Proteomic analysis reveals platelet factor 4 and beta-thromboglobulin as prognostic markers in severe acute respiratory syndrome

Serum Proteomic Analysis for New Types of Long-Term Persistent COVID-19 Patients in Wuhan

The emergence of a new type of COVID-19 patients, who were retested positive after hospital discharge with long-term persistent SARS-CoV-2 infection but without COVID-19 clinical symptoms (hereinafter, LTPPs), poses novel challenges to COVID-19 treatment and prevention. Why was there such a contradictory phenomenon in LTPPs? To explore the mechanism underlying this phenomenon, we performed quantitative proteomic analyses using the sera of 12 LTPPs (Wuhan Pulmonary Hospital), with the longest carrying history of 132 days, and mainly focused on 7 LTPPs without hypertension (LTPPs-NH). The results showed differential serum protein profiles between LTPPs/LTPPs-NH and health controls. Further analysis identified 174 differentially-expressed-proteins (DEPs) for LTPPs, and 165 DEPs for LTPPs-NH, most of which were shared. GO and KEGG analyses for these DEPs revealed significant enrichment of "coagulation" and "immune response" in both LTPPs and LTPPs-NH. A unity of contradictory genotypes in the 2 aspects were then observed: some DEPs showed the same dysregulated expressed trend as that previously reported for patients in the acute phase of COVID-19, which might be caused by long-term stimulation of persistent SARS-CoV-2 infection in LTPPs, further preventing them from complete elimination; in contrast, some DEPs showed the opposite expression trend in expression, so as to retain control of COVID-19 clinical symptoms in LTPPs. Overall, the contrary effects of these DEPs worked together to maintain the balance of LTPPs, further endowing their contradictory steady-state with long-term persistent SARS-CoV-2 infection but without symptoms. Additionally, our study revealed some potential therapeutic targets of COVID-19. Further studies on these are warranted. IMPORTANCE This study reported a new type of COVID-19 patients and explored the underlying molecular mechanism by quantitative proteomic analyses. DEPs were significantly enriched in "coagulation" and "immune response". Importantly, we identified 7 "coagulation system"- and 9 "immune response"-related DEPs, the expression levels of which were consistent with those previously reported for patients in the acute phase of COVID-19, which appeared to play a role in avoiding the complete elimination of SARS-CoV-2 in LTPPs. On the contrary, 6 "coagulation system"- and 5 "immune response"-related DEPs showed the opposite trend in expression. The 11 inconsistent serum proteins seem to play a key role in the fight against long-term persistent SARS-CoV-2 infection, further retaining control of COVID-19 clinical symptom of LTPPs. The 26 proteins can serve as potential therapeutic targets and are thus valuable for the treatment of LTPPs; further studies on them are warranted.

Screening and Analysis of Serum Protein Biomarkers Infected by Coronavirus Disease 2019 (COVID-19)

Coronavirus disease 2019 (COVID-19) has spread widely around the world, and in-depth research on COVID-19 is necessary for biomarkers and target drug discovery. This analysis collected serum from six COVID-19-infected patients and six healthy people. The protein changes in the infected and healthy control serum samples were evaluated by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and high-performance liquid chromatography (HPLC). The differential protein signature in both groups was retrieved and analyzed by the Kyoto Encyclopedia of Gene and Genomes (KEGG), Gene ontology, COG/KOG, protein-protein interaction, and protein domain interactions tools. We shortlisted 24 differentially expressed proteins between both groups. Ten genes were significantly up-regulated in the infection group, and fourteen genes were significantly down-regulated. The GO and KEGG pathway enrichment analysis suggested that the chromosomal part and chromosome were the most enriched items. The oxytocin signaling pathway was the most enriched item of KEGG analysis. The netrin module (non-TIMP type) was the most enriched protein domain in this study. Functional analysis of S100A9, PIGR, C4B, IL-6R, IGLV3-19, IGLV3-1, and IGLV5-45 revealed that SARS-CoV-2 was closely related to immune response.

