Atherosclerosis (ATH) is a major complication for patients with systemic lupus erythematosus (SLE). Despite the increased risk of cardiovascular morbidity in SLE, there are no established methods to identify which SLE patients are at risk for premature ATH. Our primary goal in this project is to develop and validate a panel of biomarkers in SLE that can be easily used by clinicians to predict patients at risk for accelerated progression of ATH. Our group has identified several biomarkers associated with increased ATH in SLE, including dysfunctional piHDL, leptin, sTWEAK, and homocysteine. We propose that when selected markers of risk can be grouped into a comprehensive profile, PREDICTS, the combination will have high positive and negative predictive values, sensitivity, and specificity, and can be used to project the future progression of ATH far better than any individual component alone. In addition, we have preliminary data that suggest our panel of ATH biomarkers is also predictive of SLE disease flares and damage accumulation. Our hypothesis is that the same ongoing process that results in accelerated ATH may also be contributing to the risk of disease flare and inflammation in other organ systems. The following are therefore proposed:
Aim 1 : To validate the PREDICTS model in a broadly representative cohort of SLE subjects, we will: 1a.) Expand our SLE cohort to include higher representation of all SLE patients, including subjects with i) active nephritis, ii) on statins and iii) male gender;1b.) Validate the PREDICTS panel as a biomarker for accelerated ATH in SLE using i.) carotid ultrasound, ii.)measures of endothelial dysfunction, and iii.) cardiovascular events;and 1c.) Validate the PREDICTS panel in a second independent cohort.
In Aim 2, we wish to optimize the PREDICTS model for implementation into clinical practice. Therefore, we propose Aim 2a.) To determine whether PREDICTS profiles are stable over time in SLE subjects and controls, and 2b.) To examine the most promising biomarkers for potential inclusion into PREDICTS, including markers of chronic inflammation and chronic oxidative damage, to determine if these markers strengthen the predictive power of the PREDICTS profile. Finally, in Aim 3, we will determine the predictive value of the PREDICTS profile for progression of SLE disease by comparing the rate of cumulative disease activity, damage, and disease flares in SLE subjects with a high compared to a low PREDICTS profile.
This study will define the PREDICTS profile, a risk profile of biomarkers in SLE that can be used to predict accelerated cardiovascular disease, a significant cause of SLE morbidity and mortality. This prediction model will be used to both identify patients at risk for developing atherosclerosis and progression of disease flares and damage. Ultimately, it may highlight dysregulated molecules and pathways that are novel therapeutic targets for intervention.
| Beigneux, Anne P; Miyashita, Kazuya; Ploug, Michael et al. (2017) Autoantibodies against GPIHBP1 as a Cause of Hypertriglyceridemia. N Engl J Med 376:1647-1658 |
| McMahon, Maureen; Skaggs, Brian (2016) Autoimmunity: Do IgM antibodies protect against atherosclerosis in SLE? Nat Rev Rheumatol 12:442-4 |
| McMahon, Maureen; Skaggs, Brian (2014) Pathogenesis and treatment of atherosclerosis in lupus. Rheum Dis Clin North Am 40:475-95, viii |
