An Adaptive Multivariate Two-Sample Test With Application to Microbiome Differential Abundance Analysis

Differential abundance analysis is a crucial task in many microbiome studies, where the central goal is to identify microbiome taxa associated with certain biological or clinical conditions. There are two different modes of microbiome differential abundance analysis: the individual-based univariate differential abundance analysis and the group-based multivariate differential abundance analysis. The univariate analysis identifies differentially abundant microbiome taxa subject to multiple correction under certain statistical error measurements such as false discovery rate, which is typically complicated by the high-dimensionality of taxa and complex correlation structure among taxa. The multivariate analysis evaluates the overall shift in the abundance of microbiome composition between two conditions, which provides useful preliminary differential information for the necessity of follow-up validation studies. In this paper, we present a novel Adaptive multivariate two-sample test for Microbiome Differential Analysis (AMDA) to examine whether the composition of a taxa-set are different between two conditions. Our simulation studies and real data applications demonstrated that the AMDA test was often more powerful than several competing methods while preserving the correct type I error rate. A free implementation of our AMDA method in R software is available at https://github.com/xyz5074/AMDA

Evolution of the facial skin microbiome during puberty in normal and acne skin.

BackgroundThe composition of the skin microbiome varies from infancy to adulthood and becomes most stable in adulthood. Adult acne patients harbour an 'acne microbiome' dominated by specific strains of Cutibacterium acnes. However, the precise timing of skin microbiome evolution, the development of the acne microbiome, and the shift to virulent C. acnes strain composition during puberty is unknown.ObjectivesWe performed a cross-sectional pilot study in a paediatric population to understand how and when the skin microbiome composition transitions during puberty and whether a distinct 'acne microbiome' emerges in paediatric subjects.MethodsForty-eight volunteers including males and females, ages 7-17 years, with and without acne were enrolled and evaluated for pubertal development using the Tanner staging criteria. Sebum levels were measured, and skin microbiota were collected by sterile swab on the subject's forehead. DNA was sequenced by whole genome shotgun sequencing.ResultsA significant shift in microbial diversity emerged between early (T1-T2) and late (T3-T5) stages of puberty, coinciding with increased sebum production on the face. The overall relative abundance of C. acnes in both normal and acne skin increased during puberty and individual C. acnes strains were uniquely affected by pubertal stage and the presence of acne. Further, an acne microbiome signature associated with unique C. acnes strain composition and metabolic activity emerges in late puberty in those with acne. This unique C. acnes strain composition is predicted to have increased porphyrin production, which may contribute to skin inflammation.ConclusionsOur data suggest that the stage of pubertal development influences skin microbiome composition. As children mature, a distinct acne microbiome composition emerges in those with acne. Understanding how both puberty and acne influence the microbiome may support novel therapeutic strategies to combat acne in the paediatric population

Treatment response to isotretinoin correlates with specific shifts in Cutibacterium acnes strain composition within the follicular microbiome

There are no drugs as effective as isotretinoin for acne. Deciphering the changes in the microbiome induced by isotretinoin in the pilosebaceous follicle of successfully treated patients can pave the way to identify novel therapeutic alternatives. We determined how the follicular microbiome changes with isotretinoin and identified which alterations correlate with a successful treatment response. Whole genome sequencing was done on casts from facial follicles of acne patients sampled before, during and after isotretinoin treatment. Alterations in the microbiome were assessed and correlated with treatment response at 20 weeks as defined as a 2-grade improvement in global assessment score. We investigated the α-diversity, β-diversity, relative abundance of individual taxa, Cutibacterium acnes strain composition and bacterial metabolic profiles with a computational approach. We found that increased β-diversity of the microbiome coincides with a successful treatment response to isotretinoin at 20 weeks. Isotretinoin selectively altered C. acnes strain diversity in SLST A and D clusters, with increased diversity in D1 strains correlating with a successful clinical response. Isotretinoin significantly decreased the prevalence of KEGG Ontology (KO) terms associated with four distinct metabolic pathways inferring that follicular microbes may have limited capacity for growth or survival following treatment. Importantly, these alterations in microbial composition or metabolic profiles were not observed in patients that failed to achieve a successful response at 20 weeks. Alternative approaches to recapitulate this shift in the balance of C. acnes strains and microbiome metabolic function within the follicle may be beneficial in the future treatment of acne

Treatment response to isotretinoin correlates with specific shifts in Cutibacterium acnes strain composition within the follicular microbiome.

There are no drugs as effective as isotretinoin for acne. Deciphering the changes in the microbiome induced by isotretinoin in the pilosebaceous follicle of successfully treated patients can pave the way to identify novel therapeutic alternatives. We determined how the follicular microbiome changes with isotretinoin and identified which alterations correlate with a successful treatment response. Whole genome sequencing was done on casts from facial follicles of acne patients sampled before, during and after isotretinoin treatment. Alterations in the microbiome were assessed and correlated with treatment response at 20 weeks as defined as a 2-grade improvement in global assessment score. We investigated the α-diversity, β-diversity, relative abundance of individual taxa, Cutibacterium acnes strain composition and bacterial metabolic profiles with a computational approach. We found that increased β-diversity of the microbiome coincides with a successful treatment response to isotretinoin at 20 weeks. Isotretinoin selectively altered C. acnes strain diversity in SLST A and D clusters, with increased diversity in D1 strains correlating with a successful clinical response. Isotretinoin significantly decreased the prevalence of KEGG Ontology (KO) terms associated with four distinct metabolic pathways inferring that follicular microbes may have limited capacity for growth or survival following treatment. Importantly, these alterations in microbial composition or metabolic profiles were not observed in patients that failed to achieve a successful response at 20 weeks. Alternative approaches to recapitulate this shift in the balance of C. acnes strains and microbiome metabolic function within the follicle may be beneficial in the future treatment of acne