Laura Jelliffe-Pawlowski

Faculty

Jelliffe-Pawlowski Headsot

Laura Jelliffe-Pawlowski

MS PhD

1 212 998 9020

433 First Ave
New York, NY 10010
United States

Laura Jelliffe-Pawlowski, PhD, MS, is a Professor. Prof. Jelliffe-Pawlowski’s research interests focus on understanding and addressing the drivers and consequences of adverse pregnancy outcomes with a special emphasis on preterm birth and associated racial/ethnic and socioeconomic inequities. Her work is highly transdisciplinary and looks at the interplay of biomolecular, social, and policy factors in observed patterns and outcomes. Her teaching and mentorship activities reflect this transdisciplinary approach with an emphasis on motivating the translation of research findings into action.

 

Prof. Jelliffe-Pawlowski leads a number of statewide, national, and international research efforts funded by the National Institutes of Health, the Bill and Melinda Gates Foundation, the March of Dimes, the State of California, and other entities. These includes, notably, the “Healthy Outcomes of Pregnancy for Everyone (HOPE)” consortium and study which focuses on understanding the experience of pregnant people and their infants pre- and post-COVID 19 pandemic. HOPE examines how biomolecular, social, and community factors affect the well-being and outcomes of mothers and infants and includes enrollment during pregnancy with outcome follow-up to 18-months after birth. Other ongoing projects include, for example, the NIH funded “Prediction Of Maturity, Morbidity, and Mortality in PreTerm Infants (PROMPT)”, study which focuses on examining the metabolic profiles of newborns with early preterm birth and associated outcomes, the “Transforming Health and Reducing PerInatal Anxiety through Virtual Engagement (THRIVE)”, randomized control trial (RCT), funded by the State of California which examines whether digital cognitive behavior therapy delivered by mobile app can assist in reducing anxiety symptoms in pregnant people and also examines participant acceptability of the application. Ongoing efforts also include leading the “California Prediction of Poor Outcomes of Pregnancy (CPPOP)” cohort study which focuses on investigating multi-omic drivers of preterm birth. The study interrogates biomolecular signals associated with preterm birth and includes full genome sequencing and mid-pregnancy biomolecular signaling related to metabolic, immune, stress, and placental function in hundreds of pregnancies with and without preterm birth. 

 

Prior to her joining NYU Meyers, Prof. Jelliffe-Pawlowski was a Professor of Epidemiology & Biostatistics, Chief of the Division of Lifecourse Epidemiology, a Professor in the Institute of Global Health Sciences, and Director of Discovery and Precision Health for the UCSF California Preterm Birth Initiative in the University of California San Francisco (UCSF) School of Medicine. She has a lifetime appointment as an Emeritus Professor of Epidemiology & Biostatistics in the UCSF School of Medicine and continues to work closely with the new Center for Birth Equity at UCSF. Prior to her appointment at UCSF, she was a leader at the Genetic Disease Screening Program within the California Department of Public Health. 

 

Prof. Jelliffe-Pawlowski efforts have been highlighted in numerous academic and lay articles including in the New York Times, in WIRED Magazine, in the Atlantic, on CNN, and on MSNBC. In 2023, she was recognized by Forbes Magazine as one of the top 50 over 50 Innovators in the United States. She is also a Phase I and Phase II Bill and Melinda Gates Foundation Grand Challenges awardee for her work in the United States and Uganda which focused on the development and validation of newborn metabolic profile as a novel measure of gestational age in infants.

BA, Psychology, University of California Los Angeles
MS, Child Development, University of California Davis
PhD, Human Development, University of California Davis

Preterm Birth

Forbes 50 over 50 awardee in Innovation (2023)
Delegate, African Academy of Sciences (2016)
Governor Brown Appointee for the California Department of Public Health, Interagency Coordinating Council on Early Intervention
Awardee, Bill and Melinda Bates Foundation, Gates Grand Challenges Phase I and II

Patterns of Preterm Birth among Women of Native Hawaiian and Pacific Islander Descent

