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Research Article | Clinical Science and Epidemiology

Gut Microbiota in the First 2 Years of Life and the Association with Body Mass Index at Age 12 in a Norwegian Birth Cohort

Maggie A. Stanislawski, Dana Dabelea, Brandie D. Wagner, Nina Iszatt, Cecilie Dahl, Marci K. Sontag, Rob Knight, Catherine A. Lozupone, Merete Eggesbø
Melinda M. Pettigrew, Editor
Maggie A. Stanislawski
Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado, USA
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Dana Dabelea
Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado, USADepartment of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado, USA
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Brandie D. Wagner
Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, USA
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Nina Iszatt
Department of Environmental Exposure and Epidemiology, Norwegian Institute of Public Health, Oslo, Norway
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Cecilie Dahl
Department of Community Medicine and Global Health, University of Oslo, Oslo, Norway
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Marci K. Sontag
Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado, USACenter for Public Health Innovation, CI International
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Rob Knight
Department of Pediatrics, University of California San Diego, La Jolla, California, USADepartment of Computer Science and Engineering, University of California San Diego, La Jolla, California, USACenter for Microbiome Innovation, University of California San Diego, La Jolla, California, USA
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Catherine A. Lozupone
Department of Biomedical Informatics and Personalized Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA
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Merete Eggesbø
Department of Environmental Exposure and Epidemiology, Norwegian Institute of Public Health, Oslo, Norway
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Melinda M. Pettigrew
Yale School of Public Health
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DOI: 10.1128/mBio.01751-18
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  • FIG 1
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    FIG 1

    Evaluation of the association between the gut microbiota taxonomic composition at 6 time points in early life with BMI z-score at age 12. This plot shows the estimated P values from unadjusted (circles) and adjusted (squares) Microbiome Regression-Based Kernel Association Tests of the unweighted (coral) and weighted (blue) UniFrac distance matrices and BMI z-scores at age 12. These UniFrac measures capture qualitative and quantitative differences in phylogeny, respectively. Dashed lines show P = 0.05 (black) and P = 0.1 (gray). Adjusted models controlled for breastfeeding, delivery mode, antibiotic exposures, gestational age at birth, and twin status.

  • FIG 2
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    FIG 2

    Amount of variation in BMI z-score at age 12 explained by the infant gut microbiota at each sampling time. This plot shows the estimated R2 values with 95% confidence intervals from the repeated cross-validation of the random forests to predict childhood BMI z-scores based on infant gut microbiota characteristics at each sampling time, both unadjusted and adjusted for confounding factors (breastfeeding, delivery mode, antibiotic exposures, gestational age at birth, and twin status).

  • FIG 3
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    FIG 3

    The infant gut microbiota taxa and alpha diversity measures at each sampling time that were most highly predictive of BMI z-score at age 12. Infant gut microbiota taxa and diversity measures (OTUs listed with OTU, phylum, and most specific level of known taxonomic classification) over the first 2 years of life that were selected as most predictive of childhood BMI z-score in random forests at six points (grouped vertically). We used linear regressions in order to assess the direction of association between these features at each sampling time with BMI z-score at age 12, controlling for confounding factors (breastfeeding, delivery mode, antibiotic exposures, gestational age at birth, and twin status). While a feature may have been selected as predictive of BMI only at a certain sampling time, we plotted the linear associations at all times (horizontal axis) in order to assess the temporal consistency of the association. Since the assumptions underlying random forests and linear regressions are very different, we would not expect important features to necessarily be significant in regressions. The colors represent the regression coefficients for each feature: red indicates a positive relationship between the feature and childhood BMI, e.g., higher abundance corresponds with higher BMI; green indicates negative relationships; gray indicates that the regression model failed to converge (NA). The column labeled “maternal taxa” shows whether these gut microbiota species or diversity measures were also associated with maternal overweight/obesity (Ow/Ob), excessive gestational weight gain (GWG), or both, in the maternal gut microbiota at the time of delivery; Fig. 5 provides more detail and Fig. S4 shows the association between these BMI-associated infant taxa and maternal characteristics.

  • FIG 4
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    FIG 4

    Spaghetti plots of BMI z-scores over time by Ow/Ob status at age 12. The regression lines (denoted by thicker lines) show that BMI z-scores were fairly constant between ages 2 and 12 for children who were not Ow/Ob at age 12, but there was an increase in BMI z-scores during this time for children who became Ow/Ob. At age 2, there was no significant difference between BMI z-scores of children who later became Ow/Ob and those who did not.

