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The gut microbiome seems to play a role in migraines through increasing intestinal epithelial permeability and pro-inflammatory processes. The associations between the gut microbiome and migraines are uncertain in children.
Aim
The purpose of this quantitative study was to examine the associations between the gut microbiome and migraines in children aged 7-18 years from the American Gut Project (AGP).
Method
A cohort of children aged 7-18 years from the AGP was analyzed. 16S rRNA V4 gene sequences for the gut microbiome, migraines, and demographics were obtained from the AGP Public Repository. After quality control of 16S rRNA gene sequences, α-diversity (Shannon, Faith's_PD, and evenness) and β-diversity metrics (Bray-Curtis and weighted-UniFrac distances), taxonomy, and abundance analyses were implemented using QIIME 2.
Results
In total, 381 children (341 without migraines; 40 with professional or self-diagnosed migraines) were analyzed with a mean age of 11.5 years. Compared with those without migraines, children with migraines showed lower estimates in Shannon and Faith's_PD (p < .01). Both Bray-Curtis and weighted-UniFrac distances displayed the gut microbial dissimilarities between these two groups (p = .001). Children with migraines had higher abundances in genus of phylum Bacteroidetes (Bacteroides, Parabacteroides, Odoribacter), Actinobacteria (Eggerthella, Varibaculum), Firmicutes (SMB53, Lachnospira, Dorea, Veillonella, Anaerotruncus, Butyricicoccus, Coprobacillus, Eubacterium), and Proteobacteria (Sutterella) than children without migraines.
Conclusions
Associations of the gut microbiome diversity and abundances with migraines in children indicated potential biological mechanisms of migraines. Future work needs to confirm our findings in children.
Migraines are frequently reported in children and adolescents. Migraines exhibit in various forms in children and adolescents based on age and have an estimated overall prevalence of 10% in children and adolescents worldwide (
). As a multifactorial health condition, the risk factors of migraines include familial history, environmental factors, and gastrointestinal (GI) disorders (
). An inappropriate management of the severe health effects of migraines can adversely impact childhood school performance, such as more school absences and missing extracurricular activities, leading to potential mental and physical health complications in adulthood (
Generally, pediatric migraines clinically manifest in various ways and are usually age-dependent. Infants under the age of one may experience and show migraine discomfort by “head banging” episodes, whereas toddlers may appear more sickly, experiencing bouts of vomiting and abdominal pain. As children get older, migraines tend to last longer and have more intense symptoms, such as lethargy, phonophobia, swollen nasal passages, dehydration, edema, or diarrhea (
). Compared with the adult population, children with migraines experience a wide range of GI symptoms, including abdominal pain, nausea, vomiting, diarrhea, and constipation (
). After the headache phase subsides, children may experience an altered physical state, such as elation and pronounced energy, or lethargy and exhaustion (
). In addition, migraines are often associated with psychiatric and neurologic conditions (e.g., depression, anxiety, and seizures) as well as sleep disturbance (
How stress, discrimination, acculturation and the gut microbiome affect depression, anxiety and sleep among Chinese and Korean immigrants in the USA: a cross-sectional pilot study protocol.
). These associations of migraines with GI symptoms and psychoneurologic conditions in children suggest that the gut microbiome might play a critical role in migraines via the microbiome-gut-brain axis (
). Numerous advances have been made to describe the critical role of the gut microbiome (i.e., a collection of all genomes of microbes in the GI tract) in human health and disease (
). Dysbiosis (i.e., the biological diversity, abundance of bacterial taxa, or combinations of both components) of the gut microbiome can increase human disease susceptibility and impact many aspects of health, including migraine development (
). Since the microbiome is such an integral part of the body, it is important to understand their effects on human health to elucidate potential targets of treatment and other medical interventions.
Recent discoveries further highlight the microbiome-gut-brain axis. Specifically, migraines were found correlated with increased levels of nitrate, which is commonly consumed as a food additive or in nitrate-containing medication (
). Higher levels of nitrate, nitrite, and nitric oxide reductase genes in the oral and gut microbiome were reported in those who experienced migraines than those who did not, alluding to a potential symbiotic relationship between the gut microbiome and migraines (
). Furthermore, there were increased concentrations of bacteria associated with negative health effects (e.g., irritable bowel disease, inflammation, and bacteremia) while there were increased concentrations of healthy gut microbes in healthy adults (
). According to the microbiome-gut-brain axis, biologic pathways through which the gut microbiome influences the migraines include: altering gut microbiome composition and the functional metabolome of the gut microbiome; upsetting the balance of “beneficial” and “detrimental” bacteria in the lumen; and activating neuro-immune signaling pathways (
Composition of gut microbiota and its association with body mass index and lifestyle factors in a cohort of 7-18 years old children from the American Gut Project.
