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. 2019 Aug 29;105(3):606–615. doi: 10.1016/j.ajhg.2019.07.019

Redefining the Etiologic Landscape of Cerebellar Malformations

Kimberly A Aldinger 1, Andrew E Timms 2, Zachary Thomson 1, Ghayda M Mirzaa 1,3, James T Bennett 2,3, Alexander B Rosenberg 4, Charles M Roco 5, Matthew Hirano 4, Fatima Abidi 6, Parthiv Haldipur 1, Chi V Cheng 1, Sarah Collins 1, Kaylee Park 1, Jordan Zeiger 1, Lynne M Overmann 7, Fowzan S Alkuraya 8, Leslie G Biesecker 9, Stephen R Braddock 10, Sara Cathey 6, Megan T Cho 11, Brian HY Chung 12, David B Everman 6, Yuri A Zarate 13, Julie R Jones 6, Charles E Schwartz 6, Amy Goldstein 14,15, Robert J Hopkin 16, Ian D Krantz 15,17, Roger L Ladda 18,19, Kathleen A Leppig 20, Barbara C McGillivray 21, Susan Sell 18, Katherine Wusik 22, Joseph G Gleeson 23, Deborah A Nickerson 24,25, Michael J Bamshad 3,24,25, Dianne Gerrelli 26, Steven N Lisgo 7, Georg Seelig 4,27, Gisele E Ishak 1,28, A James Barkovich 29, Cynthia J Curry 30, Ian A Glass 1,3, Kathleen J Millen 1,3, Dan Doherty 1,3, William B Dobyns 1,3,31,∗
PMCID: PMC6731369  PMID: 31474318

Abstract

Cerebellar malformations are diverse congenital anomalies frequently associated with developmental disability. Although genetic and prenatal non-genetic causes have been described, no systematic analysis has been performed. Here, we present a large-exome sequencing study of Dandy-Walker malformation (DWM) and cerebellar hypoplasia (CBLH). We performed exome sequencing in 282 individuals from 100 families with DWM or CBLH, and we established a molecular diagnosis in 36 of 100 families, with a significantly higher yield for CBLH (51%) than for DWM (16%). The 41 variants impact 27 neurodevelopmental-disorder-associated genes, thus demonstrating that CBLH and DWM are often features of monogenic neurodevelopmental disorders. Though only seven monogenic causes (19%) were identified in more than one individual, neuroimaging review of 131 additional individuals confirmed cerebellar abnormalities in 23 of 27 genetic disorders (85%). Prenatal risk factors were frequently found among individuals without a genetic diagnosis (30 of 64 individuals [47%]). Single-cell RNA sequencing of prenatal human cerebellar tissue revealed gene enrichment in neuronal and vascular cell types; this suggests that defective vasculogenesis may disrupt cerebellar development. Further, de novo gain-of-function variants in PDGFRB, a tyrosine kinase receptor essential for vascular progenitor signaling, were associated with CBLH, and this discovery links genetic and non-genetic etiologies. Our results suggest that genetic defects impact specific cerebellar cell types and implicate abnormal vascular development as a mechanism for cerebellar malformations. We also confirmed a major contribution for non-genetic prenatal factors in individuals with cerebellar abnormalities, substantially influencing diagnostic evaluation and counseling regarding recurrence risk and prognosis.

Keywords: autism, cerebellar hypoplasia, cerebellum, Dandy-Walker malformation, epilepsy, exome, genes, heterotopia, intellectual disability, twins

Introduction

Cerebellar malformations, including Dandy-Walker malformation (DWM) and several cerebellar hypoplasia (CBLH) subtypes, are among the most common malformations recognized in utero, though their prevalence is unknown.1 They have proven difficult to study due to inconsistent classification, largely unknown pathogenesis, and diverse developmental outcomes that may include childhood epilepsy, intellectual disability (ID), cerebral palsy, autism, and other neuropsychiatric disorders.2, 3

