Patient-centered mobile health technology intervention to improve self-care in patients with chronic heart failure: Protocol for a feasibility randomized controlled trial.

This randomized controlled trial aims to determine the feasibility and preliminary efficacy of a patient-centered, mobile health technology intervention (iCardia4HF) in patients with chronic Heart Failure (HF). Participants (n = 92) are recruited and randomized 1:1 to the intervention or control group. The intervention group receives a commercial HF self-care app (Heart Failure Storylines), three connected health devices that interface with the app (Withings weight scale and blood pressure monitor, and Fitbit activity tracker), and a program of individually tailored text-messages targeting health beliefs, self-care self-efficacy, HF-knowledge, and physical activity. The control group receives the same connected health devices, but without the HF self-care app and text messages. Follow-up assessments occur at 30 days and 12 weeks. The main outcome of interest is adherence to HF self-care assessed objectively through time-stamped data from the electronic devices and also via patient self-reports. Primary measures of HF self-care include medication adherence and adherence to daily weight monitoring. Secondary measures of HF self-care include adherence to daily self-monitoring of HF symptoms and blood pressure, adherence to low-sodium diet, and engagement in physical activity. Self-reported HF self-care and health-related quality of life are assessed with the Self-care Heart Failure Index and the Kansas City Cardiomyopathy Questionnaire, respectively. Hospitalizations and emergency room visits are tracked in both groups over 12 weeks as part of our safety protocol. This study represents an important step in testing a scalable mHealth solution that has the potential to bring about a new paradigm in self-management of HF.

Gene-expression-guided selection of candidate loci and molecular phenotype analyses enhance genetic discovery in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a highly heterogeneous autoimmune disorder characterized by differences in autoantibody profiles, serum cytokines, and clinical manifestations. We have previously conducted a case-case genome-wide association study (GWAS) of SLE patients to detect associations with autoantibody profile and serum interferon alpha (IFN-α). In this study, we used public gene expression data sets to rationally select additional single nucleotide polymorphisms (SNPs) for validation. The top 200 GWAS SNPs were searched in a database which compares genome-wide expression data to genome-wide SNP genotype data in HapMap cell lines. SNPs were chosen for validation if they were associated with differential expression of 15 or more genes at a significance of P < 9 × 10(-5). This resulted in 11 SNPs which were genotyped in 453 SLE patients and 418 matched controls. Three SNPs were associated with SLE-associated autoantibodies, and one of these SNPs was also associated with serum IFN-α (P < 4.5 × 10(-3) for all). One additional SNP was associated exclusively with serum IFN-α. Case-control analysis was insensitive to these molecular subphenotype associations. This study illustrates the use of gene expression data to rationally select candidate loci in autoimmune disease, and the utility of stratification by molecular phenotypes in the discovery of additional genetic associations in SLE.

Trait-stratified genome-wide association study identifies novel and diverse genetic associations with serologic and cytokine phenotypes in systemic lupus erythematosus.

INTRODUCTION: Systemic lupus erythematosus (SLE) is a highly heterogeneous disorder, characterized by differences in autoantibody profile, serum cytokines, and clinical manifestations. SLE-associated autoantibodies and high serum interferon alpha (IFN-α) are important heritable phenotypes in SLE which are correlated with each other, and play a role in disease pathogenesis. These two heritable risk factors are shared between ancestral backgrounds. The aim of the study was to detect genetic factors associated with autoantibody profiles and serum IFN-α in SLE. METHODS: We undertook a case-case genome-wide association study of SLE patients stratified by ancestry and extremes of phenotype in serology and serum IFN-α. Single nucleotide polymorphisms (SNPs) in seven loci were selected for follow-up in a large independent cohort of 538 SLE patients and 522 controls using a multi-step screening approach based on novel metrics and expert database review. The seven loci were: leucine-rich repeat containing 20 (LRRC20); protein phosphatase 1 H (PPM1H); lysophosphatidic acid receptor 1 (LPAR1); ankyrin repeat and sterile alpha motif domain 1A (ANKS1A); protein tyrosine phosphatase, receptor type M (PTPRM); ephrin A5 (EFNA5); and V-set and immunoglobulin domain containing 2 (VSIG2). RESULTS: SNPs in the LRRC20, PPM1H, LPAR1, ANKS1A, and VSIG2 loci each demonstrated strong association with a particular serologic profile (all odds ratios > 2.2 and P < 3.5 × 10-4). Each of these serologic profiles was associated with increased serum IFN-α. SNPs in both PTPRM and LRRC20 were associated with increased serum IFN-α independent of serologic profile (P = 2.2 × 10-6 and P = 2.6 × 10-3 respectively). None of the SNPs were strongly associated with SLE in case-control analysis, suggesting that the major impact of these variants will be upon subphenotypes in SLE. CONCLUSIONS: This study demonstrates the power of using serologic and cytokine subphenotypes to elucidate genetic factors involved in complex autoimmune disease. The distinct associations observed emphasize the heterogeneity of molecular pathogenesis in SLE, and the need for stratification by subphenotypes in genetic studies. We hypothesize that these genetic variants play a role in disease manifestations and severity in SLE.