Association between Serum Uric Acid Levels and Bone Mineral Density in Postmenopausal Women: A Cross-Sectional and Longitudinal Study.

BACKGROUND: Uric acid is one of natural antioxidants in human body. There have been several studies on the correlation between uric acid with oxidative stress and osteoporosis. However, the data are insufficient and results are controversial. In this regard, we determined the association between uric acid levels and bone mineral density (BMD) during the postmenopausal period. METHODS: We analyzed data from 328 postmenopausal women (mean age, 57.3 ± 6.5 years; mean serum uric acid level, 4.6 ± 1.0 mg/dL). The participants were divided into three groups based on tertiles of the serum uric acid level. The participants receiving hormone replacement therapy (HRT), bisphosphonates, or lipid-lowering agents were included. RESULTS: Blood urea nitrogen, serum creatinine, and serum triglyceride levels were significantly higher in the upper tertiles of uric acid levels. No significant difference was found in the mean uric acid levels between medication users and non-users. Each HRT regimen had a different mean serum uric acid level. A cross-sectional analysis showed no significant correlation between the serum uric acid levels and BMD in the spine and femoral neck (spine BMD: 1.050 ± 0.131, 1.060 ± 0.160, 1.084 ± 0.140, p = 0.22; femoral neck BMD: 0.837 ± 0.110, 0.849 ± 0.096, 0.863 ± 0.115, p = 0.28 for each tertile of uric acid). Longitudinal analysis of data from 186 women with follow-up examinations at a mean interval of 14.6 months also revealed no difference in reduction in both spine and femoral neck BMD between tertile groups of serum uric acid (the median BMD reduction for spine: -0.02, 0.01, -0.04, p = 0.95; the median BMD reduction for femoral neck: 0.008, 0.005, -0.003, p = 0.34). CONCLUSIONS: Serum uric acid level is not associated with BMD in postmenopausal women.

Alterations of Brain Signal Oscillations in Older Individuals with HIV Infection and Parkinson's Disease.

More than 30 years after the human immunodeficiency virus (HIV) epidemic, HIV patients are now aging due to the advances of antiretroviral therapy. With immunosenescence and the susceptibility of dopamine-rich basal ganglia regions to HIV-related injury, older HIV patients may show neurofunctional deficits similar to patients with Parkinson's disease (PD). We examined the amplitudes of low frequency fluctuations (ALFF) across different frequency bands of the BOLD signal in 30 older HIV-infected individuals, 33 older healthy controls, and 36 PD patients. Participants underwent resting-state fMRI, neuropsychological testing, and a clinical motor exam. HIV patients mainly showed abnormalities in cortical ALFF with reduced prefrontal amplitudes and enhanced sensorimotor and inferior temporal amplitudes. Frontal hypoactivation was overlapping for HIV and PD groups and different from controls. PD patients further exhibited reduced pallidum amplitudes compared to the other groups. In the HIV group, lower pallidum amplitudes were associated with lower CD4+ nadir and CD4+ T cell counts. Abnormalities in ALFF dynamics were largely associated with cognitive and motor functioning in HIV and PD groups. The disruption of neurofunctional frequency dynamics in subcortical-cortical circuits could contribute to the development of cognitive and motor dysfunction and serve as a biomarker for monitoring disease progression with immunosenescence. Graphical Abstract.

Effects of age, sex, and puberty on neural efficiency of cognitive and motor control in adolescents.

Critical changes in adolescence involve brain cognitive maturation of inhibitory control processes that are essential for a myriad of adult functions. Cognitive control advances into adulthood as there is more flexible integration of component processes, including inhibitory control of conflicting information, overwriting inappropriate response tendencies, and amplifying relevant responses for accurate execution. Using a modified Stroop task with fMRI, we investigated the effects of age, sex, and puberty on brain functional correlates of cognitive and motor control in 87 boys and 91 girls across the adolescent age range. Results revealed dissociable brain systems for cognitive and motor control processes, whereby adolescents flexibly adapted neural responses to control demands. Specifically, when response repetitions facilitated planning-based action selection, frontoparietal-insular regions associated with cognitive control operations were less activated, whereas cortical-pallidal-cerebellar motor regions associated with motor skill acquisition, were more activated. Attenuated middle cingulate cortex activation occurred with older adolescent age for both motor control and cognitive control with automaticity from repetition learning. Sexual dimorphism for control operations occurred in extrastriate cortices involved in visuo-attentional selection: While boys enhanced extrastriate selection processes for motor control, girls activated these regions more for cognitive control. These sex differences were attenuated with more advanced pubertal stage. Together, our findings show that brain cognitive and motor control processes are segregated, demand-specific, more efficient in older adolescents, and differ between sexes relative to pubertal development. Our findings advance our understanding of how distributed brain activity and the neurodevelopment of automaticity enhances cognitive and motor control ability in adolescence.

