Analyzing Clustered Data: Why and How to Account for Multiple Observations Nested within a Study Participant?

A conventional study design among medical and biological experimentalists involves col- lecting multiple measurements from a study subject. For example, experiments utilizing mouse models in neuroscience often involve collecting multiple neuron measurements per mouse to increase the number of observations without requiring a large number of mice. This leads to a form of statistical dependence referred to as clustering. Inappropriate analy- ses of clustered data have resulted in several recent critiques of neuroscience research that suggest the bar for statistical analyses within the field is set too low. We compare naïve ana- lytical approaches to marginal, fixed-effect, and mixed-effect models and provide guidelines for when each of these models is most appropriate based on study design. We demonstrate the influence of clustering on a between-mouse treatment effect, a within-mouse treatment effect, and an interaction effect between the two. Our analyses demonstrate that these sta- tistical approaches can give substantially different results, primarily when the analyses include a between-mouse treatment effect. In a novel analysis from a neuroscience per- spective, we also refine the mixed-effect approach through the inclusion of an aggregate mouse-level counterpart to a within-mouse (neuron level) treatment as an additional predic- tor by adapting an advanced modeling technique that has been used in social science research and show that this yields more informative results. Based on these findings, we emphasize the importance of appropriate analyses of clustered data, and we aim for this work to serve as a resource for when one is deciding which approach will work best for a given study

Fatty Acids Increase Neuronal Hypertrophy of Pten Knockdown Neurons

Phosphatase and tensin homolog (Pten) catalyzes the reverse reaction of PI3K by dephosphorylating PIP3 to PIP2. This negatively regulates downstream Akt/mTOR/S6 signaling resulting in decreased cellular growth and proliferation. Co-injection of a lentivirus knocking Pten down with a control lentivirus allows us to compare the effects of Pten knockdown between individual neurons within the same animal. We find that knockdown of Pten results in neuronal hypertrophy by 21 days post-injection. This neuronal hypertrophy is correlated with increased p-S6 and p-mTOR in individual neurons. We used this system to test whether an environmental factor that has been implicated in cellular hypertrophy could influence the severity of the Pten knockdown-induced hypertrophy. Implantation of mini-osmotic pumps delivering fatty acids results in increased neuronal hypertrophy and p-S6/p-mTOR staining. These hypertrophic effects were reversed in response to rapamycin treatment. However, we did not observe a similar increase in hypertrophy in response to dietary manipulations of fatty acids. Thus, we conclude that by driving growth signaling with fatty acids and knocking down a critical regulator of growth, Pten, we are able to observe an additive morphological phenotype of increased soma size mediated by the mTOR pathway

Analyzing Clustered Data: Why and How to Account for Multiple Observations Nested within a Study Participant?

A conventional study design among medical and biological experimentalists involves collecting multiple measurements from a study subject. For example, experiments utilizing mouse models in neuroscience often involve collecting multiple neuron measurements per mouse to increase the number of observations without requiring a large number of mice. This leads to a form of statistical dependence referred to as clustering. Inappropriate analyses of clustered data have resulted in several recent critiques of neuroscience research that suggest the bar for statistical analyses within the field is set too low. We compare naïve analytical approaches to marginal, fixed-effect, and mixed-effect models and provide guidelines for when each of these models is most appropriate based on study design. We demonstrate the influence of clustering on a between-mouse treatment effect, a within-mouse treatment effect, and an interaction effect between the two. Our analyses demonstrate that these statistical approaches can give substantially different results, primarily when the analyses include a between-mouse treatment effect. In a novel analysis from a neuroscience perspective, we also refine the mixed-effect approach through the inclusion of an aggregate mouse-level counterpart to a within-mouse (neuron level) treatment as an additional predictor by adapting an advanced modeling technique that has been used in social science research and show that this yields more informative results. Based on these findings, we emphasize the importance of appropriate analyses of clustered data, and we aim for this work to serve as a resource for when one is deciding which approach will work best for a given study

