A Spatial Omnibus Test (SPOT) for Spatial Proteomic Data

Spatial proteomics can reveal the spatial organization of immune cells in the tumor immune microenvironment. Relating measures of spatial clustering, such as Ripley's K or Besag's L, to patient outcomes may offer important clinical insights. However, these measures require pre-specifying a radius in which to quantify clustering, yet no consensus exists on the optimal radius which may be context-specific. We propose a SPatial Omnibus Test (SPOT) which conducts this analysis across a range of candidate radii. At each radius, SPOT evaluates the association between the spatial summary and outcome, adjusting for confounders. SPOT then aggregates results across radii using the Cauchy combination test, yielding an omnibus p-value characterizing the overall degree of association. Using simulations, we verify that the type I error rate is controlled and show SPOT can be more powerful than alternatives. We also apply SPOT to an ovarian cancer study. An R package and tutorial is provided at https://github.com/sarahsamorodnitsky/SPOT.

Do Genetic Variants Modify the Effect of Smoking on Risk of Preeclampsia in Pregnancy?

OBJECTIVE

 Maternal smoking is associated with as much as a 50% reduced risk of preeclampsia, despite increasing risk of other poor pregnancy outcomes that often co-occur with preeclampsia, such as preterm birth and fetal growth restriction. Researchers have long sought to understand whether this perplexing association is biologically based, or a result of noncausal mechanisms. We examined whether smoking-response genes modify the smoking-preeclampsia association to investigate potential biological explanations.

STUDY DESIGN

 We conducted a nested case-control study within the Norwegian Mother, Father and Child Birth Cohort (1999-2008) of 2,596 mother-child dyads. We used family-based log-linear Poisson regression to examine modification of the maternal smoking-preeclampsia relationship by maternal and fetal single nucleotide polymorphisms involved in cellular processes related to components of cigarette smoke (n = 1,915 with minor allele frequency ≥10%). We further investigated the influence of smoking cessation during pregnancy.

RESULTS

 Three polymorphisms showed overall (p < 0.001) multiplicative interaction between smoking and maternal genotype. For rs3765692 (TP73) and rs10770343 (PIK3C2G), protection associated with smoking was reduced with two maternal copies of the risk allele and was stronger in continuers than quitters (interaction p = 0.02 for both loci, based on testing 3-level smoking by 3-level genotype). For rs2278361 (APAF1) the inverse smoking-preeclampsia association was eliminated by the presence of a single risk allele, and again the trend was stronger in continuers than in quitters (interaction p = 0.01).

CONCLUSION

 Evidence for gene-smoking interaction was limited, but differences by smoking cessation warrant further investigation. We demonstrate the potential utility of expanded dyad methods and gene-environment interaction analyses for outcomes with complex relationships between maternal and fetal genotypes and exposures.

KEY POINTS

· Maternal and fetal genotype may differentially influence preeclampsia.. · Smoking-related genes did not strongly modify smoking-preeclampsia association.. · Smoking cessation reduced strength of gene by smoking interactions..

Limitation of permutation-based differential correlation analysis

The comparison of biological systems, through the analysis of molecular changes under different conditions, has played a crucial role in the progress of modern biological science. Specifically, differential correlation analysis (DCA) has been employed to determine whether relationships between genomic features differ across conditions or outcomes. Because ascertaining the null distribution of test statistics to capture variations in correlation is challenging, several DCA methods utilize permutation which can loosen parametric (e.g., normality) assumptions. However, permutation is often problematic for DCA due to violating the assumption that samples are exchangeable under the null. Here, we examine the limitations of permutation-based DCA and investigate instances where the permutation-based DCA exhibits poor performance. Experimental results show that the permutation-based DCA often fails to control the type I error under the null hypothesis of equal correlation structures.

Ipilimumab with or without nivolumab in PD-1 or PD-L1 blockade refractory metastatic melanoma: a randomized phase 2 trial

In this randomized phase 2 trial, blockade of cytotoxic T-lymphocyte protein 4 (CTLA-4) with continuation of programmed death protein 1 (PD-1) blockade in patients with metastatic melanoma who had received front-line anti-PD-1 or therapy against programmed cell death 1 ligand 1 and whose tumors progressed was tested in comparison with CTLA-4 blockade alone. Ninety-two eligible patients were randomly assigned in a 3:1 ratio to receive the combination of ipilimumab and nivolumab, or ipilimumab alone. The primary endpoint was progression-free survival. Secondary endpoints included the difference in CD8 T cell infiltrate among responding and nonresponding tumors, objective response rate, overall survival and toxicity. The combination of nivolumab and ipilimumab resulted in a statistically significant improvement in progression-free survival over ipilimumab (hazard ratio = 0.63, 90% confidence interval (CI) = 0.41-0.97, one-sided P = 0.04). Objective response rates were 28% (90% CI = 19-38%) and 9% (90% CI = 2-25%), respectively (one-sided P = 0.05). Grade 3 or higher treatment-related adverse events occurred in 57% and 35% of patients, respectively, which is consistent with the known toxicity profile of these regimens. The change in intratumoral CD8 T cell density observed in the present analysis did not reach statistical significance to support the formal hypothesis tested as a secondary endpoint. In conclusion, primary resistance to PD-1 blockade therapy can be reversed in some patients with the combination of CTLA-4 and PD-1 blockade. Clinicaltrials.gov identifier: NCT03033576 .

The intratumor microbiome is associated with microsatellite instability

Intratumoral microbes may have multifunctional roles in carcinogenesis. Microsatellite instability (MSI) is associated with higher tumor immunity and mutational burden. Using whole transcriptome and whole genome sequencing microbial abundance data, we investigated associations of intratumoral microbes with MSI, survival, and MSI-relevant tumor molecular characteristics across multiple cancer types including colorectal cancer (CRC), stomach adenocarcinoma, and endometrial carcinoma. Among 451 CRC patients, our key finding was strong associations of multiple CRC-associated genera, including Dialister and Casatella, with MSI. Dialister and Casatella abundance was associated with improved overall survival (hazard ratiomortality = 0.56, 95% confidence interval = 0.34 to 0.92, and hazard ratiomortality = 0.44, 95% confidence interval = 0.27 to 0.72), respectively, comparing higher relative to lower quantiles. Multiple intratumor microbes were associated with immune genes and tumor mutational burden. Diversity of oral cavity-originating microbes was also associated with MSI among CRC and stomach adenocarcinoma patients. Overall, our findings suggest the intratumor microbiota may differ by MSI status and play a role in influencing the tumor microenvironment.

