Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Douglas Bigwood.
Gene | 2015
William Rounds; Edward Salinas; Tom B. Wilks; Mikhail K. Levin; Ann J. Ligocki; Carolina Ionete; Carlos A. Pardo; Steven Vernino; Benjamin Greenberg; Douglas Bigwood; Eric M. Eastman; Lindsay G. Cowell; Nancy L. Monson
BACKGROUND We have previously demonstrated that cerebrospinal fluid-derived B cells from early relapsing-remitting multiple sclerosis (RRMS) patients that express a VH4 gene accumulate specific replacement mutations. These mutations can be quantified as a score that identifies such patients as having or likely to convert to RRMS. Furthermore, we showed that next generation sequencing is an efficient method for obtaining the sequencing information required by this mutation scoring tool, originally developed using the less clinically viable single-cell Sanger sequencing. OBJECTIVE To determine the accuracy of MSPrecise, the diagnostic test that identifies the presence of the RRMS-enriched mutation pattern from patient cerebrospinal fluid B cells. METHODS Cerebrospinal fluid cell pellets were obtained from RRMS and other neurological disease (OND) patient cohorts. VH4 gene segments were amplified, sequenced by next generation sequencing and analyzed for mutation score. RESULTS The diagnostic test showed a sensitivity of 75% on the RRMS cohort and a specificity of 88% on the OND cohort. The accuracy of the test in identifying RRMS patients or patients that will develop RRMS is 84%. CONCLUSION MSPrecise exhibits good performance in identifying patients with RRMS irrespective of time with RRMS.
Frontiers in Neurology | 2014
William Rounds; Ann J. Ligocki; Mikhail K. Levin; Benjamin Greenberg; Douglas Bigwood; Eric M. Eastman; Lindsay G. Cowell; Nancy L. Monson
We previously identified a distinct mutation pattern in the antibody genes of B cells isolated from cerebrospinal fluid (CSF) that can identify patients who have relapsing-remitting multiple sclerosis (RRMS) and patients with clinically isolated syndromes who will convert to RRMS. This antibody gene signature (AGS) was developed using Sanger sequencing of single B cells. While potentially helpful to patients, Sanger sequencing is not an assay that can be practically deployed in clinical settings. In order to provide AGS evaluations to patients as part of their diagnostic workup, we developed protocols to generate AGS scores using next-generation DNA sequencing (NGS) on CSF-derived cell pellets without the need to isolate single cells. This approach has the potential to increase the coverage of the B-cell population being analyzed, reduce the time needed to generate AGS scores, and may improve the overall performance of the AGS approach as a diagnostic test in the future. However, no investigations have focused on whether NGS-based repertoires will properly reflect antibody gene frequencies and somatic hypermutation patterns defined by Sanger sequencing. To address this issue, we isolated paired CSF samples from eight patients who either had MS or were at risk to develop MS. Here, we present data that antibody gene frequencies and somatic hypermutation patterns are similar in Sanger and NGS-based antibody repertoires from these paired CSF samples. In addition, AGS scores derived from the NGS database correctly identified the patients who initially had or subsequently converted to RRMS, with precision similar to that of the Sanger sequencing approach. Further investigation of the utility of the AGS in predicting conversion to MS using NGS-derived antibody repertoires in a larger cohort of patients is warranted.
Archive | 2008
Douglas Bigwood; Eric M. Eastman; Eric Kaldjian
Archive | 2013
Eric M. Eastman; Douglas Bigwood
Archive | 2011
Douglas Bigwood; Eric M. Eastman; Michael Elashoff
Archive | 2012
Douglas Bigwood; Eric M. Eastman
Journal of Immunology | 2014
William Rounds; Ann J. Ligocki; Mikhail K. Levin; Benjamin Greenberg; Douglas Bigwood; Eric M. Eastman; Lindsay G. Cowell; Nancy L. Monson
Neurology | 2014
Nancy L. Monson; Eric M. Eastman; Douglas Bigwood; Mikhail K. Levin; William Rounds; Lindsay G. Cowell; Benjamin Greenberg
Neurology | 2014
Benjamin Greenberg; Nancy L. Monson; Douglas Bigwood; Eric M. Eastman
Neurology | 2013
Nancy L. Monson; Ann J. Ligocki; William Rounds; Douglas Bigwood; Eric M. Eastman; Lindsay G. Cowell; Elliot M. Frohman; Benjamin Greenberg