). A previous study observed a greater microbial diversity and abundance of probiotic Coprococcus, Lachnospira, Faecalibacterium genera in participants who had higher levels of physical activities and diet containing more fruits and vegetables (
). Consistent with these findings, a lower α-diversity, such as an increased proportion of pathogenic bacteria (e.g., Escherichia coli and Bacteroides fragilis), is often associated with negative health outcomes, such as inflammatory bowel diseases, autism, and obesity (
has indicated that dysbiotic gut microbiome contributes to migraines due to upregulation of tumor necrosis factor (TNF)-α, resulting in pain from inflammation (
). Although dysbiosis of the gut microbiome is associated with migraines, exact mechanisms of the gut microbiome involvement in migraines need to be further characterized in children (
The biologic mechanism of how the gut microbiome impacts the onset of migraines or how migraines can potentially be caused by gut dysbiosis has yet to be elucidated. While there have been studies on the association between migraines and the gut microbiome, only the adult demographic has been researched, despite migraines afflicting 10% of children worldwide. Thus, studying the gut microbiome and its association with migraines in children could help design targeted interventions (e.g., probiotics) (
The effects of a multispecies probiotic supplement on inflammatory markers and episodic and chronic migraine characteristics: A randomized double-blind controlled trial.
) in preventing and alleviating the migraines. This quantitative study examines the associations between the gut microbiome and migraines in a cohort of children aged 7-18 years from the American Gut Project (AGP) (
A secondary data analysis of the American Gut Project (AGP) cohort (children aged 7-18 years) was conducted.
Data Source
The AGP is a national initiative to identify factors associated with the diversity and abundance of the gut microbiome. The AGP dataset consists of over 15,000 samples from 11,336 subjects, collected primarily from the United States, United Kingdom, and Australia (
). Following the Illumina MiSeq 515f-806r amplification protocol, 16S rRNA V4 gene region was sequenced by AGP scientists and all de-identified AGP data were then deposited into the European Bioinformatics Institute (EBI) sequence repository. The V4 region of most bacterial 16S rRNA is commonly used for taxonomic assignments, as previous studies have demonstrated the accuracy of utilizing short, hypervariable sequences for microbial identification (
). In this study, 16S rRNA single-end sequencing data (∼150bp reads) per sample and relevant metadata were obtained from the EBI repository and subsequently analyzed using Quantitative Insight Into Microbial Ecology 2 (QIIME 2) (
). The AGP indicates that all data are openly and freely released into public databases for use except information that needs to be kept confidential for privacy reasons. All the data we obtained were de-identified for further analysis.
Sample
A total of 15,279 samples (the gut microbiome) and 174 phenotypic variables (metadata, such as age, gender, and migraines) were assembled in the AGP dataset. Eligible samples were extracted from the EBI repository following the inclusion criteria: (1) were children aged 7-18 years; (2) had gut microbiota data (16S rRNA V4 gene sequences); and (3) had no chronic illness such as irritable bowel syndrome, cancer, and diabetes. Duplicate samples were excluded, resulting in 411 samples eligible for analysis in QIIME 2. The gut microbiome data of this cohort of children were published to understand associations of the gut microbiome with body mass index (BMI) and lifestyle factors (i.e., dietary status and physical activity) (
Composition of gut microbiota and its association with body mass index and lifestyle factors in a cohort of 7-18 years old children from the American Gut Project.
Each child provided responses on a self-reported questionnaire about their type of migraine. The responses included: no migraine, self-diagnosed migraine, or physician (professional)-diagnosed migraine.
Gut microbiome
Stool specimens were collected for gut microbiome analysis as part of the AGP initiative. Following the standard data collection protocol from the Human Microbiome Project (
), eligible participants who agreed to participate in the AGP registered detailed personal information online. After receiving the gut microbiome data collection kits, each participant placed the gut microbial collection tube in a built-in tube holder. Then, the participant opened the sampling swabs and collected the stool specimens via swabs. After the sample collection, the sample swabs were placed into the collection tube with the preservation solution. The collection tubes were inserted into the safety bag, sealed, and shipped to a lab ideally within 48 hours of collection.