Vaginal Microbiome Metagenome Inference Accuracy: Differential Measurement Error according to Community Composition

Several studies have compared metagenome inference performance in different human body sites; however, none specifically reported on the vaginal microbiome. Findings from other body sites cannot easily be generalized to the vaginal microbiome due to unique features of vaginal microbial ecology, and investigators seeking to use metagenome inference in vaginal microbiome research are "flying blind" with respect to potential bias these methods may introduce into analyses. We compared the performance of PICRUSt2 and Tax4Fun2 using paired 16S rRNA gene amplicon sequencing and whole-metagenome sequencing data from vaginal samples from 72 pregnant individuals enrolled in the Pregnancy, Infection, and Nutrition (PIN) cohort. Participants were selected from those with known birth outcomes and adequate 16S rRNA gene amplicon sequencing data in a case-control design. Cases experienced early preterm birth (<32 weeks of gestation), and controls experienced term birth (37 to 41 weeks of gestation). PICRUSt2 and Tax4Fun2 performed modestly overall (median Spearman correlation coefficients between observed and predicted KEGG ortholog [KO] relative abundances of 0.20 and 0.22, respectively). Both methods performed best among Lactobacillus crispatus-dominated vaginal microbiotas (median Spearman correlation coefficients of 0.24 and 0.25, respectively) and worst among Lactobacillus iners-dominated microbiotas (median Spearman correlation coefficients of 0.06 and 0.11, respectively). The same pattern was observed when evaluating correlations between univariable hypothesis test P values generated with observed and predicted metagenome data. Differential metagenome inference performance across vaginal microbiota community types can be considered differential measurement error, which often causes differential misclassification. As such, metagenome inference will introduce hard-to-predict bias (toward or away from the null) in vaginal microbiome research. IMPORTANCE Compared to taxonomic composition, the functional potential within a bacterial community is more relevant to establishing mechanistic understandings and causal relationships between the microbiome and health outcomes. Metagenome inference attempts to bridge the gap between 16S rRNA gene amplicon sequencing and whole-metagenome sequencing by predicting a microbiome's gene content based on its taxonomic composition and annotated genome sequences of its members. Metagenome inference methods have been evaluated primarily among gut samples, where they appear to perform fairly well. Here, we show that metagenome inference performance is markedly worse for the vaginal microbiome and that performance varies across common vaginal microbiome community types. Because these community types are associated with sexual and reproductive outcomes, differential metagenome inference performance will bias vaginal microbiome studies, obscuring relationships of interest. Results from such studies should be interpreted with substantial caution and the understanding that they may over- or underestimate associations with metagenome content.

Kernel-based genetic association analysis for microbiome phenotypes identifies host genetic drivers of beta-diversity

BACKGROUND

Understanding human genetic influences on the gut microbiota helps elucidate the mechanisms by which genetics may influence health outcomes. Typical microbiome genome-wide association studies (GWAS) marginally assess the association between individual genetic variants and individual microbial taxa. We propose a novel approach, the covariate-adjusted kernel RV (KRV) framework, to map genetic variants associated with microbiome beta-diversity, which focuses on overall shifts in the microbiota. The KRV framework evaluates the association between genetics and microbes by comparing similarity in genetic profiles, based on groups of variants at the gene level, to similarity in microbiome profiles, based on the overall microbiome composition, across all pairs of individuals. By reducing the multiple-testing burden and capturing intrinsic structure within the genetic and microbiome data, the KRV framework has the potential of improving statistical power in microbiome GWAS.

RESULTS

We apply the covariate-adjusted KRV to the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) in a two-stage (first gene-level, then variant-level) genome-wide association analysis for gut microbiome beta-diversity. We have identified an immunity-related gene, IL23R, reported in a previous microbiome genetic association study and discovered 3 other novel genes, 2 of which are involved in immune functions or autoimmune disorders. In addition, simulation studies show that the covariate-adjusted KRV has a greater power than other microbiome GWAS methods that rely on univariate microbiome phenotypes across a range of scenarios.

CONCLUSIONS

Our findings highlight the value of the covariate-adjusted KRV as a powerful microbiome GWAS approach and support an important role of immunity-related genes in shaping the gut microbiome composition. Video Abstract.

Abstract 3275: Combination of talimogene laherparepvec (T-VEC) with pembrolizumab (pembro) in advanced melanoma patients following progression on a prior PD-1 inhibitor: SWOG S1607

We hypothesize that a significant number of patients do not respond to PD-1/L1 blockade because there are no pre-existing tumor antigen-specific T-cells, and this can be addressed by combination therapy with an oncolytic virus such as T-VEC. S1607 is a single arm Phase 2 study of T-VEC plus pembro in patients with advanced melanoma after PD-1/L1 inhibitor progression. The primary endpoint is ORR by modified RECIST (progression at the first follow-up disease assessment had to be confirmed). Secondary endpoints include durable response rate (response ≥ 6 months), ORR in injected, non-visceral non-injected, and visceral lesions, PFS, OS and toxicity. In Cohort A patients must have at least one measurable visceral lesion; in Cohort B patients must not have any visceral lesions. Each cohort had an independent accrual goal with a 2-stage design. All received intratumoral T-VEC and pembro 200mg IV every 21 days. Tumor biopsy and research blood are taken at baseline and on Day 28 (both injected and non-injected lesions). Tumor assessments are performed every 12 weeks for up to 2 years. 38 evaluable patients were enrolled. As of July 26, 2022, the median follow up was 28 months. Treatment was well tolerated, with 5/38 (13%) grade 3 AE (no grade 4/5) including injection site reactions, lymphocyte count decrease, and hypoxia. Cohort A was closed after stage I (n=11) with no confirmed responses. In Cohort B (n=27), there were 7 confirmed responses (26%; 2 CR, 5 PR; this rejected H0: ORR = 10%, p=0.01). Clinical outcomes are summarized in Table 1. Baseline tumor mutational burden from 17 patients in Cohort B were not different between responder vs non-responders (p=0.96). Translational study is ongoing for pharmacodynamic confirmation. T-VEC plus pembro in melanoma patients who have progressed on prior anti-PD1/L1 therapy has efficacy in the subset of melanoma patients who have non-visceral metastases.

Table 1 Cohort A (Visceral) Cohort B(Non-Visceral) N (%; 95% CI) 11 27 Confirmed PR + CR 0 (0%; 0%-28%) 7 (26%; 11%-46%) Confirmed + Unconfirmed 1 (9%; 0%-41%) 9 (33%; 17%-54%) Durable response 0 (0%; 0%-28%) 4 (15%; 4%-34%) Median PFS in months 2.1 (0.7-5.5) 2.3 (1.9-6.2) INJECTED LESIONS 11 27 Confirmed PR + CR 0 (0%; 0%-28%) 6 (22%; 9%-42%) Confirmed + Unconfirmed, PR + CR 1 (9%; 0%-41%) 8 (30%; 14%-50%) NON-INJECTED, NON-VISCERAL LESIONS 8 19 Confirmed PR + CR 0 (0%; 0%-37%) 3 (16%; 3%-40%) Confirmed + Unconfirmed, PR + CR 0 (0%; 0%-37%) 5 (26%; 9%-51%) VISCERAL LESIONS 11 Confirmed PR + CR 0 (0%; 0%-28%) Confirmed + Unconfirmed, PR + CR 1 (9%; 0%-41%) ACQUIRED RESISTANCE 3 2 Confirmed PR + CR 0 (0%; 0%-71%) 2 (100%; 16%-100%) Confirmed + Unconfirmed, PR + CR 0 (0%; 0%-71%) 2 (100%; 16%-100%) Median PFS in months 2.1 (2.0-4.1) NR (8.0-∞) PRIMARY RESISTANCE 8 25 Confirmed PR + CR 0 (0%; 0%-37%) 5 (20%; 7%-41%) Confirmed + Unconfirmed, PR + CR 1 (13%; 0%-53%) 7 (28%; 12%-49%) Median PFS in months 1.8 (0.3-6.2) 2.1 (1.9-3.3)

Citation Format: Siwen Hu-Lieskovan, James Moon, John Hyngstrom, Katie M. Campbell, Gino K. In, Theodore F. Logan, Kari L. Kendra, Ding M. Wang, Douglas B. Johnson, Gary C. Doolittle, Alan Tan, Ann W. Silk, Kenneth F. Grossmann, Christopher W. Ryan, Sapna P. Patel, Shay Bellasea, Michael C. Wu, John M. Kirkwood, Helen X. Chen, Antoni Ribas. Combination of talimogene laherparepvec (T-VEC) with pembrolizumab (pembro) in advanced melanoma patients following progression on a prior PD-1 inhibitor: SWOG S1607 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3275.

