The use of non-selective tumor necrosis factor (TNF) inhibitors is well known in the treatment of inflammatory diseases such as rheumatoid arthritis, Crohn’s disease, and psoriasis. Its use in neurological disorders is limited however, due to rare adverse events of demyelination, even in patients without preceding demyelinating disease. We review here the molecular and cellular aspects of this neuroinflammatory process in light of a case of severe monophasic demyelination caused by treatment with infliximab. Focusing on the role of TNF, we review the links between CNS inflammation, demyelination, and neurodegenerative changes leading to permanent neurological deficits in a young woman, and we discuss the growing evidence for selective soluble TNF inhibitors as a new treatment approach in inflammatory and neurological diseases. The use of tumor necrosis factor (TNF) blockers has revolutionized the treatment of a number of chronic inflammatory diseases such as Crohn’s disease, ankylosing spondylitis, psoriasis, and rheumatoid arthritis.Although TNF blockers are generally considered safe, an increasing number of neurologic adverse effects have been reported in the literature, consisting primarily of demyelination of the central nervous system (CNS) or peripheral nervous system (PNS) with a prevalence ranging from 0.050 to 0.100% .TNF is a pleiotropic cytokine known to play important regulatory roles in the development and homeostasis of the healthy CNS . It is pIn animal models of multiple sclerosis (MS), such as experimental autoimmune encephalomyelitis (EAE), the administration of TNF blockers slowed the demyelinating process and improved outcome ,9. AblatWe present here a case of severe demyelination following treatment with infliximab, a chimeric monoclonal antibody that prevents binding of TNF to TNFR1 and TNFR2 by blocking both solTNF and tmTNF . We discThe case is a 27-year-old woman with psoriatic arthritis, treated with methotrexate and infliximab. No family history of neurological disorders was reported.After 4.5 years of treatment with infliximab, she complained of increasing fatigue, muscle pain, and mild cognitive difficulties. After a few months, she developed a subacute hemiparesis. MRI scan showed a solitary process with gadolinium ring enhancement —Week 0.CSF analysis revealed no pleocytosis and normal protein levels, but did reveal oligoclonal bands and an elevated IgG index of 0.78. Initial blood tests showed a positive toxoplasmosis IgG, and PET-CT and a following biopsy from a single lymph node showed signs of granulomatous inflammation. The infliximab was discontinued, and the patient was initially treated for both toxoplasmosis and tuberculosis —Week 0.Further investigations revealed no pathology on repeated PET-CT, including no pathological lymph nodes.Repeated blood and CSF tests were found negative for toxoplasmosis, tuberculosis, varicella-zoster, Epstein–Barr, herpes simplex I+II, cytomegalovirus, Bartonella, Brucella, Aspergillus, hepatitis, and HIV. Microbiome PCR sequencing revealed no pathological DNA.Antinuclear antibodies (ANA), Extractable Nuclear Antigen antibodies (ENA), Proteinase 3 Anti Neutrophil Cytoplasmic Antibody (C-ANCA), and Perinuclear Anti Neutrophil Cytoplasmic Antibodies (P-ANCA) were all negative.Despite discontinuation of infliximab, the patient progressed clinically and radiologically over the next 12 weeks —Week 12.Repeated CSF analysis confirmed oligoclonal bands and elevated IgG index but no increase in cell count or protein. Cytology described normal-appearing lymphocytes without pathological changes. Flow cytometry revealed 74% T cells, 7.9% polyclonal B cells, 1.6% NK cells, and CD4/CD8 of 4.1.A biopsy was taken from the lesions in the brain, and histology showed unspecific reactive microglia and few infiltrating CD8+ T and B cells. There were no signs of tumor, lymphoma, vasculitis, progressive multifocal leukoencephalopathy, or infection with herpes, toxoplasmosis, or tuberculosis.The patient was treated with high-dose glucocorticoid intravenously (1 g a day for 5 days) followed by five courses of plasma exchange —Week 12.The following MRI showed remission, and the patient continued with a slight hemiparesis.After 2 years —Week 104We present a case of severe demyelination in a young woman who received infliximab as treatment for psoriatic arthritis. Because of the atypical presentation, many differential diagnoses were considered:As the patient had been on different types of immunosuppressants since her early childhood, and at the time her symptoms developed she was treated with both infliximab and methotrexate, an infectious cause was first suspected. This was supported by the first MRI, which showed a characteristic ring enhancement comparable to cerebral toxoplasmosis, and a positive IgA test for toxoplasmosis. To further complicate the matter, a biopsy from a neck gland showed granulomatous inflammation, which could suggest tuberculosis. However, later test results for tuberculosis were negative . Although the patient received treatment for both toxoplasmosis and tuberculosis, this had no effect on the intracranial process or her clinical status. Furthermore, the CSF showed no signs of pleocytosis or elevated protein, nor did it confirm toxoplasmosis, tuberculosis, or any other form of infection.Treatment with a TNF inhibitor has been suspected to increase the risk of certain malignancies, but this is still debated and may be related to the underlying autoimmune disease rather than the treatment ,19,20,21Studies suggest that patients with an autoimmune disease have an increased risk of developing other diseases with similar pathological mechanisms. Although still controversial, psoriasis has been shown to carry an increased risk of MS ,23,24. RA register-based study from 2019 found an increased risk of MS and neuroinflammatory disease in patients with psoriatic arthritis but not rheumatoid arthritis, both with and without treatment with non-selective TNF inhibitors . In viewIn this case, the patient remained stable without specific MS treatment, although Secukinumab was later introduced as an arthritis treatment and could in theory suppress any underlying MS activity. Secukinumab has been shown to be effective in MS , but it As previously mentioned, the use of non-selective TNF blockers has been linked to demyelinating diseases, including MS, optic neuritis, transverse myelitis, and demyelinating neuropathies ,28. FurtThe patient described here received infliximab for approximately 4.5 years before developing symptoms. In a 2017 review of reported cases of CNS demyelination associated with TNF inhibitors , the meaThe mechanisms behind the potential demyelinating role of non-selective TNF blockers are not completely clear. In general, TNF blockers are large molecules that do not penetrate the intact blood–brain barrier, possibly explaining the lack of positive effects in TNF-mediated CNS diseases as opposed to other autoimmune disease such as rheumatoid and psoriatic arthritis ,35. AnotThe infliximab used in this case blocks binding of TNF to TNFR1 and TNFR2 by blocking both solTNF and tmTNF , therefoThis case supports the growing evidence suggesting demyelinating events as adverse effects of non-selective TNF inhibitors, but distinguishes itself by the long follow-up time and the in-depth discussion of the underlying mechanisms using selective versus non-selective TNF inhibition. As demyelination is a rare adverse event and TNF blockers are generally considered safe and effective in many chronic autoimmune disorders, this should not preclude this treatment, but rather suggests caution in patients of high risk of developing demyelinating events. With the introduction of selective solTNF inhibitors and the growing evidence of their effect, this may form the basis of a new treatment approach in inflammatory and neurological diseases.


International attention on the environmental impacts of China’s Belt and Road Initiative (BRI) is increasing, but little is known internationally about the large corpus of Chinese BRI environmental research. We present the first systematic review of the Chinese and English-language BRI environmental research, supported with text mining and sentiment analysis. We found that the research is dominated by Chinese authors writing about BRI routes within China in Chinese, even though concerns around BRI are largely about impacts and benefits within host countries, and the volume of publications in English is recently catching up. Different disciplines and methods are well-represented across languages, apart from specific types of Chinese social science papers. The sentiments of academic research are largely neutral and less polarised than media discourse. We recommend that scientists and practitioners should pay more attention to BRI environmental impacts in developing countries and proactively engage local voices. China's multi-trillion dollar Belt and Road Initiative (BRI) is the largest infrastructure scheme in our lifetime, involving multilateral actors in constructing a network of infrastructure and economic cooperation corridors across Eurasia . It willSince the BRI’s announcement in 2013, research on BRI environmental issues has grown to encompass a plurality of disciplines and approaches. It is thus timely to present the first systematic review of Chinese and English-language BRI environmental research. This can provide a comprehensive picture of international and Chinese BRI research, and highlight possible differences and biases in the two corpuses. Monolingual systematic reviews can be systemically biased, such as when positive and significant results are reported only in English , 9. OtheSystematic reviews of scientific papers often use methods such as citation metrics and topic modelling which provide objective information , 12, butIn this paper, we present a systematic review of BRI environmental research published in both English and Chinese languages. We first examine the geographical characteristics of this research, including who and where the research is coming from, how much international collaboration there is, how it is funded, and the spatial coverage of the research. Secondly, we examine methods and content to characterise what is being researched. Thirdly, we examine how positive environmental researchers are about BRI, using sentiment analysis to compare languages and authors. To provide an independent measure of relative sentiment, we then compare the sentiments expressed in academic BRI environmental research with media coverage, as well as another contested environmental issue, oil palm . FinallyA search string capturing a broad range of environmental papers from various disciplines was formulated, consisting of the terms “ecology”, “environment”, “green”, and various permutations of BRI  was performed on the document term matrix constructed from the corpus using the ‘decorana’ function in the ‘vegan’ package  to derivFinally, sentiment analysis was conducted on the BRI and oil palm environmental papers and news articles to compare the sentiments expressed in academic BRI environmental research with media coverage and another contested environmental issue, oil palm. We used the ‘sentimentr’ package , which oResearch on BRI increased rapidly since 2013, but appears to be tapering off from 2018, especially for Chinese-language papers . SearchiMost (92%) of the first authors of both Chinese and English BRI environmental papers were based in Chinese institutions . Out of Most of the BRI environmental papers did not involve international collaborations. None of the Chinese-language papers had foreign-based co-authors; while 56% of English-language papers had authors based in China only, 18% were written by foreign-based authors in the same country, and 2% were collaborations between foreign-based co-authors in more than one country. Only 24% (35 papers) of English-language papers involved collaboration between authors based in China and overseas. 18 of those papers were collaborations only between co-authors in Western countries (Europe (excluding Russia), US, Canada, Australia and New Zealand), while 17 involved at least one co-author in a non-Western country.A larger proportion of the Chinese literature (47%) was funded; compared to the English literature (36%). All funded papers, except four, received funding from Chinese state-related entities of different levels–national research funds, state agencies, provinces, cities and universities . The proChinese portions of the route were addressed by a large proportion of papers in the Chinese corpus (39%) and English corpus (29%). Only 7% of Chinese papers were specific to a BRI route outside China, while 31% of English papers studied a BRI route outside China .A higher proportion of English papers (67%) used empirical methods than the Chinese literature (28%). There was also a stronger focus on the principles, rationale, and goals for a green BRI in the Chinese literature. Also, English-language papers displayed a lack of engagement with Chinese key BRI environmental policy documents, i.e. “The Belt and Road Ecological and Environmental Cooperation Plan”  and “GuiThe body of literature analysed encompassed different disciplines and themes Figs  and 4. GF = 1.1, p = 0.36). We then tested for differences in average sentiment between author countries, funding sources, and languages (among China-based authors) using independent two-sample t-tests. First authors with a Chinese affiliation were more positive  than authors with a foreign affiliation ; t(47) = 3.4, p < 0.01, power = 0.93  = 101, p < 0.01, power = 1; p ≤ 0.015); the five non-significantly different pairs were oil palm news against oil palm papers and BRI English news , as well as BRI English news against BRI English papers, oil palm papers and oil palm news , BRI environmental news articles , oil palm environmental academic papers , and oil palm news articles Click here for additional data file.S1 TextSupporting information including Appendices A and B and S1 and S2 Tables.(DOCX)Click here for additional data file.S1 Dataset(XLSX)Click here for additional data file.S2 Dataset(CSV)Click here for additional data file.


