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BMJ Open
BMJ Open
bmjopen
bmjopen
BMJ Open
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BMJ Publishing Group BMA House, Tavistock Square, London, WC1H 9JR

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10.1136/bmjopen-2023-083358
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Protocol
Obstetrics and Gynaecology
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Identifying microbiome-based changes and biomarkers prior to disease development in mother and child, with a focus on gestational diabetes mellitus: protocol for the DANish Maternal and Offspring Microbiome (DANMOM) cohort study
Rold Louise Søndergaard 12l.rold@rn.dk

Jensen Ann-Maria 1a.maria@rn.dk

Arenholt Louise 123ltsa@rn.dk

Leutscher Peter Derek Christian 12p.leutscher@rn.dk

Ovesen Per Glud 45per.ovesen@clin.au.dk

Hagstrøm Søren 267soha@rn.dk

http://orcid.org/0000-0002-4201-1168
Sørensen Suzette 127suzette.soerensen@rn.dk

1 Centre for Clinical Research, North Denmark Regional Hospital, Hjørring, Denmark
2 Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
3 Department of Gynecology and Obstetrics, North Denmark Regional Hospital, Hjørring, Denmark
4 Department of Gynecology and Obstetrics, Aarhus University Hospital, Aarhus, Denmark
5 Steno Diabetes Center Aarhus, Aarhus, Denmark
6 Department of Pediatrics and Adolescent Medicine, Aalborg University Hospital, Aalborg, Denmark
7 Steno Diabetes Center North Denmark, Aalborg, Denmark
DrSuzetteSørensen; suzette.soerensen@rn.dk
None declared.

2024
05 9 2024
14 9 e08335818 12 2023
23 8 2024
Copyright © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

Abstract

Introduction

The human gut microbiota is associated with gestational diabetes mellitus (GDM), which imposes a risk of developing long-term health problems for mother and child. Most studies on GDM and microbiota have been cross-sectional, which makes it difficult to make any conclusions on causality. Furthermore, it is important to assess if a dysbiotic microbiota is passed from the mother to the child, and then being at risk of developing metabolic health problems later in life. The DANish Maternal and Offspring Microbiome study aims to identify gut microbiota-related factors involved in metabolic dysfunction in women with GDM and their offspring. Importantly, the study design allows for early detection of biological changes associated with later development of metabolic disease. This could provide us with unique tools to support early diagnosis or implement preventative measures.

Methods and analysis

Pregnant women are included in the study after the 11–14 weeks’ prenatal ultrasound scan and followed throughout pregnancy with enrolment of the offspring at birth. 202 women and 112 children have been included from North Denmark Regional Hospital and Aalborg University Hospital in Denmark. Mother and child are followed until the children reach the age of 5 years. From the mother, we collect faeces, urine, blood, saliva, vaginal fluid and breast milk samples, in addition to faeces and a blood sample from the child. Microbiota composition in biological samples will be analysed using 16S rRNA gene sequencing and compared with demographic and clinical data from medical charts, registers and questionnaires. Sample and data collection will continue until July 2028.

Ethics and dissemination

The study protocol has been approved by the North Denmark Region Committee on Health Research Ethics (N20190007). Written informed consent is obtained from all participants prior to study participation. Study results will be published in international peer-reviewed journals and presented at international conferences. The results will also be presented to the funders of the study and study participants.

Diabetes in pregnancy
MICROBIOLOGY
PAEDIATRICS
OBSTETRICS
Marie Pedersen og Jensine Heiberg’s Foundation N/A Steno Diabetes Center North Denmark N/A Niels Jensen’s Foundation N/A
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pmcSTRENGTHS AND LIMITATIONS OF THIS STUDY

The longitudinal study design allows us to identify dynamic changes in the microbiota in both mother and child from early pregnancy to 5 years post partum.

The inclusion of both the mother and child gives us the opportunity to closely follow the transfer of bacteria from mother to child, and thereby identify important factors for the colonisation of the gut microbiota in the child.

The extensive collection of diverse biological samples and clinical data throughout the project will ensure a comprehensive understanding of the microbiota in both mother and child.

Some of the clinical data rely on self-reporting and interviews and are therefore prone to recall bias (to minimise this, we offer fill-out booklets to the parents in which they can report the different data along with the study period).

Due to the high number of study visits expanding over several years, the primary limitation of this study is the loss to follow-up and missing data points.