Regional growth trajectories of cortical myelination in adolescents and young adults: longitudinal validation and functional correlates.

Adolescence is a time of continued cognitive and emotional evolution occurring with continuing brain development involving synaptic pruning and cortical myelination. The hypothesis of this study is that heavy myelination occurs in cortical regions with relatively direct, predetermined circuitry supporting unimodal sensory or motor functions and shows a steep developmental slope during adolescence (12-21 years) until young adulthood (22-35 years) when further myelination decelerates. By contrast, light myelination occurs in regions with highly plastic circuitry supporting complex functions and follows a delayed developmental trajectory. In support of this hypothesis, cortical myelin content was estimated and harmonized across publicly available datasets provided by the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) and the Human Connectome Project (HCP). The cross-sectional analysis of 226 no-to-low alcohol drinking NCANDA adolescents revealed relatively steeper age-dependent trajectories of myelin growth in unimodal primary motor cortex and flatter age-dependent trajectories in multimodal mid/posterior cingulate cortices. This pattern of continued myelination showed smaller gains when the same analyses were performed on 686 young adults of the HCP cohort free of neuropsychiatric diagnoses. Critically, a predicted correlation between a motor task and myelin content in motor or cingulate cortices was found in the NCANDA adolescents, supporting the functional relevance of this imaging neurometric. Furthermore, the regional trajectory slopes were confirmed by performing longitudinally consistent analysis of cortical myelin. In conclusion, coordination of myelin content and circuit complexity continues to develop throughout adolescence, contributes to performance maturation, and may represent active cortical development climaxing in young adulthood.

Logistic Regression Confined by Cardinality-Constrained Sample and Feature Selection.

Many vision-based applications rely on logistic regression for embedding classification within a probabilistic context, such as recognition in images and videos or identifying disease-specific image phenotypes from neuroimages. Logistic regression, however, often performs poorly when trained on data that is noisy, has irrelevant features, or when the samples are distributed across the classes in an imbalanced setting; a common occurrence in visual recognition tasks. To deal with those issues, researchers generally rely on ad-hoc regularization techniques or model a subset of these issues. We instead propose a mathematically sound logistic regression model that selects a subset of (relevant) features and (informative and balanced) set of samples during the training process. The model does so by applying cardinality constraints (via l0-'norm' sparsity) on the features and samples. l0 defines sparsity in mathematical settings but in practice has mostly been approximated (e.g., via l1 or its variations) for computational simplicity. We prove that a local minimum to the non-convex optimization problems induced by cardinality constraints can be computed by combining block coordinate descent with penalty decomposition. On synthetic, image recognition, and neuroimaging datasets, we show that the accuracy of the method is higher than alternative methods and classifiers commonly used in the literature.

Longitudinally consistent estimates of intrinsic functional networks.

Increasing numbers of neuroimaging studies are acquiring data to examine changes in brain architecture by investigating intrinsic functional networks (IFN) from longitudinal resting-state functional MRI (rs-fMRI). At the subject level, these IFNs are determined by cross-sectional procedures, which neglect intra-subject dependencies and result in suboptimal estimates of the networks. Here, a novel longitudinal approach simultaneously extracts subject-specific IFNs across multiple visits by explicitly modeling functional brain development as an essential context for seeking change. On data generated by an innovative simulation based on real rs-fMRI, the method was more accurate in estimating subject-specific IFNs than cross-sectional approaches. Furthermore, only group-analysis based on longitudinally consistent estimates identified significant developmental effects within IFNs of 246 adolescents from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study. The findings were confirmed by the cross-sectional estimates when the corresponding group analysis was confined to the developmental effects. Those effects also converged with current concepts of neurodevelopment.

Distribution of brain iron accrual in adolescence: Evidence from cross-sectional and longitudinal analysis.