In this study, we aimed to explore the relationship between five selected proinflammatory and immune-mediated genes  and the risk and overall survival of DLBCL patients within the Jordanian Arab population. ® sequencer system (iPLEX GOLD) was used. The analyses included assessments of population variability and survival. One hundred twenty-five patients (125) diagnosed with DLBCL at the King Abdullah University Hospital (KAUH) between 2013 and 2018 and 238 healthy cancer-free control subjects with similar geographic and ethnic backgrounds to the patients were included in the study. Genomic DNA was extracted from the formalin-fixed paraffin-embedded tissues of the subjects and from peripheral blood samples of the controls. The Sequenom MassARRAYOur study showed significant differences in the distribution of the studied polymorphisms of DLBCL between the patients and controls for TNF rs1800629G>A, LTA rs909253 G>A and LEP rs2167270 G>A. TNF rs1800629G>A (p = 0.01), in which the G allele harbors a higher risk of DLBCL (GG and GA genotypes when compared with AA genotype) (p = 0.044). The LTA rs909253 A>G polymorphism is associated with a higher risk of DLBCL in the allelic model (p = .004). LEP rs2167270 G>A polymorphism is associated with a decreased risk of DLBCL in the recessive mode models (p = .03). Subjects with the dominant model for TNF-a rs1799964 (TT genotype in comparison with the combined TT/TC genotype) and patients with the homozygous genotype (GG) of rs361525 have better overall survival rates. Our results confirmed the diversity and the heterogeneity of the disease. Although the study has a limitation because of its relatively small size, it clearly emphasizes the significance of ancestry and genetic composition as the determinants of DLBCL risk and behavior. The World Health Organization’s (WHO) classification of hematolymphoid malignancies depends on a combination of morphologic, immunophenotypic, cytogenetic, and molecular findings. Accordingly, mature B-cell lymphomas are divided into Hodgkin and non-Hodgkin lymphoma types (HL and NHL). NHL is one of the most common hematologic malignancies with over 60 subtypes sharing the cell of origin but ranging in behavior from indolent to aggressive and very aggressive types. NHL is considered the sixth most common type of cancer and the ninth leading cause of cancer deaths among both males and females worldwide . The incidence of non-Hodgkin lymphoma (NHL) is increasing, and in the United States alone, approximately 81,080 new cases have been diagnosed in 2016. That comprises 89% of all new lymphoma cases. However, the trends of NHL incidence are variable and show significant age, gender, racial, and geographic differences . Generally, the overall incidence of NHL is higher in males, but females show greater extra-nodal involvement . Regarding geographic variation, developing countries show lower incidence but higher grade of B-cell lymphomas in comparison with developed countries . The surrounding environment, infectious microorganisms, and lifestyle all play an important role in NHL pathogenesis .Diffuse large B-cell lymphoma is the most common NHL . DLBCL is a diverse disease and can be classified into two genetically distinct types: the germinal center B-like type, characterized by the expression of germinal center B-cell genes, and the activated B-like type, characterized by the gene expression of activated peripheral blood B-cells. Clinically, the germinal center B-like type shows better overall survival . The standard chemotherapy regimen for patients with DLBCL is the CHOP regimen . Adding Rituximab  increases the rate of complete remission and overall survival in comparison with the CHOP regimen alone . Several studies reveal that different genetic loci are linked with risk and/or outcome in DLBCL. Among them, the most notable genes are the IL6, IL10, LEPR, CTLA-4, IL4RA, TNF-α, and LT-a immunity genes . There is strong proof that changes in immunological functions pose an increased risk of lymphoma. Inflammatory and immune-response genes are the inventive messengers of adaptive immunity; they regulate the function of the immune system and growth of the lymphoid tissues.In this study, we aimed to investigate the relationship between eight single nucleotide polymorphisms (SNPs) in five selected proinflammatory and immune-mediated genes  and the risk and overall survival of DLBCL patients in the Jordanian Arab population.Patients and data collectionOne hundred twenty-five (125) patients and two hundred and thirty-eight (238) healthy cancer-free control subjects with similar environmental and racial backgrounds to the patients were included in the study. All cases of DLBCL diagnosed from the beginning of 2013 to the end of 2018 were collected from the archives of pathology of King Abdullah University Hospital. All cases were reviewed by (SK) and one representative section was chosen from each case. All the procedures in the study was approved by the Scientific Research Committee and Institutional Review Board (IRB) at the Jordan University of Science and Technology  in accordance with the 1964 Declaration of Helsinki and its later amendments. For the patients; the need for formal written informed consent was waived by the IRB. All control subjects were voluntarily involved and signed written informed consent. Cases’ and controls’ names were coded and blinded and treated confidentially.DNA analysis® spectrophotometer. The pure DNA samples and their concentrations were sent to the Australian Genome Research Facility  for the genotyping of TNF , LTA (rs1800683G>A and rs909253A>G), TNFAIP8 (rs1042541C>T), LEPR (rs1327118G>C), and LEP (rs2167270G>A). Genotyping with the Sequenom MassARRAY® system (iPLEX GOLD)  was performed at the AGRF, as per the manufacturer’s recommendations . The SNPs, SNP positions, and primer sequences for the TNF-a, LTA, TNFAIP8, LEPR, and LEP genes are shown in Formalin-fixed paraffin-embedded tissues of the DLBCL patients were used to extract the genomic DNA using the commercially available DNeasy Blood and Tissue Kit , according to the manufacturer’s protocols. Peripheral blood samples were used to extract the genomic DNA of control healthy subjects using the QIAamp® or Promega DNA Mini Kit, in accordance with the manufacturer’s instructions. The quality of the extracted DNA was examined using agarose gel electrophoresis and ethidium bromide staining. The concentration and purity of the extracted DNA were assessed using a NanoDrop 1000Statistical analysisχ2 test. All the results were considered significant (P < 0.05). The follow-up period was calculated by subtracting the date of diagnosis from the date of death for the dead cases and by subtracting the date of diagnosis from the last updated date for the vital status of those patients who were alive until the last date of check-up. The actuarial life table survival analysis was used to obtain the overall survival probabilities. Cox’s proportional hazard regression was used to identify the independent factors related to survival. The survival analyses  were performed using the Statistical Package for the Social Sciences (SPSS), version 25.0 . The survival curves were displayed using the GraphPad Prism 6 software. The SNPStats Web Tool was used to analyze the distribution of genotypes in the patients and the associations between polymorphisms and clinical variables (independent variables), including gender, age, and response to treatment. The patients’ clinical characteristics and response rates were compared using Chi square tests. The Hardy–Weinberg equilibrium was estimated through a goodness-of-fit Demographic and Clinical DataAssociation between TNF, LTA, TNFAIP8, LEPR and LEP genes polymorphisms and the risk of DLBCLEight single nucleotide polymorphisms (SNPs) in four inflammation and immune-related genes  were genotyped in all the subjects (patients and controls). The genotype distributions of the patients and controls were compared. Unconditional logistic regression analysis was used to estimate the association between the genotype frequency and the risk of developing DLBCL. Additional analyses based on four genetic models  shows that LEP rs2167270 G>A polymorphism is associated with a decreased risk of DLBCL in the recessive mode models (p = 0.03). The results are shown in Association between TNF, LTA, TNFAIP8, LEPR and LEP genes polymorphisms and the survival rate of DLBCLAll the 125 DLBCL patients were included in the survival analysis. Survival analyses were performed using the Kaplan-Meier curve and log-rank test. The only SNPs to show significant survival results were TNF-a rs1799964 and TNF rs361525. In our study, subjects with the dominant model for TNF-a rs1799964 (TT genotype in comparison with the combined TT/TC genotype) and patients with the homozygous genotype (GG) of rs361525 have better overall survival- rates. Lymphomagenesis is a complex process involving an interaction between the tumor cells and the surrounding stromal cells