Demographic variables
Participants’ demographic data included age, sex (male or female), race (Black, White, or others), and BMI. Age of children was stratified into child (7-12 years) vs. teen (13-18 years), considering the general age of pubertal development which may play a role in the gut microbiota. The stratified age groups are comparable with previous literature (
Composition of gut microbiota and its association with body mass index and lifestyle factors in a cohort of 7-18 years old children from the American Gut Project.
). Age and BMI were used as continuous and categorical variables. Based on Centers for Disease Control and Prevention (CDC) guidelines, BMI percentile levels were defined as underweight (<5th percentile), normal (5th to <85th percentile); overweight (85th to <95th percentile), and obese (>95th percentile). Clinical variables extracted from the AGP dataset included use of antibiotics and probiotics.
Ethical Consideration
The AGP dataset were reviewed by University of California San Diego's Institutional Review Board to ensure the research was in accordance with ethical guidelines and Health Insurance Portability and Accountability Act (HIPAA) compliance. All the collected samples were de-identified to protect the privacy of participants. IRB approval is not applicable for this secondary analysis.
Bioinformatics Preprocessing
QIIME 2 was used to process 16S rRNA V4 gene sequences to obtain the diversity, taxonomy, and abundance of the gut microbiome. All 16S rRNA gene sequences from the AGP were obtained from the EBI repository and demultiplexed. Therefore, sequence quality control was directly implemented using dada2, a package for modeling and correcting Illumina-sequenced amplicon errors as little as one nucleotide (or called amplicon sequence variants [ASV]) (
). The obtained sequencing data were trimmed at 115 bp based on a Phred score of 33 (99.95% accuracy). Bacterial taxonomic analyses were conducted based on the trained classifiers of Greengenes 13_8 99% operational taxonomic units (OTUs, taxonomic assignment based on a 99% OTU similarity).
Statistical Analysis
All the analyses were performed using QIIME 2. Following the rarefaction curve analysis via default median feature frequencies (25,000 in our sample), 16S rRNA gene sequences with ≥3,000 feature frequencies were adequate for microbial diversity and abundance analysis, resulting in a sample size of 395 children (16 samples with <3000 frequencies removed). After removing 14 samples without migraine variables, 381 children were analyzed, combining self- and physician-diagnosed migraine categories into one group. No significant differences were found between samples with missing values and samples for the final analysis in age, sex, and race.
Diversity analysis can assess both within-sample diversity (α-diversity) and between-sample diversity (β-diversity). The α-diversity was calculated using standard parameters: Shannon's index, Faith's phylogenetic diversity (Faith's_PD), and evenness (Pielou_e). The Spearman correlational analysis was used to analyze associations between α-diversity parameters and continuous variables such as age. The Kruskal-Wallis (pairwise) test was used to analyze α-diversity estimates associated with categorical variables (race and BMI) and the outcome variable (migraines). Bray-Curtis and weighted UniFrac distance metrics, and principal coordinates analysis (PCoA) were used to analyze and visualize patterns of β-diversity. The 2-dimensional PCoA was performed by the emperor tool (
The abundance analysis discriminates differentially abundant taxa based on variables of interest such as migraines. Pairwise permutational multivariate analysis of variance (permANOVA) (
) was used to analyze associations between migraine and the abundance of the gut microbiome. This test compares abundances of genera to determine if they change significantly between populations or environments. According to ANCOM requirements, we filtered out the taxa that only appear in one sample and taxa counts <10 across all samples. W value was computed for the statistical analysis, in which high W values indicate significant differences in abundance levels between study groups. The higher the W value, the more significant the differences in abundance levels between group.
Results
Subject Characteristics
Of the 381 (5 with self-diagnosed migraines, 35 with professional diagnosis, and 341 without migraines) children included in this study, there was a mean age of 11.5 years (SD = 3.8) and 66.7% were boys. The rate of migraines, self- and physician-diagnosed, was 10.5% (1.3% and 9.2%, respectively) in this cohort. Our sample was predominantly White (85.8%). The majority (62.9%) fell within the normal BMI level, and about one third of the children were either at underweight (21.0%) or overweight and obese (16.1%) levels. The majority of children with migraines were White (p = .04), boys (p = .01), young child (p = .002), and underweight (p < .001).
