Early life experience influences stress reactivity and mental health through effects on cognitive-emotional functions that are, in part, linked to gene expression in the dorsal and ventral hippocampus. The hippocampal dentate gyrus (DG) is a major site for experience-dependent plasticity associated with sustained transcriptional alterations, potentially mediated by epigenetic modifications. Here, we report comprehensive DNA methylome, hydroxymethylome and transcriptome data sets from mouse dorsal and ventral DG. We find genome-wide transcriptional and methylation differences between dorsal and ventral DG, including at key developmental transcriptional factors. Peripubertal environmental enrichment increases hippocampal volume and enhances dorsal DG-specific differences in gene expression. Enrichment also enhances dorsal-ventral differences in DNA methylation, including at binding sites of the transcription factor NeuroD1, a regulator of adult neurogenesis. These results indicate a dorsal-ventral asymmetry in transcription and methylation that parallels well-known functional and anatomical differences, and that may be enhanced by environmental enrichment.

Author(s): Keown, Christopher Lee | Advisor(s): Mukamel, Eran A | Abstract: Developmental processes, genes and environmental factors interact to produce changes in cognition and behavior over the lifespan of an individual. However, the underlying molecular genetic mechanisms that mediate these changes remain to be fully elucidated. DNA methylation is an epigenetic mechanism that defines cell identity and helps regulate gene expression. DNA methylation is dynamic over development and has been shown to mediate experience-dependent changes, including those resulting from learning and memory and early life adversity. Although methylation mainly occurs at genomic cytosines in the CG dinucleotide context, methylation at non-CG sites was recently found in brain tissue. Non-CG methylation is specifically enriched in neurons and accumulates during the early childhood stages of brain development. The biological impact of non-CG methylation in regulating gene expression and regulating cellular function, if any, remains unclear. A major challenge for addressing this question is the complexity and scale of the DNA methylation landscape, which includes nearly one billion cytosines throughout the genome that are potential sites of modification in every cell. Targeted studies of specific candidate genes and genomic loci do not elucidate the overall configuration of the cellular epigenome. Techniques for comprehensively mapping the genome-wide distribution of DNA methylation are powerful, but they require sophisticated new computational methods of analysis that can reliably distinguish and statistically validate epigenomic differences related to developmental and environmental factors.In this thesis we develop new approaches to comprehensively analyze DNA methylation throughout the genome and with single base resolution in order to better characterize the role of CG methylation and elucidate the potential role of CH methylation in mammalian brain cells. First, we consider the impact of enriched early life (peri-pubertal) experience on DNA methylation and gene expression in the dentate gyrus of the hippocampus. In addition to its role in experience-dependent gene regulation, DNA methylation also plays a key role in innate developmental processes, including female X chromosome inactivation. We provide the first allele-specific DNA methylomes from the active and inactive X chromosomes in female brain, and use comprehensive genomic analyses to gain insight into the functional relationship between allele-specific DNA methylation and transcription. These two studies provide new evidence of the dynamic changes in DNA methylation in whole brain tissue caused by environmental and innate developmental factors. However, they do not address the heterogeneity of brain cell types, a hallmark of mammalian brain organization. To address the role of DNA methylation in brain cell diversity, we develop computational methods to analyze data from a new assay that measures single cell methylomes. Using these data, we show that brain cell methylomes can be clustered and used to assess neuronal heterogeneity in the frontal cortex of mouse and human. Upon clustering cells, we are able to gain insight into the role of methylation in the establishment and maintenance of cellular identity in neuronal types.Overall, this thesis adds to the increasing evidence that DNA methylation is a cell type-specific, dynamic epigenomic modification of brain cells that is impacted by, and may in turn help to regulate, neuronal development and adaptation. In addition, this thesis provides new computational methods for analyzing large-scale, whole-genome DNA methylation data sets and demonstrates their use in uncovering new insights into the mammalian brain epigenome.