Altman, M. R., Baer, R. J., & Jelliffe-Pawlowski, L. L. (2019). American Journal of Perinatology, 36(12), 1256-1263. 10.1055/s-0038-1676487
Abstract
Abstract
Objective †To describe the characteristics and risk factors for preterm birth in Hawaiian and Pacific Islander women. Study Design †Retrospective cohort study of 10,470 women of Hawaiian or Pacific Islander descent drawn from a population-based birth cohort dataset in California. Variables were examined across preterm birth subtype (spontaneous, provider initiated) and by gestational age grouping (early preterm birth and late preterm birth) and all preterm births. Results †Hawaiian/Pacific Islander women were at higher risk for preterm birth when they had fewer than three prenatal visits; were underweight, reported tobacco, alcohol, or illicit drugs use in pregnancy; had a diagnosis of anemia, gestational diabetes, preexisting diabetes, or hypertension with or without pre-eclampsia; or had a history of previous preterm birth. Obesity was found to be protective for preterm birth. Conclusion †Women of Hawaiian and Pacific Islander descent demonstrate a similar yet unique constellation of risk and protective factors for preterm birth as compared with other groups at high risk for preterm birth. Interventions aimed to prevent preterm birth need to support the specific needs of this population.

Previous Adverse Outcome of Term Pregnancy and Risk of Preterm Birth in Subsequent Pregnancy

Baer, R. J., Berghella, V., Muglia, L. J., Norton, M. E., Rand, L., Ryckman, K. K., Jelliffe-Pawlowski, L. L., & McLemore, M. R. (2019). Maternal and Child Health Journal, 23(4), 443-450. 10.1007/s10995-018-2658-z
Abstract
Abstract
Objective Evaluate risk of preterm birth (PTB, < 37 completed weeks’ gestation) among a population of women in their second pregnancy with previous full term birth but other adverse pregnancy outcome. Methods The sample included singleton live born infants between 2007 and 2012 in a birth cohort file maintained by the California Office of Statewide Health Planning and Development. The sample was restricted to women with two pregnancies resulting in live born infants and first birth between 39 and 42 weeks’ gestation. Logistic regression was used to calculate the risk of PTB in the second birth for women with previous adverse pregnancy outcome including: small for gestational age (SGA) infant, preeclampsia, placental abruption, or neonatal death (≤ 28 days). Risks were adjusted for maternal factors recorded for second birth. Results The sample included 133,622 women. Of the women with any previous adverse outcome, 4.7% had a PTB while just 3.0% of the women without a previous adverse outcome delivered early (relative risk adjusted for maternal factors known at delivery 1.4, 95% CI 1.3–1.5). History of an SGA infant, placental abruption, or neonatal death increased the adjusted risk of PTB in their second birth by 1.5–3.7-fold. History of preeclampsia did not elevate the risk of a preterm birth in the subsequent birth. Conclusions for Practice The findings indicate that women with previous SGA infant, placental abruption, or neonatal death, despite a term delivery, may be at increased risk of PTB in the subsequent birth. These women may be appropriate participates for future interventions aimed at reduction in PTB.

Risk of preterm and early term birth by maternal drug use

Baer, R. J., Chambers, C. D., Ryckman, K. K., Oltman, S. P., Rand, L., & Jelliffe-Pawlowski, L. L. (2019). Journal of Perinatology, 39(2), 286-294. 10.1038/s41372-018-0299-0
Abstract
Abstract
Objective: Examine the risk of preterm birth (PTB, < 37 weeks) and early term birth (37–38 weeks) for women with reported drug abuse/dependence. Study Design: The population was drawn from singleton livebirths in California from 2007 to 2012. Drug abuse/dependence was determined from maternal diagnostic codes (opioid, cocaine, cannabis, amphetamine, other, or polysubstance). Relative risks, adjusted for maternal factors were calculated for PTB and early term birth. Result: Of the 2,890,555 women in the sample, 1.7% (n = 48,133) had a diagnostic code for drug abuse/dependence. The percentage of PTBs varied from 11.6% (cannabis) to 24.3% (cocaine), compared with 6.7% of women without reported drug abuse/dependence. Conclusion: Women with reported drug abuse/dependence during pregnancy were at increased risk of having a PTB and all but those using cannabis were at risk of having an early term birth. Women using cocaine and polysubstance were at the highest risk of birth < 32 weeks.

