Minimax-inspired Semiparametric Estimation and Causal Inference

This thesis focuses on estimation and inference for a large class of semiparametric estimands: the class of continuous functionals of regression functions. This class includes a number of estimands derived from causal inference problems, among then the average treatment effect for a binary treatment when treatment assignment is unconfounded and many of its generalizations for non-binary treatments and individualized treatment policies. Chapter 2, based on work with Stefan Wager, introduces the augmented minimax linear es- timator (AMLE), a general approach to the problem of estimating a continuous linear functional of a regression function. In this approach, we estimate the regression function, then subtract from a simple plug-in estimator of the functional a weighted combination of the estimated regression function’s residuals. For this, we use weights chosen to minimize the maximum of the mean squared error of the resulting estimator over regression functions in a chosen neighborhood of our estimated regression function. These weights are shown to be a universally consistent estimator our linear functional’s Riesz representer, the use of which would result in an exact bias correction for our plug- in estimator. While this convergence can be slow, especially when the Riesz representer is highly nonsmooth, the action of these weights on functions in the aforementioned neighborhood imitates that of the Riesz representer accurately even when they are slow to converge in other respects. As a result, we show that under no regularity conditions on the Riesz representer and minimal regularity conditions on the regression function, the proposed estimator is semiparametrically efficient. In simulation, it is shown to perform very well in the context of estimating the average partial effect in the conditional linear model, a simultaneous generalization of the average treatment effect to address continuous-valued treatments and of the partial linear model to address treatment effect heterogeneity. Chapter 3, based on work with Arian Maleki and José Zubizarreta, studies the minimax linear estimator, a simplified version of the AMLE in which the estimated regression function is taken to be zero, for a class of estimands generalizing the mean with outcomes missing at random. We show semiparametric efficiency under conditions that are only slightly stronger than those required for the AMLE. In addition, we bound the deviation of our estimator’s error from the averaged efficient influence function, characterizing the degree to which the first order asymptotic characterization of semiparametric efficiency is meaningful in finite samples. In simulation, this estimator is shown to perform well relative to alternatives in high-noise, small-sample settings with limited overlap between the covariate distribution of missing and nonmissing units, a setting that is challenging for approaches reliant on accurate estimation of either or both of the regression function and the propensity score. Chapter 4 discusses an approach to rounding linear estimators for the targeted average treatment effect into matching estimators. The targeted average treatment effect is a generalization of the average treatment effect and the average treatment effect on the treated units

Identification of RNA editing sites in the SNP database

The relationship between human inherited genomic variations and phenotypic differences has been the focus of much research effort in recent years. These studies benefit from millions of single-nucleotide polymorphism (SNP) records available in public databases, such as dbSNP. The importance of identifying false dbSNP records increases with the growing role played by SNPs in linkage analysis for disease traits. In particular, the emerging understanding of the abundance of DNA and RNA editing calls for a careful distinction between inherited SNPs and somatic DNA and RNA modifications. In order to demonstrate that some of the SNP database records are actually somatic modification, we focus on one type of these modifications, namely A-to-I RNA editing, and present evidence for hundreds of dbSNP records that are actually editing sites. We provide a list of 102 RNA editing sites previously annotated in dbSNP database as SNPs, and experimentally validate seven of these. Interestingly, we show how dbSNP can serve as a starting point to look for new editing sites. Our results, for this particular type of RNA editing, demonstrate the need for a careful analysis of SNP databases in light of the increasing recognition of the significance of somatic sequence modifications

The peripheral blood transcriptome in septic cardiomyopathy: an observational, pilot study.

BACKGROUND:Septic cardiomyopathy (SCM) is common in sepsis and associated with increased morbidity and mortality. Left ventricular global longitudinal strain (LV GLS), measured by speckle tracking echocardiography, allows improved identification of impaired cardiac contractility. The peripheral blood transcriptome may be an important window into SCM pathophysiology. We therefore studied the peripheral blood transcriptome and LV GLS in a prospective cohort of patients with sepsis. RESULTS:In this single-center observational pilot study, we enrolled adult patients (age > 18) with sepsis within 48 h of admission to the ICU. SCM was defined as LV GLS > - 17% based on echocardiograms performed within 72 h of admission. We enrolled 27 patients, 24 of whom had high-quality RNA results; 18 (75%) of 24 had SCM. The group was 50% female and had a median (IQR) age of 59.5 (48.5-67.0) years and admission APACHE II score of 21.0 (16.0-32.3). Forty-six percent had septic shock. After filtering for low-expression and non-coding genes, 15,418 protein coding genes were expressed and 73 had significantly different expression between patients with vs. without SCM. In patients with SCM, 43 genes were upregulated and 30 were downregulated. Pathway analysis identified enrichment in type 1 interferon signaling (adjusted p < 10-5). CONCLUSIONS:In this hypothesis-generating study, SCM was associated with upregulation of genes in the type 1 interferon signaling pathway. Interferons are cytokines that stimulate the innate and adaptive immune response and are implicated in the early proinflammatory and delayed immunosuppression phases of sepsis. While type 1 interferons have not been implicated previously in SCM, interferon therapy (for viral hepatitis and Kaposi sarcoma) has been associated with reversible cardiomyopathy, perhaps suggesting a role for interferon signaling in SCM

Donor-derived brain tumor following neural stem cell transplantation in an ataxia telangiectasia patient.