DNA methylation at gene promoters in a CG context is associated with transcriptional repression, including at genes silenced on the inactive X chromosome in females. Non-CG methylation (mCH) is a distinct feature of the neuronal epigenome that is differentially distributed between males and females on the X chromosome. However, little is known about differences in mCH on the active (Xa) and inactive (Xi) X chromosomes because stochastic X-chromosome inactivation (XCI) confounds allele-specific epigenomic profiling. We used whole-genome bisulfite sequencing in a mouse model with nonrandom XCI to examine allele-specific DNA methylation in frontal cortex. Xi was largely devoid of mCH, whereas Xa contained abundant mCH similar to the male X chromosome and the autosomes. In contrast to the repressive association of DNA methylation at CG dinucleotides (mCG), mCH accumulates on Xi in domains with transcriptional activity, including the bodies of most genes that escape XCI and at the X-inactivation center, validating this epigenetic mark as a signature of transcriptional activity. Escape genes showing CH hypermethylation were the only genes with CG-hypomethylated promoters on Xi, a well-known mark of active transcription. Finally, we found extensive allele-specific mCH and mCG at autosomal imprinted regions, some with a negative correlation between methylation in the two contexts, further supporting their distinct functions. Our findings show that neuronal mCH functions independently of mCG and is a highly dynamic epigenomic correlate of allele-specific gene regulation.

The neural underpinnings of repetitive behaviors (RBs) in autism spectrum disorders (ASDs), ranging from cognitive to motor characteristics, remain unknown. We assessed RB symptomatology in 50 ASD and 52 typically developing (TD) children and adolescents (ages 8-17 years), examining intrinsic functional connectivity (iFC) of corticostriatal circuitry, which is important for reward-based learning and integration of emotional, cognitive and motor processing, and considered impaired in ASDs. Connectivity analyses were performed for three functionally distinct striatal seeds (limbic, frontoparietal and motor). Functional connectivity with cortical regions of interest was assessed for corticostriatal circuit connectivity indices and ratios, testing the balance of connectivity between circuits. Results showed corticostriatal overconnectivity of limbic and frontoparietal seeds, but underconnectivity of motor seeds. Correlations with RBs were found for connectivity between the striatal motor seeds and cortical motor clusters from the whole-brain analysis, and for frontoparietal/limbic and motor/limbic connectivity ratios. Division of ASD participants into high (n = 17) and low RB subgroups (n = 19) showed reduced frontoparietal/limbic and motor/limbic circuit ratios for high RB compared to low RB and TD groups in the right hemisphere. Results suggest an association between RBs and an imbalance of corticostriatal iFC in ASD, being increased for limbic, but reduced for frontoparietal and motor circuits.

The mammalian brain contains diverse neuronal types, yet we lack single-cell epigenomic assays that are able to identify and characterize them. DNA methylation is a stable epigenetic mark that distinguishes cell types and marks regulatory elements. We generated >6000 methylomes from single neuronal nuclei and used them to identify 16 mouse and 21 human neuronal subpopulations in the frontal cortex. CG and non-CG methylation exhibited cell type-specific distributions, and we identified regulatory elements with differential methylation across neuron types. Methylation signatures identified a layer 6 excitatory neuron subtype and a unique human parvalbumin-expressing inhibitory neuron subtype. We observed stronger cross-species conservation of regulatory elements in inhibitory neurons than in excitatory neurons. Single-nucleus methylomes expand the atlas of brain cell types and identify regulatory elements that drive conserved brain cell diversity.

Objective: The objective of this study was to determine whether functional connectivity of the amygdala is altered in preschool-age children with autism spectrum disorder (ASD) and to assess the clinical relevance of observed alterations in amygdala connectivity.Method: A resting-state functional connectivity magnetic resonance imaging study of the amygdala (and a parallel study of primary visual cortex) was conducted in 72 boys (mean age 3.5 years; n = 43 with ASD; n = 29 age-matched controls).Results: The ASD group showed significantly weaker connectivity between the amygdala and several brain regions involved in social communication and repetitive behaviors, including bilateral medial prefrontal cortex, temporal lobes, and striatum (p < .05, corrected). Weaker connectivity between the amygdala and frontal and temporal lobes was significantly correlated with increased autism severity in the ASD group (p < .05). In a parallel analysis examining the functional connectivity of primary visual cortex, the ASD group showed significantly weaker connectivity between visual cortex and sensorimotor regions (p < .05, corrected). Weaker connectivity between visual cortex and sensorimotor regions was not correlated with core autism symptoms, but instead was correlated with increased sensory hypersensitivity in the visual/auditory domain (p < .05).Conclusion: These findings indicate that preschool-age children with ASD have disrupted functional connectivity between the amygdala and regions of the brain important for social communication and language, which might be clinically relevant because weaker connectivity was associated with increased autism severity. Moreover, although amygdala connectivity was associated with behavioral domains that are diagnostic of ASD, altered connectivity of primary visual cortex was related to sensory hypersensitivity.

