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TNF-α Is a Predictor of Insulin Resistance in Human Pregnancy
Open accessAbstract
Historically, insulin resistance during pregnancy has been ascribed to increased production of placental hormones and cortisol. The purpose of this study was to test this hypothesis by correlating the longitudinal changes in insulin sensitivity during pregnancy with changes in placental hormones, cortisol, leptin, and tumor necrosis factor (TNF)-α. Insulin resistance was assessed in 15 women (5 with gestational diabetes mellitus [GDM] and 10 with normal glucose tolerance) using the euglycemic-hyperinsulinemic clamp procedure, before pregnancy (pregravid) and during early (12–14 weeks) and late (34–36 weeks) gestation. Body composition, plasma TNF-α, leptin, cortisol, and reproductive hormones (human chorionic gonadotropin, estradiol, progesterone, human placental lactogen, and prolactin) were measured in conjunction with the clamps. Placental TNF-α was measured in vitro using dually perfused human placental cotyledon from five additional subjects. Compared with pregravid, insulin resistance was evident during late pregnancy in all women (12.4 ± 1.2 vs. 8.1 ± 0.8 10−2 mg · kg−1 fat-free mass · min−1 · μU−1 · ml−1). TNF-α, leptin, cortisol, all reproductive hormones, and fat mass were increased in late pregnancy (P < 0.001). In vitro, most of the placental TNF-α (94%) was released into the maternal circulation; 6% was released to the fetal side. During late pregnancy, TNF-α was inversely correlated with insulin sensitivity (r = −0.69, P < 0.006). Furthermore, among all of the hormonal changes measured in this study, the change in TNF-α from pregravid to late pregnancy was the only significant predictor of the change in insulin sensitivity (r = −0.60, P < 0.02). The placental reproductive hormones and cortisol did not correlate with insulin sensitivity in late pregnancy. Multivariate stepwise regression analysis revealed that TNF-α was the most significant independent predictor of insulin sensitivity (r = −0.67, P < 0.0001), even after adjustment for fat mass by covariance (r = 0.46, P < 0.01). These observations challenge the view that the classical reproductive hormones are the primary mediators of change in insulin sensitivity during gestation and provide the basis for including TNF-α in a new paradigm to explain insulin resistance in pregnancy.
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“Similarly, placental gene expression of TNF-α, IL-1β and their receptors has been reported to be increased in GDM [118,119].”
From The Pathophysiology of Gestational Diabetes Mellitus (2018) · cites this paper as [118]
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“Excess visceral adiposity does not merely represent a passive energy reserve; rather, it acts as an active immunometabolic organ [8-10].”
From Trimester-Specific Bioelectrical Impedance Reference Curves in Physiological Pregnancy: Mapping Maternal Body Composition and Hydration Trajectories (2026) · cites this paper as [10]
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“Plasma TNF-α, in particular, is strongly correlated with insulin resistance [118].”
From The Pathophysiology of Gestational Diabetes Mellitus (2018) · cites this paper as [118]
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“Kirwan et al. stated that an increase in insulin resistance, which is characteristic of pregnancy, most strongly correlates with the increase in TNF-α concentration, considering that TNF-α as a marker of insulin resistance during pregnancy [45].”
From Gestational Diabetes Mellitus—Recent Literature Review (2022) · cites this paper as [45]
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Citations
Cites
Positional cloning of the mouse obese gene and its human homologue
Zhang, Y., Proenca, R., Maffei, M., Barone, M., Leopold, L., & Friedman, J. M. (1994) · Nature · doi:10.1038/372425a0 · Cited by 13,419
Self-citationGlucose clamp technique: a method for quantifying insulin secretion and resistance.
DeFronzo, R. A., Tobin, J. D., & Andres, R. (1979) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.1979.237.3.e214 · Cited by 7,425
Maffei, M., Halaas, J., Ravussin, E., Pratley, R. E., Lee, G. H., Zhang, Y., Fei, H., Kim, S., Lallone, R., Ranganathan, S., et al. (1995) · Nature Medicine · doi:10.1038/nm1195-1155 · Cited by 3,725
Self-citationHotamisligil, G. S., Peraldi, P., Budavari, A., Ellis, R., White, M. F., & Spiegelman, B. M. (1996) · Science · doi:10.1126/science.271.5249.665 · Cited by 2,630
Criteria for screening tests for gestational diabetes
Carpenter, M. W., & Coustan, D. R. (1982) · American Journal of Obstetrics and Gynecology · doi:10.1016/0002-9378(82)90349-0 · Cited by 1,924
Kern, P. A., Ranganathan, S., Li, C., Wood, L., & Ranganathan, G. (2001) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.2001.280.5.e745 · Cited by 1,883
Nonadipose tissue production of leptin: Leptin as a novel placenta-derived hormone in humans
Masuzaki, H., Ogawa, Y., Sagawa, N., Hosoda, K., Matsumoto, T., Mise, H., Nishimura, H., Yoshimasa, Y., Tanaka, I., Mori, T., et al. (1997) · Nature Medicine · doi:10.1038/nm0997-1029 · Cited by 1,277
Tumor necrosis factor alpha inhibits signaling from the insulin receptor.
