BACKGROUND: The human exposome is composed of diverse metabolites and small chemical compounds originated from endogenous and exogenous sources, respectively. Genetic and environmental factors influence metabolite levels, while the extent of genetic contributions across metabolic pathways is not yet known. Untargeted profiling of human metabolome using high-resolution mass spectrometry (HRMS) combined with genome-wide genotyping allows comprehensive identification of genetically influenced metabolites. As such previous studies of adults discovered and replicated genotype-metabotype associations. However, these associations have not been characterized in children. RESULTS: We conducted the largest genome by metabolome-wide association study to date of children (N = 441) using 619,688 common genetic variants and 14,342 features measured by HRMS. Narrow-sense heritability (h2) estimates of plasma metabolite concentrations using genomic relatedness matrix restricted maximum likelihood (GREML) method showed a bimodal distribution with high h2 (> 0.8) for 15.9% of features and low h2 (< 0.2) for most of features (62.0%). The features with high h2 were enriched for amino acid and nucleic acid metabolism, while carbohydrate and lipid concentrations showed low h2. For each feature, a metabolite quantitative trait loci (mQTL) analysis was performed to identify genetic variants that were potentially associated with plasma levels. Fifty-four associations among 29 features and 43 genetic variants were identified at a genome-wide significance threshold p < 3.5 × 10-12 (= 5 × 10-8/14,342 features). Previously reported associations such as UGT1A1 and bilirubin; PYROXD2 and methyl lysine; and ACADS and butyrylcarnitine were successfully replicated in our pediatric cohort. We found potential candidates for novel associations including CSMD1 and a monostearyl alcohol triglyceride (m/z 781.7483, retention time (RT) 89.3 s); CALN1 and Tridecanol (m/z 283.2741, RT 27.6). A gene-level enrichment analysis using MAGMA revealed highly interconnected modules for dADP biosynthesis, sterol synthesis, and long-chain fatty acid transport in the gene-feature network. CONCLUSION: Comprehensive profiling of plasma metabolome across age groups combined with genome-wide genotyping revealed a wide range of genetic influence on diverse chemical species and metabolic pathways. The developmental trajectory of a biological system is shaped by gene-environment interaction especially in early life. Therefore, continuous efforts on generating metabolomics data in diverse human tissue types across age groups are required to understand gene-environment interaction toward healthy aging trajectories.

BACKGROUND: Blood plasma, one of the most studied liquid biopsies, contains various molecules that have biomarker potential for cancer detection, including cell-free DNA (cfDNA) and cell-free RNA (cfRNA). As the vast majority of cell-free nucleic acids in circulation are non-cancerous, a laboratory workflow with a high detection sensitivity of tumor-derived nucleic acids is a prerequisite for precision oncology. One way to meet this requirement is by the combined analysis of cfDNA and cfRNA from the same liquid biopsy sample. So far, no study has systematically compared the performance of cfDNA and cfRNA co-purification to increase sensitivity. RESULTS: First, we set up a framework using digital PCR (dPCR) technology to quantify cfDNA and cfRNA from human blood plasma in order to compare cfDNA/cfRNA co-purification kit performance. To that end, we optimized two dPCR duplex assays, designed to quantify both cfDNA and cfRNA with the same assays, by ensuring that primers and probes are located within a highly abundant exon. Next, we applied our optimized workflow to evaluate the co-purification performance of two manual and two semi-automated methods over a range of plasma input volumes (0.06-4 mL). Some kits result in higher nucleic acid concentrations in the eluate, while consuming only half of the plasma volume. The combined nucleic acid quantification systematically results in higher nucleic acid concentrations as compared to a parallel quantification of cfDNA and cfRNA in the eluate. CONCLUSIONS: We provide a framework to evaluate the performance of cfDNA/cfRNA co-purification kits and have tested two manual and two semi-automated co-purification kits in function of the available plasma input amount and the intended use of the nucleic acid eluate. We demonstrate that the combined quantification of cfDNA and cfRNA has a benefit compared to separate quantification. We foresee that the results of this study are instrumental for clinical applications to help increase mutation detection sensitivity, allowing improved disease detection and monitoring.

