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

A genome-wide association study identifies only two ancestry specific variants associated with spontaneous preterm birth

Rappoport, N., Toung, J., Hadley, D., Wong, R. J., Fujioka, K., Reuter, J., Abbott, C. W., Oh, S., Hu, D., Eng, C., Huntsman, S., Bodian, D. L., Niederhuber, J. E., Hong, X., Zhang, G., Sikora-Wohfeld, W., Gignoux, C. R., Wang, H., Oehlert, J., … Sirota, M. (2018). Scientific Reports, 8(1). 10.1038/s41598-017-18246-5
Abstract
Abstract
Preterm birth (PTB), or the delivery prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. Although twin studies estimate that maternal genetic contributions account for approximately 30% of the incidence of PTB, and other studies reported fetal gene polymorphism association, to date no consistent associations have been identified. In this study, we performed the largest reported genome-wide association study analysis on 1,349 cases of PTB and 12,595 ancestry-matched controls from the focusing on genomic fetal signals. We tested over 2 million single nucleotide polymorphisms (SNPs) for associations with PTB across five subpopulations: African (AFR), the Americas (AMR), European, South Asian, and East Asian. We identified only two intergenic loci associated with PTB at a genome-wide level of significance: rs17591250 (P = 4.55E-09) on chromosome 1 in the AFR population and rs1979081 (P = 3.72E-08) on chromosome 8 in the AMR group. We have queried several existing replication cohorts and found no support of these associations. We conclude that the fetal genetic contribution to PTB is unlikely due to single common genetic variant, but could be explained by interactions of multiple common variants, or of rare variants affected by environmental influences, all not detectable using a GWAS alone.

Initial Metabolic Profiles Are Associated with 7-Day Survival among Infants Born at 22-25 Weeks of Gestation

Oltman, S. P., Rogers, E. E., Baer, R. J., Anderson, J. G., Steurer, M. A., Pantell, M. S., Partridge, J. C., Rand, L., Ryckman, K. K., & Jelliffe-Pawlowski, L. L. (2018). Journal of Pediatrics, 198, 194-200.e3. 10.1016/j.jpeds.2018.03.032
Abstract
Abstract
Objective: To evaluate the association between early metabolic profiles combined with infant characteristics and survival past 7 days of age in infants born at 22-25 weeks of gestation. Study design: This nested case-control consisted of 465 singleton live births in California from 2005 to 2011 at 22-25 weeks of gestation. All infants had newborn metabolic screening data available. Data included linked birth certificate and mother and infant hospital discharge records. Mortality was derived from linked death certificates and death discharge information. Each death within 7 days was matched to 4 surviving controls by gestational age and birth weight z score category, leaving 93 cases and 372 controls. The association between explanatory variables and 7-day survival was modeled via stepwise logistic regression. Infant characteristics, 42 metabolites, and 12 metabolite ratios were considered for model inclusion. Model performance was assessed via area under the curve. Results: The final model included 1 characteristic and 11 metabolites. The model demonstrated a strong association between metabolic patterns and infant survival (area under the curve [AUC] 0.885, 95% CI 0.851-0.920). Furthermore, a model with just the selected metabolites performed better (AUC 0.879, 95% CI 0.841-0.916) than a model with multiple clinical characteristics (AUC 0.685, 95% CI 0.627-0.742). Conclusions: Use of metabolomics significantly strengthens the association with 7-day survival in infants born extremely premature. Physicians may be able to use metabolic profiles at birth to refine mortality risks and inform postnatal counseling for infants born at <26 weeks of gestation.

Maternal dyslipidemia and risk for preterm birth

Smith, C. J., Baer, R. J., Oltman, S. P., Breheny, P. J., Bao, W., Robinson, J. G., Dagle, J. M., Liang, L., Feuer, S. K., Chambers, C. D., Jelliffe-Pawlowski, L. L., & Ryckman, K. K. (2018). PloS One, 13(12). 10.1371/journal.pone.0209579
Abstract
Abstract
Maternal lipid profiles during pregnancy are associated with risk for preterm birth. This study investigates the association between maternal dyslipidemia and subsequent preterm birth among pregnant women in the state of California. Births were identified from California birth certificate and hospital discharge records from 2007–2012 (N = 2,865,987). Preterm birth was defined as <37 weeks completed gestation and dyslipidemia was defined by diagnostic codes. Subtypes of preterm birth were classified as preterm premature rupture of membranes (PPROM), spontaneous labor, and medically indicated, according to birth certificate data and diagnostic codes. The association between dyslipidemia and preterm birth was tested with logistic regression. Models were adjusted for maternal age at delivery, race/ethnicity, hypertension, pre-pregnancy body mass index, insurance type, and education. Maternal dyslipidemia was significantly associated with increased odds of preterm birth (adjusted OR: 1.49, 95%CI: 1.39, 1.59). This finding was consistent across all subtypes of preterm birth, including PPROM (adjusted OR: 1.54, 95%CI: 1.34, 1.76), spontaneous (adjusted OR: 1.51, 95%CI: 1.39, 1.65), and medically indicated (adjusted OR: 1.454, 95% CI: 1.282, 1.649). This study suggests that maternal dyslipidemia is associated with increased risk for all types of preterm birth.