Second trimester inflammatory and metabolic markers in women delivering preterm with and without preeclampsia

Ross, K. M., Baer, R. J., Ryckman, K., Feuer, S. K., Bandoli, G., Chambers, C., Flowers, E., Liang, L., Oltman, S., Dunkel Schetter, C., & Jelliffe-Pawlowski, L. (2019). Journal of Perinatology, 39(2), 314-320. 10.1038/s41372-018-0275-8
Abstract
Abstract
Objective: Inflammatory and metabolic pathways are implicated in preterm birth and preeclampsia. However, studies rarely compare second trimester inflammatory and metabolic markers between women who deliver preterm with and without preeclampsia. Study design: A sample of 129 women (43 with preeclampsia) with preterm delivery was obtained from an existing population-based birth cohort. Banked second trimester serum samples were assayed for 267 inflammatory and metabolic markers. Backwards-stepwise logistic regression models were used to calculate odds ratios. Results: Higher 5-α-pregnan-3β,20α-diol disulfate, and lower 1-linoleoylglycerophosphoethanolamine and octadecanedioate, predicted increased odds of preeclampsia. Conclusions: Among women with preterm births, those who developed preeclampsia differed with respect metabolic markers. These findings point to potential etiologic underpinnings for preeclampsia as a precursor to preterm birth.

Socioeconomic Status, Preeclampsia Risk and Gestational Length in Black and White Women

Ross, K. M., Dunkel Schetter, C., McLemore, M. R., Chambers, B. D., Paynter, R. A., Baer, R., Feuer, S. K., Flowers, E., Karasek, D., Pantell, M., Prather, A. A., Ryckman, K., & Jelliffe-Pawlowski, L. (2019). Journal of Racial and Ethnic Health Disparities, 6(6), 1182-1191. 10.1007/s40615-019-00619-3
Abstract
Abstract
Background: Higher socioeconomic status (SES) has less impact on cardio-metabolic disease and preterm birth risk among Black women compared to White women, an effect called “diminishing returns.” No studies have tested whether this also occurs for pregnancy cardio-metabolic disease, specifically preeclampsia, or whether preeclampsia risk could account for race-by-SES disparities in birth timing. Methods: A sample of 718,604 Black and White women was drawn from a population-based California cohort of singleton births. Education, public health insurance status, gestational length, and preeclampsia diagnosis were extracted from a State-maintained birth cohort database. Age, prenatal care, diabetes diagnosis, smoking during pregnancy, and pre-pregnancy body mass index were covariates. Results: In logistic regression models predicting preeclampsia risk, the race-by-SES interaction (for both education and insurance status) was significant. White women were at lower risk for preeclampsia, and higher SES further reduced risk. Black women were at higher risk for preeclampsia, and SES did not attenuate risk. In pathway analyses predicting gestational length, an indirect effect of the race-by-SES interaction was observed. Among White women, higher SES predicted lower preeclampsia risk, which in turn predicted longer gestation. The same was not observed for Black women. Conclusions: Compared to White women, Black women had increased preeclampsia risk. Higher SES attenuated risk for preeclampsia among White women, but not for Black women. Similarly, higher SES indirectly predicted longer gestational length via reduced preeclampsia risk among White women, but not for Black women. These findings are consistent with diminishing returns of higher SES for Black women with respect to preeclampsia.

Towards precision quantification of contamination in metagenomic sequencing experiments

Zinter, M. S., Mayday, M. Y., Ryckman, K. K., Jelliffe-Pawlowski, L. L., & Derisi, J. L. (2019). Microbiome, 7(1). 10.1186/s40168-019-0678-6
Abstract
Abstract
Metagenomic next-generation sequencing (mNGS) experiments involving small amounts of nucleic acid input are highly susceptible to erroneous conclusions resulting from unintentional sequencing of occult contaminants, especially those derived from molecular biology reagents. Recent work suggests that, for any given microbe detected by mNGS, an inverse linear relationship between microbial sequencing reads and sample mass implicates that microbe as a contaminant. By associating sequencing read output with the mass of a spike-in control, we demonstrate that contaminant nucleic acid can be quantified in order to identify the mass contributions of each constituent. In an experiment using a high-resolution (n = 96) dilution series of HeLa RNA spanning 3-logs of RNA mass input, we identified a complex set of contaminants totaling 9.1 ± 2.0 attograms. Given the competition between contamination and the true microbiome in ultra-low biomass samples such as respiratory fluid, quantification of the contamination within a given batch of biological samples can be used to determine a minimum mass input below which sequencing results may be distorted. Rather than completely censoring contaminant taxa from downstream analyses, we propose here a statistical approach that allows separation of the true microbial components from the actual contribution due to contamination. We demonstrate this approach using a batch of n = 97 human serum samples and note that despite E. coli contamination throughout the dataset, we are able to identify a patient sample with significantly more E. coli than expected from contamination alone. Importantly, our method assumes no prior understanding of possible contaminants, does not rely on any prior collection of environmental or reagent-only sequencing samples, and does not censor potentially clinically relevant taxa, thus making it a generalized approach to any kind of metagenomic sequencing, for any purpose, clinical or otherwise.

