime-

PAK1 variable region inhibits cell-cell contact targeting
ras to identify domains involved in this differential targeting. Surprisingly, rather than revealing a unique targeting domain in type II PAKs, we discovered that the nonconserved central variable region inhibits cell-cell contact localization of type I PAKs. Notably, removal of this region allows CRIB domain-dependent accumulation of PAK1 at cell-cell contacts. Furthermore, we show that this localization depends on an N-terminal polybasic motif as well as the small GTPase binding activity of the CRIB domain. These data explain why type I PAKs are not routinely found at cell-cell contacts but also highlight the importance of future studies to understand how the variable region modulates PAK localization and raise the interesting possibility that cellular modulation of variable region inhibition may control PAK1 subcellular localization.
In all six PAKs, the highly conserved kinase domain is located at the very C terminus, and the regulatory Cdc42/Rac-binding CRIB domain is found near the N terminus, often accompanied by a stretch of basic residues, the polybasic motif (11). The PAKs were identified as Cdc42/Rac binding partners, and in all six PAKs the highly conserved CRIB domain binds Cdc42/Rac, albeit with various affinities (5)(6)(7)(8)(9)(10). Functionally, all PAKs have key roles at either cell-matrix or cell-cell junctions, where they regulate adhesion turnover and cell motility (11). Consistent with this, overexpression of PAKs are commonly seen in more aggressive and metastatic cancers (23). Despite these many similarities, the type I and II PAKs harbor a number of unique characteristics. For example, the mode of activation differs between groups. Type I PAKs are maintained as autoinhibited homodimers with the CRIB domain masked by association in trans with a part of CRIB domain called the dimerization segment, and the kinase inhibitor segment passing through a kinase cleft, stabilizes the inactive catalytic domain. Cdc42/Rac binding to the CRIB domain disrupts this inhibitory interaction, permitting kinase activation (11,14,29,37). In contrast, type II PAKs exist as monomers in solution, and their activation is generally considered not to require the binding of Cdc42/Rac, with type II PAK kinase activity instead controlled by binding of an inhibitory pseudosubstrate region (located in the variable region) to the kinase domain in cis (2,16). The key regulator that releases this inhibitory interaction remains to be identified. Rather than controlling kinase activation, GTPase binding is instead considered to act mainly by controlling type II PAK localization (11). In this regard, it is noteworthy that whereas both type I and type II PAKs have been reported at cell-matrix junctions, where they apparently influence focal adhesion stability and integrity, only type II PAKs have been found at cellcell junctions, where they drive adherens junction turnover and favor colony escape in epithelial cancer cell lines (6,20,36). Given the highly similar domain organization, we sought to understand what caused the differences in type I and II PAK localization.
We have previously shown that for PAK6, the N-terminal region along with Cdc42 binding to the CRIB domain is necessary and sufficient for targeting to cell-cell junctions (20). Here we expanded this observation to confirm the differences in type I and II PAK localization to cell-cell junctions. Then, using a series of PAK1/6 chimeras, we found switching the variable region from PAK6 into PAK1 directed the chimeric PAK1 con-struct to cell-cell junctions. Deletion experiments indicated that this gain of targeting was not due to the addition of the PAK6 variable region but instead due to the loss of the PAK1 variable region, leading us to suggest an inhibitory function mediated by the variable region (Fig. 7). Notably, a PAK6 construct containing the PAK1 variable region retained cell-cell contact targeting ability, demonstrating that the PAK1 variable region only inhibits PAK1 localization at cell-cell contacts, suggesting that it might exert its effect via association with another region of PAK1. Attempts to identify such an interaction using a bacterially purified GST-tagged PAK1 variable region to pull down PAK domains expressed in 293T cells have thus far failed to reveal any interactions (data not shown). The possibility remains that the interaction, which might normally occur in cis or in the context of a preformed dimer, might be too weak to be detectable in our pulldown assay. However, we note that structural studies indicate the variable region to be largely disordered and only revealed interactions of residues Asp-126 and Glu-129 of the inhibitory switch region in addition to the kinase inhibitor segment (residues 136 -149) with the kinase domain. Deletion of the kinase domain does not trigger targeting to cell-cell contacts, and inclusion of residues Asp-126, Glu-129, and the kinase inhibitory switch in truncation constructs PAK1(1-149) did not alter targeting to cell-cell contacts compared with minimal PAK1(1-107) constructs. Thus, currently we cannot explain the inhibitory effect of the variable region through inhibitory PAK1-PAK1 interactions.
Our studies did, however, confirm the interaction of the PAK1 variable region with the Rho GEF ␤-PIX. The ␤-PIX-  (14), whereas PAK6 is inhibited in cis by binding of a pseudosubstrate sequence (18). PAKs are recruited to cell-cell contacts through direct interactions between their CRIB domain and Cdc42 and potentially through interactions of their polybasic (PB) motifs with the membrane. In PAK1, recruitment is blocked by the variable region, possibly through effects on PAK1 conformation or through interactions with other proteins.