Pre-pregnancy or first-trimester risk scoring to identify women at high risk of preterm birth

Baer, R. J., McLemore, M. R., Adler, N., Oltman, S. P., Chambers, B. D., Kuppermann, M., Pantell, M. S., Rogers, E. E., Ryckman, K. K., Sirota, M., Rand, L., & Jelliffe-Pawlowski, L. L. (2018). European Journal of Obstetrics and Gynecology and Reproductive Biology, 231, 235-240. 10.1016/j.ejogrb.2018.11.004
Abstract
Abstract
Objective To develop a pre-pregnancy or first-trimester risk score to identify women at high risk of preterm birth. Study design In this retrospective cohort analysis, the sample was drawn from California singleton livebirths from 2007 to 2012 with linked birth certificate and hospital discharge records. The dataset was divided into a training (2/3 of sample) and a testing (1/3 of sample) set for discovery and validation. Predictive models for preterm birth using pre-pregnancy or first-trimester maternal factors were developed using backward stepwise logistic regression on a training dataset. A risk score for preterm birth was created for each pregnancy using beta-coefficients for each maternal factor remaining in the final multivariable model. Risk score utility was replicated in a testing dataset and by race/ethnicity and payer for prenatal care. Results The sample included 2,339,696 pregnancies divided into training and testing datasets. Twenty-three maternal risk factors were identified including several that were associated with a two or more increased odds of preterm birth (preexisting diabetes, preexisting hypertension, sickle cell anemia, and previous preterm birth). Approximately 40% of women with a risk score ≥ 3.0 in the training and testing samples delivered preterm (40.6% and 40.8%, respectively) compared to 3.1–3.3% of women with a risk score of 0.0 [odds ratio (OR) 13.0, 95% confidence interval (CI) 10.7–15.8, training; OR 12.2, 95% CI 9.4–15.9, testing). Additionally, over 18% of women with a risk score ≥ 3.0 had an adverse outcome other than preterm birth. Conclusion Maternal factors that are identifiable prior to pregnancy or during the first-trimester can be used create a cumulative risk score to identify women at the lowest and highest risk for preterm birth regardless of race/ethnicity or socioeconomic status. Further, we found that this cumulative risk score could also identify women at risk for other adverse outcomes who did not have a preterm birth. The risk score is not an effective screening test, but does identify women at very high risk of a preterm birth.

Prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics

Jelliffe-Pawlowski, L. L., Rand, L., Bedell, B., Baer, R. J., Oltman, S. P., Norton, M. E., Shaw, G. M., Stevenson, D. K., Murray, J. C., & Ryckman, K. K. (2018). Journal of Perinatology, 38(8), 963-972. 10.1038/s41372-018-0112-0
Abstract
Abstract
Objective:: To evaluate if mid-pregnancy immune and growth-related molecular factors predict preterm birth (PTB) with and without (±) preeclampsia. Study design:: Included were 400 women with singleton deliveries in California in 2009–2010 (200 PTB and 200 term) divided into training and testing samples at a 2:1 ratio. Sixty-three markers were tested in 15–20 serum samples using multiplex technology. Linear discriminate analysis was used to create a discriminate function. Model performance was assessed using area under the receiver operating characteristic curve (AUC). Results:: Twenty-five serum biomarkers along with maternal age <34 years and poverty status identified >80% of women with PTB ± preeclampsia with best performance in women with preterm preeclampsia (AUC = 0.889, 95% confidence interval (0.822–0.959) training; 0.883 (0.804–0.963) testing). Conclusion:: Together with maternal age and poverty status, mid-pregnancy immune and growth factors reliably identified most women who went on to have a PTB ± preeclampsia.