Using Index of Concentration at the Extremes as Indicators of Structural Racism to Evaluate the Association with Preterm Birth and Infant Mortality—California, 2011–2012

Chambers, B. D., Baer, R. J., McLemore, M. R., & Jelliffe-Pawlowski, L. L. (2019). Journal of Urban Health, 96(2), 159-170. 10.1007/s11524-018-0272-4
Abstract
Abstract
Disparities in adverse birth outcomes for Black women continue. Research suggests that societal factors such as structural racism explain more variation in adverse birth outcomes than individual-level factors and societal poverty alone. The Index of Concentration at the Extremes (ICE) measures spatial social polarization by quantifying extremes of deprived and privileged social groups using a single metric and has been shown to partially explain racial disparities in black carbon exposures, mortality, fatal and non-fatal assaults, and adverse birth outcomes such as preterm birth and infant mortality. The objective of this analysis was to assess if local measures of racial and economic segregation as proxies for structural racism are associated and preterm birth and infant mortality experienced by Black women residing in California. California birth cohort files were merged with the American Community Survey by zip code (2011–2012). The ICE was used to quantify privileged and deprived groups (i.e., Black vs. White; high income vs. low income; Black low income vs. White high income) by zip code. ICE scores range from − 1 (deprived) to 1 (privileged). ICE scores were categorized into five quintiles based on sample distributions of these measures: quintile 1 (least privileged)–quintile 5 (most privileged). Generalized linear mixed models were used to test the likelihood that ICE measures were associated with preterm birth or with infant mortality experienced by Black women residing in California. Black women were most likely to reside in zip codes with greater extreme income concentrations, and moderate extreme race and race + income concentrations. Bivariate analysis revealed that greater extreme income, race, and race + income concentrations increased the odds of preterm birth and infant mortality. For example, women residing in least privileged zip codes (quintile 1) were significantly more likely to experience preterm birth (race + income ICE OR = 1.31, 95% CI = 1.72–1.46) and infant mortality (race + income ICE OR = 1.70, 95% CI = 1.17–2.47) compared to women living in the most privileged zip codes (quintile 5). Adjusting for maternal characteristics, income, race, and race + income concentrations remained negatively associated with preterm birth. However, only race and race + income concentrations remained associated with infant mortality. Findings support that ICE is a promising measure of structural racism that can be used to address racial disparities in preterm birth and infant mortality experienced by Black women in California.

Altered metabolites in newborns with persistent pulmonary hypertension

Steurer, M. A., Oltman, S., Baer, R. J., Feuer, S., Liang, L., Paynter, R. A., Rand, L., Ryckman, K. K., Keller, R. L., & Jelliffe-Pawlowski, L. L. (2018). Pediatric Research, 84(2), 272-278. 10.1038/s41390-018-0023-y
Abstract
Abstract
Background: There is an emerging evidence that pulmonary hypertension is associated with amino acid, carnitine, and thyroid hormone aberrations. We aimed to characterize metabolic profiles measured by the newborn screen (NBS) in infants with persistent pulmonary hypertension of the newborn (PPHN) Methods: Nested case–control study from population-based database. Cases were infants with ICD-9 code for PPHN receiving mechanical ventilation. Controls receiving mechanical ventilation were matched 2:1 for gestational age, sex, birth weight, parenteral nutrition administration, and age at NBS collection. Infants were divided into derivation and validation datasets. A multivariable logistic regression model was derived from candidate metabolites, and the area under the receiver operator characteristic curve (AUROC) was generated from the validation dataset. Results: We identified 1076 cases and 2152 controls. Four metabolites remained in the final model. Ornithine (OR 0.32, CI 0.26–0.41), tyrosine (OR 0.48, CI 0.40–0.58), and TSH 0.50 (0.45–0.55) were associated with decreased odds of PPHN; phenylalanine was associated with increased odds of PPHN (OR 4.74, CI 3.25–6.90). The AUROC was 0.772 (CI 0.737–0.807). Conclusions: In a large, population-based dataset, infants with PPHN have distinct, early metabolic profiles. These data provide insight into the pathophysiology of PPHN, identifying potential therapeutic targets and novel biomarkers to assess the response.

