Age-dependent changes in the gut microbiota and serum metabolome correlate with renal function and human aging.

Human aging is invariably accompanied by a decline in renal function, a process potentially exacerbated by uremic toxins originating from gut microbes. Based on a registered household Chinese Guangxi longevity cohort (n = 151), we conducted comprehensive profiling of the gut microbiota and serum metabolome of individuals from 22 to 111 years of age and validated the findings in two independent East Asian aging cohorts (Japan aging cohort n = 330, Yunnan aging cohort n = 80), identifying unique age-dependent differences in the microbiota and serum metabolome. We discovered that the influence of the gut microbiota on serum metabolites intensifies with advancing age. Furthermore, mediation analyses unveiled putative causal relationships between the gut microbiota (Escherichia coli, Odoribacter splanchnicus, and Desulfovibrio piger) and serum metabolite markers related to impaired renal function (p-cresol, N-phenylacetylglutamine, 2-oxindole, and 4-aminohippuric acid) and aging. The fecal microbiota transplantation experiment demonstrated that the feces of elderly individuals could influence markers related to impaired renal function in the serum. Our findings reveal novel links between age-dependent alterations in the gut microbiota and serum metabolite markers of impaired renal function, providing novel insights into the effects of microbiota-metabolite interplay on renal function and healthy aging.

Immune Repertoire Profiling Reveals Its Clinical Application Potential and Triggers for Neuromyelitis Optica Spectrum Disorders.

BACKGROUND AND OBJECTIVES: Neuromyelitis optica spectrum disorders (NMOSD) is widely recognized as a CNS demyelinating disease associated with AQP4-IgG (T cell-dependent antibody), and its trigger is still unclear. In addition, although the treatment of NMOSD currently can rely on traditional immunosuppressive and modulating agents, effective methods to predict the efficacy of these therapeutics are lacking. METHODS: In this study, high-throughput T-cell receptor (TCR) sequencing was performed on peripheral blood from 151 pretreatment patients with AQP4-IgG+ NMOSD and 151 healthy individuals. We compared the TCR repertoire of those with NMOSD with that of healthy individuals and identified TCR clones that were significantly enriched in NMOSD. In addition, we treated 28 patients with AQP4-IgG+ NMOSD with immunosuppressants and followed up for 6 months to compare changes in NMOSD-specific TCRs (NMOSD-TCRs) before and after treatment. Moreover, we analyzed transcriptome and single-cell B-cell receptor (BCR) data from public databases and performed T-cell activation experiments using antigenic epitopes of cytomegalovirus (CMV) to further explore the triggers of AQP4-IgG+ NMOSD. RESULTS: Compared with healthy controls, patients with AQP4-IgG+ NMOSD had significantly reduced diversity and shorter CDR3 length of TCRß repertoire. Furthermore, we identified 597 NMOSD-TCRs with a high sequence similarity that have the potential to be used in the diagnosis and prognosis of NMOSD. The characterization of NMOSD-TCRs and pathology-associated clonotype annotation indicated that the occurrence of AQP4-IgG+ NMOSD may be associated with CMV infection, which was further corroborated by transcriptome and single-cell BCR analysis results from public databases and T-cell activation experiments. DISCUSSION: Our findings suggest that the occurrence of AQP4-IgG+ NMOSD may be associated with CMV infection. In conclusion, our study provides new clues to uncover the causative factors of AQP4-IgG+ NMOSD and provides a theoretical foundation for treating and monitoring the disease.

The STROMICS genome study: deep whole-genome sequencing and analysis of 10K Chinese patients with ischemic stroke reveal complex genetic and phenotypic interplay.

