Clinical Phenome Research Articles

Phenome-wide association study and precision medicine of cardiovascular diseases in the post-COVID-19 era.

SARS-CoV-2 infection causes injuries of not only the lungs but also the heart and endothelial cells in vasculature of multiple organs, and induces systemic inflammation and immune over-reactions, which makes COVID-19 a disease phenome that simultaneously affects multiple systems. Cardiovascular diseases (CVD) are intrinsic risk and causative factors for severe COVID-19 comorbidities and death. The wide-spread infection and reinfection of SARS-CoV-2 variants and the long-COVID may become a new common threat to human health and propose unprecedented impact on the risk factors, pathophysiology, and pharmacology of many diseases including CVD for a long time. COVID-19 has highlighted the urgent demand for precision medicine which needs new knowledge network to innovate disease taxonomy for more precise diagnosis, therapy, and prevention of disease. A deeper understanding of CVD in the setting of COVID-19 phenome requires a paradigm shift from the current phenotypic study that focuses on the virus or individual symptoms to phenomics of COVID-19 that addresses the inter-connectedness of clinical phenotypes, i.e., clinical phenome. Here, we summarize the CVD manifestations in the full clinical spectrum of COVID-19, and the phenome-wide association study of CVD interrelated to COVID-19. We discuss the underlying biology for CVD in the COVID-19 phenome and the concept of precision medicine with new phenomic taxonomy that addresses the overall pathophysiological responses of the body to the SARS-CoV-2 infection. We also briefly discuss the unique taxonomy of disease as Zheng-hou patterns in traditional Chinese medicine, and their potential implications in precision medicine of CVD in the post-COVID-19 era.

Novel lipidomes profile and clinical phenotype identified in pneumoconiosis patients

BackgroundPneumoconiosis is a group of occupational lung diseases caused by the inhalation of mineral dust in the lungs, leading to lung dysfunction. Patients with pneumoconiosis are usually accompanied by weight loss, which suggests a lipid metabolism disorder. Recent progress in lipidomics uncovered detailed lipid profiles that play important roles in respiratory diseases, such as asthma, lung cancer and lung injury. The purpose of this study was to shed light on the different expression of lipidome between pneumoconiosis and healthy, hoping to bring new ideas for the diagnosis and treatment of pneumoconiosis.MethodologyThis non-matching case–control study was performed among 96 subjects (48 outpatients with male pneumoconiosis and 48 healthy volunteers), data of clinical phenotypes were recorded, and plasma biochemistry (lipidomic profiles) was tested for both pneumoconiosis patients and healthy controls. A total of 426 species in 11 lipid classes were analyzed by high-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (HPLC-QqQ-MS) for the cases and controls. We also analyzed the correlation of lipid profiles with clinical phenomes from pneumoconiosis patients by expression quantitative trait locus (eQTL) model to evaluate trans-nodules between lipidomic profiles and clinical phenomes. All visually re-checked data were analyzed using appropriate statistical tools (t-test or one-way ANOVA test) on SPSS.ResultsCompared with healthy people, 26 significantly increased (> 1.5-fold) and 30 decreased lipid elements (< 2/threefold) in patients with pneumoconiosis were identified (P values all < 0.05). The majority of those elevated lipid elements were phosphatidylethanolamines (PEs), and the minority were free fatty acids (FFAs), while phosphatidylcholines (PCs) and lysophosphatidylcholines (lysoPCs) declined in pneumoconiosis. Clinical trans-omics analyses demonstrated that phenomes in pneumoconiosis connections with multiple lipids, which showed that pH, lung function, mediastinal lymph node calcification, and complication were highly correlated with lipid elements. Furthermore, up-regulated PE was corresponded to pH, smoking history and mediastinal lymph node calcification. PC was corresponded to dust exposure history, BMI and mediastinal lymph node calcification.ConclusionWe found altered lipid panels between male pneumoconiosis patients and healthy people by qualitatively and quantitatively measured plasma lipidomic profiles. The trans-omic analysis between clinical phenomes and lipidomes might have the potential to uncover the heterogeneity of lipid metabolism of pneumoconiosis patients and to screen out clinically significant phenome-based lipid panels.

