An Analytic Approach Using Candidate Gene Selection and Logic Forest to Identify Gene by Environment Interactions (G × E) for Systemic Lupus Erythematosus in African Americans

The role of environmental exposures and gene-environment interactions in the etiology of systemic lupus erythematous

Systemic lupus erythematosus (SLE) is a complex, chronic autoimmune disease, whose etiology includes both genetic and environmental factors. Individual genetic risk factors likely only account for about one-third of observed heritability among individuals with a family history of SLE. A large portion of the remaining risk may be attributable to environmental exposures and gene-environment interactions. This review focuses on SLE risk associated with environmental factors, ranging from chemical and physical environmental exposures to lifestyle behaviors, with the weight of evidence supporting positive associations between SLE and occupational exposure to crystalline silica, current smoking, and exogenous estrogens (e.g., oral contraceptives and postmenopausal hormones). Other risk factors may include lifestyle behaviors (e.g., dietary intake and sleep) and other exposures (e.g., ultraviolet [UV] radiation, air pollution, solvents, pesticides, vaccines and medications, and infections). Alcohol use may be associated with decreased SLE risk. We also describe the more limited body of knowledge on gene-environment interactions and SLE risk, including IL-10, ESR1, IL-33, ITGAM, and NAT2 and observed interactions with smoking, UV exposure, and alcohol. Understanding genetic and environmental risk factors for SLE, and how they may interact, can help to elucidate SLE pathogenesis and its clinical heterogeneity. Ultimately, this knowledge may facilitate the development of preventive interventions that address modifiable risk factors in susceptible individuals and vulnerable populations.

Mechanisms of Environment-Induced Autoimmunity

Although numerous environmental exposures have been suggested as triggers for preclinical autoimmunity, only a few have been confidently linked to autoimmune diseases. For disease-associated exposures, the lung is a common site where chronic exposure results in cellular toxicity, tissue damage, inflammation, and fibrosis. These features are exacerbated by exposures to particulate material, which hampers clearance and degradation, thus facilitating persistent inflammation. Coincident with exposure and resulting pathological processes is the posttranslational modification of self-antigens, which, in concert with the formation of tertiary lymphoid structures containing abundant B cells, is thought to promote the generation of autoantibodies that in some instances demonstrate major histocompatibility complex restriction. Under appropriate gene-environment interactions, these responses can have diagnostic specificity. Greater insight into the molecular and cellular requirements governing this process, especially those that distinguish preclinical autoimmunity from clinical autoimmunedisease, may facilitate determination of the significance of environmental exposures in human autoimmune disease.

Novel Machine Learning Approach to Identify Preoperative Risk Factors Associated With Super-Utilization of Medicare Expenditure Following Surgery

Importance

Typically defined as the top 5% of health care users, super-utilizers are responsible for an estimated 40% to 55% of all health care costs. Little is known about which factors may be associated with increased risk of long-term postoperative super-utilization.

Objective

To identify clusters of patients with distinct constellations of clinical and comorbid patterns who may be associated with an elevated risk of super-utilization in the year following elective surgery.

Design, Setting, and Participants

A retrospective longitudinal cohort study of 1 049 160 patients who underwent abdominal aortic aneurysm repair, coronary artery bypass graft, colectomy, total hip arthroplasty, total knee arthroplasty, or lung resection were identified from the 100% Medicare inpatient and outpatient Standard Analytic Files at all inpatient facilities performing 1 or more of the evaluated surgical procedures from 2013 to 2015. Data from 2012 to 2016 were used to evaluate expenditures in the year preceding and following surgery. Using a machine learning approach known as Logic Forest, comorbidities and interactions of comorbidities that put patients at an increased chance of becoming a super-utilizer were identified. All comorbidities, as defined by the Charlson (range, 0-24) and Elixhauser (range, 0-29) comorbidity indices, were used in the analysis. Higher scores indicated higher comorbidity burden. Data analysis was completed on November 16, 2018.

Main Outcome and Measures

Super-utilization of health care in the year following surgery.

Results

In total, 1 049 160 patients met inclusion criteria and were included in the analytic cohort. Their median (interquartile range) age was 73 (69-78) years, and approximately 40% were male. Super-utilizers comprised 4.8% of the overall cohort (n = 79 746) yet incurred 31.7% of the expenditures. Although the difference in overall expenditures per person between super-utilizers ($4049) and low users ($2148) was relatively modest prior to surgery, the difference in expenditures between super-utilizers ($79 698) vs low users ($2977) was marked in the year following surgery. Risk factors associated with super-utilization of health care included hemiplegia/paraplegia (odds ratio, 5.2; 95% CI, 4.4-6.2), weight loss (odds ratio, 3.5; 95% CI, 2.9-4.2), and congestive heart failure with chronic kidney disease stages I to IV (odds ratio, 3.4; 95% CI, 3.0-3.9).

Conclusions and Relevance

Super-utilizers comprised only a small fraction of the surgical population yet were responsible for a disproportionate amount of Medicare expenditure. Certain subpopulations were associated with super-utilization of health care following surgical intervention despite having lower overall use in the preoperative period.

Assessing an intervention to increase knowledge related to cervical cancer and the HPV vaccine

Human papillomavirus (HPV) infection is the primary risk factor for cervical cancer. While the HPV vaccine significantly reduces the risk of HPV infection and subsequent cervical cancer diagnosis, underuse is linked to lack of knowledge of its effectiveness in preventing cervical cancer. The purpose of this study was to evaluate a cancer educational intervention (titled "MOVENUP") to improve knowledge of cervical cancer, HPV, and the HPV vaccine among predominantly African American communities in South Carolina. The MOVENUP cancer educational intervention was conducted among participants residing in nine South Carolina counties who were recruited by community partners. The 4.5-h MOVENUP cancer educational intervention included a 30-min module on cervical cancer, HPV, and HPV vaccination. A six-item investigator-developed instrument was used to evaluate pre- and post-intervention changes in knowledge related to these content areas. Ninety-three percent of the 276 participants were African American. Most participants reporting age and gender were 50+ years (73%) and female (91%). Nearly half of participants (46%) reported an annual household income <$40,000 and 49% had not graduated from college. Statistically significant changes were observed at post-test for four of six items on the knowledge scale (P<0.05), as compared to pre-test scores. For the two items on the scale in which statistically significant changes were not observed, this was due primarily due to a baseline ceiling effect.

Assessment of utilization efficiency using machine learning techniques: A study of heterogeneity in preoperative healthcare utilization among super-utilizers

INTRODUCTION

In the United States, 5% of patients represent up to 55% of all health care costs. This study sought to define healthcare utilization patterns among super-utilizers, as well as assess possible variation in patient outcomes.

METHODS

Medicare super-utilizers undergoing either a total hip or knee arthroplasty were identified and entered into a cluster analysis using annual preoperative charges to identify distinct patterns of utilization.

RESULTS

Among 19,522 super-utilizers who underwent THA or TKA, there was a marked heterogeneity in overall utilization with 5 distinct clusters of utilization patterns. Of note, comorbidity burden was similar among the 5 clusters. Patient outcomes also varied by Cluster type, ranging from 6.9% to 16.5% experiencing complications and 1.0%-3.2% experiencing 90-day mortality.

CONCLUSION

While previous studies have suggested that super-utilizers are a homogenous group of patients, the current study demonstrated a large degree of heterogeneity within super-utilizers. Variations in utilization patterns were associated with postoperative outcomes and subsequent health care costs.