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Metabolomics move toward clinical use to predict gestational and youth-onset diabetes


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Yeyi Zhu, PhD
Yeyi Zhu, PhD

Obesity and pregnancy can foster a cycle of pathogenesis leading to both gestational diabetes (GDM) and type 2 diabetes in the mother and cardiometabolic disorders in her offspring. But not all women who are overweight to obese and become pregnant develop GDM or type 2 diabetes, nor do all normoweight women who become pregnant escape GDM. And not all children born to women with GDM develop their own cardiometabolic disorders.

“Conventional risk factors for GDM—age, pre-pregnancy body mass index, family history of diabetes, parity, history of GDM or macrosomia, even biomarkers such as fasting glucose, fasting insulin, or HOMA-IR—do not explain GDM, later progression to type 2 diabetes, or cardiometabolic disorders in offspring,” said Yeyi Zhu, PhD, Research Scientist, Kaiser Permanente Northern California. “There are multiple metabolite pathways associated with GDM risk—amino acids, glutamine, carbohydrates, fatty acids, the microbiome, and more. Metabolomics can help identify biomarkers to better understand the etiology of GDM, better predict risk, and better manage risk factors.”

Dr. Zhu opened Metabolomics During and After Pregnancy—Mechanisms and Steps Towards Precision Medicine on Sunday, June 5, which discussed how metabolomics research is moving from discovery to pre-validation, development, validation, and novel clinical applications. The session was livestreamed and can be viewed on-demand by registered meeting participants at If you haven’t registered for the 82nd Scientific Sessions, register today to access the valuable meeting content.

Denise Scholtens, PhD
Denise Scholtens, PhD

Even-chain saturated fatty acids (SFA) are strongly associated with risk for GDM, while odd-chain SFA are strongly associated with reduced risk for GDM, Dr. Zhu said. Elevated triglycerides are associated with increased GDM risk and cholesterol esters with reduced GDM risk. Combining conventional risk factors with metabolites, including microbiome-related metabolites, can dramatically improve GDM prediction.

“We need standardized sample collection and operational procedures to increase accuracy and reproducibility,” Dr. Zhu said. “Metabolomics has the potential to identify new etiologic or pathologic markers and better understand the mechanism of GDM. It has the potential to contribute to risk-stratified care, precision medicine.”

Teasing out mechanisms linking maternal glycemia and fetal outcomes is even more complex. Studies require enormous numbers of pregnancies and births with years of follow-up and statistical analysis.

“The HAPO (Hyperglycemia and Adverse Pregnancy Outcome) Study clearly showed that as maternal glucose gets higher, the risk of high birth weight gets higher, as do several other newborn risks,” said Denise Scholtens, PhD, Professor of Preventive Medicine and Neurological Surgery, Chief of Biostatistics in the Department of Preventive Medicine, Northwestern University, and Director, Northwestern University Data Analysis and Coordinating Center.

Erica P. Gunderson, PhD, MS, MPH
Erica P. Gunderson, PhD, MS, MPH

The original HAPO Study, 2000-2006, involved more than 25,000 pregnant women. The HAPO Follow-Up Study, 2013-2016, followed more than 4,500 mother-child pairs. Multiple analytic approaches suggest serial mechanisms link maternal features to newborn outcomes.

“We know that maternal genotype and metabolites inform fetal genotype and metabolites,” Dr. Scholtens said. “Maternal metabolomic influences appear more important than genetic variants in offspring outcomes.”

Metabolomics may also identify biomarkers to predict progression from GDM to type 2 diabetes.

“Pregnancy is a stress test, and GDM may represent pre-clinical, undetected, pre-existing metabolic dysfunction,” said Erica P. Gunderson, PhD, MS, MPH, Senior Research Scientist, Kaiser Permanente Northern California and Professor of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine. “If we can find pre-clinical changes in metabolism, we may be able to improve risk stratification for type 2 diabetes and develop new prevention strategies.”

The Study of Women, Infant Feeding and Type 2 Diabetes After Gestational Diabetes (SWIFT) identified strong associations between hyperactive amino acid metabolism in the early postpartum period and later type 2 diabetes, Dr. Gunderson said. SWIFT also found that elevated phospholipid and sphingolipid pathways are associated with reduced risk for future type 2 diabetes, while elevated triglyceride pathways are associated with increased type 2 diabetes risk. Longer duration of breastfeeding can reduce the risk of type 2 diabetes for up to 20 years, she noted, likely because lactation upregulates phospholipid and sphingolipid pathways while down regulating triglyceride pathways.

Wei Perng, PhD, MPH
Wei Perng, PhD, MPH

GDM can also have a profound impact on the offspring. Youth-onset type 2 diabetes is increasing about 5% annually, noted Wei Perng, PhD, MPH, Assistant Professor of Epidemiology, Colorado School of Public Health, and Associate Director, Research Training & Education, Lifecourse Epidemiology of Adiposity and Diabetes Center, University of Colorado School of Medicine, Anschutz Medical Campus. Youth-onset type 2 diabetes is more aggressive than adult-onset disease with lower response to medication, more rapid development of complications, and more rapid beta cell deterioration.

“We need to better understand risk and progression,” Dr. Perng said. “Metabolic diseases start in utero, and metabolic risk factors continue to accumulate over time. Exposure to developmental overnutrition, including maternal diabetes, can set a child on metabolic pathways that translate in increased adiposity, metabolic risk, and metabolic disease.”

The Exploring Perinatal Outcomes Among Children study followed children from in utero GDM exposure into adolescence. A panel of 10 phospholipid metabolites in childhood showed strong prospective associations with multiple metabolic risk factors through adolescence, but there are likely multiple pathways and mechanisms at work.

Sex may also play a role.

In boys, both branched chain amino acid metabolism and energetics (cell turnover and RNA/DNA cycling) predict metabolic dysfunction. Energetics was the more important predictor in girls.

“We need studies to confirm and validate findings in more diverse cohorts, especially impaired glucose tolerance, which may have etiologically distinct underpinnings from impaired fasting glucose,” Dr. Perng said. “And we need to advance precision medicine in ways that narrow, rather than widen, existing socioeconomic gaps.”