Chen, Jun

A decrease in ovarian estrogens in postmenopausal women increases the risk of weight gain, cardiovascular disease, type 2 diabetes, and chronic inflammation. While it is known that gut microbiota regulates energy homeostasis, it is unclear if gut microbiota is associated with estradiol regulation of metabolism. In this study, we tested if estradiol-mediated protection from high-fat diet (HFD)-induced obesity and metabolic changes are associated with longitudinal alterations in gut microbiota in female mice. Ovariectomized adult mice with vehicle or estradiol (E2) implants were fed chow for two weeks and HFD for four weeks. As reported previously, E2 increased energy expenditure, physical activity, insulin sensitivity, and whole-body glucose turnover. Interestingly, E2 decreased the tight junction protein occludin, suggesting E2 affects gut epithelial integrity. Moreover, E2 increased Akkermansia and decreased Erysipleotrichaceae and Streptococcaceae. Furthermore, Coprobacillus and Lactococcus were positively correlated, while Akkermansia was negatively correlated, with body weight and fat mass. These results suggest that changes in gut epithelial barrier and specific gut microbiota contribute to E2-mediated protection against diet-induced obesity and metabolic dysregulation. These findings provide support for the gut microbiota as a therapeutic target for treating estrogen-dependent metabolic disorders in women.

Abstract Summary PERMANOVA (permutational multivariate analysis of variance based on distances) has been widely used for testing the association between the microbiome and a covariate of interest. Statistical significance is established by permutation, which is computationally intensive for large sample sizes. As large-scale microbiome studies, such as American Gut Project (AGP), become increasingly popular, a computationally efficient version of PERMANOVA is much needed. To achieve this end, we derive the asymptotic distribution of the PERMANOVA pseudo-F statistic and provide analytical P-value calculation based on chi-square approximation. We show that the asymptotic P-value is close to the PERMANOVA P-value even under a moderate sample size. Moreover, it is more accurate and an order-of-magnitude faster than the permutation-free method MDMR. We demonstrated the use of our procedure D-MANOVA on the AGP dataset. Availability and implementation D-MANOVA is implemented by the dmanova function in the CRAN package GUniFrac. Supplementary information Supplementary data are available at Bioinformatics online.

Abstract Background MR elastography can determine organ‐related stiffness, which reflects the degree of fibrosis. Liver stiffness increases in cirrhosis, and stiffness increases further post‐prandially due to increased portal blood in‐flow. Non‐selective beta‐blockers (NSBB) reduce the portal venous inflow, but their effect on liver and spleen stiffness are disputed. Aims To assess whether MR elastography of the liver or spleen reflects the severity of cirrhosis, whether treatment with NSBB changes liver and spleen stiffness and whether changes in stiffness can predict the effect of NSBB on portal pressure. Methods Fifty‐two patients with cirrhosis underwent liver vein catheterization and two‐dimensional (2D) MR elastography on separate days. Thirty‐six of the patients had a hepatic venous pressure gradient (HVPG) of ≥12 mmHg and were tested prior to, and after, intravenous infusion of NSBB using HVPG measurement and MR elastography. Results HVPG showed a strong, positive, linear relationship with liver stiffness ( r 2 = 0.92; P < .001) and spleen stiffness ( r 2 = 0.94; P < .001). The cut‐off points for identifying patients with a HVPG ≥ 12 mmHg were 7.7 kPa for liver stiffness (sensitivity 0.78, specificity 0.64) and 10.5 kPa for spleen stiffness (sensitivity 0.8, specificity 0.79). Intravenous administration of NSBB significantly decreased spleen stiffness by 6.9% (CI: 3.5‐10.4, P < .001), but NSBB had no consistent effect on liver stiffness. However, changes in spleen stiffness were not related to the HVPG response ( P = .75). Conclusions Two‐dimensional MR elastographic estimation of liver or spleen stiffness reflects the degree of portal hypertension in patients with liver cirrhosis, but changes in stiffness after NSBB do not predict the effect on HVPG.

