Associations between the Safe Prevention of Primary Cesarean Delivery Care Consensus and Maternal/Neonatal Outcomes

OBJECTIVE

 This study aimed to compare cesarean delivery (CD) rates and maternal/neonatal outcomes before and after the 2014 ACOG/SMFM Obstetric Care Consensus for Safe Prevention of Primary CD.

STUDY DESIGN

 This retrospective study compared unscheduled CD rates and outcomes of singleton, cephalic, term pregnancies at a tertiary-care teaching maternity hospital. Births 5 years before (March 2009-February 2014) and after (June 2014-May 2019) release of the consensus were included. Chi-square and t-test were used to compare outcomes and logistic regression to adjust for confounders.

RESULTS

 In this study, 44,001 pregnancies were included, 20,887 before and 23,114 after the consensus. Unscheduled CD rates increased after the consensus (12.9 vs. 14.3%, p < 0.001); however, there was no difference after adjustment (adjusted odds ratio [aOR], 0.97; 95% confidence interval [CI], 0.91-1.03). Vaginal birth after cesarean (VBAC) deliveries increased among multiparas (4.8 vs. 7.2%, p < 0.001), which remained significant after adjustment (aOR, 1.51; 95% CI, 1.37-1.66). Postpartum hemorrhage, blood transfusion, and chorioamnionitis were modestly increased, while third-degree perineal lacerations decreased. Uterine rupture and neonatal outcomes were unchanged after adjustment.

CONCLUSION

 At our tertiary-care maternity hospital, the Safe Prevention of Primary CD Care Consensus was not associated with a change in unscheduled CD, though VBAC deliveries increased. We did not demonstrate improved neonatal outcomes and showed increased maternal morbidity that warrants further study.

KEY POINTS

· Consensus did not change unscheduled cesarean rates.. · Consensus associated with increased hemorrhage.. · Institutional outcomes can assist implementing changes..

The fungal intestinal microbiota predict the development of bronchopulmonary dysplasia in very low birthweight newborns

RATIONALE

Bronchopulmonary dysplasia (BPD) is the most common morbidity affecting very preterm infants. Gut fungal and bacterial microbial communities contribute to multiple lung diseases and may influence BPD pathogenesis.

METHODS

We performed a prospective, observational cohort study comparing the multikingdom fecal microbiota of 144 preterm infants with or without moderate to severe BPD by sequencing the bacterial 16S and fungal ITS2 ribosomal RNA gene. To address the potential causative relationship between gut dysbiosis and BPD, we used fecal microbiota transplant in an antibiotic-pseudohumanized mouse model. Comparisons were made using RNA sequencing, confocal microscopy, lung morphometry, and oscillometry.

RESULTS

We analyzed 102 fecal microbiome samples collected during the second week of life. Infants who later developed BPD showed an obvious fungal dysbiosis as compared to infants without BPD (NoBPD, p = 0.0398, permutational multivariate ANOVA). Instead of fungal communities dominated by Candida and Saccharomyces, the microbiota of infants who developed BPD were characterized by a greater diversity of rarer fungi in less interconnected community architectures. On successful colonization, the gut microbiota from infants with BPD augmented lung injury in the offspring of recipient animals. We identified alterations in the murine intestinal microbiome and transcriptome associated with augmented lung injury.

CONCLUSIONS

The gut fungal microbiome of infants who will develop BPD is dysbiotic and may contribute to disease pathogenesis.

The Pacific Innovations, Knowledge, and Opportunities (PIKO) Program: A Data Lifecycle Research Experience

Pacific evidence-based clinical and translational research is greatly needed. However, there are research challenges that stem from the creation, accessibility, availability, usability, and compliance of data in the Pacific. As a result, there is a growing demand for a complementary approach to the traditional Western research process in clinical and translational research. The data lifecycle is one such approach with a history of use in various other disciplines. It was designed as a data management tool with a set of activities that guide researchers and organizations on the creation, management, usage, and distribution of data. This manuscript describes the data lifecycle and its use by the Biostatistics, Epidemiology, and Research Design core data science team in support of the Center for Pacific Innovations, Knowledge, and Opportunities program.