Pathogenic variants in only a few genes have been implicated in CBLH or DWM. After excluding rare, autosomal recessive disorders such as α-dystroglycanopathies and ciliopathies, the list includes variants of CASK (MIM: 300172), OPHN1 (MIM: 300127), ZIC1-ZIC4 (MIM: 220200), and FOXC1 (MIM: 601090).4 Cerebellar abnormalities have also been linked to non-genetic mechanisms, especially prematurity, twinning, and prenatal cerebellar hemorrhage.5, 6, 7 To fundamentally advance our understanding of these disorders, we analyzed neuroimaging and other phenotypic data, and we performed exome sequencing in 100 families with CBLH or DWM. We further performed single-cell RNA sequencing of human fetal cerebellar tissue to evaluate whether cerebellar malformation genes map onto specific cell types.

Material and Methods

Discovery Cohort

From our cohort of >4,200 individuals with developmental brain disorders, we used specific inclusion and exclusion criteria for CBLH and DWM (Table S1) to select 100 individuals with cerebellar imaging abnormalities. We included individuals with available DNA and clinical data, including neuroimaging studies, and we excluded individuals with prior genetic diagnoses or recognizable disorders such as ciliopathies. Written informed consent was obtained under protocols approved by institutional review boards at the University of Chicago, Seattle Children’s Hospital, and the University of Washington.

Exome Sequencing and Variant Analysis

We performed exome sequencing on genomic DNA from 105 affected individuals and 177 parents (Table S2). Variants were filtered for >10× coverage, <0.001 minor allele frequency in public databases, and CADD score >10,8 as well as for de novo, autosomal recessive, or X-linked inheritance. Filtered variants were visually inspected using IGV,9 and frameshift mutations were validated by Sanger sequencing. The criteria used to determine pathogenicity are described in Supplemental Methods (see Supplemental Data).

Confirmation Cohort

The cerebellar malformation confirmation cohort included 131 individuals who were identified through our developmental brain disorders cohort, colleagues, or GeneMatcher10 and who had previously received a genetic diagnosis for one of the monogenic disorders detected in the discovery cohort. We obtained original neuroimaging studies for all 131 individuals.

Single-Cell RNA Sequencing and Analysis of Human Cerebellar Tissue

We obtained cerebellar tissue from the Birth Defects Research Laboratory at the University of Washington and from the Human Developmental Biology Resource11 with ethics board approval and maternal written consent. Specimens were dissociated to obtain whole cells (n = 4) or flash frozen in liquid nitrogen and stored at -80°C until use (n = 1). Whole-cell dissociation and fixation were performed as described.12 Nuclei were isolated using a published protocol modified by fixation conditions specified in the SPLiT-seq protocol.13, 14 We used SPLiT-Seq for single-cell or single-nucleus RNA sequencing14 as described in the Supplemental Methods (see Supplemental Data).

Statistical Analyses

For clinical data, pairwise comparisons were performed using Fisher’s exact test (with any number of cells less than five) or two-tailed Chi-square test. Detailed analyses of gene expression and single-cell datasets are described in the Supplemental Methods (see Supplemental Data).

Results

Of the 100 probands, 88 had European ancestry, 60 were male, and 67% were younger than seven years of age; 94 had cognitive function data available (Figure S1 and Tables S3 and S4). All probands had neuroimaging features of CBLH (57 individuals) or DWM (43 individuals). Examples of the variability among cerebellar malformations are shown in Figures 1, S2, and S3. The rate of ID was significantly higher in CBLH (48 of 57 [84%]) than in DWM (20 of 37 [54%]; χ2 = 10.2, df = 1, p = 0.001).

Figure 1.