PAK1 variable region inhibits cell-cell contact targeting
binding site is conserved on all type I PAKs, but not in type II PAKs, and the complex between PAK, PIX, and the PIX binding partner GIT localizes to focal adhesions and promotes junction disassembly by interacting with paxillin (31,32,36). Surprisingly, studies in C. elegans identified a novel PAK1-specific regulation of cell shape and migration, where the GIT/PIX/PAK signaling pathway acts independently of Cdc42/Rac, and complex recruitment and formation is negatively regulated by PAK1 autophosphorylation (38). However, mutation of the PIX-binding site in PAK1 or PAK2 (PAK2 data not shown) did not alter PAK localization to cell-cell contacts, suggesting that PIX binding cannot explain the differential adherens junction targeting of type I and type II PAKs. In our study, PIX and GIT were the only visible bands from a Coomassie-stained GST-PAK1-variable region pulldown experiment of DU145 cell lysate; however, we cannot rule out the possibility of other important binding partners interacting at low levels. Therefore, although our data clearly point to an inhibitory role for the variable region of PAK1, the molecular basis for this effect remains to be fully elucidated.
Once the variable region inhibition of PAK1 targeting to cell-cell contacts is released by deletion or substitution, PAK1 targets to junctions in a process that requires a functional CRIB domain. In our study, all of the PAK constructs that target to cell-cell junctions exhibited high Cdc42 binding in pulldown assays, and disrupting binding to Cdc42 with point mutations in the CRIB domain abolished targeting to cell-cell contacts. This is consistent with our prior studies on PAK6 and the impairment of PAK6 targeting in Cdc42 knockdown cells (20). Thus, high Cdc42 binding is apparently required for PAK targeting to cell-cell contacts but is not sufficient, as not all high Cdc42 binders are targeting constructs, meaning the high binding is not the sole mechanism directing constructs to cell-cell junctions.
We previously implicated the polybasic sequence of PAK6 in targeting to cell-cell junctions (20), and once we observed that the PAK1 CRIB domain alone was unable to target despite a high level of binding to Cdc42, we recognized that the largely unstructured N-terminal region of PAK1 must provide an additional regulator for targeting. Previous studies have suggested that the polybasic sequence N-terminal to the CRIB domain aids Cdc42 binding to Cdc42 (39) in PAK6, but our semiquantitative pulldown experiments using GST-Cdc42 and lysates from DU145 cells overexpressing GFPtagged PAK1 constructs did not reveal differences between the N-terminal region of PAK1(1-107) and the PAK1-CRIB alone. However, we abolished targeting by either truncating the N-terminal region or by mutating the polybasic sequence in PAK1(1-107). Notably, the length and position of the polybasic sequence are apparently not important, because when we created a construct expressing the short PAK6 polybasic motif fused directly to the PAK1 CRIB domain, this localized in cell-cell contacts. We hypothesize that the polybasic motif aids membrane targeting and so facilitates recruitment or retention of PAKs at cell-cell contact sites (Fig. 7). Thus, strong Cdc42 binding and an intact polybasic motif are needed to target PAK1 to cell-cell contacts, but this only occurs if the PAK1 variable region is removed, illus-trating that the inhibitory effect of the variable region is dominant. Although we do not yet know how this region inhibits targeting, our results raise the intriguing possibility that cellular signals may release this inhibition such that under certain circumstances, PAK1 may localize to cell-cell contacts, potentially leading to adhesion turnover.

Cell culture and transfection
DU145 prostate cancer cells were kindly provided by Raymond Baumann at Yale University. HEK293T cells were purchased from ATCC. Cells were cultured in Dulbecco's modified Eagle's medium, containing 4.5 g/liter D-glucose and L-glutamine (Gibco, 11965-092), supplemented with 9% fetal bovine serum (Life Technologies). Cells were incubated at 37°C with 5% CO 2 . Cells were transfected using PEI (linear polyethyleneimine, Polysciences, Inc.) at 8 g/ml overnight in serum-free media.

PAK1 variable region inhibits cell-cell contact targeting
ase inhibitor mixture, EDTA-free (Roche Applied Science, 11836170001)). Cell lysates were diluted in sample buffer, fractionated on 10% SDS-polyacrylamide gels, and transferred to 0.45-m nitrocellulose membrane at 0.25 mA for 1.5 h. Membranes were blocked with blocking buffer (5% milk in TBS with Tween 20 (TBS-T)) at room temperature for 1 h before incubation with primary antibody in blocking buffer overnight at 4°C. Membranes were washed with TBS-T before incubating with secondary antibody diluted in blocking buffer for 1 h at room temperature. Membranes were washed with TBS-T before imaging with an Odyssey IR imaging system (LI-COR). All quantification of the immunoblots was done using Image Studio (LI-COR).

Immunofluorescence and scoring of cell-cell targeting
DU145 cells were seeded on coverslips in complete culture medium. 24 h post-transfection, coverslips were fixed in 4% paraformaldehyde in PBS for 15 min at room temperature. Cells on coverslips were permeabilized with 0.05% Triton in PBS for 5 min at room temperature. Coverslips were washed with PBS and blocked with blocking solution (5% BSA in PBS) for 1 h at 37°C in a humidity chamber. Anti-␤-catenin antibody was diluted 1:100 in blocking buffer and incubated with the coverslips for 1 h at 37°C in a humidity chamber. Coverslips were washed three times with PBS before incubation with secondary antibody diluted 1:500 in blocking buffer for 1 h at 37°C in a humidity chamber. Coverslips were washed three times and rinsed with milliQ water before mounting with ProLong Diamond Antifade mountant (Thermo Fisher Scientific, P36962). Images were captured using either a Nikon Ti1 or Ti2 microscope with ϫ100 immersion oil objective.
Mander's colocalization coefficient, which measures the fraction of one protein that colocalizes with a second, in our case the fraction of GFP co-localizing with ␤-catenin staining, was calculated using JACoP (just another colocalization plugin) in ImageJ (28). This requires effective thresholding to remove background, allowing identification of pixels that are negative for ␤-catenin or GFP signal (42). There are a variety of mechanisms for removing background, but all require checking visually against the parental image (42). We found that manually setting fixed thresholds in each experiment produced the best overall visual concordance between the thresholded and parental images to ensure the incorporation of all positive structures. As all images in an experiment were recorded at identical exposure times and illumination settings, a fixed background (ϳ1500 in the GFP channel and 5000 in the red channel) was applied to all images. Mander's coefficient was calculated, and the score showing the fraction of GFP signal overlapping with ␤-catenin signal was recorded. At least 20 nonoverlapping frames from at least three independent transfections were analyzed for quantification.

Cdc42-binding assays
DU145 cells were transiently transfected with pEGFP-PAK constructs overnight with PEI. Cells were harvested and lysed in buffer X lysis buffer. Lysates were clarified and incubated with GSH-Sepharose beads loaded with GST-Cdc42 proteins. Samples were diluted in buffer X-T (5 mM PIPES, pH 6.8, 0.5 mM Na 3 VO 4 , 25 mM NaF, 20 mM NaPP i , 25 mM NaCl, 75 mM sucrose, 0.05% Triton X-100) and incubated overnight on a roller at 4°C. Beads were washed three times with buffer X-T before elution in SDS-PAGE sample buffer at 95°C for 5 min. Samples were run on 10% SDS-polyacrylamide gels, transferred to nitrocellulose, and immunoblotted for GFP.
HEK293T cells were transiently transfected with pEGFP-PAK constructs overnight with PEI. Cells were harvested and lysed in PBS, pH 7.4, 1% Triton X-100 plus EDTA-free complete mini protease inhibitor mixture (Roche Applied Science, 11836170001). Cells were sheared with a 23-gauge needle and sonicated briefly, and insoluble material was removed by centrifugation. GFP proteins from the clarified lysate were immobilized on GFP-nanotrap beads (prepared as described previously (34,43)) by mixing for 2 h at 4°C with rotation. Beads were washed three times with PBS, 0.1% Triton X-100, and the binding of purified GST-Cdc42 was assessed by incubating for 2 h at 4°C with rotation. Beads were washed three times with PBS, 0.1% Triton X-100 before elution in SDS-PAGE sample buffer at 95°C for 5 min. Samples were fractionated on 10% SDS-polyacrylamide gels and immunoblotted for GST and GFP.