Platelet-Released Factors: Their Role in Viral Disease and Applications for Extracellular Vesicle (EV) Therapy

Platelets, which are small anuclear cell fragments, play important roles in thrombosis and hemostasis, but also actively release factors that can both suppress and induce viral infections. Platelet-released factors include sCD40L, microvesicles (MVs), and alpha granules that have the capacity to exert either pro-inflammatory or anti-inflammatory effects depending on the virus. These factors are prime targets for use in extracellular vesicle (EV)-based therapy due to their ability to reduce viral infections and exert anti-inflammatory effects. While there are some studies regarding platelet microvesicle-based (PMV-based) therapy, there is still much to learn about PMVs before such therapy can be used. This review provides the background necessary to understand the roles of platelet-released factors, how these factors might be useful in PMV-based therapy, and a critical discussion of current knowledge of platelets and their role in viral diseases.

Biomarkers of ageing and frailty may predict COVID-19 severity

Coronavirus Disease 2019 (COVID-19) is caused by the novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) - the culprit of an ongoing pandemic responsible for the loss of over 3 million lives worldwide within a year and a half. While the majority of SARS-CoV-2 infected people develop no or mild symptoms, some become severely ill and may die from COVID-19-related complications. In this review, we compile and comment on a number of biomarkers that have been identified and are expected to enhance the detection, protection and treatment of individuals at high risk of developing severe illnesses, as well as enable the monitoring of COVID-19 prognosis and responsiveness to therapeutic interventions. Consistent with the emerging notion that the majority of COVID-19 deaths occur in older and frail individuals, we researched the scientific literature and report the identification of a subset of COVID-19 biomarkers indicative of increased vulnerability to developing severe COVID-19 in older and frail patients. Mechanistically, increased frailty results from reduced disease tolerance, a phenomenon aggravated by ageing and comorbidities. While biomarkers of ageing and frailty may predict COVID-19 severity, biomarkers of disease tolerance may predict resistance to COVID-19 with socio-economic factors such as access to adequate health care remaining as major non-biomolecular influencers of COVID-19 outcomes.

GraphOmics: an interactive platform to explore and integrate multi-omics data

BACKGROUND

An increasing number of studies now produce multiple omics measurements that require using sophisticated computational methods for analysis. While each omics data can be examined separately, jointly integrating multiple omics data allows for deeper understanding and insights to be gained from the study. In particular, data integration can be performed horizontally, where biological entities from multiple omics measurements are mapped to common reactions and pathways. However, data integration remains a challenge due to the complexity of the data and the difficulty in interpreting analysis results.

RESULTS

Here we present GraphOmics, a user-friendly platform to explore and integrate multiple omics datasets and support hypothesis generation. Users can upload transcriptomics, proteomics and metabolomics data to GraphOmics. Relevant entities are connected based on their biochemical relationships, and mapped to reactions and pathways from Reactome. From the Data Browser in GraphOmics, mapped entities and pathways can be ranked, sorted and filtered according to their statistical significance (p values) and fold changes. Context-sensitive panels provide information on the currently selected entities, while interactive heatmaps and clustering functionalities are also available. As a case study, we demonstrated how GraphOmics was used to interactively explore multi-omics data and support hypothesis generation using two complex datasets from existing Zebrafish regeneration and Covid-19 human studies.

CONCLUSIONS

GraphOmics is fully open-sourced and freely accessible from https://graphomics.glasgowcompbio.org/ . It can be used to integrate multiple omics data horizontally by mapping entities across omics to reactions and pathways. Our demonstration showed that by using interactive explorations from GraphOmics, interesting insights and biological hypotheses could be rapidly revealed.

EVALUATION OF THE RELATIONSHIP OF MPV, RDW AND PVI PARAMETERS WITH DISEASE SEVERITY IN COVID-19 PATIENTS

Coronavirus was first detected in three severe pneumonia cases in Wuhan, China, in December 2019. Studies on red cell distribution width (RDW-CV) and mean platelet volume (MPV) laboratory parameters, which can be examined in complete blood count in COVID-19 patients, are still very limited. However, to the best of our knowledge, there are no studies examining the relationship between platelet volume index (PVI) and disease severity in COVID-19 patients, which was evaluated in this study. The aim of this study was to evaluate the relationship of disease severity in COVID-19 patients with their MPV, RDW, and PVI parameters. The study included 92 COVID-19 patients as a study group and 84 healthy individuals as control group. All laboratory data and radiological images were scanned retrospectively from patient files and hospital information system. Evaluation of the RDW-CV and MPV blood parameters, and PVI measured in COVID-19 patients yielded statistically significant differences according to the disease severity. We suggest that RDW-CV and PVI, evaluated within the scope of the study, may be the parameters that should be considered in the early diagnosis of the disease, from the initial stages of COVID-19. In addition, we think that the RDW-CV and MPV laboratory parameters, as well as PVI, which all are simple, inexpensive and widely used hematologic tests, can be used as important biomarkers in determining COVID-19 severity and mortality.