Figure 1

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Neuroimaging of Cerebellar Malformations

Four cerebellar malformation patterns are shown with midline sagittal (left column), axial (middle column), and axial or coronal (right column) images using T2-weighted (A–C, H–I, N–O), T1-weighted (D, G), or volumetric (E–F, J–L) sequences. The white horizontal bars in the left column mark the obex, which approximates the normal lower limit of the vermis. The top and bottom rows demonstrate features of DWM in individuals LR05-354 at 1 day (A–C) and LR05-265 at 5 years (J–L). Midline sagittal images (A, J) demonstrate small to very small and upwardly rotated vermis (v), widely open fourth ventricle communicating with large posterior fossa fluid spaces (∗∗) or cystic dilatation of the fourth ventricle (4V), and elevated tentorium. The newborn in the top row (A–C) has an easily detected unpaired caudal lobule or Dandy-Walker tail (black arrow), a single periventricular nodular heterotopia (white arrow), and small cerebellar hemispheres (h). The child in the second row has cerebellar vermis hypoplasia (v), mega-cisterna magna (∗∗), and a mildly small right cerebellar hemisphere (h), which is associated with a FOXP1 mutation (from confirmation cohort). The bottom two rows show features associated with prenatal risk factors in individuals LR05-398 at 1 year (G–I; discordant monozygotic twin) and LR05-265 at 5 years (J–L). Midline sagittal image from the affected twin (G) shows a small cerebellar vermis (v) and posterior fossa, while the second individual (J) has classic DWM with small upwardly rotated vermis (v), Dandy-Walker tail (white arrow in d), cystic enlargement of the fourth ventricle (∗∗), and elevated tentorium. In the third row, the axial image (H) shows bilateral cerebellar clefts (white arrows), while the coronal image (I) shows asymmetric cerebellar hemisphere hypoplasia more severe on the right (H). In the bottom row, the axial image (K) shows posterior predominant periventricular nodular heterotopia larger on the left (black arrows; the right side of axial images shows the left side of the brain). The coronal image (F) shows small asymmetric cerebellar hemispheres, smaller on the left (H), and a large cleft removing most of the left middle cerebellar peduncle (F, white arrow).

Cerebellar Malformation Gene Discovery

We identified 41 pathogenic or likely pathogenic (diagnostic) variants in 36 families; these variants included 27 de novo (66%; 19 autosomal, five X-linked heterozygous, and three X-linked hemizygous), three inherited X-linked hemizygous (7%), one autosomal homozygous (2%), and 10 autosomal compound heterozygous (24%) variants involving 27 genes (Figure 2A and Table S5). The 41 diagnostic variants included 30 missense, two in-frame deletion, seven protein truncating, and two splice-acceptor mutation variants; 14 variants (34%) were previously reported as pathogenic.

Figure 2.

Figure 2

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Summary of Genetic and Prenatal Risk Factor Analyses in Cerebellar Malformations

(A) The left panel shows the counts of individuals with genetic diagnosis per gene in the discovery cohort. Counts for DWM are represented below zero in orange and counts for CBLH are above zero in blue. Novel gene is indicated with an asterisk. The right panel shows the counts for individuals with cerebellar malformations in the discovery cohort, confirmation cohort, and literature combined per gene. The counts for three genes (TUBA1A, CASK, OPHN1) extend beyond the chart.

(B) Clinical diagnoses and genetic diagnostic yield. The left panel shows the frequency of genetic diagnosis per cerebellar malformation diagnosis. The right panel shows the frequency of genetic diagnosis per cognitive function. The rate of ID is higher in CBLH than in DWM. The rate of genetic diagnosis was highest in CBLH and ID. Plus or minus sign indicates presence or absence, respectively.

(C) Rates of prenatal risk factors, genetic diagnosis, and cerebellar malformation group. The relative proportions of individuals with prenatal risk factors, genetic diagnosis, and cerebellar malformation diagnosis. Plus or minus sign indicate presence or absence, respectively. Only 3% of individuals with genetic diagnoses also had prenatal risk factors, while 30% of individuals without genetic diagnoses had prenatal risk factors for any cerebellar malformation. The genetic diagnostic yield was highest among individuals with CBLH who lacked prenatal risk factors. The genetic diagnostic yield was lowest among individuals with DWM who also lacked prenatal risk factors. Abbreviations: CBLH, cerebellar hypoplasia; DWM, Dandy-Walker malformation; GDX, genetic diagnosis; ID, intellectual disability; PRF, prenatal risk factors.

