Abstract

   Cilia are dynamic microtubule-based organelles present on the surface
   of many eukaryotic cell types and can be motile or non-motile primary
   cilia. Cilia defects underlie a growing list of human disorders,
   collectively called ciliopathies, with overlapping phenotypes such as
   developmental delays and cognitive and memory deficits. Consistent with
   this, cilia play an important role in brain development, particularly
   in neurogenesis and neuronal migration. These findings suggest that a
   deeper systems-level understanding of how ciliary proteins function
   together may provide new mechanistic insights into the molecular
   etiologies of nervous system defects. Towards this end, we performed a
   protein–protein interaction (PPI) network analysis of known
   intraflagellar transport, BBSome, transition zone, ciliary membrane and
   motile cilia proteins. Known PPIs of ciliary proteins were assembled
   from online databases. Novel PPIs were predicted for each ciliary
   protein using a computational method we developed, called
   High-precision PPI Prediction (HiPPIP) model. The resulting cilia
   “interactome” consists of 165 ciliary proteins, 1,011 known PPIs, and
   765 novel PPIs. The cilia interactome revealed interconnections between
   ciliary proteins, and their relation to several pathways related to
   neuropsychiatric processes, and to drug targets. Approximately 184
   genes in the cilia interactome are targeted by 548 currently approved
   drugs, of which 103 are used to treat various diseases of nervous
   system origin. Taken together, the cilia interactome presented here
   provides novel insights into the relationship between ciliary protein
   dysfunction and neuropsychiatric disorders, for e.g. interconnections
   of Alzheimer’s disease, aging and cilia genes. These results provide
   the framework for the rational design of new therapeutic agents for
   treatment of ciliopathies and neuropsychiatric disorders.

   Subject terms: Developmental biology, Molecular neuroscience

Introduction

   Cilia are dynamic organelles projecting from the surface of many types
   of eukaryotic cells. They detect changes in the extracellular
   environment and transduce signals into the cell to regulate a wide
   variety of physiological and developmental processes. They can be
   either motile or non-motile, and exhibit a microtubule organization of
   9 + 2 or 9 + 0, respectively^[30]1. Primary cilia are sensory
   organelles modulating several core signaling and cellular polarity
   pathways that are fundamental for tissue homeostasis and embryonic
   development^[31]2. Motile cilia drive the flow of bodily fluids
   including mucus and cerebrospinal fluid^[32]3,[33]4. Defects involving
   the primary cilia are observed in various human ciliopathies such as
   Bardet-Biedl syndrome (BBS), Joubert syndrome and Meckel–Gruber
   syndrome. Motile cilia defects are seen in primary ciliary dyskinesia
   (PCD), male infertility and laterality defects^[34]5.

   The cilium is a complex organelle comprising over 600 proteins^[35]1.
   Underscoring their functional importance, many of these ciliary
   proteins are highly evolutionarily conserved including the
   intraflagellar transport (IFT) complexes located within the axoneme
   involved in bidirectional protein transport between the ciliary base
   and the tip, complexes localizing to the transition zone (TZ) at the
   ciliary base acting as a ‘ciliary gate’ regulating protein trafficking
   into and out of the cilia and BBSomes mediating cilia
   assembly^[36]6–[37]8.

   Primary cilium is increasingly viewed as a hub for neuronal signalling.
   A large body of evidence has emerged demonstrating the role of cilia in
   the development and function of the central nervous system
   (CNS)^[38]9–[39]11. Gene knockdown of BBS proteins such as BBS1,
   BBS4-5, BBS7, and BBS9-12 lead to cortical defects and improper
   neuronal migration, highlighting the significance of cilia genes in
   brain development^[40]12. Additionally, neural tube defects are
   observed in the brain with the disruption of cilia-transduced sonic
   hedgehog signaling (Shh) and Wnt signaling^[41]13,[42]14. Indeed, many
   ciliopathies are known to be associated with neurological deficits such
   as developmental delays, cognitive impairment and neuropsychiatric
   disorders including ataxia, autism spectrum disorders and
   schizophrenia^[43]10,[44]12. Importantly, the ciliary proteins AHI1,
   ARL13b, CDKL5 and EFHC1 have been implicated in autism spectrum
   disorder, epilepsy, and schizophrenia^[45]15–[46]18. A recent study
   identified neuropsychiatric risk genes (NEK4, SDCCAG8, FEZ1, CEP63,
   PDE4B and SYNE1) to be linked to cilia assembly and function^[47]15. In
   addition, several ciliary proteins interact with proteins that are
   known to play a role in neuropsychiatric disorders: PCM1, BBS4 with
   DISC1 in schizophrenia, bipolar disorder and depression^[48]19,[49]20,
   KIF3A, PCNT with DCDC2 in dyslexia^[50]21,[51]22, and PCM, AHI1 with
   HTT in Huntington disease^[52]12,[53]23,[54]24. Hydrocephalus, a
   phenotype observed frequently in BBS and other ciliopathies, may
   reflect the role of motile cilia in the flow of cerebrospinal fluid in
   the brain^[55]10. Ciliopathies have also been associated with obesity,
   suggesting a role for cilia in the neural circuitry responsible for
   monitoring food intake and satiety^[56]25. The obesity-related genes
   MC4R and ADCY3 co-localize to primary cilia of hypothalamic neurons,
   and impairing this localization or blocking their signalling in primary
   cilia led to gain in body weight in mice^[57]26.

   Given the importance of large multi-protein complexes in its assembly
   and function, knowledge of the protein–protein interactions (PPIs) of
   ciliary proteins would help to elucidate the potential role of cilia
   biology in neuropsychiatric diseases. Studies based on PPI networks
   have significantly advanced our knowledge of specific proteins or the
   diseases that they are associated with, such as DISC1 in schizophrenia,
   or the NPHP-JBTS-MKS protein complex in ciliopathies^[58]27. DISC1 was
   a novel protein with well-characterized domains but of unknown function
   with no known human homolog, when it was identified as being associated
   with schizophrenia^[59]28,[60]29. To understand the function of DISC1,
   its PPIs were determined using yeast 2-hybrid technology^[61]30,[62]31.
   This led to a large number of studies, which connected DISC1 to cAMP
   signaling, axon elongation and neuronal migration. A study revealed
   that the role played by DISC1 in dopamine signaling, which is
   implicated in schizophrenia, may also involve primary cilia on
   neurons^[63]19. DISC1 localized to primary cilia on rat striatal
   neurons and was found to be involved in the formation and maintenance
   of cilia with certain dopamine receptors^[64]19. The PPI network of
   ciliary proteins CEP290 and RPGR revealed their connection to
   photoreceptors, and disruption of this network has been shown to cause
   blindness on rapid degeneration of photoreceptors, a finding associated
   with several ciliopathies^[65]32.

