Search

As our understanding of the microbiome has expanded, so has the recognition of its critical role in human health and disease, thereby emphasizing the importance of testing whether microbes are associated with environmental factors or clinical outcomes. However, many of the fundamental challenges that concern microbiome surveys arise from statistical and experimental design issues, such as the sparse and overdispersed nature of microbiome count data and the complex correlation structure among samples. For example, in the human microbiome project (HMP) dataset, the repeated observations across time points (level 1) are nested within body sites (level 2), which are further nested within subjects (level 3). Therefore, there is a great need for the development of specialized and sophisticated statistical tests. In this paper, we propose multilevel zero-inflated negative-binomial models for association analysis in microbiome surveys. We develop a variational approximation method for maximum likelihood estimation and inference. It uses optimization, rather than sampling, to approximate the log-likelihood and compute parameter estimates, provides a robust estimate of the covariance of parameter estimates and constructs a Wald-type test statistic for association testing. We evaluate and demonstrate the performance of our method using extensive simulation studies and an application to the HMP dataset. We have developed an R package MZINBVA to implement the proposed method, which is available from the GitHub repository https://github.com/liudoubletian/MZINBVA. [ABSTRACT FROM AUTHOR]

Background: Let-7 is a microRNA (miRNA) that targets the β2 adrenergic receptor ( ADRB2 ), hypoxia inducible factor 1 subunit alpha inhibitor ( HIF1AN ), and claudin 12 ( CLDN12 ) genes. Single nucleotide polymorphisms (SNPs) in the structural or regulatory regions of these miRNA let-7-related genes may be associated with breast cancer carcinogenesis and prognosis. Low let-7 expression may increase breast cancer risk. We investigated the effects of let-7-related gene SNP (mirSNPs) on breast cancer risk and clinical outcomes., Methods: The distribution frequencies of the three SNPs were genotyped in patients with breast cancer and controls. Multivariate logistic regression analysis was used to evaluate the association between the SNPs and susceptibility to breast cancer. We investigated the effects of these mirSNPs prospectively on disease-free survival (DFS) using the Kaplan-Meier method and the extended multivariate Cox model., Results: We found that rs1042713 in the ADRB2 gene and rs11292 in the 3'-UTR of the HIF1AN gene were associated with breast cancer susceptibility ( P <0.05). The CLDN12 rs1017105 genotype was associated with estrogen receptor ( P =0.031) and progesterone receptor status ( P =0.007). The number of risk alleles was associated with estrogen receptor (P=0.034) status in breast cancer patients. In the survival analysis, the extended Cox model demonstrated that rs1042713 (P=0.000) and rs1017105 (P=0.004) were independent predictors of DFS. The number of risk alleles of the ADRB2 , HIF1AN , and CLDN12 genes was an independent predictor of DFS (P<0.001)., Conclusion: Let-7-related mirSNPs might be associated with carcinogenesis and clinical outcome in breast cancer, suggesting that variants of miRNA let-7-related gene networks coregulate breast cancer characteristics., Competing Interests: None.

Background: Germline genetic polymorphisms in certain genes are associated with the response to anthracycline- and taxane-based neoadjuvant chemotherapy in breast cancer (BC). This translational study aims to evaluate the potential role of rs1042713 in the beta 2-adrenergic receptor ( ADRB2 ) gene in predicting pathological complete responses (pCRs) to taxane- and platinum-based neoadjuvant chemotherapy in locally advanced breast cancer (LABC)., Materials and Methods: The distribution frequencies of rs1042713 were genotyped in LABC patients who received taxane- and platinum-based neoadjuvant chemotherapy. Associations between tumor-relevant biomarkers, genotypes and pCRs were evaluated using Student's t -test for continuous variables and Chi-square or Fisher's exact test for categorical variables. For univariate analysis, the relationship between the rs1042713 polymorphism and pCR was analyzed by Chi-square or Fisher's exact test. The modified ORs with their 95% CIs were calculated by a multivariate logistic regression analysis to explore the association between genotype and pCR., Results: There was a significant correlation of the rs1042713 genotype with estrogen receptor (ER) status ( P =0.008). Significant differences were detected in the rs1042713 genotypes of pCR and non-pCR patients ( P =0.046). The pCR rate was 18.2% in patients with ADRB2 rs1042713 AA genotypes and 38.7% in AG+GG genotypes. Women carrying the AG+GG (OR=2.91, 95% CI: 1.02-8.29, P =0.046) genotype had a higher pCR rate than those with the AA genotype., Conclusion: rs1042713, which is located in the ADRB2 gene, could predict pCR to taxane-and platinum-based neoadjuvant chemotherapy in LABC. This finding suggests that rs1042713 could play a potential role as a predictive marker in clinical settings., Competing Interests: Disclosure The authors report no conflicts of interest in this work.