Consensus tissue domain detection in spatial omics data using multiplex image labeling with regional morphology (MILWRM).

Spatially resolved molecular assays provide high dimensional genetic, transcriptomic, proteomic, and epigenetic information in situ and at various resolutions. Pairing these data across modalities with histological features enables powerful studies of tissue pathology in the context of an intact microenvironment and tissue structure. Increasing dimensions across molecular analytes and samples require new data science approaches to functionally annotate spatially resolved molecular data. A specific challenge is data-driven cross-sample domain detection that allows for analysis within and between consensus tissue compartments across high volumes of multiplex datasets stemming from tissue atlasing efforts. Here, we present MILWRM (multiplex image labeling with regional morphology)-a Python package for rapid, multi-scale tissue domain detection and annotation at the image- or spot-level. We demonstrate MILWRM's utility in identifying histologically distinct compartments in human colonic polyps, lymph nodes, mouse kidney, and mouse brain slices through spatially-informed clustering in two different spatial data modalities from different platforms. We used tissue domains detected in human colonic polyps to elucidate the molecular distinction between polyp subtypes, and explored the ability of MILWRM to identify anatomical regions of the brain tissue and their respective distinct molecular profiles.

Mapping Individual Differences in Intermodal Coupling in Neurodevelopment.

Within-individual coupling between measures of brain structure and function evolves in development and may underlie differential risk for neuropsychiatric disorders. Despite increasing interest in the development of structure-function relationships, rigorous methods to quantify and test individual differences in coupling remain nascent. In this article, we explore and address gaps in approaches for testing and spatially localizing individual differences in intermodal coupling. We propose a new method, called CIDeR, which is designed to simultaneously perform hypothesis testing in a way that limits false positive results and improve detection of true positive results. Through a comparison across different approaches to testing individual differences in intermodal coupling, we delineate subtle differences in the hypotheses they test, which may ultimately lead researchers to arrive at different results. Finally, we illustrate the utility of CIDeR in two applications to brain development using data from the Philadelphia Neurodevelopmental Cohort.

Network enrichment significance testing in brain-phenotype association studies.

Functional networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about spatial properties of imaging data, leading to inflated false positive rates. We seek to address this gap in existing methodology by borrowing insight from a method widely used in genetics research for testing enrichment of associations between a set of genes and a phenotype of interest. We propose network enrichment significance testing (NEST), a flexible framework for testing the specificity of brain-phenotype associations to functional networks or other sub-regions of the brain. We apply NEST to study enrichment of associations with structural and functional brain imaging data from a large-scale neurodevelopmental cohort study.

Smaller anterior hippocampal subfields in the early stage of psychosis.

Hippocampal volume is smaller in schizophrenia, but it is unclear when in the illness the changes appear and whether specific regions (anterior, posterior) and subfields (CA1, CA2/3, dentate gyrus, subiculum) are affected. Here, we used a high-resolution T2-weighted sequence specialized for imaging hippocampal subfields to test the hypothesis that anterior CA1 volume is lower in early psychosis. We measured subfield volumes across hippocampal regions in a group of 90 individuals in the early stage of a non-affective psychotic disorder and 70 demographically similar healthy individuals. We observed smaller volume in the anterior CA1 and dentate gyrus subfields in the early psychosis group. Our findings support models that implicate anterior CA1 and dentate gyrus subfield deficits in the mechanism of psychosis.

In-hospital catatonia, delirium, and coma and mortality: Results from the delirium and catatonia prospective cohort investigation.

BACKGROUND: Catatonia, a form of acute brain dysfunction typically linked with severe affective and psychotic disorders, occurs in critical illness with delirium and coma. Delirium and coma are associated with mortality, though catatonia's relationship with mortality is unclear. We aim to describe whether catatonia, delirium, and coma are associated with mortality. METHODS: We enrolled a convenience cohort of critically ill adults (N = 378) at an academic medical center. We assessed catatonia, delirium, and coma using the Bush-Francis Catatonia Rating Scale, the Confusion Assessment Method for the Intensive Care Unit and the Richmond Agitation-Sedation Scale, respectively. We tested the associations between previous day brain dysfunction state occurrence with in-hospital and one-year mortality using multivariable time-dependent risk models. Additionally, we tested the association between brain dysfunction duration and one-year mortality. RESULTS: Catatonia was not associated with death on the day after diagnosis during hospitalization, and neither previous catatonia occurrence nor duration was associated with one-year mortality. Delirium was not associated with death on any day following diagnosis during hospitalization, and neither previous delirium occurrence nor duration was associated with one-year mortality. The occurrence of coma was associated with death on any day after diagnosis during hospitalization (HR 2.30,CI 1.19-4.44,p = 0.014), as well as through one year following hospital discharge (HR 1.68,CI 1.09-2.59,p = 0.02). CONCLUSIONS: Coma, but neither catatonia nor delirium, was associated with future day in-hospital and one-year mortality. More research is needed to understand catatonia's clinical impact. Delirium results differ from existing literature likely due to cohort demographics and size. Coma results highlight the prognostic significance of suppressed arousal while critically ill.

