Prolactin and Maternal Metabolism in Women With a Recent GDM Pregnancy and Links to Future T2D: The SWIFT Study

Abstract

Context: Prolactin is a multifaceted hormone known to regulate lactation. In women with gestational diabetes mellitus (GDM) history, intensive lactation has been associated with lower relative risk of future type 2 diabetes (T2D). However, the role of prolactin in T2D development and maternal metabolism in women with a recent GDM pregnancy has not been ascertained.

Objective: We examined the relationships among prolactin, future T2D risk, and key clinical and metabolic parameters.

Methods: We utilized a prospective GDM research cohort (the SWIFT study) and followed T2D onset by performing 2-hour 75-g research oral glucose tolerance test (OGTT) at study baseline (6-9 weeks postpartum) and again annually for 2 years, and also by retrieving clinical diagnoses of T2D from 2 years through 10 years of follow up from electronic medical records. Targeted metabolomics and lipidomics were applied on fasting plasma samples collected at study baseline from 2-hour 75-g research OGTTs in a nested case-control study (100 future incident T2D cases vs 100 no T2D controls).

Results: Decreasing prolactin quartiles were associated with increased future T2D risk (adjusted odds ratio 2.48; 95% CI, 0.81-7.58; P = 0.05). In women who maintained normoglycemia during the 10-year follow-up period, higher prolactin at baseline was associated with higher insulin sensitivity (P = 0.038) and HDL-cholesterol (P = 0.01), but lower BMI (P = 0.001) and leptin (P = 0.002). Remarkably, among women who developed future T2D, prolactin was not correlated with a favorable metabolic status (all P > 0.05). Metabolomics and lipidomics showed that lower circulating prolactin strongly correlated with a T2D-high risk lipid profile, with elevated circulating neutral lipids and lower concentrations of specific phospholipids/sphingolipids.

Conclusion: In women with recent GDM pregnancy, low circulating prolactin is associated with specific clinical and metabolic parameters and lipid metabolites linked to a high risk of developing T2D.

Trial registration: ClinicalTrials.gov NCT01967030.

Keywords: gestational diabetes; lactation; maternal metabolism; prolactin; type 2 diabetes.

© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Figures

Figure 1.

Overview of the SWIFT cohort and study design (34). (A) SWIFT cohort enrolled 1035 women with GDM pregnancy that occurred from 2008 to 2011, who attended 3 in-person research exams with research 2-hour 75 g OGTTs starting from 6 to 9 weeks postpartum (study baseline). Of 1010 women with no diabetes at baseline were followed for future T2D onset up to 10 years post-baseline through 2-hour 75-g research OGTTs and electronic health records. A total of 226 participants developed incident T2D during the follow-up period. At baseline, 100 cases (future T2D) and 100 controls (no T2D) were pair-matched and included in the present study. (B) Baseline fasting plasma from the pair-matched 100 cases and 100 controls were measured using targeted metabolomics and lipidomics. Research metabolic variables were also collected for these 200 participants. Bioinformatic analyses, including correlation analysis, pathway analysis, and network analysis, were carried out. Abbreviations: AA, amino acid; BA, biogenic amine; EHR, electronic health record; GDM, gestational diabetes; HDL-C, high-density lipoprotein-cholesterol; KEGG, Kyoto Encyclopedia of Genes and Genomes; KPNC, Kaiser Permanente Northern California; LC-MS, liquid chromatography–mass spectrometry; OGTT, oral glucose tolerance test; SM, sphingomyelin; SWIFT, Study of Women, Infant Feeding, and Type 2 Diabetes after GDM Pregnancy, infant feeding, and type 2 diabetes after GDM pregnancy; T2D, type 2 diabetes; TAG, triglyceride.

Figure 2.

Correlation analysis of prolactin and research metabolic variables. Correlation between log10 prolactin levels and research metabolic variables; and the distribution of indicated variable within 4 quartiles of prolactin levels (first quartile: ≤34.85 ng/mL, second quartile: >34.85-60.88 ng/mL; third quartile: >60.88-126.24 ng/mL; fourth quartile: >126.24 ng/mL). (A) Age. (B) Baseline BMI. (C) Lactation intensity/duration (LIR 2-month score and total lactation duration). (D) Glucose tolerance variables (Research FPG and 2-hour PG). (E) Insulin resistance variables (fasting insulin and HOMA-IR). (F) Lipids (TAG and HDL-C). (G) Hormones (adiponectin and leptin). *P < 0.05, **P < 0.01, ***P < 0.001. Abbreviations: 2-h PG, 2-hour plasma glucose; BMI, body mass index; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; LIR, lactation intensity/duration ratio; TAG, triglyceride.

Figure 3.

Correlation of prolactin levels and research metabolic variables in the subgroups. Spearman correlation analysis of prolactin levels and research metabolic variables in the following 3 subgroups: future T2D (n = 100), no T2D (n = 100), and overall (n = 200). (A) Age. (B) Baseline BMI. (C) Lactation intensity/duration (LIR 2-month score and total lactation duration). (D) Glucose tolerance variables (FPG and 2-hour PG). (E) Insulin resistance variables (fasting insulin and HOMA-IR). (F) Lipids (TAG and HDL-C). (G) Hormones (adiponectin and leptin). Significance of correlation analysis: *FDR 

Figure 4.

Identification of prolactin-associated metabolites/lipids and metabolic pathways. (A) Workflow of the identification of prolactin-associated metabolites/lipids and metabolic pathways. (B) Bubble plot showing the significantly prolactin-correlated metabolites and lipid species (FDR P < 0.05) at baseline analyzed by KEGG pathway analysis. Red indicates positively correlated with prolactin levels. (D) Integrated metabolic pathway of lipid biosynthesis (fatty acids, neutral lipids, glycerophospholipids, and sphingolipids metabolism). Red indicates positive-correlated, and blue denotes negative-correlated. Abbreviations: AA, amino acid; KEGG, Kyoto Encyclopedia of Genes and Genomes; FFA, free fatty acid; CER, ceramide; DAG, diacylglycerol; DCER, dihydroceramide; LCER, lactosylceramide; LC-MS, liquid chromatography–mass spectrometry; LPC, lysophosphatidylcholine; PC, phosphatidylcholine; PE, phosphatidylethanolamine; SM, sphingomyelin; TAG, triacylglycerol.

Figure 5.

Network analysis of master transcription factors and genes involved in the prolactin-associated metabolism at early postpartum. (A) Flow chart of the identification of co-expressed genes and master transcription factors (TFs) from prolactin-correlated metabolites using MetaBridge and iRegulon. (B) iRegulon analysis depicting the regulatory network between the master regulons associated with prolactin and their downstream target genes. Abbreviations: NES, normalized enrichment score; TF, transcription factor.

Figure 6.

Identification of cutoff point of prolactin level. A cutoff point of prolactin levels (78.68 ng/mL) was identified by using package “cutpointr” in R, at which level the glucose tolerance outcomes (i.e., new onset of T2D) were found in the current study. The left showing the distribution of predictor values per class, the right showing the receiver operating characteristic (ROC) curve.