Accommodating multiple potential normalizations in microbiome associations studies

BACKGROUND

Microbial communities are known to be closely related to many diseases, such as obesity and HIV, and it is of interest to identify differentially abundant microbial species between two or more environments. Since the abundances or counts of microbial species usually have different scales and suffer from zero-inflation or over-dispersion, normalization is a critical step before conducting differential abundance analysis. Several normalization approaches have been proposed, but it is difficult to optimize the characterization of the true relationship between taxa and interesting outcomes.  RESULTS: To avoid the challenge of picking an optimal normalization and accommodate the advantages of several normalization strategies, we propose an omnibus approach. Our approach is based on a Cauchy combination test, which is flexible and powerful by aggregating individual p values. We also consider a truncated test statistic to prevent substantial power loss. We experiment with a basic linear regression model as well as recently proposed powerful association tests for microbiome data and compare the performance of the omnibus approach with individual normalization approaches. Experimental results show that, regardless of simulation settings, the new approach exhibits power that is close to the best normalization strategy, while controling the type I error well.  CONCLUSIONS: The proposed omnibus test releases researchers from choosing among various normalization methods and it is an aggregated method that provides the powerful result to the underlying optimal normalization, which requires tedious trial and error. While the power may not exceed the best normalization, it is always much better than using a poor choice of normalization.

A fast kernel independence test for cluster-correlated data

Cluster-correlated data receives a lot of attention in biomedical and longitudinal studies and it is of interest to assess the generalized dependence between two multivariate variables under the cluster-correlated structure. The Hilbert-Schmidt independence criterion (HSIC) is a powerful kernel-based test statistic that captures various dependence between two random vectors and can be applied to an arbitrary non-Euclidean domain. However, the existing HSIC is not directly applicable to cluster-correlated data. Therefore, we propose a HSIC-based test of independence for cluster-correlated data. The new test statistic combines kernel information so that the dependence structure in each cluster is fully considered and exhibits good performance under high dimensions. Moreover, a rapid p value approximation makes the new test fast applicable to large datasets. Numerical studies show that the new approach performs well in both synthetic and real world data.

Batch effects removal for microbiome data via conditional quantile regression

Batch effects in microbiome data arise from differential processing of specimens and can lead to spurious findings and obscure true signals. Strategies designed for genomic data to mitigate batch effects usually fail to address the zero-inflated and over-dispersed microbiome data. Most strategies tailored for microbiome data are restricted to association testing or specialized study designs, failing to allow other analytic goals or general designs. Here, we develop the Conditional Quantile Regression (ConQuR) approach to remove microbiome batch effects using a two-part quantile regression model. ConQuR is a comprehensive method that accommodates the complex distributions of microbial read counts by non-parametric modeling, and it generates batch-removed zero-inflated read counts that can be used in and benefit usual subsequent analyses. We apply ConQuR to simulated and real microbiome datasets and demonstrate its advantages in removing batch effects while preserving the signals of interest.

Abstract CT013: S1616: Ipilimumab plus nivolumab versus ipilimumab alone in patients with metastatic or unresectable melanoma that did not respond to anti-PD-1 therapy

Background: Patients with advanced melanoma primarily refractory to single agent PD-1 blockade therapy have an option of receiving the CTLA-4 blocking antibody ipilimumab, but if ipilimumab should be given as a single agent or in combination with the anti-PD-1 nivolumab has not been established prospectively.

Methods: Patients aged &gt;18 with metastatic or unresectable melanoma without objective response to anti-PD-1 therapy given without CTLA-4 therapy were randomized 3:1 to receive either ipilimumab 3mg/kg + nivolumab 1mg/kg q3 wks x4 cycles followed by nivolumab 480mg q4wks (ipi/nivo) up to 2 years, or ipilimumab 3mg/kg q3weeks x4 cycles (ipi). Additional key eligibility criteria included ECOG Performance Statue (PS) 0-2, no active central nervous system metastases, autoimmune disease, or need for steroids at doses of &gt;10 mg of prednisone or the equivalent. The primary endpoint was progression free survival (PFS). Disease assessments were performed every 12 weeks until progression. Secondary endpoints included overall survival (OS), objective response rate (ORR), and toxicity. All patients were to submit a fresh tumor biopsy and whole blood for correlative endpoints prior to cycle 1 and again at week 5.

Results: 92 eligible patients were enrolled, 69 to ipi/nivo, 23 to ipi. Median age was 64 and 69 in the ipi/nivo and ipi arm respectively. 67% and 65% were male. 65% of patients in both arms had ECOG PS of 0. With a median follow up of 25.3 months, the hazard ratio (HR) for PFS was 0.63 (90% CI 0.41, 0.97) with a statistically significant 1-sided p-value of 0.04 favoring ipi/nivo. The 6-month PFS estimates were 34% (90% CI: 25%-44%) and 13% (4%-27%) for ipi/nivo and ipi respectively. ORR was 28% for ipi/nivo (95% CI 17%-40%) and 9% for ipi (95% CI: 3%-34%). With a median follow up of 24.4 months, 39/69 patients in the ipi/nivo arm and 12/23 patients in the ipi arm had died. 12-month OS was 63% (90% CI 52%-72%) in the ipi/nivo arm and 57% (38%-71%) months in the ipi arm. HR for OS was 0.94 (90% CI 0.54, 1.62) in favor of ipi/nivo with a p-value of 0.42. Adverse event rates were similar in both arms. One treatment related death was reported in the ipi/nivo arm due to disseminated intravascular coagulation and one treatment related death was reported in the ipi arm due to colonic perforation.

Conclusions: This is the first prospective randomized study comparing ipi/nivo to ipi alone in patients with melanoma without response to anti-PD1 therapy. Ipi/nivo was associated with improved progression free survival as compared to ipi alone. The response rate of 28% to ipi/nivo as compared to 9% to ipi alone implies that patients who do not respond to PD-1 alone can be rescued with ipi/nivo. The toxicity of combination therapy was manageable. Ipi/nivo is an appropriate standard in patients with metastatic melanoma who do not respond to single-agent PD-1 therapy. ClinicalTrials.gov Identifier: NCT03033576

Funding: NIH/NCI grants: U10CA180888, U10CA180819, U10CA180821, U10CA180868; Other grants: SU2C-AACR-CT06-17

Citation Format: Ari M. Vanderwalde, James Moon, Kari Kendra, Nikhil I. Khushalani, Frances Collichio, Jeffrey A. Sosman, Alexandra Ikeguchi, Adrienne I. Victor, Thach-Giao Truong, Bartosz Chmielowski, David C. Portnoy, Michael C. Wu, Kenneth F. Grossmann, Antoni Ribas. S1616: Ipilimumab plus nivolumab versus ipilimumab alone in patients with metastatic or unresectable melanoma that did not respond to anti-PD-1 therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT013.

Phylogeny-guided microbiome OTU-specific association test (POST)

BACKGROUND

The relationship between host conditions and microbiome profiles, typically characterized by operational taxonomic units (OTUs), contains important information about the microbial role in human health. Traditional association testing frameworks are challenged by the high dimensionality and sparsity of typical microbiome profiles. Phylogenetic information is often incorporated to address these challenges with the assumption that evolutionarily similar taxa tend to behave similarly. However, this assumption may not always be valid due to the complex effects of microbes, and phylogenetic information should be incorporated in a data-supervised fashion.