   Large-scale proteomic and protein interactome analyses have
   significantly advanced our understanding of its role in developmental
   biology and disease^[66]33–[67]37. Multidimensional protein
   identification technology (MudPIT) was used to identify 195 candidate
   primary cilia proteins localizing to sensory cilia, or linked to known
   ciliopathies^[68]33. 850 interactors of nine NPHP/JBTS/MKS proteins
   (i.e. Nephronophthisis/Joubert/Meckel-Gruber syndromes) were identified
   using the G-LAP-Flp purification strategy, and several cilia-specific
   modules, namely ‘NPHP1-4-8’ functioning at the apical surface,
   ‘NPHP5-6’ at centrosomes and ‘MKS’ linked to hedgehog signaling were
   uncovered^[69]34. In another study, in vivo proximity-dependent
   biotinylation (BioID) was used to identify more than 7,000 interactions
   of 58 centriole, satellite and ciliary transition zone proteins, which
   revealed protein modules involved in cilia and centrosome
   biogenesis^[70]35. The interactome of CPLANE (ciliogenesis and planar
   polarity effector) proteins, namely that of Inturned (INTU), Fuzzy
   (FUZ) and Wdpcp (WDPCP), consisting of ~ 250 interactions, was
   identified using LAP-tagged immunoprecipitation, and it was shown that
   the CPLANE proteins govern IFT-A/B trafficking^[71]36. Systematic
   tandem affinity purifications coupled to mass spectrometry was employed
   to identify 4,905 interactions and 52 complexes for 217 proteins with
   known or suspected involvement in ciliary function or disease, and this
   study linked vesicle transport, the cytoskeleton and ubiquitination to
   ciliary signaling and proteostasis^[72]37. None of these experimental
   methods are single handedly capable of identifying all the possible
   interactions of ciliary genes. In fact, it is the ability of an
   experimental method to discover interactions not detected by another
   method that makes it truly valuable. Machine learning methods can
   computationally predict new interactions that other high throughput
   detection methods may fail to capture and serve as
   hypotheses-generation methods that may be validated by other
   experimental methods. Here, we applied computational method that we
   developed previously to discover novel PPIs of 165 ciliary proteins and
   analyzed the resulting ciliary PPI interactome for novel associations
   and potential connections to neuropsychiatric diseases.

Experimental procedures

Dataset

   Compilation of Cilia Gene List: We obtained a list of 165 cilia genes
   that were curated from literature by prioritizing the genes based on
   their association with cilia from Dr. Gregory Pazour’s lab building
   upon their prior work^[73]38. This list includes IFT proteins, BBS
   proteins, TZ proteins, ciliary membrane proteins, and proteins
   restricted to motile cilia. Known PPIs were collected from Human
   Protein Reference Database (HPRD)^[74]39 and Biological General
   Repository for Interaction Datasets (BioGRID)^[75]40. Gene-drug
   associations and ATC classifications were collected from
   DrugBank^[76]41, while neuropsychiatric gene-disease associations were
   collected from the GWAS catalog ([77]www.ebi.ac.uk/gwas/). Random gene
   sets used in shortest path comparisons were sampled from about twenty
   thousand human proteins listed in the Ensembl database
   ([78]www.ensembl.org).

   Novel PPIs were predicted using the HiPPIP model that we
   developed^[79]42. Each ciliary protein (say C[1]) was paired with each
   of the other human genes say, (G[1], G[2], … G[n]), and each pair
   was evaluated with the HiPPIP model. The predicted interactions of each
   of the cilia genes were extracted, which resulted in 620 newly
   discovered PPIs of cilia genes. The average shortest path distance was
   computed using the Networkx package in python. Pathway associations
   were computed using Ingenuity Pathway Analysis suite. GO term
   enrichment was carried out using BinGO^[80]43; for each C[1], a list of
   its known and predicted interacting partners (i.e. B[1], B[2], … B[n])
   are given as input to BinGO, which extracts the GO terms of all these
   genes and finds which of the GO terms are statistically enriched in
   comparison to the background distribution of GO terms of all human
   proteins. All statistically significant terms are assigned as
   network-based enriched GO terms of C[1].

   Gene expression datasets in Gene Expression Omnibus were used to
   compute the overlap of the cilia interactome with genes differentially
   expressed in various neuropsychiatric disorders: major depressive
   disorder ([81]GSE53987^[82]44), schizophrenia ([83]GSE17612^[84]45),
   bipolar disorder ([85]GSE12679^[86]46), autism spectrum disorder
   ([87]GSE18123^[88]47), Alzheimer’s disease ([89]GSE29378^[90]48 and
   [91]GSE28146^[92]49), Parkinson’s disease ([93]GSE28894) and
   non-syndromic intellectual disability ([94]GSE39326^[95]50). Genes with
   fold change > 2 or < ½ were considered as significantly overexpressed
   and underexpressed respectively at p value < 0.05. A gene with
   transcripts per million ≥ 2 was considered to be ‘expressed’ while
   analyzing the overlap of the interactome with genes expressed in the
   amygdala, anterior cingulate cortex, caudate, cerebellum, frontal
   cortex, hippocampus, hypothalamus, nucleus accumbens, putamen, spinal
   cord and substantia nigra extracted from GTEx^[96]51. Time-dependent
   gene expression variation in the hippocampal region was extracted from
   BrainSpan Atlas containing RNA-Seq data from post-conceptional weeks to
   middle adulthood^[97]52. 78 genes associated with Alzheimer’s disease
   were extracted from DisGeNET^[98]53 (with score > 0.2 to include only
   expert-curated disease-gene associations). Then, to construct the
   Alzheimer’s disease interactome, whose overlap was to be checked with
   the cilia interactome, 4,742 known PPIs extracted from HPRD^[99]54 and
   BioGRID^[100]55, and 490 computationally predicted PPIs of these 78
   genes were assembled. The biological validity of the interactome was
   shown by the fact that 676 genes out of the 3,944 genes in the AD
   interactome are differentially expressed in CA1 hippocampal gray matter
   from patients with severe Alzheimer's disease versus healthy controls
   ([101]GSE28146^[102]49), out of which 71 were novel interactors (p
   value = 1.138e−20).

Results

   We assembled a list of 165 genes encoding proteins known to be
   associated with primary and/or motile cilia, including IFT, BBS, TZ,
   and ciliary membrane proteins, as well as proteins restricted to motile
   cilia. Known PPIs of ciliary proteins were assembled from HPRD and
   BioGRID^[103]40,[104]56. Novel PPIs were predicted for each of the
   cilia genes using our High-precision Protein–Protein Interaction
   Prediction (HiPPIP) model^[105]42. In this manner, a ciliary protein
   interactome was assembled comprising 165 ciliary proteins (red color
   square shaped nodes) with 1,011 known PPIs (blue edges) and 765 novel
   PPIs (red edges) that connect to 800 previously known interactors
   (light blue nodes) and 705 novel interactors (red nodes) (Fig. [106]1
   and Table [107]1). We predicted 216 new interactions for 50 out of the
   56 cilia genes that had no known PPIs. For example, GPR83 has 12 novel
   PPIs, LRRC48 has 10, PKD1L1 has 10, and SPEF has 10 novel PPIs. The
   number of known and novel PPIs of cilia genes are given in
   Supplementary File [108]1, and the lists of all genes and PPIs is given
   in Supplementary File [109]2.

Figure 1.

   [110]Figure 1
   [111]Open in a new tab

   Cilia interactome. Cilia genes are shown as small dark-blue colored
   nodes and interactor genes are larger round nodes; the interactors are
   colored in light blue if they are previously known interactors and in
   red if they are found only through novel PPIs. PPIs are shown as edges,
   where blue color edges are known PPIs and red color edges are novel
   predicted PPIs. Most genes at the bottom of the figure have had zero
   known PPIs, and have multiple novel predicted PPIs.

Table 1.