Hotamışlıgil, G. S., Murray, D. L., Choy, L., & Spiegelman, B. M. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.11.4854 · Cited by 1,220
Catalano, P. M., Huston, L., Amini, S. B., & Kalhan, S. C. (1999) · American Journal of Obstetrics and Gynecology · doi:10.1016/s0002-9378(99)70662-9 · Cited by 680
Self-citationDirect antidiabetic effect of leptin through triglyceride depletion of tissues
Shimabukuro, M., Koyama, K., Chen, G., Wang, M.-Y., Trieu, F., Lee, Y., Newgard, C. B., & Unger, R. H. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.9.4637 · Cited by 646
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Westergaard, D., Lundgaard, A. T., Vomstein, K., Fich, L., Hviid, K. V. R., Egerup, P., Christiansen, A.-M. H., Nielsen, J. R., Lindman, J., Holm, P. C., et al. (2023) · medRxiv · doi:10.1101/2023.08.10.23293934
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Otto, S., Burow, K., Eckert, A. J., Heldt, K., Henn, M., Holder, M., Schweizer, R., & Holl, R. W. (2024) · Diabetologie und Stoffwechsel · doi:10.1055/a-2270-4038
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Cinkajzlová, A., Anderlová, K., Hornová, M., Pařı́zek, A., Mráz, M., Kršek, M., Haluzı́k, M., & Šimják, P. (2025) · Physiological Research · doi:10.33549/physiolres.935424
Zhao, S. S., Woolf, B. A. R., Rogne, T., & Gill, D. (2025) · Rheumatology Advances in Practice · doi:10.1093/rap/rkaf100
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Ni, Y., Bi, Y., Xu, X., Hu, Y., Ma, J., & Wang, Y. (2025) · Frontiers in Endocrinology · doi:10.3389/fendo.2025.1616668
Rehman, R., Asif, K., Sindhura, H., & Ediga, S. (2025) · Journal of Indian Society of Periodontology · doi:10.4103/jisp.jisp_259_24
Chen, S., Persson, M., Wang, R., Dalman, C., Lee, B. K., Karlsson, H., & Gardner, R. M. (2023) · Figshare · doi:10.6084/m9.figshare.23714104
Chen, S., Persson, M., Wang, R., Dalman, C., Lee, B. K., Karlsson, H., & Gardner, R. M. (2023) · Figshare · doi:10.6084/m9.figshare.23714101
Chen, S., Persson, M., Wang, R., Dalman, C., Lee, B. K., Karlsson, H., & Gardner, R. M. (2023) · Figshare · doi:10.6084/m9.figshare.23714107
Basri, N. I., Wahab, N. S. A., Nawi, A. M., Ishak, S., Murthi, P., & Rahman, R. A. (2026) · BMJ Open · doi:10.1136/bmjopen-2025-106653
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Zhou, C., Ding, J., Bai, M., Zhang, M., Liu, Y., Yao, B., & Chen, L. (2026) · BMC Pregnancy and Childbirth · doi:10.1186/s12884-026-08945-1
Opportunities and Challenges for Precision Nutrition in Gestational Obesity Management
Söderström, E., Kaegi-Braun, N., Sandborg, J., Lilliecreutz, C., & Löf, M. (2026) · Current Obesity Reports · doi:10.1007/s13679-026-00710-x · Cited by 1
Janc, M., Tomažič, M., Pirc, M., Skalerič, U., & Schara, R. (2026) · International Journal of Dental Hygiene · doi:10.1111/idh.70088
Metformin and Placental Ferroptosis in Gestational Diabetes: A Mechanistic Study
Lin, Q., Qin, X., Shen, M., Xia, D., Cao, X., She, G., Wang, H., & Zhou, W. (2026) · Journal of Diabetes Research · doi:10.1155/jdr/2226729
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Schaefer-Graf, U. M., Kautzky‐Willer, A., & Groten, T. (2026) · Springer eBooks · doi:10.1007/978-3-662-70578-0_38
Purc-Bandurko, K., Trojnar, K., Masiarz, A., Bandurko, A., Kimber-Trojnar, Ż., & Leszczyńska‐Gorzelak, B. (2026) · Biomolecules · doi:10.3390/biom16070998
Coltro, D. B., Mateus, J. D. O., Ferreira, I. D. O., Goettert, M. I., Costella, A. P., da Silva, G. L., Torres, I. L. D. S., da Silva, A. A., & Laste, G. (2026) · Journal of Pregnancy · doi:10.1155/jp/4762066
