Gene-based burden scores identify rare variant associations for 28 blood biomarkers.

BACKGROUND: A relevant part of the genetic architecture of complex traits is still unknown; despite the discovery of many disease-associated common variants. Polygenic risk score (PRS) models are based on the evaluation of the additive effects attributable to common variants and have been successfully implemented to assess the genetic susceptibility for many phenotypes. In contrast, burden tests are often used to identify an enrichment of rare deleterious variants in specific genes. Both kinds of genetic contributions are typically analyzed independently. Many studies suggest that complex phenotypes are influenced by both low effect common variants and high effect rare deleterious variants. The aim of this paper is to integrate the effect of both common and rare functional variants for a more comprehensive genetic risk modeling. METHODS: We developed a framework combining gene-based scores based on the enrichment of rare functionally relevant variants with genome-wide PRS based on common variants for association analysis and prediction models. We applied our framework on UK Biobank dataset with genotyping and exome data and considered 28 blood biomarkers levels as target phenotypes. For each biomarker, an association analysis was performed on full cohort using gene-based scores (GBS). The cohort was then split into 3 subsets for PRS construction and feature selection, predictive model training, and independent evaluation, respectively. Prediction models were generated including either PRS, GBS or both (combined). RESULTS: Association analyses of the cohort were able to detect significant genes that were previously known to be associated with different biomarkers. Interestingly, the analyses also revealed heterogeneous effect sizes and directionality highlighting the complexity of the blood biomarkers regulation. However, the combined models for many biomarkers show little or no improvement in prediction accuracy compared to the PRS models. CONCLUSION: This study shows that rare variants play an important role in the genetic architecture of complex multifactorial traits such as blood biomarkers. However, while rare deleterious variants play a strong role at an individual level, our results indicate that classical common variant based PRS might be more informative to predict the genetic susceptibility at the population level.

Machine Learning for Decision-Support in Acute Abdominal Pain - Proof of Concept and Central Considerations.

Acute abdominal pain is a common presenting symptom in the emergency department and represents heterogeneous causes and diagnoses. There is often a decision to be made regarding emergency surgical care. Machine learning (ML) could be used here as a decision-support and relieve the time and personnel resource shortage.Patients with acute abdominal pain presenting to the Department of Surgery at Bonn University Hospital in 2020 and 2021 were retrospectively analyzed. Clinical parameters as well as laboratory values were used as predictors. After randomly splitting into a training and test data set (ratio 80 to 20), three ML algorithms were comparatively trained and validated. The entire procedure was repeated 20 times.A total of 1357 patients were identified and included in the analysis, with one in five (n = 276, 20.3%) requiring emergency abdominal surgery within 24 hours. Patients operated on were more likely to be male (p = 0.026), older (p = 0.006), had more gastrointestinal symptoms (nausea: p < 0.001, vomiting p < 0.001) as well as a more recent onset of pain (p < 0.001). Tenderness (p < 0.001) and guarding (p < 0.001) were more common in surgically treated patients and blood analyses showed increased inflammation levels (white blood cell count: p < 0.001, CRP: p < 0.001) and onset of organ dysfunction (creatinine: p < 0.014, quick p < 0.001). Of the three trained algorithms, the tree-based methods (h2o random forest and cforest) showed the best performance. The algorithms classified patients, i.e., predicted surgery, with a median AUC ROC of 0.81 and 0.79 and AUC PRC of 0.56 in test sets.A proof-of-concept was achieved with the development of an ML model for predicting timely surgical therapy for acute abdomen. The ML algorithm can be a valuable tool in decision-making. Especially in the context of heavily used medical resources, the algorithm can help to use these scarce resources more effectively. Technological progress, especially regarding artificial intelligence, increasingly enables evidence-based approaches in surgery but requires a strictly interdisciplinary approach. In the future, the use and handling of ML should be integrated into surgical training.

Deficiency for SAMHD1 activates MDA5 in a cGAS/STING-dependent manner.

