Disease-associated Genetic Variants Research Articles

Genetic determinants of renal scarring in children with febrile UTI.

Febrile urinary tract infections (UTIs) are among the most severe bacterial infections in infants, in which a subset of patients develops complications. Identifying infants at risk of recurrent infections or kidney damage based on clinical signs is challenging. Previous observations suggest that genetic factors influence UTI outcomes and could serve as predictors of disease severity. In this study, we conducted a nationwide survey of infant genotypes to develop a strategy for infection management based on individual genetic risk. Our aims were to identify genetic susceptibility variants for renal scarring(RS) and genetic host factors predisposing to dilating vesicoureteral reflux (VUR) and recurrent UTIs. To assess genetic susceptibility, we collected and analyzed DNA from blood using exome genotyping. Disease-associated genetic variants were identified through bioinformatics analysis, including allelic frequency tests and odds ratio calculations. Kidney involvement was defined using dimercaptosuccinic acid (DMSA) scintigraphy. In this investigation, a cohort comprising 1087 infants presenting with their first episode of febrile UTI was included. Among this cohort, a subset of 137 infants who underwent DMSA scanning was subjected to gene association analysis. Remarkable genetic distinctions were observed between patients with RS and those exhibiting resolved kidney involvement. Notably, the genetic signature indicative of renal scarring prominently featured mitochondrial genes. In this nationwide study of genetic susceptibility to RS after febrile UTIs in infancy, we identified a profile dominated by mitochondrial polymorphisms. This profile can serve as a predictor of future complications, including RS and recurrent UTIs.

The HLA region in ANCA-associated vasculitis: characterisation of genetic associations in a Scandinavian patient population

ObjectiveThe antineutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAV) are inflammatory disorders with ANCA autoantibodies recognising either proteinase 3 (PR3-AAV) or myeloperoxidase (MPO-AAV). PR3-AAV and MPO-AAV have been associated with distinct loci...

Polygenic risk associated with Alzheimer's disease and other traits influences genes involved in T cell signaling and activation.

T cells, known for their ability to respond to an enormous variety of pathogens and other insults, are increasingly recognized as important mediators of pathology in neurodegeneration and other diseases. T cell gene expression phenotypes can be regulated by disease-associated genetic variants. Many complex diseases are better represented by polygenic risk than by individual variants. We first compute a polygenic risk score (PRS) for Alzheimer's disease (AD) using genomic sequencing data from a cohort of Alzheimer's disease (AD) patients and age-matched controls, and validate the AD PRS against clinical metrics in our cohort. We then calculate the PRS for several autoimmune disease, neurological disorder, and immune function traits, and correlate these PRSs with T cell gene expression data from our cohort. We compare PRS-associated genes across traits and four T cell subtypes. Several genes and biological pathways associated with the PRS for these traits relate to key T cell functions. The PRS-associated gene signature generally correlates positively for traits within a particular category (autoimmune disease, neurological disease, immune function) with the exception of stroke. The trait-associated gene expression signature for autoimmune disease traits was polarized towards CD4+ T cell subtypes. Our findings show that polygenic risk for complex disease and immune function traits can have varying effects on T cell gene expression trends. Several PRS-associated genes are potential candidates for therapeutic modulation in T cells, and could be tested in in vitro applications using cells from patients bearing high or low polygenic risk for AD or other conditions.

SingleQ: a comprehensive database of single-cell expression quantitative trait loci (sc-eQTLs) cross human tissues.

Mapping of expression quantitative trait loci (eQTLs) and other molecular QTLs can help characterize the modes of action of disease-associated genetic variants. However, current eQTL databases present data from bulk RNA-seq approaches, which cannot shed light on the cell type- and environment-specific regulation of disease-associated genetic variants. Here, we introduce our Single-cell eQTL Interactive Database which collects single-cell eQTL (sc-eQTL) datasets and provides online visualization of sc-eQTLs across different cell types in a user-friendly manner. Although sc-eQTL mapping is still in its early stage, our database curates the most comprehensive summary statistics of sc-eQTLs published to date. sc-eQTL studies have revolutionized our understanding of gene regulation in specific cellular contexts, and we anticipate that our database will further accelerate the research of functional genomics. Database URL: http://www.sqraolab.com/scqtl.

Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens

BackgroundDrug targets with genetic evidence are expected to increase clinical success by at least twofold. Yet, translating disease-associated genetic variants into functional knowledge remains a fundamental challenge of drug discovery. A key issue is that the vast majority of complex disease associations cannot be cleanly mapped to a gene. Immune disease-associated variants are enriched within regulatory elements found in T-cell-specific open chromatin regions.ResultsTo identify genes and molecular programs modulated by these regulatory elements, we develop a CRISPRi-based single-cell functional screening approach in primary human T cells. Our pipeline enables the interrogation of transcriptomic changes induced by the perturbation of regulatory elements at scale. We first optimize an efficient CRISPRi protocol in primary CD4+ T cells via CROPseq vectors. Subsequently, we perform a screen targeting 45 non-coding regulatory elements and 35 transcription start sites and profile approximately 250,000 T -cell single-cell transcriptomes. We develop a bespoke analytical pipeline for element-to-gene (E2G) mapping and demonstrate that our method can identify both previously annotated and novel E2G links. Lastly, we integrate genetic association data for immune-related traits and demonstrate how our platform can aid in the identification of effector genes for GWAS loci.ConclusionsWe describe “primary T cell crisprQTL” — a scalable, single-cell functional genomics approach for mapping regulatory elements to genes in primary human T cells. We show how this framework can facilitate the interrogation of immune disease GWAS hits and propose that the combination of experimental and QTL-based techniques is likely to address the variant-to-function problem.

Blood donor biobank as a resource in personalised biomedical genetic research.

Health questionnaires and donation criteria result in accumulation of highly selected individuals in ablood donor population. To understand better the usefulness of ablood donor-based biobank in personalised disease-associated genetic studies, and for possible personalised blood donation policies, we evaluated the occurrence and distributions of common and rare disease-associated genetic variants in Finnish Blood Service Biobank. We analysed among 31,880 blood donors the occurrence and geographical distribution of (i) 53 rare Finnish-enriched disease-associated variants, (ii) mutations assumed to influence blood donation: four Bernard-Soulier syndrome and two hemochromatosis mutations, (iii) type I diabetes risk genotype HLA-DQ2/DQ8. In addition, we analysed the level of consanguinity in Blood Service Biobank. 80.3% of blood donors carried at least one (range 0-9 per donor) of the rare variants, many in homozygous form, as well. Donors carrying multiple rare variants were enriched in Eastern Finland. Haemochromatosis mutation HFE C282Y homozygosity was 43.8% higher than expected, whereas mutations leading to Bernard-Soulier thrombocytopenia were rare. The frequency of HLA-DQ2/DQ8 genotype was slightly lower than expected. First-degree consanguinity was higher in Blood Service Biobank than in the general population. We demonstrate that despite donor selection, the Blood Service Biobank is a valuable resource for personalised medical research and for genotype-selected samples from unaffected individuals. The geographical genetic substructure of Finland enables efficient recruitment of donors carrying rare variants. Furthermore, we show that blood donor biobank material can be utilised for personalised blood donation policies.

Integrating External Controls by Regression Calibration for Genome-Wide Association Study.

Genome-wide association studies (GWAS) have successfully revealed many disease-associated genetic variants. For a case-control study, the adequate power of an association test can be achieved with a large sample size, although genotyping large samples is expensive. A cost-effective strategy to boost power is to integrate external control samples with publicly available genotyped data. However, the naive integration of external controls may inflate the type I error rates if ignoring the systematic differences (batch effect) between studies, such as the differences in sequencing platforms, genotype-calling procedures, population stratification, and so forth. To account for the batch effect, we propose an approach by integrating External Controls into the Association Test by Regression Calibration (iECAT-RC) in case-control association studies. Extensive simulation studies show that iECAT-RC not only can control type I error rates but also can boost statistical power in all models. We also apply iECAT-RC to the UK Biobank data for M72 Fibroblastic disorders by considering genotype calling as the batch effect. Four SNPs associated with fibroblastic disorders have been detected by iECAT-RC and the other two comparison methods, iECAT-Score and Internal. However, our method has a higher probability of identifying these significant SNPs in the scenario of an unbalanced case-control association study.