GST-VR pulldown
DU145 cells were harvested and lysed in buffer X lysis buffer. Lysates were sheared with a 30-gauge needle and clarified. GSH-Sepharose beads loaded with GST, GST-VR, or GST-VR-GA were incubated with or without lysates overnight on a roller at 4°C. Beads were washed three times with buffer X-T and diluted in sample buffer. Samples were then heated to 70°C for 15 min and spun down, and supernatants were transferred to new tubes and heated to 95°C for an additional 10 min. Samples were run on 10% polyacrylamide gels and stained with Coomassie Blue.

PAK1 variable region inhibits cell-cell contact targeting
Author contributions-X. S. and D. A. C. conceptualization; X. S. formal analysis; X. S. and V. L. S. investigation; X. S. writing-original draft; X. S., V. L. S., and D. A. C. writing-review and editing; V. L. S. validation; D. A. C. supervision; D. A. C. funding acquisition; D. A. C. project administration.


extfieldsofstudy: Biology Medicine

s2fieldsofstudy: Biology Psychology

text:
Association of genes with phenotype in autism spectrum disorder

Autism spectrum disorder (ASD) is a genetic heterogeneous neurodevelopmental disorder that is characterized by impairments in social interaction and speech development and is accompanied by stereotypical behaviors such as body rocking, hand flapping, spinning objects, sniffing and restricted behaviors. The considerable significance of the genetics associated with autism has led to the identification of many risk genes for ASD used for the probing of ASD specificity and shared cognitive features over the past few decades. Identification of ASD risk genes helps to unravel various genetic variants and signaling pathways which are involved in ASD. This review highlights the role of ASD risk genes in gene transcription and translation regulation processes, as well as neuronal activity modulation, synaptic plasticity, disrupted key biological signaling pathways, and the novel candidate genes that play a significant role in the pathophysiology of ASD. The current emphasis on autism spectrum disorders has generated new opportunities in the field of neuroscience, and further advancements in the identification of different biomarkers, risk genes, and genetic pathways can help in the early diagnosis and development of new clinical and pharmacological treatments for ASD.

AGING prevalence of ASD was reported to range from 1.4-29 in 10,000 individuals [7]. The rise in the prevalence of ASDs is a result of many contributing factors. Some researchers believe in the biome depletion theory, which states that an overreaction of maternal immune response is an underlying factor responsible for the development of ASD in children. In addition, as our immune systems co-evolve with many types of pathogens, a lack of these pathogens within urban and developed areas can cause overreactivity of the immune system [8]. Other factors include increased exposure to environmental toxins that can damage the genetic structure of an individual, thereby increasing genetic susceptibility ( Figure 1) [9][10][11]. A study by Velasquez-Manoff (2012) reported that autoimmune disorders and immune dysregulation in pregnancy are also found to contribute to the rise of ASD [12]. The genetics involved in autism are of considerable importance as they help us identify various genes, proteins, and signaling pathways found in ASD. The study of genes and genetic changes found in patients with ASD can help unravel the genetic architecture underlying ASD and can aid in early diagnosis and clinical treatment. In the present study, the genomic changes that occur in ASD with different genetic variations will be discussed, and the role of ASD risk genes in gene transcription and translation regulation processes, neuronal activity modulation, synaptic plasticity, signaling pathways, and the novel candidate genes that play a significant role in the pathophysiology of ASD will be examined.

Genetic basis of autism
Many genes associated with ASD are found in circadian entrainment, which indicates a heterogeneous genetic etiology for ASD [13]. Some rare mutations cause the development of syndromic autism. For example, about 30% of patients with Fragile-X Syndrome (FXS) have also been found to develop ASD [14]. A subgroup of patients with Cortical Dysplasia-focal Epilepsy (CDFE), Rett Syndrome and Tuberous Sclerosis Syndrome have also found to express autistic behavior [15,16]. Copy number variations (CNVs) that involve the deletion or duplication of loci are also responsible for syndromic autism. For example, mutations in SHANK3/PROSAP2 that are found in Phelan-McDermid syndrome are associated with ASD [17]. Mutations in different genes, such as STXBP1, KCNQ4, MYH14, GJB6, COL11A1, UBE3A, KATNAL2, and THRA, have also been associated with ASD [13].

Common genetic variants
Three independent genome-wide association studies (GWAS) have reported genetic variants commonly associated with autism. Out of these 3 studies, 2 have used 0.5 million single nucleotide polymorphisms (SNPs) and have discovered that they are linked at 5p14.1 [18] and 5p15.2 [19] loci. Similarly, in a different study, other associations for rs4141463 have been found at loci 20p12.1. by using one million SNPs [20]. Another ASD risk gene, CNTNAP2, has been found to have a common genetic SNP variation caused by an alteration of functional connectivity in the frontal lobes [21]. A high contribution of these common genetic variants has been associated to autism liability, estimated to be about 40% in simplex and 60% in multiplex families. The contribution of these common variants is of great significance for better diagnosis in autism but the SNPs associated with ASD are still under research [22].

Copy number variations (CNVs)
CNVs are found to be a source of autism risk. A study conducted on autism-affected families reported excess gene duplications and deletions in affected autistic individuals compared to the normal controls [23]. Rare de novo and inherited events found in pathogenic CNVs involved genes associated with autism, such as CHD2 [24][25][26], HDAC4, and GDI1, SETD5, HDAC9, and MIR137 [23]. CNVs were found to be highly penetrant in females with autism and in individuals with X syndrome protein targets. It was also found that de novo CNV-affected genes converge on neuronal signaling and networks associated with the functioning of synapse and regulation of chromatin [23].
In an ASD gene study, 6 risk loci, namely 1q21.1, 3q29, 7q11.23, 16p11.2, 15q11.2-13, and 22q11.2, associated with autism disorders were reported by analyzing de novo CNVs that were tested within 2,591 families. The study found out that genes within small de novo mutations tend to overlap with high risk genes associated with ASD [27]. Most of the affected individuals were found to carry a de novo causative mutation, as well as deleterious mutations [28]. Gene disrupting mutations, such as frame-shift, splice site, and nonsense mutations, were most frequently found in individuals with ASD [28]. Three percent of the autistic individuals were found to have gene disrupting mutations that were present on both maternal and paternal chromosomes, and 2% of autistic males had a 1.5 fold increase in complete loss of function mutations for X-chromosomes, compared to males without ASD [29].

