@article {797, title = {Biomarkers of vascular calcification and mortality in patients with ESRD.}, journal = {Clin J Am Soc Nephrol}, volume = {9}, year = {2014}, month = {2014 Apr}, pages = {745-55}, abstract = {

BACKGROUND: Vascular calcification is common among patients undergoing dialysis and is associated with mortality. Factors such as osteoprotegerin (OPG), osteopontin (OPN), bone morphogenic protein-7 (BMP-7), and fetuin-A are involved in vascular calcification.

DESIGN, SETTING, PARTICIPANTS, \& MEASUREMENTS: OPG, OPN, BMP-7, and fetuin-A were measured in blood samples from 602 incident dialysis patients recruited from United States dialysis centers between 1995 and 1998 as part of the Choices for Healthy Outcomes In Caring for ESRD Study. Their association with all-cause and cardiovascular mortality were assessed using Cox proportional hazards models adjusted for demographic characteristics, comorbidity, serum phosphate, and calcium. An interaction with diabetes was tested because of its known association with vascular calcification. Predictive accuracy of selected biomarkers was explored by C-statistics in nested models with training and validation subcohorts.

RESULTS: Higher OPG and lower fetuin-A levels were associated with higher mortality over up to 13 years of follow-up (median, 3.4 years). The adjusted hazard ratios (HR) for highest versus lowest tertile were 1.49 (95\% confidence interval [95\% CI], 1.08 to 2.06) for OPG and 0.69 (95\% CI, 0.52 to 0.92) for fetuin-A. In stratified models, the highest tertile of OPG was associated with higher mortality among patients without diabetes (HR, 2.42; 95\% CI, 1.35 to 4.34), but not patients with diabetes (HR, 1.26; 95\% CI, 0.82 to 1.93; P for interaction=0.001). In terms of cardiovascular mortality, higher fetuin-A was associated with lower risk (HR, 0.85 per 0.1 g/L: 95\% CI, 0.75 to 0.96). In patients without diabetes, higher OPG was associated with greater risk (HR for highest versus lowest tertile, 2.91; 95\% CI, 1.06 to 7.99), but not in patients with diabetes or overall. OPN and BMP-7 were not independently associated with outcomes overall. The addition of OPG and fetuin-A did not significantly improve predictive accuracy of mortality.

CONCLUSIONS: OPG and fetuin-A may be risk factors for all-cause and cardiovascular mortality in patients undergoing dialysis, but do not improve risk prediction.

}, issn = {1555-905X}, doi = {10.2215/CJN.05450513}, author = {Scialla, Julia J and Kao, W H Linda and Crainiceanu, Ciprian and Sozio, Stephen M and Oberai, Pooja C and Shafi, Tariq and Coresh, Josef and Powe, Neil R and Plantinga, Laura C and Jaar, Bernard G and Parekh, Rulan S} } @article {831, title = {Disruption of functional organization within the primary motor cortex in children with autism.}, journal = {Hum Brain Mapp}, volume = {35}, year = {2014}, month = {2014 Feb}, pages = {567-80}, abstract = {

Accumulating evidence suggests that motor impairments are prevalent in autism spectrum disorder (ASD), relate to the social and communicative deficits at the core of the diagnosis and may reflect abnormal connectivity within brain networks underlying motor control and learning. Parcellation of resting-state functional connectivity data using spectral clustering approaches has been shown to be an effective means of visualizing functional organization within the brain but has most commonly been applied to explorations of normal brain function. This article presents a parcellation of a key area of the motor network, the primary motor cortex (M1), a key area of the motor control network, in adults, typically developing (TD) children and children with ASD and introduces methods for selecting the number of parcels, matching parcels across groups and testing group differences. The parcellation is based solely on patterns of connectivity between individual M1 voxels and all voxels outside of M1, and within all groups, a gross dorsomedial to ventrolateral organization emerged within M1 which was left-right symmetric. Although this gross organizational scheme was present in both groups of children, statistically significant group differences in the size and segregation of M1 parcels within regions of the motor homunculus corresponding to the upper and lower limbs were observed. Qualitative comparison of the M1 parcellation for children with ASD with that of younger and older TD children suggests that these organizational differences, with a lack of differentiation between lower limb/trunk regions and upper limb/hand regions, may be due, at least in part, to a delay in functional specialization within the motor cortex.

