MAOB expression correlates with a favourable prognosis in prostate cancer, and its genetic variants are associated with the metastasis of the disease.

Monoamine oxidase B (MAOB), a neurotransmitter-degrading enzyme, was reported to reveal conflicting roles in various cancers. However, the functional role of MAOB and impacts of its genetic variants on prostate cancer (PCa) is unknown. Herein, we genotyped four loci of MAOB single-nucleotide polymorphisms (SNPs), including rs1799836 (A/G), rs3027452 (G/A), rs6651806 (A/C) and rs6324 (G/A) in 702 PCa Taiwanese patients. We discovered that PCa patients carrying the MAOB rs6324 A-allele exhibited an increased risk of having a high initial prostate-specific antigen (iPSA) level (>10 ng/mL). Additionally, patients with the rs3027452 A-allele had a higher risk of developing distal metastasis, particularly in the subpopulation with high iPSA levels. In a subpopulation without postoperative biochemical recurrence, patients carrying the rs1799836 G-allele had a higher risk of developing lymph node metastasis and recurrence compared to those carrying the A-allele. Furthermore, genotype screening in PCa cell lines revealed that cells carrying the rs1799836 G-allele expressed lower MAOB levels than those carrying the A-allele. Functionally, overexpression and knockdown of MAOB in PCa cells respectively suppressed and enhanced cell motility and proliferation. In clinical observations, correlations of lower MAOB expression levels with higher Gleason scores, advanced clinical T stages, tumour metastasis, and poorer prognosis in PCa patients were noted. Our findings suggest that MAOB may act as a suppressor of PCa progression, and the rs3027452 and rs1799836 genetic variants of MAOB are linked to PCa metastasis within the Taiwanese population.

Gut flora metagenomic analysis coupled with metabolic and deep immune profiling in chronic kidney disease.

BACKGROUND AND HYPOTHESIS: Perturbation of gut microbiota has been linked to chronic kidney disease (CKD), which was correlated with a sophisticated milieu of metabolic and immune dysregulation. METHODS: To clarify the underlying host-microbe interaction in CKD, we performed multi-omics measurements, including systems-level gut microbiome, targeted serum metabolome, and deep immunotyping, in a cohort of patients and non-CKD controls. RESULTS: Our analyses on functional profiles of gut microbiome showed a decrease in the diversity and abundance of carbohydrate-active enzyme (CAZyme) genes but an increase in the abundance of antibiotic resistance, nitrogen cycling enzyme, and virulence factor genes in CKD. Moreover, models generated using measurements of serum metabolites (amino acids, bile acids, and short-chain fatty acids) or immunotypes were predictive of renal impairment but less so than many of functional profiles derived from gut microbiota, with the CAZyme genes being the top performing model to accurately predict early stage of diseases. In addition, co-occurrence analyses revealed coordinated host-microbe relationships in CKD. Specifically, the highest fractions of significant correlations were identified with circulating metabolites by several taxonomic and functional profiles of gut microbiome, while immunotype features were moderately associated with the abundance of microbiome-encoded metabolic pathways and serum levels of amino acids (e.g. B cell cluster-tryptophan and B cell cluster-tryptophan metabolism). CONCLUSION: Overall, our multi-omics integration revealed several signatures of systems-level gut microbiome in robust associations with host-microbe co-metabolites and renal function, which may be of etiological and diagnostic implications in CKD.

Potential impact of ADAM-10 genetic variants with the clinical features of oral squamous cell carcinoma.

A disintegrin and metalloproteinase domain-containing protein 10 (ADAM-10) involves in the tumour progression, but the impacts of single-nucleotide polymorphism (SNP) of ADAM-10 on oral squamous cell carcinoma (OSCC) remain unclear. The aim of this study was to investigate the influence of SNP of ADAM-10 on the clinical features of OSCC in male Taiwanese. Five loci of ADAM-10 SNPs including rs653765 (C/T), rs2305421 (A/G), rs514049 (A/C), rs383902 (T/C) and rs2054096 (A/T) were genotyped by TaqMan allelic discrimination in 1138 OSCC patients and 1199 non-OSCC individuals. The ADAM-10 SNP rs2305421 GG (AOR: 1.399, 95% CI: 1.045-1.874, p = 0.024) and G allele (AOR: 1.170, 95% CI: 1.012-1.351, p = 0.034) illustrated a significantly higher genotypic frequencies in the OSCC group compared to the distribution of the ADAM-10 SNP rs2305421 AA wild type. In the subgroup analysis, the ADAM-10 SNP rs383902 TC+CC was significantly correlated to tumour size larger than T2 in betel quid chewer (AOR: 1.375, 95% CI: 1.010-1.872, p = 0.043), while the ADAM-10 SNP rs653765 CT+TT was significantly associated with tumour size larger than T2 in cigarette smoker (AOR: 1.346, 95% CI: 1.023-1.772, p = 0.034). The results from The Cancer Genome Atlas revealed highest ADAM-10 mRNA level in T2 stage of current smokers with head and neck squamous cell carcinoma (HNSCC). In conclusions, the ADAM-10 SNP rs2305421 G allele is associated with the presence of OSCC, and the ADAM-10 SNP rs383902 TC+CC and ADAM-10 SNP rs653765 CT+TT correlates to large tumour size in specific conditions.