Gene aberrations associated with ASD
A study associated with the identification of novel candidate genes in ASD-associated pathways revealed several deletions and gene disruptions in many ASD cases, wherein eighteen deletions were detected at the 3p26.3, 4q12, 14q23, and 2q22.1 regions [30]. Candidate genes associated with GABAergic signaling and neural development pathways were revealed by the evidence provided by case specific CNVs. These genes include a GABA type A receptor associated protein (GABARAPL1), a postsynaptic GABA transporter protein (SLC6A11), and a GABA receptor allosteric binder known as diazepam binding inhibitor (DBI). A genetic overlap between ASD and other neurodevelopmental disorders was also reported, including genes such as GRID1, GRIK2, and GRIK4, which include glutamate receptors, NRXN3, SLC6A8, and SYN3, and are responsible for synaptic regulation. These CNVs are associated with ASD heritability and can help to uncover new etiological mechanisms underlying ASD [30].

Genetic variation in ASD
There is a substantial variation in the ASD genetic architecture and the heterogeneity of ASD is due to the genetic variability that underlies this disorder. A single mutation is enough to cause ASD and several thousand low-risk alleles can contribute to the development of ASD [31]. There are many rare variants that can contribute to the risk of developing ASD and there is extreme locus heterogeneity in ASD due to copynumber variant data and mutations involving the alteration of de novo proteins [32]. Many of the ASD genes share a common pathway that affects neuronal and synaptic homeostasis. For example, social impairment and speech problems in ASD individuals are due to a single copy mutation SHANK3 [33]. This shows that many of the ASD associated genes are part of a large number of molecular pathways or mechanisms that are related to other neuropsychiatric conditions [34].

Novel candidates in ASD
Many mutations have been reported in CHD8, an ATPdependent chromodomain helicase responsible for the regulation of CTNNB1 [35] and p53 pathway [36]. CHD8 has been investigated in many exome studies and is considered as a novel candidate for ASD [37][38][39]. In addition, the SCN2A gene, which encodes a voltagegated sodium channel, plays an important role in the generation of action potentials in neurons. These mutations are most frequently found in Identity Disorder (ID), with some cases also showing signs of autism [40,41]. In autism probands, three truncating mutations of GRIN2B and SYNGAP1 and TBR1 associated with dual-specificity tyrosine phosphorylationregulated kinase 1A (DYRK1A) play an important role in excitatory signaling in ASD. While, GRIN2B is associated with learning and memory, and targeted sequencing has linked it with various neurodevelopmental disorders, including ASD [38].
An ASD study showed the differential expression of autism candidate genes in lymphoid cell lines of autistic individuals [42]. The study reported the upregulation and increased expression of protein argininosuccinate synthetase (ASS), which acts as an important brain signaling molecule and is involved in controlling the rate-limiting step in the production of nitric oxide (NO), is associated with ASD [42]. An upregulation in the mRNA expression levels of ITGA2B encoding glycoprotein αIIβ was found in ASD affected individuals. This elevated level of expression can disrupt the cellular morphology in affected individuals [43]. Another autism study that identified abnormal brain gene expression patterns in autistic brains via whole-genome analysis of mRNA levels and CNVs reported that in young autistic individuals, the highly dysregulated pathway was the adenosine A2A receptor-signaling pathway [44]. Adenosine receptors play an important role in the development and functioning of the brain, as well as the synaptic plasticity, motor, and cognitive function and neuronal stem cell proliferation regulation [44].
Many studies have reported the association between Purkinje cells (PCs) and ASD [45][46][47]. Additionally, many studies have reported a significant reduction in the number of PCs in the post-mortem brains of patients who were affected with ASD [48][49][50][51]. Lower expression of neurotrophins NT3 and NT4, which play an important role in the climbing fiber system development in PCs, was also reported in affected autistic individuals [52]. Downregulation of neural and muscle specific alternative splicing regulator (A2BP1/FOX1) [53] and the MOCOS gene was also reported in ASD individuals [54]. Language and speech disorders in ASD were found to be result of mutations in the FOXP2 and CNTNAP2 genes [55]. The FOXP1 gene, which is a transcription repressor and is important for normal brain development and functioning, was found to be elevated in individuals with ASD. This indicates the involvement of FOXP1, FOXP2, and CNTNAP2 genes in the pathogenesis of ASD [56]. Synaptic components such as Nav1.2 channel, which is a voltage-gated ion channel involved in action potential propagation, neuronal pacemaking and Cav1.3 channel, which is an excitabilitytranscription coupling were found to be mutated in autistic patients [57]. Another ASD study showed the presence of an additional copy of 22q13/SHANK3 in a boy with Asperger syndrome that caused severe social communication impairment [58]. The SHANK3 gene is involved in the enlargement of dendritic spine heads as evidenced in mice [59]. There have also been reports of X-linked mutations in NLGN3 and NLGN4 in ASD that affect synapse formation and maintenance, which is important for speech development and social communication [58]. An ASD study that identified rare variants in mGLUR signaling pathway reported rare and deleterious variants in the SHANK3, TSC1, and TSC2 genes in non-syndromic autism individuals [60]. HOMER1, which is an autism risk gene, is considered an important component of the postsynaptic density (PSD) proteins network. This network creates a link between gene products associated with autism and neuroligins [60]. Disruption of mGluR5-Homer1 interactions can cause the development of phenotypes associated with autism [61]. Mutations in SYNGAP1, which is involved in the negative regulation of the Ras/ERK pathway and synaptic transmission, have also been identified in ASD [60]. The UBE3A and GABA receptor genes, which are expressed in the central nervous system, are located at the15q11-13 locus, and are also associated with autism [62]. O'Roak, Vives, Fu, et al. (2012) also discovered that six genes (GRIN2B, TBR1, CHD8, PTEN, TBL1XR1, and DYRK1A) contribute to 1% of ASDs and were found to be sporadic. Parikshak et al. [63] found that genes associated with autism tightly bind together in modules that are responsible for human cortical development and biological functions, including transcriptional regulation and the development of synapses.
Disruption of the NRXN1 gene in autism reported that in autistic individuals, the amino acid alterations in the NRXN1 gene are not frequently present as compared to non-autistic individuals in an NRXN1 gene coding sequence scan [64]. Two missense changes seen in the residues of the leader sequence of a-NRXN1 and epidermal growth factor (EGF)-like domain suggests these changes in NRXN1 might be a contributing factor in developing autism [64].