Whole exome sequencing of patients with varicella-zoster virus and herpes simplex virus induced acute retinal necrosis reveals rare disease-associated genetic variants.

Herpes simplex virus (HSV) and varicella-zoster virus (VZV) are neurotropic human alphaherpesviruses endemic worldwide. Upon primary infection, both viruses establish lifelong latency in neurons and reactivate intermittently to cause a variety of mild to severe diseases. Acute retinal necrosis (ARN) is a rare, sight-threatening eye disease induced by ocular VZV or HSV infection. The virus and host factors involved in ARN pathogenesis remain incompletely described. We hypothesize an underlying genetic defect in at least part of ARN cases. We collected blood from 17 patients with HSV-or VZV-induced ARN, isolated DNA and performed Whole Exome Sequencing by Illumina followed by analysis in Varseq with criteria of CADD score > 15 and frequency in GnomAD < 0.1% combined with biological filters. Gene modifications relative to healthy control genomes were filtered according to high quality and read-depth, low frequency, high deleteriousness predictions and biological relevance. We identified a total of 50 potentially disease-causing genetic variants, including missense, frameshift and splice site variants and on in-frame deletion in 16 of the 17 patients. The vast majority of these genes are involved in innate immunity, followed by adaptive immunity, autophagy, and apoptosis; in several instances variants within a given gene or pathway was identified in several patients. We propose that the identified variants may contribute to insufficient viral control and increased necrosis ocular disease presentation in the patients and serve as a knowledge base and starting point for the development of improved diagnostic, prophylactic, and therapeutic applications.

TargetGene: a comprehensive database of cell-type-specific target genes for genetic variants.

Annotating genetic variants to their target genes is of great importance in unraveling the causal variants and genetic mechanisms that underlie complex diseases. However, disease-associated genetic variants are often located in non-coding regions and manifest context-specific effects, making it challenging to accurately identify the target genes and regulatory mechanisms. Here, we present TargetGene (https://ngdc.cncb.ac.cn/targetgene/), a comprehensive database reporting target genes for human genetic variants from various aspects. Specifically, we collected a comprehensive catalog of multi-omics data at the single-cell and bulk levels and from various human tissues, cell typesand developmental stages. To facilitate the identification of Single Nucleotide Polymorphism (SNP)-to-gene connections, we have implemented multiple analytical tools based on chromatin co-accessibility, 3D interaction, enhancer activitiesand quantitative trait loci, among others. We applied the pipeline to evaluate variants from nearly 1300 Genome-wide association studies (GWAS) and assembled a comprehensive atlas of multiscale regulation of genetic variants. TargetGene is equipped with user-friendly web interfaces that enable intuitive searching, navigationand browsing through the results. Overall, TargetGene provides a unique resource to empower researchers to study the regulatory mechanisms of genetic variants in complex human traits.

DisVar: an R library for identifying variants associated with diseases using large-scale personal genetic information.

Genetic variants may potentially play a contributing factor in the development of diseases. Several genetic disease databases are used in medical research and diagnosis but the web applications used to search these databases for disease-associated variants have limitations. The application may not be able to search for large-scale genetic variants, the results of searches may be difficult to interpret and variants mapped from the latest reference genome (GRCH38/hg38) may not be supported. In this study, we developed a novel R library called "DisVar" to identify disease-associated genetic variants in large-scale individual genomic data. This R library is compatible with variants from the latest reference genome version. DisVar uses five databases of disease-associated variants. Over 100 million variants can be simultaneously searched for specific associated diseases. The package was evaluated using 24 Variant Call Format (VCF) files (215,054 to 11,346,899 sites) from the 1000 Genomes Project. Disease-associated variants were detected in 298,227 hits across all the VCF files, taking a total of 63.58 m to complete. The package was also tested on ClinVar's VCF file (2,120,558 variants), where 20,657 hits associated with diseases were identified with an estimated elapsed time of 45.98 s. DisVar can overcome the limitations of existing tools and is a fast and effective diagnostic and preventive tool that identifies disease-associated variations from large-scale genetic variants against the latest reference genome.