Opportunities for growth in the growing field of psychobiotics

There is growing interest in the field of psychobiotics, which are probiotics that confer a mental health benefit when ingested. As this field grows, it should pay particular attention to three areas within psychobiotics research that are currently under-studied - sex (and gender) representation, fungi and the mycobiome, and vagus nerve activity. Giving these three domains more attention is currently feasible without significant increased investment of time or money. We discuss these three domains briefly, why they are of particular relevance for psychobiotics research, and how psychobiotics research can easily integrate their perspectives. Our recommendations are summarised in the conclusion, but include equal sex representation at all phases of research (human and animal studies), investigating the relationship between psychobiotics and commensal fungi, and measuring the activity of the vagus nerve in psychobiotics studies.

Hawaiian Fungal Amplicon Sequence Variants Reveal Otherwise Hidden Biogeography

To study biogeography and other ecological patterns of microorganisms, including fungi, scientists have been using operational taxonomic units (OTUs) as representations of species or species hypotheses. However, when defined by 97% sequence similarity cutoff at an accepted barcode locus such as 16S in bacteria or ITS in fungi, these OTUs can obscure biogeographic patterns, mask taxonomic diversity, and hinder meta-analyses. Amplicon sequence variants (ASVs) have been proposed to alleviate all of these issues and have been shown to do so in bacteria. Analyzing ASVs is just emerging as a common practice among fungal studies, and it is unclear whether the benefits found in bacterial studies of using such an approach carryover to fungi. Here, we conducted a meta-analysis of Hawaiian fungi by analyzing ITS1 amplicon sequencing data as ASVs and exploring ecological patterns. These surveys spanned three island groups and five ecosystems combined into the first comprehensive Hawaiian Mycobiome ASV Database. Our results show that ASVs can be used to combine fungal ITS surveys, increase reproducibility, and maintain the broad ecological patterns observed with OTUs, including diversity orderings. Additionally, the ASVs that comprise some of the most common OTUs in our database reveals some island specialists, indicating that traditional OTU clustering can obscure important biogeographic patterns. We recommend that future fungal studies, especially those aimed at assessing biogeography, analyze ASVs rather than OTUs. We conclude that similar to bacterial studies, ASVs improve reproducibility and data sharing for fungal studies.

Functional lower airways genomic profiling of the microbiome to capture active microbial metabolism

BACKGROUND

Microbiome studies of the lower airways based on bacterial 16S rRNA gene sequencing assess microbial community structure but can only infer functional characteristics. Microbial products, such as short-chain fatty acids (SCFAs), in the lower airways have significant impact on the host's immune tone. Thus, functional approaches to the analyses of the microbiome are necessary.

METHODS

Here we used upper and lower airway samples from a research bronchoscopy smoker cohort. In addition, we validated our results in an experimental mouse model. We extended our microbiota characterisation beyond 16S rRNA gene sequencing with the use of whole-genome shotgun (WGS) and RNA metatranscriptome sequencing. SCFAs were also measured in lower airway samples and correlated with each of the sequencing datasets. In the mouse model, 16S rRNA gene and RNA metatranscriptome sequencing were performed.

RESULTS

Functional evaluations of the lower airway microbiota using inferred metagenome, WGS and metatranscriptome data were dissimilar. Comparison with measured levels of SCFAs shows that the inferred metagenome from the 16S rRNA gene sequencing data was poorly correlated, while better correlations were noted when SCFA levels were compared with WGS and metatranscriptome data. Modelling lower airway aspiration with oral commensals in a mouse model showed that the metatranscriptome most efficiently captures transient active microbial metabolism, which was overestimated by 16S rRNA gene sequencing.

CONCLUSIONS

Functional characterisation of the lower airway microbiota through metatranscriptome data identifies metabolically active organisms capable of producing metabolites with immunomodulatory capacity, such as SCFAs.

The values of AHCY and CBS promoter methylation on the diagnosis of cerebral infarction in Chinese Han population

BACKGROUND

The goal of our study is to investigate whether the methylation levels of AHCY and CBS promoters are related to the risk of cerebral infarction by detecting the methylation level of AHCY and CBS genes.