Multi-omics blood atlas reveals unique features of immune and platelet responses to SARS-CoV-2 Omicron breakthrough infection

Although host responses to the ancestral SARS-CoV-2 strain are well described, those to the new Omicron variants are less resolved. We profiled the clinical phenomes, transcriptomes, proteomes, metabolomes, and immune repertoires of >1,000 blood cell or plasma specimens from SARS-CoV-2 Omicron patients. Using in-depth integrated multi-omics, we dissected the host response dynamics during multiple disease phases to reveal the molecular and cellular landscapes in the blood. Specifically, we detected enhanced interferon-mediated antiviral signatures of platelets in Omicron-infected patients, and platelets preferentially formed widespread aggregates with leukocytes to modulate immune cell functions. In addition, patients who were re-tested positive for viral RNA showed marked reductions in B cell receptor clones, antibody generation, and neutralizing capacity against Omicron. Finally, we developed a machine learning model that accurately predicted the probability of re-positivity in Omicron patients. Our study may inspire a paradigm shift in studying systemic diseases and emerging public health concerns.

Untargeted metabolomics reveals gender- and age- independent metabolic changes of type 1 diabetes in Chinese children.

Type 1 diabetes (T1D) is a chronic condition associated with multiple complications that substantially affect both the quality of life and the life-span of children. Untargeted Metabolomics has provided new insights into disease pathogenesis and risk assessment. In this study, we characterized the serum metabolic profiles of 76 children with T1D and 65 gender- and age- matched healthy controls using gas chromatography coupled with timeof-flight mass spectrometry. In parallel, we comprehensively evaluated the clinical phenome of T1D patients, including routine blood and urine tests, and concentrations of cytokines, hormones, proteins, and trace elements. A total of 70 differential metabolites covering 11 metabolic pathways associated with T1D were identified, which were mainly carbohydrates, indoles, unsaturated fatty acids, amino acids, and organic acids. Subgroup analysis revealed that the metabolic changes were consistent among pediatric patients at different ages or gender but were closely associated with the duration of the disease. Carbohydrate metabolism, unsaturated fatty acid biosynthesis, and gut microbial metabolism were identified as distinct metabolic features of pediatric T1D. These metabolic changes were also associated with T1D, which may provide important insights into the pathogenesis of the complications associated with diabetes.

Gradually shifting clinical phenomics in migraine spectrum: a cross-sectional, multicenter study of 5438 patients

BackgroundThe aim of the study was to investigate whether MwoA and MwA are different manifestations of a single disease, distinct clinical entities, or located at two poles of a spectrum.MethodsIn this cross-sectional study, 5438 patients from 10 hospitals in China were included: 4651 were diagnosed with migraine without aura (MwoA) and 787 with migraine with aura (MwA). We used a validated standardized electronic survey to collect multidimensional data on headache characteristics and evaluated the similarities and differences between migraine subtypes. To distinguish migraine subtypes, we employed correlational analysis, factor analysis of mixed data (FAMD), and decision tree analysis.ResultsCompared to MwA, MwoA had more severe headaches, predominantly affected females, were more easily produced by external factors, and were more likely to have accompanying symptoms and premonitory neck stiffness. Patients with MwA are heterogeneous, according to correlation analysis; FAMD divided the subjects into three clear clusters. The majority of the differences between MwoA and MwA were likewise seen when typical aura with migraine headache (AWM) and typical aura with non-migraine headache (AWNM) were compared. Furthermore, decision trees analysis revealed that the chaotic MwA data reduced the decision tree’s accuracy in distinguishing MwoA from MwA, which was significantly increased by splitting MwA into AWM and AWNM.ConclusionsThe clinical phenomics of headache phenotype varies gradually from MwoA to AWM and AWNM, and AWM is a mid-state between MwoA and AWNM. We tend to regard migraine as a spectrum disorder, and speculate that different migraine subtypes have different “predominant regions” that generate attacks.

Integration Profiling Between Plasma Lipidomics, Epstein-Barr Virus and Clinical Phenomes in Nasopharyngeal Carcinoma Patients.

Plasma lipidomics has been commonly used for biomarker discovery. Studies in cancer have suggested a significant alteration of circulating metabolite profiles which is correlated with cancer characteristics and treatment outcome. However, the lipidomics characteristics of nasopharyngeal carcinoma (NPC) have rarely been studied. We previously described the phenomenon of lipid droplet accumulation in NPC cells and showed that such accumulation could be regulated by latent infection of Epstein–Barr virus (EBV). Here, we compared the plasma lipidome of NPC patients to that of healthy controls by liquid chromatography-tandem mass spectrometry (LC–MS/MS). We found 19 lipids (e.g., phosphatidylinositols 18:0/20:4 and 18:0/18:2 and free fatty acid 22:6) to be remarkably decreased, whereas 2 lipids (i.e., diacylglycerols 16:0/16:1 and 16:0/20:3) to be increased, in the plasma of NPC patients, compared with controls. Different lipid profiles were also observed between patients with different titers of EBV antibodies (e.g., EA-IgA and VCA-IgA) as well as between patients with and without lymph node or distant organ metastasis. In conclusion, plasma lipidomics might help to differentiate NPC cases from controls, whereas EBV infection might influence the risk and prognosis of NPC through modulating lipid metabolism in both tumor cells and peripheral blood.