Loss of Grin2a causes a transient delay in the electrophysiological maturation of hippocampal parvalbumin interneurons

N-methyl-D-aspartate receptors (NMDARs) are ligand-gated ionotropic glutamate receptors that mediate a calcium-permeable component to fast excitatory neurotransmission. NMDARs are heterotetrameric assemblies of two obligate GluN1 subunits (GRIN1) and two GluN2 subunits (GRIN2A-GRIN2D). Sequencing data shows that 43% (297/679) of all currently known NMDAR disease-associated genetic variants are within the GRIN2A gene, which encodes the GluN2A subunit. Here, we show that unlike missense GRIN2A variants, individuals affected with disease-associated null GRIN2A variants demonstrate a transient period of seizure susceptibility that begins during infancy and diminishes near adolescence. We show increased circuit excitability and CA1 pyramidal cell output in juvenile mice of both Grin2a+/− and Grin2a−/− mice. These alterations in somatic spiking are not due to global upregulation of most Grin genes (including Grin2b). Deeper evaluation of the developing CA1 circuit led us to uncover age- and Grin2a gene dosing-dependent transient delays in the electrophysiological maturation programs of parvalbumin (PV) interneurons. We report that Grin2a+/+ mice reach PV cell electrophysiological maturation between the neonatal and juvenile neurodevelopmental timepoints, with Grin2a+/− mice not reaching PV cell electrophysiological maturation until preadolescence, and Grin2a−/− mice not reaching PV cell electrophysiological maturation until adulthood. Overall, these data may represent a molecular mechanism describing the transient nature of seizure susceptibility in disease-associated null GRIN2A patients.

A cell-based assay for rapid assessment of ACE2 catalytic function

Angiotensin-converting enzyme II (ACE2) is a monocarboxypeptidase expressed throughout multiple tissues and its catalysis of bioactive peptides regulates the renin-angiotensin system mediating blood pressure homeostasis. ACE2 is implicated in a variety of diseases, including obesity, diabetes, and cardiovascular diseases, and is the obligate entry receptor for SARS-CoV-2 infection. Disease-associated genetic variants of ACE2 are increasingly being identified but are poorly characterized. To aid this problem, we introduce a fluorometric cell-based assay for evaluating surface-expressed ACE2 catalytic activity that preserves the native glycosylation of the host environment and is amenable to high-throughput analysis of ACE2 variants in multi-well plates. We demonstrate sensitivity to detecting catalysis of the key ACE2 substrates, Angiotensin II, Apelin-13, and des-Arg9-bradykinin, and impact of a catalytically-deficient ACE2 variant. Normalizing catalytic measures to surface ACE2 expression accounts for variability in ACE2 variant transfection, surface delivery or stability. This assay provides a convenient and powerful approach for investigating the catalytic characteristics of ACE2 variants involved in cardiovascular peptide cascades and homeostasis of multiple organs.

Screening properties of trend tests in genetic association studies

In genome-wide association study, extracting disease-associated genetic variants among millions of single nucleotide polymorphisms is of great importance. When the response is a binary variable, the Cochran-Armitage trend tests and associated MAX test are among the most widely used methods for association analysis. However, the theoretical guarantees for applying these methods to variable screening have not been built. To fill this gap, we propose screening procedures based on adjusted versions of these methods and prove their sure screening properties and ranking consistency properties. Extensive simulations are conducted to compare the performances of different screening procedures and demonstrate the robustness and efficiency of MAX test-based screening procedure. A case study on a dataset of type 1 diabetes further verifies their effectiveness.

The interaction between enhancer variants and environmental factors as an overlooked aetiological paradigm in human complex disease.

The interactions between genetic and environmental risk factors contribute to the aetiology of complex human diseases. Genome-wide association studies (GWAS) have revealed that most of the genetic variants associated with complex diseases are located in the non-coding part of the genome, preferentially within enhancers. Enhancers are distal cis-regulatory elements composed of clusters of transcription factors binding sites that positively regulate the expression of their target genes. The generation of genome-wide maps for histone marks (e.g., H3K27ac), chromatin accessibility and transcription factor and coactivator (e.g., p300) binding profiles have enabled the identification of enhancers across many human cell types and tissues. Nonetheless, the functional and pathological consequences of the majority of disease-associated genetic variants located within enhancers seem to be rather minor under normal conditions, thus questioning their medical relevance. Here we propose that, due to the prevalence of enhancer redundancy, the pathological effects of many disease-associated non-coding genetic variants might be preferentially (or even only) manifested under environmental stress.

