Open Access Research article

Identification of Chiari Type I Malformation subtypes using whole genome expression profiles and cranial base morphometrics

Christina A Markunas1, Eric Lock1, Karen Soldano12, Heidi Cope12, Chien-Kuang C Ding1, David S Enterline3, Gerald Grant4, Herbert Fuchs5, Allison E Ashley-Koch12 and Simon G Gregory16*

Author Affiliations

1 Duke Center for Human Genetics, Duke University Medical Center, Durham, NC, USA

2 Duke Center for Human Disease Modeling, Duke University Medical Center, Durham, NC, USA

3 Division of Neuroradiology, Department of Radiology, Duke University Medical Center, Durham, NC, USA

4 Department of Neurosurgery, Stanford University/Lucile Packard Children’s Hospital, Stanford, CA, USA

5 Division of Neurosurgery, Department of Surgery, Duke University Medical Center, Durham, NC, USA

6 Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA

For all author emails, please log on.

BMC Medical Genomics 2014, 7:39  doi:10.1186/1755-8794-7-39

Published: 25 June 2014



Chiari Type I Malformation (CMI) is characterized by herniation of the cerebellar tonsils through the foramen magnum at the base of the skull, resulting in significant neurologic morbidity. As CMI patients display a high degree of clinical variability and multiple mechanisms have been proposed for tonsillar herniation, it is hypothesized that this heterogeneous disorder is due to multiple genetic and environmental factors. The purpose of the present study was to gain a better understanding of what factors contribute to this heterogeneity by using an unsupervised statistical approach to define disease subtypes within a case-only pediatric population.


A collection of forty-four pediatric CMI patients were ascertained to identify disease subtypes using whole genome expression profiles generated from patient blood and dura mater tissue samples, and radiological data consisting of posterior fossa (PF) morphometrics. Sparse k-means clustering and an extension to accommodate multiple data sources were used to cluster patients into more homogeneous groups using biological and radiological data both individually and collectively.


All clustering analyses resulted in the significant identification of patient classes, with the pure biological classes derived from patient blood and dura mater samples demonstrating the strongest evidence. Those patient classes were further characterized by identifying enriched biological pathways, as well as correlated cranial base morphological and clinical traits.


Our results implicate several strong biological candidates warranting further investigation from the dura expression analysis and also identified a blood gene expression profile corresponding to a global down-regulation in protein synthesis.

Chiari Type I Malformation; Posterior fossa; Disease subtypes; Whole genome expression; Cranial base morphometrics; Clustering