Zebrafish and mouse models for studying deubiquitinating enzyme genes as candidates for retinal dystrophies

[eng] The retina consists of several structured layers of highly specialized neurons that capture and process light stimuli enabling vision. Such a fine architecture turns retinal differentiation into an extremely complex event that must be accurately regulated. The ubiquitin-proteasome system (UPS) is considered one of the most dynamic and versatile mechanisms of protein regulation in eukaryotic cells. As ubiquitination is reversible, deubiquitinating enzymes (DUBs) play a major regulatory role in the UPS. Despite the importance of proteostasis and the UPS in health and disease, a more comprehensive in-depth analysis of DUB expression and function on particular tissues or organs, such as the retina, is still missing. Combining expression quantification, mRNA localization assays and functional analyses in animal and cellular models, we analyzed the function of several DUB genes in the retina to identify DUBs that regulate important retinal cell mechanisms, explore their relevance in retinal function in health and disease, and finally, posit them as new potential candidate genes for retinal dystrophies. Taking into consideration our results in the expression levels and pattern of DUBs in the retina, we first selected USP45 to perform functional assays in animal models in order to define its role and function in the retina. By morpholino-knockdown of usp45 in zebrafish embryos, our results showed moderate to severe eye morphological defects, eye size reduction, small body size with small tail or without tail, and disruption in notochord formation. There is also defective lamination and formation of the retinal structures, with no distinguishable layers and smaller retinas. Overall, our results supported the relevance of USP45 in the normal development and formation of the vertebrate retina, and we proposed this gene as a good candidate for causing hereditary retinal dystrophies, as later confirmed by other authors in several families. We also selected ATXN3, a DUB gene that causes the dominant polyQ disease Spinocerebellar ataxia type 3 (SCA3), and we aimed to analyze its function in the retina. We showed that depletion of Atxn3 in zebrafish and mice caused retinal morphological and functional alterations with photoreceptor outer segment elongation, cone opsin mislocalization, and cone hyperexcitation upon light stimuli. A pool of ATXN3 resides at the basal body and axoneme of the photoreceptor cilium, where it controls the levels and recruitment of the regulatory proteins KEAP1 and HDAC6. Abrogation of Atxn3 expression causes delayed phagosome maturation in the retinal pigment epithelium. We propose that ATXN3 regulates two relevant biological processes in the retina, ciliogenesis and phagocytosis, by modulating microtubule polymerization and microtubule-dependent retrograde transport, and propose ATXN3 as a causative or modifier gene in retinal/macular dystrophies. We further aimed to explore whether the SCA3 humanized mouse model showed specific retinal phenotype traits. We showed that polyQ-expanded ATXN3 protein formed a high number of progressive pathogenic aggregates in the retinal layers of transgenic Atxn3Q84 mice, and caused a decrease in the number of cone photoreceptors. Optical coherence tomography revealed a general decrease in the thickness of the retinal layers whereas retinal electrophysiological analyses showed a strong decrease in photoreceptor response to light, thus supporting severe retinal dysfunction in Atxn3Q84 mice. Similar analyses in human patients detected a correlation of retinal alterations with the number of CAG repeats and the age of onset of SCA3 symptoms. We propose that retinal alterations detected by non-invasive eye examination and electroretinography tests in SCA3 patients could serve as a valuable early-onset symptom and a biological marker of disease progression. As a conclusion, our work posits several DUB genes as candidates for inherited retinal dystrophies, but further investigation is needed to dissect the function of DUBs in retinal cell differentiation, photoreceptor function, and retinal homeostasis

Randomization tests for peer effects in group formation experiments

Measuring the effect of peers on individual outcomes is a challenging problem, in part because individuals often select peers who are similar in both observable and unobservable ways. Group formation experiments avoid this problem by randomly assigning individuals to groups and observing their responses; for example, do first-year students have better grades when they are randomly assigned roommates who have stronger academic backgrounds? Standard approaches for analyzing these experiments, however, are heavily model-dependent and generally fail to exploit the randomized design. In this paper, we extend methods from randomization-based testing under interference to group formation experiments. The proposed tests are justified by the randomization itself, require relatively few assumptions, and are exact in finite samples. First, we develop procedures that yield valid tests for arbitrary group formation designs. Second, we derive sufficient conditions on the design such that the randomization test can be implemented via simple random permutations. We apply this approach to two recent group formation experiments

Causal Inference When Counterfactuals Depend on the Proportion of All Subjects Exposed

The assumption that no subject's exposure affects another subject's outcome, known as the no-interference assumption, has long held a foundational position in the study of causal inference. However, this assumption may be violated in many settings, and in recent years has been relaxed considerably. Often this has been achieved with either the aid of a known underlying network, or the assumption that the population can be partitioned into separate groups, between which there is no interference, and within which each subject's outcome may be affected by all the other subjects in the group via the proportion exposed (the stratified interference assumption). In this paper, we instead consider a complete interference setting, in which each subject affects every other subject's outcome. In particular, we make the stratified interference assumption for a single group consisting of the entire sample. This can occur when the exposure is a shared resource whose efficacy is modified by the number of subjects among whom it is shared. We show that a targeted maximum likelihood estimator for the i.i.d.~setting can be used to estimate a class of causal parameters that includes direct effects and overall effects under certain interventions. This estimator remains doubly-robust, semiparametric efficient, and continues to allow for incorporation of machine learning under our model. We conduct a simulation study, and present results from a data application where we study the effect of a nurse-based triage system on the outcomes of patients receiving HIV care in Kenyan health clinics.Comment: 23 pages main article, 23 pages supplementary materials + references, 4 tables, 1 figur