METHODS

We extracted peripheral venous blood from 152 patients with cerebral infarction and 152 gender- and age-matched healthy controls, and determined methylation levels of AHCY and CBS promoters using quantitative methylation-specific polymerase chain reaction. We used the percentage of methylation reference (PMR) to indicate gene methylation level.

RESULTS

We compared the promoter methylation levels of two genes (AHCY and CBS) in peripheral blood DNA between the cerebral infarction case group and the control group. Our study showed no significant difference in AHCY promoter methylation between case and control. Subgroup analysis by gender showed that the methylation level of AHCY in males in the case group was lower than that in the control group, but the difference was not statistically significant in females. In a subgroup analysis by age, there was no significant difference in the AHCY methylation level between the case and control in the young group (≤44 years old). However, the level of AHCY gene methylation in the middle-aged group (45-59 years old) was significantly higher and the aged group (≥60 years old) was significantly lower than that in the control groups. However, CBS promoter methylation levels were significantly lower in the case group than in the control group (median PMR: 70.20% vs 104.10%, P = 3.71E-10). In addition, the CBS methylation levels of males and females in the case group were significantly lower than those in the control group (male: 64.33% vs 105%, P = 2.667E-08; female: 78.05% vs 102.8%, P = 0.003). We also found that the CBS levels in the young (23-44), middle-aged (45-59), and older (60-90) groups were significantly lower than those in the control group (young group: 69.97% vs 114.71%; P = 0.015; middle-aged group: 56.04% vs 91.71%; P = 6.744E-06; older group: 81.6% vs 119.35%; P = 2.644E-04). Our ROC curve analysis of CBS hypomethylation showed an area under the curve of 0.713, a sensitivity of 67.4%, and a specificity of 74.0%.

CONCLUSION

Our study suggests that hypomethylation of the CBS promoter may be closely related to the risk of cerebral infarction and may be used as a non-invasive diagnostic biomarker for cerebral infarction.

Prebiotic Potential of Taro (Colocasia esculenta) to Modulate Gut Bacteria Composition and Short Chain Fatty Acid Production

Objectives

Taro (Colocasia esculenta) is a high fiber tuber that holds cultural and agricultural importance in the Pacific. The high fiber content offers potential as a dietary prebiotic through the presence of resistant starch (RS). RS aids gut bacteria in the production of short-chain fatty acids (SCFA), which have health benefits to the host. As such, this study aimed to investigate the effect of taro on gut bacteria composition and SCFA production through in vitro human digestion and fecal fermentation methodology.

Methods

Five taro varieties (Bun Long, Mana Ulu, Moi, Kauai Lehua, Tahitian) were processed. RS concentration of taro was determined using Megazyme Resistant Starch kit. Taro samples were subjected to in vitro human digestion, replicating oral, gastric, small intestinal, and large intestinal phases. Digested taro samples were mixed with fresh human fecal slurries and fermented at 37°C for 24 hours. During fermentation, samples were collected at specific time points for analyzation of SCFA contents using gas chromatography and bacterial composition using 16S rRNA gene targeted amplicon sequencing.

Results

Tahitian variety had the highest RS concentration of 25.1%, with no significantly difference between Tahitian, Bun Long, and Moi varieties. All taro varieties exhibited statistically similar SCFA concentrations for 3-hydroxybutyric acid, acetic acid and propionic acid. Bun-Long, Tahitian, and Moi varieties exhibited significantly higher butyric acid levels than two other taro varieties. Butyric acid production had the highest correlation coefficient with RS concentration of 0.80. The bacterial community present in all taro varieties after 24 hours of fermentation was markedly different from that of the control communities, including shifts in both the Bacteriodes and Firmicutes phyla.

Conclusions

Different taro varieties have varying RS concentrations that affect the production of SCFA in an in vitro human digestion and fecal fermentation. The production of health-promoting butyric acid shows a strong positive correlation with the resistant starch concentration of taro. Taro distinctly causes shifts after 24 hours of fecal fermentation in Bacteriodes and Firmicutes phyla. These results provide new insights into the modulation of gut microbiota through dietary interventions.

Funding Sources

USDA-NIFA Hatch C-Maīki, University of Hawaii.

