Searching for biomarkers: humoral response profiling with luciferase immunoprecipitation systems

B-cell-mediated humoral responses are triggered in many human diseases, including autoimmune diseases, cancer, and neurologic and infectious diseases. However, the full exploitation of the information contained within a patient’s antibody repertoire for diagnosis, monitoring and even disease prediction has been limited due to the poor diagnostic performance of many immunoassay formats. We have developed luciferase immunoprecipitation systems (LIPS) that harnesses light-emitting proteins to generate high-definition antibody profiles that are optimal for both diagnostics and biomarker discovery. Here, we describe the results and implications from a range of LIPS-antibody profiling studies performed in our laboratory. These include highly sensitive diagnostics for domestic and global pathogens, insights into infection-related diseases, discovery of new biomarkers for human diseases, subcategorization of symptoms and identification of pathogenic autoantibodies against self-proteins. These investigations highlight the types of humoral response profiles associated with different diseases, provide new information related to disease pathogenesis and offer a framework for incorporating LIPS antibody profiling into global health initiatives and disease monitoring.     

Antibody Profiling by Luciferase Immunoprecipitation Systems (LIPS)

Technologies for comprehensively understanding and quantifying antibody profiles to autoantigens and infectious agents may yield new insights into disease mechanisms and may elucidate new markers to substratify disease with different clinical features and better understand pathogenesis. We have developed a highly quantitative method called Luciferase Immunoprecipitation Systems (LIPS) for profiling patient sera antibody responses to autoantigens and pathogen antigens associated with infection. Unlike ELISAs, the highly sensitive LIPS is easily implemented to survey humoral serological response profiles to different antigens in a universal format and produces dynamic antibody titer ranges up to 6 log₁₀ for some antigens. In these studies, quantitative profiling by LIPS of patient humoral responses against panels of antigens or even the entire proteome of some pathogens (i.e. HIV), is typically more informative than testing a single antigen by ELISA. In addition, LIPS also eliminates time and effort needed to produce highly purified antigens as well as the labor-intensive assay optimization steps needed for standard ELISAs. Here we provide a detailed protocol describing the technical aspects of performing LIPS assays for readily profiling antibody responses to single or multiple antigens.Download video file.^{(144M, mp4)}     

LIPS arrays for simultaneous detection of antibodies against partial and whole proteomes of HCV, HIV and EBV

For many infectious agents, the detection of antibodies is critical for diagnosing, monitoring and understanding vaccine responses. To facilitate the highly quantitative and simultaneous analysis of antibodies against multiple proteins from infectious agents, we have developed Luciferase Immunoprecipitation Systems (LIPS) arrays. By configuring microtiter plates with multiple antigens and testing control and infected serum samples at one time in solution, LIPS arrays provided highly reproducible antibody titers to panels of antigens with a wide dynamic range of detection. While all serum samples showed similar positive and negative immunoreactivity with internal control antigens derived from Influenza and Renilla luciferase-alone protein, respectively, antibody titers to many HCV and HIV antigens were generally 10 to over 400-fold higher in the infected versus uninfected samples. Additional screening of 18 proteins from the EBV proteome with serum samples from healthy EBV-infected individuals showed statistically significant antibody titers to 50% of the proteins tested. Antibody titers for the different EBV antigens in the healthy EBV-infected individuals were markedly heterogeneous highlighting the complexity of host humoral responses. These results suggest that LIPS arrays offer a highly discriminating platform for simultaneously profiling a wide spectrum of antibodies associated with many infectious agents.     

