Conflict of Interest
The authors have no conflicts of interest to declare.
References:
1. Flenady V, Koopmans L, Middleton P, Frøen JF, Smith GC, Gibbons K, et
al. Major risk factors for stillbirth in high-income countries: a
systematic review and meta-analysis. Lancet. 2011;377(9774):1331-40.2. Kabiri D, Romero R, Gudicha DW,
Hernandez-Andrade E, Pacora P, Benshalom-Tirosh N, et al. Prediction of
adverse perinatal outcome by fetal biometry: comparison of customized
and population-based standards. Ultrasound Obstet Gynecol. 2020;55(2):177-88.3. Gardosi J, and Francis A. A customized standard to
assess fetal growth in a US population. Am J Obstet Gynecol. 2009;201(1):25.e1-7.4. Saperstein A, and Penner AM. Racial Fluidity and
Inequality in the United States. American Journal of Sociology. 2012;118(3):676-727.5. Ganzevoort W, Thilaganathan B, Baschat A, and
Gordijn JS. Point. American Journal of Obstetrics and Gynecology. 2019;220(1):74-82.6. Vyas AD, Eisenstein GL, and Jones SD. Hidden in
Plain Sight — Reconsidering the Use of Race Correction in Clinical
Algorithms. New England Journal of Medicine. 2020;383(9):874-82.7. Chen J, Bacelis J, Sole-Navais P, Srivastava A,
Juodakis J, Rouse A, et al. Dissecting maternal and fetal genetic
effects underlying the associations between maternal phenotypes, birth
outcomes, and adult phenotypes: A mendelian-randomization and
haplotype-based genetic score analysis in 10,734 mother–infant pairs.PLOS Medicine. 2020;17(8):e1003305.8. Beaumont NR, Kotecha JS,
Wood RA, Knight AB, Sebert S, Mccarthy IM, et al. Common maternal and
fetal genetic variants show expected polygenic effects on risk of small-
or large-for-gestational-age (SGA or LGA), except in the smallest 3% of
babies. PLOS Genetics. 2020;16(12):e1009191.9. Engelbrechtsen L,
Gybel-Brask D, Mahendran Y, Crusell M, Hansen HT, Schnurr MT, et al.
Birth weight variants are associated with variable fetal intrauterine
growth from 20 weeks of gestation. Scientific Reports. 2018;8(1).10. Martin RA, Gignoux RC, Walters KR, Wojcik LG, Neale MB,
Gravel S, et al. Human Demographic History Impacts Genetic Risk
Prediction across Diverse Populations. The American Journal of
Human Genetics. 2017;100(4):635-49.11. Need CA, and Goldstein BD. Next
generation disparities in human genomics: concerns and remedies.Trends in Genetics. 2009;25(11):489-94.12. Popejoy BA, and
Fullerton MS. Genomics is failing on diversity. Nature. 2016;538(7624):161-4.13. Haas DM, Parker CB, Wing DA, Parry S, Grobman
WA, Mercer BM, et al. A description of the methods of the Nulliparous
Pregnancy Outcomes Study: monitoring mothers-to-be (nuMoM2b). Am J
Obstet Gynecol. 2015;212(4):539 e1- e24.14. Pedersen SB, and Quinlan
RA. Who’s Who? Detecting and Resolving Sample Anomalies in Human DNA
Sequencing Studies with Peddy. The American Journal of Human
Genetics. 2017;100(3):406-13.15. Khan RR, Guerrero RF, Wapner RJ, Hahn
MW, Raja A, Salleb-Aouissi A, et al. Genetic polymorphisms associated
with adverse pregnancy outcomes in nulliparas. Sci Rep. 2024;14(1):10514.16. Louis BMG, Grewal J, Albert SP, Sciscione A, Wing
AD, Grobman AW, et al. Racial/ethnic standards for fetal growth: the
NICHD Fetal Growth Studies. American Journal of Obstetrics and
Gynecology. 2015;213(4):449.e1-.e41.17. Blue RN, Grobman AW, Larkin CJ,
Scifres MC, Simhan NH, Chung HJ, et al. Customized versus Population
Growth Standards for Morbidity and Mortality Risk Stratification Using
Ultrasonographic Fetal Growth Assessment at 22 to 29 Weeks’ Gestation.American Journal of Perinatology. 2021;38(S 01):e46-e56.18.