Autistic phenotypes
To identify the genes affected by rare de novo CNVs, in autism, a network-based analysis of genetic associations (NETBAG) is used [65]. The network forming genes are associated with autism and are involved in the development of synapse, neuron motility and axon targeting. In addition to the WNT signaling pathway, which is responsible for neural circuits formation and dendrite morphogenesis regulation, there is a reelin signaling pathway that plays a significant role in neuron motility and autistic phenotypes [66,67]. This network also includes deleted in colorectal carcinoma (DCC) protein, which is responsible for guiding the axon in autism disorder [68]. In addition, other proteins involved in the regulation of actin network that are used in axonal morphogenesis, such as p21-activated kinase (PAK) and LIM-domain containing protein kinase (LIMK) and any malfunction in these proteins influences autistic phenotypes as they play a significant role in dendrite/axon signaling [65]. Autistic individuals are also found to have increased density of spine in portions of cerebral cortex with over-connectivity in local brain regions [69,70]. This indicates that malfunctioning of the neuronal and synaptic connectivity is central to autism, and several genes could be related to postsynaptic density and actin remodeling that could contribute to autistic phenotypes [65]. Also, higher ASD rates have been reported in individuals with low copy repeats LCR-A to B region deletion compared to individuals without deletions. This might contribute to autistic phenotypes in disorders related to 22q11.2 (also known as DiGeorge syndrome) in addition to decreased adaptive functioning [71].
There are ASD risk genes that contribute to autistic phenotypes and are associated with different lobes of the brain (Figure 2). The frontal lobe is the largest and controls different cognitive functions such as memory, behaviors, language and voluntary movements. The parietal lobe controls sensorimotor planning, language and touch. The temporal lobe is mainly involved in controlling the semantic and recognition memory and the occipital lobe, which is the smallest lobe in the brain mainly controls visual processes [72]. One of the most important ASD risk gene is CNTNAP2 and it is found to be associated with frontal and occipital lobes of the brain [70,73]. While NRXN1 is found to be linked with parietal and frontal lobes [74]. FOXP2 is found to be linked with temporal lobes and MET in occipital and temporal lobes [75]. Genetic findings have associated cadherins as an ASD risk gene [18,[76][77][78] and a recent study identified the expression of cadherins CDH9 and CDH11 in the ASD-relevant areas of the cerebellum in mice and reported high expression of these genes in segregated populations of the Purkinje cells present in the cerebellum [79].

DNA methylation
A global methylation profiling study in lymphoblastoid cell lines derived from autistic monozygotic twins and their non-autistic siblings revealed decreased expression of RORA and BCL-2 proteins in autistic individuals as compared to the controls [80]. The study confirms how DNA methylation in idiopathic autism affects the epigenetic regulation of gene expression and the molecular changes associated with brain pathobiology in ASD [80].

Postsynaptic translational regulation
Postsynaptic density plays a critical role in the neural transmission and maturation of synapsis and forms the basis of the etiology of ASD [81]. The encoded proteins of autism associated genes located in the postsynaptic density are associated with FMRP, and there is a localization of mutated protein found in Fragile-X syndrome, which is responsible for the synthesis of proteins at the postsynaptic density [82]. The SHANK2 and SHANK3 genes are found in the postsynaptic density, which bind to neuroligins and are involved in the glutamatergic response in ASD, as well as in language and social cognition development [83]. Other candidate genes of autism include NF1, PTEN, MET, TSC1, TSC2, and CYFIP1 that are located in the duplication region (15q11-13) [84][85][86][87]. Mutations in ASD genes also implicate the protein metabolism at the synapse that is modulated by the ubiquitination pathways [88]. For example, UBE3A, which is the Angelman syndrome gene, has an important role in this pathway, in addition to genes such as FBXO40, RFWD2, USP7, and PARK2 [89,90]. This indicates that remodeling and maintenance of the synapse functioning is an important determinant in the pathology of ASD [91].

Modulation of neuronal activity
Mutations in neurexin and neuroligin families are associated with the pathophysiology of ASD [92]. found to be associated with frontal and occipital lobes of the brain [70,73]. NRXN1 is found to be linked with parietal and frontal lobes [74]. FOXP2 is found to be linked with temporal lobe and MET in occipital and temporal lobes [75]. Cadherins (CDH9 and CDH11) are found to be linked with the cerebellum region [37]. AGING Together, neurexins and neuroligins are involved in the modulation of excitatory and inhibitory synaptic functions [93]. The genes of these super families that play a significant role in ASD include NRXN1, NLGN1, NLGN3, CNTN4, CNTN6, and CNTNAP2 [94]. Neuronal activity is influenced by genes such as GRIN2B, SCN1A, and SCN2A, and they are involved in the mediation of synaptic plasticity. In addition, they encode for ion channels [32]. Neuronal activity that regulates transcription factors also regulates other genes, including UBE3A, PCDH10, DIA1, and NHE9/SLC9A9 [95,96]. Imbalances in excitation and inhibition in brain regions have been found in knockout ASD mouse models of genes, such as NRXN1, SHANK3, FMR1, CNTNAP2, and these knockout models had social interaction impairments and reduced ultrasonic vocalizations that overlapped behavioral endophenotypes relevant to ASD [91].

Synaptic plasticity
Synaptic plasticity is affected by cytogenetic abnormalities, such as the duplication of maternal allele 15q11-q13 and genetic syndromes like Rett or Fragile-X syndrome associated with ASD. In idiopathic autism, most commonly identified synaptic gene mutations include NLGN4X [96,98] or SHANK3 [33] and NLGN3. Abnormalities in the formation of synapse and disrupted pathways, such as GTPase/Ras signaling and neurogenesis, are revealed by the analysis of genes affected by rare CNVs [99,100]. The identification of specific ASD genes are found to be resisted by some de novo or inherited CNVs, for example, the 16p11 region, recur at the same locus in individuals who are not related [101]. This indicates a locus and allelic heterogeneity in ASD [101]. Another X-linked gene GLRA2 deletion has been identified in autism disorder [102]. This gene encodes the glycine receptors (GlyR) α2 subunits. These glycine receptors are involved in the mediation of inhibitory neurotransmission in the nervous system. Mutations in GLRA2 results in synaptic plasticity, language delay, cognitive and social impairments, as well as altered glycinergic signaling [102]. Mutations in Calcium voltage-gated channel subunit alpha1 C (CACNA1C) might contribute to NMDA-receptor independent synaptic plasticity associated with ASD [103]. A study showed that mutations in CACNA1C cause alterations in calcium homeostasis that contribute to the development of ASD [104].