}, keywords = {Adult, Autistic Disorder, brain mapping, Child, Developmental Disabilities, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Motor Cortex, Oxygen, Young Adult}, issn = {1097-0193}, doi = {10.1002/hbm.22188}, author = {Nebel, Mary Beth and Joel, Suresh E and Muschelli, John and Barber, Anita D and Caffo, Brian S and Pekar, James J and Mostofsky, Stewart H} } @article {793, title = {Multilevel sparse functional principal component analysis.}, journal = {Stat}, volume = {3}, year = {2014}, month = {2014 Jan 29}, pages = {126-143}, abstract = {

We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.

}, issn = {0038-9986}, doi = {10.1002/sta4.50}, author = {Di, Chongzhi and Crainiceanu, Ciprian M and Jank, Wolfgang S} } @article {786, title = {Statistical normalization techniques for magnetic resonance imaging.}, journal = {Neuroimage Clin}, volume = {6}, year = {2014}, month = {2014}, pages = {9-19}, abstract = {

While computed tomography and other imaging techniques are measured in absolute units with physical meaning, magnetic resonance images are expressed in arbitrary units that are difficult to interpret and differ between study visits and subjects. Much work in the image processing literature on intensity normalization has focused on histogram matching and other histogram mapping techniques, with little emphasis on normalizing images to have biologically interpretable units. Furthermore, there are no formalized principles or goals for the crucial comparability of image intensities within and across subjects. To address this, we propose a set of criteria necessary for the normalization of images. We further propose simple and robust biologically motivated normalization techniques for multisequence brain imaging that have the same interpretation across acquisitions and satisfy the proposed criteria. We compare the performance of different normalization methods in thousands of images of patients with Alzheimer{\textquoteright}s disease, hundreds of patients with multiple sclerosis, and hundreds of healthy subjects obtained in several different studies at dozens of imaging centers.

}, issn = {2213-1582}, doi = {10.1016/j.nicl.2014.08.008}, author = {Shinohara, Russell T and Sweeney, Elizabeth M and Goldsmith, Jeff and Shiee, Navid and Mateen, Farrah J and Calabresi, Peter A and Jarso, Samson and Pham, Dzung L and Reich, Daniel S and Crainiceanu, Ciprian M} } @article {806, title = {Acute lesions that impair affective empathy.}, journal = {Brain}, volume = {136}, year = {2013}, month = {2013 Aug}, pages = {2539-49}, abstract = {

Functional imaging studies of healthy participants and previous lesion studies have provided evidence that empathy involves dissociable cognitive functions that rely on at least partially distinct neural networks that can be individually impaired by brain damage. These studies converge in support of the proposal that affective empathy--making inferences about how another person feels--engages at least the following areas: prefrontal cortex, orbitofrontal gyrus, anterior insula, anterior cingulate cortex, temporal pole, amygdala and temporoparietal junction. We hypothesized that right-sided lesions to any one of these structures, except temporoparietal junction, would cause impaired affective empathy (whereas bilateral damage to temporoparietal junction would be required to disrupt empathy). We studied 27 patients with acute right hemisphere ischaemic stroke and 24 neurologically intact inpatients on a test of affective empathy. Acute impairment of affective empathy was associated with infarcts in the hypothesized network, particularly temporal pole and anterior insula. All patients with impaired affective empathy were also impaired in comprehension of affective prosody, but many patients with impairments in prosodic comprehension had spared affective empathy. Patients with impaired affective empathy were older, but showed no difference in performance on tests of hemispatial neglect, volume of infarct or sex distribution compared with patients with intact affective empathy.

