Intra-Individual Variability Measurements as an Earlier Diagnostic for Patients with Multiple Sclerosis | NYU Langone Health

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Parekh Center for Interdisciplinary Neurology Main Research Projects Intra-Individual Variability Measurements as an Earlier Diagnostic for Patients with Multiple Sclerosis

Intra-Individual Variability Measurements as an Earlier Diagnostic for Patients with Multiple Sclerosis

We currently identify a patient’s advancing neurological decline when it reaches a clinically detectable threshold. There remains an unmet need to identify patients before the onset of decline and disability. Our scientific premise is that the initial neuronal dysfunction that defines prodromal neurodegeneration can be reliably identified by subtle inconsistencies in cognitive processes. We therefore propose using a clinically applicable approach to evaluate cognitive consistency as an indicator of prodromal neurological disability.

Cognitive consistency can be easily measured using simple computer-based psychomotor tasks, capturing intra-individual variability (IIV) across an individual’s repeated reaction times (RTs). IIV, compared to the conventional measures of cognitive accuracy or speed, is a highly sensitive marker of future health status at the population level as well as in prodromal neurological disease.

IIV is a highly sensitive indicator of general central nervous system integrity capturing subtle failures in information processing and is uniquely (e.g., versus mean-level speed or accuracy) and highly predictive of future cognitive and physical health status. Applied in the context of neurodegenerative disorders, IIV marks the earliest onset of disease and risk of future onset of neurologic disability across many conditions, including mild cognitive impairment and early dementia, Parkinson’s disease, epilepsy, and schizophrenia.

Specifically for multiple sclerosis (MS), our group and many other investigative teams have confirmed that increased IIV distinguishes those with MS, and without clinically detectable impairment, from healthy controls.

For this project, we propose to develop the measurement of IIV toward its clinical application as prodromal marker across neurological conditions. We are utilizing an innovative and accessible approach to measure IIV in patients that provides an age-normative score to represent cognitive consistency interpreted at the individual level. We are testing IIV at baseline and again every three months across one year for the following:

  • Cross-sectional validation. Comparison of IIV values with biomarkers of interest for convergent validation of risk indication for decline. Hypothesis: Patients with IIV higher than age-expected normative values will have corresponding biomarkers of pending neurological degeneration/inflammation.
  • Longitudinal predictive. Identify patients who have had a defined clinical event within the year following baseline evaluation. Hypothesis: Patients with higher versus lower IIV at baseline will have a higher rate of progression toward a clinical event (defined and measured within and across disease conditions).
  • Longitudinal detection (validation and prediction). Identify patients who have a significant increase in IIV (decreased consistency) from baseline at any three-month evaluation over the year of monitoring. Hypothesis: Increased IIV (defined as >1 SD from baseline) will (a) have a corresponding increase in biomarkers and (b) be at greatest risk for near-term clinical event indicating progression.

We are measuring IIV with the simple and choice RT tasks in the computer-based platform, Cogstate. This brief (about 7 minutes), practical, and widely available IIV measurement is clinically validated and with an extensive (n = 95,162) normative database for comparison. As a key strength to our approach, the normative Cogstate database provides a healthy control reference sample for comparison.

This work will develop a clinical measure of IIV as behavioral measure of prodromal neurodegeneration that can guide early detection and, ultimately, prevention of disability.

Contact Us

For more information about this research, please contact principal investigators Leigh E. Charvet, PhD, at leigh.charvet@nyulangone.org, or Lauren B. Krupp, MD, at lauren.krupp@nyulangone.org.