or extracellular matrix . The tumor-microenvironment interaction is influenced by proinflammatory and immune-related factors that affect the proliferation and maturation of the interacting cells . There is increasing evidence that the genetic composition of the host (gene polymorphism) influences incidence variation and the outcomes of patients with a similar tumor stage and histological grade . Based on their ability to kill mouse fibrosarcoma L-929 cells, two cytotoxic factors were subsequently reported: the first was the lymphotoxin (LT) factor, which is produced by lymphocytes and was recognized by Gale A Garner in 1968 . And the second was the tumor necrosis factor (TNF), discovered in 1975 by LIoyd J. Old . The last exon is similar in both LT and TNF. Due to sequential homology in addition to functional homology, TNF was renamed as TNF-alpha, and LT was renamed as TNF-beta, they both belong to the TNF superfamily . TNF is a proinflammatory cytokine secreted mainly by macrophages and involved in the regulation of cell proliferation, differentiation, and programmed cell death . It also affects lipid metabolism, coagulation, and endothelial functioning .Tumor necrosis factor-alpha (TNF-a) is an acute phase reactant cytokine produced by many cells, including granulocytes, T-lymphocytes, and neurons, but mainly by macrophages. Its gene is located within the major histocompatibility complex (MHC) region of chromosome 6 (6p21.33), with biased expressions in the bone marrow and lymph nodes. As a functional protein, TNF-a has two forms: bound  and soluble. The soluble form is released from its original integral membrane or transmembrane (TP) form by a cleavage enzyme  called (ADAm17) .As an immune regulator, TNF-a is able to induce fever, cachexia, apoptosis, and inflammation. Additionally, it inhibits tumor genesis and viral replication. TNF binds to TNFR1, which is expressed by most cells, and activated by both the membrane-bound and soluble forms of TNF-a. However, TNFR2, which is primarily found in the immune system cells, is activated only by the membrane-bound form of TNF-a .Protein signaling in the TNF–TNFR1 interaction occurs through the tumor necrosis factor receptor type 1-associated DEATH domain protein (TRADD), a 34 kDa adaptor protein that interacts with an intracellular domain (death domain) of TNFR1 after its dissociation from the inhibitory protein, SODD. The overexpression of TRADD is responsible for two major roles of TNF: anti-apoptosis and inflammation by activating the NF-ΚB pathway . The inflammatory response of TNF is also induced by the inflammatory, pro-apoptotic MAPK pathway. The FADD/Caspase 8 pathway plays a minor role in the TNF induction of cell death .TNF is produced by the TNF gene cluster, which consists of three functional genes  . Sequencing the entire coding region of the TNF-a gene shows the presence of five single nucleotide polymorphisms (SNP)—four in the upstream region and one in the non-translated region. In the upstream region, and with respect to the TNF transcriptional start site, there are three SNPs characterized by the substitution of adenine for guanine at nucleotides -238 (rs361525), -308 (rs1800629), and -376 (rs1800750) . The first two SNPs (rs361525 and rs1800629) are found in the promoter region, and they lead to increased TNF expression. These SNPs have been implicated in a variety of diseases, including autoimmune diseases, diabetes, coronary heart diseases, and cancer . Additionally, the level of TNF-a is associated with poor prognosis and can expect treatment outcome in lymphoma patients . Among the most widely studied polymorphisms in TNF-a is -308G/A (rs1800629), in which the A allele is associated with an increase in transcriptional activity and the level of TNF-alpha. Reported studies from different institutions and geographic regions show no consistent relationships between -308G/A polymorphism and the risk of DLBCL. Both positive and negative associations have been reported between subjects of the same ethnicity and/or country of origin. For example, among American and Norway Caucasians, both Morton et al., (2008) and Yri et al., (2013) reported an increased risk of DLBCL with TNF -308G/A polymorphism . But Skibola et al., (2010) and Thunberg et al., (2010) found no such associations . Among Asians, the results are inconsistent; some studies indicate that TNF-a G308A polymorphism is significantly associated with an increased risk of DLBCL while others show negative associations . Our study among the Jordanian Arab population showed a positive association and an increased risk of DLBCL associated with TNF rs1800629G>A in the co-dominant, dominant, and recessive models . The conflicting results of different studies indicate that the genetic effect of TNF-a 308G/A polymorphism on NHL risk is ethnically and geographically dependent and may be partially explained by different allele frequencies among different populations .Among our notable findings, the rs1799964T>C SNP in the TNF-a gene was associated with better overall survival (OS) in DLBCL patients. Kaplan-Meier analyses of overall survival rates revealed that patients with a dominant genotype (TT genotype in comparison with combined TC/CC genotypes) of TNF rs1799964 had a higher overall survival rate (log-rank p = 0.028).Lymphotoxin-A (LTA), or tumor necrosis factor beta (TNF-b), acts as a modulator in the immune system; it is a key regulator in lipid metabolism, secreted by lymphocytes, and has 35% identity and 50% homology in the amino acid sequence of TNF-alpha . The genetic location of LTA is (6p21.33) and induces its functions through the TNF alpha receptor-1 (TNFRSF1A/TNFR1) and TNF beta receptor-2 (TNFRSF1B / TNFR2) .We found that lymphotoxin-a (LTA) 252A>G (rs909253) polymorphism was associated with an increased risk of DLBCL among our population (p = o.oo4), a result that is in concordance with previous reports in studies among the non-Hispanic white populations .The tumor necrosis factor-alpha-induced protein 8 (TNFAIP8) is a protein with 188 amino acids and a molecular mass of 21 kD, located on chromosome 5q23.1 . TNFAIP8 is an early anti-inflammatory cytokine and apoptosis regulator that negatively regulates T-cell receptor signaling, is involved in oncogenesis, and is found in many normal tissues and malignant cells. Its expression is induced by TNF-alpha through NF-KB pathway activation . Head and neck squamous cell carcinoma, esophageal squamous cell carcinoma, breast cancer, and non-small cell lung carcinoma show an increased expression of TNFAIP8 mRNA . However; the association between TNFAIP8 (rs1045241C>T) polymorphism and NHL, DLBCL in particular, is not well explored. In a study by Yan et al., (2012), the presence of TNFAIP8 (rs1045241C>T) polymorphism was significantly associated with the overall risk of DLBCL and follicular lymphoma (FL) among a Chinese population . In our study, no significant relationship was found between TNFAIP8 rs1045241 C>T polymorphism and the risk of DLBCL.Leptin, or the obese (OB) gene, is a 16-kD endocrine (adipocyte-derived) protein mapped to chromosome 7 (7q32.1) and has an important role in regulating appetite, basal body metabolism, body weight, insulin level, and inflammatory response . Leptin mediates its effects through a cytokine single transmembrane domain receptor called leptin receptor (LEPR). Accordingly, leptin and LEPR are associated with the pathogenesis of obesity, diabetes mellitus (DM), blood pressure, and cancers . Leptin gene expression is increased by sugar-rich diets and reduced by fasting. Polymorphisms in leptin (OB) and LEPR affect body weight homeostasis in different ways . LEP rs2167270 G>A polymorphism, which involves the untranslated 5-prime region of the gene and results in a single A-to-G transition in the 26th nucleotide, is associated with low leptin levels and morbid obesity . The obese phenotype is also associated with LEPR rs1137101 polymorphism, which results in the replacement of glutamine by arginine at codon 223 . However, the relationship between body mass index (BMI) and the risk of cancers, including hematologic malignancies, is not well established, and previous studies show inconsistent results . In their studies, Skibola et al., (2004) and Willett et al., (2005) found that the presence of A allele associated with LEP rs2167270 G>A polymorphism decreases the risk of NHL, but both LEP rs7799039 G>A and LEPR rs1137101 (Q223R) polymorphisms are associated with increased risk of NHL . These findings contradict the results of an Asian Chinese population study, in which no relationship was found between LEP rs2167270G>A and LEPR rs1327118C>G polymorphisms and risk of NHL . Our results showed no significant association between LEPR rs1327118 G>C polymorphism and the patient’s susceptibility to DLBCL. However, contrary to what was reported for the Chinese population, we found that LEP rs2167270 G>A polymorphism is associated with a decreased risk of DLBCL in the recessive mode models .