To track iron accumulation and location in the brain across adolescence, we repurposed diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) data acquired in 513 adolescents and validated iron estimates with quantitative susceptibility mapping (QSM) in 104 of these subjects. DTI and fMRI data were acquired longitudinally over 1 year in 245 male and 268 female, no-to-low alcohol-consuming adolescents (12-21 years at baseline) from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study. Brain region average signal values were calculated for susceptibility to nonheme iron deposition: pallidum, putamen, dentate nucleus, red nucleus, and substantia nigra. To estimate nonheme iron, the corpus callosum signal (robust to iron effects) was divided by regional signals to generate estimated R2 (edwR2 for DTI) and R2 * (eR2 * for fMRI). Longitudinal iron deposition was measured using the normalized signal change across time for each subject. Validation using baseline QSM, derived from susceptibility-weighted imaging, was performed on 46 male and 58 female participants. Normalized iron deposition estimates from DTI and fMRI correlated with age in most regions; both estimates indicated less iron in boys than girls. QSM results correlated highly with DTI and fMRI results (adjusted R2 = 0.643 for DTI, 0.578 for fMRI). Cross-sectional and longitudinal analyses indicated an initial rapid increase in iron, notably in the putamen and red nucleus, that slowed with age. DTI and fMRI data can be repurposed for identifying regional brain iron deposition in developing adolescents as validated with high correspondence with QSM.

Salicylic acid-induced transcriptional reprogramming by the HAC-NPR1-TGA histone acetyltransferase complex in Arabidopsis.

Plant immunity depends on massive expression of pathogenesis-related genes (PRs) whose transcription is de-repressed by pathogen-induced signals. Salicylic acid (SA) acts as a major signaling molecule in plant immunity and systemic acquired resistance triggered by bacterial or viral pathogens. SA signal results in the activation of the master immune regulator, Nonexpressor of pathogenesis-related genes 1 (NPR1), which is thought to be recruited by transcription factors such as TGAs to numerous downstream PRs. Despite its key role in SA-triggered immunity, the biochemical nature of the transcriptional coactivator function of NPR1 and the massive transcriptional reprogramming induced by it remain obscure. Here we demonstrate that the CBP/p300-family histone acetyltransferases, HACs and NPR1 are both essential to develop SA-triggered immunity and PR induction. Indeed HACs and NPR1 form a coactivator complex and are recruited to PR chromatin through TGAs upon SA signal, and finally the HAC-NPR1-TGA complex activates PR transcription by histone acetylation-mediated epigenetic reprogramming. Thus, our study reveals a molecular mechanism of NPR1-mediated transcriptional reprogramming and a key epigenetic aspect of the central immune system in plants.

Accelerated and Premature Aging Characterizing Regional Cortical Volume Loss in Human Immunodeficiency Virus Infection: Contributions From Alcohol, Substance Use, and Hepatitis C Coinfection.

BACKGROUND: Life expectancy of successfully treated human immunodeficiency virus (HIV)-infected individuals is approaching normal longevity. The growing HIV population ≥50 years of age is now at risk of developing HIV-associated neurocognitive disorder, acquiring coinfection with the hepatitis C virus (HCV), and engaging in hazardous drinking or drug consumption that can adversely affect trajectories of the healthy aging of brain structures. METHODS: This cross-sectional/longitudinal study quantified regional brain volumes from 1101 magnetic resonance imaging scans collected over 14 years in 549 participants (25 to 75 years of age): 68 HIV-infected individuals without alcohol dependence, 60 HIV-infected individuals with alcohol dependence, 222 alcohol-dependent individuals, and 199 control subjects. We tested 1) whether localized brain regions in HIV-infected individuals exhibited accelerated aging, or alternatively, nonaccelerated premature aging deficits; and 2) the extent to which alcohol or substance dependence or HCV coinfection altered brain aging trajectories. RESULTS: The HIV-infected cohort exhibited steeper declining volume trajectories than control subjects, consistently in the frontal cortex. Nonaccelerated volume deficits occurred in the temporal, parietal, insular, and cingulate regions of all three diagnostic groups. Alcohol and drug dependence comorbidities and HCV coinfection exacerbated HIV-related volume deficits. Accelerated age interactions in frontal and posterior parietal volumes endured in HIV-infected individuals free of alcohol or substance dependence and HCV infection comorbidities. Functionally, poorer HIV-associated neurocognitive disorder scores and Veterans Aging Cohort Study indices correlated with smaller regional brain volumes in the HIV-infected individuals without alcohol dependence and alcohol-dependent groups. CONCLUSIONS: HIV infection itself may confer a heightened risk of accelerated brain aging, potentially exacerbated by HCV coinfection and substance dependency. Confirmation would require a prospective study with a preinfection baseline.