Ischemic stroke is a leading cause of global mortality and long-term disability. However, there is a paucity of whole-genome sequencing studies on ischemic stroke, resulting in limited knowledge of the interplay between genomic and phenotypic variations among affected patients. Here, we outline the STROMICS design and present the first whole-genome analysis on ischemic stroke by deeply sequencing and analyzing 10,241 stroke patients from China. We identified 135.59 million variants, > 42% of which were novel. Notable disparities in allele frequency were observed between Chinese and other populations for 89 variants associated with stroke risk and 10 variants linked to response to stroke medications. We investigated the population structure of the participants, generating a map of genetic selection consisting of 31 adaptive signals. The adaption of the MTHFR rs1801133-G allele, which links to genetically evaluated VB9 (folate acid) in southern Chinese patients, suggests a gene-specific folate supplement strategy. Through genome-wide association analysis of 18 stroke-related traits, we discovered 10 novel genetic-phenotypic associations and extensive cross-trait pleiotropy at 6 lipid-trait loci of therapeutic relevance. Additionally, we found that the set of loss-of-function and cysteine-altering variants present in the causal gene NOTCH3 for the autosomal dominant stroke disorder CADASIL displayed a broad neuro-imaging spectrum. These findings deepen our understanding of the relationship between the population and individual genetic layout and clinical phenotype among stroke patients, and provide a foundation for future efforts to utilize human genetic knowledge to investigate mechanisms underlying ischemic stroke outcomes, discover novel therapeutic targets, and advance precision medicine.

Integrated multi-omics analyses and functional validation reveal TTK as a novel EMT activator for endometrial cancer.

BACKGROUND: Cancer-testis antigens (CTAs) are often expressed in tumor and testicular tissues but not in other normal tissues. To date, there has been no comprehensive study of the expression and clinical significance of CTA genes associated with endometrial cancer (EC) development. Additionally, the clinical relevance, biological role, and molecular mechanisms of the CTA gene TTK protein kinase (TTK) in EC are yet to be fully understood. METHODS: Using bioinformatics methods, we comprehensively investigated the genomic, transcriptomic, and epigenetic changes associated with aberrant TTK overexpression in EC samples from the TCGA database. We further investigated the mechanisms of the lower survival associated with TTK dysregulation using single-cell data of EC samples from the GEO database. Cell functional assays were used to confirm the biological roles of TTK in EC cells. RESULTS: We identified 80 CTA genes that were more abundant in EC than in normal tissues, and high expression of TTK was significantly linked with lower survival in EC patients. Furthermore, ROC analysis revealed that TTK could accurately distinguish stage I EC tissues from benign endometrial samples, suggesting that TTK has the potential to be a biomarker for early EC detection. We found TTK overexpression was more prevalent in EC patients with high-grade, advanced tumors, serous carcinoma, and TP53 alterations. Furthermore, in EC tissue, TTK expression showed a strong positive correlation with EMT-related genes. With single-cell transcriptome data, we identified a proliferative cell subpopulation with high expression of TTK and known epithelial-mesenchymal transition (EMT)-related genes and transcription factors. When proliferative cells were grouped according to TTK expression levels, the overexpressed genes in the TTKhigh group were shown to be functionally involved in the control of chemoresistance. Utilizing shRNA to repress TTK expression in EC cells resulted in substantial decreases in cell proliferation, invasion, EMT, and chemoresistance. Further research identified microRNA-21 (miR-21) as a key downstream regulator of TTK-induced EMT and chemoresistance. Finally, the TTK inhibitor AZ3146 was effective in reducing EC cell growth and invasion and enhancing the apoptosis of EC cells generated by paclitaxel. CONCLUSION: Our findings establish the clinical significance of TTK as a new biomarker for EC and an as-yet-unknown carcinogenic function. This present study proposes that the therapeutic targeting of TTK might provide a viable approach for the treatment of EC.

CMDB: the comprehensive population genome variation database of China.