Remote tropical island colonization does not preclude symbiotic specialists: new evidence of mycorrhizal specificity across the geographic distribution of the Hawaiian endemic orchid Anoectochilus sandvicensis

BACKGROUND AND AIMS

For symbiotic organisms, their colonization and spread across remote oceanic islands should favour generalists. Plants that form obligate symbiotic associations with microbes dominate island ecosystems, but the relationship between island inhabitance and symbiotic specificity is unclear, especially in the tropics. To fill this gap, we examined the mycorrhizal specificity of the Hawaiian endemic orchid Anoectochilus sandvicensis across multiple populations encompassing its entire geographic distribution.

METHODS

By molecular phylogenetic approaches we identified the mycorrhizal fungi associated with A. sandvicensis across its entire geographic distribution and determined the relationship of these fungi to others found elsewhere around the globe. With richness estimators, we assessed the mycorrhizal specificity of A. sandvicensis within and among islands. We then tested whether geographic proximity of orchid populations was a significant predictor for the presence of particular mycorrhizal fungi and their community composition.

KEY RESULTS

We found that each population of A. sandvicensis forms specific associations with one of three fungi in the genus Ceratobasidium and that the closest relatives of these fungi are globally widespread. Based on diversity indices, A. sandvicensis populations were estimated to partner with one to four mycorrhizal taxa with an estimated total of four compatible mycorrhizal fungi across its entire distribution. However, the geographic proximity of orchid populations was not a significant predictor of mycorrhizal fungal community composition.

CONCLUSIONS

Our findings indicate that the colonization and survival of plant species on even the most remote oceanic islands is not restricted to symbiotic generalists, and that partnering with few, but cosmopolitan microbial symbionts is an alternative means for successful island establishment. We suggest that the spatial distribution and abundance of symbionts in addition to island age, size and isolation should also be taken into consideration for predictions of island biodiversity.

A Developing Symbiosis: Enabling Cross-Talk Between Ecologists and Microbiome Scientists

Like all interactions, the success of cross-discipline collaborations relies on effective communication. Ecology offers theoretical frameworks and lexicons to study microbiomes. Yet some of the terms and concepts borrowed from ecology are being used discordantly by microbiome studies from their traditional definitions. Here we define some of the ecological terms and concepts as they are used in ecology and the study of microbiomes. Where applicable, we have provided the historical context of the terms, highlighted examples from microbiome studies, and considered the research methods involved. We divided these concepts into four sections: Biomes, Diversity, Symbiosis, and Succession. Biomes encompass the interactions within the biotic and abiotic features of an environment. This extends to the term "microbiome," derived from "biome," and includes an environment and all the microbes within it. Diversity encompasses patterns of species richness, abundance, and biogeography, all of which are important to understanding the distribution of microbiomes. Symbiosis emphasizes the relationships between organisms within a community. Symbioses are often misunderstood to be synonymous with mutualism. We discard that implication, in favor of a broader, more historically accurate definition which spans the continuum from parasitism to mutualism. Succession includes classical succession, alternative stable states, community assembly frameworks, and r/K-selection. Our hope is that as microbiome researchers continue to apply ecological terms, and as ecologists continue to gain interest in microbiomes, each will do so in a way that enables cross-talk between them. We recommend initiating these collaborations by using a common lexicon, from which new concepts can emerge.

Measuring associations between the microbiota and repeated measures of continuous clinical variables using a lasso-penalized generalized linear mixed model

Background

Human microbiome studies in clinical settings generally focus on distinguishing the microbiota in health from that in disease at a specific point in time. However, microbiome samples may be associated with disease severity or continuous clinical health indicators that are often assessed at multiple time points. While the temporal data from clinical and microbiome samples may be informative, analysis of this type of data can be problematic for standard statistical methods.

Results

To identify associations between microbiota and continuous clinical variables measured repeatedly in two studies of the respiratory tract, we adapted a statistical method, the lasso-penalized generalized linear mixed model (LassoGLMM). LassoGLMM can screen for associated clinical variables, incorporate repeated measures of individuals, and address the large number of species found in the microbiome. As is common in microbiome studies, when the number of variables is an order of magnitude larger than the number of samples LassoGLMM can be imperfect in its variable selection. We overcome this limitation by adding a pre-screening step to reduce the number of variables evaluated in the model. We assessed the use of this adapted two-stage LassoGLMM for its ability to determine which microbes are associated with continuous repeated clinical measures.