   Novel interactors of each of the cilia genes.
   Cilia gene K N Novel interactors
   AHI1 1 2 ARFGEF3, IFNGR1
   AK7 0 3 BEGAIN, C14orf177, SLC25A29
   ARL13B 1 4 MINA, CRYBG3, ARL6, DHFRL1
   ARMC4 3 3 ARHGAP21, OTUD1, PIP4K2A
   ATP8A2 1 3 C1QTNF9B-AS1, WASF3, SACS
   ATXN10 9 9 TTLL12, RIBC2, SMC1B, GGA1, KCNH3, PIK3R2, KIAA0930, SAMM50,
   CERK
   B9D1 7 3 TNFRSF13B, USP22, GIT1
   B9D2 2 7 PLEKHG2, YIF1B, CCDC97, CNFN, CEACAM21, ZNF574, CNTD2
   BBIP1 0 0 None
   BBS1 13 6 ACTN3, BAK1, BAD, ATP6AP2, PEPD, POLR2G
   BBS2 11 10 APOC2, WRNIP1, CETP, GOT2, SPTSSA, CES1, CNOT1, HSF4,
   MAP2K5, KCNK17
   BBS4 13 5 ANP32A, AAGAB, MRPL28, SEMA7A, IGDCC3
   BBS5 5 11 SLC6A15, CCDC173, KLHL41, CTSK, COTL1, EIF4EBP3, UBR3,
   KLHL23, ORM2, PRDM2, HRH1
   BBS7 5 8 ANXA5, PDE8B, MSH6, MAD2L1, TRPC3, NDNF, QRFPR, CNGA1
   BBS9 0 6 NME8, CD33, EHMT2, TRGV9, FGF2, CAPN1
   CASC1 1 2 GOLT1B, PYROXD1
   CBY1 8 3 APOL2, BCR, SPTLC3
   CC2D2A 0 3 CPEB2, NCAPG, RAB28
   CCDC114 8 4 CGB8, EXOC3L2, CGB7, CGB1
   CCDC135 6 0 None
   CCDC39 0 1 TTC14
   CCDC40 1 3 NARF, RPTOR, WDR45B
   CCDC63 0 2 ALKBH2, C12orf76
   CCDC65 0 3 FAM186B, DNAJC22, RHEBL1
   CCNA1 32 7 VDR, RFC3, GJB2, ZNF385A, PSMB9, SLC7A1, EDEM1
   CDK3 17 10 CCDC47, CA4, ALG1, TLK2, ITIH4, PRKCA, PECAM1, NAP1L1,
   FOXJ1, TBX2
   CEP290 2 0 None
   CETN1 4 10 ALDH7A1, CCNH, GABRE, MUL1, YES1, LGALS3, PTPRM, USP14,
   TPD52L2, PTAFR
   CETN2 9 12 ATP6AP1, C14orf166, ATP2B3, NUCB1, DKC1, PTPRN, CLIC2,
   DNASE1L1, TEX28, IL2RG, DDX3X, CORIN
   CETN3 6 11 ATP6AP1L, HSP90AB1, HOXD10, SGOL1, FABP4, HAPLN1, TNNT1,
   P3H1, DNAJC19, POLR3G, PRKD3
   CHMP5 14 6 NUP98, UBAP1, DYNLL2, TMEM8B, DOPEY2, GPX3
   DAW1 2 1 RAB25
   DDI2 0 3 AADACL3, CELA2A, PRAMEF1
   DNAAF1 0 2 LINC00311, KCNG4
   DNAAF2 1 4 ATL1, TRIM9, L2HGDH, TMX1
   DNAAF3 0 7 ACPT, BRSK1, SIGLEC14, SIGLEC12, LENG9, LILRA5, ZNF606
   DNAH1 0 7 ABHD14A, SEPSECS, LIN7B, POC1A, RPP30, GNL3, G3BP1
   DNAH10 0 3 GATC, RILPL2, TMEM120B
   DNAH11 0 3 CPVL, GGCT, IL6
   DNAH12 0 1 PDE12
   DNAH14 1 6 ACBD3, CNIH3, ENAH, TMEM63A, SDE2, MIXL1
   DNAH17 0 0 None
   DNAH2 0 6 CDK18, CCDC42, KCTD11, ODF4, PIK3R6, KRBA2
   DNAH3 0 7 ERI2, TCIRG1, SOD1, THUMPD1, NPIPB3, LOC81691, IVL
   DNAH5 0 13 CTNND2, CKB, CDH6, DAP, LARGE, MYO10, TLE1, MVP, RAN, TRIO,
   MARCH6, MICAL1, RBFOX2
   DNAH6 0 1 PLGLB1
   DNAH7 2 9 CSTF3, SHC1, STK17B, STAT4, METTL21A, TMEFF2, NABP1,
   TMEM194B, MIB2
   DNAH8 0 3 TOMM6, RAB44, RASGRP1
   DNAH9 0 3 YBX2, NLGN2, STX8
   DNAI1 2 6 ATG10, CDKN2A, ZIC3, NPR2, METTL21B, GLDC
   DNAI2 0 1 MFSD11
   DNAJB1 28 10 CYP4F3, ARR3, CEP72, ADGRL3, ELAVL3, DNM2, ILF3, LYL1,
   SH3BP1, SSTR2
   DNAJB13 0 4 BDKRB1, ARFRP1, KLHL35, WISP1
   DNAL1 0 3 CIPC, LIN52, SLIRP
   DNAL4 9 9 DDX17, CACNA1I, UBA7, TRIOBP, TOM1, GTPBP1, RHOT2, JOSD1,
   HMGXB4
   DNALI1 5 3 GJA4, GJB5, TMEM200B
   DRC1 1 4 C2orf44, CENPO, C2orf16, TCF23
   DRC7 6 8 CCDC102A, ADGRG5, CPNE2, C16orf70, ZNF319, USB1, NDUFB9, MT4
   DRD1 11 5 AP3M1, PLCD1, RARS, PPP4C, KCNMB1
   DRD2 20 13 CASP1, CCNA2, CD3G, CD3E, GPC6, SGSH, VWA5A, INPPL1, IL10RA,
   PSG7, NQO2, RBM22, E2F6
   DRD5 5 2 NKX3-2, FGFBP2
   DYNLL1 76 5 RFC5, SUDS3, GABRQ, WSB2, VSIG10
   DYNLL2 47 9 C17orf67, CHMP5, C17orf47, HSF5, STXBP4, F13A1, KIF2B,
   PRKD3, MSI2
   DYNLRB1 6 2 CBFB, PDRG1
   DYNLRB2 4 8 WWOX, SDR42E1, TGFBI, ZNF134, SLC38A8, NECAB2, IRF2BPL,
   MPHOSPH6
   DYNLT1 28 7 CRHBP, ACAT2, SYNJ2, RPS6KA2, TMEM143, PARK2, ERO1L
   DYNLT3 7 4 CYBB, IFITM1, UIMC1, FOS
   DYX1C1 4 3 GCOM1, PRTG, WDR72
   DZIP1L 4 3 PRR23B, NME9, PRR23C
   EFHC1 6 2 CENPQ, ADGRF4
   ESYT3 0 2 FAIM, SLC35G2
   GALR2 1 1 EIF4A3
   GALR3 0 4 EIF3D, CEP72, ENTHD1, SUV420H1
   GAS8 0 7 FANCA, COX7B, DPEP1, MYLIP, MVD, MC1R, TAF1C
   GPR161 0 3 C1orf112, TOR1AIP1, TBX19
   GPR83 0 12 FUT4, CST1, CDK2AP1, AQP3, FGF13, PLSCR3, TYR, TPBG, JRKL,
   MRE11A, NINJ1, SPR
   HEPH 0 1 MSN
   HSPB11 2 4 C1orf168, C1orf87, RPS26P15, PARS2
   HYDIN 1 2 FAM96B, CFDP1
   IFT122 1 2 ZNF148, SLCO2A1