Chained regularization for identifying brain patterns specific to HIV infection.

Human Immunodeficiency Virus (HIV) infection continues to have major adverse public health and clinical consequences despite the effectiveness of combination Antiretroviral Therapy (cART) in reducing HIV viral load and improving immune function. As successfully treated individuals with HIV infection age, their cognition declines faster than reported for normal aging. This phenomenon underlines the importance of improving long-term care, which requires a better understanding of the impact of HIV on the brain. In this paper, automated identification of patients and brain regions affected by HIV infection are modeled as a classification problem, whose solution is determined in two steps within our proposed Chained-Regularization framework. The first step focuses on selecting the HIV pattern (i.e., the most informative constellation of brain region measurements for distinguishing HIV infected subjects from healthy controls) by constraining the search for the optimal parameter setting of the classifier via group sparsity (ℓ2,1-norm). The second step improves classification accuracy by constraining the parameterization with respect to the selected measurements and the Euclidean regularization (ℓ2-norm). When applied to the cortical and subcortical structural Magnetic Resonance Images (MRI) measurements of 65 controls and 65 HIV infected individuals, this approach is more accurate in distinguishing the two cohorts than more common models. Finally, the brain regions of the identified HIV pattern concur with the HIV literature that uses traditional group analysis models.

Alcohol use effects on adolescent brain development revealed by simultaneously removing confounding factors, identifying morphometric patterns, and classifying individuals.

Group analysis of brain magnetic resonance imaging (MRI) metrics frequently employs generalized additive models (GAM) to remove contributions of confounding factors before identifying cohort specific characteristics. For example, the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) used such an approach to identify effects of alcohol misuse on the developing brain. Here, we hypothesized that considering confounding factors before group analysis removes information relevant for distinguishing adolescents with drinking history from those without. To test this hypothesis, we introduce a machine-learning model that identifies cohort-specific, neuromorphometric patterns by simultaneously training a GAM and generic classifier on macrostructural MRI and microstructural diffusion tensor imaging (DTI) metrics and compare it to more traditional group analysis and machine-learning approaches. Using a baseline NCANDA MR dataset (N = 705), the proposed machine learning approach identified a pattern of eight brain regions unique to adolescents who misuse alcohol. Classifying high-drinking adolescents was more accurate with that pattern than using regions identified with alternative approaches. The findings of the joint model approach thus were (1) impartial to confounding factors; (2) relevant to drinking behaviors; and (3) in concurrence with the alcohol literature.

The Role of Aging, Drug Dependence, and Hepatitis C Comorbidity in Alcoholism Cortical Compromise.

