The stool microbiota of insulin resistant women with recent gestational diabetes, a high risk group for type 2 diabetes

The gut microbiota has been linked to metabolic diseases. However, information on the microbiome of young adults at risk for type 2 diabetes (T2D) is lacking. The aim of this cross-sectional analysis was to investigate whether insulin resistant women with previous gestational diabetes (pGDM), a high risk group for T2D, differ in their stool microbiota from women after a normoglycemic pregnancy (controls). Bacterial communities were analyzed by high-throughput 16S rRNA gene sequencing using fecal samples from 42 pGDM and 35 control subjects 3–16 months after delivery. Clinical characterization included a 5-point OGTT, anthropometrics, clinical chemistry markers and a food frequency questionnaire. Women with a Prevotellaceae-dominated intestinal microbiome were overrepresented in the pGDM group (p < 0.0001). Additionally, the relative abundance of the phylum Firmicutes was significantly lower in women pGDM (median 48.5 vs. 56.8%; p = 0.013). Taxa richness (alpha diversity) was similar between the two groups and with correction for multiple testing we observed no significant differences on lower taxonomic levels. These results suggest that distinctive features of the intestinal microbiota are already present in young adults at risk for T2D and that further investigations of a potential pathophysiological role of gut bacteria in early T2D development are warranted.

The gut microbiota has been linked to metabolic diseases. However, information on the microbiome of young adults at risk for type 2 diabetes (T2D) is lacking. The aim of this cross-sectional analysis was to investigate whether insulin resistant women with previous gestational diabetes (pGDM), a high risk group for T2D, differ in their stool microbiota from women after a normoglycemic pregnancy (controls). Bacterial communities were analyzed by high-throughput 16S rRNA gene sequencing using fecal samples from 42 pGDM and 35 control subjects 3-16 months after delivery. Clinical characterization included a 5-point OGTT, anthropometrics, clinical chemistry markers and a food frequency questionnaire. Women with a Prevotellaceae-dominated intestinal microbiome were overrepresented in the pGDM group (p < 0.0001). Additionally, the relative abundance of the phylum Firmicutes was significantly lower in women pGDM (median 48.5 vs. 56.8%; p = 0.013). Taxa richness (alpha diversity) was similar between the two groups and with correction for multiple testing we observed no significant differences on lower taxonomic levels. These results suggest that distinctive features of the intestinal microbiota are already present in young adults at risk for T2D and that further investigations of a potential pathophysiological role of gut bacteria in early T2D development are warranted.
Data from human and animal studies suggest that the gut microbiota influences metabolic health 1,2 . The microbiota itself can be markedly affected by dietary habits and medications as well as probably by other until now not fully defined factors 3,4 .
Several studies examined stool microbiota changes associated with metabolic diseases in human subjects. A lower bacterial diversity has been described in association with obesity and insulin resistance 5,6 . On the level of bacterial phyla, a decreased ratio of Bacteroidetes to Firmicutes (B/F ratio) has been shown to be associated with obesity 7,8 but these findings are controversial 9-11 . Finucane et al. concluded in a recent review that there are no simple taxonomic compositions, consistent over different studies, which differentiate between obese and lean individuals 12 . Reduced relative abundance of Firmicutes and of the class Clostridia was found in individuals with type 2 diabetes (T2D) [13][14][15] . On a functional level, several groups reported a reduction of butyrate-producing bacteria in diabetic individuals [14][15][16] . A causal role of the gut microbiota in the development of T2D and also metabolic syndrome is supported by transplantation studies, both in animal models and in humans 17,18 .
Previous human studies concerning associations of the intestinal microbiota with T2D focused on individuals above 50 years of age [14][15][16] and no information is available on the microbiome composition of younger subjects at risk for T2D. In this study, we therefore wanted to test if the composition of the stool microbiota already varied with T2D risk in young adults. Since no biomarkers exist to reliably identify at-risk subjects at this age we chose insulin resistant women with a recent history of gestational diabetes (GDM) as our high risk cohort and compared these to a suitable control group. Women post-GDM have a substantially increased risk for T2D, particularly if they remain insulin resistant after the pregnancy [19][20][21] .