Network Enrichment Significance Testing in Brain-Phenotype Association Studies.

Functional networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about the spatial structure of imaging data, leading to inflated false positive rates. We seek to address this gap in existing methodology by borrowing insight from a method widely used in genomics research for testing enrichment of associations between a set of genes and a phenotype of interest. We propose Network Enrichment Significance Testing (NEST), a flexible framework for testing the specificity of brain-phenotype associations to functional networks or other sub-regions of the brain. We apply NEST to study phenotype associations with structural and functional brain imaging data from a large-scale neurodevelopmental cohort study.

Hippocampal Network Dysfunction in Early Psychosis: A 2-Year Longitudinal Study.

Background: Hippocampal abnormalities are among the most consistent findings in schizophrenia. Numerous studies have reported deficits in hippocampal volume, function, and connectivity in the chronic stage of illness. While hippocampal volume and function deficits are also present in the early stage of illness, there is mixed evidence of both higher and lower functional connectivity. Here, we use graph theory to test the hypothesis that hippocampal network connectivity is broadly lowered in early psychosis and progressively worsens over 2 years. Methods: We examined longitudinal resting-state functional connectivity in 140 participants (68 individuals in the early stage of psychosis, 72 demographically similar healthy control individuals). We used an anatomically driven approach to quantify hippocampal network connectivity at 2 levels: 1) a core hippocampal-medial temporal lobe cortex (MTLC) network; and 2) an extended hippocampal-cortical network. Group and time effects were tested in a linear mixed effects model. Results: Early psychosis patients showed elevated functional connectivity in the core hippocampal-MTLC network, but contrary to our hypothesis, did not show alterations within the broader hippocampal-cortical network. Hippocampal-MTLC network hyperconnectivity normalized longitudinally and predicted improvement in positive symptoms but was not associated with increasing illness duration. Conclusions: These results show abnormally elevated functional connectivity in a core hippocampal-MTLC network in early psychosis, suggesting that selectively increased hippocampal signaling within a localized cortical circuit may be a marker of the early stage of psychosis. Hippocampal-MTLC hyperconnectivity could have prognostic and therapeutic implications.

Clinical hypnosis can reduce lower urinary tract symptoms in individuals with chronic pain.

STUDY PURPOSE: Lower urinary tract symptoms (LUTS) can occur in chronic pain populations at high rates and drastically affect quality of life. Hypnosis is a nonpharmacological treatment used in chronic pain known to have beneficial implications to health outside of pain reduction. This study evaluated the potential for hypnosis to reduce LUTS in a sample of individuals with chronic pain, if baseline LUTS severity affected outcomes, and specific LUTS that may respond to hypnosis. METHODS: Sixty-four adults with chronic pain and LUTS at a level of detectable symptom change (American Urological Association Symptom Index, AUASI 3) participated in an 8-week group hypnosis protocol. Participants completed validated assessments of LUTS, pain, and overall functioning before, after, 3- and 6-months posttreatment. Linear mixed effects models assessed improvement in LUTS over time while accounting for known factors associated with outcome (e.g., age, gender). The interaction of baseline symptom severity and treatment assessed the potential effect of baseline symptoms on change scores. RESULTS: Participants experienced significant and meaningful improvements in LUTS following group hypnosis (p = 0.006). There was a significant interaction between baseline symptom severity and treatment (p < 0.001), such that those with severe symptoms experienced the most pronounced gains over time (e.g., an 8.8 point reduction). Gains increased over time for those with moderate and severe symptoms. Changes in LUT symptoms occurred independently of pain relief. CONCLUSIONS: This pilot study suggests hypnosis has the potential to drastically improve LUTS in individuals with chronic pain, even when pain reduction does not occur. Results provide initial evidence for the treatment potential of hypnosis in urologic pain (and possibly non-pain/benign) populations, with randomized trials needed for definitive outcomes.