   IFT140 4 7 DNAJA3, ZNF263, SLC9A3R2, RAB11FIP3, TELO2, IL32, TRAP1
   IFT172 2 4 EFR3B, DNAJC27, RAB10, TMEM214
   IFT20 28 7 ABHD15, COASY, HLCS, RALGPS2, RICTOR, TP53I13, RAB11FIP4
   IFT22 0 5 C7orf43, NFE4, ORAI2, KMT2E, ZNF655
   IFT27 2 5 DDX17, TNRC6B, KDELR3, TRIOBP, TAB1
   IFT43 2 3 ELMSAN1, LIN52, NEK9
   IFT46 0 6 NLRX1, TMPRSS4, SCN3B, TRAPPC4, SIDT2, PDZD3
   IFT52 1 2 SPINT3, TOMM34
   IFT57 4 6 CLTA, CASP8, CBLB, HTT, SLC25A3, TERT
   IFT74 0 0 None
   IFT80 1 5 FGFR4, OTOL1, SLITRK3, NMD3, ZBBX
   IFT81 1 6 ERP29, NAA25, TPCN1, SLC8B1, SDS, RPH3A
   IFT88 6 6 C1QTNF9B-AS1, ALDH8A1, MAP4K5, PDX1, TRIM24, SAP18
   INVS 5 2 ABCA1, TMEM245
   IQCB1 1 6 CD80, UPK1B, TRH, LMOD1, PVRL3, TBL1X
   LCA5 3 1 FILIP1
   LOXHD1 0 4 HDHD2, HAUS1, C18orf25, SKA1
   LRRC48 0 10 ELAC2, GID4, EIF3E, FUNDC2, SMCR8, ZNF287, SPECC1, PLAGL1,
   ZNF624, SOD2
   LRRC56 0 2 KRTAP5-1, MOB2
   LRRC6 2 1 ST3GAL1
   MCHR1 2 8 GRAP2, EP300, APOBEC3A, MASP2, EFCAB6, TCIRG1, MRPS18A, ST13
   MKS1 2 5 ABCC3, DGKE, CACNA1G, RNF43, SMG8
   NEK8 4 0 None
   NME5 2 8 HBEGF, APTX, MKRN1, IFITM1, VDAC1, SPOCK1, VIPR1, P4HA2
   NME8 1 2 BBS9, SUGCT
   NPHP1 15 2 BCL2L11, COX5B
   NPHP3 2 15 CCDC50, ANAPC13, COL7A1, ASTE1, NAA50, DPP7, EPC1, DDX3Y,
   CDV3, DNAJC13, PIK3R4, TOPBP1, PARP14, PPP2R3A, RAB6B
   NPHP4 1 6 FBXO44, EDIL3, C1orf127, TMEM201, SCRG1, RBP7
   NPY2R 4 3 APOC3, ABCE1, SMAD1
   NPY5R 4 2 MDH2, KIF23
   PDCD6IP 37 5 ATG7, CLASP2, FBXL2, CRTAP, STAC
   PIH1D1 31 5 CABP5, C19orf73, RCN3, RASIP1, PRKG2
   PKD1 24 9 NTHL1, NADSYN1, PDPK1, OR1F1, DDX58, NTN3, RPL3L, SOX17, PPL
   PKD1L1 0 10 C7orf69, ABCC3, C7orf65, ACAA2, C7orf57, MGAT2, ABCA13,
   RPL6, PLCB2, PSME3
   PKD2 14 6 KIF11, ADH1C, MTAP, ADH1A, PPP3CA, UCHL3
   PKD2L1 3 6 MYOF, HNRNPA2B1, LGI1, CAB39, GBF1, PRPS2
   PKHD1 1 7 ORM1, CSTF2T, ILK, ATXN2, EML4, BAG2, PTGIS
   PPIL6 0 2 AK9, CEP57L1
   PPP1CB 26 9 NRBP1, DHX57, GCKR, NCOA1, MATN1, SRD5A2, UPK2, SH3KBP1,
   ZNF512
   PTCH1 65 5 CORO2A, ECM2, DPP3, TMOD1, UFM1
   QRFPR 0 9 BBS12, BBS7, NDNF, EXOSC9, ADAD1, KIAA1109, TRPC3, TNIP3,
   TMEM155
   RABL5 0 0 None
   ROPN1L 3 4 FAM173B, 42435, CMBL, CCT5
   RPGR 11 5 NUDT12, ATP6AP2, USP9X, SLC9A7, TSPAN7
   RPGRIP1 23 1 SLC6A2
   RPGRIP1L 3 2 CES1P1,SLC6A2
   RSPH1 1 7 LINC01547, OSMR, COL18A1, LINC00313, LINC00334, LRRC3, UMODL1
   RSPH10B 0 7 DAGLB, CCZ1B, FOXK1, MMD2, RBAKDN, GRID2IP, SLC29A4
   RSPH3 5 6 PNLDC1, MRPL18, RGS17, TAGAP, SERAC1, SYTL3
   RSPH4A 0 6 LACE1, HS3ST5, FAM26F, FLJ34503, FAM26E, ZUFSP
   RSPH6A 0 1 SLC1A5
   RSPH9 2 9 C6orf223, LRRC73, OARD1, KLHDC3, ADCY10P1, TSPO2, TCTE1,
   TAF8, SPATS1
   RTDR1 13 0 None
   SMO 8 1 LINC-PINT
   SPAG1 3 7 MME, NIPAL2, CPQ, POLR2K, RGS22, COL4A1, STK3
   SPAG16 2 1 IKZF2
   SPAG17 0 2 GDAP2, FAM46C
   SPAG6 2 2 OTUD1, PIP4K2A
   SPEF2 0 10 C5orf42, BRIX1, NIPBL, LMBRD2, DNAJC21, CAPSL, NADK2,
   UGT3A1, TARS, WDR70
   TCTE1 1 7 KLC4, C6orf223, LRRC73, KLHDC3, SPATS1, TAF8, RSPH9
   TCTE3 1 4 TCP10, LINC01558, RPS6KA2, RNASET2
   TCTN1 0 3 GLTP, SVOP, FAM222A
   TCTN2 0 3 COQ5, KDM2B, CCDC92
   TCTN3 0 0 None
   TMEM17 0 3 FAM161A, COMMD1, C2orf74
   TMEM216 1 9 TEX40, SAC3D1, ATL3, EFEMP2, CABP2, CCDC87, SSH3, POLA2,
   TRMT112
   TMEM231 3 4 TMEM170A, CNTNAP4, ADAT1, VAT1L
   TMEM237 2 2 ATP6V1C2, SFXN5
   TMEM30B 0 4 BCAR1, SLC38A6, C14orf37, NAA30
   TMEM67 1 4 NDUFAF6, INTS8, FAM92A1, LAPTM4B
   TRAF3IP1 27 3 ATG4B, ANO7, SNED1
   TSG101 86 10 PILRA, RPS13, MYLPF, DNAJB11, CALML5, ST5, PPP2R5D,
   MAPK15, ZNF160, ZNF419
   TTC21B 0 4 COBLL1, G6PC2, CSRNP3, CERS6
   TTC28 3 4 GATSL3, TPST2, PES1, PITPNB
   TTC30B 0 7 FKBP7, CCDC141, PLEKHA3, RBM45, HNRNPA3, SESTD1, TTC30A
   TTC8 1 1 PTPN21
   VPS28 27 7 THEM6, CCNB1, OXCT1, OPLAH, RPL37A, SCRIB, CACNA1I
   VPS37A 7 4 MICU3, CCAR2, COL11A2, KIAA1456
   VPS4B 7 2 SPHAR, PHLPP1
   WDR19 0 3 NWD2, TLR10, CHRNA9
   WDR35 0 0 None
   WDR63 0 2 RPL17P5, RPF1
   WDR78 0 1 GNG12
   ZMYND10 10 2 ACTR3, RALGDS
   ZMYND12 0 3 ERMAP, C1orf50, CABIN1
   [112]Open in a new tab