Introduction

The prevalence of gestational diabetes mellitus (GDM) is on the rise, impacting up to 14% of pregnancies worldwide.13 Known risk factors for developing GDM include a family history of type 2 diabetes mellitus (T2DM), previous delivery of macrosomic infants (>4500 g), prepregnancy body mass index (BMI) >27 kg/m², glucosuria and polycystic ovarian syndrome.4 While GDM usually resolves after pregnancy, it still has substantial health implications.57 GDM impacts both the mother and the child, leading to short-term complications like pre-eclampsia, neonatal hypoglycaemia and congenital malformations.57 Furthermore, it increases the risk of long-term complications such as diabetes, obesity and other metabolic disorders for both the mother and the child.813 Women with GDM have a 11-fold increased risk of developing T2DM within a few years postpartum, while the child has an 8-fold increased risk of developing T2DM in early adult life.11 13 14 However, it is still not fully elucidated why the women develop GDM and why the children are at higher risk of developing metabolic diseases such as diabetes and obesity, but the role of bacteria has been suggested.

The human gut is inhabited by numerous micro-organisms including viruses, fungi and bacteria,15 16 collectively known as the gut microbiota. The gut microbiota plays a crucial role in maintaining human health by contributing to various physiological processes. These include synthesis of essential vitamins and nutrients,1719 development of host immunity,20 21 regulation of immune responses22 and maintenance of a healthy gut barrier.23 24 Disruption in the balance of gut microbiota composition, known as dysbiosis, has been linked to several diseases and disorders, including GDM,2527 obesity28 29 and type 2 diabetes.30 31

Pregnancy represents a period of dramatic physiological, hormonal and metabolic changes in the mother with the purpose of supporting the growing fetus.32 It has been shown that the gut microbiota likewise changes throughout pregnancy and is functionally associated with increases in insulin resistance and hyperglycaemia, possibly leading to GDM.33 Most of the studies investigating the gut microbiota in women with GDM have found dysbiosis after the time of diagnosis.27 However, recent research suggests that dysbiosis may precede the onset of disease, highlighting a potential early role of dysbiosis in the development of GDM.34 Bacterial dysbiosis may result in a decrease of beneficial microbial metabolites, such as circulating short-chain fatty acids (SCFAs). For instance, reduced levels of isovalerate and isobutyrate, two SCFAs that promote glucose homeostasis and suppress inflammatory responses, have been observed in women before the GDM diagnosis.34 Therefore, it is possible that gut dysbiosis alters the metabolic response in the host, thereby playing a role in the development of GDM and other metabolic diseases.

Furthermore, it has been proposed that the dysbiotic GDM-associated microbiota of the mother could be transferred to the child early in life. The gut microbiota is established early in life, with bacterial diversity expanding dramatically during the first 3 years until stabilising to a composition resembling that in the adult gut.35 36 This process is affected by several factors, including both prenatal and postnatal factors.37 Among these, the maternal health during pregnancy seems to be important. For instance, studies have shown that children of women with GDM have a different gut microbiota compared with children born to mothers without GDM.3843 These children harbour similar bacteria to their mothers, pointing towards the transmission of maternal dysbiotic microbiota to the infant.41 44 Thus, children of GDM mothers may inherit their mothers’ dysbiotic microbiota, which again may alter their metabolism.38 This early transfer from mother to child could therefore have a great impact on disease development in the child. This is further supported by previous studies that have shown an association between infant gut dysbiosis and the development of endocrine and metabolic diseases such as type 1 diabetes mellitus45 and obesity later in life.46 Thus, it is believed that the establishment of a healthy gut microbiota early in life is important for disease prevention. Exactly how these dysbiotic traits are transferred from mother to child is not very well understood, although different modes of transmission have been suggested.4751 For vaginally delivered children where the membrane has ruptured before birth, children are initially exposed to bacteria from the mother’s gut and vagina, while children born via caesarean section encounter bacteria from the skin and hospital environment, and thereby lack key microbes from the mother.50 51 During the first months of life, breast milk is an important source in modulating the infant’s gut microbiota.5254 This occurs both through prebiotic components55 and direct bacterial content.55 In fact, the infant gut microbiota is associated with the maternal breast milk composition, suggesting vertical transmission of early gut colonisers.55

The description of different gut microbiota in cases versus controls does, however, not directly implicate causality. Since most of the above-mentioned studies are of cross-sectional design, it hampers the possibility of determining whether the dysbiotic microbiota existed prior to GDM development or merely occurs as a consequence of the disease. Therefore, studies based on longitudinal prospective cohorts are crucial in order to identify temporal changes in the microbiota prior to GDM manifestation. Furthermore, a longitudinal study design will also make it possible to investigate the effect of GDM on the child’s gut microbiota development. This will provide us with valuable information on metabolic dysfunction and give the basis for identifying new biomarkers and treatment strategies, with the purpose of reducing the risk of different metabolic complications later in life.