Defects in nucleic acid metabolizing enzymes can lead to spontaneous but selective activation of either cGAS/STING or RIG-like receptor (RLR) signaling, causing type I interferon-driven inflammatory diseases. In these pathophysiological conditions, activation of the DNA sensor cGAS and IFN production are linked to spontaneous DNA damage. Physiological, or tonic, IFN signaling on the other hand is essential to functionally prime nucleic acid sensing pathways. Here, we show that low-level chronic DNA damage in mice lacking the Aicardi-Goutières syndrome gene SAMHD1 reduced tumor-free survival when crossed to a p53-deficient, but not to a DNA mismatch repair-deficient background. Increased DNA damage did not result in higher levels of type I interferon. Instead, we found that the chronic interferon response in SAMHD1-deficient mice was driven by the MDA5/MAVS pathway but required functional priming through the cGAS/STING pathway. Our work positions cGAS/STING upstream of tonic IFN signaling in Samhd1-deficient mice and highlights an important role of the pathway in physiological and pathophysiological innate immune priming.

Identification of de novo variants in nonsyndromic cleft lip with/without cleft palate patients with low polygenic risk scores.

BACKGROUND: Nonsyndromic cleft lip with/without cleft palate (nsCL/P) is a congenital malformation of multifactorial etiology. Research has identified >40 genome-wide significant risk loci, which explain less than 40% of nsCL/P heritability. Studies show that some of the hidden heritability is explained by rare penetrant variants. METHODS: To identify new candidate genes, we searched for highly penetrant de novo variants (DNVs) in 50 nsCL/P patient/parent-trios with a low polygenic risk for the phenotype (discovery). We prioritized DNV-carrying candidate genes from the discovery for resequencing in independent cohorts of 1010 nsCL/P patients of diverse ethnicities and 1574 population-matched controls (replication). Segregation analyses and rare variant association in the replication cohort, in combination with additional data (genome-wide association data, expression, protein-protein-interactions), were used for final prioritization. CONCLUSION: In the discovery step, 60 DNVs were identified in 60 genes, including a variant in the established nsCL/P risk gene CDH1. Re-sequencing of 32 prioritized genes led to the identification of 373 rare, likely pathogenic variants. Finally, MDN1 and PAXIP1 were prioritized as top candidates. Our findings demonstrate that DNV detection, including polygenic risk score analysis, is a powerful tool for identifying nsCL/P candidate genes, which can also be applied to other multifactorial congenital malformations.

Genome-wide identification of disease-causing copy number variations in 450 individuals with anorectal malformations.

Anorectal malformations (ARM) represent a spectrum of rare malformations originating from a perturbated development of the embryonic hindgut. Approximately 60% occur as a part of a defined genetic syndrome or within the spectrum of additional congenital anomalies. Rare copy number variations (CNVs) have been associated with both syndromic and non-syndromic forms. The present study represents the largest study to date to explore the contribution of CNVs to the expression of ARMs. SNP-array-based molecular karyotyping was applied in 450 individuals with ARM and 4392 healthy controls. CNVs were identified from raw intensity data using PennCNV. Overlapping CNVs between cases and controls were discarded. Remaining CNVs were filtered using a stringent filter algorithm of nine filter steps. Prioritized CNVs were confirmed using qPCR. Filtering prioritized and qPCR confirmed four microscopic chromosomal anomalies and nine submicroscopic CNVs comprising seven microdeletions (del2p13.2, del4p16.2, del7q31.33, del9p24.1, del16q12.1, del18q32, del22q11.21) and two microduplications (dup2p13.2, dup17q12) in 14 individuals (12 singletons and one affected sib-pair). Within these CNVs, based on their embryonic expression data and function, we suggest FOXK2, LPP, and SALL3 as putative candidate genes. Overall, our CNV analysis identified putative microscopic and submicroscopic chromosomal rearrangements in 3% of cases. Functional characterization and re-sequencing of suggested candidate genes is warranted.

A novel serum extracellular vesicle protein signature to monitor glioblastoma tumor progression.

Detection of tumor progression in patients with glioblastoma remains a major challenge. Extracellular vesicles (EVs) are potential biomarkers and can be detected in the blood of patients with glioblastoma. In our study, we evaluated the potential of serum-derived EVs from glioblastoma patients to serve as biomarker for tumor progression. EVs from serum of glioblastoma patients and healthy volunteers were separated by size exclusion chromatography and ultracentrifugation. EV markers were defined by using a proximity-extension assay and bead-based flow cytometry. Tumor progression was defined according to modified RANO criteria. EVs from the serum of glioblastoma patients (n = 67) showed an upregulation of CD29, CD44, CD81, CD146, C1QA and histone H3 as compared to serum EVs from healthy volunteers (P value range: <.0001 to .08). For two independent cohorts of glioblastoma patients, we noted upregulation of C1QA, CD44 and histone H3 upon tumor progression, but not in patients with stable disease. In a multivariable logistic regression analysis, a combination of CD29, CD44, CD81, C1QA and histone H3 correlated with RANO-defined tumor progression with an AUC of 0.76. Measurement of CD29, CD44, CD81, C1QA and histone H3 in serum-derived EVs of glioblastoma patients, along with standard MRI assessment, has the potential to improve detection of true tumor progression and thus could be a useful biomarker for clinical decision making.

