The New Zealand Community Fault Model (NZ CFM) is a publicly available representation of New Zealand fault zones that have the potential to produce damaging earthquakes. Compiled through collaborative engagement between New Zealand earthquake-science experts, this first edition (version 1.0) of the NZ CFM builds upon previous compilations of earthquake-source active fault models with the addition of new and modified information. Developed primarily to support an update of the New Zealand National Seismic Hazard Model, the NZ CFM comprises two principal components. The first dataset is a two-dimensional map representation of the surface traces of 880 generalised fault zones. Each fault zone is assigned specific geometric and kinematic attributes, including uncertainties, supplemented with a subjective quality ranking focused primarily on the confidence in assigned slip rates. The second component is a three-dimensional representation of the fault zones as triangulated mesh surfaces that are projected down-dip from the two-dimensional mapped traces to a geophysically-defined maximum fault rupture depth. This article summarises the compilation and parameterisation of the NZ CFM, along with background on its relation to predecessor datasets, and forward applications to probabilistic seismic hazard assessment and physics-based earthquake models currently being developed for Aotearoa New Zealand.

Background and Aims: Ritlecitinib, an oral JAK3/TEC family kinase inhibitor, was well-tolerated and efficacious in the phase 2b VIBRATO study in participants with moderate-to-severe ulcerative colitis [UC]. The aim of this study was to identify baseline serum and microbiome markers that predict subsequent clinical efficacy and to develop noninvasive serum signatures as potential real-time noninvasive surrogates of clinical efficacy after ritlecitinib.Methods: Tissue and peripheral blood proteomics, transcriptomics, and faecal metagenomics were performed on samples before and after 8 weeks of oral ritlecitinib induction therapy [20 mg, 70 mg, 200 mg, or placebo once daily, N = 39, 41, 33, and 18, respectively]. Linear mixed models were used to identify baseline and longitudinal protein markers associated with efficacy. The combined predictivity of these proteins was evaluated using a logistic model with permuted efficacy data. Differential expression of faecal metagenomics was used to differentiate responders and nonresponders.Results: Peripheral blood serum proteomics identified four baseline serum markers [LTA, CCL21, HLA-E, MEGF10] predictive of modified clinical remission [MR], endoscopic improvement [EI], histological remission [HR], and integrative score of tissue molecular improvement. In responders, 37 serum proteins significantly changed at Week 8 compared with baseline [false discovery rate of <0.05]; of these, changes in four [IL4R, TNFRSF4, SPINK4, and LAIR-1] predicted concurrent EI and HR responses. Faecal metagenomics analysis revealed baseline and treatment response signatures that correlated with EI, MR, and tissue molecular improvement.Conclusions: Blood and microbiome biomarkers stratify endoscopic, histological, and tissue molecular responses to ritlecitinib, which may help guide future precision medicine approaches to UC treatment. ClinicalTrials.gov NCT02958865

The specialized cell types of the mucociliary epithelium (MCE) lining the respiratory tract enable continuous airway clearing, with its defects leading to chronic respiratory diseases. The molecular mechanisms driving cell fate acquisition and temporal specialization during mucociliary epithelial development remain largely unknown. Here, we profile the developing Xenopus MCE from pluripotent to mature stages by single-cell transcriptomics, identifying multipotent early epithelial progenitors that execute multilineage cues before specializing into late-stage ionocytes and goblet and basal cells. Combining in silico lineage inference, in situ hybridization, and single-cell multiplexed RNA imaging, we capture the initial bifurcation into early epithelial and multiciliated progenitors and chart cell type emergence and fate progression into specialized cell types. Comparative analysis of nine airway atlases reveals an evolutionary conserved transcriptional module in ciliated cells, whereas secretory and basal types execute distinct function-specific programs across vertebrates. We uncover a continuous nonhierarchical model of MCE development alongside a data resource for understanding respiratory biology.