Anterior hippocampal dysfunction in early psychosis: a 2-year follow-up study.

BACKGROUND: Cross-sectional studies indicate that hippocampal function is abnormal across stages of psychosis. Neural theories of psychosis pathophysiology suggest that dysfunction worsens with illness stage. Here, we test the hypothesis that hippocampal function is impaired in the early stage of psychosis and declines further over the next 2 years. METHODS: We measured hippocampal function over 2 years using a scene processing task in 147 participants (76 individuals in the early stage of a non-affective psychotic disorder and 71 demographically similar healthy control individuals). Two-year follow-up was completed in 97 individuals (50 early psychosis, 47 healthy control). Voxelwise longitudinal analysis of activation in response to scenes was carried out within a hippocampal region of interest to test for group differences at baseline and a group by time interaction. RESULTS: At baseline, we observed lower anterior hippocampal activation in the early psychosis group relative to the healthy control group. Contrary to our hypothesis, hippocampal activation remained consistent and did not show the predicted decline over 2 years in the early psychosis group. Healthy controls showed a modest reduction in hippocampal activation after 2 years. CONCLUSIONS: The results of this study suggest that hippocampal dysfunction in early psychosis does not worsen over 2 years and highlight the need for longer-term longitudinal studies.

Evaluation of resampling-based inference for topological features of neuroimages.

Many recent studies have demonstrated the inflated type 1 error rate of the original Gaussian random field (GRF) methods for inference of neuroimages and identified resampling (permutation and bootstrapping) methods that have better performance. There has been no evaluation of resampling procedures when using robust (sandwich) statistical images with different topological features (TF) used for neuroimaging inference. Here, we consider estimation of distributions TFs of a statistical image and evaluate resampling procedures that can be used when exchangeability is violated. We compare the methods using realistic simulations and study sex differences in life-span age-related changes in gray matter volume in the Nathan Kline Institute Rockland sample. We find that our proposed wild bootstrap and the commonly used permutation procedure perform well in sample sizes above 50 under realistic simulations with heteroskedasticity. The Rademacher wild bootstrap has fewer assumptions than the permutation and performs similarly in samples of 100 or more, so is valid in a broader range of conditions. We also evaluate the GRF-based pTFCE method and show that it has inflated error rates in samples less than 200. Our R package, pbj , is available on Github and allows the user to reproducibly implement various resampling-based group level neuroimage analyses.

Spatially-enhanced clusterwise inference for testing and localizing intermodal correspondence.

With the increasing availability of neuroimaging data from multiple modalities-each providing a different lens through which to study brain structure or function-new techniques for comparing, integrating, and interpreting information within and across modalities have emerged. Recent developments include hypothesis tests of associations between neuroimaging modalities, which can be used to determine the statistical significance of intermodal associations either throughout the entire brain or within anatomical subregions or functional networks. While these methods provide a crucial foundation for inference on intermodal relationships, they cannot be used to answer questions about where in the brain these associations are most pronounced. In this paper, we introduce a new method, called CLEAN-R, that can be used both to test intermodal correspondence throughout the brain and also to localize this correspondence. Our method involves first adjusting for the underlying spatial autocorrelation structure within each modality before aggregating information within small clusters to construct a map of enhanced test statistics. Using structural and functional magnetic resonance imaging data from a subsample of children and adolescents from the Philadelphia Neurodevelopmental Cohort, we conduct simulations and data analyses where we illustrate the high statistical power and nominal type I error levels of our method. By constructing an interpretable map of group-level correspondence using spatially-enhanced test statistics, our method offers insights beyond those provided by earlier methods.

Increased amplitude of hippocampal low frequency fluctuations in early psychosis: A two-year follow-up study.

Neuroimaging studies have revealed hippocampal hyperactivity in schizophrenia. In the early stage of the illness, hyperactivity is present in the anterior hippocampus and is thought to spread to other regions as the illness progresses. However, there is limited evidence for changes in basal hippocampal function following the onset of psychosis. Resting state functional MRI signal amplitude may be a proxy measure for increased metabolism and disrupted oscillatory activity, both consequences of an excitation/inhibition imbalance underlying hippocampal hyperactivity. Here, we used fractional amplitude of low frequency fluctuations (fALFF) to test the hypothesis of progressive hippocampal hyperactivity in a two-year longitudinal case-control study. We found higher fALFF in the anterior and posterior hippocampus of individuals in the early stage of non-affective psychosis at study entry. Contrary to our hypothesis of progressive hippocampal dysfunction, we found evidence for normalization of fALFF over time in psychosis. Our findings support a model in which hippocampal fALFF is a marker of psychosis vulnerability or acute illness state rather than an enduring feature of the illness.