BACKGROUND: Despite abundant evidence of brain network anomalies in autism spectrum disorder (ASD), findings have varied from broad functional underconnectivity to broad overconnectivity. Rather than pursuing overly simplifying general hypotheses (i.e., under vs. over), we tested the hypothesis of atypical network distribution in ASD (i.e., the participation of unusual loci in distributed functional networks).METHODS: We used a selective high-quality data subset from the Autism Brain Imaging Data Exchange (including 111 ASD and 174 typically developing participants) and several graph theory metrics. Resting state functional magnetic resonance imaging data were preprocessed and analyzed for the detection of low-frequency intrinsic signal correlations. Groups were tightly matched for available demographics and head motion.RESULTS: As hypothesized, the Rand index (reflecting how similar network organization was to a normative set of networks) was significantly lower in participants with ASD compared with typically developing participants. This was accounted for by globally reduced cohesion and density but increased dispersion of networks. While differences in hub architecture did not survive correction, rich club connectivity (among the hubs) was increased in the ASD group.CONCLUSIONS: Our findings support the model of reduced network integration (i.e., connectivity within networks) and differentiation (or segregation; based on connectivity outside network boundaries) in ASD. While the findings were applied at the global level, they were not equally robust across all networks and in one case (i.e., greater cohesion within ventral attention network in ASD) even reversed.

Autism spectrum disorder (ASD) is characterized by atypical brain network organization, but findings have been inconsistent. While methodological and maturational factors have been considered, the network specificity of connectivity abnormalities remains incompletely understood. We investigated intrinsic functional connectivity (iFC) for four "core" functional networks-default-mode (DMN), salience (SN), and left (lECN) and right executive control (rECN). Resting-state functional MRI data from 75 children and adolescents (37 ASD, 38 typically developing [TD]) were included. Functional connectivity within and between networks was analyzed for regions of interest (ROIs) and whole brain, compared between groups, and correlated with behavioral scores. ROI analyses showed overconnectivity (ASD > TD), especially between DMN and ECN. Whole-brain results were mixed. While predominant overconnectivity was found for DMN (posterior cingulate seed) and rECN (right inferior parietal seed), predominant underconnectivity was found for SN (right anterior insula seed) and lECN (left inferior parietal seed). In the ASD group, reduced SN integrity was associated with sensory and sociocommunicative symptoms. In conclusion, atypical connectivity in ASD is network-specific, ranging from extensive overconnectivity (DMN, rECN) to extensive underconnectivity (SN, lECN). Links between iFC and behavior differed between groups. Core symptomatology in the ASD group was predominantly related to connectivity within the salience network.

Despite consensus on the neurological nature of autism spectrum disorders (ASD), brain biomarkers remain unknown and diagnosis continues to be based on behavioral criteria. Growing evidence suggests that brain abnormalities in ASD occur at the level of interconnected networks; however, previous attempts using functional connectivity data for diagnostic classification have reached only moderate accuracy. We selected 252 low-motion resting-state functional MRI (rs-fMRI) scans from the Autism Brain Imaging Data Exchange (ABIDE) including typically developing (TD) and ASD participants (n = 126 each), matched for age, non-verbal IQ, and head motion. A matrix of functional connectivities between 220 functionally defined regions of interest was used for diagnostic classification, implementing several machine learning tools. While support vector machines in combination with particle swarm optimization and recursive feature elimination performed modestly (with accuracies for validation datasets <70%), diagnostic classification reached a high accuracy of 91% with random forest (RF), a nonparametric ensemble learning method. Among the 100 most informative features (connectivities), for which this peak accuracy was achieved, participation of somatosensory, default mode, visual, and subcortical regions stood out. Whereas some of these findings were expected, given previous findings of default mode abnormalities and atypical visual functioning in ASD, the prominent role of somatosensory regions was remarkable. The finding of peak accuracy for 100 interregional functional connectivities further suggests that brain biomarkers of ASD may be regionally complex and distributed, rather than localized.