RESULTS

In this work, we propose a local collapsing test called phylogeny-guided microbiome OTU-specific association test (POST). In POST, whether or not to borrow information and how much information to borrow from the neighboring OTUs in the phylogenetic tree are supervised by phylogenetic distance and the outcome-OTU association. POST is constructed under the kernel machine framework to accommodate complex OTU effects and extends kernel machine microbiome tests from community level to OTU level. Using simulation studies, we show that when the phylogenetic tree is informative, POST has better performance than existing OTU-level association tests. When the phylogenetic tree is not informative, POST achieves similar performance as existing methods. Finally, in real data applications on bacterial vaginosis and on preterm birth, we find that POST can identify similar or more outcome-associated OTUs that are of biological relevance compared to existing methods.

CONCLUSIONS

Using POST, we show that adaptively leveraging the phylogenetic information can enhance the selection performance of associated microbiome features by improving the overall true-positive and false-positive detection. We developed a user friendly R package POSTm which is freely available on CRAN ( https://CRAN.R-project.org/package=POSTm ). Video Abstract.

TCR-L: an analysis tool for evaluating the association between the T-cell receptor repertoire and clinical phenotypes

Background

T cell receptors (TCRs) play critical roles in adaptive immune responses, and recent advances in genome technology have made it possible to examine the T cell receptor (TCR) repertoire at the individual sequence level. The analysis of the TCR repertoire with respect to clinical phenotypes can yield novel insights into the etiology and progression of immune-mediated diseases. However, methods for association analysis of the TCR repertoire have not been well developed.

Methods

We introduce an analysis tool, TCR-L, for evaluating the association between the TCR repertoire and disease outcomes. Our approach is developed under a mixed effect modeling, where the fixed effect represents features that can be explicitly extracted from TCR sequences while the random effect represents features that are hidden in TCR sequences and are difficult to be extracted. Statistical tests are developed to examine the two types of effects independently, and then the p values are combined.

Results

Simulation studies demonstrate that (1) the proposed approach can control the type I error well; and (2) the power of the proposed approach is greater than approaches that consider fixed effect only or random effect only. The analysis of real data from a skin cutaneous melanoma study identifies an association between the TCR repertoire and the short/long-term survival of patients.

Conclusion

The TCR-L can accommodate features that can be extracted as well as features that are hidden in TCR sequences. TCR-L provides a powerful approach for identifying association between TCR repertoire and disease outcomes.

Impact of Topical Interventions on the Vaginal Microbiota and Metabolome in Postmenopausal Women: A Secondary Analysis of a Randomized Clinical Trial

IMPORTANCE

Postmenopausal women with genitourinary symptoms of menopause are often prescribed vaginal estradiol or moisturizer for symptom improvement, but the impact of these treatments on the local microenvironment is poorly understood.

OBJECTIVE

To compare changes in the vaginal microbiota, metabolome, and pH among women using low-dose vaginal estradiol tablet or low pH moisturizer gel for 12-weeks vs low pH placebo.

DESIGN, SETTING, AND PARTICIPANTS

This is a post hoc prespecified secondary analysis of a 12-week multicenter randomized clinical trial among postmenopausal women with moderate to severe genitourinary symptoms. Women were enrolled between April 2016 and February 2017; final follow-up visits occurred in April 2017. Data were analyzed from November 2018 to July 2021.

INTERVENTIONS

Ten-μg vaginal estradiol plus placebo gel vs placebo tablet plus vaginal moisturizer vs dual placebo.

MAIN OUTCOMES AND MEASURES

The main outcome measures were changes in the diversity and composition of the vaginal microbiota, changes in the metabolome, and pH.

RESULTS

Of 302 postmenopausal women from the parent trial, 144 women (mean [SD] age, 61 [4] years) were included in this analysis. After 12 weeks, the microbiota was dominated with Lactobacillus and Bifidobacterium communities among 36 women (80%) in the estradiol group, compared with 16 women (36%) using moisturizer and 13 women (26%) using placebo (P < .001). The composition of vaginal fluid metabolites also varied after 12-weeks among women in the estradiol group with significant changes in 90 of 171 metabolites measured (53%) (P < .001), including an increase in lactate. The 12-week pH among women in the estradiol group was lower vs placebo (median [IQR] pH, 5 [4.5-6.0] vs 6 [5.5-7.0]; P = .005) but not the moisturizer group vs placebo (median [IQR] pH, 6 [5.5-6.5]; P = .28). There was a decrease in pH from baseline to 12-weeks within the moisturizer (median [IQR] pH, 7 [6.0-7.5] vs 6 [5.5-6.5]; P < .001) and placebo (median [IQR] pH, 7 [7.0-7.5] vs 6 [5.5-7.0]; P < .001) groups. Women with high-diversity bacterial communities at baseline exhibited greater median change in pH compared with women with low-diversity communities (median [IQR] change, -1 [-2 to -0.5] vs -0.3 [-1.1 to 0], P = .007).

CONCLUSIONS AND RELEVANCE

This secondary analysis of a randomized clinical trial found that use of vaginal estradiol tablets resulted in substantial changes in the vaginal microbiota and metabolome with a lowering in pH, particularly in women with high-diversity bacterial communities at baseline. Low pH moisturizer or placebo did not significantly impact the vaginal microbiota or metabolome despite lowering the vaginal pH. Estradiol use may offer additional genitourinary health benefits to postmenopausal women.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02516202.

Testing microbiome association using integrated quantile regression models

MOTIVATION

Most existing microbiome association analyses focus on the association between microbiome and conditional mean of health or disease-related outcomes, and within this vein, vast computational tools and methods have been devised for standard binary or continuous outcomes. However, these methods tend to be limited either when the underlying microbiome-outcome association occurs somewhere other than the mean level, or when distribution of the outcome variable is irregular (e.g. zero-inflated or mixtures) such that conditional outcome mean is less meaningful. We address this gap by investigating association analysis between microbiome compositions and conditional outcome quantiles.

RESULTS

We introduce a new association analysis tool named MiRKAT-IQ within the Microbiome Regression-based Kernel Association Test framework using Integrated Quantile regression models to examine the association between microbiome and the distribution of outcome. For an individual quantile, we utilize the existing kernel machine regression framework to examine the association between that conditional outcome quantile and a group of microbial features (e.g. microbiome community compositions). Then, the goal of examining microbiome association with the whole outcome distribution is achieved by integrating all outcome conditional quantiles over a process, and thus our new MiRKAT-IQ test is robust to both the location of association signals (e.g. mean, variance, median) and the heterogeneous distribution of the outcome. Extensive numerical simulation studies have been conducted to show the validity of the new MiRKAT-IQ test. We demonstrate the potential usefulness of MiRKAT-IQ with applications to actual biological data collected from a previous microbiome study.

AVAILABILITY AND IMPLEMENTATION

R codes to implement the proposed methodology is provided in the MiRKAT package, which is available on CRAN.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A Kernel-based Test of Independence for Cluster-correlated Data

The Hilbert-Schmidt Independence Criterion (HSIC) is a powerful kernel-based statistic for assessing the generalized dependence between two multivariate variables. However, independence testing based on the HSIC is not directly possible for cluster-correlated data. Such a correlation pattern among the observations arises in many practical situations, e.g., family-based and longitudinal data, and requires proper accommodation. Therefore, we propose a novel HSIC-based independence test to evaluate the dependence between two multivariate variables based on cluster-correlated data. Using the previously proposed empirical HSIC as our test statistic, we derive its asymptotic distribution under the null hypothesis of independence between the two variables but in the presence of sample correlation. Based on both simulation studies and real data analysis, we show that, with clustered data, our approach effectively controls type I error and has a higher statistical power than competing methods.