Thrombosis in COVID-19

Thrombotic complications are frequent in COVID-19 and contribute significantly to mortality and morbidity. We review several mechanisms of hypercoagulability in sepsis that may be upregulated in COVID-19. These include immune-mediated thrombotic mechanisms, complement activation, macrophage activation syndrome, antiphospholipid antibody syndrome, hyperferritinemia, and renin-angiotensin system dysregulation. We highlight biomarkers within each pathway with potential prognostic value in COVID-19. Lastly, recent observational studies have evaluated a role for the expanded use of therapeutic anticoagulation in COVID-19. We review strengths and weaknesses of these studies, and we also discuss the hypothetical benefit and anticipated challenges of fibrinolytic therapy in COVID-19.

Proteomics and Informatics for Understanding Phases and Identifying Biomarkers in COVID-19 Disease

The emergence of novel coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 coronavirus, has necessitated the urgent development of new diagnostic and therapeutic strategies. Rapid research and development, on an international scale, has already generated assays for detecting SARS-CoV-2 RNA and host immunoglobulins. However, the complexities of COVID-19 are such that fuller definitions of patient status, trajectory, sequelae, and responses to therapy are now required. There is accumulating evidence-from studies of both COVID-19 and the related disease SARS-that protein biomarkers could help to provide this definition. Proteins associated with blood coagulation (D-dimer), cell damage (lactate dehydrogenase), and the inflammatory response (e.g., C-reactive protein) have already been identified as possible predictors of COVID-19 severity or mortality. Proteomics technologies, with their ability to detect many proteins per analysis, have begun to extend these early findings. To be effective, proteomics strategies must include not only methods for comprehensive data acquisition (e.g., using mass spectrometry) but also informatics approaches via which to derive actionable information from large data sets. Here we review applications of proteomics to COVID-19 and SARS and outline how pipelines involving technologies such as artificial intelligence could be of value for research on these diseases.

Continuous thrombocytopenia after SARS-CoV-2 nucleic acid negative in a non-severe COVID-19 patient for several months

Background

Thrombocytopenia was common in the coronavirus disease (Covid-19) patients during the infection, especially in severe COVID-19 patients, but was less in the non-severe Covid-19 patients. However, the platelet count would be restored after antivirus treatment. In this paper, we report continuous thrombocytopenia in a non-severe Covid-19 case after a negative nucleic acid test for Covid-19.

Case presentation

A non-severe COVID-19 patient had the platelet continuous decrease for several months after the SARS-CoV-2 nucleic acid turning negative, and without well response to the glucocorticoid. The dynamic change of platelet count followed that of the lymphocyte count. After excluding the medicines possibility, immune system disorders, other specific virus infection and specific antibody of platelet, the thrombocytopenia continuously lasted for several months. The upward trend did not begin until June 2020 and she took the tapering dose of prednisone under the instruction of the hematologist.

Conclusion

Excluding other potentialities inducing thrombocytopenia, we highly hypothesized the SARS-CoV-2 may cause thrombocytopenia by disturbing the immune system to induce the thrombocytopenia in our report,, which needs longer time to restore the immune system and platelet count via the glucocorticoid. We firstly reported this case in order to contribute the clinician to better deal with the patients like this.