BACKGROUND: The cerebellum plays important roles in sensori-motor and supramodal cognitive functions. Cellular, volumetric, and functional abnormalities of the cerebellum have been found in autism spectrum disorders (ASD), but no comprehensive investigation of cerebro-cerebellar connectivity in ASD is available.METHODS: We used resting-state functional connectivity magnetic resonance imaging in 56 children and adolescents (28 subjects with ASD, 28 typically developing subjects) 8-17 years old. Partial and total correlation analyses were performed for unilateral regions of interest (ROIs), distinguished in two broad domains as sensorimotor (premotor/primary motor, somatosensory, superior temporal, and occipital) and supramodal (prefrontal, posterior parietal, and inferior and middle temporal).RESULTS: There were three main findings: 1) Total correlation analyses showed predominant cerebro-cerebellar functional overconnectivity in the ASD group; 2) partial correlation analyses that emphasized domain specificity (sensori-motor vs. supramodal) indicated a pattern of robustly increased connectivity in the ASD group (compared with the typically developing group) for sensori-motor ROIs but predominantly reduced connectivity for supramodal ROIs; and 3) this atypical pattern of connectivity was supported by significantly increased noncanonical connections (between sensori-motor cerebral and supramodal cerebellar ROIs and vice versa) in the ASD group.CONCLUSIONS: Our findings indicate that sensori-motor intrinsic functional connectivity is atypically increased in ASD, at the expense of connectivity supporting cerebellar participation in supramodal cognition.

IMPORTANCE Converging evidence indicates that brain abnormalities in autism spectrum disorder (ASD) involve atypical network connectivity, but it is unclear whether altered connectivity is especially prominent in brain networks that participate in social cognition. OBJECTIVE To investigate whether adolescents with ASD show altered functional connectivity in 2 brain networks putatively impaired in ASD and involved in social processing, theory of mind (ToM) and mirror neuron system (MNS). DESIGN, SETTING, AND PARTICIPANTS Cross-sectional study using resting-state functional magnetic resonance imaging involving 25 adolescents with ASD between the ages of 11 and 18 years and 25 typically developing adolescents matched for age, handedness, and nonverbal IQ. MAIN OUTCOMES AND MEASURES Statistical parametric maps testing the degree of whole-brain functional connectivity and social functioning measures. RESULTS Relative to typically developing controls, participants with ASD showed a mixed pattern of both over- and underconnectivity in the ToM network, which was associated with greater social impairment. Increased connectivity in the ASD group was detected primarily between the regions of the MNS and ToM, and was correlated with sociocommunicative measures, suggesting that excessive ToM-MNS cross talk might be associated with social impairment. In a secondary analysis comparing a subset of the 15 participants with ASD with the most severe symptomology and a tightly matched subset of 15 typically developing controls, participants with ASD showed exclusive overconnectivity effects in both ToM and MNS networks, which were also associated with greater social dysfunction. CONCLUSIONS AND RELEVANCE Adolescents with ASD showed atypically increased functional connectivity involving the mentalizing and mirror neuron systems, largely reflecting greater cross talk between the 2. This finding is consistent with emerging evidence of reduced network segregation in ASD and challenges the prevailing theory of general long-distance underconnectivity in ASD. This excess ToM-MNS connectivity may reflect immature or aberrant developmental processes in 2 brain networks involved in understanding of others, a domain of impairment in ASD. Further, robust links with sociocommunicative symptoms of ASD implicate atypically increased ToM-MNS connectivity in social deficits observed in ASD.

Growing evidence suggests that Autism Spectrum Disorder (ASD) involves abnormalities of multiple functional networks. Neuroimaging studies of ASD have therefore increasingly focused on connectivity. Many functional connectivity (fcMRI) studies have reported network underconnectivity in children and adults with ASD. However, there are notable inconsistencies, with some studies reporting overconnectivity. A previous literature survey suggested that a few methodological factors play a crucial role in differential fcMRI outcomes. Using three ASD data sets (two task-related, one resting state) from 54 ASD and 51 typically developing (TD) participants (ages 9-18 years), we examined the impact of four methodological factors: type of pipeline (co-activation vs. intrinsic analysis, related to temporal filtering and removal of task-related effects), seed selection, field of view (whole brain vs. limited ROIs), and dataset. Significant effects were found for type of pipeline, field of view, and dataset. Notably, for each dataset results ranging from robust underconnectivity to robust overconnectivity were detected, depending on the type of pipeline, with intrinsic fcMRI analyses (low bandpass filter and task regressor) predominantly yielding overconnectivity in ASD, but co-activation analyses (no low bandpass filter or task removal) mostly generating underconnectivity findings. These results suggest that methodological variables have dramatic impact on group differences reported in fcMRI studies. Improved awareness of their implications appears indispensible in fcMRI studies when inferences about "underconnectivity" or "overconnectivity" in ASD are made. In the absence of a gold standard for functional connectivity, the combination of different methodological approaches promises a more comprehensive understanding of connectivity in ASD.