Taxonomic Analysis
Using the trained classifier of Greengenes, all bacterial features (ASV) from 381 fecal specimens represented 28 bacterial phyla and 455 bacterial genera. The top dominant bacterial phyla included Firmicutes (41.3%), Bacteroidetes (31.3%), Proteobacteria (21%), Actinobacteria (2.5%), and Verrucomicrobia (1.8%) and the dominant bacterial genera were Bacteroides (22.8%), unidentified family Enterobacteriaceae (16.4%), Faecalibacterium (7.8%), Roseburia (4.6%), and Ruminococcus (2.7%). Figure 1 describes the relative abundances of phyla (1A) and genera (1B) according to type of the migraine diagnosis (medical professional diagnosis, self-diagnosis, or no migraine).
Figure 1Taxonomic analysis of the gut microbiome based on types of migraine diagnosis. (A) Presents the gut microbiome phyla among children without migraines (n = 341), with physician (professional)-diagnosed (n = 35) migraines, or self-diagnosed migraines (n = 5). (B) Presents the gut microbiome genera (top 30 genera) phyla among children without migraines (n = 341), with physician (professional)-diagnosed (n = 35) migraines, or self-diagnosed migraines (n = 5).
The α-diversity estimates (Shannon, Faith's_PD, and Pielou's_e) were not associated with age and BMI (continuous variables) and sex. White children showed higher estimate in Shannon index (p = .02) than others. Types of migraine diagnosis were associated with α-diversity estimates (Table 1). Children without migraines showed higher Faith's_PD (p < .001) and Shannon index (p = .037) than children with medical professional diagnosis of migraines. Children without migraines showed higher Faith's_PD (p = .002), Shannon index (p = .006), and Pielou's_e (p = .024) than children with self-diagnosis of migraines. Children with medical professional diagnosed migraines showed higher Faith's_PD (p = .013), Shannon index (p = .026), and Pielou's_e (p = .035) than children with self-diagnosed migraines.
Table 1Differences of α-Diversity based on Types of Migraine Diagnosis.
Professional Diagnosis (n = 35) vs. No Migraine (n = 341)
Professional Diagnosis (n = 35) vs. Self-Diagnosis (n = 5)
PCoA plot visualized the gut microbial dissimilarities (β-diversity) between children with migraines and without migraines based on the Bray-Curtis (Fig. 2A) and weighted UniFrac (Fig. 2B) distances. PermANOVA analyses showed that children with medical professional diagnosed migraines showed significantly different gut microbiome compared with from those without migraines (p = .001 for both β-diversity metrics) and those with self-diagnosed migraines (p = .001 for Bray-Curtis distance; p = .003 for weighed UniFrac distance) (Table 2).
Figure 2The β-diversity of the gut microbiome based on types of migraine diagnosis. (A) Presents the gut microbiome dissimilarities phyla among children without migraines (n = 341), with physician (professional)-diagnosed (n = 35) migraines, or self-diagnosed migraines (n = 5) using Bray-Curtis distance parameter. (B) Presents the gut microbiome dissimilarities phyla among children without migraines (n = 341), with physician (professional)-diagnosed (n = 35) migraines, or self-diagnosed migraines (n = 5) using weighed UniFrac distance parameter.
Weighted UniFrac distance is a quantitative measure of community dissimilarity that incorporates phylogenetic relationships between the features. Bolded data present significant findings with p < .05.
pseudo-F = 20.22
pseudo-F = 1.70
pseudo-F = 8.63
p = .001
p = .149
p = .003
a Bray-Curtis distance means a quantitative measure of community dissimilarity.
b Weighted UniFrac distance is a quantitative measure of community dissimilarity that incorporates phylogenetic relationships between the features.Bolded data present significant findings with p < .05.
ANCOM was used to identify taxa associated with migraines (Table 3). Children with migraines had higher abundances in the following phyla compared with children without migraines: phylum Bacteroidetes driven genera, including Bacteroides, Parabacteroides, and Odoribacter; phylum Actinobacteria driven genera, including Eggerthella and Varibaculum; phylum Firmicutes driven genera, including SMB53, Lachnospira, Dorea, Veillonella, Anaerotruncus, Butyricicoccus, Coprobacillus, unidentified family Lachnospiraceae, unidentified family Erysipelotrichaceae, and Eubacterium; and phylum Proteobacteria driven genus Sutterella.
Table 3Abundance Analysis of Gut Microbial Features based on Types of Migraine Diagnosis.
Children without migraines had higher abundances in phylum Firmicutes driven genera, including unidentified families Christensenellaceae, Lachnospiraceae, and Ruminococcaceae, Anaerostipes, and Oribacterium.