Importance: The prevalence of alcohol misuse increased substantially over a decade in adults, particularly in those aged 65 years or older. Ramifications for brain structural integrity are significant, especially in older adults. Objectives: To combine cross-sectional, longitudinal data to test age-alcoholism interactions and examine the association between prevalent comorbidities (drug dependence and hepatitis C virus [HCV] infection) and cortical volume deficits in alcohol dependence. Design, Setting, and Participants: During 14 years, 826 structural magnetic resonance images were acquired in 222 individuals with alcohol dependence and 199 age-matched control participants (aged 25-75 years at initial study), parcellated with a common atlas, and adjusted for brain volume. Longitudinal data were available on 116 participants with alcoholism and 96 control participants. DSM-IV criteria determined alcohol and drug diagnoses; serology testing determined HCV status. The study was conducted at SRI International and Stanford University School of Medicine from April 11, 2003, to March 3, 2017. Main Outcomes and Measures: Magnetic resonance imaging-derived regional cortical volumes corrected for supratentorial volume and sex. Results: Of the 222 participants with alcoholism, 156 (70.3%) were men; mean (SD) age was 48.0 (10.0) years; the mean age for the 199 control participants was 47.6 (14.0) years. Participants with alcohol dependence had volume deficits in frontal (t = -5.732, P < .001), temporal (t = -3.151, P = .002), parietal (t = -5.063, P < .001), cingulate (t = -3.170, P = .002), and insular (t = -4.920, P < .001) cortices; deficits were prominent in frontal subregions and were not sex dependent. Accelerated aging occurred in frontal cortex (t = -3.019, P < .02) and precentral (t = -2.691, P < .05) and superior gyri (t = -2.763, P < .05) and could not be attributed to the amount of alcohol consumed, which was greater in younger-onset than older-onset participants with alcoholism (t = 6.1191, P < .001). Given the high drug-dependence incidence (54.5%) in the alcoholism group, analysis examined drug subgroups (cocaine, cannabis, amphetamines, opiates) compared with drug-dependence-free alcoholism and control groups. Although the alcohol plus cocaine (t = -2.310, P = .04) and alcohol plus opiate (t = -2.424, P = .04) groups had smaller frontal volumes than the drug-dependence-free alcoholism group, deficits in precentral (t = -2.575, P = .01), supplementary motor (t = -2.532, P = .01), and medial (t = -2.800, P = .01) volumes endured in drug-dependence-free participants with alcoholism compared with control participants. Those with HCV infection had greater deficits than those without HCV infection in frontal (t = 3.468, P = .01), precentral (t = 2.513, P = .03), superior (t = 2.533, P = .03), and orbital (t = 2.506, P = .03) volumes, yet total frontal (t = 2.660, P = .02), insular (t = 3.526, P = .003), parietal (t = 2.414, P = .03), temporal (t = 3.221, P = .005), and precentral (t = 3.180, P = .01) volume deficits persisted in the uninfected participants with alcoholism compared with control participants with known HCV status. Conclusions and Relevance: Drug dependence and HCV infection compounded deleterious effects of alcohol dependence on frontal cortical volumes but could not account for the frontally distributed volume deficits in the drug-free participants with alcoholism. We speculate that age-alcohol interactions notable in frontal cortex put older adults at heightened risk for age-associated neurocompromise even if alcohol misuse is initiated later in life.

The mediating role of cortical thickness and gray matter volume on sleep slow-wave activity during adolescence.

During the course of adolescence, reductions occur in cortical thickness and gray matter (GM) volume, along with a 65% reduction in slow-wave (delta) activity during sleep (SWA) but empirical data linking these structural brain and functional sleep differences, is lacking. Here, we investigated specifically whether age-related differences in cortical thickness and GM volume and cortical thickness accounted for the typical age-related difference in slow-wave (delta) activity (SWA) during sleep. 132 healthy participants (age 12-21 years) from the National Consortium on Alcohol and NeuroDevelopment in Adolescence study were included in this cross-sectional analysis of baseline polysomnographic, electroencephalographic, and magnetic resonance imaging data. By applying mediation models, we identified a large, direct effect of age on SWA in adolescents, which explained 45% of the variance in ultra-SWA (0.3-1 Hz) and 52% of the variance in delta-SWA (1 to <4 Hz), where SWA was lower in older adolescents, as has been reported previously. In addition, we provide evidence that the structure of several, predominantly frontal, and parietal brain regions, partially mediated this direct age effect, models including measures of brain structure explained an additional 3-9% of the variance in ultra-SWA and 4-5% of the variance in delta-SWA, with no differences between sexes. Replacing age with pubertal status in models produced similar results. As reductions in GM volume and cortical thickness likely indicate synaptic pruning and myelination, these results suggest that diminished SWA in older, more mature adolescents may largely be driven by such processes within a number of frontal and parietal brain regions.

Influences of Age, Sex, and Moderate Alcohol Drinking on the Intrinsic Functional Architecture of Adolescent Brains.

The transition from adolescent to adult cognition and emotional control requires neurodevelopmental maturation likely involving intrinsic functional networks (IFNs). Normal neurodevelopment may be vulnerable to disruption from environmental insult such as alcohol consumption commonly initiated during adolescence. To test potential disruption to IFN maturation, we used resting-state functional magnetic resonance imaging (rs-fMRI) in 581 no-to-low alcohol-consuming and 117 moderate-to-high-drinking youth. Functional seed-to-voxel connectivity analysis assessed age, sex, and moderate alcohol drinking on default-mode, executive-control, salience, reward, and emotion networks and tested cognitive and motor coordination correlates of network connectivity. Among no-to-low alcohol-consuming adolescents, executive-control frontolimbicstriatal connectivity was stronger in older than younger adolescents, particularly boys, and predicted better ability in balance, memory, and impulse control. Connectivity patterns in moderate-to-high-drinking youth were tested mainly in late adolescence when drinking was initiated. Implicated was the emotion network with attenuated connectivity to default-mode network regions. Our cross-sectional rs-fMRI findings from this large cohort of adolescents show sexual dimorphism in connectivity and suggest neurodevelopmental rewiring toward stronger and spatially more distributed executive-control networking in older than younger adolescents. Functional network rewiring in moderate-to-high-drinking adolescents may impede maturation of affective and self-reflection systems and obscure maturation of complex social and emotional behaviors.