Abstract Background Liver disease remains a significant cause of morbidity and mortality in HIV-infected persons. Soluble CD163 is a marker of Kupffer cell activation that is highly associated with development of hepatic fibrosis. The relative contributions of HIV-associated systemic immune activation vs other etiologies of injury are poorly characterized. Methods We utilized subjects in the Miami Adult Studies on HIV (MASH) cohort to evaluate 464 participants including 361 people with HIV (PWH) and 103 hepatitis C virus (HCV)/HIV-uninfected controls. Subjects underwent testing for hepatic fibrosis using both magnetic resonance elastography and the Enhanced Liver Fibrosis Index. Steatosis was evaluated by magnetic resonance imaging–derived proton density fat fraction. Immune activation markers and cytokines were quantitated using Luminex methodologies. Results Participants with HIV with or without HCV coinfection had higher levels of sCD163 than uninfected controls (P &lt; .05). Soluble sCD163 was highly associated with elevated alanine aminotransferase, a key marker of inflammation/injury and with hepatic fibrosis. Hepatic steatosis was also associated with a cytokine pattern suggestive of Kupffer cell activation but was not associated with an increase in sCD14 or sCD27. Conclusions Injury and resultant hepatic fibrosis occur by distinct though overlapping mechanistic pathways. In PWH, sCD163 is highly associated with both injury and fibrosis, suggesting that persistent systemic immune activation is a major contributor to long-term outcomes, adding to damage caused by alcohol, steatosis, and other hepatotoxic drug effects.

In persons living with HIV (PLWH), there are multiple sources of liver injury. Gene polymorphisms of PNPLA3 (patatin-like phospholipase domain-containing protein 3) have been identified as an important cofactor for increased disease severity in both alcoholic and non-alcoholic steatohepatitis (NASH). We utilized a well-characterized cohort of ethnically and racially diverse patients with HIV to define the prevalence of PNPLA3 SNPs (single nucleotide polymorphism) (rs738409), and to determine the relationship to hepatic steatosis and liver fibrosis. Steatosis was determined using MRI-PDFF (magnetic resonance imaging-determined proton density fat fraction) and fibrosis was estimated using MR Elastography (MRE). From the Miami Area HIV Study (MASH) cohort, 100 HIV positive participants and 40 controls (HCV/HIV = 20; HCV and HIV negative = 20) were evaluated. Nearly 40% of all participants carried the variant G allele associated with increased liver disease severity and 5% were homozygotic GG. The variant SNP occurred most frequently in those self-identified as Hispanic compared to white or Black participants. Hepatic steatosis (>5% fat) was present significantly more often in those without HIV vs. those with (p < 0.001). Putative NAFLD/NASH was found to be present in 6% of tested subjects, who were HIV monoinfected. BMI was lower in those that carried the G allele for PNPLA3. This finding suggests that PNPLA3 may be an independent component to NAFLD (non-alcoholic fatty liver disease)/NASH development and longitudinal follow-up of the cohort is warranted.

AbstractAdvances in high‐throughput biotechnologies have culminated in a wide range of omics (such as genomics, epigenomics, transcriptomics, metabolomics, and metagenomics) studies, and increasing evidence in these studies indicates that the biological architecture of complex traits involves a large number of omics variants each with minor effects but collectively accounting for the full phenotypic variability. Thus, a major challenge in many “ome‐wide” association analyses is to achieve adequate statistical power to identify multiple variants of small effect sizes, which is notoriously difficult for studies with relatively small‐sample sizes. A small‐sample adjustment incorporated in the kernel machine regression framework was proposed to solve this for association studies under various settings. However, such an adjustment in the generalized linear mixed model (GLMM) framework, which accounts for both sample relatedness and non‐Gaussian outcomes, has not yet been attempted. In this study, we fill this gap by extending small‐sample adjustment in kernel machine association test to GLMM. We propose a new Variant‐Set Association Test (VSAT), a powerful and efficient analysis tool in GLMM, to examine the association between a set of omics variants and correlated phenotypes. The usefulness of VSAT is demonstrated using both numerical simulation studies and applications to data collected from multiple association studies. The software for implementing the proposed method in R is available at https://www.github.com/jchen1981/SSKAT.

Giving birth too soon accounts for half of all newborn deaths worldwide. Clinical symptoms alone are not sufficient to identify women at risk of giving birth too early, as such a pragmatic approach to reducing the incidence of preterm birth entails developing early strategies for intervention before it materializes.

The microbiome plays an important role in human health by mediating the path from environmental exposures to health outcomes. The relative abundances of the high‐dimensional microbiome data have an unit‐sum restriction, rendering standard statistical methods in the Euclidean space invalid. To address this problem, we use the isometric log‐ratio transformations of the relative abundances as the mediator variables. To select significant mediators, we consider a closed testing‐based selection procedure with desirable confidence. Simulations are provided to verify the effectiveness of our method. As an illustrative example, we apply the proposed method to study the mediation effects of murine gut microbiome between subtherapeutic antibiotic treatment and body weight gain, and identify Coprobacillus and Adlercreutzia as two significant mediators.