Differential Effect of Vaginal Microbiota on Spontaneous Preterm Birth among Chinese Pregnant Women

Kan, Hui; He, Yining; Li, Qing; Mu, Yutong; Dong, Yao; Fan, Wei; Zhang, Miao; Wang, Tianlei; Li, Yaxin; Liu, Haiyan; Hu, Anqun; Ying, Zheng

doi:10.1155/2022/3536108

Cited by 5 publications

(4 citation statements)

References 84 publications

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“…Specifically, we reanalyzed data from a study of the vaginal microbiome and preterm birth, and examined the first time point from each of the 40 individuals included in the study 13 ( Methods ). As previously reported 22–24 , we observed an association between α diversity and subsequent preterm birth ( Fig. 2a , Mann-Whitney U p = 0.037).…”

Section: Resultssupporting

confidence: 88%

Compositional transformations can reasonably introduce phenotype-associated values into sparse features

Austin,

Korem

2024

Preprint

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It was recently argued1that an analysis of tumor-associated microbiome data2is invalid because features that were originally very sparse (genera with mostly zero read counts) became associated with the phenotype following batch correction1. Here, we examine whether such an observation should necessarily indicate issues with processing or machine learning pipelines. We focus on the centered log ratio (CLR) transformation, which is often recommended for analysis of compositional microbiome data3. The CLR transformation has similarities to Voom-SNM4,5, the batch-correction method brought into question1,2, yet is a sample-wise operation that cannot, in itself, “leak” information or invalidate downstream analyses. We show that because the CLR transformation divides each value by the geometric mean of its sample, common imputation strategies for missing or zero values result in transformed features that are associated with the geometric mean. Through analyses of both synthetic and vaginal microbiome datasets we demonstrate that when the geometric mean is associated with a phenotype, sparse and CLR-transformed features will also become associated with it. We re-analyze features highlighted by Gihawi et al.1and demonstrate that the phenomena of sparse features becoming phenotype-associated can also be observed after a CLR transformation. While we do not intend to validate tumor-associated microbiome signatures2or evaluate other concerns regarding their detection and analysis1,6, we conclude that as phenotype-associated features that were initially sparse can be created by a sample-wise transformation that cannot artifactually inflate machine learning performance, their detection is not independently sufficient to demonstrate an analytic issue in machine learning pipelines. However, as was also previously noted by others, features transformed with sample-wise operations such as the CLR transformation should be interpreted with caution.

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Section: Resultssupporting

confidence: 88%

Compositional transformations can reasonably introduce phenotype-associated values into sparse features

Austin,

Korem

2024

Preprint

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“…This hypothesis has been supported in studies involving white individuals, but further research is needed to determine its applicability to individuals of other groups [16]. In the Hui Kan et al study, the presence or absence of diabetes was included as an influencing factor, and it was found that the risk of spontaneous preterm birth in all women decreased with Lactobacillus mulieris while the risk in gestational diabetics increased with Lactobacillus paragasseri, Lactobacillus gasseri, Streptococcus, and Proteobacteria [54]. Elovitz and his team conducted a prospective cohort study of 2000 singleton pregnancies to examine the association of cervicovaginal microbiota with spontaneous preterm birth and local immunologic characteristics.…”

Section: Vaginal Microbiota and Spontaneous Preterm Birthmentioning

confidence: 96%

Advances in Research on the Relationship between Vaginal Microbiota and Adverse Pregnancy Outcomes and Gynecological Diseases

Zhao

Ying

2023

Microorganisms

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The human microbiota inhabiting different parts of the body has been shown to have a significant impact on human health, with the gut microbiota being the most extensively studied in relation to disease. However, the vaginal microbiota is also an essential commensal microbiota in the female body that plays a crucial role in female health. Despite receiving less attention than gut microbiota, its importance in regulating reproductive immunity and its complex dynamic properties have been increasingly recognized in recent years. Advances in research on the relationship between vaginal microbiota and pregnancy outcomes & gynecological diseases in women have shed light on the importance of maintaining a healthy vaginal microbiota. In this review, we aim to compile recent developments in the study of the vaginal microbial ecosystem and its role in female health and reproductive outcomes. We provide a comprehensive account of the normal vaginal microbiota, the association between the vaginal microbiota and pregnancy outcomes, and the impact of the vaginal microbiota on gynecological diseases in women. By reviewing recent research, we hope to contribute to the advancement of academic medicine’s understanding of the vaginal microbiota’s importance in female health. We also aim to raise awareness among healthcare professionals and the general public of the significance of maintaining a healthy vaginal microbiota for better reproductive health and the prevention of gynecological diseases.

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“…The species Lactobacillus mulieris was described in March 2020 from a urine isolate ( 3 ), leading to the subsequent reclassification of numerous Lactobacillus jensenii strains based on average nucleotide identity (ANI) ( 3 , 4 ). L. jensenii and L. mulieris are members of both the urinary and vaginal microbiota ( 4 – 6 ). More recently , L. mulieris abundance in the vaginal microbiota has been associated with a decreased risk of spontaneous preterm birth ( 5 ).…”

Section: Announcementmentioning

confidence: 99%

“…L. jensenii and L. mulieris are members of both the urinary and vaginal microbiota ( 4 – 6 ). More recently , L. mulieris abundance in the vaginal microbiota has been associated with a decreased risk of spontaneous preterm birth ( 5 ).…”

Section: Announcementmentioning

confidence: 99%

Draft genome sequences of Lactobacillus mulieris strains isolated from the female urinary tract

Stegman,

Steiling,

Sedano

et al. 2024

Microbiol Resour Announc

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Differential Effect of Vaginal Microbiota on Spontaneous Preterm Birth among Chinese Pregnant Women

Cited by 5 publications

References 84 publications

Compositional transformations can reasonably introduce phenotype-associated values into sparse features

Compositional transformations can reasonably introduce phenotype-associated values into sparse features

Advances in Research on the Relationship between Vaginal Microbiota and Adverse Pregnancy Outcomes and Gynecological Diseases

Draft genome sequences of Lactobacillus mulieris strains isolated from the female urinary tract

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