We found associations (retaining a non-zero coefficient in the LassoGLMM) between 10 laboratory measurements and 43 bacterial genera in the oral microbiota, and between 2 cytokines and 3 bacterial genera in the lung. We compared our associations with those identified by the Wilcoxon test after dichotomizing our outcomes and identified a non-significant trend towards differential abundance between high and low outcomes. Our two-step LassoGLMM explained more of the variance seen in the outcome of interest than other variants of the LassoGLMM method.

Conclusions

We demonstrated a method that can account for the large number of genera detected in microbiome studies and repeated measures of clinical or longitudinal studies, allowing for the detection of strong associations between microbes and clinical measures. By incorporating the design strengths of repeated measurements and a prescreening step to aid variable selection, our two-step LassoGLMM will be a useful analytic method for investigating relationships between microbes and repeatedly measured continuous outcomes.

Electronic supplementary material

The online version of this article (10.1186/s13040-018-0173-9) contains supplementary material, which is available to authorized users.

Fungi stabilize connectivity in the lung and skin microbial ecosystems

BACKGROUND

No microbe exists in isolation, and few live in environments with only members of their own kingdom or domain. As microbiome studies become increasingly more interested in the interactions between microbes than in cataloging which microbes are present, the variety of microbes in the community should be considered. However, the majority of ecological interaction networks for microbiomes built to date have included only bacteria. Joint association inference across multiple domains of life, e.g., fungal communities (the mycobiome) and bacterial communities, has remained largely elusive.

RESULTS

Here, we present a novel extension of the SParse InversE Covariance estimation for Ecological ASsociation Inference (SPIEC-EASI) framework that allows statistical inference of cross-domain associations from targeted amplicon sequencing data. For human lung and skin micro- and mycobiomes, we show that cross-domain networks exhibit higher connectivity, increased network stability, and similar topological re-organization patterns compared to single-domain networks. We also validate in vitro a small number of cross-domain interactions predicted by the skin association network.

CONCLUSIONS

For the human lung and skin micro- and mycobiomes, our findings suggest that fungi play a stabilizing role in ecological network organization. Our study suggests that computational efforts to infer association networks that include all forms of microbial life, paired with large-scale culture-based association validation experiments, will help formulate concrete hypotheses about the underlying biological mechanisms of species interactions and, ultimately, help understand microbial communities as a whole.

Variation in Maturity-Onset Diabetes of the Young Genes Influence Response to Interventions for Diabetes Prevention

Context

Variation in genes that cause maturity-onset diabetes of the young (MODY) has been associated with diabetes incidence and glycemic traits.

Objectives

This study aimed to determine whether genetic variation in MODY genes leads to differential responses to insulin-sensitizing interventions.

Design and Setting

This was a secondary analysis of a multicenter, randomized clinical trial, the Diabetes Prevention Program (DPP), involving 27 US academic institutions. We genotyped 22 missense and 221 common variants in the MODY-causing genes in the participants in the DPP.

Participants and Interventions

The study included 2806 genotyped DPP participants randomized to receive intensive lifestyle intervention (n = 935), metformin (n = 927), or placebo (n = 944).

Main Outcome Measures

Association of MODY genetic variants with diabetes incidence at a median of 3 years and measures of 1-year β-cell function, insulinogenic index, and oral disposition index. Analyses were stratified by treatment group for significant single-nucleotide polymorphism × treatment interaction (Pint < 0.05). Sequence kernel association tests examined the association between an aggregate of rare missense variants and insulinogenic traits.

Results

After 1 year, the minor allele of rs3212185 (HNF4A) was associated with improved β-cell function in the metformin and lifestyle groups but not the placebo group; the minor allele of rs6719578 (NEUROD1) was associated with an increase in insulin secretion in the metformin group but not in the placebo and lifestyle groups.

Conclusions

These results provide evidence that genetic variation among MODY genes may influence response to insulin-sensitizing interventions.

