Abstract
Cerebral arachnoid cysts (ACs) are one of the most common and poorly understood types of developmental brain lesion. To begin to elucidate AC pathogenesis, we performed an integrated analysis of 617 patient–parent (trio) exomes, 152,898 human brain and mouse meningeal single-cell RNA sequencing transcriptomes and natural language processing data of patient medical records. We found that damaging de novo variants (DNVs) were highly enriched in patients with ACs compared with healthy individuals (P = 1.57 × 10−33). Seven genes harbored an exome-wide significant DNV burden. AC-associated genes were enriched for chromatin modifiers and converged in midgestational transcription networks essential for neural and meningeal development. Unsupervised clustering of patient phenotypes identified four AC subtypes and clinical severity correlated with the presence of a damaging DNV. These data provide insights into the coordinated regulation of brain and meningeal development and implicate epigenomic dysregulation due to DNVs in AC pathogenesis. Our results provide a preliminary indication that, in the appropriate clinical context, ACs may be considered radiographic harbingers of neurodevelopmental pathology warranting genetic testing and neurobehavioral follow-up. These data highlight the utility of a systems-level, multiomics approach to elucidate sporadic structural brain disease.
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Data availability
The sequencing data for all AC parent–offspring trios and singletons from the healthcare-acquired cohort have been deposited in the NCBI database of Genotypes and Phenotypes and AnVIL (https://anvilproject.org/data/studies/phs000744/) under the accession number phs000744.v4.p2. Patients referred to GeneDx are consented to aggregate, de-identified research and subject to US Health Insurance Portability and Accountability Act (HIPAA) privacy protections. The patient-level alignment, phenotypic and variant call data for the GeneDx cohort cannot be shared without a HIPAA Business Associate Agreement. Access to the de-identified, aggregate data used in this analysis is available upon request to GeneDx, provided that a HIPAA Business Associate Agreement is established. Under those conditions, researchers can request the de-identified, aggregate data from GeneDx by contacting smcgee@genedx.com and can expect to receive the requested data within approximately 26 weeks.
Code availability
The software utilized in this study is available at the following web addresses: SAMtools version 1.3.1 (https://github.com/samtools/samtools); GATK HaplotypeCaller version 3.7.0 (https://github.com/broadinstitute/gatk/releases); GATK GenotypeGVCFs version 3.7.0 (https://github.com/broadinstitute/gatk/releases); GATK VariantRecalibrator version 3.7.0 (https://github.com/broadinstitute/gatk/releases); TrioDeNovo version 0.6.0 (http://genome.sph.umich.edu/wiki/Triodenovo); denovolyzeR version 0.2.0 (http://denovolyzer.org); DeNovoWEST 42 version 1.0.0 (https://github.com/queenjobo/DeNovoWEST); PLINK version 1.9 (http://pngu.mgh.harvard.edu/~purcell/plink); MetaSVM/cadd13/ANNOVAR version 4.2 (http://annovar.openbioinformatics.org); R version 3.5.0 (https://www.r-project.org/); Python version 2.7 (https://www.python.org/downloads/); EIGENSTRAT version 7.2.1 (https://github.com/DReichLab/EIG/tree/master/EIGENSTRAT); DMLE+ version 2.3 (http://dmle.org/); enrichR R package version 3.0 (https://cran.r-project.org/web/packages/enrichR/index.html); GOrilla (http://cbl-gorilla.cs.technion.ac.il/); QIAGEN December 2021 release (http://www.ingenuity.com); txt2hpo version 0.2.3 (https://github.com/GeneDx/txt2hpo); phenopy version 0.3.0 (https://github.com/GeneDx/phenopy); Monocle R package version 3 (https://cole-trapnell-lab.github.io/monocle3/); and disgenet2r R package version 0.0.9 (https://www.disgenet.org/static/disgenet2r/disgenet2r.html). Our in-house pipelines and codes are available at https://github.com/Kahle-Lab/Arachnoid-Cyst.
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Acknowledgements
We are grateful to the patients and families who participated in this research for their invaluable role in this study. This work is supported by the Yale–National Institutes of Health (NIH) Center for Mendelian Genomics (5U54HG006504); R01 NS111029-01A1, R01 NS109358, K12 228168 and the Rudi Schulte Research Institute (to K.T.K.); the NIH Medical Scientist Training Program (NIH/National Institute of General Medical Sciences grant T32GM007205); an NIH Clinical and Translational Science Award from the National Center for Advancing Translational Sciences (TL1 TR001864); the K99/R00 Pathway to Independence Award R00HL143036 (to S.C.J.); the Children’s Discovery Institute Faculty Scholar award CDI-FR-2021-926 (to S.C.J.); the Vernon W. Lippard Research Fellowship; and the Howard Hughes Medical Institute.
