Dense deposit disease (DDD) is a severe renal disease characterized by accumulation of electron-dense material in the mesangium and glomerular basement membrane. Previously, DDD has been associated with deficiency of factor H (fH), a plasma regulator of the alternative pathway (AP) of complement activation, and studies in animal models have linked pathogenesis to the massive complement factor 3 (C3) activation caused by this deficiency. Here, we identified a unique DDD pedigree that associates disease with a mutation in the C3 gene. Mutant C3 923ΔDG , which lacks 2 amino acids, could not be cleaved to C3b by the AP C3-convertase and was therefore the predominant circulating C3 protein in the patients. However, upon activation to C3b by proteases, or to C3(H 2 O) by spontaneous thioester hydrolysis, C3 923ΔDG generated an active AP C3-convertase that was regulated normally by decay accelerating factor (DAF) but was resistant to decay by fH. Moreover, activated C3b 923ΔDG and C3(H 2 O) 923ΔDG were resistant to proteolysis by factor I (fI) in the presence of fH, but were efficiently inactivated in the presence of membrane cofactor protein (MCP). These characteristics cause a fluid phase-restricted AP dysregulation in the patients that continuously activated and consumed C3 produced by the normal C3 allele. These findings expose structural requirements in C3 that are critical for recognition of the substrate C3 by the AP C3-convertase and for the regulatory activities of fH, DAF, and MCP, all of which have implications for therapeutic developments. IntroductionComplement is a major component of innate immunity, with crucial roles in microbial killing, apoptotic cell clearance, immune complex handling, and modulation of adaptive immune responses. Complement is activated by 3 independent activation pathways: the classical pathway (CP), the lectin pathway (LP), and the alternative pathway (AP). The critical steps in complement activation are the formation of unstable protease complexes, named complement factor 3-convertases (C3-convertases; specifically, C3bBb for AP and C4b2a for CP and LP), and the cleavage of C3 by the convertases to generate C3b. Convertase-generated C3b can form more AP C3-convertase, providing exponential amplification to the initial activation. Binding of C3b to the C3-convertases generates the C5-convertases with the capacity to bind and cleave C5, initiating formation of the lytic membrane attack complex (MAC). In contrast to the CP and the LP, whose activation is triggered by immune complexes and bacterial mannose groups, respectively, the AP is intrinsically activated. Spontaneous activation of C3 in plasma occurs through the tick-over mecha-

Common polymorphisms in complement alternative pathway (AP) proteins C3 (C3 R102G ), factor B (fB R32Q ), and factor H (fH V62I ) are associated with age-related macular degeneration (AMD) and other pathologies. Our published work showed that fB R32Q influences C3 convertase formation, whereas fH V62I affects factor I cofactor activity. Here we show how C3 R102G

Vaccines derived from chimpanzee adenovirus Y25 (ChAdOx1), human adenovirus type 26 (HAdV-D26), and human adenovirus type 5 (HAdV-C5) are critical in combatting the severe acute respiratory coronavirus 2 (SARS-CoV-2) pandemic. As part of the largest vaccination campaign in history, ultrarare side effects not seen in phase 3 trials, including thrombosis with thrombocytopenia syndrome (TTS), a rare condition resembling heparin-induced thrombocytopenia (HIT), have been observed. This study demonstrates that all three adenoviruses deployed as vaccination vectors versus SARS-CoV-2 bind to platelet factor 4 (PF4), a protein implicated in the pathogenesis of HIT. We have determined the structure of the ChAdOx1 viral vector and used it in state-of-the-art computational simulations to demonstrate an electrostatic interaction mechanism with PF4, which was confirmed experimentally by surface plasmon resonance. These data confirm that PF4 is capable of forming stable complexes with clinically relevant adenoviruses, an important step in unraveling the mechanisms underlying TTS.

Complement is a key component of immune defence against infection; it potently drives inflammation at sites of pathology and is essential for killing of pathogens. Genetic linkage of common complement polymorphisms to disease has advanced the concept that subtle changes in complement activity significantly affect disease risk. Functional analyses of disease-linked polymorphic variants demonstrate that, although individual polymorphisms cause only small changes in activity, when combined, the aggregate effects are large. The inherited set of common variants, the complotype, thus has a major impact on susceptibility to inflammatory and infectious diseases. Assessing the complotype of an individual will aid prediction of disease risk and inform intervention to reduce or eliminate risk.

IMPORTANCE Biomarkers that are predictive of outcomes in individuals at risk of psychosis would facilitate individualized prognosis and stratification strategies. OBJECTIVE To investigate whether proteomic biomarkers may aid prediction of transition to psychotic disorder in the clinical high-risk (CHR) state and adolescent psychotic experiences (PEs) in the general population. DESIGN, SETTING, AND PARTICIPANTS This diagnostic study comprised 2 case-control studies nested within the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) and the Avon Longitudinal Study of Parents and Children (ALSPAC). EU-GEI is an international multisite prospective study of participants at CHR referred from local mental health services. ALSPAC is a United Kingdom-based general population birth cohort. Included were EU-GEI participants who met CHR criteria at baseline and ALSPAC participants who did not report PEs at age 12 years. Data were analyzed from September 2018 to April 2020. MAIN OUTCOMES AND MEASURES In EU-GEI, transition status was assessed by the Comprehensive Assessment of At-Risk Mental States or contact with clinical services. In ALSPAC, PEs at age 18 years were assessed using the Psychosis-Like Symptoms Interview. Proteomic data were obtained from mass spectrometry of baseline plasma samples in EU-GEI and plasma samples at age 12 years in ALSPAC. Support vector machine learning algorithms were used to develop predictive models. RESULTS The EU-GEI subsample (133 participants at CHR (mean [SD] age, 22.6 [4.5] years; 68 [51.1%] male) comprised 49 (36.8%) who developed psychosis and 84 (63.2%) who did not. A model based on baseline clinical and proteomic data demonstrated excellent performance for prediction of transition outcome (area under the receiver operating characteristic curve [AUC], 0.95; positive predictive value [PPV], 75.0%; and negative predictive value [NPV], 98.6%). Functional analysis of differentially expressed proteins implicated the complement and coagulation cascade. A model based on the 10 most predictive proteins accurately predicted transition status in training (AUC, 0.99; PPV, 76.9%; and NPV, 100%) and test (AUC, 0.92; PPV, 81.8%; and NPV, 96.8%) data. The ALSPAC subsample (121 participants from the general population with plasma samples available at age 12 years (61 [50.4%] male) comprised 55 participants (45.5%) with PEs at age 18 years and 61 (50.4%) without PEs at age 18 years. A model using proteomic data at age 12 years predicted PEs at age 18 years, with an AUC of 0.74 (PPV, 67.8%; and NPV, 75.8%). CONCLUSIONS AND RELEVANCE In individuals at risk of psychosis, proteomic biomarkers may contribute to individualized prognosis and stratification strategies. These findings implicate early dysregulation of the complement and coagulation cascade in the development of psychosis outcomes.