Proteomics Research Blog

Biomarker Discovery for Predicting Dengue Deterioration: A Breakthrough Study

Authors: Jana S. Röder, Henning Boekhoff

Dengue is caused by the dengue virus (DENV), which is transmitted by multiple Aedes mosquito species. The disease has spread globally due to globalization, but infections are currently most common in tropical and subtropical regions. Endemic transmission of the dengue virus is mainly reported in the Eastern Mediterranean, the Americas, Southeast Asia, the Western Pacific, and Africa. However, transmissions have also been reported in Europe and the United States. In 2023, the World Health Organization (WHO) reported a near historic peak of dengue cases: there were over five million cases and more than 5000 dengue-related deaths. Close to 80 % of these cases, or 4.1 million, have been reported in the region of the Americas. The WHO states that the actual disease burden is likely higher, due to under-reporting of infections. It is estimated that more than half of the world’s population lives in areas affected by dengue virus. Dengue is a global threat. 


Dengue is a disease caused by dengue virus (DENV), which is transmitted by Aedes species. Dengue is a global threat. Simple and inexpensive strategies for the identification of patients with severe or life-threatening illness are urgently needed.

Phylogenetically, dengue viruses belong to the flaviviruses and are divided into four genetically related viruses, known as serotypes 1-4 (DENV-1 to DENV-4). Infection with any of these can result in dengue fever, dengue hemorrhagic fever, or even dengue shock syndrome. The disease is divided into three distinct phases: the acute phase, the critical phase, and the convalescent phase. Severe dengue may involve shock, severe bleeding, or severe organ impairment. This stage often starts once the fever receded and it is preceded by warning signs such as intense abdominal pain, persistent vomiting, bleeding gums, fluid accumulation, lethargy or restlessness, and liver enlargement. In 2009, the WHO introduced a dengue classification system that distinguishes between dengue with or without warning signs and severe dengue, with the aim of improving clinical management of patients. The warning signs are intended to identify patients with more severe or even life-threatening illness as early as possible so that they can receive supportive care. 

Currently, a full blood count is part of the recommended laboratory testing. It serves, for example, as an indicator of plasma leakage in the critical phase, resulting in a rapid decrease in platelet count and a rise in hematocrit level. Simple and inexpensive strategies to identify patients affected by dengue deterioration are urgently needed. 
There is currently no specific treatment for dengue. The severity of complications is increasing which, together with frequent epidemics and pandemics, places a significant burden on healthcare systems. Along with the potential long-term health impairments dengue patients face, this has a negative impact on the economy and society. Factors such as urbanization, water scarcity and environmental change make dengue a disease of the future. 

In a collaboration with Roche, we have successfully identified predictive protein biomarkers for dengue deterioration, bringing early intervention and cost-effective treatment of this increasingly deadly disease one step closer.
In this prospective study, blood samples were collected from 20 hospitalized dengue patients and 20 non-hospitalized patients with confirmed dengue infection in Iquitos, Peru, along with clinical data and laboratory test results. Blood samples were collected for both patient groups on the day of their first presentation.
The serum samples were analyzed using our scioDiscover protein profiling microarray platform, targeting 1,438 different proteins with 1,924 antibodies, to identify predictive biomarkers of dengue deterioration. Each antibody was represented on the microarray in four replicates. A total of 86 differentially abundant proteins were identified between hospitalized and non-hospitalized patients. This biomarker screening revealed potential key biomarkers for predicting dengue deterioration. These included CRP, ICAM-1 (intercellular adhesion molecule 1, CD54), fetuins (FETUA, FETUB), ferritin (FRIH), and thrombin, among others. The AUC values of the identified biomarker candidates ranged from 0.73 to 0.93, allowing a good prediction of the disease severity. The scioDiscover results for ferritin and ICAM-1 were validated in the same sample set using Roche’s Elecsys® immunoassays. While a good discrimination ability was confirmed for ferritin (AUC = 0.831), ICAM-1 levels showed a superior predictive value (AUC = 1.0). The results of this study were presented at the 6th Asia Dengue Summit in 2023.


Selected receiver operating characteristic (ROC) curves for classification of hospitalized and non-hospitalized dengue patients derived from the scioDiscover screen.



Selected protein levels for hospitalized, non-hospitalized and healthy donor groups derived from the antibody microarray screen.

In conclusion, this study has identified a set of predictive protein biomarkers for dengue deterioration and hospitalization by combining the Sciomics’ scioDiscover assay technology for biomarker screening with the Roche’s Elecsys® immunoassay for validation. These biomarkers are known to be involved in biological processes related to viral infection, such as inflammation (CRP, fetuins, ferritin), immune response (fetuins, A2MG, thrombin, ICAM-1) and blood coagulation (thrombin, platelet count), making their utility in predicting dengue severity functionally plausible. In the future, these biomarker candidates will be independently evaluated within a prospective, multicenter study initiated by Roche. This will allow for a head-to-head comparison of various markers and panels, parameters, multivariate analyses, and the development of a multi-parameter algorithm.