Among the 27 distinct monogenic disorders detected, seven genes accounted for 16 (44.4%) of the 36 genetic diagnoses: BCL11A (MIM: 606557), FOXP1 (MIM: 605515), SETD2 (MIM: 612778), STXBP1 (MIM: 602926), TUBA1A (MIM: 602529), CASK, and DDX3X (MIM: 300160). However, the majority of genetic disorders identified (20 of 27 [74%]) were unique to a single family in the discovery cohort. Diagnostic variants in SETD2 and TUBA1A were each detected in two individuals, one with CBLH and another with DWM. We found diagnostic variants in three genes associated with disorders excluded by our selection criteria, two with Joubert syndrome (ARMC9 [MIM: 617612], PIBF1 [MIM: 607532]) and one with pontocerebellar hypoplasia (RARS2 [MIM: 611524]); the neuroimaging features were atypical and only recognized on re-review. Five genes were initially characterized as novel but were reported during the course of our study (ARMC9, MACF1 [MIM: 608271], PPP1CB [MIM: 600590], TUBB2A [MIM: 615101], WDR37) and one had not previously been associated with disease in humans (FZD3). We also identified heterozygous de novo variants of uncertain significance in three candidate genes (BACH1, BAG6, DPYSL5), and two genes previously associated with different phenotypes (MACF1, SEMA6B) as summarized in the Supplemental Note (see Supplemental Data).

The diagnostic yield was highest among individuals with CBLH (29 of 57 [51%]) and with ID (33 of 68 [49%]; Figure 2B and Table S6). Only seven out of 43 individuals with DWM (16%) received a genetic diagnosis, which was significantly lower than for CBLH (χ2 = 12.73, df = 1, P = 0.0004). Among the 43 individuals with DWM, 36 had neuroimaging with sufficient resolution to assess for the presence of an unpaired caudal lobule or “DW-tail” of the cerebellar vermis.15 The rate of genetic diagnosis was lowest among individuals with the DW-tail (4 of 30 [13%]) and higher in those without the DW-tail (3 of 6 [50%]).

Cerebellar Malformations Co-Occur with Distinct Monogenic Disorders

Most of the genes identified in our discovery cohort (21 of 27 [78%]; Figure 2A) were previously associated with known neurodevelopmental disorders; these included 11 genes associated with non-syndromic early childhood epilepsy, ID, or autism. We reviewed original neuroimaging studies from another 122 individuals with monogenic disorders involving the 21 known neurodevelopmental disorder-associated genes, and we verified CBLH or DWM in 99 of 122 (81%; Tables S7, S8, S9, and S10). We found reports supporting cerebellar malformations for 13 genes; these included reports for four genes that were not in our confirmation cohort (AHDC1 [MIM: 615790], FGFR1 [MIM: 136350], TUBB2A, DKC1 [MIM: 200126]). These results confirm a cerebellar phenotype for 23 of 27 (85%) genes (Tables S7 and S11). Notably, DWM was an inconsistent feature of any genetic disorder.

Differences in Brain Gene Expression

The disparate rates of ID and genetic diagnosis in CBLH versus DWM (Figure 2B) led us to examine whether genes found in each neuroimaging group were differentially expressed in prenatal brains. We used the BrainSpan Atlas of the Developing Human Brain to examine expression of the genes found in our discovery cohort between 8 and 37 postconceptual weeks (pcw; Figure S5).16 All 27 genes were expressed in the cerebellum and neocortex, and we found significant correlation between the two regions (Spearman’s ρ = 0.976, p = 1.26 × 10-7). Neuroimaging group was a significant predictor of brain gene expression with lower brain expression for genes with diagnostic variants in individuals with DWM compared those with CBLH [F(2, 3882) = 5.443, p = 0.028].

