Initial Identification of a Blood-Based Chromosome Conformation Signature for Aiding in the Diagnosis of Amyotrophic Lateral Sclerosis.
Salter M., Corfield E., Ramadass A., Grand F., Green J., Westra J., Lim CR., Farrimond L., Feneberg E., Scaber J., Thompson A., Ossher L., Turner M., Talbot K., Cudkowicz M., Berry J., Hunter E., Akoulitchev A.
BACKGROUND: The identification of blood-based biomarkers specific to the diagnosis of amyotrophic lateral sclerosis (ALS) is an active field of academic and clinical research. While inheritance studies have advanced the field, a majority of patients do not have a known genetic link to the disease, making direct sequence-based genetic testing for ALS difficult. The ability to detect biofluid-based epigenetic changes in ALS would expand the relevance of using genomic information for disease diagnosis. METHODS: Assessing differences in chromosomal conformations (i.e. how they are positioned in 3-dimensions) represents one approach for assessing epigenetic changes. In this study, we used an industrial platform, EpiSwitch™, to compare the genomic architecture of healthy and diseased patient samples (blood and tissue) to discover a chromosomal conformation signature (CCS) with diagnostic potential in ALS. A three-step biomarker selection process yielded a distinct CCS for ALS, comprised of conformation changes in eight genomic loci and detectable in blood. FINDINGS: We applied the ALS CCS to determine a diagnosis for 74 unblinded patient samples and subsequently conducted a blinded diagnostic study of 16 samples. Sensitivity and specificity for ALS detection in the 74 unblinded patient samples were 83∙33% (CI 51∙59 to 97∙91%) and 76∙92% (46∙19 to 94∙96%), respectively. In the blinded cohort, sensitivity reached 87∙50% (CI 47∙35 to 99∙68%) and specificity was 75∙0% (34∙91 to 96∙81%). INTERPRETATIONS: The sensitivity and specificity values achieved using the ALS CCS identified and validated in this study provide an indication that the detection of chromosome conformation signatures is a promising approach to disease diagnosis and can potentially augment current strategies for diagnosing ALS. FUND: This research was funded by Oxford BioDynamics and Innovate UK. Work in the Oxford MND Care and Research Centre is supported by grants from the Motor Neurone Disease Association and the Medical Research Council. Additional support was provided by the Northeast ALS Consortium (NEALS).