Fatty acids increase neuronal hypertrophy of Pten knockdown neurons

Phosphatase and tensin homolog (Pten) catalyzes the reverse reaction of PI3K by dephosphorylating PIP3 to PIP2. This negatively regulates downstream Akt/mTOR/S6 signaling resulting in decreased cellular growth and proliferation. Co-injection of a lentivirus knocking Pten down with a control lentivirus allows us to compare the effects of Pten knockdown between individual neurons within the same animal. We find that knockdown of Pten results in neuronal hypertrophy by 21 days post-injection. This neuronal hypertrophy is correlated with increased p-S6 and p-mTOR in individual neurons. We used this system to test whether an environmental factor that has been implicated in cellular hypertrophy could influence the severity of the Pten knockdown-induced hypertrophy. Implantation of mini-osmotic pumps delivering fatty acids results in increased neuronal hypertrophy and p-S6/p-mTOR staining. These hypertrophic effects were reversed in response to rapamycin treatment. However, we did not observe a similar increase in hypertrophy in response to dietary manipulations of fatty acids. Thus, we conclude that by driving growth signaling with fatty acids and knocking down a critical regulator of growth, Pten, we are able to observe an additive morphological phenotype of increased soma size mediated by the mTOR pathway

Visualization of clustered data.

<p>(A) Visualization of a between-mouse factor. Each point represents the mean soma size of a mouse ± standard error (SE). [SE = standard deviation (mean soma size)]. (B) Visualization of a within-mouse factor. Each point represents the soma size of an individual neuron within a mouse. The colors correspond to the mouse to which the neurons belonged. Each mouse has neurons with control and Pten shRNA. (C) Visualization of an interaction effect between the within-mouse and between-mouse factor. The red dotted line represents the vehicle control mice and the blue solid line represents the fatty acid delivery mice. Pten knockdown status 0 = control shRNA and 1 = Pten shRNA. The black dotted line depicts the expected result if there were no interaction effect, and the space between the black dotted line and the blue line, denoted by the curly bracket, represents the size of the interaction effect.</p

Main decision points for statistical analysis of clustered data.

<p>The flow chart outlines the primary questions researchers should address when weighing options of statistical research design of a study with clustered data. *Readers should refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146721#pone.0146721.t002" target="_blank">Table 2</a> for subtler differences between the marginal and mixed-effect model.</p

A Retroviral CRISPR-Cas9 System for Cellular Autism-Associated Phenotype Discovery in Developing Neurons

Retroviruses expressing a fluorescent protein, Cas9, and a small guide RNA are used to mimic nonsense PTEN mutations from autism patients in developing mouse neurons. We compare the cellular phenotype elicited by CRISPR-Cas9 to those elicited using shRNA or Cre/Lox technologies and find that knockdown or knockout (KO) produced a corresponding moderate or severe neuronal hypertrophy in all cells. In contrast, the Cas9 approach produced missense and nonsense Pten mutations, resulting in a mix of KO-equivalent hypertrophic and wild type-like phenotypes. Importantly, despite this mixed phenotype, the neuronal hypertrophy resulting from Pten loss was evident on average in the population of manipulated cells. Having reproduced the known Pten KO phenotype using the CRISPR-Cas9 system we design viruses to target a gene that has recently been associated with autism, KATNAL2. Katnal2 deletion in the mouse results in decreased dendritic arborization of developing neurons. We conclude that retroviral implementation of the CRISPR-Cas9 system is an efficient system for cellular phenotype discovery in wild-type animals

Transcription factor network analysis identifies REST/NRSF as an intrinsic regulator of CNS regeneration in mice.

The inability of neurons to regenerate long axons within the CNS is a major impediment to improving outcome after spinal cord injury, stroke, and other CNS insults. Recent advances have uncovered an intrinsic program that involves coordinate regulation by multiple transcription factors that can be manipulated to enhance growth in the peripheral nervous system. Here, we use a systems&nbsp;genomics approach to characterize regulatory relationships of regeneration-associated transcription factors, identifying RE1-Silencing Transcription Factor (REST; Neuron-Restrictive Silencer Factor, NRSF) as a predicted upstream suppressor of a pro-regenerative gene program associated with axon regeneration in the CNS. We validate our predictions using multiple paradigms, showing that mature mice bearing cell type-specific deletions of REST or expressing dominant-negative mutant REST show improved regeneration of the corticospinal tract and optic nerve after spinal cord injury and optic nerve crush, which is accompanied by upregulation of regeneration-associated genes in cortical motor neurons and retinal ganglion cells, respectively. These analyses identify a role for REST as an upstream suppressor of the intrinsic regenerative program in the CNS and demonstrate the utility of a systems biology approach involving integrative genomics and bio-informatics to prioritize hypotheses relevant to CNS repair