Estimation of causal effects using instrumental variables with nonignorable missing covariates: Application to effect of type of delivery NICU on premature infants

Understanding how effective high-level NICUs (neonatal intensive care units that have the capacity for sustained mechanical assisted ventilation and high volume) are compared to low-level NICUs is important and valuable for both individual mothers and for public policy decisions. The goal of this paper is to estimate the effect on mortality of premature babies being delivered in a high-level NICU vs. a low-level NICU through an observational study where there are unmeasured confounders as well as nonignorable missing covariates. We consider the use of excess travel time as an instrumental variable (IV) to control for unmeasured confounders. In order for an IV to be valid, we must condition on confounders of the IV---outcome relationship, for example, month prenatal care started must be conditioned on for excess travel time to be a valid IV. However, sometimes month prenatal care started is missing, and the missingness may be nonignorable because it is related to the not fully measured mother's/infant's risk of complications. We develop a method to estimate the causal effect of a treatment using an IV when there are nonignorable missing covariates as in our data, where we allow the missingness to depend on the fully observed outcome as well as the partially observed compliance class, which is a proxy for the unmeasured risk of complications. A simulation study shows that under our nonignorable missingness assumption, the commonly used estimation methods, complete-case analysis and multiple imputation by chained equations assuming missingness at random, provide biased estimates, while our method provides approximately unbiased estimates. We apply our method to the NICU study and find evidence that high-level NICUs significantly reduce deaths for babies of small gestational age, whereas for almost mature babies like 37 weeks, the level of NICUs makes little difference. A sensitivity analysis is conducted to assess the sensitivity of our conclusions to key assumptions about the missing covariates. The method we develop in this paper may be useful for many observational studies facing similar issues of unmeasured confounders and nonignorable missing data as ours.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS699 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

In Vitro Analysis of the Thyroid Hormone Receptor in Mitochondrial Transcription

The central dogma theory relates how DNA is transcribed into messenger RNA (mRNAs) and then translated into proteins. Since the nucleus contains the majority of the DNA in cells, research related to transcription and translation focuses on these processes within the nucleus and cytosol; however, these processes are also taking place within the mitochondrial organelle. Mitochondria are most widely known for their essential role in producing energy for the cell, but the organelle also contains its own small, circular genome. Transcription of mitochondrial DNA (mtDNA) follows similar mechanisms as does transcription of nuclear DNA. During this essential process, specific mitochondrial transcription factors, such as TFAM and TFB2M, regulate the attachment of the mitochondrial RNA polymerase (POLRMT) to the promoter and initiation of transcription. With a fully functioning mitochondrial RNA polymerase, transcription is properly conducted, and transcripts can be translated to protein by the mitochondrial ribosome. Mitochondrial transcription is a major regulatory process within the organelle, and determining transcription factors involved in this control point is important for understanding mitochondrial function and many diseases relating to mitochondrial dysfunction. Numerous transcription factors are found both in the nucleus as well as in the mitochondria where their function is not well understood. One such transcription factor is the thyroid hormone receptor. Previous research suggests that when the hormone triiodothyronine (T3) is present and taken up in cells, mitochondrial transcription increases. The mechanism behind the T3 stimulation of transcription is thought to be a coordinated effect by interacting with both the mitochondrial and nuclear thyroid hormone receptor. Our aim is to analyze the level of interaction that the mitochondrial thyroid hormone receptor (mt-TRalpha1) has with the mitochondrial DNA and other core mitochondrial transcription factors in the presence and absence of the T3 hormone. With this information, we further understand another component of mitochondrial transcription that could have implications in mitochondrial dysfunction and disease