Role of Platelet Cytokines in Dengue Virus Infection

Platelets are anucleated blood cells derived from bone marrow megakaryocytes and play a crucial role in hemostasis and thrombosis. Platelets contain specialized storage organelles, called alpha-granules, contents of which are rich in cytokines such as C-X-C Motif Chemokine Ligand (CXCL) 1/4/7, (C-C motif) ligand (CCL) 5/3, CXCL8 (also called as interleukin 8, IL-8), and transforming growth factor β (TGF-β). Activation of platelets lead to degranulation and release of contents into the plasma. Platelet activation is a common event in many viral infections including human immunodeficiency virus (HIV), H1N1 influenza, Hepatitis C virus (HCV), Ebola virus (EBV), and Dengue virus (DENV). The cytokines CXCL8, CCL5 (also known as Regulated on Activation, Normal T Expressed and Secreted, RANTES), tumor necrosis factor α (TNF-α), CXCL1/5 and CCL3 released, promote development of a pro-inflammatory state along with the recruitment of other immune cells to the site of infection. Platelets also interact with Monocytes and Neutrophils and facilitate their activation to release different cytokines which further enhances inflammation. Upon activation, platelets also secrete factors such as CXCL4 (also known as platelet factor, PF4), CCL5 and fibrinopeptides which are critical regulators of replication and propagation of several viruses in the host. Studies suggest that CXCL4 can both inhibit as well as enhance HIV1 infection. Data from our lab show that CXCL4 inhibits interferon (IFN) pathway and promotes DENV replication in monocytes in vitro and in patients significantly. Inhibition of CXCL4 mediated signaling results in increased IFN production and suppressed DENV and JEV replication in monocytes. In this review, we discuss the role of platelets in viral disease progression with a focus on dengue infection.

Analysis of the Risk Factors for Mortality in Adult COVID-19 Patients in Wuhan: A Multicenter Study

Objectives: An outbreak of coronavirus disease (COVID-19) in 2019 in Wuhan, China, has spread quickly worldwide. However, the risk factors associated with COVID-19-related mortality remain controversial. Methods: A total of 245 adult patients with laboratory-confirmed COVID-19 from two centers were analyzed. Chi-square, Fisher's exact, and the Mann-Whitney U-tests were used to compare the clinical characteristics between the survivors and non-survivors. To explore the risk factors associated with in-hospital death, univariable and multivariable cox regression analyses were used. Results: Of the 245 patients included in this study, 23 (9.4%) died in the hospital. The multivariate regression analysis showed increased odds of in-hospital deaths associated with age, D-dimer levels >1,000 ng/L, platelet count <125, and higher serum creatinine levels. Conclusions: We identified risk factors that show significant association with mortality in adult COVID-19 patients, and our findings provide valuable references for clinicians to identify high-risk patients with COVID-19 at an early stage.

A novel indicator predicts 2019 novel coronavirus infection in subjects with diabetes

AIMS

Diabetes mellitus (DM) is associated with significant morbidity and mortality. The disease severity in 2019 novel coronavirus (Covid 19) infection has varied from mild self-limiting flu-like illness to fulminant pneumonia, respiratory failure and death. Since DM and Covid 19 infection are closely associated with inflammatory status, mean platelet volume (MPV) was suggested to be useful in predicting Covid infection onset. This study aimed to evaluate the diagnostic role of MPV in Covid patients with diabetes.

METHODS

A total of 640 subjects (160 Covid patients with type 2 diabetes, 160 healthy controls, 160 patients with non-spesific infections and 160 Covid patients without type 2 diabetes) enrolled in the study.

RESULTS

MPV was significantly higher (11.21 ± 0.61 fL) as compared to the results from the last routine visits of the the same individuals with diabetes (10.59 ± 0.96 fL) (p = 0.000).

CONCLUSIONS

MPV could be used as a simple and cost-effective tool to predict the Covid infection in subjects with diabetes in primary care.

Proteomic and Metabolomic Characterization of COVID-19 Patient Sera

Early detection and effective treatment of severe COVID-19 patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model was validated using 10 independent patients, 7 of which were correctly classified. Targeted proteomics and metabolomics assays were employed to further validate this molecular classifier in a second test cohort of 19 COVID-19 patients, leading to 16 correct assignments. We identified molecular changes in the sera of COVID-19 patients compared to other groups implicating dysregulation of macrophage, platelet degranulation, complement system pathways, and massive metabolic suppression. This study revealed characteristic protein and metabolite changes in the sera of severe COVID-19 patients, which might be used in selection of potential blood biomarkers for severity evaluation.