Genes and brain connectivity
Genes involved in ASD are related to each other within many processes, including neuronal and synaptic development, modulation, protein synthesis, calcium signaling, oxytocin pathways, mTOR, and various transcriptional mechanisms (Figure 3) [105]. ASD potential endophenotypes include brain connectivity and morphology alterations [106]. A study by Frazier et al. (2014) on ASD subjects carrying heterogenous germline PTEN mutations showed cognitive malfunctioning and abnormalities in the white matter with reductions in PTEN protein compared to the healthy controls [117]. Alterations were also found in the gene-brain pathway based on the rs1858830 MET risk allele by differences seen in activation and deactivation patterns of fMRI in response to social stimuli, as well as the structural and functional connectivity in the temporal-parietal region of the brain in ASD subjects [108].

Genome-wide association study (GWAS)
Many GWASs have been performed in ASD [89,[109][110][111]. Within the intergenic region between CDH9 and CDH10 cell adhesion genes, a linkage disequilibrium block has been reported [18]. Another gene called Semaphorin 5A (SEMA5A), which plays an important role in axonal guidance and the development of neurons is found to be a susceptibility gene for ASD as a study has found a de novo microdeletion of SEMA5A in ASD and ID patients [112]. There was another genome-wide significance reported in the macro domain containing 2 (MACROD2) gene at an intronic SNP [113]. Replication and identification of a common variation on chromosome 5p14.1 associated with autism was reported by another GWAS study [57,114].

Wnt-signaling in ASD
Wnt-signaling plays an important role in the differentiation and morphology of neurons, and neurotransmission [115]. This pathway is found to be dysregulated in individuals affected with ASD [116]. Dysregulation of this pathway is found to affect the cortical and spine patterning and morphology with cytoarchitecture disruption in the cortex of the affected brains of autistic individuals [117,118]. Glycogen Synthase Kinase-3 (GSK3), which is a Wnt-signaling pathway component, plays an important role in ASD development as it was found to be hyperactive and caused impaired social interaction and increased anxiety in a GSK3 knockout mouse model [119]. Another gene, known as CHD8, which regulates the Wnt signaling pathway and promotes transcriptional factor activity in the brain, is found to be associated with ASD [120]. Knockout of CHD8 gene during cortical development resulted in the downregulation of the CHD8 gene, which lead to the reduction of the TCF/LEF transcription factor family, causing a defect in the development of the brain [121] (Figure 4). This proves that the dysregulation of the Wnt-signaling pathway affects the cortical patterning and synaptic development in individuals with ASD [122].
The DISC1 gene is associated with Wnt signaling and ASD and is involved in the inhibition of GSK3β that leads to the activation of β-catenin; thus, it acts as a positive regulator of the Wnt/β-catenin signaling [123]. Mutations in DISC1 fail to inhibit GSK3β and cause suppression of the Wnt/β-catenin signaling pathway [124]. Mutations in an intracellular Wnt/β-catenin signal pathway protein, DIX domain containing-1 (DIXDC1), displayed impairment in social behavior, coupled with anxiety and depression in mice models [125] and also showed reduction in the dendritic spines and glutamatergic synapses in brains of the experimental mice. It has been suggested that the functional sequence variants of DIXDC1 can manifest as behavioral syndromes in human due to its restricted tissue distribution property in the late developmental and postnatal central nervous system [126]. The TSC1 and TSC2 genes are also found to play a significant role in Wnt signaling [127]. These genes are associated with GSK3β and Axin and help in the degradation of βcatenin leading to the inhibition of Wnt/β-catenin mediated gene transcription. Mutations in these genes are found to increase Wnt signaling, while overexpression of these genes caused reduction in Wnt/β-catenin signaling [119,128,129]. Dedicator of cytokinesis 4 (DOCK4) is another gene that plays an important role in Wnt signaling [123]. DOCK4 is a part of the destruction complex and its decreased expression is found to reduce the transcriptional activity induced by Wnt signaling [123]. In autism, levels of DOCK4 are found to be diminished, which leads to reduced Wnt signaling and the growth of dendrites [123,130]. Several genes belonging to the non-canonical Wnt signaling pathway are found to be associated with autism [119]. The Prickle2 (Pk2) gene interacts with post synaptic density 95 (PSD-95). Mouse models with Prickle2 mutations displayed altered social, learning, and behavioral abnormalities, in addition to reductions in dendrite branching. Mutations in Ankyrin-3 (ANK3) and Prostaglandin E2 (PGE2) genes are associated with ASD [131][132][133]. ANK3 and PGE2 genes are important in neuronal development. PGE2 is regulated by Cyclooxygenase-2 (COX2) and is the main regulator of PGE2 synthesis. Studies have shown there is an association of abnormal COX2/PGE2 signaling with ASD [133]. All the findings suggest that both activation and inhibition of Wnt signaling pathway are associated with autism risk.

Presynaptic Wnt signaling
Canonical Wnt signaling or Wnt/β-catenin signaling plays an important role in the development of synapsis in the pre-and post-synaptic terminals. The release of neurotransmitters at the presynaptic terminal is triggered by the binding of Wnt ligand to a receptor that activates Dishevelled-1 (DVL1). This binds to the presynaptic proteins, such as Synapsin-1 (SYN1) and Synaptotagmin (SYT) that are associated with ASD and enhance the clustering of synaptic vesicles (SV's) and release of neurotransmitters. On the other hand, cell adhesion proteins, such as cadherins and cell adhesion complexes (NLGN/NRXN), play an important role in the modulation of presynaptic terminal activity. Their interaction regulates both excitatory and inhibitory synaptic function, disrupting the E/I balance in the postsynaptic neurons. β-catenin is bound to cadherins and their interaction is essential for the recruitment of SVs to synapses. MET, a receptor for hepatocyte growth factor (HGF), is found to have a genetic link with ASD. MET phosphorylates Tyr-142 of β-catenin and promotes its dissociation from the cadherins leading to its release in the postsynaptic terminal [119] (Figure   4). Wnt/β-catenin signaling plays a significant role in ASD as it is involved in stabilizing the synaptic structure by enhancing clustering of SVs, release of neurotransmitters and modulation of cell adhesion complexes [134].