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A.J.K. and K.T.K. designed and conceptualized the study. A.J.K., G.A., S. McGee, K.Y.M., V.G., E.K., P.Q.D., H.S., J.O., J.S., A.A., M.L.D., C.G.F., A.T.T., H.M.Q., A.A.E., B.S.C., M.G., R.P.L., F.M., R.I.T., S.C.J. and K.T.K. performed cohort ascertainment, recruitment and phenotypic characterization. I.R.T., C.C., F.L.-G. and S. Mane produced and validated the exome sequencing data. G.A., S. McGee, V.G., A.J.K., S.Z., Y.-C.W., A.T.T., J.R.K., P.-Y.F., W.D., F.M., R.I.T., S.C.J. and K.T.K. performed the exome sequencing analysis. G.A., E.K. and K.T.K. performed the integrative genomics analysis. A.J.K., S. McGee, K.Y.M., V.G., A.M.-D.-L. and K.T.K. performed the phenomics analysis. G.A., A.J.K., S.C.J. and W.D. performed the statistical analysis. C.N.-W. performed Sanger sequencing validation. A.J.K., A.M.-D.-L. and K.T.K. performed neuroimaging characterization. S.H. performed the biophysical simulation. C.N.-W., S. Mane, M.G., R.P.L, R.I.T., S.C.J. and K.T.K. provided resources. A.J.K., G.A., S. McGee, K.Y.M., E.K., S.L.A., M.G., R.P.L., F.M., R.I.T., S.C.J. and K.T.K. wrote and reviewed the manuscript. A.J.K., G.A., S. McGee, K.Y.M., R.I.T., S.C.J. and K.T.K. performed project administration. R.P.L., S.C.J. and K.T.K. acquired funding and supervised the project.
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Extended data
Extended Data Fig. 1 Graphical summary of the methodological framework of the study.
Graphical summary of the methodological framework of the study.
Extended Data Fig. 2 De novo variation (DNV) rate closely approximated Poisson distribution in AC cases and controls.
The observed number of DNVs per subject (bars) compared to the numbers expected (lines) from the Poisson distribution in the case (red) and control (blue) cohorts. ‘p’ denotes chi-squared p-value. P-values determined by Chi-squared goodness of fit test, two sided. Not adjusted.
Extended Data Fig. 3 Quantile-quantile (Q-Q) plot comparing observed versus expected p-values.
(a) DeNovoWEST derived plots for de novo variants (DNVs) in each gene in 617 AC cases. ADNP, ARIDB1, KDM5C, PURA, FOXP1, and MAP2K1 exhibit exome-wide significant enrichment for all DNVs in AC cases. ARID1B, ADNP, and FOXP1 exhibit significant enrichment of loss-of-function (LoF) DNVs comprising premature termination, frameshift, or splice-site variants. KDM5C and MAP2K1 exhibit significant enrichment of missense variants. ARID1B, FOXP1, ADNP, and KDM5C exhibit significant enrichment of protein-altering variants, including missense and predictive LoF DNVs. ARID1B, ADNP, FOXP1, MAP2K1, PURA, and KDM5C exhibit significant enrichment of protein-damaging variants, including D-mis and LoF DNVs. There is no significant enrichment of synonymous DNVs among the 617 cases. Grey areas within graphs represents 95% confidence interval for expected values. (b) DenovolyzeR derived plots for DNVs in each gene in 617 AC cases. ARID1B, PURA, ADNP, and FOXP1 exhibit exome-wide significant enrichment for all DNVs in AC cases. ARID1B and ADNP exhibit significant enrichment of LoF DNVs. MAP2K1 exhibits significant enrichment of damaging-missense (D-mis) variants (MetaSVM = ‘D’ or MPC > 2 damaging missense). ARID1B, ADNP, FOXP1, MAP2K1, and KDM5C exhibit significant enrichment of protein-altering variants. ARID1B, ADNP, FOXP1, MAP2K1, and DDX3X exhibit significant enrichment of protein-damaging variants. There is no significant enrichment of tolerated-missense (T-mis) DNVs or synonymous DNVs among the 617 cases. The grey areas within graphs represents 95% confidence interval centered around the observed = expected line.
Extended Data Fig. 4 Phenomic heat map of traits identified in AC patients harboring de novo variants (DNVs) in exome-wide significant AC risk genes.
Subject phenotypes were determined by text2HPO natural language processing of medical record data (https://github.com/GeneDx/txt2hpo).
Extended Data Fig. 5 Integrative genomic findings within meningeal cell dataset.
(a) Enrichment of AC genes in meningeal gene modules. Numbers displayed exceed the Bonferroni-corrected statistical significance threshold tested by one sided Fisher’s exact test and are -log10(p-value). pAC: possible AC gene set; hcAC; high-confidence AC gene set; EWS exome-wide significant; Mod: module. (b) GOrilla and WikiPathways analyses of enriched arachnoid cell module 3. P-values determined by one sided Fisher’s exact test. Bonferroni-corrected significance threshold denoted by the vertical yellow line. Top terms displayed. (c) Enrichment of gene modules in specific meningeal cell types. P-values by one sided Fisher’s exact test. Modules in red have similar meningeal cell-type enrichment compared to AC risk gene meningeal cell-type enrichment. The red asterisk highlights significant enrichment (Bonferroni corrected) for cell types in the pAC gene set.
Supplementary information
Supplementary Information
Supplementary Figs. 1 and 2 and Tables 1–5.
Supplementary Table 6
Top 20 gene markers per cell cluster in the Spatio-Temporal Cell Atlas of the Human Brain dataset ranked by log2[fold change].
Supplementary Table 7
Top 20 gene markers per cell cluster in the the embryonic forebrain meningeal dataset ranked by log2[fold change].
Supplementary Table 8
Phenotype groupings of HPO terms.
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Kundishora, A.J., Allington, G., McGee, S. et al. Multiomic analyses implicate a neurodevelopmental program in the pathogenesis of cerebral arachnoid cysts. Nat Med 29, 667–678 (2023). https://doi.org/10.1038/s41591-023-02238-2
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DOI: https://doi.org/10.1038/s41591-023-02238-2
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