Supplementary Figure 1 from Genetically Lowered Microsomal Epoxide Hydrolase Activity and Tobacco-Related Cancer in 47,000 Individuals

Supplementary Table 2 from Genetically Lowered Microsomal Epoxide Hydrolase Activity and Tobacco-Related Cancer in 47,000 Individuals

The c. 15 km-long Ngapouri-Rotomahana Fault (NRF) is a major splay of the Paeroa Fault at the eastern margin of the modern Taupo over bar Rift, the active tectonic structure embedded within the Taupo over bar Volcanic Zone of North Island, New Zealand. The NRF and Paeroa Fault extend to the southern margin of the Okataina Volcanic Centre (OVC) and lie southwest of the Tarawera vent lineation, which is the source of approximately half of the eruptions of the OVC in the past 25 cal. ka BP. Here, we explore volcano-tectonic relationships between the OVC and the NRF and Paeroa Fault. Collective evidence used in our analysis includes: volcanic processes interpreted as occurring during the historic 1886 Tarawera (basalt) and the prehistoric 1314 +/- 12 CE Kaharoa (basalt triggered rhyolite) eruptions, both on the Tarawera vent lineation; exposures in five trenches excavated across the NRF and seven trenches across the Paeroa Fault; data on a series of explosion craters formed to the southwest of the volcano associated with the -1314 CE Kaharoa eruption and the Rotoma rhyolite (-9.4 cal. ka BP) eruption from the OVC; and mafic dykes that primed several of the OVC eruptions. Data from the twelve trenches on the two faults reveal eight surface fault ruptures since 15.6 cal. ka BP, with most closely coinciding with volcanic eruptions, providing a first-order indication of probable causality. Three principal modes of interaction are identified. Firstly, large displacement events on the Paeroa fault, arguably immediately prior to the Mamaku and Rotoma rhyolite eruptions (-7.9 and -9.4. cal. ka BP, respectively) and on the NRF immediately prior to the -1314 CE Kaharoa eruption are candidates for earthquake static or dynamic stress triggers for those explosive eruptive events. Secondly, basalt dyke intrusion was also involved in the initiation of the Kaharoa eruption, so the spatial and temporal relationships between dyke intrusion, smaller displacement fault ruptures and initiation of the Kaharoa eruption appear closely connected. Thirdly, faulting events that are interpreted as co- or posteruption may be the result of stress triggers associated with magma chamber deflation.

The aim of this study is to characterize cell type-specific transcriptional signatures in non-alcoholic steatohepatitis (NASH) to improve our understanding of the disease. We performed single-cell RNA sequencing on liver biopsies from 10 patients with NASH. We applied weighted gene co-expression network analysis and validated our findings using a publicly available RNA sequencing data set derived from 160 patients with non-alcoholic fatty liver disease (NAFLD) and 24 controls with normal liver histology. Our study provides a comprehensive single-cell analysis of NASH pathology in humans, describing 19,627 single-cell transcriptomes from biopsy-proven NASH patients. Our data suggest that the previous notion of "NASH-associated macrophages" can be explained by an up-regulation of normally existing subpopulations of liver macrophages. Similarly, we describe two distinct populations of activated hepatic stellate cells, associated with the level of fibrosis. Finally, we find that the expression of several circulating markers of NAFLD are co-regulated in hepatocytes together with predicted effector genes from NAFLD genome-wide association studies (GWAS), coupled to abnormalities in the complement system. In sum, our single-cell transcriptomic data set provides insights into novel cell type-specific and general biological processes associated with inflammation and fibrosis, emphasizing the importance of studying cell type-specific biological processes in human NASH.

