Hyperglycemia in pregnancy (i.e., type 1 diabetes, type 2 diabetes, and gestational diabetes mellitus) is the most common metabolic disorder during gestation, affecting approximately 16.7% of pregnancies worldwide (1). Gestational hyperglycemia has been associated with several short- and long-term adverse outcomes for both women (2–5) and their offspring (6). For offspring, gestational hyperglycemia is related to both adverse birth outcomes and long-term cardiometabolic and neurodevelopmental disorders (6–8). Additionally, previous research suggested that gestational hyperglycemia may influence the metabolite profiles of fetuses and neonates (9,10). These alterations of offspring metabolism may persist into mid-childhood (11,12), providing some evidence of the long-term impacts of gestational hyperglycemia on offspring health. Notably, among different metabolites, neonatal amino acid and acylcarnitine profiles were significantly associated with growth (13–15), cardiometabolic health (16,17), and neurodevelopment (18,19) across childhood. Previous studies also demonstrated that amino acids (e.g., branched-chain amino acids) and acylcarnitines (e.g., short- and medium-chain acylcarnitines, notably C6 and C7 carnitines) were positively related to type 2 diabetes (20), stroke (17), and blood pressure (16), in both adults and children, highlighting the importance of these metabolites across the life span. As such, understanding and identifying in utero determinants of these metabolites may have significant health implications.

As glycemia status varies substantially through pregnancy, exploring the intergenerational impact of hyperglycemia requires longitudinal assessments of glucose concentrations throughout pregnancy. In this issue of Diabetes Care, Zheng et al. (21) examined how longitudinal maternal glucose concentrations across pregnancy were associated with neonatal amino acid and acylcarnitine profiles, using data from 11,457 mother-child pairs, in the Beijing Birth Cohort Study (22). The authors identified three distinct trajectories of glucose profiles: consistent normoglycemia (n = 8,648), mid- to late-gestation hyperglycemia (n = 2,540), and early-onset hyperglycemia (n = 269). Compared with the normoglycemia group, the mid- to late-gestation hyperglycemia group had neonates with lower concentrations of several amino acids or acylcarnitines (alanine, arginine, glycine, leucine + isoleucine + hydroxyproline, ornithine, proline, valine, C6DC, and C10:1) and higher concentrations of C4DC+C5-OH. Neonates of women in the early-onset hyperglycemia group had higher concentrations of free acylcarnitine (C0) and C4DC+C5-OH and a lower concentration of C10:1 compared with those born to women in the normoglycemia group. Results from the pathway analysis highlighted that mid- to late-gestational hyperglycemia was associated with the arginine and proline metabolism and urea cycle pathway, whereas the early-onset hyperglycemia was related to the β-oxidation of very-long-chain fatty acids pathway. Interestingly, these metabolic pathways intersected with the citric acid cycle, which is, notably, indispensable for energy production. Further, more significant associations were found in male than in female infants (21).

This prospective study presents several unique strengths. The longitudinal assessment of maternal glucose concentrations across different trimesters of pregnancy allowed the authors to comprehensively explore the most relevant timing in the associations between maternal glucose concentrations and neonatal metabolites. The large sample size provided better statistical power and generalizability of findings and also provided for investigations on sex-specific associations. Additionally, pathway analyses provided important and interesting insights into the functional pathways underlying the association of gestational hyperglycemia with short- and long-term offspring neurodevelopment and cardiometabolic health, which is potentially through their impacts on offspring amino acid and acylcarnitine profiles.

The study is subject to several potential limitations as well. First, as stated by the authors, neonatal glucose concentration was not considered in this study, and neonatal glucose concentration may mediate the associations between maternal glycemia status in pregnancy and neonatal amino acid or acylcarnitine profiles. Second, maternal amino acid and acylcarnitine concentrations were not considered in the current study. Some studies demonstrated that maternal amino acid and acylcarnitine concentrations in early and mid-pregnancy may be associated with the risk of developing gestational hyperglycemia later in pregnancy (23,24). Further, there is evidence that the metabolite profile is heritable (11,25). As such, the offspring’s amino acid and acylcarnitine profiles reported in the study of Zheng et al. may reflect the mother’s metabolite profile rather than her glycemic status in pregnancy. To investigate the intergenerational health implications of gestational hyperglycemia more comprehensively, future studies with maternal and neonatal data on both glycemia status and amino acid and acylcarnitine concentrations are warranted (Fig. 1). In addition, more research on the longitudinal assessment of maternal biomarkers throughout pregnancy and offspring outcomes is needed to pinpoint critical time windows of these associations.