Interactive effects of CDKN2B-AS1 gene polymorphism and habitual risk factors on oral cancer.

Oral squamous cell carcinoma (OSCC) is a common malignant disease associated with a high mortality rate and heterogeneous disease aetiology. Cyclin dependent kinase inhibitor 2B antisense RNA 1 (CDKN2B-AS1), is a long noncoding RNA that has been shown to act as a scaffold, sponge, or signal hub to promote carcinogenesis. Here, we attempted to assess the effect of CDKN2B-AS1 single-nucleotide polymorphisms (SNPs) on the susceptibility to OSCC. Five CDKN2B-AS1 SNPs, including rs564398, rs1333048, rs1537373, rs2151280 and rs8181047, were analysed in 1060 OSCC cases and 1183 cancer-free controls. No significant association of these five SNPs with the risk of developing OSCC was detected between the case and control group. However, while examining the clinical characteristics, patients bearing at least one minor allele of rs1333048 (CA and CC) were more inclined to develop late-stage (stage III/IV, adjusted OR, 1.480; 95% CI, 1.129-1.940; p = 0.005) and large-size (greater than 2 cm in the greatest dimension, adjusted OR, 1.347; 95% CI, 1.028-1.765; p = 0.031) tumours, as compared with those homologous for the major allele (AA). Further stratification analyses demonstrated that this genetic correlation with the advanced stage of disease was observed only in habitual betel quid chewers (adjusted OR, 1.480; 95% CI, 1.076-2.035; p = 0.016) or cigarette smokers (adjusted OR, 1.531; 95% CI, 1.136-2.063; p = 0.005) but not in patients who were not exposed to these major habitual risks. These data reveal an interactive effect of CDKN2B-AS1 rs1333048 with habitual exposure to behavioural risks on the progression of oral cancer.

Genetic variants of dipeptidyl peptidase IV are linked to the clinicopathologic development of prostate cancer.

CD26/dipeptidyl peptidase IV (DPP4) is a multifunctional cell-surface glycoprotein widely found in many cell types, and a soluble form is present in body fluids. There is longstanding evidence indicating a tumour-promoting or -suppressive role of DPP4 in different cancer types. However, studies focusing on the impacts of genetic variants of DPP4 on cancers are very rare. Herein, we conducted a case-control study to evaluate whether single-nucleotide polymorphisms (SNPs) of DPP4 were associated with the risk or clinicopathologic development of prostate cancer (PCa). We genotyped four loci of DPP4 SNPs, including rs7608798 (A/G), rs3788979 (C/T), rs2268889 (T/C) and rs6741949 (G/C), using a TaqMan allelic discrimination assay in 704 PCa patients and 704 healthy controls. Our results showed that PCa patients with the DPP4 rs7608798 AG+GG genotype or rs2268889 TC+CC genotype had a higher risk of developing an advanced clinical primary tumour (cT) stage (adjusted odds ratio (AOR): 1.680, 95% confidence interval (CI): 1.062-2.659, p = 0.025; AOR: 1.693, 95% CI: 1.092-2.624, p = 0.018). Additionally, in The Cancer Genome Atlas (TCGA) database, we observed that lower DPP4 expression levels were correlated with higher Gleason scores, advanced cT and pathological stages, tumour metastasis, and shorter progression-free survival rates in PCa patients. Furthermore, overexpression of DPP4 suppressed migration/invasion of metastatic PC3 PCa cells. Our findings suggest that DPP4 levels may affect the progression of PCa, and the DPP4 rs7608798 and rs2268889 SNPs are associated with the clinicopathologic development of PCa in a Taiwanese population.