CBLH and DWM Genes Have Cell-Type Specificity

To examine how differences in gene expression between neuroimaging groups extended to cerebellar cell types, we used SPLiT-seq to generate single-cell RNA sequencing data from five fetal cerebellar samples (12–21 pcw), and we obtained 4,306 single-cell transcriptomes (Figure 3A and Table S12). We used unsupervised clustering to define distinct cell clusters and applied known gene expression patterns to define 13 identities encompassing multiple neuronal, glial, and vascular cell types (Figure 3B, Figure S6, and Table S13). We examined expression for the 27 discovery cohort genes among developmental cerebellar cell types and found enrichment in Purkinje cells (nine of 27 [33%]; Figure 3C and Table S14). We then grouped the 13 cerebellar cell clusters into broad categories (neurons, glia, and vascular cell types), and we found that genes mutated in individuals with cerebellar malformations were specifically enriched in neurons and vascular cells (Figure 3D–E and Table S15).

Figure 3.

Figure 3

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Cell Types in the Prenatal Cerebellum and Enrichment of Cerebellar Malformation Genes

(A) Workflow for single-cell transcriptome profiling of prenatal cerebellum cells or nuclei.

(B) Cell clusters from SPLiT-seq analysis visualized by t-stochastic neighbor embedding (tSNE). Colors indicate cell type.

(C) Heatmap of differential gene expression per cell type for each of the 27 genes identified in the discovery cohort. Genes with significant differential expression (FDR < 0.05) per cluster are indicated (∗).

(D) The same tSNE scatter plot as in (B) but cells are colored according to three broad cell classes.

(E) Heatmap of differential gene expression per broad cell class for each of the 27 genes identified in the discovery cohort. Genes with significant differential expression (FDR < 0.05) per cluster are indicated (∗).

Cerebellar Abnormalities Are Associated with Prenatal Factors

Our data left 64% of individuals without genetic diagnoses. We therefore reviewed prenatal clinical history and neuroimaging studies (Table S16) to identify individuals with high risk factors for prenatal brain injury. We found four extremely low gestational age newborns (ELGAN, defined as 22–27 weeks gestation) and 12 discordant twins (one ELGAN). The four individuals with ELGAN all had CBLH. The twins included six who were discordant for DWM (four of six were monozygotic), five who were discordant for CBLH (four of five were dizygotic), and one with intrauterine demise of her co-twin. The overall rate of molecular diagnosis was lower in individuals with clinical prenatal risk factors (two of 15 [13%]) versus without (21 of 52 [40%]; Figure 2C and Table S17).

We also re-examined neuroimaging studies for features associated with prenatal brain injury including (1) unilateral or highly asymmetric CBLH and (2) cerebellar clefts.17, 18, 19 We also considered (3) posterior-predominant periventricular nodular heterotopia (PNH, Figure 1B, 1K) and curvilinear subcortical heterotopia based on low yield in exome studies and occurrence in discordant monozygotic twins including one twin (LR12-313a2) in this study.20, 21, 22, 23 We identified 24 individuals with neuroimaging evidence supporting prenatal brain injury; these individuals included 20 with prominent cerebellar asymmetry, seven with cerebellar clefts, and 15 with cerebral heterotopia. The rate of molecular diagnosis was significantly lower among individuals with disruptive neuroimaging patterns (one of 24 [4%]) versus individuals without (35 of 76 [46%]; Figure 2C and Table S17).

We next combined clinical and neuroimaging prenatal risk factors and found that 24 of 33 (73%) had two or more risk factors. Overall, prenatal risk factors had similar rates in CBLH (21 of 57 [37%]) and DWM (12 of 43 [28%]; Figure 2C). And as expected, the rate of molecular diagnosis was significantly lower in individuals with any prenatal risk factor (3 of 33 [9%]) versus those without (33 of 67 [49%];Figure 2C and Table S17).