Revisiting the Table 2 fallacy: A motivating example examining preeclampsia and preterm birth

Bandoli, G., Palmsten, K., Chambers, C. D., Jelliffe-Pawlowski, L. L., Baer, R. J., & Thompson, C. A. (2018). Paediatric and Perinatal Epidemiology, 32(4), 390-397. 10.1111/ppe.12474
Abstract
Abstract
Background: A “Table Fallacy,” as coined by Westreich and Greenland, reports multiple adjusted effect estimates from a single model. This practice, which remains common in published literature, can be problematic when different types of effect estimates are presented together in a single table. The purpose of this paper is to quantitatively illustrate this potential for misinterpretation with an example estimating the effects of preeclampsia on preterm birth. Methods: We analysed a retrospective population-based cohort of 2 963 888 singleton births in California between 2007 and 2012. We performed a modified Poisson regression to calculate the total effect of preeclampsia on the risk of PTB, adjusting for previous preterm birth. pregnancy alcohol abuse, maternal education, and maternal socio-demographic factors (Model 1). In subsequent models, we report the total effects of previous preterm birth, alcohol abuse, and education on the risk of PTB, comparing and contrasting the controlled direct effects, total effects, and confounded effect estimates, resulting from Model 1. Results: The effect estimate for previous preterm birth (a controlled direct effect in Model 1) increased 10% when estimated as a total effect. The risk ratio for alcohol abuse, biased due to an uncontrolled confounder in Model 1, was reduced by 23% when adjusted for drug abuse. The risk ratio for maternal education, solely a predictor of the outcome, was essentially unchanged. Conclusions: Reporting multiple effect estimates from a single model may lead to misinterpretation and lack of reproducibility. This example highlights the need for careful consideration of the types of effects estimated in statistical models.

Risk of preterm birth by maternal age at first and second pregnancy and race/ethnicity

Baer, R. J., Yang, J., Berghella, V., Chambers, C. D., Coker, T. R., Kuppermann, M., Oltman, S. P., Rand, L., Ryckman, K. K., Muglia, L. J., Chung, P. J., & Jelliffe-Pawlowski, L. L. (2018). Journal of Perinatal Medicine, 46(5), 539-546. 10.1515/jpm-2017-0014
Abstract
Abstract
We examined the risk of preterm birth (PTB, <37 weeks' gestation) in a second pregnancy and analyzed the extent to which this risk varies by maternal age and race/ethnicity. The sample included nulligravida mothers in California who delivered two singletons between 2005 and 2011. Logistic regression was used to calculate the odds of PTB in the second pregnancy. Within each race/ethnicity stratum, women delivering term infants in their first pregnancy and between 25 and 34 years old for both pregnancies served as the referent group. There were 2,90,834 women included in the study. Among women who delivered their first infant at term, the odds of delivering their second infant early differed by race and age. Hispanic, Black and Asian non-Hispanic women who were <18 years for both pregnancies were at higher odds of having a PTB in their second pregnancy (adjusted odds ratios 1.7, 3.3 and 2.9, respectively). Asian non-Hispanic women who were <18 years for their first delivery at term and between 18 and 24 years for their second delivery, or were >34 years for both, were also at higher odds of delivering their second baby prematurely (adjusted odds ratios 1.9 and 1.3, respectively). Women who deliver their first infant at <37 weeks of gestation are at 3 to 7 times higher odds of delivering their second infant preterm. Providers should consider including information about these risks in counseling their patients.

Second trimester serum cortisol and preterm birth: an analysis by timing and subtype

Bandoli, G., Jelliffe-Pawlowski, L. L., Feuer, S. K., Liang, L., Oltman, S. P., Paynter, R., Ross, K. M., Schetter, C. D., Ryckman, K. K., & Chambers, C. D. (2018). Journal of Perinatology, 38(8), 973-981. 10.1038/s41372-018-0128-5
Abstract
Abstract
Objective: We hypothesized second trimester serum cortisol would be higher in spontaneous preterm births compared to provider-initiated (previously termed ‘medically indicated’) preterm births. Study design: We used a nested case-control design with a sample of 993 women with live births. Cortisol was measured from serum samples collected as part of routine prenatal screening. We tested whether mean-adjusted cortisol fold-change differed by gestational age at delivery or preterm birth subtype using multivariable linear regression. Result: An inverse association between cortisol and gestational age category (trend p = 0.09) was observed. Among deliveries prior to 37 weeks, the mean-adjusted cortisol fold-change values were highest for preterm premature rupture of the membranes (1.10), followed by premature labor (1.03) and provider-initiated preterm birth (1.01), although they did not differ statistically. Conclusion: Cortisol continues to be of interest as a marker of future preterm birth. Augmentation with additional biomarkers should be explored.