Antibodies targeting the SARS-CoV-2 spike receptor-binding domain (RBD) are being developed as therapeutics and make a major contribution to the neutralizing antibody response elicited by infection. Here, we describe a deep mutational scanning method to map how all amino-acid mutations in the RBD affect antibody binding, and apply this method to 10 human monoclonal antibodies. The escape mutations cluster on several surfaces of the RBD that broadly correspond to structurally defined antibody epitopes. However, even antibodies targeting the same RBD surface often have distinct escape mutations. The complete escape maps predict which mutations are selected during viral growth in the presence of single antibodies, and enable us to design escape-resistant antibody cocktails–including cocktails of antibodies that compete for binding to the same surface of the RBD but have different escape mutations. Therefore, complete escape-mutation maps enable rational design of antibody therapeutics and assessment of the antigenic consequences of viral evolution. The COVID-19 pandemic has generated urgent interest in antibody therapeutics and vaccines that induce antibodies to SARS-CoV-2. Many of the most potently neutralizing anti-SARS-CoV-2 antibodies target the receptor-binding domain (RBD) of the viral spike protein, often competing with its binding to the ACE2 receptor , 2020b. Determining which viral mutations escape from antibodies is crucial for designing therapeutics and vaccines and assessing the antigenic implications of viral evolution. Escape mutants can be selected by passaging virus expressing the SARS-CoV-2 spike protein in the presence of anti-RBD antibodies in the laboratory , and somHowever, current methods to identify SARS-CoV-2 escape mutations by passaging virus in the presence of antibodies are incomplete in the sense that they only find one or a few of the possible escape mutations. Structural biology can more comprehensively define how an antibody physically contacts the virus, but structures are time consuming to determine and still do not directly report which viral mutations escape from antibody binding .Here we overcome these limitations by developing a high-throughput approach to completely map mutations in the SARS-CoV-2 RBD that escape antibody binding, and apply this approach to 10 human antibodies. The resulting escape maps reveal the extent to which different antibodies are escaped by mutations at overlapping or orthogonal sites, and show that antibodies targeting structurally similar regions sometimes have escape mutations at entirely distinct residues. Furthermore, we show that the escape maps predict which mutations are selected when spike-expressing virus is passaged in the presence of neutralizing antibodies, and can inform the design of antibody cocktails that resist escape. Therefore, complete escape-mutation maps can be used to assess the antigenic consequences of viral genetic variation and the potential for viral escape from specific antibodies or antibody cocktails.To map antibody-escape mutations in a high-throughput manner, we leveraged a system for expressing conformationally-intact RBD on the surface of yeast cells . As descHere, we developed a method to use these libraries to comprehensively identify mutations in the RBD that allow it to escape binding by antibodies. To eliminate RBD mutants that were completely misfolded or unable to bind ACE2, we first used fluorescence-activated cell sorting (FACS) to eliminate RBD variants with <0.01x the affinity for ACE2 compared to that of the unmutated RBD ,B. We reWe applied our escape-mutation mapping to 10 human monoclonal antibodies: 9 neutralizing antibodies isolated from SARS-CoV-2 convalescent patients , and a rWe mapped escape mutations for each of the 10 antibodies in biological duplicate by applying the workflow in The effects of mutations on antibody escape are summarized in e.g., COV2–2082 is similar to COV2–2094, and COV2–2479 is similar to COV2–2050), antibodies that target the same broad region of the RBD often have distinct escape mutations . There is also heterogeneity in which specific amino acid mutations mediate escape. At some selected sites, many mutations confer escape . But at other sites, only certain mutations confer escape: for instance, only negatively-charged amino acids at site 408 escape COV2–2082, and only mutations at site 372 that introduce a serine or threonine (creating an N-linked glycosylation motif at site 370) escape COV2–2677.However, the escape-mutation maps are far more nuanced than can be represented by simply grouping the RBD into broad antigenic regions. While a few antibodies have extremely similar escape mutations  to obtain structures of five of the antibodies in complex with the RBD, and analyzed an existing structure of rCR3022 bound to RBD . To enabBoth the antibody-RBD structures and the escape maps highlight several antigenic regions on the RBD . The fire.g., COV-2050) are only sensitive to mutations at a handful of sites.However, the escape-mutation maps contain substantial information beyond what can be gleaned from structure alone. For example, COV2–2832 and COV2–2479 both target the ACE2-binding ridge, but have non-overlapping escape mutations on different faces of the ridge . SimilarThe fact that the escape mutations occur at only a subset of sites in the antibody-RBD interfaces is consistent with classical biochemical studies showing that protein-protein binding interfaces can be dominated by “hot spots” that contribute most of the binding energy , and morOur complete maps of escape mutations enable us to assess the potential for SARS-CoV-2 to evolve to escape antibodies targeting the RBD. We first examined whether the antibody-escape mutations identified in our study are present in viruses circulating in the human population. Of 93,858 SARS-CoV-2 sequences in the GISAID database as of September 6, 2020, there were 5 or more naturally occurring mutants at 14 of the 36 RBD sites where mutations escape at least one antibody . Howevere.g., mutations at site 435), whereas some escape mutations from the RBD-directed antibody COV2–2165 are deleterious for ACE2 binding . To quantify this trend, we determined the mean functional effect of all mutations at each site of escape from each antibody . To do this, we included in our libraries the unmutated RBDs from two close relatives of SARS-CoV-2 , and used a high-throughput quantitative real-time cell analysis assay  expressing the SARS-CoV-2 spike in place of the endogenous VSV glycoprotein (G) . Such viis assay , 2020b tis assay ,B,C. Foris assay . For oneis assay . We sequis assay .We next sought to understand why the antibodies selected the viral mutations that they did–and why it was not possible to select any viral mutants that escaped one of the antibodies. To do this, we considered two additional factors: which mutations are tolerated for protein function, and which mutations are accessible by single-nucleotide changes. We assessed how well mutations are tolerated functionally using deep mutational scanning measurements of how all RBD mutations affect ACE2 binding . We plotOne approach to thwart the risk of viral escape that is inherent in monotherapy approaches is to use antibody cocktails . In the e.g., the cocktail COV2–2499 + COV2–2050).We created three different two-antibody cocktails: one “conventional” cocktail of antibodies that did not compete for binding to spike protein (COV2–2499 + COV2–2094), and two cocktails of antibodies that competed for binding to the RBM region of the spike protein RBD but that our maps indicated were escaped by distinct mutations (COV2–2479 + COV2–2165 and COV2–2499 + COV2–2050)  and S6D.We have described an approach to completely map mutations to the SARS-CoV-2 RBD that escape antibody binding. Unlike traditional selection experiments that only identify a handful of the possible escape mutations, our method completely maps mutations that escape antibody binding. These maps complement structure-based approaches that define the physical interface between an antibody and virus but do not directly measure how mutations affect antibody binding.The escape maps reveal remarkable nuance in which mutations escape individual antibodies. Our maps and corroborating structural data show that at a superficial level, the antibodies target just a few patches on the surface of the RBD that likely correspond to “antigenic regions” that have been defined using other approaches . HoweverWe also overlaid the escape maps with existing deep mutational scanning data on the functional consequences of mutations for the expression of properly folded RBD and its affinity for ACE2 . In geneRemarkably, combining the escape maps with these functional measurements predicts which mutations are selected when spike-expressing virus is grown in the presence of individual antibodies. The selected viral escape mutations are consistently those that have large effects on antibody escape but little negative impact on ACE2 binding and RBD folding, and are also accessible by single-nucleotide mutations. Furthermore, one of the antibodies was highly resistant to viral escape–and we showed this could be explained by the fact that the virus has no escape mutations from this antibody that are both tolerable for RBD function and accessible by single-nucleotide changes. Therefore, complete measurements of both the antigenic and functional consequences of viral mutations provide the phenotypic data necessary to assess both the likelihood of viral escape under antibody pressure and the specific mutations that arise when escape occurs.One immediate implication of our results is that counter to prevailing wisdom, antibody cocktails do not have to target distinct regions of the RBD in order to resist viral escape. Simple inspection of the escape maps reveals pairs of antibodies targeting the RBD’s ACE2-binding interface that share no common escape mutations, and so could be good candidates for therapeutic cocktails. Indeed, we combined our escape maps with selections on spike-expressing viruses to show that cocktails of antibodies that compete for binding to spike but have different escape mutations still resist viral escape. It is possible that such cocktails could even be preferable to cocktails of antibodies targeting distinct regions , since aOur results are also of utility for assessing if ongoing viral evolution is likely to be of antigenic consequence. The escape maps enable immediate assessment of whether mutations to the RBD alter antigenicity. At over a dozen of the sites of escape that we mapped for these antibodies, there is already low-level genetic variation among circulating SARS-CoV-2 strains. Furthermore, the high-throughput nature of our experimental approach should make it possible to rapidly generate similar maps for other monoclonal antibodies or polyclonal antibodies in sera, thereby providing quantitative experimental data that can be cross-referenced to mutations observed during genomic surveillance of circulating SARS-CoV-2 strains .It is important to note that our approach maps how mutations affect antibody binding to yeast-displayed RBD, which comes with two caveats. First, our approach can only map escape from antibodies that target epitopes entirely within the RBD, and will not identify mutations that mediate escape by altering the relative positioning of the RBD in the context of full spike protein . Second,Some viruses, such as measles, are antigenically stable such that immunity from an initial infection or vaccination typically provides life-long protection . Others,https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Crowe_antibodies/blob/master/results/supp_data/MAP_paper_antibodies_raw_data.csv)Raw data