Functional variants of the chitinase 3-like 1 gene are associated with clinicopathologic outcomes and progression of prostate cancer.

Chitinase 3-like 1 (CHI3L1 or YKL40) is a secreted glycoprotein highly expressed in advanced stages of several cancer types, including prostate cancer (PCa). Impacts of genetic variants of CHI3L1 on PCa development have not yet been investigated. The most common well-studied genetic variations are single-nucleotide polymorphisms (SNPs). Therefore, the objective of this study was to explore associations of CHI3L1 SNPs with both the susceptibility to PCa and its clinicopathological development. Three promoter SNPs, rs6691378 (-1371, G>A), rs10399805 (-247, G>A) and rs4950928 (-131, C>G), and one non-synonymous SNP, rs880633 (+2950, T>C), were analysed using a TaqMan allelic discrimination assay for genotyping in a cohort of 701 PCa patients and 701 healthy controls. Results indicated that there were no significant associations of PCa susceptibility with these four CHI3L1 SNPs. However, among elderly PCa patients (aged >65 years), it was observed that polymorphic variants (GA + AA) of CHI3L1 rs6691378 and 10399805 were significantly linked to reduced risks of several clinicopathological characteristics, including a high Gleason grade, advanced pathologic T stage and tumour cell invasion. Moreover, analyses of The Cancer Genome Atlas database revealed that CHI3L1 expression levels were elevated in PCa tissues compared with normal tissues. Interestingly, higher CHI3L1 expression levels were found to be associated with longer progression-free survival rates in PCa patients. Our findings indicated that levels of CHI3L1 may influence the progression of PCa, and the rs6691378 and 10399805 SNP genetic variants of CHI3L1 are linked to the clinicopathological development of PCa within a Taiwanese population.

Phenotype-specific signatures of systems-level gut microbiome associated with childhood airway allergies.

BACKGROUND: Perturbation of gut symbiosis has been linked to childhood allergic diseases. However, the underlying host-microbe interaction connected with specific phenotypes is poorly understood. METHODS: To address this, integrative analyses of stool metagenomic and metabolomic profiles associated with IgE reactions in 56 children with mite-sensitized airway allergies (25 with rhinitis and 31 with asthma) and 28 nonallergic healthy controls were conducted. RESULTS: We noted a decrease in the number and abundance of gut microbiome-encoded carbohydrate-active enzyme (CAZyme) genes, accompanied with a reduction in species richness, in the asthmatic gut microflora but not in that from allergic rhinitis. Such loss of CAZymes was consistent with the observation that a CAZyme-linked decrease in fecal butyrate was found in asthmatics and negatively correlated with mite-specific IgE responses. Different from the CAZymes, we demonstrated an increase in α diversity at the virulome levels in asthmatic gut microbiota and identified phenotype-specific variations of gut virulome. Moreover, use of fecal metagenomic and metabolomic signatures resulted in distinct effects on differentiating rhinitis and asthma from nonallergic healthy controls. CONCLUSION: Overall, our integrative analyses reveal several signatures of systems-level gut microbiome in robust associations with fecal metabolites and disease phenotypes, which may be of etiological and diagnostic implications in childhood airway allergies.

Compositional Alteration of Gut Microbiota in Psoriasis Treated with IL-23 and IL-17 Inhibitors.

Alterations in the gut microbiota composition and their associated metabolic dysfunction exist in psoriasis. However, the impact of biologics on shaping gut microbiota is not well known. This study aimed to determine the association of gut microorganisms and microbiome-encoded metabolic pathways with the treatment in patients with psoriasis. A total of 48 patients with psoriasis, including 30 cases who received an IL-23 inhibitor (guselkumab) and 18 cases who received an IL-17 inhibitor (secukinumab or ixekizumab) were recruited. Longitudinal profiles of the gut microbiome were conducted by using 16S rRNA gene sequencing. The gut microbial compositions dynamically changed in psoriatic patients during a 24-week treatment. The relative abundance of individual taxa altered differently between patients receiving the IL-23 inhibitor and those receiving the IL-17 inhibitor. Functional prediction of the gut microbiome revealed microbial genes related to metabolism involving the biosynthesis of antibiotics and amino acids were differentially enriched between responders and non-responders receiving IL-17 inhibitors, as the abundance of the taurine and hypotaurine pathway was found to be augmented in responders treated with the IL-23 inhibitor. Our analyses showed a longitudinal shift in the gut microbiota in psoriatic patients after treatment. These taxonomic signatures and functional alterations of the gut microbiome could serve as potential biomarkers for the response to biologics treatment in psoriasis.

