The effects of aging on the BTBR mouse model of autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex heterogeneous neurodevelopmental disorder characterized by alterations in social functioning, communicative abilities, and engagement in repetitive or restrictive behaviors. The process of aging in individuals with autism and related neurodevelopmental disorders is not well understood, despite the fact that the number of individuals with ASD aged 65 and older is projected to increase by over half a million individuals in the next 20 years. To elucidate the effects of aging in the context of a modified central nervous system, we investigated the effects of age on the BTBR T + tf/j mouse, a well characterized and widely used mouse model that displays an ASD-like phenotype. We found that a reduction in social behavior persists into old age in male BTBR T + tf/j mice. We employed quantitative proteomics to discover potential alterations in signaling systems that could regulate aging in the BTBR mice. Unbiased proteomic analysis of hippocampal and cortical tissue of BTBR mice compared to age-matched wild-type controls revealed a significant decrease in brain derived neurotrophic factor and significant increases in multiple synaptic markers (spinophilin, Synapsin I, PSD 95, NeuN), as well as distinct changes in functional pathways related to these proteins, including "Neural synaptic plasticity regulation" and "Neurotransmitter secretion regulation." Taken together, these results contribute to our understanding of the effects of aging on an ASD-like mouse model in regards to both behavior and protein alterations, though additional studies are needed to fully understand the complex interplay underlying aging in mouse models displaying an ASD-like phenotype.

IL-10-producing Regulatory B Cell Development in Human Autoimmune Disease

B cell abnormalities contribute to the development and progress of autoimmune disease. Traditionally, the role of B cells in autoimmune disease was thought to be predominantly limited to the production of autoantibodies. Nevertheless, in addition to autoantibody production, B cells have other functions potentially relevant to autoimmunity. Such functions include antigen presentation to and activation of T cells, expression of costimulatory molecules and cytokine production. Recently, the ability of B cells to negatively regulate cellular immune responses and inflammation has been described and the concept of “regulatory B cells” has emerged. A variety of cytokines produced by regulatory B cell subsets have been reported with interleukin-10 (IL-10) being the most studied. IL-10-producing regulatory B cells predominantly localize within a rare CD1dhiCD5+ B cell subset in mice and the CD24hiCD27+ B cell subset in adult humans. This specific IL-10-producing subset of regulatory B cells have been named “B10 cells” to highlight that the regulatory function of these rare B cells is primarily mediated by IL-10, and to distinguish them from other regulatory B cell subsets that regulate immune responses through different mechanisms. B10 cells have been studies in a variety of animal models with autoimmune disease and clinical settings of human autoimmunity. There are many unsolved questions related to B10 cells including their surface phenotype, their origin and development in vivo, and their role in autoimmunity.

In Chapter 3 of this dissertation, the role of the B cell receptor (BCR) in B10 cell development is highlighted. First, the BCR repertoire of mouse peritoneal cavity B10 cells is examined by single cell sequencing; peritoneal cavity B10 cells have clonally diverse germline BCRs that are predominantly unmutated. Second, mouse B10 cells are shown to have higher frequencies of λ+ BCRs compared to non-B10 cells which may indicate the involvement of BCR light chain editing early in the process of B10 cell development in vivo. Third, human peripheral blood B10 cells are examined and are also found to express higher frequencies of λ chains compared to non-b10 cells. Therefore, B10 cell BCRs are clonally diverse and enriched for unmutated germline sequences and λ light chains.

In Chapter 4 of this dissertation, B10 cells are examined in the healthy developing human across the entire age range of infancy, childhood and adolescence, and in a large cohort of children with autoimmunity. The study of B10 cells in the developing human documents a massive transient expansion during middle childhood when up to 30% of blood B cells were competent to produce IL-10. The surface phenotype of pediatric B10 cells was variable and reflective of overall B cell development. B10 cells down-regulated CD4+ T cell interferon-gamma (IFN-γ) production through IL-10-dependent pathways and IFN-γ inhibited whereas interleukin-21 (IL-21) promoted B cell IL-10 competency in vitro. Children with autoimmunity had a contracted B10 cell compartment, along with increased IFN-γ and decreased IL-21 serum levels compared to age-matched healthy controls. The decreased B10 cell frequencies and numbers in children with autoimmunity may be partially explained by the differential regulation of B10 cell development by IFN-γ and IL-21 and alterations in serum cytokine levels. The age-related changes of the B10 cell compartment during normal human development provide new insights into immune tolerance mechanisms involved in inflammation and autoimmunity.

These studies collectively demonstrate that BCR signals are the most important early determinant of B10 cell development in vivo, that human B10 cells are not a surface phenotype defined developmental B cell subset but a functionally defined regulatory B cell subset that regulates CD4+ T IFN-γ production through IL-10-dependent pathways and that human B10 cell development can be regulated by soluble factors in vivo such as the cytokine milieu. The findings of these studies provide new insights into immune tolerance mechanisms involved in human autoimmunity and the potent effects of IL-21 on human B cell IL-10 competence in vitro open new horizons in the development of autologous B10 cell-based therapies as an approach to treat human autoimmune disease in the future.

Inter-site and inter-scanner diffusion MRI data harmonization.

We propose a novel method to harmonize diffusion MRI data acquired from multiple sites and scanners, which is imperative for joint analysis of the data to significantly increase sample size and statistical power of neuroimaging studies. Our method incorporates the following main novelties: i) we take into account the scanner-dependent spatial variability of the diffusion signal in different parts of the brain; ii) our method is independent of compartmental modeling of diffusion (e.g., tensor, and intra/extra cellular compartments) and the acquired signal itself is corrected for scanner related differences; and iii) inter-subject variability as measured by the coefficient of variation is maintained at each site. We represent the signal in a basis of spherical harmonics and compute several rotation invariant spherical harmonic features to estimate a region and tissue specific linear mapping between the signal from different sites (and scanners). We validate our method on diffusion data acquired from seven different sites (including two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. Since the extracted rotation invariant spherical harmonic features depend on the accuracy of the brain parcellation provided by Freesurfer, we propose a feature based refinement of the original parcellation such that it better characterizes the anatomy and provides robust linear mappings to harmonize the dMRI data. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across multiple sites before and after data harmonization. We also show results using tract-based spatial statistics before and after harmonization for independent validation of the proposed methodology. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences can be accurately removed using the proposed method.