A high-quality genome variation database derived from a large-scale population is one of the most important infrastructures for genomics, clinical and translational medicine research. Here, we developed the Chinese Millionome Database (CMDB), a database that contains 9.04 million single nucleotide variants (SNV) with allele frequency information derived from low-coverage (0.06×-0.1×) whole-genome sequencing (WGS) data of 141 431 unrelated healthy Chinese individuals. These individuals were recruited from 31 out of the 34 administrative divisions in China, covering Han and 36 other ethnic minorities. CMDB, housing the WGS data of a multi-ethnic Chinese population featuring wide geographical distribution, has become the most representative and comprehensive Chinese population genome database to date. Researchers can quickly search for variant, gene or genomic regions to obtain the variant information, including mutation basic information, allele frequency, genic annotation and overview of frequencies in global populations. Furthermore, the CMDB also provides information on the association of the variants with a range of phenotypes, including height, BMI, maternal age and twin pregnancy. Based on these data, researchers can conduct meta-analysis of related phenotypes. CMDB is freely available at https://db.cngb.org/cmdb/.

A population-based study of precision health assessments using multi-omics network-derived biological functional modules.

Recent technological advances in multi-omics and bioinformatics provide an opportunity to develop precision health assessments, which require big data and relevant bioinformatic methods. Here we collect multi-omics data from 4,277 individuals. We calculate the correlations between pairwise features from cross-sectional data and then generate 11 biological functional modules (BFMs) in males and 12 BFMs in females using a community detection algorithm. Using the features in the BFM associated with cardiometabolic health, carotid plaques can be predicted accurately in an independent dataset. We developed a model by comparing individual data with the health baseline in BFMs to assess health status (BFM-ash). Then we apply the model to chronic patients and modify the BFM-ash model to assess the effects of consuming grape seed extract as a dietary supplement. Finally, anomalous BFMs are identified for each subject. Our BFMs and BFM-ash model have huge prospects for application in precision health assessment.

Rare Variants in Inborn Errors of Immunity Genes Associated With Covid-19 Severity.

Host genetic factors have been shown to play an important role in SARS-CoV-2 infection and the course of Covid-19 disease. The genetic contributions of common variants influencing Covid-19 susceptibility and severity have been extensively studied in diverse populations. However, the studies of rare genetic defects arising from inborn errors of immunity (IEI) are relatively few, especially in the Chinese population. To fill this gap, we used a deeply sequenced dataset of nearly 500 patients, all of Chinese descent, to investigate putative functional rare variants. Specifically, we annotated rare variants in our call set and selected likely deleterious missense (LDM) and high-confidence predicted loss-of-function (HC-pLoF) variants. Further, we analyzed LDM and HC-pLoF variants between non-severe and severe Covid-19 patients by (a) performing gene- and pathway-level association analyses, (b) testing the number of mutations in previously reported genes mapped from LDM and HC-pLoF variants, and (c) uncovering candidate genes via protein-protein interaction (PPI) network analysis of Covid-19-related genes and genes defined from LDM and HC-pLoF variants. From our analyses, we found that (a) pathways Tuberculosis (hsa:05152), Primary Immunodeficiency (hsa:05340), and Influenza A (hsa:05164) showed significant enrichment in severe patients compared to the non-severe ones, (b) HC-pLoF mutations were enriched in Covid-19-related genes in severe patients, and (c) several candidate genes, such as IL12RB1, TBK1, TLR3, and IFNGR2, are uncovered by PPI network analysis and worth further investigation. These regions generally play an essential role in regulating antiviral innate immunity responses to foreign pathogens and in responding to many inflammatory diseases. We believe that our identified candidate genes/pathways can be potentially used as Covid-19 diagnostic markers and help distinguish patients at higher risk.

Identification of Potential Biomarkers for Pan-Cancer Diagnosis and Prognosis Through the Integration of Large-Scale Transcriptomic Data.