BackgroundNeural stem cells are currently being investigated as potential therapies for neurodegenerative diseases, stroke, and trauma. However, concerns have been raised over the safety of this experimental therapeutic approach, including, for example, whether there is the potential for tumors to develop from transplanted stem cells.Methods and findingsA boy with ataxia telangiectasia (AT) was treated with intracerebellar and intrathecal injection of human fetal neural stem cells. Four years after the first treatment he was diagnosed with a multifocal brain tumor. The biopsied tumor was diagnosed as a glioneuronal neoplasm. We compared the tumor cells and the patient's peripheral blood cells by fluorescent in situ hybridization using X and Y chromosome probes, by PCR for the amelogenin gene X- and Y-specific alleles, by MassArray for the ATM patient specific mutation and for several SNPs, by PCR for polymorphic microsatellites, and by human leukocyte antigen (HLA) typing. Molecular and cytogenetic studies showed that the tumor was of nonhost origin suggesting it was derived from the transplanted neural stem cells. Microsatellite and HLA analysis demonstrated that the tumor is derived from at least two donors.ConclusionsThis is the first report of a human brain tumor complicating neural stem cell therapy. The findings here suggest that neuronal stem/progenitor cells may be involved in gliomagenesis and provide the first example of a donor-derived brain tumor. Further work is urgently needed to assess the safety of these therapies

Gold Nanorods Based Air Scanning Electron Microscopy and Diffusion Reflection Imaging for Mapping Tumor Margins in Squamous Cell Carcinoma

A critical challenge arising during a surgical procedure for tumor removal is the determination of tumor margins. Gold nanorods (GNRs) conjugated to epidermal growth factor receptors (EGFR) (GNRs-EGFR) have long been used in the detection of cancerous cells as the expression of EGFR dramatically increases once the tissue becomes cancerous. Optical techniques for the identification of these GNRs-EGFR in tumor are intensively developed based on the unique scattering and absorption properties of the GNRs. In this study, we investigate the distribution of the GNRs in tissue sections presenting squamous cell carcinoma (SCC) to evaluate the SCC margins. Air scanning electron microscopy (airSEM), a novel, high resolution microscopy is used, enabling to localize and actually visualize nanoparticles on the tissue. The airSEM pictures presented a gradient of GNRs from the tumor to normal epithelium, spread in an area of 1 mm, suggesting tumor margins of 1 mm. Diffusion reflection (DR) measurements, performed in a resolution of 1 mm, of human oral SCC have shown a clear difference between the DR profiles of the healthy epithelium and the tumor itself

The peripheral blood transcriptome in septic cardiomyopathy: an observational, pilot study.

BACKGROUND:Septic cardiomyopathy (SCM) is common in sepsis and associated with increased morbidity and mortality. Left ventricular global longitudinal strain (LV GLS), measured by speckle tracking echocardiography, allows improved identification of impaired cardiac contractility. The peripheral blood transcriptome may be an important window into SCM pathophysiology. We therefore studied the peripheral blood transcriptome and LV GLS in a prospective cohort of patients with sepsis. RESULTS:In this single-center observational pilot study, we enrolled adult patients (age > 18) with sepsis within 48 h of admission to the ICU. SCM was defined as LV GLS > - 17% based on echocardiograms performed within 72 h of admission. We enrolled 27 patients, 24 of whom had high-quality RNA results; 18 (75%) of 24 had SCM. The group was 50% female and had a median (IQR) age of 59.5 (48.5-67.0) years and admission APACHE II score of 21.0 (16.0-32.3). Forty-six percent had septic shock. After filtering for low-expression and non-coding genes, 15,418 protein coding genes were expressed and 73 had significantly different expression between patients with vs. without SCM. In patients with SCM, 43 genes were upregulated and 30 were downregulated. Pathway analysis identified enrichment in type 1 interferon signaling (adjusted p < 10-5). CONCLUSIONS:In this hypothesis-generating study, SCM was associated with upregulation of genes in the type 1 interferon signaling pathway. Interferons are cytokines that stimulate the innate and adaptive immune response and are implicated in the early proinflammatory and delayed immunosuppression phases of sepsis. While type 1 interferons have not been implicated previously in SCM, interferon therapy (for viral hepatitis and Kaposi sarcoma) has been associated with reversible cardiomyopathy, perhaps suggesting a role for interferon signaling in SCM