HCMMCNVs: hierarchical clustering mixture model of copy number variants detection using whole exome sequencing technology.

SUMMARY: In this article, we introduce a hierarchical clustering and Gaussian mixture model with expectation-maximization (EM) algorithm for detecting copy number variants (CNVs) using whole exome sequencing (WES) data. The R shiny package 'HCMMCNVs' is also developed for processing user-provided bam files, running CNVs detection algorithm and conducting visualization. Through applying our approach to 325 cancer cell lines in 22 tumor types from Cancer Cell Line Encyclopedia (CCLE), we show that our algorithm is competitive with other existing methods and feasible in using multiple cancer cell lines for CNVs estimation. In addition, by applying our approach to WES data of 120 oral squamous cell carcinoma (OSCC) samples, our algorithm, using the tumor sample only, exhibits more power in detecting CNVs as compared with the methods using both tumors and matched normal counterparts. AVAILABILITY AND IMPLEMENTATION: HCMMCNVs R shiny software is freely available at github repository https://github.com/lunching/HCMM_CNVs.and Zenodo https://doi.org/10.5281/zenodo.4593371. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

wiSDOM: a visual and statistical analytics for interrogating microbiome.

MOTIVATION: We proposed a wiSDOM (web-based inclusionary analysis Suite for Disease-Oriented Metagenomics) R Shiny application which comprises six functional modules: (i) initial visualization of sampling effort and distribution of dominant bacterial taxa among groups or individual samples at different taxonomic levels; (ii) statistical and visual analysis of α diversity; (iii) analysis of similarity (ANOSIM) of ß diversity on UniFrac, Bray-Curtis, Horn-Morisita or Jaccard distance and visualizations; (iv) microbial biomarker discovery between two or more groups with various statistical and machine learning approaches; (v) assessment of the clinical validity of selected biomarkers by creating the interactive receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC) for binary classifiers; and lastly (vi) functional prediction of metagenomes with PICRUSt or Tax4Fun. RESULTS: The performance of wiSDOM has been evaluated in several of our previous studies for exploring microbial biomarkers and their clinical validity as well as assessing the alterations in bacterial diversity and functionality. The wiSDOM can be customized and visualized as per users' needs and specifications, allowing researchers without programming background to conduct comprehensive data mining and illustration using an intuitive browser-based interface. AVAILABILITY AND IMPLEMENTATION: The browser-based R Shiny interface can be accessible via (https://lun-ching.shinyapps.io/wisdom/) and freely available at (https://github.com/lunching/wiSDOM). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Older molecular brain age in severe mental illness.

Psychiatric disorders are associated with accelerated aging and enhanced risk for neurodegenerative disorders. Brain aging is associated with molecular, cellular, and structural changes that are robust on the group level, yet show substantial inter-individual variability. Here we assessed deviations in gene expression from normal age-dependent trajectories, and tested their validity as predictors of risk for major mental illnesses and neurodegenerative disorders. We performed large-scale gene expression and genotype analyses in postmortem samples of two frontal cortical brain regions from 214 control subjects aged 20-90 years. Individual estimates of "molecular age" were derived from age-dependent genes, identified by robust regression analysis. Deviation from chronological age was defined as "delta age". Genetic variants associated with deviations from normal gene expression patterns were identified by expression quantitative trait loci (cis-eQTL) of age-dependent genes or genome-wide association study (GWAS) on delta age, combined into distinct polygenic risk scores (PRScis-eQTL and PRSGWAS), and tested for predicting brain disorders or pathology in independent postmortem expression datasets and clinical cohorts. In these validation datasets, molecular ages, defined by 68 and 76 age-related genes for two brain regions respectively, were positively correlated with chronological ages (r = 0.88/0.91), elevated in bipolar disorder (BP) and schizophrenia (SCZ), and unchanged in major depressive disorder (MDD). Exploratory analyses in independent clinical datasets show that PRSs were associated with SCZ and MDD diagnostics, and with cognition in SCZ and pathology in Alzheimer's disease (AD). These results suggest that older molecular brain aging is a common feature of severe mental illnesses and neurodegeneration.