Discussion

The scientific literature contains reports of cerebellar malformations dating from the 1800s, and DWM was clearly defined by 1942.24, 25, 26 Many distinct cerebellar malformations have since been described.4 In this study, we report (1) a high rate (36%) of molecular diagnosis in individuals with cerebellar malformations that genetically overlap with neurodevelopmental disorders, (2) significantly lower rates of ID and molecular diagnosis in DWM versus CBLH, (3) a high rate of prenatal risk and neuroimaging features associated with injury that implicate frequent non-genetic causes of cerebellar malformations including DWM, and (4) evidence suggesting that genetic defects of vasculogenesis may underlie some cerebellar malformations, providing an important biological link between genetic and non-genetic causes.

Genetic Basis for Cerebellar Malformations

The molecular diagnostic rate in our discovery cohort (36%) is similar to those for childhood epilepsy (25%), ID (28%), and autism (28%).27, 28, 29 However, after removing the 33 individuals with any prenatal risk factor, the diagnostic yield in our cohort rises to 33 of 67 (49%). If we then partition our cohort by cerebellar malformation, the diagnostic yield is 72% (26 of 36) in CBLH and 23% (7 of 31) in DWM. These data support a “genotype-first” testing approach for affected individuals without these defined prenatal risk factors.

Cerebellar Malformation in Neurodevelopmental Disorders

Though cerebellar malformations have historically been used as primary diagnoses, we show that CBLH often occurs and DWM sometimes occurs as a co-morbidity of monogenic neurodevelopmental disorders with variable expressivity. These include at least 11 genes associated with childhood epilepsy, ID, or autism without syndromic features: AHDC1, AUTS2 (MIM: 607270), BCL11A, DDX3X, FOXP1, KIF4A (MIM: 300521), PUS3 (MIM: 616283), SETD2, SPTAN1 (MIM: 182810), STXBP1, and TMLHE (MIM: 300777). We also identified several individuals with diagnostic variants in these genes with expanded phenotypes which included other congenital anomalies, for example, individuals with AUTS2, KIF4A, and SETD2. Our results might also explain the small reductions in regional cerebellar volume reported in autism, schizophrenia, and bipolar disorder, as well as anecdotal reports of CBLH associated with these disorders (Table S18). Finally, our data combined with prior reports identified only four genes associated with non-syndromic (and inconsistently syndromic) ID that have a high penetrance of CBLH—BCL11A, CASK, FOXP1, and OPHN1 (Tables S7 and S8).

DWM Differs from CBLH

DWM has long been viewed as a distinct malformation, although neuroimaging studies in large cohorts have suggested that it may represent one end of a wide CBLH–DWM spectrum,30, 31 and several genes have been associated both with CBLH subtypes and with DWM, including FOXP1, SETD2, PUS3 (all mentioned previously in this article), ZIC1-ZIC4, and FOXC1.32, 33 However, we report a higher frequency of typical cognitive function and a lower rate of molecular diagnosis in DWM compared to CBLH; this supports important clinical distinctions between them. Further, the unpaired caudal lobule or Dandy-Walker “tail” was recently proposed as an important diagnostic sign.15 Our data support this observation, showing that the molecular diagnostic rate is even lower in DWM with the tail compared to DWM without the tail, although the numbers are small. If future studies confirm this difference, the tail should become an additional criterion for classic DWM. We also show that DWM-associated genes have lower expression in the prenatal brain, which provides additional support for DWM being mechanistically distinct from CBLH despite the overlap in underlying genes and prenatal risk factors.

