PDF herunterladen
Am J Perinatol 2016; 33(13): 1306-1312
DOI: 10.1055/s-0036-1586508
Original Article
Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

First Trimester Detection of Placental Disease: Challenges and Opportunities

Carolyn M. Salafia
1   Placental Modulation Laboratory, Institute for Basic Research, Staten Island, New York
2   Division of Predictive Modeling, Placental Analytics, New Rochelle, New York
,
Diana M. Thomas
3   Center for Quantitative Obesity Research, Montclair State University, Montclair, New Jersey
,
Drucilla J. Roberts
4   Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
,
Jennifer K. Straughen
5   Department of Public Health Sciences, Henry Ford Hospital, Detroit, Michigan
,
Patrick M. Catalano
6   Clinical Research Unit, Case Western Reserve University, Cleveland, Ohio
7   Center for Reproductive Health, Department of Obstetrics and Gynecology, MetroHealth Medical Center, Case Western Reserve University, Cleveland, Ohio
,
Gabriela Perez-Avilan
2   Division of Predictive Modeling, Placental Analytics, New Rochelle, New York
› Institutsangaben
Weitere Informationen

Publikationsverlauf

29. Februar 2016

21. Juni 2016

Publikationsdatum:
04. August 2016 (online)

    Lizenzen und Reprints

Abstract

It is generally agreed that placental pathology accounts for the majority of perinatal morbidity and mortality. If a placental prodrome could be diagnosed in vivo, risk for maternal or fetal complications could be estimated and acted upon before clinical symptoms are apparent. This is especially relevant in early diagnoses of gestational diabetes mellitus, which can be controlled through carefully monitored diet and activity changes. To meet this important need, there have been increased efforts to identify early gestation biomarkers of placental dysfunction using innovative imaging technologies. Here we outline innovative quantitative markers of placental shape and their relationship to placental function, clinical implications of these quantifiers, and the most recent mathematical models that utilize placental images to delineate at risk from normal pregnancies. We propose that novel contexts of readily available placental measures and routine collection of in vivo placental images in all pregnancies may be all that are needed to advance the identification of early risk determination of complicated pregnancies from placental images.