Polygenic Liability to Depression Is Associated With Multiple Medical Conditions in the Electronic Health Record: Phenome-wide Association Study of 46,782 Individuals

BackgroundMajor depressive disorder (MDD) is a leading cause of disease-associated disability, with much of the increased burden due to psychiatric and medical comorbidity. This comorbidity partly reflects common genetic influences across conditions. Integrating molecular-genetic tools with health records enables tests of association with the broad range of physiological and clinical phenotypes. However, standard phenome-wide association studies analyze associations with individual genetic variants. For polygenic traits such as MDD, aggregate measures of genetic risk may yield greater insight into associations across the clinical phenome. MethodsWe tested for associations between a genome-wide polygenic risk score for MDD and medical and psychiatric traits in a phenome-wide association study of 46,782 unrelated, European-ancestry participants from the Michigan Genomics Initiative. ResultsThe MDD polygenic risk score was associated with 211 traits from 15 medical and psychiatric disease categories at the phenome-wide significance threshold. After excluding patients with depression, continued associations were observed with respiratory, digestive, neurological, and genitourinary conditions; neoplasms; and mental disorders. Associations with tobacco use disorder, respiratory conditions, and genitourinary conditions persisted after accounting for genetic overlap between depression and other psychiatric traits. Temporal analyses of time-at-first-diagnosis indicated that depression disproportionately preceded chronic pain and substance-related disorders, while asthma disproportionately preceded depression. ConclusionsThe present results can inform the biological links between depression and both mental and systemic diseases. Although MDD polygenic risk scores cannot currently forecast health outcomes with precision at the individual level, as molecular-genetic discoveries for depression increase, these tools may augment risk prediction for medical and psychiatric conditions.

Lipids and Genes: Regulatory roles of lipids in RNA expression

AbstractNuclear lipid metabolism and metabolites play important roles in the regulation of lipid‐lipid, lipid‐gene, lipid‐chromatin, lipid‐membrane, and lipid‐protein interactions to maintain the nuclear microenvironment, three‐dimensional chromatin architecture, gene expression and transcription, and biological function. This editorial highlights the value of lipid‐gene in the identification and development of biomarkers and targets and emphasises the significance of interregulation between lipids and genes in the innovation and application of precise therapies for patients. Regulatory functions of nuclear lipid dynamics and biophysics modify transcriptomic expression, and modification (lipotranscriptome) can be a new approach for discovery and development of disease‐specific diagnoses and therapies, although there are several challenges to be overcome. A better understanding of how lipid‐based changes in nuclear functions and transcriptomic profiles modify clinical phenomes will provide new insights to understand the molecular mechanisms of diseases and to develop spatiotemporal molecular medicine diagnostics and therapeutics.

An atlas of dynamic peripheral blood mononuclear cell landscapes in human perioperative anaesthesia/surgery.

BackgroundThe number of patients receiving anaesthesia is increasing, but the impact of general anaesthesia on the patient's immune system remains unclear. The aim of the present study is to investigate dynamics of systemic immune cell responses to anaesthesia during perioperative period at a single‐cell solution.MethodsThe peripheral blood mononuclear cells (PBMCs) and clinical phenomes were harvested and recorded 1 day before anaesthesia and operation, just after anaesthesia (0 h), and 24 and 48 h after anaesthesia. Single‐cell sequencing of PBMCs was performed with 10× genomics. Subsequently, data analysis was performed with R packages: Seurat, clusterProfiler and CellPhoneDB.ResultsWe found that the cluster of CD56+ NK cells changed at 0 h and the cluster of monocytes increased at 24 and 48 h after anaesthesia. The characteristic genes of CD56+ NK cells were mainly enriched in the Jak‐STAT signalling pathway and in cell adhesion molecules (24 h) and carbon metabolism (48 h). The communication between CD14+ monocytes and other cells decreased substantially 0 and 48 h after operation. The number of plasma cells enriched in protein export in men was substantially higher than that in women, although the total number in patients decreased 24 h after operation. CD14+ monocytes dominated that cell‐cell communications appeared in females, while CD8+ NKT cells dominated that cell‐cell communications appeared in male. The number of plasma cells increased substantially in patients with major surgical trauma, with enrichments of pentose phosphate pathway. The communications between plasma cells with other cells varied between surgical severities and anaesthetic forms. The intravenous anaesthesia caused major alterations of cell types, including CD14+ monocytes, plasmas cells and MAIT cells, as compared with inhalation anaesthesia.ConclusionWe initially reported the roles of perioperative anaesthesia/surgery in temporal phenomes of circulating immune cells at a single‐cell solution. Thus, the protection against immune cell changes would benefit the recovery from anaesthesia/surgery.