The lung mycobiome in the next-generation sequencing era

The fungi that reside in the human lungs represent an understudied, but medically relevant comm-unity. From the few studies published on the lung mycobiome, we find that there are fungi in both the healthy and diseased respiratory tract, that these fungi vary widely between individuals, and that there is a trend toward lower fungal diversity among individuals with disease. This review discusses the few studies of the lung mycobiome and details the challenges that accompany lung mycobiome studies. These challenges include sample collection and processing, sequence amplification and processing, and a history of multiple names for species. Some challenges may never be solved, but others can be solved with more data and additional studies of the lung mycobiome.

Longitudinal analysis of the lung microbiota of cynomolgous macaques during long-term SHIV infection

BACKGROUND

Longitudinal studies of the lung microbiome are challenging due to the invasive nature of sample collection. In addition, studies of the lung microbiome in human disease are usually performed after disease onset, limiting the ability to determine early events in the lung. We used a non-human primate model to assess lung microbiome alterations over time in response to an HIV-like immunosuppression and determined impact of the lung microbiome on development of obstructive lung disease. Cynomolgous macaques were infected with the SIV-HIV chimeric virus SHIV89.6P. Bronchoalveolar lavage fluid samples were collected pre-infection and every 4 weeks for 53 weeks post-infection. The microbiota was characterized at each time point by 16S ribosomal RNA (rRNA) sequencing.

RESULTS

We observed individual variation in the composition of the lung microbiota with a proportion of the macaques having Tropheryma whipplei as the dominant organism in their lungs. Bacterial communities varied over time both within and between animals, but there did not appear to be a systematic alteration due to SHIV infection. Development of obstructive lung disease in the SHIV-infected animals was characterized by a relative increase in abundance of oral anaerobes. Network analysis further identified a difference in community composition that accompanied the development of obstructive disease with negative correlations between members of the obstructed and non-obstructed groups. This emphasizes how species shifts can impact multiple other species, potentially resulting in disease.

CONCLUSIONS

This study is the first to investigate the dynamics of the lung microbiota over time and in response to immunosuppression in a non-human primate model. The persistence of oral bacteria in the lung and their association with obstruction suggest a potential role in pathogenesis. The lung microbiome in the non-human primate is a valuable tool for examining the impact of the lung microbiome in human health and disease.

Correlation of the lung microbiota with metabolic profiles in bronchoalveolar lavage fluid in HIV infection

BACKGROUND

While 16S ribosomal RNA (rRNA) sequencing has been used to characterize the lung's bacterial microbiota in human immunodeficiency virus (HIV)-infected individuals, taxonomic studies provide limited information on bacterial function and impact on the host. Metabolic profiles can provide functional information on host-microbe interactions in the lungs. We investigated the relationship between the respiratory microbiota and metabolic profiles in the bronchoalveolar lavage fluid of HIV-infected and HIV-uninfected outpatients.

RESULTS

Targeted sequencing of the 16S rRNA gene was used to analyze the bacterial community structure and liquid chromatography-high-resolution mass spectrometry was used to detect features in bronchoalveolar lavage fluid. Global integration of all metabolic features with microbial species was done using sparse partial least squares regression. Thirty-nine HIV-infected subjects and 20 HIV-uninfected controls without acute respiratory symptoms were enrolled. Twelve mass-to-charge ratio (m/z) features from C18 analysis were significantly different between HIV-infected individuals and controls (false discovery rate (FDR) = 0.2); another 79 features were identified by network analysis. Further metabolite analysis demonstrated that four features were significantly overrepresented in the bronchoalveolar lavage (BAL) fluid of HIV-infected individuals compared to HIV-uninfected, including cystine, two complex carbohydrates, and 3,5-dibromo-L-tyrosine. There were 231 m/z features significantly associated with peripheral blood CD4 cell counts identified using sparse partial least squares regression (sPLS) at a variable importance on projection (VIP) threshold of 2. Twenty-five percent of these 91 m/z features were associated with various microbial species. Bacteria from families Caulobacteraceae, Staphylococcaceae, Nocardioidaceae, and genus Streptococcus were associated with the greatest number of features. Glycerophospholipid and lineolate pathways correlated with these bacteria.