Postsynaptic Wnt signaling
Activation of the Wnt/β-catenin signaling causes Wnt ligands to bind to the Frizzled-9 (FZD9) receptor that recruits the multi-protein destruction complex consisting of scaffolding proteins (APC and Axin), phosphatases (PP1 and PP2A), and kinases (GSK3β and CK1). This activation inhibits GSK3β and prevents the degradation of β-catenin, thus stabilizing it and translocating it to the nucleus, leading to gene transcription [123] (Figure 4). Conversely, canonical and non-canonical Wnt signaling are associated with Ca 2+ signaling. Wnt ligands are found to increase the influx of Ca 2+ in neurons, and voltage gated Ca 2+ sensitive channels, like NMDAR, allows the entrance of Ca 2+ in the postsynaptic membrane that allows long term synaptic potentiation (LTP) establishment. Both high and low responses of LTP are associated with ASD. Ca 2+ causes the activation of CAMKII, which is involved in the reorganization of cytoskeleton, calcineurin (CaN), a calcium dependent protein phosphatase and protein kinase C (PKC). The activation of CAMKII leads to the activation of transcription factor CREB, causing its translocation to the nucleus, which leads to gene transcription [135].
Hyperactive pro-growth signaling pathways involved in ASD mTOR mTOR, a highly conserved serine/threonine kinase, is important in the regulation of cell growth, cell metabolism and cell survival processes [136]. The catalytic subunits of mTOR consist of two structurally and functionally distinct protein complexes known as mTORC1 and mTORC2, which are involved in integrating information in the brain received from various intracellular and extracellular responses [137]. As mTOR is shown to be a major role player in the regulation of various processes that control synthesis of proteins, dynamics of actin cytoskeletal, regulating energy homeostasis and metabolism, the dysregulation of these pathways can lead to disorders including ASD, and neurodegeneration [138][139][140]. The disruption of mTOR pathway is associated with ASD and several other disorders that are caused by genetic alterations in mTOR pathway members, such as TSC1, TSC2, and PTEN. Also, mTOR activity levels can serve as indicators of disrupted growth states in the brain [141]. Studies have shown that several mTOR substrates such as p70 ribosomal S6 kinase 1 (S6K1) and the eukaryotic translation initiation factor 4E-binding proteins (4E-BPs) are found to be associated with ASD [142]. In particular, deletion of 4E-BP2, which is also a downstream effector of mTOR results in elevated dendritic spine density, and various behavioral abnormalities that are reminiscent of ASD [143][144][145][146]. mTORC1 complex promotes the ribosome production and translation by phosphorylating S6K1 through various effectors [147]. Hyperactivation of mTORC1 is responsible for ASD symptoms as one study has showed that mTORC1 hyperactivation in cerebellar Purkinje cells resulted in autistic like behaviors in mice [148] and it can be targeted for the treatment of ASD by modulating its expression.

Brain-derived neurotrophic factor (BDNF)
Neurotrophins play an important role in the nervous system and are involved in the regulation of neuronal development, survival, morphogenesis, differentiation and synaptic plasticity [141,149]. The most abundant neurotrophin that is found in the central nervous system (CNS) is the brain-derived neurotrophic factor (BDNF) [149]. The control of neurotrophin signaling at different epigenetic, transcriptional and translational levels are critical for the overall connectivity of neurons and other physiological functions, such as cell fate, axon and dendritic growth and synaptic pruning [150,151]. The dysregulation of neurotrophin signaling has been reported in various neurological disorders, such as Alzheimer's, Huntington's disease and autism [152][153][154]. Under normal conditions, receptors such as FMRP, TSC1/2, and PTEN regulate the excitatory activity induced by BDNF by acting on its receptor TrkB. However, in pathological conditions such as ASD, lack of this regulation leads to disruption of synaptic functions [155]. The pro-growth signaling pathways induced by other trophic factors such as insulin-like growth factor (IGF), vascular endothelial growth factor (VEGF), glialderived neurotrophic factor (GDNF) and ciliary neurotrophic factor (CNTF) are found to be dysregulated in ASD and used to categorize ASD into neural overgrowth or undergrowth types [141].

ERK/MAPK
ERK1/2 are members of the MAPK signaling cascade and play important role in the regulation of cell growth, proliferation, differentiation and apoptosis [156]. MAPK/ERK pathway is involved in the signal transduction from cell surface receptors to the nucleus and they respond to growth factors, oxidative stress, chemokines and cytokines [157]. The activation of ERK1/2 is essential for dendritic spines formation and stabilization [158,159] as well as supports the development of cerebral cortex by regulating cell cycle in neural progenitor cells proliferation. It is observed that the ERK/MAPK signaling interacts with many genes and CNVs implicated in ASD [160]. Activated or blocked levels of phospho-ERK1/2 are found to be associated with autistic phenotypes [161,162]. Thus, targeting the ERK/MAPK pathway can be used to treat cognitive and behavioral impairments implicated in ASD [160] and a recent study performed in a mouse model with 16p11.2 deletion, which is a CNV associated with autism, showed that treatment with ERK inhibitor during period of development rescued anatomical and behavioral deficits in the mice [163].

