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

Stabilizing the Retromer Complex in a Human Stem Cell Model of Alzheimer's Disease Reduces TAU Phosphorylation Independently of Amyloid Precursor Protein.

Developing effective therapeutics for complex diseases such as late-onset, sporadic Alzheimer's disease (SAD) is difficult due to genetic and environmental heterogeneity in the human population and the limitations of existing animal models. Here, we used hiPSC-derived neurons to test a compound that stabilizes the retromer, a highly conserved multiprotein assembly that plays a pivotal role in trafficking molecules through the endosomal network. Using this human-specific system, we have confirmed previous data generated in murine models and show that retromer stabilization has a potentially beneficial effect on amyloid beta generation from human stem cell-derived neurons. We further demonstrate that manipulation of retromer complex levels within neurons affects pathogenic TAU phosphorylation in an amyloid-independent manner. Taken together, our work demonstrates that retromer stabilization is a promising candidate for therapeutic development in AD and highlights the advantages of testing novel compounds in a human-specific, neuronal system

Hippocampal Subregions Differentially Associate with Standardized Memory Tests

Recent studies suggest that individual hippocampal subregions perform distinct cognitive operations and are differentially targeted by aging and disease. Although originally developed to assess global hippocampal function, whether performance on standard memory tests used in neuropsychological batteries is associated with individual hippocampal subregions remains unknown. Here we addressed this issue by imaging 210 neuropsychologically characterized subjects using a high-resolution variant of functional magnetic resonance imaging that generates maps reflective of basal hippocampal metabolism. Regression analysis revealed memory tests that differentially associate with two hippocampal subregions, the entorhinal cortex (EC) and the dentate gyrus (DG). Whereas performance on the delayed retention component of the Selective Reminding Test was associated with the EC, performance on the recognition component of the Benton Visual Retention Test (BVRT) was associated with the DG. Furthermore, elevation in blood glucose, previously shown to target the DG, was found to correlate selectively with the recognition component of the BVRT. These findings provide further evidence that the hippocampal subregions perform distinct roles, and, interpreted in the context of previous neuropsychological and imaging studies, confirm that aging and Alzheimer's disease target different hippocampal subregions

Perils and Prospects of Using Aggregate Area Level Socioeconomic Information as a Proxy for Individual Level Socioeconomic Confounders in Instrumental Variables Regression

A frequent concern in making statistical inference for causal effects of a policy or treatment based on observational studies is that there are unmeasured confounding variables. The instrumental variable method is an approach to estimating a causal relationship in the presence of unmeasured confounding variables. A valid instrumental variable needs to be independent of the unmeasured confounding variables. It is important to control for the confounding variable if it is correlated with the instrument. In health services research, socioeconomic status variables are often considered as confounding variables. In recent studies, distance to a specialty care center has been used as an instrument for the effect of specialty care vs. general care. Because the instrument may be correlated with socioeconomic status variables, it is important that socioeconomic status variables are controlled for in the instrumental variables regression. However, health data sets often lack individual socioeconomic information but contain area average socioeconomic information from the US Census, e.g., average income or education level in a county. We study the effects on the bias of the two stage least squares estimates in instrumental variables regression when using an area-level variable as a controlled confounding variable that may be correlated with the instrument. We propose the aggregated instrumental variables regression using the concept of Wald’s method of grouping, provided the assumption that the grouping is independent of the errors. We present simulation results and an application to a study of perinatal care for premature infants

Proton Nuclear Magnetic Resonance Investigation of the [2Fe-2S]\u3csup\u3e1-\u3c/sup\u3e-Containing “Rieske-Type” Protein from \u3cem\u3eXanthobacter\u3c/em\u3e Strain Py2