Keywords

diabetes - obesity - placenta - fetus - ultrasound - Doppler - growth model
 

  • References

  • 1 Desoye G, van Poppel M. The feto-placental dialogue and diabesity. Best Pract Res Clin Obstet Gynaecol 2015; 29 (1) 15-23
    CrossrefPubMedGoogle Scholar
  • 2 Simmons D. Diabetes and obesity in pregnancy. Best Pract Res Clin Obstet Gynaecol 2011; 25 (1) 25-36
    CrossrefPubMedGoogle Scholar
  • 3 Rani V, Deep G, Singh RK, Palle K, Yadav UC. Oxidative stress and metabolic disorders: pathogenesis and therapeutic strategies. Life Sci 2016; 148: 183-193
    CrossrefPubMedGoogle Scholar
  • 4 Verdile G, Keane KN, Cruzat VF , et al. Inflammation and oxidative stress: the molecular connectivity between insulin resistance, obesity, and Alzheimer's disease. Mediators Inflamm 2015; 2015: 105828
    PubMedGoogle Scholar
  • 5 Dimasuay KG, Boeuf P, Powell TL, Jansson T. Placental responses to changes in the maternal environment determine fetal growth. Front Phys 2016; 7: 12
    PubMedGoogle Scholar
  • 6 Leon-Garcia SM, Roeder HA, Nelson KK , et al. Maternal obesity and sex-specific differences in placental pathology. Placenta 2016; 38: 33-40
    CrossrefPubMedGoogle Scholar
  • 7 Arizawa M, Nakayama M, Kidoguchi K. Correlation of placental villous immaturity and dysmaturity with clinical control of maternal diabetes [in Japanese]. Nippon Sanka Fujinka Gakkai Zasshi 1991; 43 (6) 595-602
    PubMedGoogle Scholar
  • 8 Seidmann L, Suhan T, Unger R, Gerein V, Kirkpatrick CJ. Transient CD15-positive endothelial phenotype in the human placenta correlates with physiological and pathological fetoplacental immaturity. Eur J Obstet Gynecol Reprod Biol 2014; 180: 172-179
    CrossrefPubMedGoogle Scholar
  • 9 Huynh J, Dawson D, Roberts D, Bentley-Lewis R. A systematic review of placental pathology in maternal diabetes mellitus. Placenta 2015; 36 (2) 101-114
    CrossrefPubMedGoogle Scholar
  • 10 Saini P, Pankaj JP, Jain A, Agarwal GC. Effect of gestational diabetes mellitus on gross morphology of placenta: a comparative study. Int J Anat Res 2015; 3 (1) 889-894
    PubMedGoogle Scholar
  • 11 Basnet K, Bentley-Lewis R, Wexler DJ, Kilic F, Roberts DJ. The prevalence of intervillous thrombi is increased in placentas from pregnancies complicated by diabetes. Pediatr Dev Pathol 2015;
    PubMedGoogle Scholar
  • 12 Li Y, Hadden C, Singh P , et al. GDM-associated insulin deficiency hinders the dissociation of SERT from ERp44 and down-regulates placental 5-HT uptake. Proc Natl Acad Sci U S A 2014; 111 (52) E5697-E5705
    CrossrefPubMedGoogle Scholar
  • 13 Starikov R, Inman K, Chen K , et al. Comparison of placental findings in type 1 and type 2 diabetic pregnancies. Placenta 2014; 35 (12) 1001-1006
    CrossrefPubMedGoogle Scholar
  • 14 Smyth S, Heron A. Diabetes and obesity: the twin epidemics. Nat Med 2006; 12 (1) 75-80
    CrossrefPubMedGoogle Scholar
  • 15 Aye IL, Lager S, Ramirez VI , et al. Increasing maternal body mass index is associated with systemic inflammation in the mother and the activation of distinct placental inflammatory pathways. Biol Reprod 2014; 90 (6) 129
    CrossrefPubMedGoogle Scholar
  • 16 Straughen JK, Misra DP, Kumar P, Misra VK. The influence of overweight and obesity on maternal soluble FMS-like tyrosine kinase 1 and its relationship with leptin during pregnancy. Reprod Sci 2013; 20 (3) 269-275
    CrossrefPubMedGoogle Scholar
  • 17 Misra VK, Straughen JK, Trudeau S. Maternal serum leptin during pregnancy and infant birth weight: the influence of maternal overweight and obesity. Obesity (Silver Spring) 2013; 21 (5) 1064-1069
    CrossrefPubMedGoogle Scholar
  • 18 Catalano P, deMouzon SH. Maternal obesity and metabolic risk to the offspring: why lifestyle interventions may have not achieved the desired outcomes. Int J Obes 2015; 39 (4) 642-649
    CrossrefPubMedGoogle Scholar
  • 19 Kleiber M. Body size and metabolic rate. Physiol Rev 1947; 27 (4) 511-541
    PubMedGoogle Scholar
  • 20 Salafia CM, Kiryankova N, Inany H , et al. Metabolic scaling and twin placentas. Placenta 2016; 37: 16-18
    CrossrefPubMedGoogle Scholar