Cancer is one of the leading causes of death worldwide, bringing a significant burden to human health and society. Accurate cancer diagnosis and biomarkers that can be used as robust therapeutic targets are of great importance as they facilitate early and effective therapies. Shared etiology among cancers suggests the existence of pan-cancer biomarkers, performance of which could benefit from the large sample size and the heterogeneity of the studied patients. In this study, we conducted a systematic RNA-seq study of 9,213 tumors and 723 para-cancerous tissue samples of 28 solid tumors from the Cancer Genome Atlas (TCGA) database, and 7,008 normal tissue samples from the Genotype-Tissue Expression (GTEx) database. By differential gene expression analysis, we identified 214 up-regulated and 186 downregulated differentially expressed genes (DEGs) in more than 80% of the studied tumors, respectively, and obtained 20 highly linked up- and downregulated hub genes from them. These markers have rarely been reported in multiple tumors simultaneously. We further constructed pan-cancer diagnostic models to classify tumors and para-cancerous tissues using 10 up-regulated hub genes with an AUC of 0.894. Survival analysis revealed that these hub genes were significantly associated with the overall survival of cancer patients. In addition, drug sensitivity predictions for these hub genes in a variety of tumors obtained several broad-spectrum anti-cancer drugs targeting pan-cancer. Furthermore, we predicted immunotherapy sensitivity for cancers based on tumor mutational burden (TMB) and the expression of immune checkpoint genes (ICGs), providing a theoretical basis for the treatment of tumors. In summary, we identified a set of biomarkers that were differentially expressed in multiple types of cancers, and these biomarkers can be potentially used for diagnosis and used as therapeutic targets.

VIPPID: a gene-specific single nucleotide variant pathogenicity prediction tool for primary immunodeficiency diseases.

Distinguishing pathogenic variants from non-pathogenic ones remains a major challenge in clinical genetic testing of primary immunodeficiency (PID) patients. Most of the existing mutation pathogenicity prediction tools treat all mutations as homogeneous entities, ignoring the differences in characteristics of different genes, and use the same model for genes in different diseases. In this study, we developed a single nucleotide variant (SNV) pathogenicity prediction tool, Variant Impact Predictor for PIDs (VIPPID; https://mylab.shinyapps.io/VIPPID/), which was tailored for PIDs genes and used a specific model for each of the most prevalent PID known genes. It employed a Conditional Inference Forest model and utilized information of 85 features of SNVs and scores from 20 existing prediction tools. Evaluation of VIPPID showed that it had superior performance (area under the curve = 0.91) over non-specific conventional tools. In addition, we also showed that the gene-specific model outperformed the non-gene-specific models. Our study demonstrated that disease-specific and gene-specific models can improve SNV pathogenicity prediction performance. This observation supports the notion that each feature of mutations in the model can be potentially used, in a new algorithm, to investigate the characteristics and function of the encoded proteins.

Calculating and comparing codon usage values in rare disease genes highlights codon clustering with disease-and tissue- specific hierarchy.

We designed a novel strategy to define codon usage bias (CUB) in 6 specific small cohorts of human genes. We calculated codon usage (CU) values in 29 non-disease-causing (NDC) and 31 disease-causing (DC) human genes which are highly expressed in 3 distinct tissues, kidney, muscle, and skin. We applied our strategy to the same selected genes annotated in 15 mammalian species. We obtained CUB hierarchical clusters for each gene cohort which showed tissue-specific and disease-specific CUB fingerprints. We showed that DC genes (especially those expressed in muscle) display a low CUB, well recognizable in codon hierarchical clustering. We defined the extremely biased codons as "zero codons" and found that their number is significantly higher in all DC genes, all tissues, and that this trend is conserved across mammals. Based on this calculation in different gene cohorts, we identified 5 codons which are more differentially used across genes and mammals, underlining that some genes have favorite synonymous codons in use. Since of the muscle genes clear clusters, and, among these, dystrophin gene surprisingly does not show any "zero codon" we adopted a novel approach to study CUB, we called "mapping-on-codons". We positioned 2828 dystrophin missense and nonsense pathogenic variations on their respective codon, highlighting that its frequency and occurrence is not dependent on the CU values. We conclude our strategy consents to identify a hierarchical clustering of CU values in a gene cohort-specific fingerprints, with recognizable trend across mammals. In DC muscle genes also a disease-related fingerprint can be observed, allowing discrimination between DC and NDC genes. We propose that using our strategy which studies CU in specific gene cohorts, as rare disease genes, and tissue specific genes, may provide novel information about the CUB role in human and medical genetics, with implications on synonymous variations interpretation and codon optimization algorithms.