Quantifying and correcting slide-to-slide variation in multiplexed immunofluorescence images.

MOTIVATION: Multiplexed imaging is a nascent single-cell assay with a complex data structure susceptible to technical variability that disrupts inference. These in situ methods are valuable in understanding cell-cell interactions, but few standardized processing steps or normalization techniques of multiplexed imaging data are available. RESULTS: We implement and compare data transformations and normalization algorithms in multiplexed imaging data. Our methods adapt the ComBat and functional data registration methods to remove slide effects in this domain, and we present an evaluation framework to compare the proposed approaches. We present clear slide-to-slide variation in the raw, unadjusted data and show that many of the proposed normalization methods reduce this variation while preserving and improving the biological signal. Furthermore, we find that dividing multiplexed imaging data by its slide mean, and the functional data registration methods, perform the best under our proposed evaluation framework. In summary, this approach provides a foundation for better data quality and evaluation criteria in multiplexed imaging. AVAILABILITY AND IMPLEMENTATION: Source code is provided at: https://github.com/statimagcoll/MultiplexedNormalization and an R package to implement these methods is available here: https://github.com/ColemanRHarris/mxnorm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Advanced Age Is Associated With Catatonia in Critical Illness: Results From the Delirium and Catatonia Prospective Cohort Investigation.

Introduction: Catatonia, characterized by motor, behavioral and affective abnormalities, frequently co-occurs with delirium during critical illness. Advanced age is a known risk factor for development of delirium. However, the association between age and catatonia has not been described. We aim to describe the occurrence of catatonia, delirium, and coma by age group in a critically ill, adult population. Design: Convenience cohort, nested within two clinical trials and two observational cohort studies. Setting: Intensive care units in an academic medical center in Nashville, TN. Patients: 378 critically ill adult patients on mechanical ventilation and/or vasopressors. Measurements and Main Results: Patients were assessed for catatonia, delirium, and coma by independent and blinded personnel, the Bush Francis Catatonia Rating Scale, the Confusion Assessment Method for the Intensive Care Unit (ICU) and the Richmond Agitation and Sedation Scale. Of 378 patients, 23% met diagnostic criteria for catatonia, 66% experienced delirium, and 52% experienced coma during the period of observation. There was no relationship found between age and catatonia severity or age and presence of specific catatonia items. The prevalence of catatonia was strongly associated with age in the setting of critical illness (p < 0.05). Delirium and comas' association with age was limited to the setting of catatonia. Conclusion: Given the significant relationship between age and catatonia independent of coma and delirium status, these data demonstrate catatonia's association with advanced age in the setting of critical illness. Future studies can explore the causative factors for this association and further elucidate the risk factors for acute brain dysfunction across the age spectrum.

A simple permutation-based test of intermodal correspondence.

Many key findings in neuroimaging studies involve similarities between brain maps, but statistical methods used to measure these findings have varied. Current state-of-the-art methods involve comparing observed group-level brain maps (after averaging intensities at each image location across multiple subjects) against spatial null models of these group-level maps. However, these methods typically make strong and potentially unrealistic statistical assumptions, such as covariance stationarity. To address these issues, in this article we propose using subject-level data and a classical permutation testing framework to test and assess similarities between brain maps. Our method is comparable to traditional permutation tests in that it involves randomly permuting subjects to generate a null distribution of intermodal correspondence statistics, which we compare to an observed statistic to estimate a p-value. We apply and compare our method in simulated and real neuroimaging data from the Philadelphia Neurodevelopmental Cohort. We show that our method performs well for detecting relationships between modalities known to be strongly related (cortical thickness and sulcal depth), and it is conservative when an association would not be expected (cortical thickness and activation on the n-back working memory task). Notably, our method is the most flexible and reliable for localizing intermodal relationships within subregions of the brain and allows for generalizable statistical inference.

Electronic Delivery of Pain Education for Chronic Overlapping Pain Conditions: A Prospective Cohort Study.