  • 21 Salafia CM, Yampolsky M. Metabolic scaling law for fetus and placenta. Placenta 2009; 30 (5) 468-471
    CrossrefPubMedGoogle Scholar
  • 22 Salafia CM, Misra DP, Yampolsky M, Charles AK, Miller RK. Allometric metabolic scaling and fetal and placental weight. Placenta 2009; 30 (4) 355-360
    CrossrefPubMedGoogle Scholar
  • 23 Thomas DM, Clapp JF, Shernce S. A foetal energy balance equation based on maternal exercise and diet. J R Soc Interface 2008; 5 (21) 449-455
    CrossrefPubMedGoogle Scholar
  • 24 Thomas DM, Navarro-Barrientos JE, Rivera DE , et al. Dynamic energy-balance model predicting gestational weight gain. Am J Clin Nutr 2012; 95 (1) 115-122
    CrossrefPubMedGoogle Scholar
  • 25 Heymsfield SB, Thomas D, Bosy-Westphal A, Shen W, Peterson CM, Müller MJ. Evolving concepts on adjusting human resting energy expenditure measurements for body size. Obes Rev 2012; 13 (11) 1001-1014
    CrossrefPubMedGoogle Scholar
  • 26 Melanson EL, Coelho LB, Tran ZV, Haugen HA, Kearney JT, Hill JO. Validation of the BodyGem hand-held calorimeter. Int J Obes Relat Metab Disord 2004; 28 (11) 1479-1484
    CrossrefPubMedGoogle Scholar
  • 27 Salafia CM, Zhang J, Charles AK , et al. Placental characteristics and birthweight. Paediatr Perinat Epidemiol 2008; 22 (3) 229-239
    CrossrefPubMedGoogle Scholar
  • 28 Misra DP, Salafia CM, Charles AK, Miller RK. Birth weights smaller or larger than the placenta predict BMI and blood pressure at age 7 years. J Dev Orig Health Dis 2010; 1 (2) 123-130
    CrossrefPubMedGoogle Scholar
  • 29 Misra DP, Salafia CM, Charles AK, Miller RK. Placental measurements associated with intelligence quotient at age 7 years. J Dev Orig Health Dis 2012; 3 (3) 190-197
    CrossrefPubMedGoogle Scholar
  • 30 Misra DP, Salafia CM, Miller RK, Charles AK. Non-linear and gender-specific relationships among placental growth measures and the fetoplacental weight ratio. Placenta 2009; 30 (12) 1052-1057
    CrossrefPubMedGoogle Scholar
  • 31 Hiroi R, Carbone DL, Zuloaga DG, Bimonte-Nelson HA, Handa RJ. Sex-dependent programming effects of prenatal glucocorticoid treatment on the developing serotonin system and stress-related behaviors in adulthood. Neuroscience 2016; 320: 43-56
    CrossrefPubMedGoogle Scholar
  • 32 Yampolsky M, Salafia CM, Shlakhter O, Haas D, Eucker B, Thorp J. Modeling the variability of shapes of a human placenta. Placenta 2008; 29 (9) 790-797
    CrossrefPubMedGoogle Scholar
  • 33 Shingleton A. Allometry: the study of biological scaling. Nature Education Knowledge 2010; 3 (10) 2
    PubMedGoogle Scholar
  • 34 Salafia CM, Yampolsky M, Shlakhter A, Mandel DH, Schwartz N. Variety in placental shape: when does it originate?. Placenta 2012; 33 (3) 164-170
    CrossrefPubMedGoogle Scholar
  • 35 Hageman JA, Hendriks MM, Westerhuis JA, van der Werf MJ, Berger R, Smilde AK. Simplivariate models: ideas and first examples. PLoS ONE 2008; 3 (9) e3259
    CrossrefPubMedGoogle Scholar
  • 36 Shah RG, Salafia CM, Girardi T, Conrad L, Keaty K, Bartleotc A. Shape matching algorithm to validate the tracing protocol of placental chorionic surface vessel networks. Placenta 2015; 36 (8) 944-946
    CrossrefPubMedGoogle Scholar
  • 37 Chan DY, Hughes BD, Leong AS, Reed WJ. Stochastically evolving networks. Phys Rev E Stat Nonlin Soft Matter Phys 2003; 68 (6, Pt 2): 066124
    CrossrefPubMedGoogle Scholar
  • 38 Calkins K, Devaskar SU. Fetal origins of adult disease. Curr Probl Pediatr Adolesc Health Care 2011; 41 (6) 158-176
    CrossrefPubMedGoogle Scholar
  • 39 Dyer JS, Rosenfeld CR. Metabolic imprinting by prenatal, perinatal, and postnatal overnutrition: a review. Semin Reprod Med 2011; 29 (3) 266-276
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 40 Ingelfinger JR, Nuyt AM. Impact of fetal programming, birth weight, and infant feeding on later hypertension. J Clin Hypertens (Greenwich) 2012; 14 (6) 365-371
    CrossrefPubMedGoogle Scholar
  • 41 Santos MS, Joles JA. Early determinants of cardiovascular disease. Best Pract Res Clin Endocrinol Metab 2012; 26 (5) 581-597
    CrossrefPubMedGoogle Scholar