PO-01-178 MAPPING OF PATHOGENIC VARIANT HOTSPOTS ON THE STRUCTURE OF RYANODINE RECEPTOR TYPE 2 DRIVES A RATIONAL DRUG DESIGN APPROACH FOR CATECHOLAMINERGIC POLYMORPHIC VENTRICULAR TACHYCARDIA

Heritable mutations in RYR2 cause sudden-death predisposing arrhythmia syndromes, such as catecholaminergic polymorphic ventricular tachycardia (CPVT), through increased sarcoplasmic reticulum (SR) diastolic Ca2+ leak. RYR2-encoded ryanodine receptor 2 is an intracellular transmembrane Ca2+ release channel in the SR of cardiomyocytes. Even on optimal medical therapy, breakthrough life-threatening arrhythmias in patients with CPVT are common. We sought to correlate identified pathogenic hotspots with key functional domains on the 3D structure of RyR2 and possible mobile binding sites to determine small molecule targets for reducing SR Ca2+ leak. We performed “signal” to “noise” (S:N) analysis in RYR2 to establish pathogenic hotspots. The minor allele frequency (MAF) of literature-derived disease-associated genetic variants at a given amino acid locus was normalized to the MAF of rare population-based variants in Genome Aggregation Database (gnomAD). Using PyMOL, a heat map overlay was generated using S:N levels and possible molecular binding pockets were identified using software PyMOL and Maestro. The highest cumulative S:N intensity of pathogenic hotspots of each domain localized on the channel domain (28.2%), helical domain 1 (25.6%), central domain (17.7%), and N-terminal domain (16.5%) of RyR2. The SPRY1 (0.498%), P1 (0.147%), handle domain (2.32%), and central U motif (8.88%) had lower S:N. Cumulative S:N intensities were nonexistent for SPRY2, SPRY3, P2, and helical domain 2. Putative small molecule binding pockets were identified in all domains while the largest number localized to the channel domain. Once binding pockets were combined with the heat map structure of RyR2, activator binding pockets of low S:N threshold in the open state of RyR2 were shown to be located heavily on the P2 domain, where CaMKII and PKA binds. The highest S:N intensity was in the channel domain with high S:N levels in other proximal domains localizing near the SR transmembrane in the lumen. Mobile binding pockets between the open and closed state of RyR2 with low S:N intensity may be alternative areas for drug targeting, especially on domains that contain binding pockets for activators of RYR2.

Unlocking Genetic Profiles with a Programmable DNA-Powered Decoding Circuit.

Human genetic architecture provides remarkable insights into disease risk prediction and personalized medication. Advances in genomics have boosted the fine-mapping of disease-associated genetic variants across human genome. In healthcare practice, interpreting intricate genetic profiles into actionable medical decisions can improve health outcomes but remains challenging. Here an intelligent genetic decoder is engineered with programmable DNA computation to automate clinical analyses and interpretations. The DNA-based decoder recognizes multiplex genetic information by one-pot ligase-dependent reactions and interprets implicit genetic profiles into explicit decision reports. It is shown that the DNA decoder implements intended computation on genetic profiles and outputs a corresponding answer within hours. Effectiveness in 30 human genomic samples is validated and it is shown that it achieves desirable performance on the interpretation of CYP2C19 genetic profiles into drug responses, with accuracy equivalent to that of Sanger sequencing. Circuit modules of the DNA decoder can also be readily reprogrammed to interpret another pharmacogenetics genes, provide drug dosing recommendations, and implement reliable molecular calculation of polygenic risk score (PRS) and PRS-informed cancer risk assessment. The DNA-powered intelligent decoder provides a general solution to the translation of complex genetic profiles into actionable healthcare decisions and will facilitate personalized healthcare in primary care.

Bi-level structured functional analysis for genome-wide association studies.