   The table shows the number of known and computationally predicted novel
   PPIs for each of the 165 cilia genes, and lists their corresponding
   novel interactors.

   For each of the ciliary proteins, we computed the enrichment of gene
   ontology (GO) terms among its interacting partners in order to aid in
   the discovery of its function using BinGO (Biological Networks Gene
   Ontology tool)^[113]43. This information is especially useful for those
   ciliary proteins that have either no known or very few known GO
   biological process terms. For example, there are 11 genes that have no
   known GO terms, and we predicted new GO terms for each of those genes,
   for e.g. 27 novel GO terms for ARMC4, 11 for CCDC63, and 30 for DNAAF2.

   We computed the pathway associations of genes in the interactome, using
   the Ingenuity Pathway Analysis (IPA) suite (Ingenuity Systems,
   [114]www.ingenuity.com). This showed a significant overlap of neuronal
   pathways with the cilia interactome (see selected pathways in Table
   [115]2). The complete list of all pathways, their p values and the
   genes from the interactome that are associated with these pathways, are
   given in Supplementary File [116]3. We also extracted information about
   drugs targeting the genes in the interactome. This analysis showed that
   there are several genes that are targets to drugs belonging to the
   Anatomic category of “nervous system”, highlighting the connection
   between cilia and the nervous system as shown in Fig. [117]2 and
   Supplementary File [118]4.

Table 2.

   Overlap of neuronal pathways in cilia interactome.
   Neuronal pathways in cilia interactome p value Number of proteins
   Proteins
   Huntington's disease signaling 1.00E−13 15
   PLCB2,SHC1,CASP1,GNG12,PIK3R6,POLR2G,PIK3R4,CLTA,PIK3R2,CAPN1,PDPK1,RPH
   3A,CASP8,POLR2K,PRKD3
   Dopamine-DARPP32 feedback in cAMP Signaling 2.00E−08 8
   PLCB2,PPP2R3A,PRKG2,CALML5,PLCD1,PPP2R5D,PPP3CA,PRKD3
   CREB signaling in neurons 3.02E−08 11
   CALML5,PLCB2,SHC1,GNG12,PIK3R6,POLR2G,PIK3R4,PIK3R2,PLCD1,POLR2K,PRKD3
   nNOS signaling in neurons 8.13E−06 4 PPP3CA,CAPN1,CALML5,PRKD3
   nNOS signaling in neurons 8.13E−06 4 PPP3CA,CAPN1,CALML5,PRKD3
   Axonal guidance signaling 8.91E−06 15
   PLCB2,GIT1,SHC1,PIK3R6,ACTR3,NTN3,GNG12,MICAL1,PIK3R4,MYLPF,PLCD1,PPP3C
   A,PRKD3,SEMA7A,PIK3R2
   eNOS signaling 1.17E−05 13
   BDKRB1,CALML5,AQP3,CNGA1,CASP8,SLC7A1,HSP90AB1,PIK3R6,PIK3R4,PIK3R2,PDP
   K1,CHRNA9,PRKD3
   Synaptic long term potentiation 1.26E−05 5
   PPP3CA,PLCB2,PRKD3,CALML5,PLCD1
   Wnt/Beta-catenin signaling 1.62E−05 6
   CDKN2A,TLE1,PPP2R3A,ILK,SOX17,PPP2R5D
   Neuregulin signaling 3.63E−05 8
   SHC1,TMEFF2,HSP90AB1,HBEGF,BAD,PIK3R2,PDPK1,PRKD3
   Neuropathic pain signaling in dorsal horn neurons 0.000224 7
   PLCB2,FOS,PIK3R6,PIK3R4,PIK3R2,PLCD1,PRKD3
   Calcium signaling 0.000603 8
   TNNT1,SLC8B1,CABIN1,CALML5,TRPC3,PPP3CA,ATP2B3,CHRNA9
   Dopamine receptor signaling 0.00251 3 PPP2R5D,SPR,PPP2R3A
   Glutamate receptor signaling 0.00398 1 CALML5
   Synaptic long term depression 0.00676 7
   PLCB2,PPP2R3A,NPR2,PLCD1,PRKG2,PPP2R5D,PRKD3
   Wnt/Ca + pathway 0.0102 3 PPP3CA,PLCB2,PLCD1
   Dendritic cell maturation 0.0102 12
   PLCB2,STAT4,COL11A2,COL18A1,CD80,TRGV9,IL6,PIK3R6,PIK3R4,IL32,PIK3R2,PL
   CD1
   Reelin signaling in neurons 0.0407 3 PIK3R6,PIK3R4,PIK3R2
   [119]Open in a new tab

   Neuronal pathways which were present in cilia interactome with number
   of novel interactors.

Figure 2.

   Figure 2
   [120]Open in a new tab

   Number of drugs targeting genes in the cilia interactome. The numbers
   are shown separated by the anatomic category of the drugs (anatomic,
   therapeutic and chemical classification) and also separated by whether
   they target known interactors (blue) or novel interactors (red) or both
   (cream-colored).

Experimental Validation of novel cilia PPIs in independent studies

   Four of the novels PPIs that we predicted for cilia genes were
   independently recovered by other groups. TMEM237-SFXN5 and
   DYNLL2-c17orf47 were recovered by yeast two-hybrid experiments in the
   recent release of the human protein interactome map^[121]57. We also
   predicted two PPIs of IFT140 that were discovered as part of the CPLANE
   interactome using affinity purification-mass spectrometry, but were not
   deposited in BioGRID or HPRD: IFT140-TELO2 and IFT140-TRAP1^[122]36. It
   is also worth noting that 8 novel interactors in the interactome
   appeared among the proteins isolated from the primary cilia of mouse
   kidney cells using a method called MudPIT (multidimensional protein
   identification technology)^[123]33: ABCE1, CCDC47, CCT5, G3BP1, GBF1,
   RAB10, RAN and USP14. 94 genes in the cilia interactome, including 44
   cilia genes, 36 known and 14 novel interactors, were also recovered as
   regulators of the ciliary sonic hedgehog pathway in a CRISPR genetic
   screen (p value = 2.28e−19)^[124]58. The interactome was also
   significantly enriched with genes differentially expressed in bronchial
   biopsies of primary ciliary dyskinesia patients (p
   value = 2.64e−02)^[125]59.

Functional interactions of cilia genes with predicted novel interactors

   We used ReactomeFIViz^[126]60, a Cytoscape plugin, to extract known
   functional interactions between cilia genes and their novel
   interactors. Five novel PPIs had such functional interactions, namely,
   IFT57-CLTA, DYNLL2-KIF2B, IFT57-HTT, CHMP5-UBAP1 (‘part of the same
   complex’, ‘bound by the same set of ligands’) and IFT57 → CASP8
   (‘activation’).