Here, we present such a longitudinal prospective study protocol for the establishment of the DANish Maternal and Offspring Microbiome study (DANMOM) cohort. The aim of this study is to identify early structural and functional microbiota changes prior to the development of GDM in the mother and the effect of GDM on the child’s gut microbiota. Furthermore, to identify important maternal, clinical and/or lifestyle factors related to healthy or dysbiotic gut microbiota establishment in children. By elucidating the temporal dynamics and potential causal relationships, we strive to advance our understanding of these interconnected factors and their impact on maternal and offspring health outcomes.

Methods and analysis

Study design

The DANMOM cohort is a longitudinal prospective cohort study that includes mother–child pairs during the prenatal period and up to 5 years after birth.

Setting

The study is conducted at the North Denmark Regional Hospital and Aalborg University Hospital, and recruitment was conducted at both locations. The project is managed by the Centre for Clinical Research at the North Denmark Regional Hospital.

Recruitment

Pregnant women were enrolled after a prenatal ultrasound scan at gestational week 11–14. Before this appointment, all eligible participants received an invitation letter with project information. The study was also advertised with flyers at the hospitals and on social media through the North Denmark Regional Hospital’s webpage, Facebook and LinkedIn profile. If a woman was interested in participating in the study and met the inclusion criteria, the project personnel enrolled the woman. The offspring was enrolled at birth. If the parents did not wish to participate with the newborn, the women could still choose to participate during pregnancy. The recruitment period was from July 2019 to July 2023, and sample and data collection will continue until July 2028.

Study population

In total, 243 pregnant women were initially enrolled in the study, out of which 202 women actively participated in sample and data collection. After giving birth, 110 of these women chose to continue in the study along with their children (n=112). The inclusion criteria for the women were (1) ≥18 years old; (2) able to read and understand Danish; (3) <14 weeks’ gestational age and (4) normal prenatal ultrasound scan at week 11–14. Women were excluded if they (1) had been treated with antibiotics within 3 months before the first sample collection time or if they (2) were diagnosed with pregestational diabetes at index pregnancy before the first sample collection.

Data collection timeline

An overview of the timeline for data and sample collections is shown in figure 1. The study period includes the time from early pregnancy until the child reaches the age of 5 years. During this period, biological samples and data are collected at 11 visits: three during pregnancy and eight after birth. ‘Three time points during pregnancy were chosen to monitor dynamic changes from early to late pregnancy. We did not include participants before week 11, as a normal ultrasound scan was required for inclusion. The mid-pregnancy time point coincided with a routine hospital visit, and the late-pregnancy visit was scheduled as late as possible but before the pregnancy is considered to be term. Postnatal visits were included to track the infant’s microbiota development and stabilization. We chose to collect microbiota samples up to five years after birth from both mother and child to study long-term microbiota dynamics and their potential impact on health outcomes.’

Figure 1 Timeline and data collection in the DANMOM study. Sample and data collection from the mother are marked with a black tick, while sample and data collection from the child are marked with a grey tick. A tick with a star indicates that the sample collection is added to the protocol after study initiation and therefore not collected for all participants. DANMOM, DANish Maternal and Offspring Microbiome; GA, gestational age (weeks); pp, post partum; wks, weeks.

Data collection

Anthropometrics and medical history of the mother before pregnancy

Information on the medical history of the mother is collected from medical records and questionnaires. This includes information on prepregnancy BMI, previous pregnancies, previous birth complications, previous diagnoses (eg, GDM, pre-eclampsia and others), use of medication and family history of diabetes.