tables of single-mutation escape fractions, averaged across libraries (https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Crowe_antibodies/blob/master/results/escape_scores/escape_fracs.csv)Raw data table of single-mutation escape fractions, measurements for individual library replicates (GitHub: https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Crowe_antibodies/blob/master/results/counts/variant_counts.csv)Illumina sequencing counts for each barcode in each antibody escape bin (GitHub: https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Crowe_antibodies)The complete computational pipeline to analyze these data (GitHub: https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Crowe_antibodies/blob/master/results/summary/summary.md)A Markdown summary of the organization of analysis steps, with links to key data files and Markdown summaries of each step in the analysis pipeline All raw sequencing data are uploaded to the NCBI Short Read Archive . Duplicate mutant libraries were generated, and contain 3,804 of the 3,819 possible amino-acid mutations, with >95% present as single mutants. Each RBD variant was linked to a unique 16-nucleotide barcode sequence to facilitate downstream sequencing. The RBD mutant library also contained non-mutated sarbecovirus RBD homologs, RaTG13, Genbank MN996532; GD-Pangolin consensus from AY278741; WIV16, Genbank KT444582; and LYRa11, Genbank KF569996.The yeast-display RBD mutant libraries are identical to those previously described . BrieflyThe 9 human monoclonal antibodies isolated from SARS-CoV-2 convalescent patients were produced as described in 50 <150 ng/mL; dark gray, 150–1,000; light gray, 1,000–1:10,000; white, no detectable inhibition); SARS-CoV-1 spike binding via ELISA ; potency of ACE2 competition via ACE2-blocking ELISA ; and rCR3022 competition via ELISA .Properties of the ten antibodies represented in i.e., 1e-10 M ACE2)  . 15 millAntibody selection experiments were performed in biological duplicate using the independently generated mutant RBD libraries. One 9 OD unit aliquot of each ACE2+-enriched RBD library was thawed and grown overnight in 45 mL SD-CAA. Libraries were induced as described above. Induced cultures were washed and incubated with 400 ng/mL antibody for 1 h at room temperature with gentle agitation, followed by secondary labeling with 1:100 FITC-conjugated anti-Myc to label for RBD expression and 1:200 PE-conjugated goat anti-human-IgG (Jackson ImmunoResearch 109-115-098) to label for bound antibody. A flow cytometric selection gate was drawn to capture unmutated SARS-CoV-2 cells labeled at 1% the antibody concentration of the library samples . LibrariPlasmid samples were prepared from overnight cultures of antibody-escaped and 30 OD units (1.6e8 cfus) of pre-selection yeast populations (Zymoprep Yeast Plasmid Miniprep II). The 16-nucleotide barcode sequences identifying each RBD variant were amplified by PCR and prepared for Illumina sequencing exactly as described in https://jbloomlab.github.io/dms_variants/, version 0.8.2) to process the Illumina sequences into counts of each barcoded RBD variant in each condition using the barcode / RBD-variant look-up table described in https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Crowe_antibodies/blob/master/results/summary/count_variants.md.We computed escape fractions for each mutation from the counts in the Illumina deep sequencing of the 16-nucleotide barcodes as schematized in F is the total fraction of the library that escapes antibody binding , using the same Gaussian likelihood function as in https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Crowe_antibodies/blob/master/results/summary/scores_to_frac_escape.md.We next deconvolved the variant-level escape fractions into escape fraction estimates for individual mutations. To do this we used global epistasis models  as impleIn some places in this paper and in For certain visualizations or analyses, it was necessary to classify which sites mediated escape from each antibody. To do this, for each antibody we identified those sites where the total site escape was >10x the median across all sites, and was also at least 10% of the maximum total site escape for any site for that antibody. We found that this heuristic reliably separated sites of clear antibody escape from other sites. This approach was used to determine which sites to display in the logo plots, and which sites to include in the analysis of natural sequence variation.https://jbloomlab.github.io/dmslogo/, version 0.3.2) and in all cases the height of each letter indicates the escape fraction for that amino-acid mutation calculated as described above. In https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Crowe_antibodies/blob/master/results/summary/analyze_escape_profiles.md.The static logo plot visualizations of the escape maps in the paper figures were created using the dmslogo package  was colhttps://jbloomlab.github.io/SARS-CoV-2-RBD_MAP_Crowe_antibodies/. The logo plots in these escape maps can be colored according to the deep mutational scanning measurements of how mutations affect ACE2 binding or RBD expression as described above.We created interactive structure-based visualizations of the escape maps using dms-view  that arehttps://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Crowe_antibodies/blob/master/data/GISAID/gisaid_hcov-19_acknowledgement_table_2020_09_06.pdf).All 94,233 spike sequences on GISAID as of 6 September 2020 were downloaded and aligned via mafft . Sequenchttps://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Crowe_antibodies/blob/master/data/RBDs_aligned.fasta.Shannon entropy of each alignment position was calculated using z pi is the proportion of sequences with amino acid i. The effective number of amino acids at each position (Neff) was calculated as 2 h.To compute conservation of positions among sarbecoviruses, we used the RBD sequence set from https://www.addgene.org/158762/). Point mutations were introduced into the RBD of this plasmid via site-directed mutagenesis.For neutralization assays, we used spike pseudotyped lentiviral particles that were generated essentially as described in Pseudotyped lentiviral particles were generated as previously described . Virusesi.e., 0.52 to 33.3 μL of virus were ultimately added to each well). Approximately 70 h post-infection, viral entry was quantified Bright-Glo Luciferase Assay System  as described in The resulting viruses were titered as previously described . 293T-ACFor the neutralization assays, the ACE2–293T cells were plated as described above for viral titering. 24 h later, pseudotyped lentivirus supernatants were diluted 1:6 and incubated with antibodies across a concentration range for 1 h at 37 °C, at a final concentration of antibody between 0.366 and 6,000 ng/mL. 100 μL of the0020virus-antibody mixture then was added to cells.https://jbloomlab.github.io/neutcurve/) to calculate the inhibitory concentration 50% (IC50) of each antibody against each virus by fitting a Hill curve with the bottom fixed at 0 and the top fixed at 1. The IC50 fold change relative to unmutated RBD was calculated for each mutant for each antibody.At ~70 h post-infection, luciferase activity was measured as described above. Fraction infectivity of each antibody-containing well was calculated relative to a “no-antibody” well inoculated with the same initial viral supernatant (containing wildtype or mutant RBD) in the same row of the plate. We used the neutcurve package . Cells were stained with recombinant biotinylated ACE2  and serial dilutions of rCR3022 antibody for 1 h at room temperature, washed with FACS buffer, resuspended in a 1:200 dilution of PE-conjugated streptavidin  and APC-conjugated Goat Anti-Human IgG , and incubated on ice for 1 h. Cells were then washed twice in the FACS buffer and resuspended in PBS. rCR3022 antibody and ACE2-binding levels were determined via flow cytometry using a BD LSRFortessa X-50. 10,000 cells were analyzed at each rCR3022 concentration. Cells were gated to select for singleton events, ACE2 labeling was used to subset RBD+ cells and measure RBD expression, and rCR3022 labeling was measured within this RBD+ population. Compensation and gating was performed using FlowJo v10.7. EC50s were computed using the neutcurve package to fit four-parameter Hill curves (both baselines free) and the midpoint is reported as the EC50. The assays were performed on two separate days, and fold changes were computed relative to the unmutated (wildtype) RBD from that day.293T cells were seeded at 6e5 cells per well in a 6-well plate. After 24 h, duplicate wells were transfected with 1 μg HDM_Spike_RBD_B7–1 plasmids and 1 μg of Transfection Carrier DNA  using BioT reagent , according to manufacturer’s protocol. At 18 to 20 h post-transfection, cells were washed with phosphate buffered saline (PBS), dissociated from the plate with enzyme-free dissociation buffer , harvested by centrifugation at 1,200 × ecto) to structurally define the sites several antibodies recognized on the SARS-CoV-2 spike trimer (ecto protein was expressed in FreeStyle 293 cells (ThermoFisher) or Expi293 cells (ThermoFisher). Expressed S2P ecto protein was isolated by metal affinity chromatography on HisTrap Excel columns , followed by further purification on a StrepTrap HP column  and size-exclusion chromatography on TSKgel G4000SW XL (TOSOH). We also expressed a recently reported spike protein construct with 4 additional proline substitutions that enhance thermostability, yield, and structural homogeneity, here referred to as S6P ecto (ecto protein was expressed in FreeStyle293 cells and isolated on a StrepTrap HP column following the addition of BioLock Biotin Blocking Solution (IBA Lifesciences) to the culture supernatant.We previously used a prefusion-stabilized, trimeric spike ectodomain . Digestions were performed in 100 Mm sodium phosphate, 150 mM NaCl pH 7.2 (PBS) for ~16 h at ambient temperature. After digestion, the digestion mix was incubated with CaptureSelect Fc resin (Genovis) for 30 min at ambient temperature in PBS buffer to remove cleaved Fc and intact, undigested IgG. If needed, the Fab was buffer exchanged into Tris buffer by centrifugation with a Zeba spin column (Thermo Scientific).ecto or SARS-CoV-2 S6P ecto protein in complex with human Fabs, the proteins were incubated at a molar ratio of 4 Fab:3 spike monomer for ~1 h and approximately 3 μL of the sample at concentrations of about 10 to 15 μg/mL was applied to a glow discharged grid with continuous carbon film on 400 square mesh copper EM grids (Electron Microscopy Sciences). The grids were stained with 0.75% uranyl formate (UF) (For screening and imaging of negatively-stained (NS) SARS-CoV-2 S2P ate (UF) . Images ate (UF) . All ima− /Å 2. Image processing was performed using the cryoSPARC software package    and a Faecto protein at 4°C overnight. Plates were blocked with 2% BSA in DPBS containing 0.05% Tween-20 (DPBS-T) for 1 h. Purified unlabeled antibodies were diluted to 20 μg/mL in blocking buffer, added to the wells (20 μL/well) in triplicate, and incubated for 1 h at ambient temperature. SARS-CoV-2 antibodies were added to each of three wells with the respective antibody at 2.5 μg/mL in a 5 μL/well volume  without washing of unlabeled antibody and then incubated for 1 h at ambient temperature. Plates were washed, and bound antibodies were detected using HRP-conjugated avidin (Sigma) and TMB substrate. The signal obtained for binding of the biotin-labeled reference antibody in the presence of the unlabeled tested antibody was expressed as a percentage of the binding of the reference antibody alone after subtracting the background signal. Tested antibodies were considered competing if their presence reduced the reference antibody binding to less than 30 % of its maximal binding and non-competing if the signal was greater than 75%. A level of 30–75% was considered intermediate competition.For the competition experiments reported in The generation of a replication-competent vesicular stomatitis virus (VSV) expressing SARS-CoV-2 S protein that replaces VSV G protein (VSV-SARS-CoV-2) has been described previously . This viTo screen for escape mutations selected in the presence of individual antibodies or antibody cocktails, we used a real-time cell analysis assay (RTCA) and xCELLigence RTCA MP Analyzer (ACEA Biosciences Inc.) with modification of previously described assays . Fifty .To identify escape mutations present in spike protein-expressing VSV antibody-selected escape variants, the escape viruses isolated after RTCA escape screening were propagated in 6-well culture plates with confluent Vero E6 cells in the presence of 10 μg/mL of the corresponding antibody. Viral RNA was isolated using a QiAmp Viral RNA extraction kit (Qiagen) from aliquots of supernatant containing a suspension of the selected virus population. The spike protein gene cDNA was amplified with a SuperScript IV One-Step RT-PCR kit (ThermoFisher Scientific) using primers flanking the S gene. The amplified PCR product  was purified using SPRI magnetic beads (Beckman Coulter) at a 1:1 ratio and sequenced by the Sanger sequence technique using primers giving forward and reverse reads of the RBD.Supplement 11