Figure 1

Potential intergenerational impacts of gestational hyperglycemia: future direction for research.

Figure 1

Potential intergenerational impacts of gestational hyperglycemia: future direction for research.

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In summary, data from the article by Zheng et al. (21) provide new evidence on in utero determinants of plasma amino acids and acylcarnitines in offspring and potential new insights into intergenerational impacts of gestational hyperglycemia. Given the known associations of branched-chain amino acid and short- and medium-chain acylcarnitine profiles with adverse health outcomes throughout the life span, including chronic diseases, the current study provides additional insights into the importance of controlling and monitoring hyperglycemia in pregnancy.

See accompanying article, p. 2128.

Acknowledgments. C.Z. is an editor of Diabetes Care but was not involved in any of the decisions regarding review of the manuscript or its acceptance.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Handling Editors. The journal editor responsible for overseeing the review of the manuscript was Matthew C. Riddle.

1.
Magliano
DJ
,
Boyko
EJ.
IDF Diabetes Atlas, 10th edition
.
Brussels
,
International Diabetes Federation
,
2021
. Accessed 11 June 2024. Available from https://www.ncbi.nlm.nih.gov/books/NBK581934/
2.
Rawal
S
,
Olsen
SF
,
Grunnet
LG
, et al
.
Gestational diabetes mellitus and renal function: a prospective study with 9- to 16-year follow-up after pregnancy
.
Diabetes Care
2018
;
41
:
1378
1384
3.
Kramer
CK
,
Campbell
S
,
Retnakaran
R.
Gestational diabetes and the risk of cardiovascular disease in women: a systematic review and meta-analysis
.
Diabetologia
2019
;
62
:
905
914
4.
Li
S
,
Zhu
Y
,
Chavarro
JE
, et al
.
Healthful dietary patterns and the risk of hypertension among women with a history of gestational diabetes mellitus: a prospective cohort study
.
Hypertension
2016
;
67
:
1157
1165
5.
Vounzoulaki
E
,
Khunti
K
,
Abner
SC
,
Tan
BK
,
Davies
MJ
,
Gillies
CL.
Progression to type 2 diabetes in women with a known history of gestational diabetes: systematic review and meta-analysis
.
BMJ
2020
;
369
:
m1361
6.
McIntyre
HD
,
Catalano
P
,
Zhang
C
,
Desoye
G
,
Mathiesen
ER
,
Damm
P.
Gestational diabetes mellitus
.
Nat Rev Dis Primers
2019
;
5
:
47
7.
Kawasaki
M
,
Arata
N
,
Miyazaki
C
, et al
.
Obesity and abnormal glucose tolerance in offspring of diabetic mothers: a systematic review and meta-analysis
.
PLoS One
2018
;
13
:
e0190676
8.
Zhang
T-N
,
Huang
X-M
,
Zhao
X-Y
,
Wang
W
,
Wen
R
,
Gao
S-Y.
Risks of specific congenital anomalies in offspring of women with diabetes: a systematic review and meta-analysis of population-based studies including over 80 million births
.
PLoS Med
2022
;
19
:
e1003900
9.
Lowe
WL
,
Bain
JR
,
Nodzenski
M
, et al.;
HAPO Study Cooperative Research Group
.
Maternal BMI and glycemia impact the fetal metabolome
.
Diabetes Care
2017
;
40
:
902
910
10.
Shokry
E
,
Marchioro
L
,
Uhl
O
, et al
.
Impact of maternal BMI and gestational diabetes mellitus on maternal and cord blood metabolome: results from the PREOBE cohort study