Discussion

   We developed the interactome of ciliary proteins that included IFT,
   BBS, TZ, ciliary membrane proteins and proteins in motile cilia. The
   interactome includes novel computationally predicted PPIs for multiple
   proteins, including proteins with few or no previously known PPIs.

   Both analysis of individual novel PPIs and the cilia interactome as a
   whole has the potential to highlight connections to specific
   neurological disorders and lead to biologically insightful and
   clinically translatable results. We interpreted the functions of
   individual novel PPIs using literature-based evidence and top pathways
   obtained from IPA (See Supplementary File [127]5 for testable
   hypotheses on novel PPIs involved in neuropsychiatric disorders,
   primary ciliary dyskinesia, hydrocephalus and in biological processes
   such as ciliogenesis and trafficking of membrane receptors in cilia).
   The following is a demonstrative example of a systems-level analysis.

Cilia, Alzheimer’s disease and aging

   Alzheimer’s disease (AD) is a progressive neurodegenerative disease
   with an estimated prevalence of 10–30% in the population aged 65 years
   and more, characterized by memory loss (dementia), behavioral changes,
   impaired cognition and language^[128]61. Around two-thirds of dementia
   cases is attributed to AD^[129]61. Hippocampus, a region in the brain
   critical to memory and learning, exhibits signs of neurodegeneration in
   the early stages of AD^[130]62. It has been speculated that memory and
   learning deficits in AD may be associated with aging and reduced
   neurogenesis in the hippocampus^[131]62–[132]64. It is interesting to
   note that primary cilia have been shown to mediate sonic hedgehog
   signaling (Shh) to regulate hippocampal neurogenesis^[133]65,[134]66.
   So, we explored interconnections of AD, aging and cilia in the PPI
   network (the ‘interactome’), while asking the following questions: Are
   genes associated with AD, aging and cilia closely connected in the
   interactome? Will such a network also include genes involved in Shh
   signaling and neurogenesis, and genes expressed in the hippocampus?
   What specific biological processes may underlie the connections of AD
   to aging, and will they interact with the Shh pathway?

   Significant overlap was found between cilia and the AD interactomes (p
   value = 0.022). The AD interactome was highly significantly enriched in
   ‘human aging-related genes’ (p value = 1.77e−37), compiled from the
   GenAge database^[135]67. 51 aging genes co-occurred in AD and cilia
   interactomes. The subnetwork of these 51 genes and their AD and cilia
   interactors is shown in Fig. [136]3. In this subnetwork, aging genes
   connected cilia genes with/without Shh involvement to AD genes
   (Fig. [137]3).The next question we asked was: do any of the 51 genes
   directly interact with a ciliary gene involved in the Shh pathway? 15
   cilia genes in the network were also recovered as regulators of the Shh
   pathway in a CRISPR genetic screen: ARL13B, BBS1-2, BBS4-5, BBS7, CBY1,
   DYNLL1, IFT140, IFT20, IFT52, IFT81, PTCH1, STUB1 and TRAF3IP1^[138]58.
   These 15 genes had direct interactions with 14 aging genes, 6 AD genes
   and 2 cilia genes. This included 13 novel predicted interactions
   connecting aging genes to cilia genes including 4 Shh genes (in
   italics): BAK1-BBS1, CDKN2A-DNAI1, TRAP1-IFT140, PDPK1-PKD1,
   SOD1-DNAH3, CCNA2-DRD2, TERT-IFT57, HTT-IFT57, FOS-DYNLT3, EP300-MCHR1,
   SHC1-DNAH7, PRKCA-CDK3 and RICTOR-IFT20. The network was significantly
   enriched in the GO term ‘neurogenesis’ (p value = 5.66e−12) and in
   genes expressed in the hippocampus (transcripts per million ≥ 2) (p
   value = 2.54e−09). The cilia genes DYNLT1 and PKD1 were associated with
   neurogenesis, and IFT20, IFT140, PTCH1 and BBS4 were Shh regulators
   also associated with neurogenesis. Reduced size of hippocampus was
   noted in mutant mouse models of 5 cilia genes, namely BBS1, BBS2, BBS4,
   BBS7 and PDCD6IP (Mammalian Phenotype Ontology term: small
   hippocampus)^[139]68–[140]70. We next identified the biological
   processes that may be specifically affected in AD in relation to its
   links with aging. 75 genes in the network were differentially expressed
   in the hippocampus of AD patients compared with non-AD subjects
   ([141]GSE48350^[142]71, [143]GSE36980^[144]72, [145]GSE1297^[146]73,
   [147]GSE28146^[148]49, [149]GSE29378^[150]48). We then examined the
   fold change in the normal expression of these 75 genes in the
   hippocampus at 40 years compared with 8 post-conceptional weeks. For
   this, we used the 'developmental transcriptome' from the BrainSpan
   Atlas containing RNA-Seq data of up to 16 brain regions from
   post-conceptional weeks (number of weeks elapsed from the first day of
   the last menstrual period and the day of the delivery) to middle
   adulthood (up to 40 years)^[151]52. The genes were grouped based on the
   specific direction in which their expression varied in AD versus aging
   (i.e. fold change in same/opposite directions in AD versus non-AD
   hippocampal samples compared with expression at 40 years versus 8
   post-conceptional weeks) (Fig. [152]4). 42 genes showed an expression
   change in the opposite direction in AD versus aging. Out of this, 18
   genes were underexpressed in AD but overexpressed in aging; they were
   enriched in the GO term ‘calcium-mediated signaling’ (p
   value = 8.72e−09). It has been postulated that calcium signaling
   pathways involved in cognition may be remodeled by an activated
   amyloidogenic pathway in AD, resulting in elevated levels of calcium
   and a constant erasure of new memories through enhancement of
   mechanisms involved in long term depression^[153]74. It is also worth
   noting that Shh signaling requires calcium mobilization^[154]75. The 18
   genes included the cilia genes DYNLL1, DYNLT3, PKD1 and MCHR1, and the
   ciliary Shh regulator BBS7. 24 genes were overexpressed in AD but
   underexpressed in aging; they were enriched in ‘circulatory system
   development’ (p value = 3.04e−07). Loss of hippocampal blood vessel
   density accompanied by ultrastructural changes in the blood vessels
   have been observed in a senescence-accelerated rat model of AD^[155]76.
   It is interesting to note that circulatory system processes were found
   to be upregulated in early stages of AD-like pathology in this model,
   while they were found to be downregulated with age, similar to our
   observations^[156]76. It is also interesting to note that
   neovascularization requires Shh signaling^[157]77. The 24 genes
   included the cilia genes CCDC40, SPAG6, ZMYND10, DNALI1 and SPAG1, BBS2
   and CBY1 which are ciliary Shh regulators, DYNLT1, a cilia gene
   involved in neurogenesis and PTCH1 which is an Shh ligand also involved
   in neurogenesis. 25 genes showed an expression change in the same
   direction (either under/overexpression) in AD versus aging including
   the cilia genes VPS4B, CCNA1, DYNLRB2, NPHP1, DNAH7 and the ciliary Shh
   regulator BBS5; ‘negative regulation of cell death’ was enriched in
   this group (p value = 1.59e−09). Shh maintains neural stem cells in the
   hippocampus by inhibiting cell death^[158]78.

Figure 3.

   [159]Figure 3
   [160]Open in a new tab

   Interconnections between cilia, aging and Alzheimer’s disease genes.
   Cilia genes are shown as red nodes; AD genes are colored in cyan and
   aging genes in green. PPIs are shown as edges, where grey edges are
   known PPIs and red color edges are novel predicted PPIs. Genes with
   bold labels are involved in the sonic hedgehog (Shh) pathway and those
   with blue labels are involved in neurogenesis. Note that, in this case,
   a bold blue-labeled gene indicates a cilia gene with Shh involvement,
   which is also involved in neurogenesis.