Psoriasis is an immune-mediated chronic inflammatory skin disorder in which the dysregulation of immune cells plays an important role in its development. Tumor necrosis factor- (TNF-) TNFAIP3 in the pathogenesis of psoriasis and determined whether it is involved in the antipsoriatic effect of TNF-α antagonists.  We investigated the immune regulation of α antagonists were examined in a mouse imiquimod- (IMQ-) induced psoriasis-like dermatitis model. In the mouse model, TNFAIP3 mRNA expression was determined using RT-PCR. Serum levels of IL-17A, IL-23, IFN-γ, TNF-α, phosphorylated ERK1/2, p38, and JNK were measured using ELISA. The proportion of Th1 and Th17 cells in mouse spleens was analyzed using flow cytometry.  mRNA levels were evaluated in blood from patients with moderate-to-severe psoriasis. The effects of TNF-TNFAIP3 in the blood were significantly lower in patients with moderate and severe psoriasis (mean ± SD = 0.44 ± 0.25) compared with normal subjects (mean ± SD = 1.00 ± 0.82) (P < 0.01). In the mouse model, IMQ downregulated TNFAIP3 expression levels, which were increased after TNF-α antagonist treatment (P < 0.05). Serum levels of Th17 cytokines (IL-17A and IL-23) and Th1 cytokines (IFN-γ and TNF-α) were significantly higher in the IMQ and IMQ/rat IgG1 groups compared with the control group, and the application of TNF-α antagonists significantly decreased the levels of inflammatory cytokines (P < 0.01). Notably, phosphorylated p38 levels were increased in the IMQ and IMQ/rat IgG1 groups compared with the control group but were downregulated by treatment with TNF-α antagonists (P < 0.05). Th1 and Th17 cells were significantly increased in the IMQ group compared with the control group (P < 0.01).  mRNA expression levels of TNFAIP3 downregulation associated with Th1 and Th17 cell differentiation and p38 activation might contribute in part to the mechanism of immune dysfunction in psoriasis. TNF-α antagonists might partly exert their effects on psoriasis via this pathway. It affects about 2% of the population worldwide, but the rate varies according to region . The mol T cells . TherefoTNFAIP3) gene encodes the TNFAIP3 protein, also known as TNF-α-inducible zinc finger protein A20, a cytoplasmic zinc-finger protein that acts as a negative immunoregulatory protein under inflammatory states [TNFAIP3 in mice led to systemic inflammation under homeostatic conditions and the exacerbation of inflammatory skin disorders [TNFAIP3 mRNA expression levels in peripheral blood mononuclear cells (PBMCs) from patients with psoriasis were negatively correlated with disease severity in psoriasis vulgaris [κB signaling pathway [TNFAIP3 overexpression in keratinocytes significantly repressed inflammatory cytokines and chemokines [The tumor necrosis factor alpha-induced protein 3  patients with psoriasis area and severity index (PASI) ≥ 10, who attended the outpatient clinic at the Dermatology Department of Peking Union Medical College Hospital from April 2019 to July 2019. All patients had received no antipsoriatic treatment in the past 4 weeks before the study started. Patient exclusion criteria included pregnancy or the presence of autoimmune diseases or major systemic diseases. Patients diagnosed with erythrodermic psoriasis, pustular psoriasis, or psoriatic arthritis were also excluded from the study. Twenty-five healthy controls (HCs) matched for age and gender were enrolled as a control group. Written consent, clinical information, and blood samples were obtained from all subjects.BALB/c mice at 7–8 weeks of age  were purchased from Huafukang Company . All mice were kept under specific pathogen-free conditions with a 12 h light-dark cycle. They were provided with a standard laboratory diet and water.α Ab (clone #XT3.11) and control rat IgG1 were purchased from Bioxcell , and 5% imiquimod cream (Aldara) was purchased from 3M Pharmaceuticals (United Kingdom). IMQ-induced psoriasiform skin inflammation was induced in mice as described previously [n = 6–8 per group): control group, IMQ group, IMQ/rat IgG1 group, and IMQ/anti-TNF-α group. A daily topical dose of 62.5 mg of 5% imiquimod cream or control Vaseline was applied to the shaved dorsal skin of the mice for six consecutive days. Mice in the IMQ/rat IgG1 group and IMQ/anti-TNF-α group were intraperitoneally injected with 200 μg anti-TNF-α antibody or control rat IgG1 1 day before (day −1) and 3 days after the imiquimod treatment (day 3). Mice were humanely euthanized on day 7 followed by sample collection. The severity of mouse psoriasis-like skin lesions was evaluated using a modified human scoring system PASI. The modified PASI system includes measurements for erythema, scaling, and thickening. Three parameters were scored independently on a scale from 0 to 4 . The cumulative dermatitis score was used to determine the severity of inflammation. Skin samples from different groups were collected and fixed in 4% formalin for 48 h. Tissue samples were dehydrated and then embedded in paraffin. Paraffin sections (4 μm thickness) were stained with hematoxylin and eosin (H&E) for histopathology.Mouse anti-mouse TNFeviously . BrieflyBlood samples of humans and mice were diluted 1 : 1 with phosphate-buffered saline (PBS), and PBMCs were separated by density gradient centrifugation . Total RNA was extracted from PBMCs using TRIzol reagent  according to the manufacturer's instructions. RNA concentration and quality were measured by a NanoDrop spectrophotometer. Samples with an A260/A280 ratio between 1.8 and 2.0 were used for further study. Then, reverse transcription for cDNA was performed using the PrimeScript RT Master Mix .ΔΔCt− method. Each reaction was set up in at least duplicate wells.RT-PCR was performed using the StepOnePlus™ Real-Time PCR System  with SYBR Premix Ex Taq II (Takara Bio Inc.) in accordance with the instructions of the manufacturer. Primer sequences were as follows: human TNFAIP3 ; human GAPDH ; mouse TNFAIP3 ; and mouse GAPDH . Amplification reactions were performed using the following program: 95°C for 60 s followed by 40 cycles of 95°C for 30 s, 60°C for 30 s, and 72°C for 30 s, then a melting curve analysis from 60°C to 95°C. The relative TNFAIP3 expression level was normalized to GAPDH housekeeping mRNA transcripts using the 2γ, and TNF-α were measured by ELISA in accordance with the manufacturer's instructions . Phosphorylation levels of ERK1/2, p38 and JNK were measured by ELISA .Mouse serum was obtained by centrifugation at 1000 × g for 20 min at 4°C and was collected and stored at −80°C until analysis. The concentrations of IL-17A, IL-23, IFN-2 for 6 h. Then, cells were stained for cell surface and intracellular markers with the following conjugated monoclonal antibodies: FITC anti-mouse CD3 (cat# 100203), PerCP/Cyanine5.5 anti-mouse CD8a (cat# 100734), APC anti-mouse IFN-γ (cat# 505810), and PE anti-mouse IL-17A (cat# 506904). All antibodies were purchased from BioLegend. CD3+CD8a−IL-17A+ cells were identified as Th17 cells, and CD3+CD8a−IFN-γ+ cells were identified as Th1 cells. Cells were analyzed with a BD Accuri C6 instrument (BD Biosciences) and FlowJo software v10.Single-cell suspensions prepared from mouse spleens were incubated with a cell activation cocktail  at 37°C and 5% COt-test was used for differences between the two groups, and one-way analysis of variance (ANOVA) was used for the four groups. All statistical analyses were performed with SPSS 23.0 software, and a level of P < 0.05 was considered statistically significant.The results are presented as the mean ± SD. The two-tailed Student TNFAIP3 in psoriasis, we collected PBMCs from patients with psoriasis and healthy controls. The mRNA expressions of TNFAIP3 were measured by RT-PCR. The study included 23 moderate-to-severe psoriatic patients aged between 15 and 65 years (39.13 ± 14.56) and 25 healthy volunteers aged between 23 and 58 years (39.12 ± 10.03). The clinical characteristics of patients with psoriasis and healthy controls included in our study are summarized in TNFAIP3 mRNA expression in PBMCs was significantly lower in patients with psoriasis (mean ± SD = 0.44 ± 0.25) compared with normal subjects  and 3 days after imiquimod treatment (day 3) as shown in α group. As shown in P > 0.05). The PASI score was decreased in the IMQ/anti-TNF-α group on day 7 after IMQ treatment (mean ± SD = 6.5 ± 0.53 g) (α antibody treatment reduced the thickness of the epidermis layer (α antibody treatment suppressed IMQ-induced psoriasiform dermatitis.To further explore the role of  0.53 g) . Next, his layer . These dTNFAIP3 in the IMQ-induced psoriasis-like dermatitis model, we collected PBMCs from mice and detected TNFAIP3 mRNA expression by RT-PCR. The application of IMQ downregulated TNFAIP3 expression  (TNFAIP3 expression in the IMQ/anti-TNF-α group was upregulated after treatment with TNF-α antagonists.To investigate the role of  < 0.05) . Moreoveγ, IL-17A, IL-23, and TNF-α were measured by ELISA, and the results are summarized in γ and TNF-α) in the serum were significantly higher in the IMQ group and IMQ/rat IgG1 group compared with the control group (P < 0.01). The application of TNF-α antagonists significantly decreased the levels of inflammatory cytokines in the IMQ-induced psoriasis-like dermatitis model.Serum levels of IFN-α antagonists   . HoweverP < 0.01)  .TNFAIP3 expression was decreased in the PBMCs of psoriatic patients and confirmed its role in association with Th1 and Th17 cell differentiation and p38 activation in psoriasis using the IMQ-induced psoriasis-like dermatitis model. Furthermore, TNF-α antagonist treatment alleviated skin inflammation caused by imiquimod application.In this study, we found that γ, and TNF-α, are also involved in the inflammatory process of psoriasis [TNFAIP3 had an important effect in several inflammatory diseases, such as systemic lupus erythematosus, inflammatory bowel disease, coeliac disease, and psoriasis [TNFAIP3 polymorphisms were associated with susceptibility to psoriasis [TNFAIP3 mRNA was expressed at low levels in psoriatic patients and the IMQ-induced psoriasis-like dermatitis model and that TNF-α antagonists increased TNFAIP3 expression and attenuated the severity of psoriasis in the mouse model. This finding was in accordance with the findings of Sahlol et al., who