Development of a decision aid to inform patients' and families' renal replacement therapy selection decisions.

BACKGROUND: Few educational resources have been developed to inform patients' renal replacement therapy (RRT) selection decisions. Patients progressing toward end stage renal disease (ESRD) must decide among multiple treatment options with varying characteristics. Complex information about treatments must be adequately conveyed to patients with different educational backgrounds and informational needs. Decisions about treatment options also require family input, as families often participate in patients' treatment and support patients' decisions. We describe the development, design, and preliminary evaluation of an informational, evidence-based, and patient-and family-centered decision aid for patients with ESRD and varying levels of health literacy, health numeracy, and cognitive function. METHODS: We designed a decision aid comprising a complementary video and informational handbook. We based our development process on data previously obtained from qualitative focus groups and systematic literature reviews. We simultaneously developed the video and handbook in "stages." For the video, stages included (1) directed interviews with culturally appropriate patients and families and preliminary script development, (2) video production, and (3) screening the video with patients and their families. For the handbook, stages comprised (1) preliminary content design, (2) a mixed-methods pilot study among diverse patients to assess comprehension of handbook material, and (3) screening the handbook with patients and their families. RESULTS: The video and handbook both addressed potential benefits and trade-offs of treatment selections. The 50-minute video consisted of demographically diverse patients and their families describing their positive and negative experiences with selecting a treatment option. The video also incorporated health professionals' testimonials regarding various considerations that might influence patients' and families' treatment selections. The handbook was comprised of written words, pictures of patients and health care providers, and diagrams describing the findings and quality of scientific studies comparing treatments. The handbook text was written at a 4th to 6th grade reading level. Pilot study results demonstrated that a majority of patients could understand information presented in the handbook. Patient and families screening the nearly completed video and handbook reviewed the materials favorably. CONCLUSIONS: This rigorously designed decision aid may help patients and families make informed decisions about their treatment options for RRT that are well aligned with their values.

Gene selection using iterative feature elimination random forests for survival outcomes.

Although many feature selection methods for classification have been developed, there is a need to identify genes in high-dimensional data with censored survival outcomes. Traditional methods for gene selection in classification problems have several drawbacks. First, the majority of the gene selection approaches for classification are single-gene based. Second, many of the gene selection procedures are not embedded within the algorithm itself. The technique of random forests has been found to perform well in high-dimensional data settings with survival outcomes. It also has an embedded feature to identify variables of importance. Therefore, it is an ideal candidate for gene selection in high-dimensional data with survival outcomes. In this paper, we develop a novel method based on the random forests to identify a set of prognostic genes. We compare our method with several machine learning methods and various node split criteria using several real data sets. Our method performed well in both simulations and real data analysis.Additionally, we have shown the advantages of our approach over single-gene-based approaches. Our method incorporates multivariate correlations in microarray data for survival outcomes. The described method allows us to better utilize the information available from microarray data with survival outcomes.

Human CD19 and CD40L deficiencies impair antibody selection and differentially affect somatic hypermutation.

Individuals with genetic defects in CD40 ligand (CD40L) or B-cell antigen receptor coreceptor molecules CD19 and CD81 suffer from an antibody deficiency. Still, these patients carry low levels of memory B cells and serum antibodies.

Invariant measure selection by noise. An example

We consider a deterministic system with two conserved quantities and infinity many invariant measures. However the systems possess a unique invariant measure when enough stochastic forcing and balancing dissipation are added. We then show that as the forcing and dissipation are removed a unique limit of the deterministic system is selected. The exact structure of the limiting measure depends on the specifics of the stochastic forcing.

Nrg1 is an injury-induced cardiomyocyte mitogen for the endogenous heart regeneration program in zebrafish.

Heart regeneration is limited in adult mammals but occurs naturally in adult zebrafish through the activation of cardiomyocyte division. Several components of the cardiac injury microenvironment have been identified, yet no factor on its own is known to stimulate overt myocardial hyperplasia in a mature, uninjured animal. In this study, we find evidence that Neuregulin1 (Nrg1), previously shown to have mitogenic effects on mammalian cardiomyocytes, is sharply induced in perivascular cells after injury to the adult zebrafish heart. Inhibition of Erbb2, an Nrg1 co-receptor, disrupts cardiomyocyte proliferation in response to injury, whereas myocardial Nrg1 overexpression enhances this proliferation. In uninjured zebrafish, the reactivation of Nrg1 expression induces cardiomyocyte dedifferentiation, overt muscle hyperplasia, epicardial activation, increased vascularization, and causes cardiomegaly through persistent addition of wall myocardium. Our findings identify Nrg1 as a potent, induced mitogen for the endogenous adult heart regeneration program.