How to translate the knowledge of COVID‐19 into prevention of Omicron variants

AbstractOmicron variants are part of the “COVID‐19 variants of concerns” and have the potential to spread around the world rapidly and can harm human life. We can anticipate that the endemic state of COVID‐19 will be characterized by development of new strains with surges that will predominate in unvaccinated and immunodeficient populations. Thus, there will be an important role for promoting vaccinations, boosters and accessible testing to prevent disease transmission and to rapidly detect surges. There is an urgent need to explore the virology and biology of Omicron variants, define clinical phenomes and therapies, monitor dynamics of genetic changes and translate the knowledge of COVID‐19 into new variants. Clinical and translational medicine will be impactful in addressing these challenges by providing new insights for understanding and predicting new variants‐associated transmissibility, disease severity, immune escape, diagnostic, or therapeutic failure.

Construction of a nitro-oxidative stress-driven, mechanistic model of mood disorders: A nomothetic network approach

Major depression is accompanied by increased IgM-mediated autoimmune responses to oxidative specific epitopes (OSEs) and nitric oxide (NO)-adducts. These responses were not examined in bipolar disorder type 1 (BP1) and BP2. IgM responses to malondialdehyde (MDA), phosphatidinylinositol, oleic acid, azelaic acid, and NO-adducts were determined in 35 healthy controls, and 47 major depressed (MDD), 29 BP1, and 25 BP2 patients. We also measured serum peroxides, IgG to oxidized LDL (oxLDL), and IgM/IgA directed to lipopolysaccharides (LPS). IgM responses to OSEs and NO-adducts (OSENO) were significantly higher in MDD and BP1 as compared with controls, and IgM to OSEs higher in MDD than in BP2. Partial Least Squares (PLS) analysis showed that 57.7% of the variance in the clinical phenome of mood disorders was explained by number of episodes, a latent vector extracted from IgM to OSENO, IgG to oxLDL, and peroxides. There were significant specific indirect effects of IgA/IgM to LPS on the clinical phenome, which were mediated by peroxides, IgM OSENO, and IgG oxLDL. Using PLS we have constructed a data-driven nomothetic network which ensembled causome (increased plasma LPS load), adverse outcome pathways (namely neuro-affective toxicity), and clinical phenome features of mood disorders in a data-driven model. Based on those feature sets, cluster analysis discovered a new diagnostic class characterized by increased plasma LPS load, peroxides, autoimmune responses to OSENO, and increased phenome scores. Using the new nomothetic network approach, we constructed a mechanistically transdiagnostic diagnostic class indicating neuro-affective toxicity in 74.3% of the mood disorder patients.

MALDI-ToF Mass Spectra Phenomic Analysis for Human Disease Diagnosis Enabled by Cutting-Edge Data Processing Pipelines and Bioinformatics Tools.

Current methods for diagnosing human disease are still incapable of rapidly and accurately screening for multiple diseases simultaneously on a large scale, and at an affordable price. MALDI-ToF mass spectrometry is an ultra-sensitive, ultra-fast, lowcost, high-throughput technology that has the potential to achieve this goal, allowing human phenotype characterization and thus phenomic screening for multiple disease states. In this review, we will discuss the main advances achieved so far, putting forward targeted applications of MALDI-ToF mass spectrometry in the service of human disease detection. This review focuses on the methodological workflow as MALDI-ToF data processing for phenomic analysis, using state-of-the-art bioinformatic pipelines and software tools. The role of mathematical modelling, machine learning, and artificial intelligence algorithms for disease screening are considered. Moreover, we present some previously developed tools for disease diagnostics and screening based on MALDI-ToF analysis. We discuss the remaining challenges that are ahead when implementing MALDI-ToF into clinical laboratories. Differentiating a standard profile from a single disease phenotype is challenging, but the potential to simultaneously run multiple algorithm screens for different disease phenotypes may only be limited by computing power once this initial hurdle is overcome. The ability to explore the full potential of human clinical phenomics may be closer than imagined; this review gives an insight into the benefits this technology may reap for the future of clinical diagnostics.