The oncomir microRNA-125b (miR-125b) is upregulated in a variety of human neoplastic blood disorders and constitutive upregulation of miR-125b in mice can promote myeloid and B-cell leukemia. We found that miR-125b promotes myeloid and B-cell neoplasm by inducing tumorigenesis in hematopoietic progenitor cells. Our study demonstrates that miR-125b induces myeloid leukemia by enhancing myeloid progenitor output from stem cells as well as inducing immortality, self-renewal, and tumorigenesis in myeloid progenitors. Through functional and genetic analyses, we demonstrated that miR-125b induces myeloid and B-cell leukemia by inhibiting interferon regulatory factor 4 (IRF4) but through distinct mechanisms; it induces myeloid leukemia through repressing IRF4 at the messenger RNA (mRNA) level without altering the genomic DNA and induces B-cell leukemia via genetic deletion of the gene encoding IRF4.

While the literature on aberrant long-distance connectivity in autism spectrum disorder (ASD) has grown fast over the past decade, little is known about local connectivity. We used regional homogeneity and local density approaches at different spatial scales to examine local connectivity in 29 children and adolescents with ASD and 29 matched typically developing participants, using resting state functional magnetic resonance imaging data. Across a total of 12 analysis pipelines, the gross pattern of between-group findings was overall stable, with local overconnectivity in the ASD group in occipital and posterior temporal regions and underconnectivity in middle/posterior cingulate, and medial prefrontal regions. This general pattern was confirmed in secondary analyses for low-motion subsamples (n = 20 per group), in which time series segments with >0.25 mm head motion were censored, as well as in an analysis including global signal regression. Local overconnectivity in visual regions appears consistent with preference for local over global visual processing previously reported in ASD, whereas cingulate and medial frontal underconnectivity may relate to aberrant function within the default mode network.

Although growing evidence indicates atypical long-distance connectivity in autism spectrum disorder (ASD), much less is known about local connectivity, despite conjectures that local overconnectivity may be causally involved in the disorder. Using functional connectivity MRI and graph theory, we found that local functional connectivity was atypically increased in adolescents with ASD in temporo-occipital regions bilaterally. Posterior overconnectivity was found to be associated with higher ASD symptom severity, whereas an ASD subsample with low severity showed frontal underconnectivity. The findings suggest links between symptomatology and local connectivity, which vary within the autism spectrum.

We demonstrate the use of support vector machine methods to classify autism neuroimaging data collected from multiple sites.

Evaluation of: Anderson JS, Nielsen JA, Froehlich AL et al. Functional connectivity magnetic resonance imaging classification of autism. Brain 134, 3742-3754 (2011). This study used functional connectivity detected from low-frequency fluctuations in functional MRI time series acquired during a resting state. Participants were adolescents and adults with autism spectrum disorder (ASD) and typically developing controls. Classification scores were used to predict group membership based on functional connectivity for a large number of regions of interest across the whole brain. Diagnostic prediction accuracy was approximately 75% overall. The results contribute to current knowledge of functional connectivit y abnormalities in ASD, generally in support of underconnectivity theories. They are also promising with respect to the search for biomarkers of ASD that are needed to replace current behavior-based diagnostic criteria. While data from young children were not available for this study, findings appear to suggest that functional connectivity signatures may be more distinctively abnormal in children compared to adults with ASD.

Background: Socio-communicative impairments are salient features of autism spectrum disorder (ASD). Abnormal development of posterior superior temporal sulcus (pSTS)-a key processing area for language, biological motion, and social context-could play a role in these deficits.Methods: Functional connectivity magnetic resonance imaging was used to examine the synchronization of low-frequency blood oxygen level-dependent fluctuations during continuous performance on a visual search task. Twenty-one children and adolescents with ASD and 26 typically developing individuals-matched on age and IQ-participated in the study. Three subregions of pSTS were delineated with a data-driven approach, and differentiation of pSTS was examined by comparing the connectivity of each subregion.Results: In typically developing individuals, differentiation of networks was positively associated with age and anatomical maturation (cortical thinning in pSTS, greater white matter volume). In the ASD group, differentiation of pSTS connectivity was significantly reduced, and correlations with anatomical measures were weak or absent. Moreover, pSTS differentiation was inversely correlated with autism symptom severity.Conclusions: Atypical maturation of pSTS suggests altered trajectories for functional segregation and integration of networks in ASD, potentially related to impaired cognitive and sensorimotor development. Furthermore, our findings provide a novel explanation for atypically increased connectivity in ASD that has been observed in some functional connectivity magnetic resonance imaging studies.