A Riemannian Framework for Longitudinal Analysis of Resting-State Functional Connectivity.

Even though the number of longitudinal resting-state-fMRI studies is increasing, accurately characterizing the changes in functional connectivity across visits is a largely unexplored topic. To improve characterization, we design a Riemannian framework that represents the functional connectivity pattern of a subject at a visit as a point on a Riemannian manifold. Geodesic regression across the 'sample' points of a subject on that manifold then defines the longitudinal trajectory of their connectivity pattern. To identify group differences specific to regions of interest (ROI), we map the resulting trajectories of all subjects to a common tangent space via the Lie group action. We account for the uncertainty in choosing the common tangent space by proposing a test procedure based on the theory of latent p-values. Unlike existing methods, our proposed approach identifies sex differences across 246 subjects, each of them being characterized by three rs-fMRI scans.

Multi-Label Transduction for Identifying Disease Comorbidity Patterns.

Study of the untoward effects associated with the comorbidity of multiple diseases on brain morphology requires identifying differences across multiple diagnostic groupings. To identify such effects and differentiate between groups of patients and normal subjects, conventional methods often compare each patient group with healthy subjects using binary or multi-class classifiers. However, testing inferences across multiple diagnostic groupings of complex disorders commonly yield inconclusive or conflicting findings when the classifier is confined to modeling two cohorts at a time or considers class labels mutually-exclusive (as in multi-class classifiers). These shortcomings are potentially caused by the difficulties associated with modeling compounding factors of diseases with these approaches. Multi-label classifiers, on the other hand, can appropriately model disease comorbidity, as each subject can be assigned to two or more labels. In this paper, we propose a multi-label transductive (MLT) method based on low-rank matrix completion that is able not only to classify the data into multiple labels but also to identify patterns from MRI data unique to each cohort. To evaluate the method, we use a dataset containing individuals with Alcohol Use Disorder (AUD) and human immunodeficiency virus (HIV) infection (specifically 244 healthy controls, 227 AUD, 70 HIV, and 61 AUD+HIV). On this dataset, our proposed method is more accurate in correctly labeling subjects than common approaches. Furthermore, our method identifies patterns specific to each disease and AUD+HIV comorbidity that shows that the comorbidity is characterized by a compounding effect of AUD and HIV infection.

Altered Brain Developmental Trajectories in Adolescents After Initiating Drinking.

OBJECTIVE: The authors sought evidence for altered adolescent brain growth trajectory associated with moderate and heavy alcohol use in a large national, multisite, prospective study of adolescents before and after initiation of appreciable alcohol use. METHOD: This study examined 483 adolescents (ages 12-21) before initiation of drinking and 1 and 2 years later. At the 2-year assessment, 356 participants continued to meet the study's no/low alcohol consumption entry criteria, 65 had initiated moderate drinking, and 62 had initiated heavy drinking. MRI was used to quantify regional cortical and white matter volumes. Percent change per year (slopes) in adolescents who continued to meet no/low criteria served as developmental control trajectories against which to compare those who initiated moderate or heavy drinking. RESULTS: In no/low drinkers, gray matter volume declined throughout adolescence and slowed in many regions in later adolescence. Complementing gray matter declines, white matter regions grew at faster rates at younger ages and slowed toward young adulthood. Youths who initiated heavy drinking exhibited an accelerated frontal cortical gray matter trajectory, divergent from the norm. Although significant effects on trajectories were not observed in moderate drinkers, their intermediate position between no/low and heavy drinkers suggests a dose effect. Neither marijuana co-use nor baseline volumes contributed significantly to the alcohol effect. CONCLUSIONS: Initiation of drinking during adolescence, with or without marijuana co-use, disordered normal brain growth trajectories. Factors possibly contributing to abnormal cortical volume trajectories include peak consumption in the past year and family history of alcoholism.