Copy number variants in hypoplastic right heart syndrome

Giannakou, A., Sicko, R. J., Kay, D. M., Zhang, W., Romitti, P. A., Caggana, M., Shaw, G. M., Jelliffe-Pawlowski, L. L., & Mills, J. L. (2018). American Journal of Medical Genetics, Part A, 176(12), 2760-2767. 10.1002/ajmg.a.40527
Abstract
Abstract
Hypoplastic right heart syndrome (HRHS) is a rare congenital defect characterized by underdeveloped and malformed structures of the right heart. Familial recurrence of HRHS indicates genetic factors contribute to its etiology. Our study investigates the presence of copy number variants (CNVs) in HRHS cases. We genotyped 42 HRHS cases identified from live births throughout California (2003–2010) using the Illumina HumanOmni2.5-8 array. We identified 14 candidate CNVs in 14 HRHS cases (33%) based on the genes included in the CNVs and their functions. Duplications overlapping part of ERBB4 were identified in two unrelated cases. ERBB4 is a neuregulin receptor with a pivotal role in cardiomyocyte differentiation and heart development. We also described a 7.5 Mb duplication at 16q11-12. Multiple genes in the duplicated region have previously been linked to heart defects and cardiac development, including RPGRIP1L, RBL2, SALL1, and MYLK3. Of the 14 validated CNVs, we identified four CNVs in close proximity to genes linked to the Wnt signaling pathway. This study expands on our previous work supporting the role of genetics in HRHS. We identified CNVs affecting crucial genes and signaling pathways involved in right heart development. ERBB4 and duplication of the 16q11-12 region are important areas for future investigation.

Effect of fetal growth on 1-year mortality in neonates with critical congenital heart disease

Steurer, M. A., Baer, R. J., Burke, E., Peyvandi, S., Oltman, S., Chambers, C. D., Norton, M. E., Rand, L., Rajagopal, S., Ryckman, K. K., Feuer, S. K., Liang, L., Paynter, R. A., McCarthy, M., Moon-Grady, A. J., Keller, R. L., & Jelliffe-Pawlowski, L. L. (2018). Journal of the American Heart Association, 7(17). 10.1161/JAHA.118.009693
Abstract
Abstract
Background—Infants with critical congenital heart disease (CCHD) are more likely to be small for gestational age (GA). It is unclear how this affects mortality. The authors investigated the effect of birth weight Z score on 1-year mortality separately in preterm (GA <37 weeks), early-term (GA 37–38 weeks), and full-term (GA 39–42 weeks) infants with CCHD. Methods and Results—Live-born infants with CCHD and GA 22 to 42 weeks born in California 2007–2012 were included in the analysis. The primary predictor was Z score for birth weight and the primary outcome was 1-year mortality. Multivariable logistic regression was used. Results are presented as adjusted odds ratios and 95% confidence intervals (CIs). The authors identified 6903 infants with CCHD. For preterm and full-term infants, only a Z score for birth weight <−2 was associated with increased mortality compared with the reference group (Z score 0–0.5, adjusted odds ratio, 2.15 [95% CI, 1.1–4.21] and adjusted odds ratio, 3.93 [95% CI, 2.32–6.68], respectively). In contrast, in early-term infants, the adjusted odds ratios for Z scores <−2, −2 to −1, and −1 to −0.5 were 3.42 (95% CI, 1.93–6.04), 1.78 (95% CI, 1.12–2.83), and 2.03 (95% CI, 1.27–3.23), respectively, versus the reference group. Conclusions—GA seems to modify the effect of birth weight Z score on mortality in infants with CCHD. In preterm and full-term infants, only the most severe small-for-GA infants (Z score <−2) were at increased risk for mortality, while, in early-term infants, the risk extended to mild to moderate small-for-GA infants (Z score <−0.5). This information helps to identify high-risk infants and is useful for surgical planning.