OBJECTIVE: To examine the impact of educational materials for chronic overlapping pain conditions (COPCs), the feasibility of delivering materials online, and to explore its impact on self-reported self-management applications at 3-month follow-up. DESIGN: Prospective cohort study. SETTING: Online. SUBJECTS: Individuals from a university-wide active research repository with ≥1 coded diagnostic COPC by ICD-9/10 in the medical record. METHODS: We determined the number of COPCs per participant as indicated by diagnostic codes in the medical record. Consenting participants completed self-report questionnaires and read educational materials. We assessed content awareness and knowledge pre- and post-exposure to education. Comprehension was assessed via embedded questions in reading materials in real time. Participants then completed assessments regarding concept retention, self-management engagement, and pain-related symptoms at 3-months. RESULTS: N = 216 individuals enrolled, with 181 (84%) completing both timepoints. Results indicated that participants understood materials. Knowledge and understanding of COPCs increased significantly after education and was retained at 3-months. Patient characteristics suggested the number of diagnosed COPCs was inversely related to age. Symptoms or self-management application did not change significantly over the 3-month period. CONCLUSIONS: The educational materials facilitated teaching of key pain concepts in self-management programs, which translated easily into an electronic format. Education alone may not elicit self-management engagement or symptom reduction in this population; however, conclusions are limited by the study's uncontrolled design. Education is likely an important and meaningful first step in comprehensive COPC self-management.

Improving the replicability of neuroimaging findings by thresholding effect sizes instead of p-values.

The classical approach for testing statistical images using spatial extent inference (SEI) thresholds the statistical image based on the p-value. This approach has an unfortunate consequence on the replicability of neuroimaging findings because the targeted brain regions are affected by the sample size-larger studies have more power to detect smaller effects. Here, we use simulations based on the preprocessed Autism Brain Imaging Data Exchange (ABIDE) to show that thresholding statistical images by effect sizes has more consistent estimates of activated regions across studies than thresholding by p-values. Using a constant effect size threshold means that the p-value threshold naturally scales with the sample size to ensure that the target set is similar across repetitions of the study that use different sample sizes. As a consequence of thresholding by the effect size, the type 1 and type 2 error rates go to zero as the sample size gets larger. We use a newly proposed robust effect size index that is defined for an arbitrary statistical image so that effect size thresholding can be used regardless of the test statistic or model.

Evidence for decreased parasympathetic response to a novel peer interaction in older children with autism spectrum disorder: a case-control study.

BACKGROUND: Individuals with autism spectrum disorder (ASD) often experience elevated stress during social interactions and may have difficulty forming and maintaining peer relationships. The autonomic nervous system (ANS) directs physiological changes in the body in response to a number of environmental stimuli, including social encounters. Evidence suggests the flexibility of the ANS response is an important driving factor in shaping social behavior. For youth with ASD, increased stress response and/or atypical ANS regulation to benign social encounters may therefore influence social behaviors, and, along with developmental and experiential factors, shape psychological outcomes. METHODS: The current study measured ANS response to a peer-based social interaction paradigm in 50 typically developing (TD) children and 50 children with ASD (ages 10-13). Respiratory sinus arrhythmia (RSA), a cardiac measure of parasympathetic influence on the heart, and pre-ejection period (PEP), a sympathetic indicator, were collected. Participants engaged in a friendly, face-to-face conversation with a novel, same-aged peer, and physiological data were collected continuously before and during the interaction. Participants also reported on state anxiety following the interaction, while parents reported on the child's social functioning and number of social difficulties. RESULTS: Linear mixed models revealed that, while there were no diagnostic effects for RSA or PEP, older youth with ASD appeared to demonstrate a blunted parasympathetic (RSA) response. Further, increased severity of parent-reported social symptoms was associated with lower RSA. Youth with ASD reported more anxiety following the interaction; however, symptoms were not related to RSA or PEP response based on linear mixed modeling. CONCLUSIONS: Physiological regulation, age, and social functioning likely influence stress responses to peer interactions for youth with ASD. Parasympathetic functioning, as opposed to sympathetic arousal, may be especially important in behavioral regulation, as older youth with ASD demonstrated atypical regulation and response to the social interaction paradigm. Future studies should help to further elucidate the developmental factors contributing to stress responses in ASD, the impact of physiological response on observable social behavior, and potential long-term consequences of chronic social stress in youth with ASD.