Assessing for prenatal risk factors associated with infant neurologic morbidity using a multivariate analysis

Samhita Jain; Scott Oltman; Elizabeth Rogers; Kelli Ryckman; Mark Petersen; Rebecca J Baer; Larry Rand; Xianhua Piao; Laura Jelliffe-Pawlowski

doi:10.1038/s41372-023-01820-3

Assessing for prenatal risk factors associated with infant neurologic morbidity using a multivariate analysis

J Perinatol. 2023 Dec;43(12):1486-1493. doi: 10.1038/s41372-023-01820-3. Epub 2023 Nov 10.

Authors

Samhita Jain¹, Scott Oltman^{2

3}, Elizabeth Rogers⁴, Kelli Ryckman⁵, Mark Petersen⁴, Rebecca J Baer^{2

6}, Larry Rand^{2

7}, Xianhua Piao^{4

8

9}, Laura Jelliffe-Pawlowski^{2

3}

Affiliations

¹ Division of Neonatology, Department of Pediatrics, University of California, San Francisco, CA, USA. Samhita.Jain@ucsf.edu.
² California Preterm Birth Initiative, University of California San Francisco, San Francisco, CA, USA.
³ Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA.
⁴ Division of Neonatology, Department of Pediatrics, University of California, San Francisco, CA, USA.
⁵ Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, IN, USA.
⁶ Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
⁷ Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Francisco School of Medicine, San Francisco, CA, USA.
⁸ Newborn Brain Research Institute, University of California, San Francisco, CA, USA.
⁹ Weill Institute for Neuroscience, University of California, San Francisco, CA, USA.

Abstract

Objective: To characterize the biochemical and demographic profiles of pregnant people with maternal immune activation (MIA) and identify the prenatal characteristics associated with neurologic morbidity in offspring.

Study design: This was a retrospective cohort study of 602 mother-infant dyads with births between 2009 and 2010 in California. Multivariable logistic regression was used to build a MIA vulnerability profile including mid-pregnancy biochemical markers and maternal demographic characteristics, and its relationship with infant neurologic morbidity was examined.

Results: Of the 602 mother-infant dyads, 80 mothers and 61 infants had diagnoses suggestive of MIA and neurologic morbidity, respectively. Our model, including two demographic and seven biochemical characteristics, identified mothers with MIA with good performance (AUC:0.814; 95% CI:0.7-0.8). Three demographic and five inflammatory markers together identified 80% of infants with neurological morbidity (AUC:0.802, 95% CI:0.7-0.8).

Conclusion: Inflammatory environment in mothers with pre-existing risk factors like obesity, poverty, and prematurity renders offspring more susceptible to neurologic morbidities.

Publication types

Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural

MeSH terms

Female
Humans
Infant
Morbidity
Multivariate Analysis
Obesity*
Pregnancy
Retrospective Studies
Risk Factors

Grants and funding

R01 NS108446/NS/NINDS NIH HHS/United States