The identification of robust, minimally invasive, and readily available biomarkers for predicting dengue deterioration has the potential to address unmet medical needs, improve clinical dengue management through better patient stratification, and reduce the socio-economic impact of this disease. 


Swiatek-de Lange, M., Schroeder, C., Klein, M., Huang, J. and Strobl, M. (2023) Identification of biomarkers for prediction of dengue deterioration, presented at 6th Asia Dengue Summit (ADS 2023), 15-16 June 2023, Bangkok, Thailand


Published: 12 March 2024


From Discovery to Clinical Application: The Role of Biomarkers in Precision Medicine

Authors: Jana S. Röder, Henning Boekhoff

Biomarkers for Precision Medicine: Shaping Diagnostics and Medical Care 


Modern medicine relies on precise diagnostics and reliable patient stratification to provide the best possible patient care. However, most diseases are still defined by symptom descriptions and selecting the best treatment option can be a trial-and-error approach. This places a burden on patients and healthcare systems, as treatments are often not as effective and as adapted to the disease as they should be. This can lead to undertreatment of certain patient subpopulations and even to adverse events without treatment benefit. Precision medicine aims to change this by using molecular mechanisms for disease definition and treatment selection.  

Using molecular markers to define diseases would enable precise patient stratification and provide information about the underlying biological mechanisms. Once identified, mechanism-based treatments that target specific pathways would allow for a more tailored approach to patient care. Understanding the molecular mechanisms of both diseases and drugs could also lead to repurposing of existing drugs to provide previously unknown treatment options to new patient populations. Giving the right drug to the right patient at the right time requires novel biomarker signatures to efficiently stratify patients. At Sciomics, we specialize in biomarker discovery at the proteomic level to enable precision medicine. We have identified molecular biomarkers in a wide range of diseases, including cancer, neurological disorders, organ failure, inflammatory diseases, and infections.


Efficient Profiling, Deep Insights: scioDiscover Biomarker Discovery

New protein biomarker signatures can be derived from various sample sources such as blood, urine, vesicles, cerebrospinal fluid, and isolated cells. The identification and validation of potential biomarker candidates can be accelerated by using high-throughput antibody microarray analysis, such as the scioDiscover platform for affinity-based proteomics.  The scioDiscover biomarker discovery platform combines antibody-based profiling with high-throughput analysis and very low sample consumption. For instance, only 5 µL of plasma or serum is sufficient to obtain highly reproducible results. The abundance of more than 1,400 proteins is profiled in a single assay, covering key pathways of disease development, including cancer pathways, apoptosis pathways, the NFkB pathway, and many cytokines and their receptors. The antibody-based protein recognition reduces attrition rates and allows a rapid translation of results to other immune-based platforms - such as ELISA, CLIA, and LFDs - for further validation and diagnostic use.


Sciomics’ Biomarker Pipeline – from Discovery to Clinical Application

At Sciomics, we are using our scioDiscover platform to identify biomarker panels for the prediction of severe COVID-19 disease and for the early diagnosis of acute kidney injury (AKI). 

We have discovered and systematically evaluated plasma protein biomarkers that can predict severe COVID-19 disease during the early phase of  SARS-CoV-2 infection. After scioDiscover analysis, biomarker candidates were ranked and marker panels were selected using machine learning. Protein concentration measurements by ELISA were comparable to the results of the discovery study. Validated markers such as S100A8/A9 and CRP showed very good correlations between scioDiscover data and clinically available assays or ELISA, demonstrating the platform's seamless translation of results to other platforms. Early stratification of patients at high risk of developing severe or even critical disease could support treatment and care decisions, ultimately improving medical interventions and reducing the burden on healthcare systems. The scioDiscover workflow allows us to identify potential biomarker panels in a very short time. It took less than eight weeks from the start of wet-lab research on predictive COVID-19 biomarkers to patent filing.SARS-CoV-2_virus_COVID19.jpg

In another project, we aim to develop a biomarker-based early diagnostic test for acute kidney injury (AKI). AKI is a sudden loss of kidney function that often occurs as a complication of other serious medical conditions. It leads to structural kidney damage, impaired filtration and potentially serious consequences, including the need for long-term dialysis and increased mortality. Early detection and intervention of AKI is critical for patients: It can reduce the extent of kidney damage and increase the chance of reversible AKI. In addition, the financial burden on healthcare systems due to prolonged intensive care unit (ICU) stays and dialysis treatments is significant. An accurate early diagnostic or even predictive test for AKI would allow early intervention and better treatment regimens, preventing long-term kidney damage, lifelong treatment and death. Our scioAKI project has identified promising early diagnostic biomarker combinations for perioperative AKI and will be extended to other patient groups. Our ultimate goal is to develop a reliable and cost-effective test for the early diagnosis of AKI in a clinical setting.