Discussion
The rate of migraines was 10.5% among children from the AGP cohort. We found that children with migraines had an overall lower diversity in the gut microbiome (
) compared with those without migraines. The AGP data provide a large and representative sample to explore the associations between the gut microbiome and migraines. However, interpretations of these findings should be cautious due to analysis of 16S rRNA sequences, which could not examine specific species or strains associated with migraines in this study.
Dysbiosis of the gut microbiome can be attributed to a variety of factors, such as genetics, use of medications (e.g., antibiotics), diet, and disease status (
Composition of gut microbiota and its association with body mass index and lifestyle factors in a cohort of 7-18 years old children from the American Gut Project.
). This study examined the associations of the gut microbiome with migraines (assessed as no migraine, self-diagnosed, or medical professional-diagnosed migraines) in children. Children with migraines showed a lower α-diversity (microbial richness assessed by Shannon and Faith's_PD indices; and evenness assessed by Pielou's_e). Meanwhile, we observed enriched Actinobacteria, Firmicutes, and Proteobacteria phyla in children with migraines. These findings were consistent with previous observations on migraines in elderly women, including a lower gut microbial diversity and concurrent increases in harmful bacteria, including those in the Firmicutes phylum (
). Additionally, a meta-analysis on the relationship between Helicobacter (H.) pylori (from the phylum Proteobacteria) and migraines elucidated that H. pylori infection was significantly greater in migraineurs than in the control groups (
Migraines in children may have a similar gut microbial dysbiosis-induced cause as reported in adult population, including shifts in the gut microbial diversity as well as in the relative abundance of probiotic versus pathogenic bacteria. We found that children without migraines showed a higher α-diversity. A higher diversity of the gut microbiome is contributed to healthier lifestyles and better disease outcomes (
Composition of gut microbiota and its association with body mass index and lifestyle factors in a cohort of 7-18 years old children from the American Gut Project.
found that those who had higher levels of physical activities and healthier diet, which was measured by amount of fruits and vegetables consumed, were associated with a higher microbial diversity (
). Consistent with these findings, a lower α-diversity is often associated with negative health outcomes, such as inflammatory bowel diseases, autism, and obesity (
). Therefore, our findings seemed to reflect previous work regarding changes of the gut microbial diversity and its contribution to migraines.
Our study found an increase in Eggerthella among those with physician-diagnosed migraines compared to non-migraineurs. Eggerthella is a Gram-positive, non-sporulating bacterial genus of Actinomycetota that is anaerobic and commonly isolated in the GI tract (
). This bacterial genus has been linked to clinically significant bacteremia and underlying GI diseases, suggesting a high level of pathogenicity, although its mechanisms have yet to be defined (
). Similarly, a meta-analysis has elucidated those elevated levels of Eggerthella are linked to mental disorders, such as depression, bipolar disorder, and schizophrenia (
This study reported elevated levels of Varibaculum, Veillonellaceae, Bacteridaceae, Anaerotruncus, Sutterella, and Erysipelotrichaceae in migraineurs compared with controls. Most Varibaculum isolates reduce nitrate to nitrite in respiratory denitrification (
). Especially with an increase of nitrates in the Western diet, overproduction of nitrites from endogenous processes can be harmful. Previous studies have observed an association between increase in nitrate production and inflammatory disease and inhibition of other bacterial species, resulting in decreased α-diversity (
). Leclerc et al.’s study also observed a dose-dependent impact of NO, such as an inhibition of Ruminococcaceae and increased Veillonellaceae and Bacteridaceae, consistent with our findings. Similarly, Veillonella, another nitrate-producing bacterium, was more abundant in patients with inflammatory diseases (
elucidated an increase in INF-γ with a higher abundance of certain Dorea species. Anaerotruncus is found to be positively associated with bloating and abdominal pain (
), while Sutterella is found to have mild pro-inflammatory properties, such as inducing TNF-α and a dose-dependent interleukin (IL)-8 response in the GI tract (
). Erysipelotrichaceae family is often found enriched in inflammation-related outcomes such as colorectal cancer, Crohn's disease-like disorder, and obesity (
). Therefore, dysbiosis of the gut microbiome may contribute to migraines via different biological mechanisms, particularly inflammation.