}, keywords = {Adult, Aged, Brain, Brain Ischemia, brain mapping, Cognition, Emotions, Empathy, Female, Functional Laterality, Humans, Male, Middle Aged, Nerve Net, Social Perception, Stroke}, issn = {1460-2156}, doi = {10.1093/brain/awt177}, author = {Leigh, Richard and Oishi, Kenichi and Hsu, John and Lindquist, Martin and Gottesman, Rebecca F and Jarso, Samson and Crainiceanu, Ciprian and Mori, Susumu and Hillis, Argye E} } @article {801, title = {Quantification of multiple-sclerosis-related brain atrophy in two heterogeneous MRI datasets using mixed-effects modeling.}, journal = {Neuroimage Clin}, volume = {3}, year = {2013}, month = {2013}, pages = {171-9}, abstract = {

Brain atrophy, measured by MRI, has been proposed as a useful surrogate marker for disease progression in multiple sclerosis (MS). However, it is conventionally assumed that the accurate quantification of brain atrophy is made difficult, if not impossible, by changes in the parameters of the MRI acquisition, which are almost inevitable over the course of a longitudinal study since MRI technology changes rapidly. This state of affairs can negatively affect clinical trial design and limit the use of historical data. Here, we investigate whether we can coherently estimate brain atrophy rates in a heterogeneous MS sample via linear mixed-effects multivariable regression, incorporating three critical assumptions: (1) using age at time of scanning, rather than time since baseline, as the regressor of interest; (2) scanning individuals with a variety of techniques; and (3) introducing a simple additive correction for major differences in MRI protocol. We fit the model to several measures of brain volume as the outcome in two MS populations: 1123 scans from 195 cases acquired for over approximately 7~years in two natural history protocols (Cohort 1), and 1331 scans from 69 cases seen for over 11~years who were primarily treated with two specific MS disease-modifying therapies (Cohort 2). We compared the mixed-effects model with additive correction for MRI acquisition parameters to a model fit without this correction and performed sample-size calculations to provide an estimate of the number of participants in an MS clinical trial that might be required to see a therapeutic effect of treatment using the approach described here. The results show that without the additive correction for T1-weighted protocol parameters, atrophy was underestimated and subject-specific estimates were more narrowly distributed about the population mean. Ventricular CSF is the most consistently estimated brain volume, with a mean of 2.8\%/year increase in Cohort 1 and 4.4\%/year increase in Cohort 2. An interesting observation was that gray matter volume decreased and white matter volume remained essentially unchanged in both cohorts, suggesting that changes in ventricular CSF volume are a surrogate for changes in gray matter volume. In conclusion, the mixed-effects modeling framework presented here allows effective use of heterogeneously acquired and historical data in the study of brain atrophy in MS, potentially simplifying the design of future single- and multi-site clinical trials and natural history studies.

}, issn = {2213-1582}, doi = {10.1016/j.nicl.2013.08.001}, author = {Jones, Blake C and Nair, Govind and Shea, Colin D and Crainiceanu, Ciprian M and Cortese, Irene C M and Reich, Daniel S} } @article {827, title = {Analysis of group ICA-based connectivity measures from fMRI: application to Alzheimer{\textquoteright}s disease.}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e49340}, abstract = {

Functional magnetic resonance imaging (fMRI) is a powerful tool for the in vivo study of the pathophysiology of brain disorders and disease. In this manuscript, we propose an analysis stream for fMRI functional connectivity data and apply it to a novel study of Alzheimer{\textquoteright}s disease. In the first stage, spatial independent component analysis is applied to group fMRI data to obtain common brain networks (spatial maps) and subject-specific mixing matrices (time courses). In the second stage, functional principal component analysis is utilized to decompose the mixing matrices into population-level eigenvectors and subject-specific loadings. Inference is performed using permutation-based exact logistic regression for matched pairs data. The method is applied to a novel fMRI study of Alzheimer{\textquoteright}s disease risk under a verbal paired associates task. We found empirical evidence of alternative ICA-based metrics of connectivity when comparing subjects evidencing mild cognitive impairment relative to carefully matched controls.