Protein profiling in respiratory disease: techniques and impact

Multifactorial diseases such as respiratory disease call for a global analysis of such disorders. Recent advances in protein profiling techniques may allow for early diagnosis of respiratory disease, which is crucial for intervention and treatment. In order to reduce false-positive rates, clinical diagnosis requires a high degree of sensitivity and specificity to be an effective screening tool. Protein profiles identified by ProteinChip^® (Ciphergen Biosystems) technology coupled with mass spectrometry affords a global analysis of clinical samples and is beginning to reach acceptable levels of sensitivity and specificity. Combining the profile with another diagnostic tool enhances the effectiveness of protein profiles to classify disease. Although current efforts have centered on serum protein profiling, the local environment of the lung may be better reflected in proteins of bronchoalveolar lavage or sputum. Identification of biomarkers of disease by protein profiling anaylses may lead to an understanding of the mechanisms of this disease and contribute to the discovery of new therapeutics for the prevention and treatment of disease. Advancing these analyses are techniques such as ProteinChip mass spectrometry, laser capture microdissection, tissue microarrays and fluorescently labeled antibody bead arrays, which enable the direct global analysis of complex mixtures. Effective high-throughput and ease of use of clinical testing will arrive with improvements in bioinformatics and decreases in instrumentation costs.     

Protein profiling in respiratory disease: techniques and impact

Multifactorial diseases such as respiratory disease call for a global analysis of such disorders. Recent advances in protein profiling techniques may allow for early diagnosis of respiratory disease, which is crucial for intervention and treatment. In order to reduce false-positive rates, clinical diagnosis requires a high degree of sensitivity and specificity to be an effective screening tool. Protein profiles identified by ProteinChip (Ciphergen Biosystems) technology coupled with mass spectrometry affords a global analysis of clinical samples and is beginning to reach acceptable levels of sensitivity and specificity. Combining the profile with another diagnostic tool enhances the effectiveness of protein profiles to classify disease. Although current efforts have centered on serum protein profiling, the local environment of the lung may be better reflected in proteins of bronchoalveolar lavage or sputum. Identification of biomarkers of disease by protein profiling analyses may lead to an understanding of the mechanisms of this disease and contribute to the discovery of new therapeutics for the prevention and treatment of disease. Advancing these analyses are techniques such as ProteinChip mass spectrometry, laser capture microdissection, tissue microarrays and fluorescently labeled antibody bead arrays, which enable the direct global analysis of complex mixtures. Effective high-throughput and ease of use of clinical testing will arrive with improvements in bioinformatics and decreases in instrumentation costs.     

Biomedical applications of protein chips

The development of microchips involving proteins has accelerated within the past few years. Although DNA chip technologies formed the precedent, many different strategies and technologies have been used because proteins are inherently a more complex type of molecule. This review covers the various biomedical applications of protein chips in diagnostics, drug screening and testing, disease monitoring, drug discovery (proteomics), and medical research. The proteomics and drug discovery section is further subdivided to cover drug discovery tools (on-chip separations, expression profiling, and antibody arrays), molecular interactions and signaling pathways, the identification of protein function, and the identification of novel therapeutic compounds. Although largely focused on protein chips, this review includes chips involving cells and tissues as a logical extension of the type of data that can be generated from these microchips.     

Genetic regulation of immunoglobulin E level in different pathological states: integration of mouse and human genetics

Immunoglobulin E (IgE) first evolved in mammals. It plays an important role in defence against helminths and parasitic infection and in pathological states including allergic reactions, anti‐tumour defence and autoimmune diseases. Elucidation of genetic control of IgE level could help us to understand regulation of the humoral immune response in health and disease, the etiology and pathogenesis of many human diseases, and to facilitate discovery of more effective methods for their prevention and cure. Herein we summarise progress in the genetics of regulation of IgE level in human diseases and show that integration of different approaches and use of animal models have synergistic effects in gaining new knowledge about both protective and pathological roles of this important antibody.     

