Early-infant diagnostic predictors of the neuro-behavioral development after neonatal care

Abstract

Multidimensional diagnosis plays a central role in infant developmental care, which leads to the prediction of future disabilities. Information consolidated from objective and subjective, early and late, central and peripheral data may reveal neuro-pathological mechanisms and realize earlier and more precise preventive intervention. In the current study, we retrospectively searched correlating factors to the following neurological and behavioral development of 'Head Control' and 'Roll Over' using multivariate correlation analysis of differ-ent diagnostic domains over age, subject/object information of the patients who were previously admitted in our neonatal intensive care unit (NICU) and could be developmentally followed up in our outpatient clinic. Based on the hematologic and biochemical data, MRI brain anatomy during NICU hospitalization, we characterized all the acquired data distribution from 31 infants with either 'appeared neurologically normal (ANN, n = 21)’ or 'appeared neurologically abnormal (ANA, n = 10)’ pro tempore, with a physician's clinical judgment before discharge. Besides single factor comparisons between ANN and ANA, we examined their development difference by using the multidimensional information processing, principal component analysis (PCA). The diagnostic predictors of neuro-behavioral development were selected by regression analysis with variable selection. It resulted that hematological and brain anatomical factors seemed correlated to both ‘Head Control’ and ‘Roll Over’. This report suggested certain possibility of the cross-domain translational approach between subjective and objective developmental information through multivariate analyses, with candidate markers preliminarily to be evaluated in further studies.

Understanding autism and other neurodevelopmental disorders through experimental translational neurobehavioral models

“…Panel E illustrates social and cognitive behavioral tests used in preclinical NDD models based on domestic chicks (Koshiba et al, 2013a;Koshiba et al, 2013c; and common marmosets Koshiba et al, 2011;Koshiba et al, 2015b;Koshiba et al, 2013b;Senoo et al, 2011;. Paralleling human clinical studies in preterm infants and juveniles (Koshiba et al, 2015a;Koshiba et al, 2013b; , such models can also enhance biomarker discovery. For example, the posterior-lateral forebrain serotonin metabolite, 5-hydroxyindolacetic acid (5HIAA), correlates with chick freezing behavior , whereas emotional phenotypes in common marmosets correlate with venous blood progesterone in female adult common marmosets (Koshiba et al, 2011).…”

“…For instance, multivariate analyses of neurological development across age in normal infants vs. infants with aberrant neural development shows correlation of physiological biomarkers (blood and brain imaging data) with specific behavioral phenotypes, such as head control and rolling behavior (Fig. 2F) (Koshiba et al, 2015a). This raises the possibility of using such phenotypes as potential 'early' behavioral biomarkers of NDDs (Koshiba et al, 2015a), crucial in the absence of other, more complex behaviors to aid diagnostics.…”

“…2F) (Koshiba et al, 2015a). This raises the possibility of using such phenotypes as potential 'early' behavioral biomarkers of NDDs (Koshiba et al, 2015a), crucial in the absence of other, more complex behaviors to aid diagnostics. This is particularly important because early neural development represents a critical window for maximizing the success of therapeutic intervention.…”

Multivariate Analyses Applied to Healthy Neurodevelopment in Fetal, Neonatal, and Pediatric MRI

“…White matter volume was shown to increase at a higher rate than gray matter volume throughout childhood. Koshiba et al used principal component analysis to examine factors associated with the neurological and behavioral development of “Head Control” and “Roll Over” in a neonatal population (Koshiba et al, 2015 ). They determined that hematological and brain anatomical factors were correlated with these basic neonatal movement patterns.…”

Inexpensive Home Infrared Living/Environment Sensor with Regional Thermal Information for Infant Physical and Psychological Development

“…Following our previously published methods (domestic chicks: [ 6 , 21 , 22 , 40 , 41 , 42 , 43 ]; common marmosets [ 6 , 7 , 8 , 9 , 21 , 33 , 34 ] and humans [ 6 , 21 , 44 , 45 ]), we then used principal component analysis (PCA) to infer the complex developmental mechanisms relating our obtained multiple variables including behavioral, physiological, biomolecular and psychological factors. The light-dark or before-after feeding differences of each principal component (PC) score were additionally analyzed by two-way ANOVA followed by Tukey’s HSD, as described above.…”