Proton NMR spectra of the Rieske-type ferredoxin from Xanthobacter strain Py2 were recorded in both H2O and D2O buffered solutions at pH 7.2. Several well-resolved hyperfine-shifted 1H NMR signals were observed in the 90 to −20 ppm chemical shift range. Comparison of spectra recorded in H2O and D2O buffered solutions indicated that the signals at −11.4 (L) and −15.5 (M) ppm were solvent-exchangeable and thus were assigned to the two histidine Nε2H protons. The remaining observed signals were assigned based upon chemical shift, T1 values, and one-dimensional nuclear Overhauser effect (nOe) saturation transfer experiments to either CβH or CαH protons of cluster cysteinyl or histidine ligands. Upon oxidation of the [2Fe-2S] cluster, only two broad resonances were observed, indicating that the two Fe(III) ions are strongly antiferromagnetically coupled. In addition, the temperature dependence of each observed hyperfine-shifted signal in the reduced state was determined, providing information about the magnetic properties of the [2Fe-2S]1- cluster. Fits of the temperature data observed for each resonance to equations describing the hyperfine shift with their Boltzmann weighting factors provided a ΔEL value of 185 ± 26 cm-1 which, in turn, gives −2J as 124 cm-1. These data indicate that the two iron centers in the reduced [2Fe-2S] Rieske-type center are moderately antiferromagnetically coupled. The combination of these data with the available spectroscopic and crystallographic results for Rieske-type proteins has provided new insights into the role of the Rieske-type protein from Xanthobacter strain Py2 in alkene oxidation

Using an Instrumental Variable to Test for Unmeasured Confounding

An important concern in an observational study is whether or not there is unmeasured confounding, that is, unmeasured ways in which the treatment and control groups differ before treatment, which affect the outcome. We develop a test of whether there is unmeasured confounding when an instrumental variable (IV) is available. An IV is a variable that is independent of the unmeasured confounding and encourages a subject to take one treatment level versus another, while having no effect on the outcome beyond its encouragement of a certain treatment level. We show what types of unmeasured confounding can be tested for with an IV and develop a test for this type of unmeasured confounding that has correct type I error rate. We show that the widely used Durbin–Wu–Hausman test can have inflated type I error rates when there is treatment effect heterogeneity. Additionally, we show that our test provides more insight into the nature of the unmeasured confounding than the Durbin–Wu–Hausman test. We apply our test to an observational study of the effect of a premature infant being delivered in a high-level neonatal intensive care unit (one with mechanical assisted ventilation and high volume) versus a lower level unit, using the excess travel time a mother lives from the nearest high-level unit to the nearest lower-level unit as an IV

Selective Decline in Memory Function among Healthy Elderly

Objective: To use longitudinally acquired data to establish whether aging is associated with memory decline. Background: Memory loss is one of the most frequent complaints among the elderly. Nevertheless, age-related memory decline remains controversial in large part because it has been established with cross-sectional studies. Methods: A total of 212 community-based healthy people were followed prospectively and evaluated annually with a neuropsychological battery testing memory and other cognitive domains. To control for the learning effect—the improvement in test performance associated with repeated exposure—longitudinal performance was compared between two age groups. Results: The older age group displayed a relative decline in memory performance with time. In contrast to memory, a relative age-related decline was not observed in tests of language, visuospatial ability, and abstract reasoning. Furthermore, within the memory domain, age-related decline was restricted to a specific aspect of memory, manifesting only in a measure sensitive to the acquisition and early retrieval of new information, and not in a measure of memory retention. This profile of age-related cognitive decline anatomically localizes to the hippocampal formation. Conclusion: This study establishes age-related memory decline using longitudinal data, and shows that this decline does not occur diffusely across multiple cognitive domains. Both early AD as well as non-AD processes likely contribute to age-related memory decline, and continued follow-up may reveal distinguishing features between these two

Building a Stronger Instrument in an Observational Study of Perinatal Care for Premature Infants

An instrument is a random nudge toward acceptance of a treatment that affects outcomes only to the extent that it affects acceptance of the treatment. Nonetheless, in settings in which treatment assignment is mostly deliberate and not random, there may exist some essentially random nudges to accept treatment, so that use of an instrument might extract bits of random treatment assignment from a setting that is otherwise quite biased in its treatment assignments. An instrument is weak if the random nudges barely influence treatment assignment or strong if the nudges are often decisive in influencing treatment assignment. Although ideally an ostensibly random instrument is perfectly random and not biased, it is not possible to be certain of this; thus a typical concern is that even the instrument might be biased to some degree. It is known from theoretical arguments that weak instruments are invariably sensitive to extremely small biases; for this reason, strong instruments are preferred. The strength of an instrument is often taken as a given. It is not. In an evaluation of effects of perinatal care on the mortality of premature infants, we show that it is possible to build a stronger instrument, we show how to do it, and we show that success in this task is critically important. We also develop methods of permutation inference for effect ratios, a key component in an instrumental variable analysis