Other signaling pathways involved in ASD
There are many ASD genes that have been associated with different signaling pathways and that contribute to different ASD phenotypes (Table 1). One such pathway is the Calcium (Ca2+) and calmodulin (CaM) signaling pathway. These pathways play a significant role in the connectivity of neurons and functioning of the synapse, so dysregulation of this pathway might be responsible for the development of ASD [164,165]. Impaired Ca2+ signaling has been found in many ASD individuals [166][167][168]. In skin fibroblasts derived from ASD individuals, the agonist evoked Ca2+ signaling was found to be dysfunctional [167]. Ca2+ signaling dysregulation and activitydependent gene transcription changes were reported in a study involving induced Pluripotent Stem Cells (iPSC) that were derived from ASD individuals diagnosed with Timothy syndrome [169]. A study identified the common variants of ASD risk genes that regulated FMRP signaling showed that a SNP in the calcium/calmodulin-dependent kinase IV (CaMKIV) gene, which is a positive regulator of the FMRP transcription, causes a higher risk for the development of ASD [170]. Similarly, a de novo mutation of Glu183 to Val (E183V) in the catalytic domain of CAMKIIα increased dendritic branching and decreased synaptic transmission with reduced dendritic spine density causing ASD-related behaviors in mice [171].
Another signaling pathway known as Sonic hedgehog (SHH) plays a major role in the developmental processes of multicellular embryos [172]. It is also the main component involved in the regulation of neural patterning and polarity of the CNS [173]. Within the forebrain, hindbrain and spinal cord, SHH signaling paces up proliferation and axonal targeting [174]. The SHH pathway has also been implicated in ASD, and mutations have been observed in patched domaincontaining 1 (PTCHD1). A deficiency of this gene in male mice caused synaptic dysfunction and abnormal neuronal excitations leading to hyperactivity and cognitive alterations [175,176]. Mutations in genes 7dehydrocholesterol reductase (DHCR7) [177] and engrailed2 (EN2) have also been associated with ASD [178,179]. In addition, similar cerebellar morphological abnormalities were displayed by mouse variants of EN2 and autistic individuals [180].
Retinoic acid (RA), derived from vitamin A (retinol), is a lipophilic molecule that is essential for vertebrate development and acts as a ligand for retinoic acid receptors (RARs) and retinoid X receptors (RXRs) [181]. Vitamin A deficiency leads to a number of abnormalities and induces autistic-like behaviors in rats by suppressing the expression of CD38 in the hypothalamus of the offspring [182]. Retinoic acidrelated orphan receptor alpha (RORA) variants have been found in ASD, and decreased protein expression and abnormal methylation have been found in the autistic brain [80]. RORA regulates FOXN1 and ALDH1A3, enzymes that synthesize Retinoic Acid (RA). These RA signaling genes have been found to be associated with ASD [183].
Another signaling that is found to be associated with ASD is the fibroblast growth factor (FGF) signaling [184]. FGF belongs to the family of cell signaling proteins that play an important role in brain patterning and any dysregulation of FGF signaling can lead to various neurological disorders [185]. The pathological role of FGF signaling in ASD was displayed by a study that reported impairment of synapse formation in hippocampal neurons in mutant mice lacking FGF7 [184].
A common pathophysiological mechanism that is disrupted in ASD is the imbalance in excitatory and inhibitory neurotransmission. The excitatory mechanism is mediated by glutamate, while the inhibitory mechanism is mediated by GABA [190,191]. Studies have reported abnormalities in glutamate and GABA receptors expression in the postmortem brains of individuals affected with ASD [192]. One of the genes affecting the GABA signaling is the MECP2 gene and a study showed that MECP2 transgenic mice displayed stereotypic behaviors, ataxia, motor dysfunction and seizures [193,194].

Clinical aspects
Clinical diagnosis of ASD is primarily based on the analysis of complex behavioral and functional changes in patients during their developmental process. Genetic tests such as comparative genomic hybridization and chromosomal microarray (CMA), and G-band karyotyping can be used for the early diagnosis of ASD. CMA has been shown to have higher clinical yield and higher resolution as compared to the G-band karyotyping [195,196]. Karyotyping is used to detect chromosomal abnormalities such as translocations or small portions of chromosomes in different disorders [197]. G-banding also known as Giemsa banding is a staining technique that is used to differentiate the chromosomal arms [198]. In ASD, G-banding is considered useful as it can help in the detection of chromosomal abnormalities in individuals affected with ASD [199]. CMA test can detect gene duplications and deletions associated with ASD [200], and proves to be more efficient in analyzing different types of variations present in ASD.
Improvement of emotional, physical and behavioral symptoms are one of the main aspects in the pharmacological treatment of ASD [201]. To treat these symptoms underlying ASD, one of the main goals is the identification of genes and biomarkers. Next generation sequencing (NGS) is a complex emerging clinical practice that is opening a new way for the identification of ASD-causing genes that includes abnormal social interaction and communication [202]. NGS helps in the identification of rare alleles, defects of single gene and variations of gene function. It includes whole-genome sequencing (WGS) and whole-exome sequencing (WES) [203,204].
A wide range of antiepileptic drugs (AEDs) are used for effective treatment of ASD. AEDs are psychotropic drugs that modulate electrochemical activity in the brain and can induce a positive or negative affect on mood and behavior [205]. One of the reasons of using AEDs in treating ASD is high incidence of epilepsy in most of the ASD affected individuals. Research has shown that AEDs treatment improved communication and behavior in ASD affected individuals with epileptic discharges [206]. Valproic acid, lamotrigine, levetiracetam and ethosuximide are most commonly used AEDs, and they are found to reduce seizures in ASD individuals [207]. Another AED, topiramate when combined with an antipsychotic drug risperidone reduced hyperactivity, irritability and stereotypical behaviors in ASD individuals [208]. Some AEDs such as sodium valproate may have negative effect on the developing fetus if the mother takes this drug during pregnancy. Sodium valproate can lead to an abnormal brain development leading to neurological disorders such as intellectual disability and autism [209,210]. Also AEDs such as lamotrigine can enhance or have a mood leveling effect, while AEDs such as levetiracetam are associated with side effects in behavior such as aggression, anxiety or nervousness and hostility [211,212]. There is a limitation of the efficacy of AEDs medications in individuals affected with ASD because AEDs show improvement in only specific type of behaviors such as hyperactivity, impulsivity, mood instability, repetitive behaviors and aggression [213].
Although there are no pharmacological treatments that are able to treat the core symptoms of ASD but there are psychotropic drugs that have similar effect as AEDs in alleviating the common symptoms of ASD such as irritability, hyperactivity, lack of focus, mood dysregulation, and social withdrawal [214].
Oxytocin is another pharmacological agent currently being used to treat core ASD symptoms [215].
Controlled trial studies showed the intravenous administration of oxytocin in ASD patients improved the symptoms in various domains including social behavior [216][217][218]. Apart from the few limitations of oxytocin such as dosage establishment, children safety and route of administration, it can be used as a potential therapeutic agent to treat ASD [105]. AGING Further studies are required to relate the pharmacological treatment with the genomic changes in ASD for better treatment planning. We expect that in few years there will be enough genomic data that can be used for the pharmacological analysis of patients with ASD.

CONCLUSIONS
The genetic architecture of ASD is heterogeneous and differs in every individual. The current identification of ASD is mostly based on observation of behaviors and the genetics that underlie ASD are still an active area of research. Nevertheless, advancements in the study of various molecular mechanisms encompassing the genetics of autism and the identification of many ASD risk genes have opened a new way to study the pathophysiology of ASD. We envisage that the identification of new biomarkers, risk genes and associated genetic pathways may help in the early diagnosis of ASD, and improvement in clinical and pharmacological treatments of the disorder.

ACKNOWLEDGMENTS
This study was supported by a PI grant from the Sidra Medicine (50610110002) to Mohammad Haris.

CONFLICTS OF INTEREST
All authors declare no conflicts of interest.

FUNDING
This study was funded by Sidra medicine, Doha, Qatar.