.
Acta Diabetol
2019
;
56
:
421
430
11.
Liu
M
,
Chan
S-Y
,
Eriksson
JG
, et al
.
Maternal glycemic status during pregnancy and mid-childhood plasma amino acid profiles: findings from a multi-ethnic Asian birth cohort
.
BMC Med
2023
;
21
:
472
12.
Ott
R
,
Pawlow
X
,
Weiß
A
, et al
.
Intergenerational metabolomic analysis of mothers with a history of gestational diabetes mellitus and their offspring
.
Int J Mol Sci
2020
;
21
:
9647
13.
Handakas
E
,
Keski-Rahkonen
P
,
Chatzi
L
, et al
.
Cord blood metabolic signatures predictive of childhood overweight and rapid growth
.
Int J Obes (Lond)
2021
;
45
:
2252
2260
14.
Isganaitis
E
,
Rifas-Shiman
SL
,
Oken
E
, et al
.
Associations of cord blood metabolites with early childhood obesity risk
.
Int J Obes (Lond)
2015
;
39
:
1041
1048
15.
Cao
T
,
Zhao
J
,
Hong
X
, et al
.
Cord blood plasma metabolome-wide associations with height from birth to adolescence
.
J Bone Miner Res
2023
May;
38
:
707
718
16.
Zhang
M
,
Brady
TM
,
Buckley
JP
, et al
.
Metabolome-wide association study of cord blood metabolites with blood pressure in childhood and adolescence
.
Hypertension
2022
;
79
:
2806
2820
17.
Guasch-Ferré
M
,
Zheng
Y
,
Ruiz-Canela
M
, et al
.
Plasma acylcarnitines and risk of cardiovascular disease: effect of Mediterranean diet interventions
.
Am J Clin Nutr
2016
;
103
:
1408
1416
18.
Anand
NS
,
Raghavan
R
,
Wang
G
, et al
.
Perinatal acetaminophen exposure and childhood attention-deficit/hyperactivity disorder (ADHD): exploring the role of umbilical cord plasma metabolites in oxidative stress pathways
.
Brain Sci
2021
;
11
:
1302
19.
Che
X
,
Roy
A
,
Bresnahan
M
, et al
.
Metabolomic analysis of maternal mid-gestation plasma and cord blood in autism spectrum disorders
.
Mol Psychiatry
2023
;
28
:
2355
2369
20.
Ramzan
I
,
Ardavani
A
,
Vanweert
F
,
Mellett
A
,
Atherton
PJ
,
Idris
I.
The association between circulating branched chain amino acids and the temporal risk of developing type 2 diabetes mellitus: a systematic review & meta-analysis
.
Nutrients
2022
;
14
:
4411
21.
Zheng
W
,
Yuan
X
,
Zhao
J
, et al
.
Neonatal amino acids and acylcarnitines associated with maternal blood glucose levels throughout pregnancy: insights from the Beijing Birth Cohort Study
.
Diabetes Care
2024
;
47
:
2128
2138
22.
Wang
J
,
Zheng
W
,
Wang
Y
, et al
.
Cohort profile: the Beijing Birth Cohort Study (BBCS)
.
Int J Epidemiol
2024
;
53
:
dyad155
23.
Lin
Y
,
Wu
J
,
Zhu
Y
, et al
.
A longitudinal study of plasma acylcarnitines throughout pregnancy and associations with risk of gestational diabetes mellitus
.
Clin Nutr
2021
;
40
:
4863
4870
24.
Yang
J
,
Wu
J
,
Tekola-Ayele
F
, et al
.
Plasma amino acids in early pregnancy and midpregnancy and their interplay with phospholipid fatty acids in association with the risk of gestational diabetes mellitus: results from a longitudinal prospective cohort
.
Diabetes Care
2023
;
46
:
722
732
25.
Cleal
JK
,
Lewis
RM.
The mechanisms and regulation of placental amino acid transport to the human foetus
.
J Neuroendocrinol
2008
;
20
:
419
426
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