PFN4 is required for manchette development and acrosome biogenesis during mouse spermiogenesis.

Profilin 4 (Pfn4) is expressed during spermiogenesis and localizes to the acrosome-acroplaxome-manchette complex. Here, we generated PFN4-deficient mice, with sperm displaying severe impairment in manchette formation. Interestingly, HOOK1 staining suggests that the perinuclear ring is established; however, ARL3 staining is disrupted, suggesting that lack of PFN4 does not interfere with the formation of the perinuclear ring and initial localization of HOOK1, but impedes microtubular organization of the manchette. Furthermore, amorphous head shape and flagellar defects were detected, resulting in reduced sperm motility. Disrupted cis- and trans-Golgi networks and aberrant production of proacrosomal vesicles caused impaired acrosome biogenesis. Proteomic analysis showed that the proteins ARF3, SPECC1L and FKBP1, which are involved in Golgi membrane trafficking and PI3K/AKT pathway, are more abundant in Pfn4-/- testes. Levels of PI3K, AKT and mTOR were elevated, whereas AMPK level was reduced, consistent with inhibition of autophagy. This seems to result in blockage of autophagic flux, which could explain the failure in acrosome formation. In vitro fertilization demonstrated that PFN4-deficient sperm is capable of fertilizing zona-free oocytes, suggesting a potential treatment for PFN4-related human infertility.

Effects of different ratios of omega-6:omega-3 fatty acids in the diet of sows on the proteome of milk-derived extracellular vesicles.

Milk is a nutrient-rich biofluid that contains several biocomponents with distinctive functions, including extracellular vesicles (EV). Milk EV have been associated with the regulation of the newborn's immune system and to influence essential cellular development. The EV proteome comprises the protein constituents and cargo; changes in these compartments could impact their role mediating communication. The ratio of dietary ω-6 to ω-3 polyunsaturated fatty acids (PUFA) is known to affect health and inflammation, and to induce changes in milk fatty acid composition, but no reports have included the milk EV fraction so far. We isolated EV from milk samples obtained on days 0, 7, and 14 after parturition from sows receiving either a standard diet or a test diet enriched in ω-3 (ω6:ω3 = 4:1). Small milk-derived EV were isolated using ultracentrifugation coupled with size exclusion chromatography, and characterized by nanoparticle tracking analysis, transmission electron microscopy, and Western blotting. Using a TMT-based high-resolution quantitative approach, the proteomics analysis revealed variations in the milk EV proteome within the diet groups with differences in the abundance of spondin-2 and 78 kDa glucose-regulated protein. Future studies are encouraged to explore further dietary effects on milk EV composition and their relation to the offspring's development. SIGNIFICANCE: Milk EV are known as key players mediating the regulation of the infant's immune system and growth. The EV proteome comprises the protein constituents and protein cargo, and any changes in this system could impact their role in intercellular communication. This study aimed at evaluating how different ω-6:ω-3 ratios in the maternal diet could translate to the milk EV proteome. This is relevant for basic research, but also has applied aspects in animal nutrition and health and may provide new perspectives for feeding additives.

Reconstruction of the origin of the first major SARS-CoV-2 outbreak in Germany.

The first major COVID-19 outbreak in Germany occurred in Heinsberg in February 2020 with 388 officially reported cases. Unexpectedly, the first outbreak happened in a small town with little to no travelers. We used phylogenetic analyses to investigate the origin and spread of the virus in this outbreak. We sequenced 90 (23%) SARS-CoV-2 genomes from the 388 reported cases including the samples from the first documented cases. Phylogenetic analyses of these sequences revealed mainly two circulating strains with 74 samples assigned to lineage B.3 and 6 samples assigned to lineage B.1. Lineage B.3 was introduced first and probably caused the initial spread. Using phylogenetic analysis tools, we were able to identify closely related strains in France and hypothesized the possible introduction from France.

GenRisk: a tool for comprehensive genetic risk modeling.