RNA-seq in DMD urinary stem cells recognized muscle-related transcription signatures and addressed the identification of atypical mutations by whole-genome sequencing.

Urinary stem cells (USCs) are a non-invasive, simple, and affordable cell source to study human diseases. Here we show that USCs are a versatile tool for studying Duchenne muscular dystrophy (DMD), since they are able to address RNA signatures and atypical mutation identification. Gene expression profiling of DMD individuals' USCs revealed a profound deregulation of inflammation, muscle development, and metabolic pathways that mirrors the known transcriptional landscape of DMD muscle and worsens following USCs' myogenic transformation. This pathogenic transcription signature was reverted by an exon-skipping corrective approach, suggesting the utility of USCs in monitoring DMD antisense therapy. The full DMD transcript profile performed in USCs from three undiagnosed DMD individuals addressed three splicing abnormalities, which were decrypted and confirmed as pathogenic variations by whole-genome sequencing (WGS). This combined genomic approach allowed the identification of three atypical and complex DMD mutations due to a deep intronic variation and two large inversions, respectively. All three mutations affect DMD gene splicing and cause a lack of dystrophin protein production, and one of these also generates unique fusion genes and transcripts. Further characterization of USCs using a novel cell-sorting technology (Celector) highlighted cell-type variability and the representation of cell-specific DMD isoforms. Our comprehensive approach to USCs unraveled RNA, DNA, and cell-specific features and demonstrated that USCs are a robust tool for studying and diagnosing DMD.

T Cell Repertoire Abnormality in Immunodeficiency Patients with DNA Repair and Methylation Defects.

Both DNA damage response and methylation play a crucial role in antigen receptor recombination by creating a diverse repertoire in developing lymphocytes, but how their defects relate to T cell repertoire and phenotypic heterogeneity of immunodeficiency remains obscure. We studied the TCR repertoire in patients with the mutation in different genes (ATM, DNMT3B, ZBTB24, RAG1, DCLRE1C, and JAK3) and uncovered distinct characteristics of repertoire diversity. We propose that early aberrancies in thymus T cell development predispose to the heterogeneous phenotypes of the immunodeficiency spectrum. Shorter CDR3 lengths in ATM-deficient patients, resulting from a decreased number of nucleotide insertions during VDJ recombination in the pre-selected TCR repertoire, as well as the increment of CDR3 tyrosine residues, lead to the enrichment of pathology-associated TCRs, which may contribute to the phenotypes of ATM deficiency. Furthermore, patients with DNMT3B and ZBTB24 mutations who exhibit discrepant phenotypes present longer CDR3 lengths and reduced number of known pathology-associated TCRs.

Urine-Derived Stem Cells Express 571 Neuromuscular Disorders Causing Genes, Making Them a Potential in vitro Model for Rare Genetic Diseases.