Impact of Leukocyte Function-Associated Antigen-1 Blockade on Endogenous Allospecific T Cells to Multiple Minor Histocompatibility Antigen Mismatched Cardiac Allograft.

BACKGROUND: Blocking leukocyte function-associated antigen (LFA)-1 in organ transplant recipients prolongs allograft survival. However, the precise mechanisms underlying the therapeutic potential of LFA-1 blockade in preventing chronic rejection are not fully elucidated. Cardiac allograft vasculopathy (CAV) is the preeminent cause of late cardiac allograft failure characterized histologically by concentric intimal hyperplasia. METHODS: Anti-LFA-1 monoclonal antibody was used in a multiple minor antigen-mismatched, BALB.B (H-2B) to C57BL/6 (H-2B), cardiac allograft model. Endogenous donor-specific CD8 T cells were tracked down using major histocompatibility complex multimers against the immunodominant H4, H7, H13, H28, and H60 minor Ags. RESULTS: The LFA-1 blockade prevented acute rejection and preserved palpable beating quality with reduced CD8 T-cell graft infiltration. Interestingly, less CD8 T cell infiltration was secondary to reduction of T-cell expansion rather than less trafficking. The LFA-1 blockade significantly suppressed the clonal expansion of minor histocompatibility antigen-specific CD8 T cells during the expansion and contraction phase. The CAV development was evaluated with morphometric analysis at postoperation day 100. The LFA-1 blockade profoundly attenuated neointimal hyperplasia (61.6 vs 23.8%; P < 0.05), CAV-affected vessel number (55.3 vs 15.9%; P < 0.05), and myocardial fibrosis (grade 3.29 vs 1.8; P < 0.05). Finally, short-term LFA-1 blockade promoted long-term donor-specific regulation, which resulted in attenuated transplant arteriosclerosis. CONCLUSIONS: Taken together, LFA-1 blockade inhibits initial endogenous alloreactive T-cell expansion and induces more regulation. Such a mechanism supports a pulse tolerance induction strategy with anti-LFA-1 rather than long-term treatment.

Scaling limits of a model for selection at two scales

The dynamics of a population undergoing selection is a central topic in evolutionary biology. This question is particularly intriguing in the case where selective forces act in opposing directions at two population scales. For example, a fast-replicating virus strain outcompetes slower-replicating strains at the within-host scale. However, if the fast-replicating strain causes host morbidity and is less frequently transmitted, it can be outcompeted by slower-replicating strains at the between-host scale. Here we consider a stochastic ball-and-urn process which models this type of phenomenon. We prove the weak convergence of this process under two natural scalings. The first scaling leads to a deterministic nonlinear integro-partial differential equation on the interval $[0,1]$ with dependence on a single parameter, $\lambda$. We show that the fixed points of this differential equation are Beta distributions and that their stability depends on $\lambda$ and the behavior of the initial data around $1$. The second scaling leads to a measure-valued Fleming-Viot process, an infinite dimensional stochastic process that is frequently associated with a population genetics.

Predictive Modeling of Loss-of-Heterozygosity Events in Yeast

During mitotic cell cycles, DNA experiences many types of endogenous and exogenous damaging agents that could potentially cause double strand breaks (DSB). In S. cerevisiae, DSBs are primarily repaired by mitotic recombination and as a result, could lead to loss-of-heterozygosity (LOH). Genetic recombination can happen in both meiosis and mitosis. While genome-wide distribution of meiotic recombination events has been intensively studied, mitotic recombination events have not been mapped unbiasedly throughout the genome until recently. Methods for selecting mitotic crossovers and mapping the positions of crossovers have recently been developed in our lab. Our current approach uses a diploid yeast strain that is heterozygous for about 55,000 SNPs, and employs SNP-Microarrays to map LOH events throughout the genome. These methods allow us to examine selected crossovers and unselected mitotic recombination events (crossover, noncrossover and BIR) at about 1 kb resolution across the genome. Using this method, we generated maps of spontaneous and UV-induced LOH events. In this study, we explore machine learning and variable selection techniques to build a predictive model for where the LOH events occur in the genome.

Randomly from the yeast genome, we simulated control tracts resembling the LOH tracts in terms of tract lengths and locations with respect to single-nucleotide-polymorphism positions. We then extracted roughly 1,100 features such as base compositions, histone modifications, presence of tandem repeats etc. and train classifiers to distinguish control tracts and LOH tracts. We found interesting features of good predictive values. We also found that with the current repertoire of features, the prediction is generally better for spontaneous LOH events than UV-induced LOH events.

Inactivation of the von Hippel-Lindau tumor suppressor leads to selective expression of a human endogenous retrovirus in kidney cancer.