reported reduced TNFAIP3 expression in psoriatic skin and blood of patients with psoriasis [α in psoriatic skin and a feedback mechanism involving the NF-κB pathway [α antagonists might be mediated by TNFAIP3 regulation.Psoriasis is a chronic T cell-mediated inflammatory skin disease. Previous studies reported that Th1 and Th17 cells have critical roles in the pathogenesis of psoriasis . Inflammsoriasis . Previousoriasis . Here, wsoriasis . However pathway . FurtherTNFAIP3 mRNA expression. Of note, cytokine expression decreased after treatment with TNF-α antagonists. Similarly, other studies reported that the severity of skin inflammation in epidermis-specific TNFAIP3-knockout mice was exacerbated and associated with the upregulation of proinflammatory cytokines and chemokines [TNFAIP3 deficiency by siRNA silencing or in knockout cells led to enhanced IL-17-dependent inflammatory gene expression, which indicates that TNFAIP3 might be an inhibitor of IL-17 signaling [TNFAIP3 expression in psoriasis might be associated with the increase in Th1 and Th17 cell numbers and their related cytokines. These results suggest a new mechanism involved in immune dysfunction in psoriasis. However, in addition to Th1 and Th17 cells, many other immune cells, such as dendritic cells and macrophages, participate in psoriasis development. Therefore, whether TNFAIP3 regulates other immune cells and cytokines requires further research.Our results showed that numbers of Th1 and Th17 cells and their related inflammatory cytokines were increased under psoriatic inflammation, which were associated with the decreased ignaling . TherefoTNFAIP3 as a regulator of the NF-κB pathway, there is evidence that TNFAIP3 is also an important regulator of other immune pathways including MAPK signaling [+ T cells in an allergic encephalomyelitis model [α therapy. Our data suggest that p38, but not ERK1/2 and JNK, was phosphorylated after mice were treated with IMQ. Furthermore, pretreatment with anti-TNF-α therapy significantly inhibited the activation of p38. Therefore, it is not surprising that TNFAIP3 downregulation is accompanied by p38 MAPK activation under psoriatic inflammation.In addition to the function of ignaling . Garg etignaling . Additiois model . Furtheris model . To furtα antagonists have high efficacy for the treatment of psoriasis by inhibiting the inflammation cascade triggered by TNF-α [γ, TNF-α, and IL-17A [α antagonists remain unclear. Our data support the idea that TNF-α antagonists attenuate skin inflammation and increase TNFAIP3 expression accompanied by the downregulation of Th1- and Th17-related cytokines and phosphorylated p38 levels. Therefore, TNF-α antagonists might exert effects on psoriasis via this pathway.It was previously demonstrated that TNF-by TNF-α . StudiesTNFAIP3 expression was downregulated in psoriasis, which might be associated with Th1 and Th17 cell differentiation and p38 activation. Furthermore, the anti-inflammatory effect of anti-TNF-α therapy involved this pathway. These results demonstrate that TNFAIP3 might be a potential new target in the research of immune dysfunction in psoriasis. Future studies should focus on the precise mechanism by which TNFAIP3 regulates the interaction between inflammatory cytokines and other immune cells.In summary,


Kd), kinetics, and higher order stoichiometries, thus providing essential information on the TNF-α–adalimumab binding mechanism. Furthermore, it is shown that the avidity stabilized complexes involving formation of multiple non-covalent bonds are formed on a longer timescale than the primary complexes formed in a simple 1 to 1 binding event.The understanding and characterization of protein interactions is crucial for elucidation of complicated biomolecular processes as well as for the development of new biopharmaceutical therapies. Often, protein interactions involve multiple binding, avidity, oligomerization, and are dependent on the local environment. Current analytical methodologies are unable to provide a detailed mechanistic characterization considering all these parameters, since they often rely on surface immobilization, cannot measure under biorelevant conditions, or do not feature a structurally-related readout for indicating formation of multiple bound species. In this work, we report the use of flow induced dispersion analysis (FIDA) for in-solution characterization of complex protein interactions under in vivo like conditions. FIDA is an immobilization-free ligand binding methodology employing Taylor dispersion analysis for measuring the hydrodynamic radius (size) of biomolecular complexes. Here, the FIDA technology is utilized for a size-based characterization of the interaction between TNF-α and adalimumab. We report concentration-dependent complex sizes, binding affinities ( Hence, appropriate analytical methodologies are required in order to comprehensively characterize and quantify these interactions7. This is often achieved via functional assays such as ligand binding assays (LBA) and cell-based assays, that serve as an important surrogate of the anticipated biological mechanism in patients7. Ligand binding technologies are capable of reporting apparent binding affinities, but most methods lack a detailed deconvolution on the structural mode of action8. Often the relevant interactions involve higher order stoichiometries driven by avidity and oligomerization; rarely a simple 1:1 binding model provides a full picture of the underlying biology10. For example, the oligomeric state of a protein may determine whether it is pathological or not, as seen with tumor necrosis alpha (TNF-α) where the TNF-α monomer and trimer are inactive and active inflammatory cytokines, respectively11. It is therefore often necessary to combine LBAs with structural methods  to get the full picture7. However, structural methodologies require relatively clean samples, which may not reflect true in-vivo conditions12. Ideally, functional assays should report an absolute measure of affinity in combination with structural information under biorelevant conditions.The elucidation of biomolecular interactions is key to understanding physiological processes on a molecular level as well as for developing novel pharmaceutical therapiesKd), complex hydrodynamic radius, analyte quantification, and physical stability17. The FIDA principle relies on Taylor dispersion analysis (TDA) for measuring the apparent hydrodynamic radius (size) of a selective ligand (the indicator) as it binds to the analyte  of interest13. The apparent size of the indicator is measured in a titration series with varying analyte concentrations. The resulting binding curve is used for determining the binding affinity (Kd) and complex size. FIDA is highly tolerant to analysis in complex and crude sample matrices, such as plasma and fermentation broth18, and the absolute size readout provides information on structural features of the formed complex as well as avidity stabilization of multiple bound species.Flow Induced Dispersion Analysis (FIDA) is a novel analytical platform for size-based characterization of biomolecules including assessment of binding affinity , bio-layer interferometry (BLI), isothermal titration calorimetry (ITC), electron microscopy (EM), dynamic light scattering (DLS), analytical ultracentrifugation and HPLC-based procedures24. However, under physiological conditions TNF-α is a trimer with up to 3 binding sites and adalimumab has two binding sites which may make characterization of the TNF-α–adalimumab interaction challenging. In particular, surface-based methodologies lack the possibility of easily controlling the concentrations of both binding partners, which complicates quantitative assessment of avidity effects. For instance, the TNF-α–adalimumab interaction was recently characterized using hydrodynamic friction measurements25, which confirmed strong avidity effects and the presence of higher order complexes. Most of the existing studies of the TNF-α–adalimumab system have been primarily conducted in neat buffer solutions, hence, little is known on TNF-α–adalimumab interactions under native (in-solution) and biorelevant conditions . Krayukhina et al. recently utilized analytical ultracentrifugation (AUC) employing fluorescence detection to assess different binding stoichiometries of TNF-α and adalimumab in buffer and human serum22. While AUC remains an important methodology, throughput and sample volume requirements limits its broad applicability.Adalimumab is a recombinant monoclonal IgG antibody, frequently used in the treatment of auto-immune diseases such as rheumatoid arthritis and Crohn’s diseaseKd) and avidity stabilized complexes, size of the formed complexes, stoichiometry modeling, and qualitative assessment of the kinetics involved in formation of lower and higher order complexes.In this work, we have developed FIDA assays for size-based characterization of the interaction between trimeric TNF-α and adalimumab in buffer as well as human plasma. The assays were based on TNF-α as the indicator (ligand); hence, the apparent size change of TNF-α was measured in the presence of varying adalimumab concentrations. We report the in-solution binding affinity , stoichiometry, and complex size.Characterization of biomolecular interactions using FIDA is based on an indicator molecule, TNF-α, selectively interacting with the analyte of interest, adalimumab. Initially, the hydrodynamic radius (size) of TNF-α is measured in the absence of adalimumab, thus the size of unbound TNF-α is measured confirming the structural integrity of the molecule. As the concentration of adalimumab is increased, the apparent size of TNF-α increases due to a higher degree of binding. Full details on how to attain the hydrodynamic radius of the indicator from the raw data, i.e. Taylorgrams, has been described elsewhere20, and Daub et al. found the structure of TNF-α as trimeric at 100 nM (pH 7.4) using hydrodynamic friction measurements25. The determined hydrodynamic radius of adalimumab was consistent with previous TDA measurements (5.6–5.9 nm)26.The hydrodynamic radii of unbound TNF-α-alexa488 (100 nM) and adalimumab (1 mg/mL) were determined by TDA to 3.20 ± 0.04 nm and 5.6 ± 0.24 nm, respectively. The size of TNF-α confirmed the expected oligomeric state as trimeric at physiological pH 7.4. Kohno et al. reported a hydrodynamic radius of 3.1 nm for the trimer using SEC-LC at the same pHThree different incubation and mixing modes were used see Fig. : (1) Pre23. The concentrations and formation of higher order complexes are heavily governed by the absolute and relative concentrations of the interacting species. Thus, at excess adalimumab concentrations  was measured throughout an adalimumab titration series (0–1000 nM) in assay buffer containing 0.1% v/v HSA, which was added in order to minimize surface adsorption of TNF-α to glass vials and pipette tips. The apparent size of TNF-α increased with increasing adalimumab concentrations resulting in a binding curve Fig. . The incKd of 1.52 nM and complex size of 8.9 nm (R2: 0.992).The simple 1:1 excess binding model [Eq. ] appeareCollectively, these results confirmed the oligomeric state of TNF-α-alexa488 as trimeric from the size measurement of unbound TNF-α as well as its ability to form higher order complexes with adalimumab. The size measurements and binding isotherm provide some information on the structural features of the complexes being formed, however, the results clearly indicate that a more advanced binding model is needed to further quantify the formation of higher order complexes, as well as taking avidity effects into account. For systems where no prior knowledge on the complex stoichiometry is available, it may be necessary to include orthogonal