SUMMARY: The genetic architecture of complex traits can be influenced by both many common regulatory variants with small effect sizes and rare deleterious variants in coding regions with larger effect sizes. However, the two kinds of genetic contributions are typically analyzed independently. Here, we present GenRisk, a python package for the computation and the integration of gene scores based on the burden of rare deleterious variants and common-variants-based polygenic risk scores. The derived scores can be analyzed within GenRisk to perform association tests or to derive phenotype prediction models by testing multiple classification and regression approaches. GenRisk is compatible with VCF input file formats. AVAILABILITY AND IMPLEMENTATION: GenRisk is an open source publicly available python package that can be downloaded or installed from Github (https://github.com/AldisiRana/GenRisk). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Overexpression of Parkin in clear cell renal cell carcinoma decreases tumor aggressiveness by regulating CKS2 levels.

Low expression levels of the E3 ubiquitin­protein ligase Parkin (PARK2) are exhibited in several cancer entities, including clear cell renal cell carcinoma (ccRCC), and are associated with poor prognosis; however, PARK2 can also function as a tumor suppressor gene. The aim of the present study was to thoroughly investigate the effects of PARK2 overexpression in ccRCC cell lines and to determine its effects on malignancy by conducting functional assays such as cell cycle analysis, apoptosis analysis, migration and invasion assays. Furthermore, liquid chromatography­mass spectrometry was used to decipher potential targets of PARK2 that may influence the behavior of ccRCC tumor cells. In addition, ccRCC tumor tissues from a patient cohort were examined in tissue microarrays to find correlations between different clinical parameters. In the present study, it was demonstrated that the induction of PARK2 resulted in a less aggressive phenotype, as indicated by lower migration and invasion in ccRCC cell lines. Mass spectrometry revealed decreased levels of 29 proteins in cells with PARK2 overexpression, including CDC28 protein kinase regulatory subunit 2 (CKS2), which is highly expressed in numerous types of cancer. The link between the function of PARK2 as an E3 ubiquitin ligase and the low expression levels of CKS2 was investigated by mutating the catalytic domain of the PARK2 gene, and it was found that the effect of decreased migration was abolished in 786­O and RCC­MH ccRCC cell lines. CKS2 silencing decreased migratory ability of the cells. Furthermore, it was revealed that high CKS2 levels are associated with high tumor grading in patient samples and lower patient survival. In conclusion, the results from the present study indicated that PARK2 may signal via CKS2 to affect tumor behavior. In consequence, CKS2 may be a biomarker in ccRCC and may also serve as potential target for ccRCC therapy.

Machine learning to guide clinical decision-making in abdominal surgery-a systematic literature review.

PURPOSE: An indication for surgical therapy includes balancing benefits against risk, which remains a key task in all surgical disciplines. Decisions are oftentimes based on clinical experience while guidelines lack evidence-based background. Various medical fields capitalized the application of machine learning (ML), and preliminary research suggests promising implications in surgeons' workflow. Hence, we evaluated ML's contemporary and possible future role in clinical decision-making (CDM) focusing on abdominal surgery. METHODS: Using the PICO framework, relevant keywords and research questions were identified. Following the PRISMA guidelines, a systemic search strategy in the PubMed database was conducted. Results were filtered by distinct criteria and selected articles were manually full text reviewed. RESULTS: Literature review revealed 4,396 articles, of which 47 matched the search criteria. The mean number of patients included was 55,843. A total of eight distinct ML techniques were evaluated whereas AUROC was applied by most authors for comparing ML predictions vs. conventional CDM routines. Most authors (N = 30/47, 63.8%) stated ML's superiority in the prediction of benefits and risks of surgery. The identification of highly relevant parameters to be integrated into algorithms allowing a more precise prognosis was emphasized as the main advantage of ML in CDM. CONCLUSIONS: A potential value of ML for surgical decision-making was demonstrated in several scientific articles. However, the low number of publications with only few collaborative studies between surgeons and computer scientists underpins the early phase of this highly promising field. Interdisciplinary research initiatives combining existing clinical datasets and emerging techniques of data processing may likely improve CDM in abdominal surgery in the future.

Iron Deficiency Caused by Intestinal Iron Loss-Novel Candidate Genes for Severe Anemia.