A human endogenous retrovirus type E (HERV-E) was recently found to be selectively expressed in most renal cell carcinomas (RCCs). Importantly, antigens derived from this provirus are immunogenic, stimulating cytotoxic T cells that kill RCC cells in vitro and in vivo. Here, we show HERV-E expression is restricted to the clear cell subtype of RCC (ccRCC) characterized by an inactivation of the von Hippel-Lindau (VHL) tumor-suppressor gene with subsequent stabilization of hypoxia-inducible transcription factors (HIFs)-1α and -2α. HERV-E expression in ccRCC linearly correlated with HIF-2α levels and could be silenced in tumor cells by either transfection of normal VHL or small interfering RNA inhibition of HIF-2α. Using chromatin immunoprecipitation, we demonstrated that HIF-2α can serve as transcriptional factor for HERV-E by binding with HIF response element (HRE) localized in the proviral 5' long terminal repeat (LTR). Remarkably, the LTR was found to be hypomethylated only in HERV-E-expressing ccRCC while other tumors and normal tissues possessed a hypermethylated LTR preventing proviral expression. Taken altogether, these findings provide the first evidence that inactivation of a tumor suppressor gene can result in aberrant proviral expression in a human tumor and give insights needed for translational research aimed at boosting human immunity against antigenic components of this HERV-E.

Examination of Endogenous Rotund Expression and Function in Developing Drosophila Olfactory System Using CRISPR-Cas9-Mediated Protein Tagging.

The zinc-finger protein Rotund (Rn) plays a critical role in controlling the development of the fly olfactory system. However, little is known about its molecular function in vivo. Here, we added protein tags to the rn locus using CRISPR-Cas9 technology in Drosophila to investigate its subcellular localization and the genes that it regulates . We previously used a reporter construct to show that rn is expressed in a subset of olfactory receptor neuron (ORN) precursors and it is required for the diversification of ORN fates. Here, we show that tagged endogenous Rn protein is functional based on the analysis of ORN phenotypes. Using this method, we also mapped the expression pattern of the endogenous isoform-specific tags in vivo with increased precision. Comparison of the Rn expression pattern from this study with previously published results using GAL4 reporters showed that Rn is mainly present in early steps in antennal disc patterning, but not in pupal stages when ORNs are born. Finally, using chromatin immunoprecipitation, we showed a direct binding of Rotund to a previously identified regulatory element upstream of the bric-a-brac gene locus in the developing antennal disc.

Evaluating marker-guided treatment selection strategies

© 2014, The International Biometric Society.A potential venue to improve healthcare efficiency is to effectively tailor individualized treatment strategies by incorporating patient level predictor information such as environmental exposure, biological, and genetic marker measurements. Many useful statistical methods for deriving individualized treatment rules (ITR) have become available in recent years. Prior to adopting any ITR in clinical practice, it is crucial to evaluate its value in improving patient outcomes. Existing methods for quantifying such values mainly consider either a single marker or semi-parametric methods that are subject to bias under model misspecification. In this article, we consider a general setting with multiple markers and propose a two-step robust method to derive ITRs and evaluate their values. We also propose procedures for comparing different ITRs, which can be used to quantify the incremental value of new markers in improving treatment selection. While working models are used in step I to approximate optimal ITRs, we add a layer of calibration to guard against model misspecification and further assess the value of the ITR non-parametrically, which ensures the validity of the inference. To account for the sampling variability of the estimated rules and their corresponding values, we propose a resampling procedure to provide valid confidence intervals for the value functions as well as for the incremental value of new markers for treatment selection. Our proposals are examined through extensive simulation studies and illustrated with the data from a clinical trial that studies the effects of two drug combinations on HIV-1 infected patients.

Selection of Postacute Stroke Rehabilitation Facilities: A Survey of Discharge Planners From the Northeast Cerebrovascular Consortium (NECC) Region.

The process of determining the level of care and specific postacute care facility for stroke patients has not been adequately studied. The objective of this study was to better understand the factors that influence postacute care decisions by surveying stroke discharge planners. Requests were sent to discharge planners at 471 hospitals in the Northeast United States to complete an online survey regarding the factors impacting the selection of postacute care. Seventy-seven (16%) discharge planners completed the online survey. Respondents were mainly nurses and social workers and 73% reported ≥20 years healthcare experience. Patients and families were found to be significantly more influential than physicians (P < 0.001) and other clinicians (P = 0.04) in influencing postdischarge care. Other clinicians were significantly more influential than physicians (P < 0.001). Insurance and quality of postacute care were the factors likely to most affect the selection of postacute care facility. Insurance was also identified as the greatest barrier in the selection of level of postacute care (70%; P < 0.001) and specific postacute care facility (46%; P = 0.02). More than half reported that pressure to discharge patients quickly impacts a patients' final destination. Nonclinical factors are perceived by discharge planners to have a major influence on postacute stroke care decision making.