Results
Baseline characteristics. We selected two diametrically opposed groups of women from a prospective post-gestation study: Insulin resistant women with a recent history of GDM (post-GDM/pGDM; n = 42) and women after a normoglycemic pregnancy as controls (n = 35). All data and samples were collected 3 to 16 months after delivery. The clinical baseline characteristics of the study cohort are shown in Table 1. A proportion of 50% of the women pGDM had impaired fasting glucose (IFG) and/ or impaired glucose tolerance (IGT), whereas all controls were normoglycemic. Data from the EPIC food-frequency questionnaire 22 (n = 64) showed no significant differences in dietary intake of macronutritients and fiber between the pGDM and the control group (Table S1).

Bacterial community structure (beta diversity) in the two study groups. A total number of 307
Operational Taxonomic Units (OTUs) were quantified in this study. To examine the bacterial community structure in the stool samples, we analyzed the dataset by a principal coordinate analysis (PCoA) on the basis of Bray-Curtis distances and a permutational MANOVA (pMANOVA) 23 . We found no significant clustering of the predefined post-GDM and control group (p = 0.1). However, the samples from 13 women (cluster P) showed a bacterial composition distinct from the rest of the study cohort (cluster B) ( Fig. 1, p = 0.001 in pMANOVA). The relative abundance of 35 OTUs was significantly different between these two groups after correction for multiple testing (Table S2). In particular, members of the family Prevotellaceae were more abundant in samples within cluster P (24.9 [17.8-30.2] vs. 0.08 [0.02-1.01] %, p < 0.0001), whereas the sequence proportion of the family Bacteroidaceae was decreased (6.2 [4.4-7.7] vs. 21.9 [15.9-30.8] %, p < 0.0001; Fig. 2). OTU2, which could be assigned down to the species level as Prevotella copri, was highly enriched in the subpopulation of cluster P (23.3 [13.1-28.5] vs. 0.01 [0.00-0.02] %, p < 0.001). Cluster P was significantly associated with belonging to the post-GDM group (11 out of 13 individuals in cluster P; p < 0.0001). EPIC-FFQ data revealed no differences in consumption of macronutrients and of different food groups (meat, fat, vegetables, fruits and cereals) between the women in cluster P and those in cluster B. A canonical correspondence analysis (CCA) and permutation tests showed no significant influence of age (p = 0.664), bmi (p = 0.806), time since delivery (p = 0.309) and plasma leptin levels (p = 0.294) on the beta diversity data.

Phylum-level differences between the post-GDM and the control group. At the phylum level,
Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria and Verrucomicrobia accounted on average for 95.4% of total sequences in all study participants, whereas 4.2% were unknown bacterial phyla. A minor fraction of sequences (0.4%) was assigned to the phyla Euryarchaeota, Elusimicrobia, Fusobacteria and Lentisphaerae (referred to as "others" in this manuscript).
Group comparisons for phyla abundances are shown in Fig. 3 and Table S3. Bacterial richness (alpha diversity) and results on lower taxonomic levels. We found no differences in the alpha diversity between pGDM and control subjects (Fig. S1). Similarly, we observed no significant differences in the taxonomic ranks class, order, family and OTU between the two study groups when we applied corrections for multiple testing. These data and the exploratory (uncorrected) p-values are shown in (Table S4).