CONCLUSIONS

In bronchoalveolar lavage fluid, specific metabolic profiles correlated with bacterial organisms known to play a role in the pathogenesis of pneumonia in HIV-infected individuals. These findings suggest that microbial communities and their interactions with the host may have functional metabolic impact in the lung.

Topographic diversity of the respiratory tract mycobiome and alteration in HIV and lung disease

RATIONALE

Microbiome studies typically focus on bacteria, but fungal species are common in many body sites and can have profound effects on the host. Wide gaps exist in the understanding of the fungal microbiome (mycobiome) and its relationship to lung disease.

OBJECTIVES

To characterize the mycobiome at different respiratory tract levels in persons with and without HIV infection and in HIV-infected individuals with chronic obstructive pulmonary disease (COPD).

METHODS

Oral washes (OW), induced sputa (IS), and bronchoalveolar lavages (BAL) were collected from 56 participants. We performed 18S and internal transcribed spacer sequencing and used the neutral model to identify fungal species that are likely residents of the lung. We used ubiquity-ubiquity plots, random forest, logistic regression, and metastats to compare fungal communities by HIV status and presence of COPD.

MEASUREMENTS AND MAIN RESULTS

Mycobiomes of OW, IS, and BAL shared common organisms, but each also had distinct members. Candida was dominant in OW and IS, but BAL had 39 fungal species that were disproportionately more abundant than in the OW. Fungal communities in BAL differed significantly by HIV status and by COPD, with Pneumocystis jirovecii significantly overrepresented in both groups. Other fungal species were also identified as differing in HIV and COPD.

CONCLUSIONS

This study systematically examined the respiratory tract mycobiome in a relatively large group. By identifying Pneumocystis and other fungal species as overrepresented in the lung in HIV and in COPD, it is the first to determine alterations in fungal communities associated with lung dysfunction and/or HIV, highlighting the clinical relevance of these findings. Clinical trial registered with www.clinicaltrials.gov (NCT00870857).

Salicylate (salsalate) in patients with type 2 diabetes: a randomized trial

BACKGROUND

Short-duration studies show that salsalate improves glycemia in type 2 diabetes mellitus (T2DM).

OBJECTIVE

To assess 1-year efficacy and safety of salsalate in T2DM.

DESIGN

Placebo-controlled, parallel trial; computerized randomization and centralized allocation, with patients, providers, and researchers blinded to assignment. (ClinicalTrials.gov: NCT00799643).

SETTING

3 private practices and 18 academic centers in the United States.

PATIENTS

Persons aged 18 to 75 years with fasting glucose levels of 12.5 mmol/L or less (≤225 mg/dL) and hemoglobin A1c (HbA1c) levels of 7.0% to 9.5% who were treated for diabetes.

INTERVENTION

286 participants were randomly assigned (between January 2009 and July 2011) to 48 weeks of placebo (n = 140) or salsalate, 3.5 g/d (n = 146), in addition to current therapies, and 283 participants were analyzed (placebo, n = 137; salsalate, n = 146).

MEASUREMENTS

Change in hemoglobin A1c level (primary outcome) and safety and efficacy measures.

RESULTS

The mean HbA1c level over 48 weeks was 0.37% lower in the salsalate group than in the placebo group (95% CI, -0.53% to -0.21%; P < 0.001). Glycemia improved despite more reductions in concomitant diabetes medications in salsalate recipients than in placebo recipients. Lower circulating leukocyte, neutrophil, and lymphocyte counts show the anti-inflammatory effects of salsalate. Adiponectin and hematocrit levels increased more and fasting glucose, uric acid, and triglyceride levels decreased with salsalate, but weight and low-density lipoprotein cholesterol levels also increased. Urinary albumin levels increased but reversed on discontinuation; estimated glomerular filtration rates were unchanged.

LIMITATION

Trial duration and number of patients studied were insufficient to determine long-term risk-benefit of salsalate in T2DM.

CONCLUSION

Salsalate improves glycemia in patients with T2DM and decreases inflammatory mediators. Continued evaluation of mixed cardiorenal signals is warranted.