Pszczolkowski, V. L., Youn, Y.-J., Her, T. K., & Alejandro, E. U. (2026) · Journal of Animal Science · doi:10.1093/jas/skag212 · Cited by 1
Rodzeń, Ł., Rodzeń, M., Dyńka, D., Łojko, D., Karakuła‐Juchnowicz, H., Kraszewski, S., Fazio, S., Unwin, D., & Bikman, B. T. (2026) · Nutrients · doi:10.3390/nu18162666
Zhao, Y., Wang, B., Yang, Y., & Li, H. (2026) · Pharmacognosy Magazine · doi:10.1177/09731296261474347
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Bilyalova, G., Baibusunova, A., Boshanova, A., Akylzhanova, Z., (Idrisov), A. I., Turgumbayeva, A., Biktashev, D., Baubekova, A., Kulbayeva, S., Azanbayeva, D., et al. (2026) · Biomedicines · doi:10.3390/biomedicines14102340
Applications of new technologies in the diagnosis and screening of gestational diabetes mellitus
Bart, Y., Melamed, N., & Bartal, M. F. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-13265-0.00003-3
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Liu, W., Yuan, Z., Lv, Q., & Hu, L. (2026) · Biomolecules and Biomedicine · doi:10.17305/bb.2026.14779
Diabetes Mellitus: Review of the Common, Rare, and Uncommon (Conceptual and Metaphorical) Types
Pliszka, M., & Szablewski, L. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27219611
Comparative study of platelet profile in GDM and non-diabetic pregnancy in a tertiary care centre
Kirubanandan, S., Hiremath, P. B., & Balaji, S. (2026) · International Journal of Reproduction Contraception Obstetrics and Gynecology · doi:10.18203/2320-1770.ijrcog20263979
ANÁLISE MORFOLÓGICA E IMUNOLÓGICA DAS PLACENTAS DE RATAS COM DIABETE DE INTENSIDADE MODERADA
Sinzato, Y. K. (2009) · Americanae (AECID Library)
Metadata
- Authors
- Kirwan, J. P., Hauguel-De Mouzon, S., Lepercq, J., Challier, J.-C., Huston-Presley, L., Friedman, J. E., Kalhan, S. C., & Catalano, P. M.
- Affiliations
- MetroHealth (US)
- Département d’Endocrinologie, Institut Cochin de Génétique Moléculaire, Paris, France
- Institut Cochin (FR)
- Hôpital Cochin (FR)
- University of Colorado Health (US)
- Venue
- Diabetes
- Publisher
- American Diabetes Association
- Published
- 2002-07-01
- Volume
- 51
- Issue
- 7
- Pages
- 2207-2213
- ISSN
- 0012-1797 (ISSN-L)
- 1939-327X
- OpenAlex
- W2130148279
- Cited by
- 738
- References
- 46
- Citations by year
- 2026: 22 · 2025: 26 · 2024: 24 · 2023: 33 · 2022: 36 · 2021: 34 · 2020: 36 · 2019: 47 · 2018: 37 · 2017: 34 · 2016: 38 · 2015: 37 · 2014: 40 · 2013: 38 · 2012: 33
- FWCI
- 19.22
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Diabetes (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (11089, HD-22965, HD-11089)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD11089, HD-22965)
- Topics
- Health Sciences › Medicine › Obstetrics and Gynecology › Gestational Diabetes Research and Management
- Health Sciences › Medicine › Obstetrics and Gynecology › Pregnancy and preeclampsia studies
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
- Keywords
- insulin resistance, pregnancy, TNF-α, gestational diabetes mellitus, insulin sensitivity, placental hormones, cortisol, leptin, human placental lactogen, human chorionic gonadotropin, hyperinsulinemic-euglycemic clamp, fat mass, reproductive hormones, body composition, estradiol
- MeSH terms
- Adult, Blood Glucose, Body Composition, Female, Gestational Age, Chorionic Gonadotropin, Humans, Hydrocortisone, Infusions, Intravenous, Insulin, Insulin Resistance, Placenta, Placental Lactogen, Predictive Value of Tests, Pregnancy, Prolactin, Reference Values, Regression Analysis, Tumor Necrosis Factor-alpha, Glucose Clamp Technique, Diabetes, Gestational, Glucose Intolerance, Leptin
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