Deep ensemble learning over the microbial phylogenetic tree (DeepEn-Phy)

Successful prediction of clinical outcomes facilitates tailored diagnosis and treatment. The microbiome has been shown to be an important biomarker to predict host clinical outcomes. Further, the incorporation of microbial phylogeny, the evolutionary relationship among microbes, has been demonstrated to improve prediction accuracy. We propose a phylogeny-driven deep neural network (PhyNN) and develop an ensemble method, DeepEn-Phy, for host clinical outcome prediction. The method is designed to optimally extract features from phylogeny, thereby take full advantage of the information in phylogeny while harnessing the core principles of phylogeny (in contrast to taxonomy). We apply DeepEn-Phy to a real large microbiome data set to predict both categorical and continuous clinical outcomes. DeepEn-Phy demonstrates superior prediction performance to existing machine learning and deep learning approaches. Overall, DeepEn-Phy provides a new strategy for designing deep neural network architectures within the context of phylogeny-constrained microbiome data.

Powerful and robust non-parametric association testing for microbiome data via a zero-inflated quantile approach (ZINQ)

BACKGROUND

Identification of bacterial taxa associated with diseases, exposures, and other variables of interest offers a more comprehensive understanding of the role of microbes in many conditions. However, despite considerable research in statistical methods for association testing with microbiome data, approaches that are generally applicable remain elusive. Classical tests often do not accommodate the realities of microbiome data, leading to power loss. Approaches tailored for microbiome data depend highly upon the normalization strategies used to handle differential read depth and other data characteristics, and they often have unacceptably high false positive rates, generally due to unsatisfied distributional assumptions. On the other hand, many non-parametric tests suffer from loss of power and may also present difficulties in adjusting for potential covariates. Most extant approaches also fail in the presence of heterogeneous effects. The field needs new non-parametric approaches that are tailored to microbiome data, robust to distributional assumptions, and powerful under heterogeneous effects, while permitting adjustment for covariates.

METHODS

As an alternative to existing approaches, we propose a zero-inflated quantile approach (ZINQ), which uses a two-part quantile regression model to accommodate the zero inflation in microbiome data. For a given taxon, ZINQ consists of a valid test in logistic regression to model the zero counts, followed by a series of quantile rank-score based tests on multiple quantiles of the non-zero part with adjustment for the zero inflation. As a regression and quantile-based approach, the method is non-parametric and robust to irregular distributions, while providing an allowance for covariate adjustment. Since no distributional assumptions are made, ZINQ can be applied to data that has been processed under any normalization strategy.

RESULTS

Thorough simulations based on real data across a range of scenarios and application to real data sets show that ZINQ often has equivalent or higher power compared to existing tests even as it offers better control of false positives.

CONCLUSIONS

We present ZINQ, a quantile-based association test between microbiota and dichotomous or quantitative clinical variables, providing a powerful and robust alternative for the current microbiome differential abundance analysis. Video Abstract.

A Method for Subtype Analysis with Somatic Mutations

MOTIVATION

Cancer is a highly heterogeneous disease, and virtually all types of cancer have subtypes. Understanding the association between cancers subtypes and genetic variations is fundamental to the development of targeted therapies for patients. Somatic mutation plays important roles in tumor development and has emerged as a new type of genetic variations for studying the association with cancer subtypes. However, the low prevalence of individual mutations poses a tremendous challenge to the related statistical analysis.

RESULTS

In this article, we propose an approach, SASOM, for the association analysis of cancer subtypes with somatic mutations. Our approach tests the association between a set of somatic mutations (from a genetic pathway) and subtypes, while incorporating functional information of the mutations into the analysis. We further propose a robust p-value combination procedure, DAPC, to synthesize statistical significance from different sources. Simulation studies show that the proposed approach has correct type I error and tends to be more powerful than possible alternative methods. In a real data application, we examine the somatic mutations from a cutaneous melanoma dataset, and identify a genetic pathway that is associated with immune-related subtypes.

AVAILABILITY AND IMPLEMENTATION

The SASOM R package is available at https://github.com/rksyouyou/SASOM-pkg. R scripts and data are available at https://github.com/rksyouyou/SASOM-analysis.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Comparison of the Vaginal Microbiota in Postmenopausal Black and White Women

BACKGROUND

We compared vaginal microbial communities in postmenopausal black and white women.

METHODS

Shotgun sequencing of vaginal swabs from postmenopausal women self-identified as black or white was compared using MiRKAT.

RESULTS

Vaginal community dominance by Lactobacillus crispatus or Lactobacillusgasseri was more common in 44 postmenopausal black women (n = 12, 27%) than among 44 matched white women (n = 2, 5%; P = .01). No individual taxa were significantly more abundant in either group.

CONCLUSIONS

We identified small overall differences in vaginal microbial communities of black and white postmenopausal women. L. crispatus dominance was more common in black women.

CLINICAL TRIALS REGISTRATION

NCT02516202 (MsFLASH05) and NCT01418209 (MsFLASH03).

MiRKAT: kernel machine regression-based global association tests for the microbiome

SUMMARY

Distance-based tests of microbiome beta diversity are an integral part of many microbiome analyses. MiRKAT enables distance-based association testing with a wide variety of outcome types, including continuous, binary, censored time-to-event, multivariate, correlated and high-dimensional outcomes. Omnibus tests allow simultaneous consideration of multiple distance and dissimilarity measures, providing higher power across a range of simulation scenarios. Two measures of effect size, a modified R-squared coefficient and a kernel RV coefficient, are incorporated to allow comparison of effect sizes across multiple kernels.

AVAILABILITY AND IMPLEMENTATION

MiRKAT is available on CRAN as an R package.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Bacterial Communities Associated With Abnormal Nugent Score in Postmenopausal Versus Premenopausal Women

The Nugent score is the reference standard for bacterial vaginosis (BV) diagnosis but has not been validated in postmenopausal women. We compared relative abundances from 16S ribosomal RNA gene sequencing of vaginal microbiota with Nugent score in cohorts of premenopausal (n = 220) and postmenopausal (n = 144) women. In premenopausal women, 33 taxa were significantly correlated with Nugent score, including the classic BV-associated taxa Gardnerella, Atopobium, Sneathia, Megasphaera, and Prevotella. In postmenopausal women, 11 taxa were significantly associated with Nugent score, including Prevotella but no other BV-associated genera. High Nugent scores should not be used to infer BV in postmenopausal women.

Mutually suppressive roles of KMT2A and KDM5C in behaviour, neuronal structure, and histone H3K4 methylation

Histone H3 lysine 4 methylation (H3K4me) is extensively regulated by numerous writer and eraser enzymes in mammals. Nine H3K4me enzymes are associated with neurodevelopmental disorders to date, indicating their important roles in the brain. However, interplay among H3K4me enzymes during brain development remains largely unknown. Here, we show functional interactions of a writer-eraser duo, KMT2A and KDM5C, which are responsible for Wiedemann-Steiner Syndrome (WDSTS), and mental retardation X-linked syndromic Claes-Jensen type (MRXSCJ), respectively. Despite opposite enzymatic activities, the two mouse models deficient for either Kmt2a or Kdm5c shared reduced dendritic spines and increased aggression. Double mutation of Kmt2a and Kdm5c clearly reversed dendritic morphology, key behavioral traits including aggression, and partially corrected altered transcriptomes and H3K4me landscapes. Thus, our study uncovers common yet mutually suppressive aspects of the WDSTS and MRXSCJ models and provides a proof of principle for balancing a single writer-eraser pair to ameliorate their associated disorders.

Extra-vaginal Bacterial Colonization and Risk for Incident Bacterial Vaginosis in a Population of Women who Have Sex with Men

Background

Bacterial vaginosis (BV) is a common cause of vaginal discharge and associated with vaginal acquisition of BV-associated bacteria (BVAB).