Background: Neuromuscular disorders (NMDs) are a heterogeneous group of genetic diseases, caused by mutations in genes involved in spinal cord, peripheral nerve, neuromuscular junction, and muscle functions. To advance the knowledge of the pathological mechanisms underlying NMDs and to eventually identify new potential drugs paving the way for personalized medicine, limitations regarding the availability of neuromuscular disease-related biological samples, rarely accessible from patients, are a major challenge. Aim: We characterized urinary stem cells (USCs) by in-depth transcriptome and protein profiling to evaluate whether this easily accessible source of patient-derived cells is suitable to study neuromuscular genetic diseases, focusing especially on those currently involved in clinical trials. Methods: The global transcriptomics of either native or MyoD transformed USCs obtained from control individuals was performed by RNA-seq. The expression of 610 genes belonging to 16 groups of disorders (http://www.musclegenetable.fr/) whose mutations cause neuromuscular diseases, was investigated on the RNA-seq output. In addition, protein expression of 11 genes related to NMDs including COL6A, EMD, LMNA, SMN, UBA1, DYNC1H1, SOD1, C9orf72, DYSF, DAG1, and HTT was analyzed in native USCs by immunofluorescence and/or Western blot (WB). Results: RNA-seq profile of control USCs shows that 571 out of 610 genes known to be involved in NMDs, are expressed in USCs. Interestingly, the expression levels of the majority of NMD genes remain unmodified following USCs MyoD transformation. Most genes involved in the pathogenesis of all 16 groups of NMDs are well represented except for channelopathies and malignant hyperthermia related genes. All tested proteins showed high expression values, suggesting consistency between transcription and protein representation in USCs. Conclusion: Our data suggest that USCs are human cells, obtainable by non-invasive means, which might be used as a patient-specific cell model to study neuromuscular disease-causing genes and that they can be likely adopted for a variety of in vitro functional studies such as mutation characterization, pathway identification, and drug screening.

CLEC4s as Potential Therapeutic Targets in Hepatocellular Carcinoma Microenvironment.

Immunosuppressive tumor microenvironment in hepatocellular carcinoma (HCC) is critical in tumor development. C-type (Ca2+ -dependent) lectin (CLEC) receptors, essential in innate pattern recognition, have potential regulatory effects on immune cell trafficking and modulatory effects on cancer cell activity. However, information on the expression and prognostic value of CLECs in HCC is scanty. Herein, we explored the potential role of CLECs in HCC based on TCGA, ONCOMINE, GEPIA, UALCAN, cBioPortal, Metascape, TRRUST, and TIMER databases. Results demonstrated a significantly higher mRNA level of CLEC4A and CLEC4L in HCC tissues than normal liver tissues. Contrarily, we found significantly low CLEC4G/H1/H2/M expression in HCC tissues. The IHC analysis revealed the following: Absence of CLEC4A/J/K/M in normal and liver cancer tissues; high CLEC4C expression in HCC tissues; low expression and zero detection of CLEC4D/E/H1/H2/L in HCC tissues and normal tissues, respectively. And the HepG2 and LX-2 were used to verify the expression level of CLEC4s via qRT-PCR in vitro. Furthermore, the expression of CLEC4H1 (ASGR1) and CLEC4H2 (ASGR2) exhibited a significant relation to clinical stages. However, the expression of CLEC4A, CLEC4D, CLEC4E, CLEC4J (FCER2), CLEC4K (CD207), CLEC4G, CLEC4H1, CLEC4M, and CLEC4H2 decreased with tumor progression. Patients expressing higher CLEC4H1/H2 levels had longer overall survival than patients exhibiting lower expression. Moreover, CLEC4A/D/E/J/K/G/H1/M/H2 had significant down-regulated levels of promoter methylation. The expression level of CLEC4s was correlated with the infiltration of B cells, CD8 + T cells, CD4 + T cells, macrophage cells, neutrophil cells, and dendritic cells. Functional analysis revealed the potential role of CLECL4s in virus infection, including COVID-19. Also, hsa-miR-4278 and hsa-miR-324-5p, two potential miRNA targets of CLEC4s, were uncovered. This article demonstrates that CLEC4 is crucial for the development of HCC and is associated with infiltration of various immune cells, providing evidence for new immunotherapy targets in HCC.

Integrated genetic analyses revealed novel human longevity loci and reduced risks of multiple diseases in a cohort study of 15,651 Chinese individuals.