Proteomic and Metabolomic Characterization of COVID-19 Patient Sera

Early detection and effective treatment of severe COVID-19 patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model was validated using 10 independent patients, 7 of which were correctly classified. Targeted proteomics and metabolomics assays were employed to further validate this molecular classifier in a second test cohort of 19 COVID-19 patients, leading to 16 correct assignments. We identified molecular changes in the sera of COVID-19 patients compared to other groups implicating dysregulation of macrophage, platelet degranulation, complement system pathways, and massive metabolic suppression. This study revealed characteristic protein and metabolite changes in the sera of severe COVID-19 patients, which might be used in selection of potential blood biomarkers for severity evaluation.

Platelet-to-lymphocyte ratio is associated with prognosis in patients with coronavirus disease-19

Since December 2019, novel coronavirus infected pneumonia emerged in Wuhan city and rapidly spread throughout China. In severe novel coronavirus pneumonia cases, the number of platelets, their dynamic changes during the treatment, platelet-to-lymphocyte ratio (PLR) were a concern. We sought to describe the platelet feature of these cases. Single-center case series of the 30 hospitalized patients with confirmed coronavirus disease (COVID)-19 in Huizhou municipal central hospital from January 2020 to February 2020 were retrospectively analyzed. Demographic, clinical, blood routine results, other laboratory results, and treatment data were collected and analyzed. Outcomes of severe patients and nonsevere patients were compared. Univariate analysis showed that: age, platelet peaks, and PLR at peak platelet were the influencing factors in severe patients, multivariate analysis showed that the PLR value at peak platelet during treatment was an independent influencing factor in severe patients. The average hospitalization day of patients with platelet peaks during treatment was longer than those without platelet peaks (P < .05). The average age of patients with platelet peaks during treatment was older than those without platelet peaks (P < .05). The patients with significantly elevated platelets during treatment had longer average hospitalization days. And the higher PLR of patients during treatment had longer average hospitalization days. Single-center case series of the 30 hospitalized patients with confirmed COVID-19 in Huizhou Municipal Central Hospital, presumed that the number of platelets and their dynamic changes during the treatment may have a suggestion on the severity and prognosis of the disease. The patient with markedly elevated platelets and longer average hospitalization days may be related to the cytokine storm. The PLR of patients means the degree of cytokine storm, which might provide a new indicator in the monitoring in patients with COVID-19.

Hepatocellular carcinoma-derived exosomes promote motility of immortalized hepatocyte through transfer of oncogenic proteins and RNAs

Exosomes are increasingly recognized as important mediators of cell-cell communication in cancer progression through the horizontal transfer of RNAs and proteins to neighboring or distant cells. Hepatocellular carcinoma (HCC) is a highly malignant cancer, whose metastasis is largely influenced by the tumor microenvironment. The possible role of exosomes in the interactions between HCC tumor cell and its surrounding hepatic milieu are however largely unknown. In this study, we comprehensively characterized the exosomal RNA and proteome contents derived from three HCC cell lines (HKCI-C3, HKCI-8 and MHCC97L) and an immortalized hepatocyte line (MIHA) using Ion Torrent sequencing and mass spectrometry, respectively. RNA deep sequencing and proteomic analysis revealed exosomes derived from metastatic HCC cell lines carried a large number of protumorigenic RNAs and proteins, such as MET protooncogene, S100 family members and the caveolins. Of interest, we found that exosomes from motile HCC cell lines could significantly enhance the migratory and invasive abilities of non-motile MIHA cell. We further demonstrated that uptake of these shuttled molecules could trigger PI3K/AKT and MAPK signaling pathways in MIHA with increased secretion of active MMP-2 and MMP-9. Our study showed for the first time that HCC-derived exosomes could mobilize normal hepatocyte, which may have implication in facilitating the protrusive activity of HCC cells through liver parenchyma during the process of metastasis.

Circulating levels of platelet α-granule cytokines in trauma patients

OBJECTIVE AND DESIGN

To elucidate whether platelets differentiate cytokine release following trauma, we prospectively measured three major platelet-derived cytokines in 213 trauma patients on hospital arrival.