Trans-omic profiling between clinical phenoms and lipidomes among patients with different subtypes of lung cancer.

Lung cancer has high mortality, often accompanied with systemic metabolic disorders. The present study aimed at defining values of trans‐nodules cross‐clinical phenomic and lipidomic network layers in patients with adenocarcinoma (ADC), squamous cell carcinomas, or small cell lung cancer (SCLC). We measured plasma lipidomic profiles of lung cancer patients and found that altered lipid panels and concentrations varied among lung cancer subtypes, genders, ages, stages, metastatic status, nutritional status, and clinical phenome severity. It was shown that phosphatidylethanolamine elements (36:2, 18:0/18:2, and 18:1/18:1) were SCLC specific, whereas lysophosphatidylcholine (20:1 and 22:0 sn‐position‐1) and phosphatidylcholine (19:0/19:0 and 19:0/21:2) were ADC specific. There were statistically more lipids declined in male, <60 ages, late stage, metastasis, or body mass index < 22 . Clinical trans‐omics analyses demonstrated that one phenome in lung cancer subtypes might be generated from multiple metabolic pathways and metabolites, whereas a metabolic pathway and metabolite could contribute to different phenomes among subtypes, although those needed to be furthermore confirmed by bigger studies including larger population of patients in multicenters. Thus, our data suggested that trans‐omic profiles between clinical phenomes and lipidomes might have the value to uncover the heterogeneity of lipid metabolism among lung cancer subtypes and to screen out phenome‐based lipid panels as subtype‐specific biomarkers.

Integration of individual prediction index based on autophagy‐related genes and clinical phenomes in melanoma patients

Integration of individual prediction index based on autophagy‐related genes and clinical phenomes in melanoma patients

Roles of acyl-CoA synthetase long-chain family member 5 and colony stimulating factor 2 in inhibition of palmitic or stearic acids in lung cancer cell proliferation and metabolism.

Lung cancer is a heterogeneous and complex disease with the highest incidence and mortality rate. The present study aims at defining the lung cancer phenome specificity of lipidomic profiles, screening target lipid-dependent transcriptional alternations, identifying target lipid-associated target genes, and exploring molecular mechanisms. Lung cancer-specific and lung cancer subtype-specific target lipids palmitic acid (C16:0) and stearic acid (C18:0) were found as target lipids by integrating clinical phenomics, lipidomics, and transcriptomics and exhibited antiproliferative effects in sensitive cells. The metabolism-associated gene ACSL5 or inflammation-associated gene CCL3 was identified in lung adenocarcinoma or small lung cancer cells, respectively. C16:0 or C18:0 could upregulate ACSL5 or CSF2 expression in a time- and dose-dependent pattern, and the deletion of both genes led to the insensitivity of cells. Target lipids increased the expression of PDK4 gene in different patterns and inhibited cell proliferation through alterations of intracellular energy. Thus, our data provide a new strategy to investigate the trans-points between clinical and phenomics and lipidomics and target lipid-associated molecular mechanisms to benefit from the discovery of new therapies.

Multidisciplinary therapy strategy of precision medicine in clinical practice.

The application of precision medicine concept in clinical work needs a period of practice and experience accumulation. The present article introduced an example of functioning approach named “multidisciplinary therapy strategy of precision medicine” (MDTS‐PM), clinical practice and process, decision‐making, and therapies. The MDTS‐PM integrates multidisciplinary experts and develops real‐time therapeutic strategy based on clinical phenomes and gene sequencing of tissue DNA and circulating DNA. The strength of MDTS‐PM is the combination of dynamical clinical phenomes, genetic information, diagnosis, and treatment to make the therapy more targeted and specific. MDTS‐PM provides comprehensive, whole‐process, and personalized diagnosis and treatment services for patients with complex cancer or complex drug resistance progression; provides guidance for further adjustment of drug use; and establishes a multidisciplinary cooperative team, improves the quality of clinical diagnosis and treatment, and optimizes the process of medical services.