Figure 4.

   [161]Figure 4
   [162]Open in a new tab

   Direction of fold change of gene expression levels in AD vs. non-AD
   hippocampal samples compared with expression at 40 years vs. 8
   post-conceptional weeks. The X-axis shows the 67 genes that are
   differentially expressed in the hippocampus of Alzheimer’s disease
   patients compared with the hippocampus of healthy subjects. The red
   bars on the Y-axis show the fold change of the differential expression
   of these genes in AD vs. non-AD hippocampal samples. The blue bars on
   the Y-axis show the fold change in the expression level of these genes
   in normal hippocampus at 40 years after birth (middle adulthood)
   compared with 8 weeks after conception (fetal life) in healthy humans.

   In summary, our analysis demonstrates that aging and AD genes directly
   interact with ciliary Shh regulators in the interactome. This network
   is enriched in genes associated with neurogenesis and expressed in the
   hippocampus. Genes involved in calcium-mediated signaling and
   circulatory system development are differentially expressed in the
   opposite direction in AD versus aging, whereas genes involved in
   regulation of cell death are differentially expressed in the same
   direction.

Cilia and neuronal pathways and functions

   Our pathways enrichment analysis of the cilia interactome revealed
   several neuronal pathways with high statistical significance (see Table
   [163]2 and Supplementary File [164]3). This included axonal guidance
   signaling pathway with 15 novel cilia interactors, Huntington disease
   signaling with 15 novel interactors, eNOS signaling pathway with 13,
   Wnt signaling with 6, DARPP32 feedback in cAMP signaling with 8,
   dopamine receptor signaling with 3, synaptic long-term depression with
   7, and synaptic long-term potentiation with 5 novel interactors.
   Dopamine receptors are localized in the membrane of neuronal
   cilia^[165]19, suggesting that these novel cilia interacting partners
   may have a role in neurotransmission. Dopamine signaling, eNOS
   signaling, and synaptic long term potentiation pathways are also known
   to be associated with neuropsychiatric disorders such as
   schizophrenia^[166]79,[167]80. The identification of Huntington’s
   disease (HD) pathway in the cilia interactome is also notable given
   that the protein huntingtin (HTT) localizes to the centrosome and plays
   an important role in ciliogenesis. The HD mutant mouse model exhibits
   abnormal cilia motility and cerebrospinal fluid flow^[168]23. Recovery
   of Wnt signaling thought to be involved in schizophrenia etiology is
   also of interest^[169]81,[170]82.

   Analysis of the known and novel PPIs and GO term associations
   identified a role for cilia in neuronal disease pathogenesis. While
   consistent with the known role of cilia in several key processes in the
   nervous system such as the neuronal signaling and development, these
   findings reveal novel connections between cilia and these functional
   modules. The defects in neuronal migration and differentiation are the
   underlying cause of abnormal neural circuitry in psychiatric
   disorders^[171]12. This is further supported by the reported linkage of
   neuropsychiatric risk genes to cilia^[172]15,[173]19 and the finding of
   neuropsychiatric phenotypes and brain abnormalities in
   ciliopathies^[174]5,[175]12. Our interactome analysis shows that TCTN2,
   cilia gene with known role in neuronal development and
   migration^[176]12 has 3 novel interactors and neuronal GO terms such as
   initiation of neural tube closure, midbrain morphogenesis and mid brain
   development are enriched among the interacting partners. The GO terms
   that are enriched for interacting partners of ARMC4 include sympathetic
   neuron projection guidance, axonogenesis, axon extension, and axon
   fasciculation. Dynein gene, DNAAF2 has only one known but 4 predicted
   interactions. Two of those novel interactors, ATL1 and TRIM9 are shown
   to be associated with cognitive performance and psychosis respectively
   through GWAS. The GO terms such as axonogenesis, neuron maturation,
   synaptic growth at neuromuscular junction are enriched among the
   interacting partners. Ciliary membrane genes DRD1 and DRD2 that are
   implicated in neurotransmission and linked to mental illnesses such as
   schizophrenia^[177]83 were identified with 4 and 12 novel interactors,
   respectively; the associated GO terms were neuronal action potential
   and synaptic plasticity regulation. We also observed 4 novel
   interactors for the cilia protein TMEM67, including two proteins
   associated with cilia assembly, LAPTM4B and NDUFAF6, with NDUFAF6 also
   known to be associated with Alzheimer’s disease^[178]84. Both ATG7, a
   novel interactor of the ciliary protein PDCD6IP, and SPR, a novel
   interactor of GPR83 have been associated with Parkinson’s
   disease^[179]85,[180]86. GIT1, a novel interactor of B9D1 is associated
   with attention deficit hyperactivity disorder and MME, a novel
   interactor of SPAG1with Alzheimer’s disease^[181]87. On inspecting
   mammalian phenotype ontology (MPO) terms
   ([182]www.informatics.jax.org/), 42 novel interactors were found to be
   associated with various morphological or physiological aspects of brain
   in mice. For example, the novel interactor ITSN1 was associated with
   decreased brain size, abnormal corpus callosum, hippocampal fimbria,
   hippocampal fornix, brain white matter and anterior commissure
   morphology. These findings support the role of these novel interactions
   and the GO terms in understanding the crucial role played by cilia
   biology in neuropsychiatric disorders.

Overlap of cilia and neuropsychiatric disorder interactomes

   To examine the connection between cilia and neuropsychiatric disorders,
   we computed the overlap between their interactomes. We considered 7
   neuropsychiatric disorders (NPDs), namely Attention Deficit
   Hyperactivity Disorder (ADHD), Major Depressive Disorder (MDD),
   schizophrenia, bipolar disorder, autism spectrum disorder, Alzheimer’s
   disease and Parkinson’s disease. We extracted the genes associated with
   each disorder from the GWAS catalog ([183]www.ebi.ac.uk/gwas/) and then
   assembled disorder-specific interactomes with known PPIs from HPRD and
   BioGRID. We then computed how closely connected the cilia genes are to
   NPD genes by computing how many genes or interactors were shared
   between the cilia interactome and each NPD interactome. This analysis
   showed the overlap to be statistically significant (Table [184]3). For
   example, cilia interactome has an overlap of 88 genes with ADHD
   interactome (p value = 1.2E−16) of which 17 are novel interactors of
   cilia. Similar comparisons with other NPDs also showed overlaps as
   shown in Table [185]3.

Table 3.

   Overlap of neuropsychiatric disease (NPD) interactomes and genes
   differentially expressed in NPDs with the cilia interactome.
   NPD NPD interactome size p value of overlap # Genes common to both
   interactomes # Novel interactors common to both # Genes differentially
   expressed in the disorder # Genes differentially expressed in the cilia
   interactome p value of overlap # Differentially expressed novel genes
   ADHD 406 1.20E−16 88 17 n/a n/a n/a n/a
   Alzheimer's disease 417 2.20E−24 104 19 1,103 106 4.70E−05 46
   Autism spectrum disorder 53 2.20E−05 15 5 3,692 314 2.40E−04 119
   Bipolar disorder 764 3.10E−29 163 31 1,188 101 3.40E−02 38
   Major depressive disorder 974 3.70E−23 177 32 187 21 2.50E−02 8
   Parkinson's disease 520 1.20E−20 112 18 2,487 258 6.20E−03 104
   Schizophrenia 688 1.50E−16 125 26 1,320 118 5.60E−03 40
   Intellectual disability n/a n/a n/a n/a 706 75 6.50E−03 32
   [186]Open in a new tab

   The significance of the overlap along with the number of genes common
   to the NPD interactome/expression datasets and the cilia interactome
   are shown.