  • FIG 5
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    FIG 5

    Venn diagrams showing the overlap between gut microbiota (a) OTUs and (b) species associated with maternal overweight/obesity (Ow/Ob) and excessive gestational weight gain (GWG) in the maternal taxa at the time of delivery and those predictive of childhood BMI in the infant gut microbiota taxa during the first 2 years of life. The OTUs are listed with OTU, phylum, and most specific level of known taxonomic classification; “species” are listed as phylum and most specific level of known taxonomic classification. The numbers in parentheses show at which time points in the infant these taxa were predictive of childhood BMI. Due to the large number of taxa associated with child BMI (green circle), these are not all listed by name but are shown in Fig. 3.

Tables

  • Figures
  • Supplemental Material
  • TABLE 1

    Characteristics and early-life exposure of infants in the NoMIC cohorta

    CharacteristicMedian (IQR) or n (%)P value
    Total (n = 165)Non-Ow/Ob = 0 (n = 132)Ow/Ob (n = 33)
    Parental characteristics
        Maternal age (yr)30 (27–32)30 (28–32)29 (26–33)0.45
        Ethnic Norwegian144 (87.3%)116 (87.9%)28 (84.8%)0.26
            Missing5 (3.0%)3 (2.3%)2 (6.1%)
        Maternal education
            <12 yr education15 (9.1%)10 (7.6%)5 (15.2%)0.002
            12 yr education29 (17.6%)20 (15.2%)9 (27.3%)
            >12 yr education118 (71.5%)99 (75.0%)19 (57.6%)
            Missing3 (1.8%)3 (2.3%)0 (0.0%)
        Maternal prepregnancy BMI24.5 (21.4–27.1)23.1 (21.0–26.1)26.3 (24.2–30.1)<0.001
        Maternal prepregnancy Ow/Ob73 (44.2%)49 (37.1%)24 (72.7%)<0.001
        Paternal BMI26.1 (23.7–28.2)25.4 (23.7–27.7)27.8 (25.9–29.2)0.13
    Exposures during pregnancy
        Maternal smoking during pregnancy20 (12.1%)12 (9.1%)8 (24.2%)0.02
        Diabetes
            Type 11 (0.6%)1 (0.8%)0 (0.0%)0.64
            Gestational diabetes1 (0.6%)1 (0.8%)0 (0.0%)
        High BP9 (5.5%)7 (5.3%)2 (6.1%)1.00
        Parity
            No prior pregnancies75 (45.5%)61 (46.2%)14 (42.4%)0.17
            1 prior child54 (32.7%)46 (34.8%)8 (24.2%)
            >1 prior child36 (21.8%)25 (18.9%)11 (33.3%)
    Infant and birth
        Female sex75 (45.5%)59 (44.7%)16 (48.5%)0.70
        Twins21 (12.7%)20 (15.2%)1 (3.0%)0.08
        Gestational age at birth (wk)39.0 (36.0–40.0)39.0 (36.5–40.0)39.0 (36.0–40.0)0.78
        C-section delivery51 (30.9%)38 (28.8%)13 (39.4%)0.24
        Birth weight (g)3,290 (2,560–3,750)3,260 (2,540–3,740)3,370 (2,878–3,990)0.31
    Infant feeding
        Length of any breastfeeding (mo)10 (5–13)11 (5.5–14)7 (3–13)0.03
        Length of exclusive breastfeeding (mo)4 (2–6)5 (2–6)2 (0–5)0.01
        Child age when introduced to porridge (wk)19 (16–22.5)20 (16–23)18 (16–20)0.24
        Child age when introduced to solids (wk)20 (16–26)22 (17.5–26)18 (16–26)0.12
    Antibiotic exposures
        Maternal antibiotics during pregnancy56 (33.9%)46 (34.8%)10 (30.3%)0.83
            Missing5 (3.0%)3 (2.3%)2 (6.1%)
        Antibiotics given to newborn24 (14.5%)16 (12.1%)8 (24.2%)0.09
            Missing2 (1.2%)1 (0.8%)1 (3.0%)
        Child antibiotics before10 (6.1%)6 (4.5%)4 (12.1%)0.11
            4 days
            10 days13 (7.9%)9 (6.8%)4 (12.1%)0.30
            30 days18 (10.9%)13 (9.8%)5 (15.2%)0.38
            120 days25 (15.2%)20 (15.2%)5 (15.2%)1.00
            1 year68 (41.2%)52 (39.4%)16 (48.5%)0.34
            2 years93 (56.4%)74 (56.1%)19 (57.6%)0.88
    Childhood BMI
        BMI-for-age Z0.1 (–0.5 to 0.7)–0.1 (–0.6 to 0.4)1.7 (1.4–1.9)<0.001
        BMI-for-age percentile54.3 (30.2–77.2)47.6 (26.9–64.4)95.1 (92.0–97.1)<0.001
    • ↵a Children are grouped by overweight/obesity (Ow/Ob) status at age 12, as defined by age- and sex-specific BMI percentiles of ≥85th percentile.

