Serum FHR1 binding to necrotic-type cells activates monocytic inflammasome and marks necrotic sites in vasculopathies

Persistent inflammation is a hallmark of many human diseases, including anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV) and atherosclerosis. Here, we describe a dominant trigger of inflammation: human serum factor H-related protein FHR1. In vitro, this protein selectively binds to necrotic cells via its N-terminus; in addition, it binds near necrotic glomerular sites of AAV patients and necrotic areas in atherosclerotic plaques. FHR1, but not factor H, FHR2 or FHR3 strongly induces inflammasome NLRP3 in blood-derived human monocytes, which subsequently secrete IL-1β, TNFα, IL-18 and IL-6. FHR1 triggers the phospholipase C-pathway via the G-protein coupled receptor EMR2 independent of complement. Moreover, FHR1 concentrations of AAV patients negatively correlate with glomerular filtration rates and associate with the levels of inflammation and progressive disease. These data highlight an unexpected role for FHR1 during sterile inflammation, may explain why FHR1-deficiency protects against certain diseases, and identifies potential targets for treatment of auto-inflammatory diseases.

A full description of the statistics including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals) For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of freedom and P value noted Give P values as exact values whenever suitable.

For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings
For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes Estimates of effect sizes (e.g. Cohen's d, Pearson's r), indicating how they were calculated

Clearly defined error bars
State explicitly what error bars represent (e.g. SD, SE, CI) Our web collection on statistics for biologists may be useful.

Software and code
Policy information about availability of computer code Data collection sequencing data are available under GSEcode 119025 Data analysis PRISM Graphpad software was used to perform One-way ANOVA, Student's t test, Welch test and Wilcoxon Signed Rank Test, Spearman correlation test. Expression Suite Software version 1.1 and StepOne™ was used for analysis of qPCR and DAVID 6.7 and Panther 9.0 software for RNAseq analysis. ZEN software package was used for PLA quantification. ImageJ/ZEN software was used to analyze image data. Flowjo software for analysis of flow cytometry data.
For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors/reviewers upon request. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.

April 2018
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: All studies must disclose on these points even when the disclosure is negative.

Sample size
Patient samples were selected according to diagnosis of ANCA vasculitis and atherosclerosis with CVD upon ethical agreement.
Data exclusions No exclusion was made, except for sequencing data: Data were filtered prior to statistical analysis to remove genes with low expression or without significant changes between groups.

Replication
All attempts at replication were successful.
Randomization Participants were allocated into groups according diagnosis of disease Blinding Human samples were examined in a blinding and randomization way.

Behavioural & social sciences study design
All studies must disclose on these points even when the disclosure is negative.

Study description
Briefly describe the study type including whether data are quantitative, qualitative, or mixed-methods (e.g. qualitative cross-sectional, quantitative experimental, mixed-methods case study). Confirm that both raw and final processed data have been deposited in a public database such as GEO.

Research sample
Confirm that you have deposited or provided access to graph files (e.g. BED files) for the called peaks.

Data access links
May remain private before publication.

Files in database submission
Provide a list of all files available in the database submission.
Genome browser session (e.g. UCSC) Provide a link to an anonymized genome browser session for "Initial submission" and "Revised version" documents only, to enable peer review. Write "no longer applicable" for "Final submission" documents. The axis labels state the marker and fluorochrome used (e.g. CD4-FITC).

Methodology
The axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of identical markers).
All plots are contour plots with outliers or pseudocolor plots.
A numerical value for number of cells or percentage (with statistics) is provided.

Methodology
Sample preparation Tick this box to confirm that a figure exemplifying the gating strategy is provided in the Supplementary Information.

Magnetic resonance imaging
Experimental design