Genome-wide association studies (GWAS) have led to great successes in identifying genotype-phenotype associations for complex human diseases. In such studies, the high dimensionality of single nucleotide polymorphisms (SNPs) often makes analysis difficult. Functional analysis, which interprets SNPs densely distributed in a chromosomal region as a continuous process rather than discrete observations, has emerged as a promising avenue for overcoming the high dimensionality challenges. However, the majority of the existing functional studies continue to be individual SNP based and are unable to sufficiently account for the intricate underpinning structures of SNP data. SNPs are often found in groups (e.g., genes or pathways) and have a natural group structure. Additionally, these SNP groups can be highly correlated with coordinated biological functions and interact in a network. Motivated by these unique characteristics of SNP data, we develop a novel bi-level structured functional analysis method and investigate disease-associated genetic variants at the SNP level and SNP group level simultaneously. The penalization technique is adopted for bi-level selection and also to accommodate the group-level network structure. Both the estimation and selection consistency properties are rigorously established. The superiority of the proposed method over alternatives is shown through extensive simulation studies. A type 2 diabetes SNP data application yields some biologically intriguingresults.

Genomic Diversity and Runs of Homozygosity in Bernese Mountain Dogs

Bernese mountain dogs are a large dog breed formed in the early 1900s in Switzerland. While originally farm dogs that were used for pulling carts, guarding, and driving cattle, today they are considered multi-purpose companion and family dogs. The breed is predisposed to several complex diseases, such as histiocytic sarcoma, degenerative myelopathy, or hip dysplasia. Using whole-genome sequencing (WGS) data, we assessed the genomic architecture of 33 unrelated dogs from four countries: France, Sweden, Switzerland, and the United States. Analysis of runs of homozygosity (ROH) identified 12,643 ROH with an average length of 2.29 Mb and an average inbreeding coefficient of 0.395. Multidimensional scaling analysis of the genetic relatedness revealed limited clustering of European versus USA dogs, suggesting exchanges of breeding stock between continents. Furthermore, only two mtDNA haplotypes were detected in the 33 studied dogs, both of which are widespread throughout multiple dog breeds. WGS-based ROH analyses revealed several fixed or nearly fixed regions harboring discreet morphological trait-associated as well as disease-associated genetic variants. Several genes involved in the regulation of immune cells were found in the ROH shared by all dogs, which is notable in the context of the breed's strong predisposition to hematopoietic cancers. High levels of inbreeding and relatedness, strongly exaggerated in the last 30 years, have likely led to the high prevalence of specific genetic disorders in this breed.

Chromosome conformation capture approaches to investigate 3D genome architecture in Ankylosing Spondylitis.

Ankylosing Spondylitis (AS) is a chronic inflammatory arthritis of the spine exhibiting a strong genetic background. The mechanistic and functional understanding of the AS-associated genomic loci, identified with Genome Wide Association Studies (GWAS), remains challenging. Chromosome conformation capture (3C) and derivatives are recent techniques which are of great help in elucidating the spatial genome organization and of enormous support in uncover a mechanistic explanation for disease-associated genetic variants. The perturbation of three-dimensional (3D) genome hierarchy may lead to a plethora of human diseases, including rheumatological disorders. Here we illustrate the latest approaches and related findings on the field of genome organization, highlighting how the instability of 3D genome conformation may be among the causes of rheumatological disease phenotypes. We suggest a new perspective on the inclusive potential of a 3C approach to inform GWAS results in rheumatic diseases. 3D genome organization may ultimately lead to a more precise and comprehensive functional interpretation of AS association, which is the starting point for emerging and more specific therapies.

A DNA methylation atlas of normal human cell types

DNA methylation is a fundamental epigenetic mark that governs gene expression and chromatin organization, thus providing a window into cellular identity and developmental processes1. Current datasets typically include only a fraction of methylation sites and are often based either on cell lines that underwent massive changes in culture or on tissues containing unspecified mixtures of cells2–5. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing, allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell type are more than 99.5% identical, demonstrating the robustness of cell identity programmes to environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny and identifies methylation patterns retained since embryonic development. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hypermethylated loci are rare and are enriched for CpG islands, Polycomb targets and CTCF binding sites, suggesting a new role in shaping cell-type-specific chromatin looping. The atlas provides an essential resource for study of gene regulation and disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.