}, keywords = {Aged, Algorithms, Alzheimer Disease, Brain, brain mapping, Case-Control Studies, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Mild Cognitive Impairment, Nerve Net, Principal Component Analysis, Task Performance and Analysis, Time Factors}, issn = {1932-6203}, doi = {10.1371/journal.pone.0049340}, author = {Li, Shanshan and Eloyan, Ani and Joel, Suresh and Mostofsky, Stewart and Pekar, James and Bassett, Susan Spear and Caffo, Brian} } @article {thom, title = {Comparison of swab versus sponge methodology for the identification of acinetobacter baumannii from the hospital environment}, journal = {Accepted in the Journal of Clinical Microbiology}, year = {2012}, author = {Thom, K and Howard, T and Sembajwe, S and Harris, A and Strassle, P and Caffo, B and Caroll, K and Johnson, J} } @article {james, title = {Genetic risk factors for longitudinal changes in structural MRI in former organolead workers}, journal = {Accepted in the Journal of Aging Research}, year = {2012}, author = {James, B and Caffo, B and Stewart, W and Yousem, D and Davatzikos, C. and Schwartz, B} } @article {barber, title = {Motor "dexterity"?: evidence that left hemisphere lateralization of motor circuit connectivity is associated with better motor performance in children}, journal = {Cerebral Cortex}, year = {2012}, author = {Barber, A and Srinivasan, P and Joel, S. and Caffo, B and Pekar, J and Mostofsky, S} } @article {MRM:MRM22818, title = {On the relationship between seed-based and ICA-based measures of functional connectivity}, journal = {Magnetic Resonance in Medicine}, volume = {66}, number = {3}, year = {2011}, pages = {644{\textendash}657}, publisher = {Wiley Subscription Services, Inc., A Wiley Company}, keywords = {between network connectivity, blood oxygenation level dependent fMRI, functional connectivity, ICA, seed-based connectivity, within network connectivity}, issn = {1522-2594}, doi = {10.1002/mrm.22818}, url = {http://dx.doi.org/10.1002/mrm.22818}, author = {Joel, S. and Caffo, B and van Zijl, P and Pekar, J} } @article {schwartz2010evaluation, title = {Evaluation of Cumulative Lead Dose and Longitudinal Changes in Structural Magnetic Resonance Imaging in Former Organolead Workers}, journal = {Journal of Occupational and Environmental Medicine, PMCID: PMC2869464}, volume = {52}, number = {4}, year = {2010}, pages = {407{\textendash}414}, author = {Schwartz, B and Caffo, B and Stewart, W and Hedlin, H and James, B and Yousem, D and Davatzikos, C.} } @article {swihart2009lasagna, title = {Lasagna plots: A Saucy alternative to spaghetti plots}, journal = {Epidemiology}, volume = {21}, number = {5}, year = {2010}, pages = {621{\textendash}625}, author = {Swihart, B and Caffo, B and James, B and Strand, M. and Schwartz, B and Punjabi, N} } @article {hao, title = {Redefining CpG Islands Using a Hidden Markov Models}, journal = {Biostatistics, PMCID: PMC2883304}, volume = {11}, number = {3}, year = {2010}, pages = {499{\textendash}514}, author = {Wu, H and Caffo, B and Jaffee, H and Feinberg, A and Irizarry, R} } @article {pmid20227508, title = {Two-stage decompositions for the analysis of functional connectivity for fMRI with application to Alzheimer{\textquoteright}s disease risk}, journal = {Neuroimage}, volume = {51}, number = {3}, year = {2010}, month = {Jul}, pages = {1140{\textendash}1149}, author = {Caffo, B and Crainiceanu, C and Verduzco, G. and Joel, S. and Mostofsky, S and Bassett, S and Pekar, J} } @article {VogelsteinPaninski09, title = {Spike inference from calcium imaging using sequential Monte Carlo methods.}, journal = {Biophys J}, volume = {97}, number = {2}, year = {2009}, pages = {636{\textendash}655}, publisher = {Department of Neuroscience, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA. joshuav@jhu.edu}, abstract = {