Aberrant blood-oxygen-level-dependent signal oscillations across frequency bands characterize the alcoholic brain.

Chronic alcoholism is associated with widespread regional differences from controls in brain activity and connectivity dynamics measured by blood-oxygen-level-dependent (BOLD) signals. Identification of alcoholism-related neurofunctional power dynamics using functional magnetic resonance imaging (fMRI) that relate to cognition and behavior may serve as biomarkers of alcoholism. Previously, resting-state fMRI studies examined BOLD signals at a single low-frequency (LF) bandwidth. BOLD signals, however, oscillate systematically at different frequencies and are organized in a resting brain where LF oscillation facilitates long-distance communication between regions across cortical regions, whereas high-frequency (HF) oscillation occurs in closely localized, subcortical areas. Using a frequency power quantification approach, we investigated whether the organization of BOLD signal oscillations across all measured frequency bandwidths is altered in alcoholism and relates to cognitive performance. Frequency-dependent oscillation power differences between 56 sober alcoholics and 56 healthy controls occurred for all frequency bands. Alcoholics exhibited greater frequency oscillation power in the orbitofrontal cortex and less power in the posterior insula within the HF bandwidth than controls. Aberrant orbitofrontal HF power was associated with poorer memory performance and slower psychomotor speed in alcoholics. Middle-frequency and LF power proved sensitive in detecting altered frequency oscillation dynamics in parietal and postcentral cortical regions of alcoholics. This study is novel in identifying alcohol-related differences in BOLD oscillation power of the full fMRI frequency bandwidth. Specifically, HF power aberrations were associated with poorer cognitive functioning in alcoholism and may serve as a biomarker for identifying neural targets for repair.

Effects of prior testing lasting a full year in NCANDA adolescents: Contributions from age, sex, socioeconomic status, ethnicity, site, family history of alcohol or drug abuse, and baseline performance.

Longitudinal study provides a robust method for tracking developmental trajectories. Yet inherent problems of retesting pose challenges in distinguishing biological developmental change from prior testing experience. We examined factors potentially influencing change scores on 16 neuropsychological test composites over 1year in 568 adolescents in the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) project. The twice-minus-once-tested method revealed that performance gain was mainly attributable to testing experience (practice) with little contribution from predicted developmental effects. Group mean practice slopes for 13 composites indicated that 60% to ∼100% variance was attributable to test experience; General Ability accuracy showed the least practice effect (29%). Lower baseline performance, especially in younger participants, was a strong predictor of greater gain. Contributions from age, sex, ethnicity, examination site, socioeconomic status, or family history of alcohol/substance abuse were nil to small, even where statistically significant. Recognizing that a substantial proportion of change in longitudinal testing, even over 1-year, is attributable to testing experience indicates caution against assuming that performance gain observed during periods of maturation necessarily reflects development. Estimates of testing experience, a form of learning, may be a relevant metric for detecting interim influences, such as alcohol use or traumatic episodes, on behavior.

Computing group cardinality constraint solutions for logistic regression problems.

We derive an algorithm to directly solve logistic regression based on cardinality constraint, group sparsity and use it to classify intra-subject MRI sequences (e.g. cine MRIs) of healthy from diseased subjects. Group cardinality constraint models are often applied to medical images in order to avoid overfitting of the classifier to the training data. Solutions within these models are generally determined by relaxing the cardinality constraint to a weighted feature selection scheme. However, these solutions relate to the original sparse problem only under specific assumptions, which generally do not hold for medical image applications. In addition, inferring clinical meaning from features weighted by a classifier is an ongoing topic of discussion. Avoiding weighing features, we propose to directly solve the group cardinality constraint logistic regression problem by generalizing the Penalty Decomposition method. To do so, we assume that an intra-subject series of images represents repeated samples of the same disease patterns. We model this assumption by combining series of measurements created by a feature across time into a single group. Our algorithm then derives a solution within that model by decoupling the minimization of the logistic regression function from enforcing the group sparsity constraint. The minimum to the smooth and convex logistic regression problem is determined via gradient descent while we derive a closed form solution for finding a sparse approximation of that minimum. We apply our method to cine MRI of 38 healthy controls and 44 adult patients that received reconstructive surgery of Tetralogy of Fallot (TOF) during infancy. Our method correctly identifies regions impacted by TOF and generally obtains statistically significant higher classification accuracy than alternative solutions to this model, i.e., ones relaxing group cardinality constraints.