Index pregnancy and birth

Clinical information regarding index pregnancy and birth is collected through medical records and pregnancy charts from the mother. This includes age, prepregnancy BMI, gestational weight gain, pregnancy complications (eg, GDM and pre-eclampsia), use of medication, mode of delivery, hours of membrane rupture before delivery and complications during birth. Furthermore, results of biochemical measurements such as oral glucose tolerance test, pregnancy-associated plasma protein A and human chorionic gonadotropin are also collected as part of the Danish prenatal screening programme.

Information on the neonatal period

Information on the neonatal period is collected from medical records and questionnaires. Neonatal information includes date and time of birth, Apgar score (1 min, 5 min and 10 min), gestational age at delivery, skin-to-skin contact after birth, delayed cord clamping, gender, anthropometrical data (weight, length, abdominal circumference and head circumference), neonatal complications and biochemical values (umbilical cord pH and blood glucose). Additionally, it will be recorded when the first meconium was delivered and if the neonate needed any treatment or early feeding after birth. Furthermore, data on neonatal feeding practices will also be collected.

Anthropometrics and medical history of mother and child post partum

Information on the postpartum period for both the mother and child is collected from medical records and questionnaires. This includes information about the use of medication, health status and vaccinations. Furthermore, maternal BMI and the weight and height of the child will also be collected.

Demographics and lifestyle factors for the mother and the child

Information regarding demographics and lifestyle will be collected from questionnaires. Demographic information includes age, living arrangement, family environment and socioeconomic data. Lifestyle information includes the level of physical activity, smoking habits, alcohol consumption (units per week), exposure to animals, travelling and use of probiotics and supplements.

Edinburgh Postnatal Depression Scale

Postnatal maternal depression will be assessed using the Edinburgh Postnatal Depression Scale.56

Dietary habits of the mother

The dietary habits of the mother will be assessed using a 3-day food record at different time points during pregnancy and post partum (see figure 1).

Dietary habits of the infant/child

The dietary habits of the child will be collected through questionnaires at each study visit. This includes information on the intake of breast milk, formula and introduction to different types of solid foods.

Developmental milestones of the child

The mother is asked to register when the child has reached different developmental milestones. The milestones include gross motor skills (sit, stand and walk), fine motor skills (transfer objects from hand=to-hand, eat and draw), language skills (laugh, speak and understand others) and social skills (interact with others).

Sample collection

Biological samples are collected from both mother and child at designated visit times (see figure 1). Faeces, urine, saliva, vaginal fluid and breast milk are collected in sterile containers by the participants at home. The participants have been instructed how to collect the samples to avoid contamination. The samples are stored immediately after sample collection in a domestic freezer (–20°C) and then transferred on ice to the hospital within 3 days after sample collection. Health professionals will take venous fasting blood samples (50 mL) from the mother and a dry blood spot from the child at the hospital. Serum, plasma and whole blood are prepared from the fasting blood samples within 60 min after sample collection. All samples, except the blood spots, are stored at –80°C prior to analysis. The dry blood spots are stored at room temperature in a multi-barrier Pouch with desiccants. Furthermore, the participants are asked to fill out the Bristol stool scale score57 for each stool sample they collect.

Biochemical analysis

Several hormonal and metabolic biomarkers such as insulin, glucagon, oestrogen, progesterone, antiglutamic acid decarboxylase autoantibody, adiponectin, triglycerides, cholesterol and leptin will be investigated from the venous fasting blood samples collected from the women. Furthermore, a panel of inflammatory biomarkers including, but not restricted to, interleukin 6, lipopolysaccharides, tumour necrosis factor alpha and C reactive protein will be analysed. Haemoglobin A1c and fasting plasma glucose will be measured within a few hours after the collection of blood samples.

DNA extraction and 16S rRNA gene amplicon sequencing

Bacterial DNA will be extracted from all biological samples. This will be done using commercial kits. The purified DNA will be amplified using primers targeting hypervariable regions of the 16S rRNA gene. Sequencing will be performed using Oxford nanopore sequencing. Additional metagenomics sequencing will furthermore be conducted for higher taxonomic resolution. Negative controls such as environment controls and reagents controls will be analysed together with the biological samples to detect and control for environmental bias.

Data management

All participants will receive a unique study identification number. All the collected data will be stored and managed using the Research Electronic Data Capture (REDCap) tool hosted at the North Denmark Regional Hospital.58 59 REDCap is a secure web-based software platform designed to support data capture for research studies.