Socioeconomic mediators of racial and ethnic disparities in congenital heart disease outcomes: A population-based study in California

Peyvandi, S., Baer, R. J., Moon-Grady, A. J., Oltman, S. P., Chambers, C. D., Norton, M. E., Rajagopal, S., Ryckman, K. K., Jelliffe-Pawlowski, L. L., & Steurer, M. A. (2018). Journal of the American Heart Association, 7(20). 10.1161/JAHA.118.010342
Abstract
Abstract
Background-—Racial/ethnic and socioeconomic disparities exist in outcomes for children with congenital heart disease. We sought to determine the influence of race/ethnicity and mediating socioeconomic factors on 1-year outcomes for live-born infants with hypoplastic left heart syndrome and dextro-Transposition of the great arteries. Methods and Results-—The authors performed a population-based cohort study using the California Office of Statewide Health Planning and Development database. Live-born infants without chromosomal anomalies were included. The outcome was a composite measure of mortality or unexpected hospital readmissions within the first year of life defined as >3 (hypoplastic left heart syndrome) or >1 readmissions (dextro-Transposition of the great arteries). Hispanic ethnicity was compared with non-Hispanic white ethnicity. Mediation analyses determined the percent contribution to outcome for each mediator on the pathway between race/ethnicity and outcome. A total of 1796 patients comprised the cohort (n=964 [hypoplastic left heart syndrome], n=832 [dextro-Transposition of the great arteries]) and 1315 were included in the analysis (n=477 non-Hispanic white, n=838 Hispanic). Hispanic ethnicity was associated with a poor outcome (crude odds ratio, 1.72; 95% confidence interval [CI], 1.37–2.17). Higher maternal education (crude odds ratio 0.5; 95% CI, 0.38–0.65) and private insurance (crude odds ratio, 0.65; 95% CI, 0.45– 0.71) were protective. In the mediation analysis, maternal education and insurance status explained 33.2% (95% CI, 7–66.4) and 27.6% (95% CI, 6.5–63.1) of the relationship between race/ethnicity and poor outcome, while infant characteristics played a minimal role. Conclusions-—Socioeconomic factors explain a significant portion of the association between Hispanic ethnicity and poor outcome in neonates with critical congenital heart disease. These findings identify vulnerable populations that would benefit from resources to lessen health disparities.

Acylcarnitine Profiles Reflect Metabolic Vulnerability for Necrotizing Enterocolitis in Newborns Born Premature

Sylvester, K. G., Kastenberg, Z. J., Moss, R. L., Enns, G. M., Cowan, T. M., Shaw, G. M., Stevenson, D. K., Sinclair, T. J., Scharfe, C., Ryckman, K. K., & Jelliffe-Pawlowski, L. L. (2017). Journal of Pediatrics, 181, 80-85.e1. 10.1016/j.jpeds.2016.10.019
Abstract
Abstract
Objective To evaluate the association between newborn acylcarnitine profiles and the subsequent development of necrotizing enterocolitis (NEC) with the use of routinely collected newborn screening data in infants born preterm. Study design A retrospective cohort study was conducted with the use of discharge records for infants born preterm admitted to neonatal intensive care units in California from 2005 to 2009 who had linked state newborn screening results. A model-development cohort of 94 110 preterm births from 2005 to 2008 was used to develop a risk-stratification model that was then applied to a validation cohort of 22 992 births from 2009. Results Fourteen acylcarnitine levels and acylcarnitine ratios were associated with increased risk of developing NEC. Each log unit increase in C5 and free carnitine /(C16 + 18:1) was associated with a 78% and a 76% increased risk for developing NEC, respectively (OR 1.78, 95% CI 1.53-2.02, and OR 1.76, 95% CI 1.51-2.06). Six acylcarnitine levels, along with birth weight and total parenteral nutrition, identified 89.8% of newborns with NEC in the model-development cohort (area under the curve 0.898, 95% CI 0.889-0.907) and 90.8% of the newborns with NEC in the validation cohort (area under the curve 0.908, 95% CI 0.901-0.930). Conclusions Abnormal fatty acid metabolism was associated with prematurity and the development of NEC. Metabolic profiling through newborn screening may serve as an objective biologic surrogate of risk for the development of disease and thus facilitate disease-prevention strategies.