Precision Medicine in the Clinic: Molecular Markers Shaping Future Treatments

Medical specimens are a limited and valuable resource. It can take years or even decades to collect enough samples for a study. It is therefore critical to make the most of them by using the most efficient methods for data generation. A single antibody microarray-based discovery study provides novel putative biomarkers, insights into the underlying disease mechanisms, and information about the patient population, enabling in-depth cohort characterization. In this way, the scioDiscover accelerates research and knowledge generation, ultimately advancing precision medicine. The combination of a better understanding of disease mechanisms and of pharmacological mechanisms of action enables the development of new treatment regimens and personalized patient care. Matching more suitable treatments to new patient populations could be further accelerated through drug repurposing. It has enormous potential to streamline drug development by making already existing drugs available to additional patient populations that may respond to the treatment. For example, clinical trials of repurposed drugs could be simplified because toxicology and mode of action analyses have previously been performed. In addition, precise patient stratification using molecular markers can improve the success rate of clinical trials, reduce drug development costs, and ultimately ensure that the patients receive the right treatment at the right time. Scientists and regulators around the world are collaborating to make these approaches a reality, for example in the EU-funded project REPO4EU. We are pleased to have been part of this consortium from the beginning. Maximizing the efficiency of medical research by using comprehensive data is the way forward to precision medicine and more efficient healthcare. 



Published: 18 January 2024


New Sciomics Proteomics Research Blog!

Sciomics Protomics Research Blog


At Sciomics, we are dedicated to advancing healthcare through proteomics research. We are collaborating with research groups and big pharma, alongside our in-house biomarker research initiatives. To make this research more accessible to you, we are launching the new Sciomics science blog!

The first study we will feature was published this year in a journal in the Nature publishing group. It's a topic that affects us all. Any guesses? Stay tuned!



Discovery: Early Biomarkers Predict Severe COVID-19

Authors: Henning Boekhoff, Jana S. Röder

Discovery of predictive COVID-19 Biomarkers using scioDiscoverThe SARS-CoV-2 pandemic posed significant challenges worldwide and raised critical questions in the scientific community. While some individuals experienced mild or asymptomatic infections, others faced severe or critical disease progression with a high mortality rate, peaking in 30 % mortality of patients aged 85 or older. The need for rapid biomarker discovery for early prediction of COVID-19 progression became evident from the outset of the pandemic.

At Sciomics, we continuously develop and optimize specific antibody microarray platforms for in-house protein and post-translational modification profiling, establishing ourselves as a world leader in microarray-based biomarker discovery. In a recent study published in Nature Communications Medicine, we leveraged our expertise to identify early predictive biomarkers for COVID-19.

In the study, we analyzed 351 proteins in 53 human plasma samples at different infection stages. We identified proteins with varying abundances in patients with severe/critical and mild/moderate disease. Building on this, we analyzed 998 proteins in a larger cohort of 94 patients, leading to the selection of eleven promising biomarkers capable of predicting severe COVID-19.

We successfully established multiple biomarker panels, offering the potential to predict disease progression early and reliably stratify patients in clinical settings. The most promising biomarker panel identified consists of three proteins: S100A8/A9, TSP1, and ERBB2. We are actively working on validating these panels in COVID-19, Long Covid and other viral diseases of the respiratory system.

Early patient stratification for those at high risk of developing severe or critical disease could significantly improve treatment decisions, ultimately easing the burden on healthcare systems and leading to an improved pandemic preparedness. This biomarker signature showcases the use of biomarkers to predict disease progression and gain insights into disease mechanisms simultaneously.

Providing a bigger picture, unbiased or semi-targeted monitoring of the systemic response to a disease can shed light on diverse patient outcomes without prior knowledge of underlying mechanisms. Through antibody microarrays, thousands of proteins in various blood components can be examined simultaneously in a minimally invasive, low-volume, rapid, and less biased manner.

For more in-depth information on this biomarker discovery study for COVID-19, you can access the publication here.


Hufnagel, K., Fathi, A., Stroh, N., Klein, M., Skwirblies, F., Girgis, R., Dahlke, C., Hoheisel, J. D., Lowy, C., Schmidt, R., Griesbeck, A., Merle, U., Addo, M. M., & Schröder, C. 2023. Discovery and systematic assessment of early biomarkers that predict progression to severe COVID-19 disease. Communications medicine, 3(1), 51. DOI: 10.1038/s43856-023-00283-z

Published: 28 Nov 2023