techniques.23. On this basis, we set out to derive an extended binding model to describe the data set in Fig. A range of different TNF-α–adalimumab stoichiometries, e.g., 1:1, 1:2, 2:1, 2:2, 3:2, has been reported2 and (TA)2. Additional higher order structures, such as T2A3 and TA3, have also been reported23, but were not taken into account here because the used concentrations of TNF-α and adalimumab would most likely not favor these complexes. The binding scheme listed above can be simulated leading to estimates of the six Kd’s, as shown in the Supplementary Information. It is assumed that Kd values in Table The formation of a 2:2  complex , as expected from the experimental data 2 complex is dominating at intermediary adalimumab concentrations  when the TNF-α concentration is relatively high. However, when the simulation is performed using a TNF-α concentration corresponding to normal blood levels (0.22 pM), only a negligible fraction is bound in the (TA)2 complex. In case of inflammation, the TNF-α level may be significantly elevated thus resulting in increased formation of (TA)2. The formation of TA2 is shown at different TNF-α concentrations in Fig. Figure 28.The fractions of the complexes are strongly dependent on both the relative and absolute concentrations of TNF-α and adalimumab. The concentrations of complex-bound and free adalimumab as well as the ability to address binding stoichiometry provides important new information on the TNF-α–adalimumab system. The nature and the amounts of the complexes formed is not only of importance for characterizing the mode of action on a molecular level, but it may also provide information on possible adverse effects. For instance, it is speculated that some of the formed complexes are particularly prone to immunogenic responses in the patientsKd does not provide a satisfactory description of the interaction and might be subject to large variations even upon small perturbations of the experimental conditions. Indeed, several techniques have been used to study the interaction between TNF-α and adalimumab. Krayukhina et al. used ITC (Kd = 2.2 nM22) at pH 7.4 and 25 °C. In comparison, surface based methods resulted in lower Kd values at similar pH and temperature: SPR , BLI (0.005 nM24), and HP-SEC (0.24 nM10). Most of the Kd values reported in the literature assumes a 1:1 interaction, however, our results show that a strong avidity effect is needed to explain the sub-nanomolar Kd values observed with many surface binding technologies. The large variation reported in surface based Kd values could be a result of subtle differences in surface coverage and orientation of immobilized TNF-α/adalimumab at the surface, where small differences result in a substantial impact on the observed Kd, since certain experimental conditions promote strong avidity effects. For binding systems composed of several active subunits (oligomers) it is therefore advisable to use orthogonal in-solution technologies to confirm or elucidate binding mechanisms and the associated Kd values.The fact that the TNF-α–adalimumab interactions results in several complexes being formed, also means that a simple 1:1 29, where binding kinetics are not probed. The experimental time frame can be precisely controlled in FIDA assays using an approach where the binding partners are mixed directly in the capillary30  of 1.75 nM and complex size of 8.3 nm (R2: 0.998). These findings were analogous to the results using the pre-incubated samples  was not observed at equivalent concentrations  relative to the mobilization time inside the capillary, whereas the avidity stabilized (TA)2 displays significantly slower dissociation kinetics as expected from SPR10 and hydrodynamic friction measurements25. According to Fig. 2 is observed at an adalimumab concentration around 100 nM, close to the sharp maximum at 70–80 nM adalimumab in Fig. 2. Thus, the capillary dilution most likely shifts the equilibrium towards the avidity stabilized (TA)2 complex. Taken together, these results highlight the importance of considering the dilution effect of the analyte , for systems where the binding kinetics occurs on a timescale similar to the experiment.Again, the apparent hydrodynamic radius of TNF-α increased with increasing adalimumab concentrations and reached a plateau value around 8.5–9.0 nm Fig. . However19, corresponding to 5.4 and 10.8 nM in 10 and 20% v/v plasma, respectively (see Supplementary Information). The dynamic range of the binding curve in Fig. 31 is several orders of magnitude below the indicator concentration of 100 nM, and thus not expected to interfere with the FIDA assay (see Supplementary Information).The TNF-α–adalimumab interactions were further characterized in human plasma since this allows for the assessment of the complex formation under physiological relevant conditions. Binding between TNF-α (100 nM) and adalimumab (0–1000 nM) was investigated in human plasma from healthy donors diluted to 10 and 20% v/v plasma with assay buffer. These plasma concentrations were based on the expected steady-state concentrations of adalimumab in patients receiving adalimumab treatment with 40 mg every other weekThe hydrodynamic radius of TNF-α, in absence of adalimumab (0 nM), was determined to be 3.3 ± 0.16 nm and 3.6 ± 0.32 nm in 10 and 20% v/v plasma, respectively, implying only very limited binding of TNF-α to plasma components when comparing with 3.20 ± 0.04 nm in neat assay buffer.The binding curves Fig.  showed aKd values of 1.01 and 1.73 nM, and complex sizes of 9.7 and 8.7 nm in 10 and 20% v/v plasma, respectively. Overall, these findings are in line with the apparent values in assay buffer . The minor differences observed in complex size as function of adalimumab concentration emphasize that attention must be drawn to performing interaction and characterization assays under physiological relevant conditions, as they might differ from experiments performed in simple buffer systems.The 1:1 excess binding model [Eq. ] resulteKd) and complex sizes as well as confirming the oligomeric state of TNF-α. We found that the interaction involved generation of higher order complexes and substantial avidity effects. Therefore, the binding mechanism was modelled and simulated, demonstrating that the formation of higher order complexes highly depends on absolute and relative TNF-α and adalimumab concentrations. Furthermore, we performed an assessment of the binding kinetics, showing that smaller and lower order stoichiometries were rapidly formed whereas larger and higher order complexes required longer reaction time to form. Finally, the TNF-α–adalimumab interaction was measured in human plasma under physiological relevant conditions, implying similarities to the buffered model system, but also slight differences, thus stressing the importance of measuring in biological samples. The developed FIDA assays are applicable to measurement of both binding affinity and structural changes of biomolecular interactions under biorelevant conditions in a single assay format.The present work demonstrates the application of FIDA assays for size-based and in-solution characterization of the interaction between TNF-α and adalimumab in both phosphate buffer and human plasma. We selectively measured the hydrodynamic radius of TNF-α in a titration series experiment with adalimumab, thereby determining the dissociation constant (Recombinant human TNF-α (cat. no. ab155699) was procured from Abcam . Adalimumab from Amgen Europe B.V.  was bought from Nomeco . The human plasma was received from Rigshospitalet . The biofluids were collected as anonymous human biological material (for waste), according to the required guidelines by the Danish Ethical Committee system and Data Protection Agency . All methods were carried out in accordance with the Danish Ethical committee system and Data Protection Agency, including any required informed consent.Alexa Fluor 488 antibody labeling kit (cat. no. A20181) was purchased from Thermo Fisher . Human serum albumin (HSA) was purchased from Sigma-Aldrich . Disodium hydrogen phosphate dihydrate, and sodium dihydrogen phosphate monohydrate were purchased from Merck . Purified water (18.2 MΩ-cm at 25 °C) was obtained from an SG Ultraclear water purification system .Phosphate buffer  was prepared with purified water and filtered using a Q-max 0.45 µm nylon syringe filter  prior to use.32. The TNF-α-alexa488 conjugate concentration was determined using a microvolume spectrophotometer  applying the extinction coefficient of TNF-α  at 280 nm33 assuming trimeric TNF-α in phosphate buffer .TNF-α was labelled with the Alexa Fluor 488 antibody labeling kit via tetrafluorophenyl (TFP) ester coupling chemistry, and subsequently purified, following the supplier’s instructionsFIDA experiments were conducted using a Fida 1 instrument employing light-emitting-diode (LED) induced fluorescence detection with an excitation wavelength of 480 nm and emission wavelength > 515 nm . TDA experiments were performed using a Fida 1 instrument coupled to an intrinsic laser-induced-fluorescence (LIF) detector (ZETALIF evolution) with an excitation wavelength of 266 nm and emission wavelength of 300—760 nm .PEG-coated capillaries with inner diameter 75 µm, outer diameter 375 µm, total length 100 cm, and length to detection window 84 cm (Fida Biosystems) were used for all experiments.For the TDA and FIDA experiments, the following protocol was applied. First, assay buffer  was used for flushing and equilibrating the PEG-coated capillary at 1500 mbar for 300 s. Subsequently, the analyte solution was filled into the capillary at 1500 mbar for 45 s followed by the indicator sample at 50 mbar for 10 s. Finally, the indicator sample was mobilized to the fluorescence detector with analyte solution at 400 mbar for 180 s. The final mobilization step of the FIDA experiments conducted in plasma was set to 240 s at 400 mbar due to an increase in sample viscosity.The hydrodynamic radius of adalimumab (1 mg/mL) was measured in assay buffer by TDA employing intrinsic fluorescence detection.Binding curves were generated using FIDA in assay buffer containing human serum albumin 0.1% v/v) as surface passivation agent. The TNF-α-alexa488 (indicator) concentration was fixed to 100 nM or 10 nM and titrated with adalimumab  in the concentration range 0–1000 nM. The different mixing schemes are described in Fig. % v/v as Binding curves were generated using FIDA in 10 and 20% v/v human plasma diluted with assay buffer. The TNF-α-alexa488 concentration was fixed to 100 nM and titrated with adalimumab in the concentration range 0–1000 nM. TNF-α-alexa488 was pre-incubated with adalimumab in the sample vials for > 10 min to attain equilibrium before the FIDA measurements.14.The Taylorgrams were processed using the FIDA software suite, version 1.1 , in order to calculate the apparent hydrodynamic radius of TNF-α-alexa488 (indicator) at each adalimumab concentration . The Taylorgram fraction setting was set to 75% for all data points, and changes in sample viscosity were corrected according to a reference measurement at 25 °C, as previously described17:Rapp, RI, and RIA are the apparent, indicator and complex hydrodynamic radii, respectively, Kd is the dissociation constant, and CI and CA are the formal concentrations of the indicator and analyte, respectively.A binding isotherm, assuming 1:1 binding and excess of indicator, was used for fitting the obtained FIDA measurements, i.e., apparent hydrodynamic radius of TNF-α-alexa488 as function of adalimumab concentration using the FIDA softwareAn extended binding model for multiple and higher order stoichiometries is derived in the results and discussion paragraph as well as in the Supplementary Information.Supplementary information.