Overlap of cilia interactome with genes differentially expressed in
neuropsychiatric disorders

   965 genes in the cilia interactome were found to be expressed
   (transcripts per million ≥ 2) in several brain regions including
   amygdala, anterior cingulate cortex, caudate, cerebellum, frontal
   cortex, hippocampus, hypothalamus, nucleus accumbens, putamen, spinal
   cord and substantia nigra, from GTEx RNA-Seq data^[187]51 (p
   value = 3.93E−58). Novel interactors of cilia genes were found to be
   highly statistically enriched among these genes expressed in the human
   brain (p value = 8.14E−09).

   We then computed the overlap of genes differentially expressed in
   neuropsychiatric disorders with the genes in the cilia interactome. We
   analyzed gene expression datasets of MDD ([188]GSE53987)^[189]44,
   schizophrenia ([190]GSE17612)^[191]45, bipolar disorder
   ([192]GSE12679)^[193]46, autism spectrum disorder
   ([194]GSE18123)^[195]47, Alzheimer’s disease ([196]GSE29378)^[197]48,
   Parkinson’s disease ([198]GSE28894) and non-syndromic intellectual
   disability ([199]GSE39326)^[200]50. The analysis showed the overlap to
   be statistically significant (Table [201]3). For example, the cilia
   interactome has an overlap of 106 genes with genes differentially in
   the Alzheimer’s disease dataset (p value = 4.7E−05) of which 46 are
   novel interactors of cilia.

Cilia and nervous system drug targets

   Given the strong connection between the cilia interactome and neuronal
   pathways, we tested the possibility of repurposing drugs targeting
   proteins in the cilia interactome for treating neurological disorders.
   Identifying new uses for drugs shortens the time of drug discovery and
   approval^[202]88. For example, the drug amantadine which is used to
   treat influenza infection was successfully repurposed to treat
   dyskinesia and Parkinson’s disease^[203]88. This analysis identified
   548 drugs targeting 184 genes in the cilia interactome. These fall into
   3 major Anatomic Therapeutic Chemical (ATC) classification system
   categories, nervous system with 99 drugs, 102 drugs in the respiratory
   system, and 98 drugs in the cardiovascular system (Fig. [204]2,
   Supplementary File [205]4). This finding points at therapeutics
   targeting the cilia proteins which may provide a novel strategy for
   treating neurological disorders.

   Overall, 76 nervous system drugs targeted 7 novel interactors: HRH1,
   SLC6A2, CHRNA9, NQO2, ORM1, CACNA1I and CACNA1G. 57 drugs targeting 22
   genes in the interactome are used in the treatment of at least one
   among the following neurological disorders- Parkinson’s disease,
   Alzheimer’s disease, attention deficit hyperactivity disorder (ADHD),
   major depressive disorder (MDD), autism spectrum disorder,
   schizophrenia and bipolar disorder- out of which 35 drugs target 6
   novel interactors, namely CACNA1G, CACNA1I, CHRNA9, HRH1, SLC6A2 and
   ORM1. 10 out of these 57 drugs targeted cilia genes as well as known
   and novel interactors of cilia genes: asenapine, chlorpromazine,
   clozapine, loxapine and paliperidone are schizophrenia drugs,
   olanzapine is used in the treatment of Alzheimer’s disease and
   schizophrenia, amphetamine in ADHD, imipramine in ADHD and MDD,
   mirtazapine in MDD and nortriptyline in schizophrenia, ADHD, MDD and
   bipolar disorder.

   Among other novel interactors targeted by nervous system drugs is
   SLC6A2 which is involved in neurotransmission and is associated with
   ADHD^[206]89,[207]90. SLC6A2 interacts with RPGRIP1L, a ciliary protein
   known to cause Joubert syndrome, MKS and bipolar
   disorder^[208]91,[209]92. The novel interactors CACNA1I and CACNA1G
   targeted by nervous system drugs are calcium channels that are known to
   be associated with Alzheimer’s disease and schizophrenia,
   respectively^[210]93,[211]94. These novel interactors which are drug
   targets may have significant impact on the nervous system, and the
   pathogenesis of neurological disorders.

   In an independent study, we proposed that the drug acetazolamide which
   targets the genes CA2 and CA4, having known interactions with the cilia
   genes, DYNLL1 and CDK3 respectively, may be repurposed for
   schizophrenia based on negative correlation of drug-induced versus
   disease-associated gene expression profiles and other biological
   evidences^[212]95. Acetazolamide is currently under consideration for
   funding for clinical trial. Several cancer drugs with reported effects
   on ciliogenesis target known and novel interactors in the cilia
   interactome. Vinblastine targeting JUNN, a known interactor of BBS7 and
   TSG101, and TUBB, a known interactor of NPHP1 and DYNLL1, inhibits
   cilia regeneration in partially deciliated Tetrahymena (a unicellular
   ciliate)^[213]96. Valproic acid targeting HDAC9, a known interactor of
   PKD1, restores ciliogenesis in pancreatic ductal adenocarcinoma
   cells^[214]97. Gefitinib targeting EGFR, a known interactor of PDCD6IP,
   inhibits the smoking-induced loss of ciliated cells in the
   airway^[215]98. Gefitinib also increases the percentage of ciliated
   cells in human pancreatic cancer cell lines^[216]99. Geldanamycin
   targeting HSP90AB1, a novel interactor of CETN3, induces lengthening of
   cilia in 3T3-L1, a fibroblast cell line^[217]100.

Conclusion

   We identified novel PPIs of cilia proteins and their associated
   pathways, their enriched Gene Ontology term associations, and drugs
   that target the interactors. This cilia interactome analysis reveals a
   link between cilia function, neuronal function and neurological
   disorders. We also demonstrated the interconnections of Alzheimer’s
   disease, cilia and aging genes. The predicted interactions will have to
   be validated at the level of network perturbations in the disease state
   by comparing neuropsychiatric patients with healthy controls. However,
   one has to be aware of a few caveats while studying the role of ciliary
   genes in neuropsychiatric disorders (NPDs). Association of a ciliary
   gene with a NPD can be unequivocally ascertained only if this
   association is discovered within the ciliary compartment in the context
   of the particular NPD, i.e. a mechanistic link between ciliary function
   and the disorder has to be demonstrated. It may not be a true
   association if a ciliary gene was shown to be associated with a NPD in
   a cellular context not connected with cilia; a protein may perform its
   function at different subcellular locations. Mapping the interactome of
   cilia genes would be useful in carrying out network-based systems
   biology studies, which will help elucidate the contribution of these
   novel PPIs to nervous system disease pathology as well as to develop
   novel therapeutics for these disorders.

Supplementary information

   [218]Supplementary Information 1.^ (36.7KB, docx)
   [219]Supplementary Information2.^ (110.5KB, xlsx)
   [220]Supplementary Information 3.^ (14.1KB, xlsx)
   [221]Supplementary Information 4.^ (127.4KB, xlsx)
   [222]Supplementary Information 5.^ (145.1KB, docx)
   [223]Supplementary Information 6.^ (149.7KB, pdf)
   [224]Supplementary Information 7.^ (1.8MB, cys)

Acknowledgements