Stellate cells are principal neurons in the entorhinal cortex that contribute to spatial processing. They also play a role in the context of Alzheimer’s disease as they accumulate Amyloid beta early in the disease. Producing human stellate cells from pluripotent stem cells would allow researchers to study early mechanisms of Alzheimer’s disease, however, no protocols currently exist for producing such cells. In order to develop novel stem cell protocols, we characterize at high resolution the development of the porcine medial entorhinal cortex by tracing neuronal and glial subtypes from mid-gestation to the adult brain to identify the transcriptomic profile of progenitor and adult stellate cells. Importantly, we could confirm the robustness of our data by extracting developmental factors from the identified intermediate stellate cell cluster and implemented these factors to generate putative intermediate stellate cells from human induced pluripotent stem cells. Six transcription factors identified from the stellate cell cluster including RUNX1T1, SOX5, FOXP1, MEF2C, TCF4, EYA2 were overexpressed using a forward programming approach to produce neurons expressing a unique combination of RELN, SATB2, LEF1 and BCL11B observed in stellate cells. Further analyses of the individual transcription factors led to the discovery that FOXP1 is critical in the reprogramming process and omission of RUNX1T1 and EYA2 enhances neuron conversion. Our findings contribute not only to the profiling of cell types within the developing and adult brain’s medial entorhinal cortex but also provides proof-of-concept for using scRNAseq data to produce entorhinal intermediate stellate cells from human pluripotent stem cells in-vitro.

Subsets of mononuclear phagocytes, including macrophages and classical dendritic cells (cDC), are highly heterogeneous in peripheral tissues such as the intestine, with each subset playing distinct roles in immune responses. Understanding this complexity at the cellular level has proven difficult due to the expression of overlapping phenotypic markers and the inability to isolate leukocytes of the mucosal lamina propria (LP) effector site, without contamination by the isolated lymphoid follicles (ILFs), which are embedded in the mucosa and which are responsible for the induction of immunity. Here we exploit our novel method for separating lamina propria from isolated lymphoid follicles to carry out single-cell RNA-seq, CITE-seq and flow cytometry analysis of MNPs in the human small intestinal and colonic LP, without contamination by lymphoid follicles. As well as classical monocytes, non-classical monocytes, mature macrophages, cDC1 and CD103+ cDC2, we find that a CD1c+ CD103- cDC subset, which shares features of both cDC2 and monocytes, is similar to the cDC3 that have recently been described in human peripheral blood. As well as differing between the steady-state small intestine and colon, the proportions of the different MNP subsets change during different stages of inflammatory bowel disease (IBD) inflammation. Putative cDC precursors (pre-cDC) were also present in the intestine, and trajectory analysis revealed clear developmental relationships between these and subsets of mature cDC, as well as between tissue monocytes and macrophages. By providing novel insights into the heterogeneity and development of intestinal MNP, our findings should help develop targeted approaches for modulating intestinal immune responses.

The brainstem dorsal vagal complex (DVC) is known to regulate energy balance and is the target of appetite-suppressing hormones, such as glucagon-like peptide 1 (GLP-1). Here we provide a comprehensive genetic map of the DVC and identify neuronal populations that control feeding. Combining bulk and single-nucleus gene expression and chromatin profiling of DVC cells, we reveal 25 neuronal populations with unique transcriptional and chromatin accessibility landscapes and peptide receptor expression profiles. GLP-1 receptor (GLP-1R) agonist administration induces gene expression alterations specific to two distinct sets of Glp1r neurons—one population in the area postrema and one in the nucleus of the solitary tract that also expresses calcitonin receptor ( Calcr ). Transcripts and regions of accessible chromatin near obesity-associated genetic variants are enriched in the area postrema and the nucleus of the solitary tract neurons that express Glp1r and/or Calcr , and activating several of these neuronal populations decreases feeding in rodents. Thus, DVC neuronal populations associated with obesity predisposition suppress feeding and may represent therapeutic targets for obesity.

Mononuclear phagocytes (MNP), including macrophages and classical dendritic cells (cDC), are highly heterogeneous cells with distinct functions. Understanding MNP complexity in the intestinal lamina propria (LP), particularly in humans, has proved difficult due to the expression of overlapping phenotypic markers and the inability to isolate these cells without contamination from gut-associated lymphoid tissues (GALT). Here, we exploited our novel method for isolation of human GALT-free LP to carry out single-cell (sc)RNA-seq, CITE-seq and flow cytometry analysis of human ileal and colonic LP MNPs. As well as classical monocytes, non-classical monocytes, mature macrophage subsets, cDC1s, and cDC2s, we identified a CD1c + cDC subset with features of both cDC2 and monocytes, which were transcriptionally similar to the recently described cDC3. While similar MNP subsets were present in both ileal and colonic LP, the proportions and transcriptional profiles of these populations differed between these sites and in diseased states, indicating local specialization and environmental imprinting. Using computational trajectory tools, we identified putative early committed pre-cDC subsets and developmental intermediates of mature cDC1, cDC2 and cDC3, as well as monocyte–to-macrophage trajectories. Collectively, our results provide novel insights into the heterogeneity and development of intestinal LP MNP and an important framework for studying the role of these populations in intestinal homeostasis and disease. One sentence summary Fenton and Wulff et al . use single-cell methods to explore the complexity of the mononuclear phagocyte compartment of the human intestinal lamina propria, identifying distinct dendritic cell and macrophage subsets, site-specific transcriptional signatures, and lineage-specific precursors.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.