Prenatal Risk Factors Contribute to Both CBLH and DWM

Prior studies have shown that the risk for cerebellar lesions with prematurity is greater at earlier gestational ages and rises to 16% in ELGAN.7, 34, 35, 36 Observations of cerebellar malformations detected by prenatal ultrasound in twins have been attributed to twin-twin transfusion syndrome (TTTS) in monozygotic twins.5, 37 Several reports have suggested that prenatal cerebellar disruptions such as hemorrhage can cause cerebellar asymmetry and clefts,17, 18, 19 and a few reports have documented evidence of prenatal cerebellar hemorrhage preceding a postnatal DWM diagnosis.38, 39, 40

Our data strongly support these prior studies by showing that prenatal risk factors contribute to CBLH generally, providing a systematic analysis demonstrating a non-genetic basis for three co-occurring brain abnormalities (asymmetric CBLH, cerebellar clefts, and cerebral heterotopia—especially posterior predominant PNH), and providing further evidence that the same prenatal risk factors contribute to DWM. However, our cohort includes DWM and CBLH in both monozygotic and dizygotic twins, which suggests that factors other than TTTS may be involved. In one of the original reports of DWM in 1954, Benda et al. reported an infant with DWM whose co-twin died at 22–25 weeks gestation.26

CBLH-DWM and Vasculogenesis

We a priori expected genes identified in our discovery cohort to be highly expressed in prenatal human cerebellar tissue. However, several genes expressed at low levels in bulk cerebellar tissue had enriched expression in developing neuronal and vascular cell types (Figures 3C and 3E). This led us to hypothesize that disruption of genes functioning in vasculogenesis might lead to the same final common pathway as prenatal risk factors by predisposing the individual to prenatal cerebellar hemorrhage or altered vascular perfusion.

The best example involves PDGFRB (MIM: 173410), a gene which is expressed primarily in vascular pericytes and radial glia and which has previously been associated with a spectrum of developmental disorders reported as infantile myofibromatosis and as Penttinen and Kosaki overgrowth syndromes.41, 42, 43, 44 We identified a pathogenic variant in PDGFRB in a girl who had infantile myofibromatosis as well as severe CBLH and mega-cisterna magna. Although we initially found no reports of CBLH for this disorder, reports of Penttinen syndrome described posterior fossa cysts.42, 44, 45 We obtained original neuroimaging studies for two individuals with Penttinen syndrome, and we found CBLH in addition to posterior fossa cysts (Figure 4A-D and Figure S3). Then a recent report described Kosaki syndrome and DWM in an individual with the same gain-of-function PDGFRB mutation found in our proband.44 Our single-cell transcriptomic analysis showed that PDGFRB expression is highly enriched in pericytes within the prenatal cerebellum. PDGFRB in situ hybridization in human cerebellar tissue confirmed pericyte expression throughout development and also transient expression in the residual ventricular zone that gives rise to Purkinje cells (Figure 4E-G).

Figure 4.

Figure 4

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PDGFRB Neuroimaging Phenotype and Prenatal Expression in Human Cerebellum

(A–B) Midline sagittal MRI in two individuals with PDGFRB (GenBank: NM_002609.3) variant c.1696T>C (p.Trp566Arg) show large head with prominent occiput, thin and stretched corpus callosum either diffusely (white arrow in [A]) or posteriorly (black arrow in [B]), massively enlarged cisterna magna (∗∗), and severe cerebellar vermis hypoplasia.

(C–D) Midline sagittal MRI in two individuals with PDGFRB (GenBank: NM_002609.3) c.1994T>C (p.Val665Ala) variant show normal head contour and corpus callosum, mildly enlarged cisterna magna (∗) and mild cerebellar vermis hypoplasia. The horizontal white or black lines to the right of the lower brainstem mark the typical inferior limit of the vermis.

The images shown are for LR05-118 in the discovery cohort (A), an individual reported by Zarate et al.44 (B), and patients 1 (C) and 3 (D) reported by Johnston et al.42

(E–G) PDGFRB expression as detected by in situ hybridization in the human cerebellum at Carnegie stage 20 (E), 14 pcw (F), and 18 pcw (G) localizes to pericytes and mesenchyme. At 14 pcw, PDGFRB expression is also detected in the residual ventricular zone ([F], arrows in inset), the stem cell niche that gives rise to Purkinje cells.