Primary and secondary outcomes

Primary objectives and outcomes:

To characterise whether and when the microbiota differs in pregnant women who experience GDM compared with women with normal pregnancies.

To investigate the effect of maternal GDM on the gut microbiota development in the infant.

Secondary objectives and outcomes:

To identify prenatal and postnatal factors that influence the development of the child’s gut microbiota.

To characterise the temporal changes in gut microbiota in the prenatal and perinatal period and up to 5 years post partum in mother–child pairs.

To identify the associations between the child’s gut microbiota composition with a focus on well-being, allergy and infection rates.

Sample size calculation

The determination of sample size for this study was based on our primary outcomes, which focused on investigating the role of gut microbiota in the development of GDM and evaluating the impact of GDM on the gut microbiota of children. Previous case-control studies examining the association between GDM and gut microbiota have successfully identified significant differences in microbiota composition between cases and controls, with sample sizes ranging from 11 to 50 women with GDM. Additionally, Su et al 2018 showed a difference in gut microbiota in children of women with and without GDM with a sample size of 20 children exposed to GDM. The prevalence of GDM (based on international criteria) was expected to be around 23%.25 We therefore aimed to include a minimum of 200 women and 100 children in our study.

Statistical analysis and data interpretation

Overall, data processing and data analysis will be conducted using R (a free software environment for statistical computing and graphics)60 and QIIME2 (a microbiome multi-omics bioinformatics and data science platform).61 General characteristics and clinical variables for the women (eg, age, prepregnancy BMI and weight) will be compared at inclusion to identify statistically significant differences between women with and without pregnancy complications. This will be done using Student’s t-test for continuous variables of normal distribution, Wilcoxon signed-rank test for continuous variables of non-parametric distribution and χ2 test for categorical variables.

To investigate the differences in bacterial composition between women with and without GDM, alpha diversity and beta diversity will be compared. Cross-sectional differences in microbiota composition between women with and without GDM will be assessed both before and after the development of GDM and at multiple time points during and after pregnancy. Various statistical analyses, such as Analysis of Compositions of Microbiomes with Bias Correction 2, Principal Coordinates Analysis and permutational multivariate analysis of variance, will be employed. The analyses will be adjusted for potential covariates. The cross-sectional differences between the offspring will be analysed from the time of birth (first meconium sample) to 5 years after birth by using the same analyses as for the women. Furthermore, we will compare the bacterial composition in mother–child dyads to investigate the bacterial transfer from mother to child.

Furthermore, the longitudinal microbiota data collected at multiple time points during pregnancy and post partum will be analysed to investigate temporal patterns and dynamic changes in the relative abundance of individual bacterial taxa and various diversity indices. Linear mixed-effects models will be used to test whether the relative abundance of specific taxa and diversity indices are associated with time (weeks, months and years) and clinical characteristics, such as GDM diagnosis, BMI and age.

Patient and public involvement

None.

Ethics and dissemination

This study is performed in accordance with the Declaration of Helsinki and has been approved by the North Denmark Region Committee on Health Research Ethics (N20190007). Written informed consent is obtained from all participants prior to study participation. Study results will be published in international peer-reviewed journals and presented at international conferences. The results will also be presented to the funders of the study and study participants.

Discussion

Here, we present the DANMOM mother–child cohort study designed to capture the temporal changes in gut microbiota composition during pregnancy and through early life. The nature of gut microbiota establishment is quite complex, and several factors may influence this. Our study design aims at addressing as many of these factors, at the highest resolution, as possible during the study period.

The longitudinal design offers a unique opportunity to investigate the temporal relationship between gut dysbiosis and GDM. This approach allows us to determine whether dysbiosis occurs before or after the GDM development, elucidating its potential involvement in disease progression. Furthermore, it will also be possible to identify specific patterns or alterations in the gut microbiota that are associated with GDM, which could serve as potential biomarkers or therapeutic targets for preventing and managing GDM. Additionally, the study focuses on investigating the transfer of bacteria from mother to child during birth and in early life. This aspect provides a unique opportunity to examine how maternal health influences the composition of the infant’s gut microbiota and subsequent health outcomes. Understanding the role of maternal microbiota in the colonisation and establishment of the infant’s gut could be used in the development of interventions aimed at reducing the risk of metabolic disorders and other adverse health outcomes in offspring. The long follow-up period of the DANMOM study is crucial as it enables the collection of data on childhood diseases and assesses whether the postpartum maternal microbiota in women with GDM resembles that in women without GDM. This allows us to explore the associations between maternal health and infant gut microbiota development. These findings can provide valuable insights for the development of preventive measures and early interventions that may mitigate the long-term health impacts associated with GDM.