Methods

We used quantitative polymerase chain reaction assays to determine whether presence or concentrations of BVAB in the mouth, anus, vagina, or labia before BV predict risk of incident BV in 72 women who have sex with men.

Results

Baseline vaginal and extra-vaginal colonization with Gardnerella spp, Megasphaera spp, Sneathia spp, BVAB-2, Dialister sp type 2, and other BVAB was more common among subjects with incident BV.

Conclusions

Prior colonization with BVAB is a consistent risk for BV.

Author Correction: Gut microbiome composition in the Hispanic Community Health Study/Study of Latinos is shaped by geographic relocation, environmental factors, and obesity

Following publication of the original paper [1], an error was reported in the third paragraph in the section "Analysis of GMB composition and its correlates" (page 3 of the PDF). The first sentence of the text should refer to Table 2, but mistakenly refers to Table 1.

Heavy Cannabis Use Associated With Reduction in Activated and Inflammatory Immune Cell Frequencies in Antiretroviral Therapy-Treated Human Immunodeficiency Virus-Infected Individuals

Background

Cannabis is a widely used drug in the United States, and the frequency of cannabis use in the human immunodeficiency virus (HIV)-infected population is disproportionately high. Previous human and macaque studies suggest that cannabis may have an impact on plasma viral load; however, the relationship between cannabis use and HIV-associated systemic inflammation and immune activation has not been well defined.

Methods

The impact of cannabis use on peripheral immune cell frequency, activation, and function was assessed in 198 HIV-infected, antiretroviral-treated individuals by flow cytometry. Individuals were categorized into heavy, medium, or occasional cannabis users or noncannabis users based on the amount of the cannabis metabolite 11-nor-carboxy-tetrahydrocannabinol (THC-COOH) detected in plasma by mass spectrometry.

Results

Heavy cannabis users had decreased frequencies of human leukocyte antigen (HLA)-DR+CD38+CD4+ and CD8+ T-cell frequencies, compared to frequencies of these cells in non-cannabis-using individuals. Heavy cannabis users had decreased frequencies of intermediate and nonclassical monocyte subsets, as well as decreased frequencies of interleukin 23- and tumor necrosis factor-α-producing antigen-presenting cells.

Conclusions

While the clinical implications are unclear, our findings suggest that cannabis use is associated with a potentially beneficial reduction in systemic inflammation and immune activation in the context of antiretroviral-treated HIV infection.

Gut microbiome composition in the Hispanic Community Health Study/Study of Latinos is shaped by geographic relocation, environmental factors, and obesity

BACKGROUND

Hispanics living in the USA may have unrecognized potential birthplace and lifestyle influences on the gut microbiome. We report a cross-sectional analysis of 1674 participants from four centers of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), aged 18 to 74 years old at recruitment.

RESULTS

Amplicon sequencing of 16S rRNA gene V4 and fungal ITS1 fragments from self-collected stool samples indicate that the host microbiome is determined by sociodemographic and migration-related variables. Those who relocate from Latin America to the USA at an early age have reductions in Prevotella to Bacteroides ratios that persist across the life course. Shannon index of alpha diversity in fungi and bacteria is low in those who relocate to the USA in early life. In contrast, those who relocate to the USA during adulthood, over 45 years old, have high bacterial and fungal diversity and high Prevotella to Bacteroides ratios, compared to USA-born and childhood arrivals. Low bacterial diversity is associated in turn with obesity. Contrasting with prior studies, our study of the Latino population shows increasing Prevotella to Bacteroides ratio with greater obesity. Taxa within Acidaminococcus, Megasphaera, Ruminococcaceae, Coriobacteriaceae, Clostridiales, Christensenellaceae, YS2 (Cyanobacteria), and Victivallaceae are significantly associated with both obesity and earlier exposure to the USA, while Oscillospira and Anaerotruncus show paradoxical associations with both obesity and late-life introduction to the USA.

CONCLUSIONS

Our analysis of the gut microbiome of Latinos demonstrates unique features that might be responsible for health disparities affecting Hispanics living in the USA.

Correction: Loss of Bardet-Biedl syndrome proteins causes synaptic aberrations in principal neurons

[This corrects the article DOI: 10.1371/journal.pbio.3000414.].

Butyrogenic bacteria after acute graft-versus-host disease (GVHD) are associated with the development of steroid-refractory GVHD

The presence of butyrogenic bacteria after the onset of acute GVHD associates with subsequent steroid-refractory GVHD or chronic GVHD. Butyrate inhibits human colonic stem cells from forming an intact epithelial monolayer.

Silica-based colloid centrifugation enhances sperm quality in cockerel semen

1. Percoll^TM is one of the most widely used colloid for animal sperm preparation. The aim of this study was to evaluate whether Percoll^TM colloid centrifugation could be practical to improve cockerel sperm quality, and to compare the effects of Percoll^TM single layer centrifugation (SLC) and density gradient centrifugation (DGC) in order to obtain the most optimal protocol for cockerel semen.2. In the experiment with Percoll^TM SLC for fresh semen, an increase of motile sperm was seen after Percoll^TM 80% SLC and 90% SLC was conducted, at levels of 28.8% and 30.2% respectively (P < 0.01). The increase of progressively motile sperm after Percoll^TM 80% SLC and 90% SLC was 177.2% and 202.4% respectively (P < 0.01). Meanwhile, for semen stored at 4°C for 24 h, the increase of motile sperm after Percoll^TM 70% SLC and 80% SLC was 41.2% and 44.0% (P < 0.01), and the increase of progressive sperm after Percoll^TM 70% SLC and 80% SLC was 71.3% and 83.1% respectively (P < 0.01). Both the percentage of motile sperm and progressive sperm of the fresh and stored cockerel semen after appropriate Percoll^TM SLC was significantly enhanced.3. Sperm membrane integrity did not show any decrease after Percoll^TM centrifugation compared with non-centrifuged semen, which suggested that the Percoll^TM centrifugation treatment in this study did not cause damage to cockerel sperm membranes.4. In the experiment regarding the comparison of Percoll^TM SLC and DGC with fresh semen, the increase of motile sperm after Percoll^TM 80% SLC, 90% SLC and 40%/80% DGC was 29.5%, 36.4%, and 25.0% respectively; and the increase of progressive sperm was 44.7%, 58.5%, and 54.7%, respectively. For semen stored at 4°C for 24 h, the increase of motile sperm after Percoll^TM 70% SLC, 80% SLC and 35%/70% DGC were 41.2%, 44.0%, and 26.4%; and the increase of progressive sperm was 71.3%, 83.1%, and 43.7%, respectively. There were no significant differences between the increase of sperm motility after Percoll^TM 80%, 90% SLC or Percoll^TM 40%/80% DGC in fresh cockerel semen. There was no significant difference between Percoll^TM 70%, 80% SLC and Percoll^TM 35%/70% in stored cockerel semen. There was a tendency for sperm recovery rates with Percoll^TM SLC to be higher than Percoll^TM DGC, although this did not reach statistical significance in this study.5. It was concluded that Percoll^TM SLC was more suitable for cockerel sperm separation than Percoll^TM DGC. The results suggested that Percoll^TM 80% SLC was the most optimal procedure to separate fresh cockerel sperm and Percoll^TM 70% SLC was the most optimal procedure to separate stored cockerel sperm. Percoll^TM SLC is more simple, user-friendly and economical and less time-consuming than DGC for cockerel semen processing.

pldist: ecological dissimilarities for paired and longitudinal microbiome association analysis

MOTIVATION

The human microbiome is notoriously variable across individuals, with a wide range of 'healthy' microbiomes. Paired and longitudinal studies of the microbiome have become increasingly popular as a way to reduce unmeasured confounding and to increase statistical power by reducing large inter-subject variability. Statistical methods for analyzing such datasets are scarce.