The application of machine learning to longitudinal gene-expression profiles has demonstrated potential to decrease the assessment gap, between biochemical determination and clinical manifestation, of a patient's response to treatment. Although psoriasis is a proven testing ground for treatment-response prediction using transcriptomic data from clinically accessible skin biopsies, these biopsies are expensive, invasive, and challenging to obtain from certain body areas. Response prediction from blood biochemical measurements could be a cheaper, less invasive predictive platform. Longitudinal profiles for 92 inflammatory and 65 cardiovascular disease proteins were measured from the blood of psoriasis patients at baseline, and 4-weeks, following tofacitinib (janus kinase-signal transducer and activator of transcription-inhibitor) or etanercept (tumor necrosis factor-inhibitor) treatment, and predictive models were developed by applying machine-learning techniques such as bagging and ensembles. This data driven approach developed predictive models able to accurately predict the 12-week clinical endpoint for psoriasis following tofacitinib (area under the receiver operating characteristic curve [auROC] = 78%), or etanercept (auROC = 71%) treatment in a validation dataset, revealing a robust predictive protein signature including well-established psoriasis markers such as IL-17A and IL-17C, highlighting potential for biologically meaningful and clinically useful response predictions using blood protein data. Although most blood classifiers were outperformed by simple models trained using Psoriasis Area Severity Index scores, performance might be enhanced in future studies by measuring a wider variety of proteins.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. By mapping and replicating protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, we identified 467 pQTLs for 85 proteins. The pQTLs were used in combination with other sources of information to evaluate known drug targets, and suggest new target candidates or repositioning opportunities, underpinned by a) causality assessment using Mendelian randomization, b) pathway mapping using -pQTL gene assignments, and c) protein-centric polygenic risk scores enabling matching of plausible target mechanisms to sub-groups of individuals enabling precision medicine.