Genetic Polymorphisms of lncRNA LINC00673 as Predictors of Hepatocellular Carcinoma Progression in an Elderly Population.

Long noncoding (lnc)RNAs are reported to be key regulators of tumor progression, including hepatocellular carcinoma (HCC). The lncRNA long intergenic noncoding RNA 00673 (LINC00673) was indicated to play an important role in HCC progression, but the impacts of genetic variants (single-nucleotide polymorphisms, SNPs) of LINC00673 on HCC remain unclear. A TaqMan allelic discrimination assay was performed to analyze the genotypes of three tagging SNPs, viz., rs9914618 G > A, rs6501551 A > G, and rs11655237 C > T, of LINC00673 in 783 HCC patients and 1197 healthy subjects. Associations of functional SNPs of LINC00673 with HCC susceptibility and clinicopathologic variables were analyzed by logistic regression models. After stratification by confounding factor, we observed that elderly patients (≥60 years) with the LINC00673 rs9914618 A allele had an increased risk of developing HCC under a codominant model (p = 0.025) and dominant model (p = 0.047). Moreover, elderly patients carrying the GA + AA genotype of rs9914618 exhibited a higher risk of having lymph node metastasis compared to those who were homozygous for the major allele (p = 0.013). Genotype screening of rs9914618 in HCC cell lines showed that cells carrying the AA genotype expressed higher LINC00673 levels compared to the cells carrying the GG genotype. Further analyses of clinical datasets from the Cancer Genome Atlas (TCGA) showed that LINC00673 expressions were upregulated in HCC tissues compared to normal tissues, and were correlated with advanced clinical stages and poorer prognoses. In conclusions, our results suggested that the LINC00673 rs9914618 polymorphism may be a promising HCC biomarker, especially in elderly populations.

Oral microbial dysbiosis and its performance in predicting oral cancer.

Dysbiosis of oral microbiome may dictate the progression of oral squamous cell carcinoma (OSCC). Yet, the composition of oral microbiome fluctuates by saliva and distinct sites of oral cavity and is affected by risky behaviors (smoking, drinking and betel quid chewing) and individuals' oral health condition. To characterize the disturbances in the oral microbial population mainly due to oral tumorigenicity, we profiled the bacteria within the surface of OSCC lesion and its contralateral normal tissue from discovery (n = 74) and validation (n = 42) cohorts of male patients with cancers of the buccal mucosa. Significant alterations in the bacterial diversity and relative abundance of specific oral microbiota (most profoundly, an enrichment for genus Fusobacterium and the loss of genus Streptococcus in the tumor sites) were identified. Functional prediction of oral microbiome shown that microbial genes related to the metabolism of terpenoids and polyketides were differentially enriched between the control and tumor groups, indicating a functional role of oral microbiome in formulating a tumor microenvironment via attenuated biosynthesis of secondary metabolites with anti-cancer effects. Furthermore, the vast majority of microbial signatures detected in the discovery cohort was generalized well to the independent validation cohort, and the clinical validity of these OSCC-associated microbes was observed and successfully replicated. Overall, our analyses reveal signatures (a profusion of Fusobacterium nucleatum CTI-2 and a decrease in Streptococcus pneumoniae) and functions (decreased production of tumor-suppressive metabolites) of oral microbiota related to oral cancer.

Effects of Low Protein Diet on Modulating Gut Microbiota in Patients with Chronic Kidney Disease: A Systematic Review and Meta-analysis of International Studies.