RESULTS

We introduce a paired UniFrac dissimilarity that summarizes within-individual (or within-pair) shifts in microbiome composition and then compares these compositional shifts across individuals (or pairs). This dissimilarity depends on a novel transformation of relative abundances, which we then extend to more than two time points and incorporate into several phylogenetic and non-phylogenetic dissimilarities. The data transformation and resulting dissimilarities may be used in a wide variety of downstream analyses, including ordination analysis and distance-based hypothesis testing. Simulations demonstrate that tests based on these dissimilarities retain appropriate type 1 error and high power. We apply the method in two real datasets.

AVAILABILITY AND IMPLEMENTATION

The R package pldist is available on GitHub at https://github.com/aplantin/pldist.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Loss of Bardet-Biedl syndrome proteins causes synaptic aberrations in principal neurons

Bardet-Biedl syndrome (BBS), a ciliopathy, is a rare genetic condition characterised by retinal degeneration, obesity, kidney failure, and cognitive impairment. In spite of progress made in our general understanding of BBS aetiology, the molecular and cellular mechanisms underlying cognitive impairment in BBS remain elusive. Here, we report that the loss of BBS proteins causes synaptic dysfunction in principal neurons, providing a possible explanation for the cognitive impairment phenotype observed in BBS patients. Using synaptosomal proteomics and immunocytochemistry, we demonstrate the presence of Bbs proteins in the postsynaptic density (PSD) of hippocampal neurons. Loss of Bbs results in a significant reduction of dendritic spines in principal neurons of Bbs mouse models. Furthermore, we show that spine deficiency correlates with events that destabilise spine architecture, such as impaired spine membrane receptor signalling, known to be involved in the maintenance of dendritic spines. Our findings suggest a role for BBS proteins in dendritic spine homeostasis that may be linked to the cognitive phenotype observed in BBS.

GWAS analysis reveals a significant contribution of PSCA to the risk of Heliobacter pylori-induced gastric atrophy

Although recent genome-wide association studies (GWASs) have identified genetic variants associated with Helicobacter pylori (HP)-induced gastric cancer, few studies have examined the genetic traits associated with the risk of HP-induced gastric precancerous conditions. This study aimed to elucidate genetic variants associated with these conditions using a genome-wide approach. Data from four sites of the Japan Multi-Institutional Collaborative Cohort (J-MICC) Study were used in the discovery phase (Stage I); two datasets from the Hospital-based Epidemiologic Research Program at Aichi Cancer Center 2 (HERPACC2) study were used in the replication phases (Stages II and III) and SKAT (SNP-set Kernel Association Test) and single variant-based GWASs were conducted for the risks of gastric atrophy (GA) and severe GA defined by serum pepsinogen (PG) levels, and PG1 and PG1/2 ratios. In the gene-based SKAT in Stage I, prostate stem cell antigen (PSCA) was significantly associated with the risks of GA and severe GA, and serum PG1/2 level by linear kernel [false discovery rate (FDR) = 0.011, 0.230 and 7.2 × 10−7, respectively]. The single variant-based GWAS revealed that nine PSCA single nucleotide polymorphisms (SNPs) fulfilled the genome-wide significance level (P < 5 × 10−8) for the risks of both GA and severe GA in the combined study, although most of these associations did not reach genome-wide significance in the discovery or validation cohort on their own. GWAS for serum PG1 levels and PG1/2 ratios revealed that the PSCA rs2920283 SNP had a striking P-value of 4.31 × 10−27 for PG1/2 ratios. The present GWAS revealed the genetic locus of PSCA as the most significant locus for the risk of HP-induced GA, which confirmed the recently reported association in Europeans.

Gut Microbiota Composition and Blood Pressure

Animal models support a role for the gut microbiota in the development of hypertension. There has been a lack of epidemiological cohort studies to confirm these findings in human populations. We examined cross-sectional associations between measures of gut microbial diversity and taxonomic composition and blood pressure (BP) in 529 participants of the biracial (black and white) CARDIA study (Coronary Artery Risk Development in Young Adults). We sequenced V3-V4 regions of the 16S ribosomal RNA marker gene using DNA extracted from stool samples collected at CARDIA's Year 30 follow-up examination (2015-2016; aged 48-60 years). We quantified associations between BP (hypertension [defined as systolic BP ≥140 mm Hg or diastolic BP ≥90 mm Hg or antihypertension medication use] and systolic BP) and within and between-person diversity measures. We conducted genera-specific multivariable-adjusted regression analysis, accounting for multiple comparisons using the false discovery rate. Hypertension and systolic BP were inversely associated with measures of α-diversity, including richness and the Shannon Diversity Index, and were distinguished with respect to principal coordinates based on a similarity matrix of genera abundance. Several specific genera were significantly associated with hypertension and systolic BP, though results were attenuated with adjustment for body mass index. Our findings support associations between within-person and between-person gut microbial community diversity and taxonomic composition and BP in a diverse population-based cohort of middle-aged adults. Future study is needed to define functional pathways that underlie observed associations and identify specific microbial targets for intervention.

Increased mucosal neutrophil survival is associated with altered microbiota in HIV infection

Gastrointestinal (GI) mucosal dysfunction predicts and likely contributes to non-infectious comorbidities and mortality in HIV infection and persists despite antiretroviral therapy. However, the mechanisms underlying this dysfunction remain incompletely understood. Neutrophils are important for containment of pathogens but can also contribute to tissue damage due to their release of reactive oxygen species and other potentially harmful effector molecules. Here we used a flow cytometry approach to investigate increased neutrophil lifespan as a mechanism for GI neutrophil accumulation in chronic, treated HIV infection and a potential role for gastrointestinal dysbiosis. We report that increased neutrophil survival contributes to neutrophil accumulation in colorectal biopsy tissue, thus implicating neutrophil lifespan as a new therapeutic target for mucosal inflammation in HIV infection. Additionally, we characterized the intestinal microbiome of colorectal biopsies using 16S rRNA sequencing. We found that a reduced Lactobacillus: Prevotella ratio associated with neutrophil survival, suggesting that intestinal bacteria may contribute to GI neutrophil accumulation in treated HIV infection. Finally, we provide evidence that Lactobacillus species uniquely decrease neutrophil survival and neutrophil frequency in vitro, which could have important therapeutic implications for reducing neutrophil-driven inflammation in HIV and other chronic inflammatory conditions.

Identifying individual risk rare variants using protein structure guided local tests (POINT)

Rare variants are of increasing interest to genetic association studies because of their etiological contributions to human complex diseases. Due to the rarity of the mutant events, rare variants are routinely analyzed on an aggregate level. While aggregation analyses improve the detection of global-level signal, they are not able to pinpoint causal variants within a variant set. To perform inference on a localized level, additional information, e.g., biological annotation, is often needed to boost the information content of a rare variant. Following the observation that important variants are likely to cluster together on functional domains, we propose a protein structure guided local test (POINT) to provide variant-specific association information using structure-guided aggregation of signal. Constructed under a kernel machine framework, POINT performs local association testing by borrowing information from neighboring variants in the 3-dimensional protein space in a data-adaptive fashion. Besides merely providing a list of promising variants, POINT assigns each variant a p-value to permit variant ranking and prioritization. We assess the selection performance of POINT using simulations and illustrate how it can be used to prioritize individual rare variants in PCSK9, ANGPTL4 and CETP in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial data.