Several compromises have, however, been made leading to some limitations. First, the logistics of collecting longitudinal data is very resource-demanding, thereby limiting sample size. This is problematic when aiming to investigate subpopulations, for example, women who develop complications during pregnancy or other diagnoses in mother and child such as diabetes, asthma, allergies, obesity and psychiatric disorders. On the other hand, we provide the opportunity to show a very detailed picture of which microbiota changes may occur prior to disease onset. Information that is not available from the more commonly performed case-control microbiota studies. Second, due to the high number of study visits and data collections, it may be difficult to retain participants in the study. We have recruited 243 pregnant women and the drop-out rate before collecting any samples is around 17%. Approximately 54% of the participating families chose to participate in the follow-up for mother and child after birth. Drop-out numbers have, however, been influenced by the COVID-19 pandemic as some of the participants dropped out due to fear of contracting COVID-19 during study visits, state restrictions and lock-down periods. The Danish population has, however, now a very high COVID-19 vaccination coverage,62 alleviating some of the obstacles and we, therefore, expect higher adherence rates for the remainder of the study. Another limitation of this study is that the exact time between birth and the initiation of skin-to-skin contact between the child and the parents is not documented. Any delay in this contact could potentially impact the colonisation of the child’s gut microbiota. Finally, several of the data points, including descriptions of periods of illness, use of nutritional supplements, developmental milestones for the child, introduction of food types for the infants, etc, rely on self-reporting and interviews and are therefore prone to recall bias. In order to minimise this, we offer fill-out booklets to the parents, in which they can report the different data along with the study period.

The DANMOM cohort study has several strengths. Compared with many other ongoing and existing mother–child cohorts, including Nutrition during Pregnancy and Early Development cohort study (NuPED),63 Alimentazione MAmma e bambino nei primi MIlle giorni project (A.MA.MI.),64 MAternal MIcrobes study (MAMI),65 the Antibiotic-induced Disruption of the Maternal and Infant Microbiota and Adverse Health outcome study (ABERRANT)66 and Microbiome Understanding in Maternity Study (MUMS),67 we follow our participants from early pregnancy and with a longer follow-up period (5 years vs up to 2 years), allowing for more data on childhood disease and the normalisation of maternal microbiota after pregnancy. Furthermore, Danish health data registries are unique and of very high quality,68 giving the opportunity to make solid associations between microbiota data and health factors. Finally, our study is based on the involvement of staff from various disciplines, for example, nurses, medical doctors, sonographers, midwives and scientists. This multidisciplinary collaboration has optimised the participant recruitment, sample integrity and data collection.

In conclusion, the DANMOM study will contribute to our understanding of gut microbiota dynamics during pregnancy and early life, and its implications for maternal and child health. By investigating the relationship between gut microbiota and pregnancy complications such as GDM, as well as their impact on health outcomes, this study will provide valuable insights into the field. The longitudinal design of the study provides a unique opportunity to identify early changes in the microbiota prior to disease development in both mothers and children, potentially serving as valuable early biomarkers of disease. Moreover, this design allows for a detailed examination of bacterial transfer from mother to child, enabling the identification of essential factors for the colonisation of the infant’s gut.

Acknowledgements

We would like to thank the families participating in the DANMOM study for their contribution to the project. Furthermore, we would like to thank the Department of Gynaecology and Obstetrics and the Department of Clinical Biochemistry from the North Denmark Regional Hospital who contribute to participant recruitment, sample collection and data analysis.

Review Process File
05 09 2024

Funding: This study was supported by the Steno Diabetes Center North Denmark (no grant number), Niels Jensen’s Foundation (no grant number) and Marie Pedersen og Jensine Heiberg’s Foundation (no grant number). The centre is neither involved in study design, sample collection, analysis and interpretation of data nor in preparation of the manuscript.

Prepublication history for this paper is available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2023-083358).

Patient consent for publication: Not applicable.

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient and public involvement: Patients and/or the public were not involved in the design, conduct, reporting or dissemination plans of this research.
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