The adult human body contains about 4 g of iron. About 1-2 mg of iron is absorbed every day, and in healthy individuals, the same amount is excreted. We describe a patient who presents with severe iron deficiency anemia with hemoglobin levels below 6 g/dL and ferritin levels below 30 ng/mL. Although red blood cell concentrates and intravenous iron have been substituted every month for years, body iron stores remain depleted. Diagnostics have included several esophago-gastro-duodenoscopies, colonoscopies, MRI of the liver, repetitive bone marrow biopsies, psychological analysis, application of radioactive iron to determine intact erythropoiesis, and measurement of iron excretion in urine and feces. Typically, gastrointestinal bleeding is a major cause of iron loss. Surprisingly, intestinal iron excretion in stool in the patient was repetitively increased, without gastrointestinal bleeding. Furthermore, whole exome sequencing was performed in the patient and additional family members to identify potential causative genetic variants that may cause intestinal iron loss. Under different inheritance models, several rare mutations were identified, two of which (in CISD1 and KRI1) are likely to be functionally relevant. Intestinal iron loss in the current form has not yet been described and is, with high probability, the cause of the severe iron deficiency anemia in this patient.

Comparative proteome profiling in exosomes derived from porcine colostrum versus mature milk reveals distinct functional proteomes.

Exosomes are membranous vesicles of endocytic origin, recently been considered as major players in cell-cell communication. Milk is highly complex, and diverse biocomponents provide adequate nutrition, transfer immunity, and promote adequate neonate development. Milk exosomes are suggested to have a key role in these processes, yet to be further explored, and the alteration of the exosomes' cargo in different stages of lactation stages is important for understanding the factors relevant in nursing and also for improving milk replacer products both for humans and animals. We isolated exosomes from porcine milk in different lactation stages and analyzed their content using a TMT-based high-resolution quantitative proteomic approach. Exosomes were isolated using ultracentrifugation coupled with size exclusion chromatography to enrich milk-derived exosomes in samples obtained at day 0, 7, and 14 after parturition, and characterized by nanoparticle tracking analysis, transmission electron microscopy, and Western blotting. Quantitative proteomics analysis revealed different proteome profiles for colostrum exosomes and milk exosomes. The functional analysis highlighted pathways related to the regulation of homeostasis to be upregulated in colostrum exosomes, and pathways such as endothelial cell development and lipid metabolism to be upregulated in mature milk exosomes. This study endorses the importance of exosomes as active biocomponents of milk and provides knowledge for future studies exploring their role in the regulation of immunity and growth of the newborn. SIGNIFICANCE: The identified functional proteome and protein-protein interaction networks identified in our study help to elucidate the role of milk exosomes in different lactation periods. The results generated herein are of relevance for the basic understanding of their impact on the infant's development but also for bringing forward the manufacturing of milk replacers.

Extending the allelic spectrum at noncoding risk loci of orofacial clefting.

Genome-wide association studies (GWAS) have generated unprecedented insights into the genetic etiology of orofacial clefting (OFC). The moderate effect sizes of associated noncoding risk variants and limited access to disease-relevant tissue represent considerable challenges for biological interpretation of genetic findings. As rare variants with stronger effect sizes are likely to also contribute to OFC, an alternative approach to delineate pathogenic mechanisms is to identify private mutations and/or an increased burden of rare variants in associated regions. This report describes a framework for targeted resequencing at selected noncoding risk loci contributing to nonsyndromic cleft lip with/without cleft palate (nsCL/P), the most frequent OFC subtype. Based on GWAS data, we selected three risk loci and identified candidate regulatory regions (CRRs) through the integration of credible SNP information, epigenetic data from relevant cells/tissues, and conservation scores. The CRRs (total 57 kb) were resequenced in a multiethnic study population (1061 patients; 1591 controls), using single-molecule molecular inversion probe technology. Combining evidence from in silico variant annotation, pedigree- and burden analyses, we identified 16 likely deleterious rare variants that represent new candidates for functional studies in nsCL/P. Our framework is scalable and represents a promising approach to the investigation of additional congenital malformations with multifactorial etiology.

Chd8 regulates X chromosome inactivation in mouse through fine-tuning control of Xist expression.