Antibody microarrays: current status and key technological advances

Antibody-based microarrays are among the novel classes of rapidly evolving proteomic technologies that holds great promise in biomedicine. Miniaturized microarrays (< 1 cm2) can be printed with thousands of individual antibodies carrying the desired specificities, and with biological sample (e.g., an entire proteome) added, virtually any specifically bound analytes can be detected. While consuming only minute amounts (< microL scale) of reagents, ultra- sensitive assays (zeptomol range) can readily be performed in a highly multiplexed manner. The microarray patterns generated can then be transformed into proteomic maps, or detailed molecular fingerprints, revealing the composition of the proteome. Thus, protein expression profiling and global proteome analysis using this tool will offer new opportunities for drug target and biomarker discovery, disease diagnostics, and insights into disease biology. Adopting the antibody microarray technology platform, several biomedical applications, ranging from focused assays to proteome-scale analysis will be rapidly emerging in the coming years. This review will discuss the current status of the antibody microarray technology focusing on recent technological advances and key issues in the process of evolving the methodology into a high-performing proteomic research tool.     

Design of high-density antibody microarrays for disease proteomics: Key technological issues

Antibody-based microarray is a novel proteomic technology setting a new standard for molecular profiling of non-fractionated complex proteomes. The first generation of antibody microarrays has already demonstrated its potential for generating detailed protein expression profiles, or protein atlases, of human body fluids in health and disease, paving the way for new discoveries within the field of disease proteomics. The process of designing highly miniaturized, high-density and high-performing antibody microarray set-ups have, however, proven to be challenging. In this mini-review we discuss key technological issues that must be addressed in a cross-disciplinary manner before true global proteome analysis can be performed using antibody microarrays.     

Biomarker discovery using protein microarray technology platforms: antibody-antigen complex profiling

Protein microarrays represent an important new tool in proteomic systems biology. This review focuses on the contributions of protein microarrays to the discovery of novel disease biomarkers through antibody-based assays. Of particular interest is the use of protein microarrays for immune response profiling, through which a disease-specific antibody repertoire may be defined. The antigens and antibodies revealed by these studies are useful for clinical assay development, with enormous potential to aid in diagnosis, prognosis, disease staging and treatment selection. The discovery and characterization of novel biomarkers specifically tailored to disease type and stage are expected to enable personalized medicine by facilitating preventative medicine, predictive diagnostics and individualized curative therapies.     

Biomarker discovery using protein microarray technology platforms: antibody-antigen complex profiling

Protein microarrays represent an important new tool in proteomic systems biology. This review focuses on the contributions of protein microarrays to the discovery of novel disease biomarkers through antibody-based assays. Of particular interest is the use of protein microarrays for immune response profiling, through which a disease-specific antibody repertoire may be defined. The antigens and antibodies revealed by these studies are useful for clinical assay development, with enormous potential to aid in diagnosis, prognosis, disease staging and treatment selection. The discovery and characterization of novel biomarkers specifically tailored to disease type and stage are expected to enable personalized medicine by facilitating preventative medicine, predictive diagnostics and individualized curative therapies.     

Clinical diagnostics and therapy monitoring in the congenital disorders of glycosylation

Abnormal protein glycosylation is observed in many common disorders like cancer, inflammation, Alzheimer’s disease and diabetes. However, the actual use of this information in clinical diagnostics is still very limited. Information is usually derived from analysis of total serum N-glycan profiling methods, whereas the current use of glycoprotein biomarkers in the clinical setting is commonly based on protein levels. It can be envisioned that combining protein levels and their glycan isoforms would increase specificity for early diagnosis and therapy monitoring. To establish diagnostic assays, based on the mass spectrometric analysis of protein-specific glycosylation abnormalities, still many technical improvements have to be made. In addition, clinical validation is equally important as well as an understanding of the genetic and environmental factors that determine the protein-specific glycosylation abnormalities. Important lessons can be learned from the group of monogenic disorders in the glycosylation pathway, the Congenital Disorders of Glycosylation (CDG). Now that more and more genetic defects are being unraveled, we start to learn how genetic factors influence glycomics profiles of individual and total serum proteins. Although only in its initial stages, such studies suggest the importance to establish diagnostic assays for protein-specific glycosylation profiling, and the need to look beyond the single glycoprotein diagnostic test. Here, we review progress in and lessons from genetic disease, and review the increasing opportunities of mass spectrometry to analyze protein glycosylation in the clinical diagnostic setting. Furthermore, we will discuss the possibilities to expand current CDG diagnostics and how this can be used to approach glycoprotein biomarkers for more common diseases.     