Several other genes with diagnostic variants in our discovery cohort were also highly expressed in vascular cell types; these genes included BRAF (MIM: 164757), DDX3X, FGFR1, FOXP1, PPP1CB, and SETD2. Adding FOXC1, HRAS (MIM: 190020), PTPN11 (MIM: 176876), and WNT1 (MIM: 164820) from prior reports establishes 10 cerebellar malformation genes with high expression during vasculogenesis, including two Forkhead box transcription factors and four RAS pathway genes.33, 46, 47, 48 These data support our hypothesis that disruption of vascular-expressed genes alters cerebellar development via secondary prenatal perfusion defects or hemorrhage, and predict that DWM and a subset of CBLH will be variable features of associated genetic syndromes.

Summary

We report that cerebellar malformations most often represent either a variable feature of diverse neurodevelopmental disorders or the sequela of prenatal risk factors that predispose the fetal brain to cerebellar hemorrhage or vascular injury. Beyond providing insight into the biological mechanisms leading to CBLH and DWM, we expect our results to change clinical care in several ways. First, CBLH and DWM should only rarely serve as primary diagnoses: when either is detected, the diagnostic journey is not over. Second, CBLH in the absence of clinical or neuroimaging evidence of prenatal injury is associated with a high yield for genetic testing, supporting a “genotype first” approach. Finally, our results stress the need for careful phenotypic assessment (prenatal history and postnatal neuroimaging) to predict the yield from genetic testing and most likely developmental outcome, thereby improving pre- and postnatal counseling.

Declaration of Interests

G.S., A.B.R., and C.R. have filed a patent related to the SPLiT-seq method. All other authors declare no competing interests.

Acknowledgements

We thank the children as well as their families and referring physicians for their important contributions to our ongoing work on cerebellar disorders. This study was funded by the National Institutes of Health under National Institute of Neurological Disorders and Stroke (NINDS) or National Institute of Child Health and Human Development (NICHD) grant numbers 5R01NS050375 to W.B.D, R01NS095733 to K.J.M., K08NS092898 to G.M.M., and R24HD000836 to I.A.G. The University of Washington Center for Mendelian Genomics provided sequencing and data analysis, supported by National Human Genome Research Institute (NHGRI) grant number U54HG006493 to D.A.N. and M.J.B., and the University of Washington Intellectual and Developmental Disabilities Research Center (IDDRC) Genetics Core, supported by NICHD grant number U54HG006493, provided support to D.D. Additional funding was provided by The Dandy-Walker Alliance and The Philly Baer Foundation. L.G.B. was supported by grant number HG200328 from the Intramural Research Program of the NHGRI. Human fetal material was provided, in part, by the Joint Medical Research Council and Wellcome (MR/R006237/1) Human Developmental Biology Resource. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding sources. Please note that the authors cite OMIM according to journal editorial policy but do not endorse the referenced OMIM data.

Published: August 29, 2019

Footnotes

Supplemental Data can be found online at https://doi.org/10.1016/j.ajhg.2019.07.019.

Accession Numbers

The accession numbers for the disease-associated variants described in this report are ClinVar: SCV000916307.1–SCV000916347.1.

Web Resources

Supplemental Data

Document S1. Supplemental Note; Figures S1–S6; Tables S1, S3, S5–S7, S9–S12, S14, S15, S17, and S18; Suplemental Methods; and Supplemental References
mmc1.pdf (3.6MB, pdf)
Document S2. Tables S2, S4, S8, S13, and S16
mmc2.xlsx (60.2KB, xlsx)
Document S3. Article plus Supplemental Data
mmc3.pdf (5.6MB, pdf)

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Supplementary Materials

Document S1. Supplemental Note; Figures S1–S6; Tables S1, S3, S5–S7, S9–S12, S14, S15, S17, and S18; Suplemental Methods; and Supplemental References
mmc1.pdf (3.6MB, pdf)
Document S2. Tables S2, S4, S8, S13, and S16
mmc2.xlsx (60.2KB, xlsx)
Document S3. Article plus Supplemental Data
mmc3.pdf (5.6MB, pdf)

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