Female mammals achieve dosage compensation by inactivating one of their two X chromosomes during development, a process entirely dependent on Xist, an X-linked long non-coding RNA (lncRNA). At the onset of X chromosome inactivation (XCI), Xist is up-regulated and spreads along the future inactive X chromosome. Contextually, it recruits repressive histone and DNA modifiers that transcriptionally silence the X chromosome. Xist regulation is tightly coupled to differentiation and its expression is under the control of both pluripotency and epigenetic factors. Recent evidence has suggested that chromatin remodelers accumulate at the X Inactivation Center (XIC) and here we demonstrate a new role for Chd8 in Xist regulation in differentiating ES cells, linked to its control and prevention of spurious transcription factor interactions occurring within Xist regulatory regions. Our findings have a broader relevance, in the context of complex, developmentally-regulated gene expression.

Prognostic Gene Expression, Stemness and Immune Microenvironment in Pediatric Tumors.

Pediatric tumors frequently arise from embryonal cells, often displaying a stem cell-like ("small round blue") morphology in tissue sections. Because recently "stemness" has been associated with a poor immune response in tumors, we investigated the association of prognostic gene expression, stemness and the immune microenvironment systematically using transcriptomes of 4068 tumors occurring mostly at the pediatric and young adult age. While the prognostic landscape of gene expression (PRECOG) and infiltrating immune cell types (CIBERSORT) is similar to that of tumor entities occurring mainly in adults, the patterns are distinct for each diagnostic entity. A high stemness score (mRNAsi) correlates with clinical and morphologic subtype in Wilms tumors, neuroblastomas, synovial sarcomas, atypical teratoid rhabdoid tumors and germ cell tumors. In neuroblastomas, a high mRNAsi is associated with shortened overall survival. In Wilms tumors a high mRNAsi correlates with blastemal morphology, whereas tumors with predominant epithelial or stromal differentiation have a low mRNAsi and a high percentage of M2 type macrophages. This could be validated in Wilms tumor tissue (n = 78). Here, blastemal areas are low in M2 macrophage infiltrates, while nearby stromal differentiated areas contain abundant M2 macrophages, suggesting local microanatomic regulation of the immune response.

Macrophage frequency in the bone marrow correlates with morphologic subtype of myeloproliferative neoplasm.

Bone marrow (BM) fibrosis in myeloproliferative neoplasms (MPNs) is associated with a poor prognosis. The development of myelofibrosis and differentiation of mesenchymal stromal cells to profibrotic myofibroblasts depends on macrophages. Here, we compared macrophage frequencies in BM biopsies of MPN patients and controls (patients with non-neoplastic processes), including primary myelofibrosis (PMF, n = 18), essential thrombocythemia (ET, n = 14), polycythemia vera (PV, n = 12), and Philadelphia chromosome-positive chronic myeloid leukemia (CML, n = 9). In PMF, CD68-positive macrophages were greatly increased compared to CML (p = 0.017) and control BM (p < 0.001). Similar findings were observed by CD163 staining (PMF vs. CML: p = 0.017; PMF vs. control: p < 0.001). Moreover, CD68-positive macrophages were increased in PV compared with ET (p = 0.009) and reactive cases (p < 0.001). PMF had higher frequencies of macrophages than PV (CD68: p < 0.001; CD163: p < 0.001) and ET (CD68: p < 0.001; CD163: p < 0.001). CD163 and CD68 were often co-expressed in macrophages with stellate morphology in Philadelphia chromosome-negative MPN, resulting in a sponge-like reticular network that may be a key regulator of unbalanced hematopoiesis in the BM space and may explain differences in cellularity and clinical course.

High-Dimensional Analysis of Immune Cell Composition Predicts Periprosthetic Joint Infections and Dissects Its Pathophysiology.

Accurate diagnosis of periprosthetic joint infections (PJI) is one of the most widely researched areas in modern orthopedic endoprosthesis. However, our understanding of the immunological basis of this severe complication is still limited. In this study, we developed a flow cytometric approach to precisely characterize the immune cell composition in periprosthetic joints. Using high-dimensional multi-parametric data, we defined, for the first time, the local immune cell populations of artificial joints. We identified significant differences in the cellular distribution between infected and non-infected samples, and revealed that myeloid-derived suppressor cells (MDSCs) act as potential regulators of infiltrating immune cells in PJI. Further, we developed an algorithm to predict septic and aseptic samples with high sensitivity and specificity, that may serve as an indispensable addition to the current criteria of the Musculoskeletal Infection Society. This study describes a novel approach to flow cytometrically analyze the immune cell infiltrate of joint fluid that not only improves our understanding of the pathophysiology of PJI, but also enables the development of a novel screening tool to predict infection status. Our data further suggest that pharmacological targeting of MDSCs represents a novel strategy for addressing PJI.