Discussion
In this study, we compared the stool microbiota of a group of young adults at high risk for subsequent T2D, namely of insulin resistant women after recent GDM with those of a control group -women after Scientific RepoRts | 5:13212 | DOi: 10.1038/srep13212 a normoglycemic pregnancy. The main findings of this study were that the analysis of beta diversity separated the study participants into two clusters with distinct microbiome compositions and that the less common, Prevotellaceae-rich type of microbiome associated strongly with the post-GDM group. Additionally, at the phylum level, the proportion of Firmicutes was lower in the women post-GDM.
Identifying young adults at risk for T2D is difficult because of a lack of suitable biomarkers or highly predictive clinical parameters. Family history or a prediabetic glucose tolerance status have been used for this purpose but these approaches have significant limitations (discussed in 20 ). We therefore used an alternative method to define a young adult at risk cohort and studied women with recent GDM, who remained insulin resistant after delivery. Women with GDM have an about 10-fold increased risk for T2D within 10 years compared to women normoglycemic during pregnancy 21 . Among those post GDM, this risk is further increased if insulin resistance persists after giving birth 19,20 .
Our analysis of beta diversity revealed that a subgroup of 13 women (17% of the study cohort) had a distinct microbiota composition characterized by a high proportion of the family Prevotellaceae, while Bacteroidaceae dominated in the other study participants. This finding was not explained by differences in dietary habits and is in line with a model of two enterotypes proposed recently 24,25 . This model remains controversial 26 and our study lacks the sample size to settle the issue. Nevertheless, a Prevotellaceae-rich microbiome was associated with belonging to the high risk group for T2D in our study. Our finding adds to previous reports of an inverse association between the Bacteroides/Prevotella ratio and obesity 27 , non-alcoholic steatohepatitis 28 and elevated total plasma cholesterol 25 . Potential causative links remain speculative. Prevotella are mucin degrading bacteria, which may be associated with increased χ -square test. NGT = normal glucose tolerance. PGT = pathologic glucose tolerance. IFG = impaired fasting glucose. IGT = impaired glucose tolerance. gut permeability 29 and P. copri, the most dominant molecular species within the taxa Prevotella in our study, has recently been associated with new-onset rheumatoid arthritis 30 . It could therefore be related to low-grade inflammation, which is also detrimental with respect to metabolism.  We further observed a lower relative abundance of Firmicutes in the post-GDM group, a finding previously reported for individuals with already established T2D [13][14][15] . This observation was also true for the normoglycemic women in our study and remained significant in an analysis restricted to women with a Bacteroidaceae-rich microbiome. The difference was small (median 49 vs. 57%) and a relevant overlap existed between the post-GDM and the control group (Fig. 3). Hence, the cause-effect relationships remain unknown. Higher resolution analyses on lower taxonomic levels, requiring large sample sizes, may nevertheless reveal specific underlying differences in microbial composition or function.
The main limitations of our present study are the limited sample size and the fact that only one stool sample per study participant was available. Additionally, the observational, cross-sectional study design precludes examining causality. Strengths of our work are the young adult, uniform cohorts of individuals with little concomitant medication and comorbidities and the detailed clinical phenotyping available.
In conclusion, this study suggests that distinctive features of the intestinal microbiota are already present in young adults at risk for T2D. In particular, it supports a link between a Prevotellaceae-dominated microbiome and T2D risk. Our results warrant further investigation in larger human cohorts and other clinical settings, as well as examination of the underlying molecular mechanisms.

Subjects and Methods
Study population. Subjects included in the present analysis were participants of the prospective, mono-center observational study PPS-Diab (prediction, prevention and subclassification of type 2 diabetes) enrolled between November 2011 and December 2013 as described previously 20 . Women with GDM during their last pregnancy and women following a normoglycemic pregnancy, treated at the Diabetes Center and the obstetrics department of the University Hospital (Klinikum der Universität München) in Munich, Germany, were consecutively recruited for this study in a 2:1 ratio. The diagnosis of GDM was based on a standardized oral glucose tolerance test (OGTT) after the 23rd week of the preceding pregnancy. Exclusion criteria for this study were alcohol or substance abuse, positivity for islet-autoantibodies and chronic diseases requiring medication except for hypothyroidism (n = 13). The study participants were not taking any antibiotic therapy for at least 14 days prior to clinical assessment and stool collection. The study was performed in accordance with relevant guidelines and regulations. Written informed consent was obtained from all study participants and the protocol was approved by the ethical review committee of the Ludwig-Maximilians-Universität München.
All data used in the present analysis were collected at the baseline visit of the PPS-Diab study, 3 to 16 months after the index pregnancy. For this analysis we selected two groups of women from the first 147 eligible study participants (thereof 96 post-GDM women with Matsuda Index  Anthropometric and clinical assessments. All subjects underwent a 5-point OGTT and anthropometric measurements. To quantify insulin sensitivity the Matsuda Index was calculated from the OGTT plasma glucose and insulin measurements as described previously 31 and the HOMA-IR was calculated as the product of fasting glucose and fasting insulin concentrations 32 . The disposition index was calculated from the OGTT to describe the relationship between insulin sensitivity and first-phase insulin secretion 33 . Thereby, the rise in serum insulin during the first 30 minutes of the OGTT was used as a measure of the first-phase insulin secretion. Prediabetes was defined as IFG, IGT or a combination of both following the definition of the American Diabetes Association 34 . Systolic and diastolic blood pressure was measured twice in a sitting position. Weight and body fat mass was assessed by a bioelectrical impedance analysis (BIA) scale (Tanita BC-418, Tanita Corporation, Tokyo, Japan). The bmi was calculated as weight in kilograms divided by height squared in meters. Waist and hip circumference were measured with a tape measurement. A food frequency questionnaire (EPIC-FFQ) for the assessment of dietary nutritional intake was completed online (n = 64) 22