Background: Although associations between low protein diet (LPD) and changes of gut microbiota have been reported; however, systematic discernment of the effects of LPD on diet-microbiome-host interaction in patients with chronic kidney disease (CKD) is lacking. Methods: We searched PUBMED and EMBASE for articles published on changes of gut microbiota associated with implementation of LPD in CKD patients until July 2021. Independent researchers extracted data and assessed risks of bias. We conducted meta-analyses of combine p-value, mean differences and random effects for gut microbiota and related metabolites. Study heterogeneity was measured by Tau2 and I2 statistic. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results: Five articles met inclusion criteria. The meta-analyses of gut microbiota exhibited enrichments of Lactobacillaceae (meta-p= 0.010), Bacteroidaceae (meta-p= 0.048) and Streptococcus anginosus (meta-p< 0.001), but revealed depletion of Bacteroides eggerthii (p=0.017) and Roseburia faecis (meta-p=0.019) in LPD patients compared to patients undergoing normal protein diet. The serum IS levels (mean difference: 0.68 ug/mL, 95% CI: -8.38-9.68, p= 0.89) and pCS levels (mean difference: -3.85 ug/mL, 95% CI: -15.49-7.78, p < 0.52) did not change between groups. We did not find significant differences on renal function associated with change of microbiota between groups (eGFR, mean difference: -7.21 mL/min/1.73 m2, 95% CI: -33.2-18.79, p= 0.59; blood urea nitrogen, mean difference: -6.8 mg/dL, 95% CI: -46.42-32.82, p= 0.74). Other clinical (sodium, potassium, phosphate, albumin, fasting sugar, uric acid, total cholesterol, triglycerides, C-reactive protein and hemoglobin) and anthropometric estimates (body mass index, systolic blood pressure and diastolic blood pressure) did not differ between the two groups. Conclusions: This systematic review and meta-analysis suggested that the effects of LPD on the microbiota were observed predominantly at the families and species levels but minimal on microbial diversity or richness. In the absence of global compositional microbiota shifts, the species-level changes appear insufficient to alter metabolic or clinical outputs.

Characterization of dementia with Lewy bodies (DLB) and mild cognitive impairment using the Lewy body dementia module (LBD-MOD).

INTRODUCTION: The National Institute on Aging Alzheimer's Disease Research Center program added the Lewy body dementia module (LBD-MOD) to the Uniform Data Set to facilitate LBD characterization and distinguish dementia with Lewy bodies (DLB) from Alzheimer's disease (AD). We tested the performance of the LBD-MOD. METHODS: The LBD-MOD was completed in a single-site study in 342 participants: 53 controls, 78 AD, and 110 DLB; 79 mild cognitive impairment due to AD (MCI-AD); and 22 MCI-DLB. RESULTS: DLB differed from AD in extrapyramidal symptoms, hallucinations, apathy, autonomic features, REM sleep behaviors, daytime sleepiness, cognitive fluctuations, timed attention tasks, and visual perception. MCI-DLB differed from MCI-AD in extrapyramidal features, mood, autonomic features, fluctuations, timed attention tasks, and visual perception. Descriptive data on LBD-MOD measures are provided for reference. DISCUSSION: The LBD-MOD provided excellent characterization of core and supportive features to differentiate DLB from AD and healthy controls while also characterizing features of MCI-DLB.

MetaOmics: analysis pipeline and browser-based software suite for transcriptomic meta-analysis.

SUMMARY: The rapid advances of omics technologies have generated abundant genomic data in public repositories and effective analytical approaches are critical to fully decipher biological knowledge inside these data. Meta-analysis combines multiple studies of a related hypothesis to improve statistical power, accuracy and reproducibility beyond individual study analysis. To date, many transcriptomic meta-analysis methods have been developed, yet few thoughtful guidelines exist. Here, we introduce a comprehensive analytical pipeline and browser-based software suite, called MetaOmics, to meta-analyze multiple transcriptomic studies for various biological purposes, including quality control, differential expression analysis, pathway enrichment analysis, differential co-expression network analysis, prediction, clustering and dimension reduction. The pipeline includes many public as well as >10 in-house transcriptomic meta-analytic methods with data-driven and biological-aim-driven strategies, hands-on protocols, an intuitive user interface and step-by-step instructions. AVAILABILITY AND IMPLEMENTATION: MetaOmics is freely available at https://github.com/metaOmics/metaOmics. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integration of metagenomics-metabolomics reveals specific signatures and functions of airway microbiota in mite-sensitized childhood asthma.

BACKGROUND: Childhood asthma is a multifactorial inflammatory condition of the airways, associated with specific changes in respiratory microbiome and circulating metabolome. METHODS: To explore the functional capacity of asthmatic microbiome and its intricate connection with the host, we performed shotgun sequencing of airway microbiome and untargeted metabolomics profiling of serum samples in a cohort of children with mite-sensitized asthma and non-asthmatic controls. RESULTS: We observed higher gene counts and sample-to-sample dissimilarities in asthmatic microbiomes, indicating a more heterogeneous community structure and functionality among the cases than in controls. Moreover, we identified airway microbial species linked to changes in circulating metabolites and IgE responses of the host, including a positive correlation between Prevotella sp oral taxon 306 and dimethylglycine that were both decreased in patients. Several control-enriched species (Eubacterium sulci, Prevotella pallens, and Prevotella sp oral taxon 306) were inversely correlated with total and allergen-specific IgE levels. Genes related to microbial carbohydrate, amino acid, and lipid metabolism were differentially enriched, suggesting that changes in microbial metabolism may contribute to respiratory health in asthmatics. Pathway modules relevant to allergic responses were differentially abundant in asthmatic microbiome, such as enrichments for biofilm formation by Pseudomonas aeruginosa, membrane trafficking, histidine metabolism, and glycosaminoglycan degradation, and depletions for polycyclic aromatic hydrocarbon degradation. Further, we identified metagenomic and metabolomic markers (eg, Eubacterium sulci) to discriminate cases from the non-asthmatic controls. CONCLUSIONS: Our dual-omics data reveal the connections between respiratory microbes and circulating metabolites perturbed in mite-sensitized pediatric asthma, which may be of etiological and diagnostic implications.