Background The Janus kinase (JAK) family of tyrosine kinases includes JAK1, JAK2, JAK3 and TYK2 which signals through type I and type II cytokine receptors. Tofacitinib is an oral JAK inhibitor approved for the treatment of rheumatoid arthritis (RA). In cellular settings where JAKs signal in pairs, tofacitinib preferentially inhibits signalling by heterodimeric receptors associated with JAK1 and/or JAK3 and has functional selectivity over JAK2. Next generation sequencing (i.e. RNA sequencing) offers an unbiased analysis of whole transcriptome pharmacology. Objectives To profile the transcriptome in whole blood samples collected in a Phase 1 healthy volunteer (HV) study and a Phase 2 study with RA subjects treated with placebo, 5 mg, 10 mg or 15 mg of tofacitinib monotherapy. Methods In the HV study, a total of 93 Paxgene RNA tubes were obtained from 30 subjects collected at screening, at baseline on day 1, and at 2 hours post dosing on day 15. HVs were treated daily with tofacitinib (10 mg BID) for 15 days. In the RA study (NCT00550446), a total of 239 RNA samples were obtained from 25–31 subjects at baseline and day 28 who were treated with tofacitinib 5 mg BID, 10 mg BID or 15 mg BID daily for 84 days. RNAseq libraries were generated using a polyA based mRNA kit and sequenced to a depth of ∼40 million paired-end reads. Upstream processing included alignment of sequences, gene quantification and data quality control. The raw reads were normalised using the Trimmed Mean of M values (TMM) method in the edgeR package. Log2 fold-changes (FC) and corresponding false discovery rate (FDR)-adjusted p-values (padj) were calculated using the voom function in the Limma package (vers 3.8) in R 3.5.1. In particular, the correlations between baseline and measurements at each visit per patient were estimated by Limma’s duplicateCorrelation function. Genes were considered significant after multiple test correction with FDR, or padj <0.1 within each study. Results Modulation of the JAK-STAT signalling pathways was observed as exemplified by gene expression differences in cytokine-inducible SH2-containing protein (CISH) (p value=4.64E-41 in the HV study and p value=1.2E-8 in the RA study) and suppressor of cytokine signalling (SOCS2) protein (p value=1.38E-18 in HV study and p value=2.27E-7 in the RA study). Gene expression of CISH, a member of the SOCS family, was decreased from its baseline value at day 15 in HV (FC from baseline=0.18) and at day 28 in RA subjects (FC from baseline=0.42) when comparing tofacitinib treatment (HV:10 mg, RA:15 mg) to baseline or placebo, respectively. SOCS2 gene expression was also decreased at day 15 in HV (FC from baseline=0.40) and at day 28 in RA subjects (FC from baseline=0.52) when comparing tofacitinib treatment (HV:10 mg, RA:15 mg) to baseline or placebo, respectively. Other changes observed in the HV study: 301 genes were upregulated and 169 genes were downregulated when comparing 2 hours post dose on day 15 to baseline. In the RA study, 643 genes were upregulated and 801 genes were downregulated when comparing the 15 mg dose to placebo at week 4. Preliminary pathway level analysis shows overall a broader modulation of cytokine and chemokine signalling pathways by tofacitinib treatment in RA compared to what we observe in HV. Conclusion The results of this post hoc analysis demonstrate that tofacitinib induces measureable changes in the modulation of the JAK-STAT signalling pathway as well as effects on inflammatory cytokines and chemokines. The existence of overlapping but also unique JAK-STAT pathway inhibition due to tofacitinib between the HV and RA studies, as well as ongoing work, will provide a better understanding of response/non-response to tofacitinib and future drug developments. Disclosure of Interests Angela Hadjipanayis Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Xing Chen Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Julie Lee Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Shanrong Zhao Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Weidong Zhang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, David Martin Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Mateusz Maciejewski Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Daniel Ziemek Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Lori Fitz Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Craig Hyde Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, David von Schack Shareholder of: Pfizer Inc, Employee of: Pfizer Inc

Classic studies investigating how and when the entorhinal cortex (component of the memory processing system of the brain) develops have been based on traditional thymidine autoradiography and histological techniques. In this study, we take advantage of modern technologies to trace at a high resolution, the cellular complexity of the developing porcine medial entorhinal cortex by using single-cell profiling. The postnatal medial entorhinal cortex comprises 4 interneuron, 3 pyramidal neuron and 2 stellate cell populations which emerge from intermediate progenitor and immature neuron populations. We discover four MGE-derived interneurons and one CGE-derived interneuron population as well as several IN progenitors. We also identify two oligodendrocyte progenitor populations and three populations of oligodendrocytes. We perform a proof-of-concept experiment demonstrating that porcine scRNA-seq data can be used to develop novel protocols for producing human entorhinal cells in-vitro. We identified six transcription factors (RUNX1A1, SOX5, FOXP1, MEF2C, TCF4, EYA2) important in neurodevelopment and differentiation from one RELN+ stellate cell population. Using a lentiviral vector approach, we reprogrammed human induced pluripotent stem cells into stellate cell-like cells which expressed RELN, SATB2, LEF1 and BCL11B. Our findings contribute to the understanding of the formation of the brain’s cognitive memory and spatial processing system and provides proof-of-concept for the production of entorhinal cells from human pluripotent stem cells in-vitro.