There is growing interest in studying the genetic contributions to longevity, but limited relevant genes have been identified. In this study, we performed a genetic association study of longevity in a total of 15,651 Chinese individuals. Novel longevity loci, BMPER (rs17169634; p = 7.91 × 10-15 ) and TMEM43/XPC (rs1043943; p = 3.59 × 10-8 ), were identified in a case-control analysis of 11,045 individuals. BRAF (rs1267601; p = 8.33 × 10-15 ) and BMPER (rs17169634; p = 1.45 × 10-10 ) were significantly associated with life expectancy in 12,664 individuals who had survival status records. Additional sex-stratified analyses identified sex-specific longevity genes. Notably, sex-differential associations were identified in two linkage disequilibrium blocks in the TOMM40/APOE region, indicating potential differences during meiosis between males and females. Moreover, polygenic risk scores and Mendelian randomization analyses revealed that longevity was genetically causally correlated with reduced risks of multiple diseases, such as type 2 diabetes, cardiovascular diseases, and arthritis. Finally, we incorporated genetic markers, disease status, and lifestyles to classify longevity or not-longevity groups and predict life span. Our predictive models showed good performance (AUC = 0.86 for longevity classification and explained 19.8% variance of life span) and presented a greater predictive efficiency in females than in males. Taken together, our findings not only shed light on the genetic contributions to longevity but also elucidate correlations between diseases and longevity.

Species-Level Analysis of the Human Gut Microbiome Shows Antibiotic Resistance Genes Associated With Colorectal Cancer.

Colorectal cancer (CRC) is the second leading cause of cancer deaths and continuously increases new cancer cases globally. Accumulating evidence links risks of CRC to antibiotic use. Long-term use and abuse of antibiotics increase the resistance of the gut microbiota; however, whether CRC is associated with antibiotic resistance in gut microbiota is still unclear. In this study, we performed a de novo assembly to metagenomic sequences in 382 CRC patients and 387 healthy controls to obtain representative species-level genome bins (rSGBs) and plasmids and analyzed the abundance variation of species and antibiotic resistance genes (ARGs). Twenty-five species and 65 ARGs were significantly enriched in the CRC patients, and among these ARGs, 12 were multidrug-resistant genes (MRGs), which mainly included acrB, TolC, marA, H-NS, Escherichia coli acrR mutation, and AcrS. These MRGs could confer resistance to fluoroquinolones, tetracyclines, cephalosporins, and rifamycin antibiotics by antibiotic efflux and inactivation. A classification model was built using the abundance of species and ARGs and achieved areas under the curve of 0.831 and 0.715, respectively. Our investigation has identified the antibiotic resistance types of ARGs and suggested that E. coli is the primary antibiotic resistance reservoir of ARGs in CRC patients, providing valuable evidence for selecting appropriate antibiotics in the CRC treatment.

Ethnicity-related DMD Genotype Landscapes in European and Non-European Countries.

OBJECTIVE: Genetic diagnosis and mutation identification are now compulsory for Duchenne (DMD) and Becker muscular dystrophies (BMD), which are due to dystrophin (DMD) gene mutations, either for disease prevention or personalized therapies. To evaluate the ethnic-related genetic assortments of DMD mutations, which may impact on DMD genetic diagnosis pipelines, we studied 328 patients with DMD and BMD from non-European countries. METHODS: We performed a full DMD mutation detection in 328 patients from 10 Eastern European countries (Poland, Hungary, Lithuania, Romania, Serbia, Croatia, Bosnia, Bulgaria, Ukraine, and Russia) and 2 non-European countries (Cyprus and Algeria). We used both conventional methods (multiplex ligation-dependent probe amplification [MLPA] followed by gene-specific sequencing) and whole-exome sequencing (WES) as a pivotal study ran in 28 patients where DMD mutations were already identified by standard techniques. WES output was also interrogated for DMD gene modifiers. RESULTS: We identified DMD gene mutations in 222 male patients. We identified a remarkable allele heterogeneity among different populations with a mutation landscape often country specific. We also showed that WES is effective for picking up all DMD deletions and small mutations and its adoption could allow a detection rate close to 90% of all occurring mutations. Gene modifiers haplotypes were identified with some ethnic-specific configurations. CONCLUSIONS: Our data provide unreported mutation landscapes in different countries, suggesting that ethnicity may orient genetic diagnosis flowchart, which can be adjusted depending on the mutation type frequency, with impact in drug eligibility.