Mutational signatures and mutagenic impacts associated with betel quid chewing in oral squamous cell carcinoma.

Betel quid (BQ) chewing is a prevailing risk for oral squamous cell carcinoma (OSCC) in Southeast Asia. Yet, the detailed mechanisms by which BQ chewing damages the genome are still not fully understood. Through exome sequencing of tumor-normal pairs from 196 male patients with OSCC, including 95 habitual BQ chewers and 101 non-BQ users, we conducted a quantitative survey of mutational signatures and genomic aberrations and explored their association with BQ chewing. We found that BQ-associated elevation in mutation rate was seen in cancers of the tongue, but not in overall OSCC. Additionally, we identified a mutational signature that is enriched in tumors from BQ users. Moreover, the numbers of small insertions and deletions (INDELs) and breakpoints derived from structural variations (SV) were increased, whereas the extent of loss of heterozygosity was decreased in BQ-related OSCC genomes. However, neither the number of base substitutions and microsatellite instability events nor the extent of copy-number alterations differed between BQ-related and -unrelated OSCC. In conclusion, consistent with the proposition that BQ chewing increases OSCC risk as a mutagen, our results unveil a BQ-associated mutational signature and indicate mutagenic impacts of BQ chewing on preferentially eliciting INDELs and SV-related breakpoints in OSCC genomes.

Detection of homozygous deletions in tumor-suppressor genes ranging from dozen to hundreds nucleotides in cancer models.

Tumor-suppressor genes can be inactivated by several mechanisms and, in a majority of cases, both alleles need to be affected. One of the mechanisms of inactivation is due to deletions ranging from dozen to hundreds of nucleotides; such deletions are often missed by variant callers. HomDelDetect is a method to detect such homozygous deletions in cancer models, such as cancer cell lines and potentially patient tumor-derived xenografts. This method can be applied to partial exome, whole-exome sequencing, whole-genome sequencing, and RNA-seq data. We applied our method across a panel of CCLE cancer cell lines and observed good concordance with SNP array-based analysis and also detected deletions that have been missed by variant callers and by SNP arrays, demonstrating the ability of HomDelDetect to improve the annotations of tumor-suppressor genes in cancer models.

A computational method for genotype calling in family-based sequencing data.

BACKGROUND: As sequencing technologies can help researchers detect common and rare variants across the human genome in many individuals, it is known that jointly calling genotypes across multiple individuals based on linkage disequilibrium (LD) can facilitate the analysis of low to modest coverage sequence data. However, genotype-calling methods for family-based sequence data, particularly for complex families beyond parent-offspring trios, are still lacking. RESULTS: In this study, first, we proposed an algorithm that considers both linkage disequilibrium (LD) patterns and familial transmission in nuclear and multi-generational families while retaining the computational efficiency. Second, we extended our method to incorporate external reference panels to analyze family-based sequence data with a small sample size. In simulation studies, we show that modeling multiple offspring can dramatically increase genotype calling accuracy and reduce phasing and Mendelian errors, especially at low to modest coverage. In addition, we show that using external panels can greatly facilitate genotype calling of sequencing data with a small number of individuals. We applied our method to a whole genome sequencing study of 1339 individuals at ~10X coverage from the Minnesota Center for Twin and Family Research. CONCLUSIONS: The aggregated results show that our methods significantly outperform existing ones that ignore family constraints or LD information. We anticipate that our method will be useful for many ongoing family-based sequencing projects. We have implemented our methods efficiently in a C++ program FamLDCaller, which is available from http://www.pitt.edu/~wec47/famldcaller.html.