Stool Microbiota at Neutrophil Recovery Is Predictive for Severe Acute Graft vs Host Disease After Hematopoietic Cell Transplantation

Background

Graft-versus-host disease (GVHD) is common after allogeneic hematopoietic cell transplantation (HCT). Risk for death from GVHD has been associated with low bacterial diversity in the stool microbiota early after transplant; however, the specific species associated with GVHD risk remain poorly defined.

Methods

We prospectively collected serial weekly stool samples from 66 patients who underwent HCT, starting pre-transplantation and continuing weekly until 100 days post-transplant, a total of 694 observations in HCT recipients. We used 16S rRNA gene polymerase chain reaction with degenerate primers, followed by high-throughput sequencing to assess the relative abundance of sequence reads from bacterial taxa in stool samples over time.

Results

The gut microbiota was highly dynamic in HCT recipients, with loss and appearance of taxa common on short time scales. As in prior studies, GVHD was associated with lower alpha diversity of the stool microbiota. At neutrophil recovery post-HCT, the presence of oral Actinobacteria and oral Firmicutes in stool was positively correlated with subsequent GVHD; Lachnospiraceae were negatively correlated. A gradient of bacterial species (difference of the sum of the relative abundance of positive correlates minus the sum of the relative abundance of negative correlates) was most predictive (receiver operator characteristic area under the curve of 0.83) of subsequent severe acute GVHD.

Conclusions

The stool microbiota around the time of neutrophil recovery post-HCT is predictive of subsequent development of severe acute GVHD in this study.

Goodness-Of-Fit Test for Nonparametric Regression Models: Smoothing Spline ANOVA Models as Example

Nonparametric regression models do not require the specification of the functional form between the outcome and the covariates. Despite their popularity, the amount of diagnostic statistics, in comparison to their parametric counter-parts, is small. We propose a goodness-of-fit test for nonparametric regression models with linear smoother form. In particular, we apply this testing framework to smoothing spline ANOVA models. The test can consider two sources of lack-of-fit: whether covariates that are not currently in the model need to be included, and whether the current model fits the data well. The proposed method derives estimated residuals from the model. Then, statistical dependence is assessed between the estimated residuals and the covariates using the HSIC. If dependence exists, the model does not capture all the variability in the outcome associated with the covariates, otherwise the model fits the data well. The bootstrap is used to obtain p-values. Application of the method is demonstrated with a neonatal mental development data analysis. We demonstrate correct type I error as well as power performance through simulations.

Evaluation of cockerel spermatozoa viability and motility by a novel enzyme based cell viability assay

1. The results of spermatozoa assessment by the WST-8 (2-[2-methoxy-4-nitrophenyl]-3-[4-nitrophenyl]-5-[2,4-disulfophenyl]-2H-tetrazolium, monosodium salt) assay, flow cytometry (FC) or computer-assisted sperm analysis (CASA) were compared. 2. Different live/killed ratios of cockerel semen were serially diluted to 120, 60, and 30 × 10⁶ cells/ml, and each sample was analysed by (1) WST-8 assay at 0, 10, 20, 30, 40, 50, 60 min, (2) viability with FC, and (3) motility with CASA. 3. The WST-8 reduction rate was closely correlated with spermatozoa viability and motility. The optimal semen concentration for the WST-8 assay was 120 × 10⁶ cells/ml, and the standard curves for spermatozoa viability and motility predictions, respectively, were y_viability60 = 162.8x + 104.96 (R² = 0.9594) after 60 min of incubation and y_motility40 = 225.09x + 96.299 (R² = 0.8475) after 40 min of incubation. 4. It was concluded that the WST-8 assay is useful for the practical evaluation of cockerel spermatozoa viability and motility. Compared to FC and CASA, the WST-8 assay does not require expensive and complex instrumentation in the lab. Furthermore, one well of the WST-8 reaction can be used to predict spermatozoa viability and motility at the same time, which all lead it to be efficient and economical for semen quality assessment.

Isolated gallbladder rupture following blunt abdominal injury

Isolated traumatic gallbladder rupture subsequent to blunt abdominal injury is rare. Most literatures on the subjects consist of case reports. We reported a rare case of isolated gallbladder rupture and discussed the possible predisposing factors to gallbladder rupture.

Genome-wide association study for pollinosis identified two novel loci in interleukin (IL)-1B in a Japanese population

The number of pollinosis patients in Japan has significantly increased over the past 20 years. The majority of genome-wide association studies (GWAS) on pollinosis have been conducted in subjects of European descent, with few studies in Japanese populations. The aim of our GWAS was to identify genetic loci associated with self-reported pollinosis in a Japanese population and to understand its molecular background using a combination of single nucleotide polymorphisms (SNPs) and gene- and pathway-based analyses. A total of 731 and 560 individuals who were recruited as participants of the Japan Multi-Institutional Collaborative Cohort Study participated in the discovery and replication phases, respectively. The phenotype of pollinosis was based on the information from a self-administered questionnaire. In the single-SNP analysis, four SNPs (rs11975199, rs11979076, rs11979422, and rs12669708) reached suggestive significance level (P < 1 × 10-4) and had effects in the same direction in both phases of the study. The pathway-based analysis identified two suggestive pathways (nucleotide-binding oligomerization domain -like receptor and tumor necrosis factor signaling pathways). Both rs1143633 and rs3917368 in the interleukin-1B gene showed associations in the retrace (from pathway to gene and SNP) analysis. We performed single-SNP, gene, and pathway analysis and shed light on the molecular mechanisms underlying pollinosis in a Japanese population.

A Guide to Illumina BeadChip Data Analysis

The Illumina Infinium BeadChips are a powerful array-based platform for genome-wide DNA methylation profiling at approximately 485,000 (450K) and 850,000 (EPIC) CpG sites across the genome. The platform is used in many large-scale population-based epigenetic studies of complex diseases, environmental exposures, or other experimental conditions. This chapter provides an overview of the key steps in analyzing Illumina BeadChip data. We describe key preprocessing steps including data extraction and quality control as well as normalization strategies. We further present principles and guidelines for conducting association analysis at the individual CpG level as well as more sophisticated pathway-based association tests.

A Family Based Study of Carbon Monoxide and Nitric Oxide Signalling Genes and Preeclampsia

BACKGROUND

Preeclampsia is thought to originate during placentation, with incomplete remodelling and perfusion of the spiral arteries leading to reduced placental vascular capacity. Nitric oxide (NO) and carbon monoxide (CO) are powerful vasodilators that play a role in the placental vascular system. Although family clustering of preeclampsia has been observed, the existing genetic literature is limited by a failure to consider both mother and child.

METHODS

We conducted a nested case-control study within the Norwegian Mother and Child Birth Cohort of 1545 case-pairs and 995 control-pairs from 2540 validated dyads (2011 complete pairs, 529 missing mother or child genotype). We selected 1518 single-nucleotide polymorphisms (SNPs) with minor allele frequency >5% in NO and CO signalling pathways. We used log-linear Poisson regression models and likelihood ratio tests to assess maternal and child effects.

RESULTS

One SNP met criteria for a false discovery rate Q-value <0.05. The child variant, rs12547243 in adenylate cyclase 8 (ADCY8), was associated with an increased risk (relative risk [RR] 1.42, 95% confidence interval [CI] 1.20, 1.69 for AG vs. GG, RR 2.14, 95% CI 1.47, 3.11 for AA vs. GG, Q = 0.03). The maternal variant, rs30593 in PDE1C was associated with a decreased risk for the subtype of preeclampsia accompanied by early delivery (RR 0.45, 95% CI 0.27, 0.75 for TC vs. CC; Q = 0.02). None of the associations were replicated after correction for multiple testing.

CONCLUSIONS

This study uses a novel approach to disentangle maternal and child genotypic effects of NO and CO signalling genes on preeclampsia.