Group penalized generalized estimating equation for correlated event-related potentials and biomarker selection

Ye Lin, Jianhui Zhou, Swapna Kumar, Wanze Xie, Sarah K G Jensen, Rashidul Haque, Charles A Nelson, William A Petri Jr, Jennie Z Ma, Ye Lin, Jianhui Zhou, Swapna Kumar, Wanze Xie, Sarah K G Jensen, Rashidul Haque, Charles A Nelson, William A Petri Jr, Jennie Z Ma

Abstract

Background: Event-related potentials (ERP) data are widely used in brain studies that measure brain responses to specific stimuli using electroencephalogram (EEG) with multiple electrodes. Previous ERP data analyses haven't accounted for the structured correlation among observations in ERP data from multiple electrodes, and therefore ignored the electrode-specific information and variation among the electrodes on the scalp. Our objective was to evaluate the impact of early adversity on brain connectivity by identifying risk factors and early-stage biomarkers associated with the ERP responses while properly accounting for structured correlation.

Methods: In this study, we extend a penalized generalized estimating equation (PGEE) method to accommodate structured correlation of ERPs that accounts for electrode-specific data and to enable group selection, such that grouped covariates can be evaluated together for their association with brain development in a birth cohort of urban-dwelling Bangladeshi children. The primary ERP responses of interest in our study are N290 amplitude and the difference in N290 amplitude.

Results: The selected early-stage biomarkers associated with the N290 responses are representatives of enteric inflammation (days of diarrhea, MIP1b, retinol binding protein (RBP), Zinc, myeloperoxidase (MPO), calprotectin, and neopterin), systemic inflammation (IL-5, IL-10, ferritin, C Reactive Protein (CRP)), socioeconomic status (household expenditure), maternal health (mother height) and sanitation (water treatment).

Conclusions: Our proposed group penalized GEE estimator with structured correlation matrix can properly model the complex ERP data and simultaneously identify informative biomarkers associated with such brain connectivity. The selected early-stage biomarkers offer a potential explanation for the adversity of neurocognitive development in low-income countries and facilitate early identification of infants at risk, as well as potential pathways for intervention.

Trial registration: The related clinical study was retrospectively registered with https://doi.org/ClinicalTrials.gov , identifier NCT01375647, on June 3, 2011.

Keywords: Correlated data; Event-related potentials; Penalized generalized estimating equations (GEE); Structured correlation matrix; Variable selection.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Boxplot of N290 amplitude under oddball/standard condition. X-axis represents 13 electrodes on the occipital regions of interest (see the supplemental figure for exact electrode locations). Y-axis shows the amplitude in uV
Fig. 2
Fig. 2
Correlation plot of N290 amplitude under oddball/standard condition

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