Significance of clinical phenomes of patients with COVID-19 infection: A learning from 3795 patients in 80 reports.

A new coronavirus SARS‐CoV‐2 has caused outbreaks in multiple countries and the number of cases is rapidly increasing through human‐to‐human transmission. Clinical phenomes of patients with SARS‐CoV‐2 infection are critical in distinguishing it from other respiratory infections. The extent and characteristics of those phenomes varied depending on the severities of the infection, for example, beginning with fever or a mild cough, progressed with signs of pneumonia, and worsened with severe or even fatal respiratory difficulty in acute respiratory distress syndrome. We summarized clinical phenomes of 3795 patients with COVID‐19 based on 80 published reports from the onset of outbreak to March 2020 to emphasize the importance and specificity of those phenomes in diagnosis and treatment of infection, and evaluate the impact on medical services. The data show that the incidence of male patients was higher than that of females and the level of C‐reaction protein was increased as well as most patients' imaging included ground‐glass opacity. Clinical phenomes of SARS‐CoV‐2 infection were compared with those of SARS‐CoV and MERS‐CoV infections. There is an urgent need to develop an artificial intelligence‐based machine learning capacity to analyze and integrate radiomics‐ or imaging‐based, patient‐based, clinician‐based, and molecular measurements‐based data to fight the outbreak of COVID‐19 and enable more efficient responses to unknown infections in future.

Understanding Diseases from Single-Cell Sequencing and Methylation.

Clinical single-cell biomedicine has become a new emerging discipline, which integrates single-cell RNA and DNA sequencing, proteomics, and functions with clinical phenomes, therapeutic responses, and prognosis. It is of great value to discover disease-, phenome-, and therapy-specific diagnostic biomarkers and therapeutic targets on the basis of the principle of clinical single-cell biomedicine. This book reviews the roles of single-cell sequencing and methylation in diseases and explores disease-specific alterations of single-cell sequencing and methylation, especially focusing on potential applications of methodologies on human single-cell sequencing and methylation, on potential correlations between those changes with pulmonary diseases, and on potential roles of signaling pathways that cause heterogeneous cellular responses during treatment. This book also emphasizes the importance of methodologies in clinical practice and application, the potential of perspectives, challenges and solutions, and the significance of single-cell preparation standardization. Alterations of DNA and RNA methylation, demethylation in lung diseases, and a deep knowledge about the regulation and function of target gene methylation for diagnosing and treating diseases at the early stage are also provided. Importantly, this book aims to apply the measurement of single-cell sequencing and methylation for clinical diagnosis and treatment and to understand clinical values of those parameters and to headline and foresee the potential values of the application of single-cell sequencing in non-cancer diseases.

Methylation of Inflammatory Cells in Lung Diseases.

This chapter overviews roles of DNA methylation in inflammatory cell biology with the focuses on lymphocytes and macrophages/monocytes in lung diseases, although the molecular mechanisms by which target genes are methylated and regulated in lung diseases remain unclear. Most of epigenetic studies on DNA methylation of target genes in lung diseases mainly demonstrated the correlation of DNA methylation of target genes with the levels of other corresponding factors, with the specificity of clinical phenomes, and with the severity of lung diseases. There is an urgent need to identify and validate the specificity and regulatory mechanisms of inflammatory cell epigenetics in depth. The epigenetic heterogeneity among different subsets of T cells and among promoters or non-promoters of target genes should be furthermore clarifiedin acute or chronic lung diseases and cancers. The hyper/hypo-methylation and modifications of chromosol and extrachromosomal DNA may result in alternations in proteins within inflammatory cells, which can be identified as disease-specific biomarkers and therapeutic targets.

End-of-stem pain in hip and knee arthroplasty

End-of-stem pain after knee and hip arthroplasty with diaphyseal supportive stems is afrequently overlooked and potentially underestimated complication. Acommonly recurring clinical phenome is the symptom-free interval after surgery of weeks to months, with new onset of symptoms under stress only later. The patient is often again reliant on walking sticks. End-of-stem pain is a diagnosis of exclusion. Pain is projected into the tip of the stem, and if differential diagnoses such as loosening are excluded, then the patient might be treated with a"bending-plate". Since bone cement has asimilar elastic modulus to human cortical bone, achange of method to acemented implant can also be expedient. In the primary situation, in addition to cemented stems, the use of "split-stems" could be useful. After revision surgery of any kind, a timely cessation of pain confirms the diagnosis.