Integrated analysis of numerous heterogeneous gene expression profiles for detecting robust disease-specific biomarkers and proposing drug targets

Genome-wide expression profiling has revolutionized biomedical research; vast amounts of expression data from numerous studies of many diseases are now available. Making the best use of this resource in order to better understand disease processes and treatment remains an open challenge. In particular, disease biomarkers detected in case–control studies suffer from low reliability and are only weakly reproducible. Here, we present a systematic integrative analysis methodology to overcome these shortcomings. We assembled and manually curated more than 14 000 expression profiles spanning 48 diseases and 18 expression platforms. We show that when studying a particular disease, judicious utilization of profiles from other diseases and information on disease hierarchy improves classification quality, avoids overoptimistic evaluation of that quality, and enhances disease-specific biomarker discovery. This approach yielded specific biomarkers for 24 of the analyzed diseases. We demonstrate how to combine these biomarkers with large-scale interaction, mutation and drug target data, forming a highly valuable disease summary that suggests novel directions in disease understanding and drug repurposing. Our analysis also estimates the number of samples required to reach a desired level of biomarker stability. This methodology can greatly improve the exploitation of the mountain of expression profiles for better disease analysis.     

Two-dimensional immune profiles improve antigen microarray-based characterization of humoral immunity

Antigen arrays are becoming widely used tools for the characterization of the complexity of humoral immune responses. Current antibody profiling techniques provide modest and indirect information about the effector functions of the antibodies that bind to particular antigens. Here we introduce an antigen array-based approach for obtaining immune profiles reflecting antibody functionality. This technology relies on the parallel measurement of antibody binding and complement activation by features of the array. By comparing sera from animals immunized against the same antigen under different conditions, we show that identifying the position of an antigen in a 2-D space, derived from antibody binding and complement deposition, permits distinction between immune profiles characterized by diverse antibody isotype distributions. Additionally, the technology provides a biologically interpretable graphical representation of the relationship between antigen and host. Our data suggest that 2-D immune profiling could enrich the data obtained from proteomic scale serum profiling studies.     

Urine metabolomics analysis for biomarker discovery and detection of jaundice syndrome in patients with liver disease

Metabolomics is a powerful new technology that allows for the assessment of global metabolic profiles in easily accessible biofluids and biomarker discovery in order to distinguish between diseased and nondiseased status information. Deciphering the molecular networks that distinguish diseases may lead to the identification of critical biomarkers for disease aggressiveness. However, current diagnostic methods cannot predict typical Jaundice syndrome (JS) in patients with liver disease and little is known about the global metabolomic alterations that characterize JS progression. Emerging metabolomics provides a powerful platform for discovering novel biomarkers and biochemical pathways to improve diagnostic, prognostication, and therapy. Therefore, the aim of this study is to find the potential biomarkers from JS disease by using a nontarget metabolomics method, and test their usefulness in human JS diagnosis. Multivariate data analysis methods were utilized to identify the potential biomarkers. Interestingly, 44 marker metabolites contributing to the complete separation of JS from matched healthy controls were identified. Metabolic pathways (Impact-value≥0.10) including alanine, aspartate, and glutamate metabolism and synthesis and degradation of ketone bodies were found to be disturbed in JS patients. This study demonstrates the possibilities of metabolomics as a diagnostic tool in diseases and provides new insight into pathophysiologic mechanisms.     