Background: Tofacitinib is an oral Janus kinase inhibitor for the treatment of RA. Herpes zoster is more common in patients (pts) with RA vs the general population.1 This risk increases with tofacitinib use2 and appears to be further increased with concomitant use of csDMARDs such as methotrexate (MTX), or glucocorticoids (GC).3 The mechanism for these increases in risk may be linked to treatment-induced interferon (IFN) suppression,3 given that replication of the varicella zoster virus appears to be limited by IFN activity.4 Objectives: To evaluate whether treatment of RA with tofacitinib + MTX or GC suppresses IFN pathway proteins to a greater extent than treatment with tofacitinib monotherapy. Methods: This was a post hoc analysis of pooled data from 1 Phase (P)2 (Japan study [NCT00687193]) and 2 P3 (ORAL Scan [NCT00847613]; ORAL Start [NCT01039688]) tofacitinib studies. Serum samples were collected at baseline (BL), Week (W)12 and/or W24 from pts with RA treated with tofacitinib 5 or 10 mg BID, given as monotherapy (Japan study; ORAL Start) or with stable doses of MTX (15–25 mg weekly for ≥6 weeks; ORAL Scan) and/or GC (≤10 mg/day prednisone or equivalent; all studies). A total of 376 proteins associated with cellular and inflammatory processes, including 6 IFN pathway proteins (CXCL10, CXCL9, CXCL11, IL-12, IFNγ and IL-20), were measured using a homogeneous solution-based assay (Olink Proseek® Multiplex Assay, Uppsala, Sweden). Changes in protein levels from BL to W12 (Japan study, ORAL Scan) and/or W24 (ORAL Scan, ORAL Start) were compared for tofacitinib monotherapy vs tofacitinib + MTX or GC using linear regression models. The dependent variable was change from BL in protein levels at W12 or W24. The independent variable was MTX or GC status. Age, gender, GC status (in MTX model) and BL protein levels and tofacitinib dose were covariates. Regressions were performed separately for each study; results for GC were combined via meta-analysis using fixed and random effect models. Significance was considered at p<0.1 after controlling for false discovery rate (FDR). Data quality control included accounting for plate/batch defects and limits of detection, and removal of sample/analytes with excessive missing data. Results: In total, 659 serum samples were collected from 321 pts. Of the 6 IFN pathway proteins, 2 (IFNγ and IL-20) were below the limit of detection. There was no strong evidence suggesting statistical differences between tofacitinib monotherapy and tofacitinib + MTX or GC in changes in levels of the 4 detectable IFN pathway proteins (CXCL10, CXCL9, CXCL11 and IL-12) from BL to W12 and/or W24. Significant differences were observed for 2 of the 370 other proteins: MMP-1 (FDR adjusted p=0.08) and IL1Ra (FDR adjusted p=0.09), where levels decreased from BL to W12 for tofacitinib + MTX to a greater extent than for tofacitinib monotherapy. Conclusion: The results of this post hoc analysis suggest that tofacitinib + MTX or GC may not suppress circulating serum levels of IFN pathway proteins to a greater extent than tofacitinib monotherapy. Although there were differences at W12 for tofacitinib + MTX vs tofacitinib monotherapy in MMP-1 and IL1Ra, it is not yet clear whether these observations may be attributable to differences in the ethnicities of the study populations receiving these two treatment regimens (global vs Japan). Further analyses of biomarker changes with tofacitinib are ongoing. References [1] McDonald JR, et al. Clin Infect Dis2009; 48: 1364-71. [2] Winthrop KL, et al. Arthritis Rheumatol2014; 66: 2675-84. [3] Winthrop KL, et al. Arthritis Rheumatol2017; 69: 1960-8. [4] Ku CC, et al. Cell Biosc2016; 6: 21. Acknowledgement: Study sponsored by Pfizer Inc. Medical writing support was provided by Sarah Piggott of CMC Connect and funded by Pfizer Inc. Disclosure of Interests: Julie Lee Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Xing Chen Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Weidong Zhang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, David Martin Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Craig Hyde Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Tomohiro Hirose Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Shweta Shah Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Lori Fitz Shareholder of: Pfizer Inc, Employee of: Pfizer Inc

Supplementary Materials, Part 1: Notes S1-S2, Figures S1-S8, and Tables S1-S6. Supplementary Materials, Part 2: Tables S7-S39. (ZIP 789 kb)