As recent advances in calcium sensing technologies facilitate simultaneously imaging action potentials in neuronal populations, complementary analytical tools must also be developed to maximize the utility of this experimental paradigm. Although the observations here are fluorescence movies, the signals of interest{\textendash}spike trains and/or time varying intracellular calcium concentrations{\textendash}are hidden. Inferring these hidden signals is often problematic due to noise, nonlinearities, slow imaging rate, and unknown biophysical parameters. We overcome these difficulties by developing sequential Monte Carlo methods (particle filters) based on biophysical models of spiking, calcium dynamics, and fluorescence. We show that even in simple cases, the particle filters outperform the optimal linear (i.e., Wiener) filter, both by obtaining better estimates and by providing error bars. We then relax a number of our model assumptions to incorporate nonlinear saturation of the fluorescence signal, as well external stimulus and spike history dependence (e.g., refractoriness) of the spike trains. Using both simulations and in vitro fluorescence observations, we demonstrate temporal superresolution by inferring when within a frame each spike occurs. Furthermore, the model parameters may be estimated using expectation maximization with only a very limited amount of data (e.g., approximately 5-10 s or 5-40 spikes), without the requirement of any simultaneous electrophysiology or imaging experiments.

}, keywords = {Animals, Biological, Calcium, cytology/metabolism, Fluorescence, Inbred C57BL, Intracellular Space, metabolism, Mice, models, Monte Carlo Method, Neurons, Probability, Time Factors}, doi = {10.1016/j.bpj.2008.08.005}, url = {http://dx.doi.org/10.1016/j.bpj.2008.08.005}, author = {Vogelstein, Joshua T and Watson, Brendon O and Packer, Adam M and Yuste, Rafael and Jedynak, Bruno and Paninski, Liam} } @article {Crai:Rupp:Carr:Josh:Good:spat:2007, title = {Spatially Adaptive Bayesian Penalized Splines with Heteroscedastic Errors}, journal = {Journal of Computational and Graphical Statistics}, volume = {16}, number = {2}, year = {2007}, pages = {265{\textendash}288}, keywords = {Heteroscedasticity, MCMC, Multivariate smoothing, Regression splines, spatially adaptive penalty, thin-plate splines, Variance functions}, author = {Crainiceanu, C and Ruppert, D. and Carroll, Raymond J. and Joshi, Adarsh and Goodner, Billy} } @article {jones2006fixed, title = {Fixed-width output analysis for Markov chain Monte Carlo}, journal = {Journal of the American Statistical Association}, volume = {101}, number = {476}, year = {2006}, pages = {1537{\textendash}1547}, publisher = {ASA}, author = {Jones, G and Haran, M and Caffo, B and Neath, R} } @article {Gime:Crai:Barb:Jeno:Morg:semi:2006, title = {Semiparametric Regression in Capture\textndashrecapture Modeling}, journal = {Biometrics}, volume = {62}, number = {3}, year = {2006}, pages = {691{\textendash}698}, keywords = {auxiliary variables, Bayesian inference, Demographic rates, Environmental covariates, penalized splines, Winbugs}, author = {Gimenez, O. and Crainiceanu, C and Barbraud, C. and Jenouvrier, S. and Morgan, B. J. T.} } @article {caffo2005ascent, title = {Ascent-Based Monte Carlo EM}, journal = {Journal of the Royal Statistical Society, Series B}, volume = {67}, year = {2005}, pages = {235{\textendash}252}, author = {Caffo, B and Jank, W and Jones, G} }