Exploring the Vaginal Microbiome and Intravaginal Practices in Postmenopausal Women.

BACKGROUND: Evidence suggests that intravaginal practices (IVPs) women use to cleanse their vagina or enhance sexual pleasure may be associated with unhealthy changes in the vaginal microbiome (VM). However, the effects of these practices in postmenopausal women are unknown. OBJECTIVES: The objective of this pilot study was to characterize the VM communities of postmenopausal women, identify types and frequency of IVPs, and explore associations between the VM and IVPs in postmenopausal women. METHODS: We analyzed the VM data of 21 postmenopausal women in Atlanta, Georgia, from vaginal swabs collected at a routine gynecological visit. 16S rRNA gene sequencing in the V3-V4 region was used to characterize the VM. In addition, we described the IVPs of these women, identified by using our newly developed instrument: the Vaginal Cleansing Practices Questionnaire. The associations between the VM and IVPs were explored by comparing the alpha diversities, beta diversities, and the relative abundances at both the community level and individual genus level. RESULTS: The most abundant known bacterial genus found in the VM samples was Lactobacillus (35.7%), followed by Prevotella (21.4%). Eleven women (52%) reported using at least one type of IVP since menopause. The most common type of IVP was soap and water to clean inside the vagina. The use of IVPs was not associated with any alpha diversity metric, including Shannon index, inverse Simpson index, and Chao1 index; beta diversity metric, including Bray-Curtis and Jaccard distances; nor relative abundances at the community and individual genus level. Sociodemographic factors were also not associated with any alpha diversity metric. DISCUSSION: Clinicians must assess IVPs and other vaginal and sexual hygiene practices of women of all ages to educate and promote healthy behaviors. More than half of the postmenopausal women in this pilot study use IVPs. Understanding the reasoning behind participants' use of IVPs and their perceptions of the possible effects of these practices will require further research. Although the small sample did not show associations with the VM, more extensive studies are warranted.

Genome-defined African ancestry is associated with distinct mutations and worse survival in patients with diffuse large B-cell lymphoma.

BACKGROUND: Significant racial differences have been observed in the incidence and clinical outcomes of diffuse large B-cell lymphoma (DLBCL) in the United States, but to the authors' knowledge it remains unclear whether genomic differences contribute to these disparities. METHODS: To understand the influences of genetic ancestry on tumor genomic alterations, the authors estimated the genetic ancestry of 1001 previously described patients with DLBCL using unsupervised model-based Admixture global ancestry analysis applied to exome sequencing data and examined the mutational profile of 150 DLBCL driver genes in tumors obtained from this cohort. RESULTS: Global ancestry prediction identified 619 patients with >90% European ancestry, 81 patients with >90% African ancestry, and 50 patients with >90% Asian ancestry. Compared with patients with DLBCL with European ancestry, patients with African ancestry were aged >10 years younger at the time of diagnosis and were more likely to present with B symptoms, elevated serum lactate dehydrogenase, extranodal disease, and advanced stage disease. Patients with African ancestry demonstrated worse overall survival compared with patients with European ancestry (median, 4.9 years vs 8.8 years; P = .04). Recurrent mutations of MLL2 (KMT2D), HIST1H1E, MYD88, BCL2, and PIM1 were found across all ancestry groups, suggesting shared mechanisms underlying tumor biology. The authors also identified 6 DLBCL driver genes that were more commonly mutated in patients with African ancestry compared with patients with European ancestry: ATM (21.0% vs 7.75%; P < .001), MGA (19.7% vs 5.33%; P < .001), SETD2 (17.3% vs 5.17%; P < .001), TET2 (12.3% vs 5.82%; P = .029), MLL3 (KMT2C) (11.1% vs 4.36%; P = .013), and DNMT3A (11.1% vs 4.52%; P = .016). CONCLUSIONS: Distinct prevalence and patterns of mutation highlight an important difference in the mutational landscapes of DLBCL arising in different ancestry groups. To the authors' knowledge, the results of the current study provide the first-ever characterization of genetic alterations among patients with African descent who are diagnosed with DLBCL.