BACKGROUND: Novel biomarkers for personalizing anticoagulation remain undetermined. We aimed to investigate the association of plasma miRNAs with pharmacokinetic-pharmacodynamic (PK-PD) profiles of rivaroxaban. METHODS: This is a multicenter, exploratory study of miRNAs in a Chinese population. Healthy volunteers and patients receiving rivaroxaban were enrolled in the study. The area under the plasma concentration-time curve from time 0-t h (AUC0-t) and anti-Xa activity at 3 h (AXA3h) were measured in healthy volunteers, and AXA3h was measured in patients. MiRNAs were detected by miRNA microarray in 26 healthy volunteers with 20 mg rivaroxaban, and quantitative reverse transcription polymerase chain reaction was used to exclude undetectable ones. MiR-320a-3p and miR-483-5p were then quantified in 65 healthy volunteers and 71 patients. MiRNA levels at 3 h were compared between high and low AXA3h or AUC0-t subjects and in matched patients with or without bleeding during follow-up. The miRNA targets were predicted by TargetScan, miRTarBase, and miRDB. Validated genes were included in GO enrichment and KEGG analyses. The protein-protein interaction network was established by STRING and visualized by Cytoscape. RESULTS: A total of 136 Chinese subjects completed the study. In healthy volunteers taking 15 mg rivaroxaban, the miR-320a level at 3 h was significantly positively correlated with AXA3h and AUC0-t (r = 0.359, p = 0.025; r = 0.370, p = 0.02, respectively). A positive correlation was also observed between miR-483 and AXA3h or AUC0-t (r = 0.372, p = 0.02; r = 0.523, p = 0.001, respectively). MiR-320a and miR-483 levels at 3 h in the higher AUC0-t group were significantly higher than those at 0 h. MiR-483 levels at 3 h may distinguish healthy volunteers with high or low AXA3h or AUC0-t. In the 10 mg fed subgroup, higher 3 h mir-483 levels were also observed compared with the control group. No significant differences were found in the comparisons among patients. Bioinformatic analysis showed that these miRNAs may play a regulatory role by targeting ABCG2, ITGB3, PTEN, MAPK1/3, etc. CONCLUSIONS: MiR-320a and miR-483 levels were found to be associated with PK and PD profiles of rivaroxaban in healthy Chinese subjects. Further studies are required to verify these findings and explore the mechanisms.

Preimplantation genetic testing for aneuploidy (PGT-A) has been used widely during in vitro fertilization procedures in assisted reproductive centers throughout the world. Despite its wide use, concerns arise from the use of PGT-A technology in clinical decision-making. We address knowledge gaps in PGT-A, summarizing major challenges and current professional guidelines. First, PGT-A is a screening test and not a diagnostic test. Second, mosaicism is much higher in the blastocyst stage from PGT-A than had been recognized previously and a mosaic embryo may not accurately represent the genetic disease risk for future fetal disorders. Third, PGT-A was not validated clinically before use in patients; the best use of this technology for selected age-groups remains uncertain. Given these gaps, we believe that current professional policies relying on industry-self-regulation are insufficient. In the USA, the Food and Drug Administration may be the most appropriate agency to provide more definitive guidelines and regulations that are needed for better practice.

BACKGROUND: Epilepsy, a serious chronic neurological condition effecting up to 100 million people globally, has clear genetic underpinnings including common and rare variants. In Saudi Arabia, the prevalence of epilepsy is high and caused mainly by perinatal and genetic factors. No whole-exome sequencing (WES) studies have been performed to date in Saudi Arabian epilepsy cohorts. This offers a unique opportunity for the discovery of rare genetic variants impacting this disease as there is a high rate of consanguinity among large tribal pedigrees. RESULTS: We performed WES on 144 individuals diagnosed with epilepsy, to interrogate known epilepsy-related genes for known and functional novel variants. We also used an American College of Medical Genetics (ACMG) guideline-based variant prioritization approach in an attempt to discover putative causative variants. We identified 32 potentially causative pathogenic variants across 30 different genes in 44/144 (30%) of these Saudi epilepsy individuals. We also identified 232 variants of unknown significance (VUS) across 101 different genes in 133/144 (92%) subjects. Strong enrichment of variants of likely pathogenicity was observed in previously described epilepsy-associated loci, and a number of putative pathogenic variants in novel loci are also observed. CONCLUSION: Several putative pathogenic variants in known epilepsy-related loci were identified for the first time in our population, in addition to several potential new loci which may be prioritized for further investigation.