Our study also elucidated certain gut microbes that may protect children from migraines (e.g., probiotics). The protective mechanism of probiotics has been linked to butyrate production. Butyrate plays a vital role in maintaining the intestinal mucosal lining and has anti-inflammatory properties via inhibition of regulatory proteins involved in the early immune inflammatory response (
). Negative health outcomes are commonly associated with a decrease in Ruminococcaceae, including Crohn's disease and high NO concentrations from an abundance of denitrifying bacteria (
). The protective mechanism of Ruminococcaceae may be attributed to its prebiotic functions, such as butyrate production and starch fermentation abilities in the GI tract, promoting the growth of other beneficial bacteria (
). Christensenellaceae family is found to be inversely related to host BMI and visceral fat mass, contributing to disorders such as obesity and inflammatory diseases (
IL23R-protective coding variant promotes beneficial bacteria and diversity in the ileal microbiome in healthy individuals without inflammatory bowel disease.
). Thus, there is compelling evidence to support Christensenellaceae's beneficial effect on host health, although its protective mechanisms have yet to be fully characterized. Additionally,
). As it is uniquely able to metabolize sugars, lactate, and acetate into butyrate, this genus is also one of the most abundant taxa of the healthy core gut microbiome (
). All these findings provide innovative evidence to potentially target to relieve migraines among children, which need to be further corroborated in a more diverse population.
Limitations
This study has several limitations. Participants in the AGP were overwhelmingly White (85%) and thus, interpretation of our findings should be cautious as it does not represent minoritized populations. Some migraines were self-diagnosed, without a formal definition utilized in the questionnaire. Additionally, this study was a cross-sectional analysis of the gut microbiome data, which are unable to elucidate the long-term effects of the gut microbiome or temporality between microbiome changes and the onset of pediatric migraines. Moreover, we did not report the impact of any other variables, such as antibiotics and probiotics on the gut microbiome, which has been reported in previous work (
Composition of gut microbiota and its association with body mass index and lifestyle factors in a cohort of 7-18 years old children from the American Gut Project.
This study found that 10.5% of children from the AGP cohort were reported as medical professional diagnosed or self-diagnosed migraines. Children with migraines had a lower diversity and higher abundances of inflammatory-related bacteria, such as Eggerthella, Sutterella, and Eubacterium. Associations between gut microbiome diversity and abundances and migraines in children suggested potential biologic mechanisms of migraines. Future work is required to examine these relationships.
Clinical Implications
Findings of this study emphasized the impact of the gut microbiome on migraines among children aged 7-18 years old, which has significant implications for nursing practice and nursing science. As the first study in children, our consistent findings with previous work in adults and other populations support the potential target to decrease the impact of migraines in children via improving gut health (e.g, the gut microbiome). Nurses play a critical role in health education and advocation for healthy lifestyles. With the identification of specific microbial taxa associated with migraines, nurses could educate children with migraines on building a healthy gut microbiome, such as eating healthy and promoting physical activities (
). These lifestyle interventions can assist in decreasing the negative impact of migraines on daily activities, school performance, and even quality of life. Additionally, nurses, through working with parents or caregivers of children, can build and implement specific gut health programs (e.g., appropriate consumption of fiber per day, adhering to a low glycemic index diet, supplementation with vitamin D, omega-3, and probiotics) to help prevent migraines. Due to the prevalence of obesity in children, weight loss dietary plans should be considered for children with overweight and obese status. For nursing scientists, as biologic mechanisms between the gut microbiome and migraines have not been clearly characterized, more work is needed to examine composition and functional capabilities of the gut microbiome that contribute to the development and severity of migraines in children.
Declaration of Competing Interest
No conflict of interest was declared.
Acknowledgments
We would like to thank all the participants in the AGP. The first author is supported by funding from National Institute of Health/National Institute of Nursing Research (1K99NR017897-01 and 4R00NR017897-03).
References
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Graham C.
Prevalence of headache and migraine in children and adolescents: a systematic review of population-based studies.
Devolpmental Medicine and Child Neurology.2010; 52: 1088-1097
Composition of gut microbiota and its association with body mass index and lifestyle factors in a cohort of 7-18 years old children from the American Gut Project.
How stress, discrimination, acculturation and the gut microbiome affect depression, anxiety and sleep among Chinese and Korean immigrants in the USA: a cross-sectional pilot study protocol.
The effects of a multispecies probiotic supplement on inflammatory markers and episodic and chronic migraine characteristics: A randomized double-blind controlled trial.
IL23R-protective coding variant promotes beneficial bacteria and diversity in the ileal microbiome in healthy individuals without inflammatory bowel disease.
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