Supplemental Material

  • Figures
  • Tables
  • FIG S1

    Characterization of the gut microbiota samples of mothers at the time of delivery and infants over the first two years of life. Mean relative abundance of the most prevalent phyla (top) and genera (bottom) in maternal gut microbiota samples at the time of delivery (n = 71; labeled “Mother”) and infant gut microbiota samples over the first two years of life by overweight/obese (Ow/Ob) status at age 12 and sampling time (4, 10, 30, 120, 365, and 730 days with n = 147, 151, 155, 147, 118, and 63, respectively). Download FIG S1, EPS file, 0.04 MB.

    Copyright © 2018 Stanislawski et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S2

    Principal coordinate analysis plots of weighted (left) and unweighted (right) UniFrac distance of infant and maternal samples by sampling time. The number of samples varied with sampling time: 4 days, n = 147; 10 days, n = 151; 30 days, n = 155; 120 days, n = 147; 365 days, n = 118; 730 days, n = 63; and maternal samples, n = 71. Download FIG S2, JPG file, 0.02 MB.

    Copyright © 2018 Stanislawski et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S3

    Conceptual model and direct acyclic graphs (DAGs) of the relationships examined in this study. The diagram at the top shows the overall conceptual model of the relationships examined in this study between maternal overweight/obesity (Ow/Ob) and excessive gestational weight gain (GWG), maternal and infant gut microbiota, and childhood BMI. Below this are DAGs of the relationships between exposures, outcomes, and other factors in the analysis of (i) infant gut microbiota and BMI z-score at age 12 and (ii) maternal characteristics and infant gut microbiota. In prior work, we examined the relationship between maternal Ow/Ob and excessive GWG and maternal gut microbiota at the time of delivery. DAGs show the conceptual relationships between exposures, outcomes, confounders, and mediators and inform decisions about what to include in statistical models. Relationships were determined based on prior research when available and on univariate analyses in this cohort for factors without prior research (using a P value cutoff of 0.1). Download FIG S3, TIF file, 0.8 MB.

    Copyright © 2018 Stanislawski et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • TABLE S1

    Results of unadjusted and adjusted linear regressions to assess the direction of association between infant gut microbiota features (selected as highly predictive of childhood BMI z-score) and BMI z-score. Adjusted models included the following: exclusive breastfeeding, delivery mode, antibiotics, twin status, and gestational age at birth. Download Table S1, XLSX file, 0.1 MB.

    Copyright © 2018 Stanislawski et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S4

    The association between maternal (a) prepregnancy Ow/Ob and (b) excessive GWG and the infant gut microbiota taxa that were highly predictive of childhood BMI. This plot shows the strength of association between maternal characteristics and the infant gut microbiota taxa selected as highly predictive of childhood BMI at each sampling time (i.e., those shown in Fig. 3). The P values are from unadjusted (circles) and adjusted (squares) permutational ANOVA models of the unweighted (coral) and weighted (blue) UniFrac distance matrices of the taxa. Dotted lines show P = 0.05 (black) and P = 0.1 (gray). Adjusted models controlled for breastfeeding, delivery mode, antibiotic exposures, and gestational age at birth. Download FIG S4, TIF file, 0.4 MB.

    Copyright © 2018 Stanislawski et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

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Gut Microbiota in the First 2 Years of Life and the Association with Body Mass Index at Age 12 in a Norwegian Birth Cohort
Maggie A. Stanislawski, Dana Dabelea, Brandie D. Wagner, Nina Iszatt, Cecilie Dahl, Marci K. Sontag, Rob Knight, Catherine A. Lozupone, Merete Eggesbø
mBio Oct 2018, 9 (5) e01751-18; DOI: 10.1128/mBio.01751-18

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Gut Microbiota in the First 2 Years of Life and the Association with Body Mass Index at Age 12 in a Norwegian Birth Cohort
Maggie A. Stanislawski, Dana Dabelea, Brandie D. Wagner, Nina Iszatt, Cecilie Dahl, Marci K. Sontag, Rob Knight, Catherine A. Lozupone, Merete Eggesbø
mBio Oct 2018, 9 (5) e01751-18; DOI: 10.1128/mBio.01751-18
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KEYWORDS

children
infants
microbiota
obesity

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