Stool sample collection.
Each study participant collected one stool sample at home using a paper stool collector and tubes pre-filled with 8 ml of stool DNA stabilizer and including a measuring spoon for the sample (PSP Spin Stool DNA Plus Kit, STRATEC Molecular, Berlin, Germany). Samples were mailed to the study center within one day after collection and then immediately stored at − 80 °C until DNA extraction.
Microbiota sequencing. Bacterial DNA was obtained from fecal samples according to the manufacturer's instructions (PSP Spin Stool DNA Plus Kit, STRATEC Molecular). The V4 region of 16S rRNA genes was amplified (25 cycles) as described previously 35 following a 2-step procedure to limit artifacts 36 . Amplicons were purified using the AMPure XP system (Beckman Coulter GmbH, Krefeld, Germany) and sequenced in paired-end modus (PE200) using the MiSeq system (Illumina Inc., San Diego, USA). The raw read files were demultiplexed (allowing a maximum of 2 errors in barcodes) and each sample was processed using usearch 37 following the UPARSE approach 38 . First, all reads were trimmed to the position of the first base with quality score < 3 and then paired. The resulted sequences were size filtered, excluding those with assembled size < 200 and > 260. Paired reads with a number of expected error > 3 were further filtered out and the remaining sequences were trimmed by 10 nucleotides on each side to avoid GC bias and non-random base composition. For each sample, sequences were de-replicated and checked for chimeras with UCHIME 39 . Sequences from all samples were merged, sorted by abundance and OTUs representatives were picked at a threshold of 97% similarity. Finally, all sequences were mapped back to the representative sequences resulting in the OTU table for all samples. The RDP classifier 40 was used to assign taxonomic classification to the OTUs representative sequences (80% confidence). OTUs of particular interest were identified more precisely using the EzTaxon server: http://www.ezbiocloud.net/ eztaxon 41 . A phylogenetic tree was constructed using fasttree 42 . Only OTUs with a relative abundance above 0.5% total sequences in at least one sample were kept. The OTU table was rarefied to the minimum count of sequences observed. After processing (quality-and chimera-check as well as OTU filtering) a total of 2,655,517 16S rRNA reads were used for analysis. We obtained a median of 33,807 sequences per sample with a range of 21,812-51,777 and used 20,000 sequences per sample for rarefaction. Statistical analysis. Statistical analyses were performed using R version 3.1.0 43 and SPSS version 22.0 (SPSS Inc., Chicago, IL, USA). Clinical baseline characteristics are presented as median with interquartile ranges (Q1-Q3). Alpha diversity was measured by the Chao1 Index, which primary calculates the number of taxa 44 and by the Shannon and Simpson Indices, which represent richness and distribution of taxa 45 . Differences in beta diversity were calculated by pMANOVA 46 and illustrated by a PCoA of Bray Curtis distances 23 . The Chi-square test was used for comparing the two subtypes of microbiota composition identified by pMANOVA. A canonical correspondence analysis (CCA) and permutation tests were done using the R package phyloseq. The relative abundances of the taxonomic ranks phylum, class, order, family and of the molecular species are shown as median, interquartile ranges and minimum (min) and maximum (max). The Mann-Whitney U test, the Fisher Exact test or the χ -square test were used for comparisons between groups. The phylum Firmicutes was further analyzed together with the variable 'time since delivery' as independent variables by a binary logistic regression model for the dependent variable pGDM status. P-values < 0.05 were considered statistically significant. Correction for multiple testing by false discovery rate control with the Benjamini-Hochberg procedure was done where indicated in the text.