BACKGROUND: Triple-negative breast cancer (TNBC) is a very heterogeneous disease. Several gene expression and mutation profiling approaches were used to classify it, and all converged to the identification of distinct molecular subtypes, with some overlapping across different approaches. However, a standardised tool to routinely classify TNBC in the clinics and guide personalised treatment is lacking. We aimed at defining a specific gene signature for each of the six TNBC subtypes proposed by Lehman et al. in 2011 (basal-like 1 (BL1); basal-like 2 (BL2); mesenchymal (M); immunomodulatory (IM); mesenchymal stem-like (MSL); and luminal androgen receptor (LAR)), to be able to accurately predict them. METHODS: Lehman's TNBCtype subtyping tool was applied to RNA-sequencing data from 482 TNBC (GSE164458), and a minimal subtype-specific gene signature was defined by combining two class comparison techniques with seven attribute selection methods. Several machine learning algorithms for subtype prediction were used, and the best classifier was applied on microarray data from 72 Italian TNBC and on the TNBC subset of the BRCA-TCGA data set. RESULTS: We identified two signatures with the 120 and 81 top up- and downregulated genes that define the six TNBC subtypes, with prediction accuracy ranging from 88.6 to 89.4%, and even improving after removal of the least important genes. Network analysis was used to identify highly interconnected genes within each subgroup. Two druggable matrix metalloproteinases were found in the BL1 and BL2 subsets, and several druggable targets were complementary to androgen receptor or aromatase in the LAR subset. Several secondary drug-target interactions were found among the upregulated genes in the M, IM and MSL subsets. CONCLUSIONS: Our study took full advantage of available TNBC data sets to stratify samples and genes into distinct subtypes, according to gene expression profiles. The development of a data mining approach to acquire a large amount of information from several data sets has allowed us to identify a well-determined minimal number of genes that may help in the recognition of TNBC subtypes. These genes, most of which have been previously found to be associated with breast cancer, have the potential to become novel diagnostic markers and/or therapeutic targets for specific TNBC subsets.

The HUGO Gene Nomenclature Committee assigns unique symbols and names to human genes. The use of approved nomenclature enables effective communication between researchers, and there are multiple examples of how the usage of unapproved alias symbols can lead to confusion. We discuss here a recent nomenclature update (May 2022) for a set of genes that encode proteins with a shared repeating β-groove domain. Some of the proteins encoded by genes in this group have already been shown to function as lipid transporters. By working with researchers in the field, we have been able to introduce a new root symbol (BLTP, which stands for "bridge-like lipid transfer protein") for this domain-based gene group. This new nomenclature not only reflects the shared domain in these proteins, but also takes into consideration the mounting evidence of a shared lipid transport function.

BACKGROUND: The tripartite motif (TRIM) proteins function as important regulators in innate immunity, tumorigenesis, cell differentiation and ontogenetic development. However, we still lack knowledge about the genetic and transcriptome alterations landscape of TRIM proteins across cancer types. METHODS: We comprehensively reviewed and characterized the perturbations of TRIM genes across > 10,000 samples across 33 cancer types. Genetic mutations and transcriptome of TRIM genes were analyzed by diverse computational methods. A TRIMs score index was calculated based on the expression of TRIM genes. The correlation between TRIMs scores and clinical associations, immune cell infiltrations and immunotherapy response were analyzed by correlation coefficients and gene set enrichment analysis. RESULTS: Alterations in TRIM genes and protein levels frequently emerge in a wide range of tumors and affect expression of TRIM genes. In particular, mutations located in domains are likely to be deleterious mutations. Perturbations of TRIM genes are correlated with expressions of immune checkpoints and immune cell infiltrations, which further regulated the cancer- and immune-related pathways. Moreover, we proposed a TRIMs score index, which can accurately predict the clinical outcome of cancer patients. TRIMs scores of patients are correlated with clinical survival and immune therapy response across cancer types. Identifying the TRIM genes with genetic and transcriptome alterations will directly contribute to cancer therapy in the context of predictive, preventive, and personalized medicine. CONCLUSIONS: Our study provided a comprehensive analysis and resource for guiding both mechanistic and therapeutic analyses of the roles of TRIM genes in cancer.

BACKGROUND: Aneuploidies are the most common chromosomal abnormality and the main genetic cause of adverse pregnancy outcomes. Since numerous studies have focused on common trisomies, relatively little is known about the association between phenotypic findings and rare autosomal aneuploidies (RAAs). We conducted a retrospective study of 48,904 cases for chromosomal microarray analysis in a large tertiary referral center and reported the overall frequencies, clinical manifestations, and outcomes of prenatal RAAs. RESULTS: A total of 90 RAAs were detected, of which 83 cases were mosaic trisomies and 7 were non-mosaic trisomies. Chromosomes 16, 22, and 9 were identified as the major chromosomes involving RAAs. The four predominant indications for prenatal diagnosis in our RAA cases were RAA-positive in noninvasive prenatal screening, advanced maternal age, ultrasound abnormalities, and high-risk for serum prenatal screening. Cardiovascular defects were the most frequently observed structural abnormalities, followed by musculoskeletal anomalies. Increased nuchal translucency and persistent left superior vena cava, the major soft marker abnormalities involved, were also observed in our RAA cases. Clinical outcomes were available for all RAAs, with 63 induced abortions and 27 live births recorded. CONCLUSIONS: Variable phenotypes and outcomes were observed, which were highly heterogeneous in cases of prenatal RAAs. Thus, a cautious and comprehensive strategy should be implemented during prenatal counseling for RAAs.