Alexander, Kogan, Himes, Mor, and Goldenberg. Racial differences in
birthweight for gestational age and infant mortality in
extremely‐low‐risk US populations. Paediatric and Perinatal
Epidemiology. 1999;13(2):205-17.19. Jee HY, Thibord F, Dominguez A,
Sept C, Boulier K, Venkateswaran V, et al. Multi-ancestry polygenic risk
scores for venous thromboembolism. Human Molecular Genetics. 2024;33(18):1584-91.20. Dikilitas O, Schaid JD, Kosel LM, Carroll JR,
Chute GC, Denny CJ, et al. Predictive Utility of Polygenic Risk Scores
for Coronary Heart Disease in Three Major Racial and Ethnic Groups.The American Journal of Human Genetics. 2020;106(5):707-16.21.
Fahed CA, Aragam GK, Hindy G, Chen IY-D, Chaudhary K, Dobbyn A, et al.
Transethnic Transferability of a Genome-Wide Polygenic Score for
Coronary Artery Disease. Circulation: Genomic and Precision
Medicine. 2021;14(1).22. Tcheandjieu C, Zhu X, Hilliard TA, Clarke LS,
Napolioni V, Ma S, et al. Large-scale genome-wide association study of
coronary artery disease in genetically diverse populations. Nature
Medicine. 2022;28(8):1679-92.23. Jones CA, Patki A,
Srinivasasainagendra V, Tiwari KH, Armstrong DN, Chaudhary SN, et al.
Single-Ancestry versus Multi-Ancestry Polygenic Risk Scores for CKD in
Black American Populations. Journal of the American Society of
Nephrology. 2024;35(11):1558-69.24. Park LS, Cheng I, and Haiman AC.
Genome-Wide Association Studies of Cancer in Diverse Populations.Cancer Epidemiology, Biomarkers & Prevention. 2018;27(4):405-17.25. Teixeira KS, Rossi NPF, Patane LJ, Neyra MJ,
Jensen VVA, Horta LB, et al. Assessing the predictive efficacy of
European-based systolic blood pressure polygenic risk scores in diverse
Brazilian cohorts. Scientific Reports. 2024;14(1).26. Clarke LS,
Assimes LT, and Tcheandjieu C. The Propagation of Racial Disparities in
Cardiovascular Genomics Research. Circulation: Genomic and
Precision Medicine. 2021;14(5).27. Martin RA, Kanai M, Kamatani Y,
Okada Y, Neale MB, and Daly JM. Clinical use of current polygenic risk
scores may exacerbate health disparities. Nature Genetics. 2019;51(4):584-91.28. Ge T, Irvin RM, Patki A, Srinivasasainagendra V,
Lin Y-F, Tiwari KH, et al. Development and validation of a
trans-ancestry polygenic risk score for type 2 diabetes in diverse
populations. Genome Medicine. 2022;14(1).29. Wang Y, Tsuo K,
Kanai M, Neale MB, and Martin RA. Challenges and Opportunities for
Developing More Generalizable Polygenic Risk Scores. Annual Review
of Biomedical Data Science. 2022;5(1):293-320.30. Sun Q, Rowland TB,
Chen J, Mikhaylova VA, Avery C, Peters U, et al. Improving polygenic
risk prediction in admixed populations by explicitly modeling
ancestral-differential effects via GAUDI. Nature Communications. 2024;15(1).31. Honigberg MC, Truong B, Khan RR, Xiao B, Bhatta L, Vy
HMT, et al. Polygenic prediction of preeclampsia and gestational
hypertension. Nat Med. 2023;29(6):1540-9.32. Pagel KA, Chu H,
Ramola R, Guerrero RF, Chung JH, Parry S, et al. Association of Genetic
Predisposition and Physical Activity With Risk of Gestational Diabetes
in Nulliparous Women. JAMA Netw Open. 2022;5(8):e2229158.
Table 1. Demographic and obstetric characteristics of nuMoM2b
participants meeting secondary analysis inclusion criteria.