Serological studies confirm the novel astrovirus HMOAstV-C as a highly prevalent human infectious agent

Molecular identification of a microbe is the first step in determining its prevalence of infection and pathogenic potential. Detection of specific adaptive immune responses can provide insights into whether a microbe is a human infectious agent and its epidemiology. Here we characterized human anti-IgG antibody responses by luciferase immunoprecipitation systems (LIPS) against two protein fragments derived from the capsid protein of the novel HMOAstV-C astrovirus. While antibodies to the N-terminal fragment were not informative, the C-terminal capsid fragment of HMOAstV-C showed a high frequency of immunoreactivity with serum from healthy blood donors. In contrast, a similar C-terminal capsid fragment from the related HMOAstV-A astrovirus failed to show immunoreactivity. Detailed analysis of adult serum from the United Sates using a standardized threshold demonstrated HMOAstV-C seropositivity in approximately 65% of the samples. Evaluation of serum samples from different pediatric age groups revealed that the prevalence of antibodies in 6-12 month, 1-2 year, 2-5 year and 5-10 year olds was 20%, 23%, 32% and 36%, respectively, indicating rising seroprevalence with age. Additionally, 50% (11/22) of the 0-6 month old children showed anti-HMOAstV-C antibody responses, likely reflecting maternal antibodies. Together these results document human humoral responses to HMOAstV-C and validate LIPS as a facile and effective approach for identifying humoral responses to novel infectious agents.     

Clinical proteomics: present and future prospects

Advances in proteomics technology offer great promise in the understanding and treatment of the molecular basis of disease. The past decade of proteomics research, the study of dynamic protein expression, post-translational modifications, cellular and sub-cellular protein distribution, and protein-protein interactions, has culminated in the identification of many disease-related biomarkers and potential new drug targets. While proteomics remains the tool of choice for discovery research, new innovations in proteomic technology now offer the potential for proteomic profiling to become standard practice in the clinical laboratory. Indeed, protein profiles can serve as powerful diagnostic markers, and can predict treatment outcome in many diseases, in particular cancer. A number of technical obstacles remain before routine proteomic analysis can be achieved in the clinic; however the standardisation of methodologies and dissemination of proteomic data into publicly available databases is starting to overcome these hurdles. At present the most promising application for proteomics is in the screening of specific subsets of protein biomarkers for certain diseases, rather than large scale full protein profiling. Armed with these technologies the impending era of individualised patient-tailored therapy is imminent. This review summarises the advances in proteomics that has propelled us to this exciting age of clinical proteomics, and highlights the future work that is required for this to become a reality.     

Sex differences in disease risk from reported genome-wide association study findings

Men and women differ in susceptibility to many diseases and in responses to treatment. Recent advances in genome-wide association studies (GWAS) provide a wealth of data for associating genetic profiles with disease risk; however, in general, these data have not been systematically probed for sex differences in gene-disease associations. Incorporating sex into the analysis of GWAS results can elucidate new relationships between single nucleotide polymorphisms (SNPs) and human disease. In this study, we performed a sex-differentiated analysis on significant SNPs from GWAS data of the seven common diseases studied by the Wellcome Trust Case Control Consortium. We employed and compared three methods: logistic regression, Woolf’s test of heterogeneity, and a novel statistical metric that we developed called permutation method to assess sex effects (PMASE). After correction for false discovery, PMASE finds SNPs that are significantly associated with disease in only one sex. These sexually dimorphic SNP-disease associations occur in Coronary Artery Disease and Crohn’s Disease. GWAS analyses that fail to consider sex-specific effects may miss discovering sexual dimorphism in SNP-disease associations that give new insights into differences in disease mechanism between men and women.     

Antibody arrays--an emerging tool in cancer proteomics

Cancer is a result of complex changes that occur in normal cells as they transform to become malignant and further when they become metastatic. These changes are not a consequence of a single protein but rather involve multiple proteins that function in pathways and networks. Thus, profiling cancer-associated changes requires simultaneous measurement of many proteins in a single sample. Identifying these changes may lead to the discovery of cancer-associated biomarkers that may assist in diagnosis, prognosis, patient monitoring and possibly for therapeutic purposes. Antibody arrays are a relatively new technology that enables one to perform multiplex high-throughput protein expression profiling. This review describes current technologies in antibody array and assay design, and presents a survey of the current literature on the use of these arrays in cancer research.