METHODS

We measured plasma levels of the anti-inflammatory β-thromboglobulins (βTGs), transforming growth factor-β1 (TGFβ1) and the pro-inflammatory platelet factor 4 (PF4) cytokines. We also measured soluble glycoprotein VI (sGPVI), procoagulant platelet microparticles (PMPs) and white blood cell (WBC) counts, and evaluated in vitro platelet function in primary and secondary haemostasis by aggregometry and thromboelastometry, respectively. We evaluated associations of each cytokine by multivariate regression including injury severity score (ISS), WBC counts, sGPVI and platelet counts as explanatory variables.

RESULTS

Severely injured patients (ISS > 15) had higher levels of βTGs and TGFβ1 (both p < 0.01) but lower levels of PF4 (p = 0.02). GPVI and PMPs levels correlated with TGFβ1 and PF4 whereas we found no significant association between cytokine levels and measures of haemostasis. By multivariate regression, a high WBC count was associated with high levels of TGFβ1 (p = 0.01) and βTGs (p < 0.01) but with low levels of PF4 (p = 0.03).

CONCLUSION

Severely injured patients had higher levels of βTGs and TGFβ1 but lower levels of the PF4; a high WBC count predicted this anti-inflammatory profile of platelet cytokines.

Serum proteomics analysis and comparisons using iTRAQ in the progression of hepatitis B

The aim of this study was to analyze the changes in serum protein levels in the progression of hepatitis B using isobaric tags for relative and absolute quantitation (iTRAQ) analysis, in addition to comparing the serum protein levels of patients with chronic hepatitis B (CHB), patients with hepatitis B virus-induced acute-on-chronic liver failure (HBV-induced ACLF) and normal individuals. Protein analysis was performed on 15 serum samples using iTRAQ. The study population included healthy controls (n=5), patients with CHB (n=5) and patients with HBV-induced ACLF (n=5). Western blotting was used to verify the results in an additional nine serum samples from healthy controls, patients with CHB and patients with HBV-induced ACLF (n=3, respectively). Using iTRAQ analysis, 16 different serum proteins with ≥1.5-fold differences in expression levels were identified in the patients with CHB and ACLF compared with the healthy controls. Five of those proteins, C-reactive protein precursor, hemoglobin β chain variant Hb S-Wake, apolipoprotein J precursor, platelet factor 4 precursor and vitronectin, which demonstrated the greatest differences in their expression levels and the most significant correlation with liver diseases, were subsequently verified using western blotting. The western blotting results were consistent with the results from the iTRAQ. Two of the five proteins are not classified by biological process, and the biological functions of all the proteins in HBV-induced ACLF remain unclear. This preliminary study demonstrated that a correlation between the expression of various serum proteins and the different pathogenetic conditions induced by HBV may exist. The analysis of a larger number of samples is required to identify potential protein biomarkers that may be involved in the pathogenesis and progression of hepatitis B.

Advances in MALDI mass spectrometry in clinical diagnostic applications

The concept of matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) was first reported in 1985. Since then, MALDI MS technologies have been evolving, and successfully used in genome, proteome, metabolome, and clinical diagnostic research. These technologies are high-throughput and sensitive. Emerging evidence has shown that they are not only useful in qualitative and quantitative analyses of proteins, but also of other types of biomolecules, such as DNA, glycans, and metabolites. Recently, parallel fragmentation monitoring (PFM), which is a method comparable to selected reaction monitoring, has been reported. This highlights the potentials of MALDI-TOF/TOF tandem MS in quantification of metabolites. Here we critically review the applications of the major MALDI MS technologies, including MALDI-TOF MS, MALDI-TOF/TOF MS, SALDI-TOF MS, MALDI-QqQ MS, and SELDI-TOF MS, to the discovery and quantification of disease biomarkers in biological specimens, especially those in plasma/serum specimens. Using SELDI-TOF MS as an example, the presence of systemic bias in biomarker discovery studies employing MALDI-TOF MS and its possible solutions are also discussed in this chapter. The concepts of MALDI, SALDI, SELDI, and PFM are complementary to each other. Theoretically, all these technologies can be combined, leading to the next generation of the MALDI MS technologies. Real applications of MALDI MS technologies in clinical diagnostics should be forthcoming.