Christina T. Stankey

Abstract Increasing rates of autoimmune and inflammatory disease present a burgeoning threat to human health 1 . This is compounded by the limited efficacy of available treatments 1 and high failure rates during drug development 2 , highlighting an urgent need to better understand disease mechanisms. Here we show how functional genomics could address this challenge. By investigating an intergenic haplotype on chr21q22—which has been independently linked to inflammatory bowel disease, ankylosing spondylitis, primary sclerosing cholangitis and Takayasu’s arteritis 3–6 —we identify that the causal gene, ETS2 , is a central regulator of human inflammatory macrophages and delineate the shared disease mechanism that amplifies ETS2 expression. Genes regulated by ETS2 were prominently expressed in diseased tissues and more enriched for inflammatory bowel disease GWAS hits than most previously described pathways. Overexpressing ETS2 in resting macrophages reproduced the inflammatory state observed in chr21q22-associated diseases, with upregulation of multiple drug targets, including TNF and IL-23. Using a database of cellular signatures 7 , we identified drugs that might modulate this pathway and validated the potent anti-inflammatory activity of one class of small molecules in vitro and ex vivo. Together, this illustrates the power of functional genomics, applied directly in primary human cells, to identify immune-mediated disease mechanisms and potential therapeutic opportunities.

Empyema is a complication of community-acquired pneumonia. We conducted a retrospective analysis of empyema patients discharged from 1996 to 2016, examining culture results according to timing of antibiotic administration. Blood culture decreased from 45% to 4% after antibiotics, and pleural fluid culture yield decreased from 67% to 30%. More than half of methicillin-resistant Staphylococcus aureus cases occurred from 2011 to 2016.

Genome-wide association studies have identified hundreds of genetic loci that are associated with immune-mediated diseases. Most disease-associated variants are non-coding, and a large proportion of these variants lie within enhancers. As a result, there is a pressing need to understand how common genetic variation might affect enhancer function and thereby contribute to immune-mediated (and other) diseases. In this Review, we first describe statistical and experimental methods to identify causal genetic variants that modulate gene expression, including statistical fine-mapping and massively parallel reporter assays. We then discuss approaches to characterise the mechanisms by which these variants modulate immune function, such as clustered regularly interspaced short palindromic repeats (CRISPR)-based screens. We highlight examples of studies that, by elucidating the effects of disease variants within enhancers, have provided important insights into immune function and uncovered key pathways of disease.

Autoimmune and inflammatory diseases are rising globally yet widely effective therapies remain elusive. Most treatments have limited efficacy, significant potential side effects, or eventually lose response, underscoring the urgent need for new therapeutic approaches. We recently discovered that ETS2, a transcription factor, functions as a master regulator of macrophage-driven inflammation-and is causally linked to the pathogenesis of multiple inflammatory diseases via human genetics. The pleotropic inflammatory effects of ETS2 included upregulation of many cytokines that are individually targeted by current disease therapies, including TNFα, IL-23, IL1β, and TNF-like ligand 1A signaling. With the move toward combination treatment-to maximize efficacy-targeting ETS2 presents a unique opportunity to potentially induce a broad therapeutic effect. However, there will be multiple challenges to overcome since direct ETS2 inhibition is unlikely to be feasible. Here, we discuss these challenges and other unanswered questions about the central role that ETS2 plays in macrophage inflammation.

PV053 / #179 Poster Topic: AS06 - Comorbidities Background/Purpose Poor sleep quality is a common complaint of patients with SLE. Although chronic sleep disruption is known to drive circadian rhythm disorders, the effects of poor sleep quality have not yet been elucidated in SLE. Actigraphy is a validated approach to objectively assess 21 sleep variables and motor activity using a noninvasive accelerometer. In addition, actigraphy can characterize circadian dysfunction by assessments of activity. We examine the relationship of actigraphy data from patients with SLE with 1) disease activity and 2) subjective patient-reported outcome measures of sleep quality. Methods Seventy-six consented subjects from the Washington University Lupus Center with classified SLE were enrolled. Participants wore a wrist-mounted actigraph (Micro Motionlogger, Ambulatory Monitoring Inc, Ardsley, NY) for 1 week. Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), Patient Reported Outcomes Measurement Instrument System (PROMIS)-Sleep Related Impairment (SRI), and PROMIS-Sleep Disturbance (SD) survey instruments were administered to measure subjective sleep quality. SLEDAI-2000 Responder Index-50 (S2K RI-50) assessed disease activity (>4, active SLE). Actigraphy data were analyzed using Action W (Ambulatory Monitoring Inc), and circadian variables were derived using ClockLab (Actimetrics, Wilmette, IL). Unpaired Student t tests (2-sided, α < 0.05) were used to compare sleep quality and circadian dysfunction in patients with active vs inactive disease. Pearson correlation coefficient was used to assess correlation of actigraphy and circadian variables with subjective sleep quality. Statistical analyses were performed using SPSS Statistics (IBM, Armonk, NY). Results No differences in actigraphic measures of sleep quality (eg, total sleep duration, percent sleep, wake after sleep onset, etc.) were observed in active vs inactive disease. Active SLE was associated with phase-dependent circadian variables including bedtime, acrophase (peak of circadian activity), M start (beginning of most active hours), and M start – waketime (p=0.01, discrepancy between natural circadian rhythm and actual activity pattern) (Table 1). Table 1. PROMIS-SRI and PROMIS-SD showed no correlation with actigraphy or circadian measures, while PSQI and ESS correlated moderately with % sleep and rho counts (activity during sleep period), and ESS additionally showed modest correlation with measures such as sleep efficiency, sleep and wake episodes, and MESOR (measure of mean activity level) (Table 2). Table 2. Conclusions Changes in circadian phase, but not sleep quality, is associated with SLE disease activity, with a phase delay in those with active disease. The ESS was the PRO that most highly associated with several actigraphy-assessed sleep parameters, including sleep efficiency and fragmentation. Circadian dysfunction may be an underlying cause for other widely experienced symptoms of SLE including cognitive dysfunction and fatigue. Future work will focus on examining this relationship.