ABSTRACT
Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion magnetic resonance imaging [MRI]). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N = 34,029) and ABCD Study (N = 8607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI in a genome-wide association study (GWAS) with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition.
Subject(s)
Genome-Wide Association Study , Neuroimaging , Humans , Genome-Wide Association Study/methods , Phenotype , Genetic Pleiotropy , Brain/anatomy & histology , Polymorphism, Single Nucleotide , Genetic Predisposition to DiseaseABSTRACT
BACKGROUND: UK Biobank (UKB) is a large prospective cohort capturing numerous health outcomes, but limited occupational information (job title, self-reported manual work and occupational walking/standing). AIMS: To create and evaluate validity of a linkage between UKB and a job exposure matrix for physical work exposures based on the US Occupational Information Network (O*NET) database. METHODS: Job titles and UK Standard Occupational Classification (SOC) codes were collected during UKB baseline assessment visits. Using existing crosswalks, UK SOC codes were mapped to US SOC codes allowing linkage to O*NET variables capturing numerous dimensions of physical work. Job titles with the highest O*NET scores were assessed to evaluate face validity. Spearman's correlation coefficients were calculated to compare O*NET scores to self-reported UKB measures. RESULTS: Among 324 114 participants reporting job titles, 323 936 were linked to O*NET. Expected relationships between scores and self-reported measures were observed. For static strength (0-7 scale), the median O*NET score was 1.0 (e.g. audiologists), with a highest score of 4.88 for stone masons and a positive correlation with self-reported heavy manual work (Spearman's coefficient = 0.50). For time spent standing (1-5 scale), the median O*NET score was 2.72 with a highest score of 5 for cooks and a positive correlation with self-reported occupational walking/standing (Spearman's coefficient = 0.56). CONCLUSIONS: While most jobs were not physically demanding, a wide range of physical work values were assigned to a diverse set of jobs. This novel linkage of a job exposure matrix to UKB provides a potentially valuable tool for understanding relationships between occupational exposures and disease.
Subject(s)
Biological Specimen Banks , Occupational Exposure , Humans , Occupational Exposure/adverse effects , Occupations , Prospective Studies , United Kingdom/epidemiologyABSTRACT
Cognitive performance in children is predictive of academic and social outcomes; therefore, understanding neurobiological mechanisms underlying individual differences in cognition during development may be important for improving quality of life. The belief that a single, psychological construct underlies many cognitive processes is pervasive throughout society. However, it is unclear if there is a consistent neural substrate underlying many cognitive processes. Here, we show that a distributed configuration of cortical surface area and apparent thickness, when controlling for global imaging measures, is differentially associated with cognitive performance on different types of tasks in a large sample (N = 10 145) of 9-11-year-old children from the Adolescent Brain and Cognitive DevelopmentSM (ABCD) study. The minimal overlap in these regionalization patterns of association has implications for competing theories about developing intellectual functions. Surprisingly, not controlling for sociodemographic factors increased the similarity between these regionalization patterns. This highlights the importance of understanding the shared variance between sociodemographic factors, cognition and brain structure, particularly with a population-based sample such as ABCD.
Subject(s)
Cerebral Cortex/anatomy & histology , Cerebral Cortex/physiology , Cognition/physiology , Adolescent , Adolescent Development , Child , Female , Humans , Longitudinal Studies , Magnetic Resonance Imaging , Male , Neuropsychological Tests , Psychomotor Performance/physiology , Sensitivity and Specificity , Sociodemographic FactorsABSTRACT
BACKGROUND: Construction is among the most dangerous industries. In addition to traditional hazards for workplace injury and illness, other threats to health and well-being may occur from work organization and work environment factors, including irregular employment, long commutes, long work hours, and employer policies regarding health and safety. These nontraditional hazards may affect work and health outcomes directly, or through effects on health behaviors. The cumulative impacts of both traditional and nontraditional hazards on health-related outcomes among construction workers are largely unknown. METHODS: We conducted a survey among apprentice construction workers to identify relationships between work organization and environmental factors with five outcomes of economic relevance to employers: missed work due to work-related injury, missed work due to any pain or injury, self-reported workability, health-related productivity, and use of prescription medications for pain. RESULTS: A total of 963 surveys were completed (response rate 90%) in this young (mean age 28) working cohort. Multivariate Poisson regression models found associations between the outcomes of interest and multiple work factors, including job strain, safety behaviors of coworkers, and mandatory overtime. Univariate analysis showed additional associations, including precarious work, and supervisor support for safety. CONCLUSIONS: Findings from this cross-sectional study suggest that work organization and environment factors influence health and work outcomes among young construction trade workers. Future work with longitudinal data will examine the hypothesized paths between work factors, health behaviors, health outcomes, and work outcomes.
Subject(s)
Construction Industry/statistics & numerical data , Occupational Health/statistics & numerical data , Occupational Injuries/drug therapy , Pain/drug therapy , Workplace/statistics & numerical data , Absenteeism , Adult , Analgesics/therapeutic use , Cross-Sectional Studies , Drug Prescriptions/statistics & numerical data , Efficiency, Organizational/statistics & numerical data , Female , Humans , Job Satisfaction , Male , Missouri , Multivariate Analysis , Occupational Injuries/complications , Organizational Culture , Pain/etiology , Poisson Distribution , Safety Management , Workplace/organization & administrationABSTRACT
Executive functions are a diverse and critical suite of cognitive abilities that are often disrupted in individuals with psychiatric disorders. Despite their moderate to high heritability, little is known about the molecular genetic factors that contribute to variability in executive functions and how these factors may be related to those that predispose to psychiatric disorders. We examined the relationship between polygenic risk scores built from large genome-wide association studies of psychiatric disorders and executive functioning in typically developing children. In our discovery sample (N = 417), consistent with previous reports on general cognitive abilities, polygenic risk for autism spectrum disorder was associated with better performance on the Dimensional Change Card Sort test from the NIH Cognition Toolbox, with the largest effect in the youngest children. Polygenic risk for major depressive disorder was associated with poorer performance on the Flanker test in the same sample. This second association replicated for performance on the Penn Conditional Exclusion Test in an independent cohort (N = 3681). Our results suggest that the molecular genetic factors contributing to variability in executive function during typical development are at least partially overlapping with those associated with psychiatric disorders, although larger studies and further replication are needed.
Subject(s)
Child Development , Depressive Disorder, Major/genetics , Executive Function , Multifactorial Inheritance , Adolescent , Brain/growth & development , Brain/physiopathology , Child , Child, Preschool , Depressive Disorder, Major/epidemiology , Female , Humans , MaleABSTRACT
BACKGROUND AND PURPOSE: ADC as a marker of tumor cellularity has been promising for evaluating the response to therapy in patients with glioblastoma but does not successfully stratify patients according to outcomes, especially in the upfront setting. Here we investigate whether restriction spectrum imaging, an advanced diffusion imaging model, performed after an operation but before radiation therapy, could improve risk stratification in patients with newly diagnosed glioblastoma relative to ADC. MATERIALS AND METHODS: Pre-radiation therapy diffusion-weighted and structural imaging of 40 patients with glioblastoma were examined retrospectively. Restriction spectrum imaging and ADC-based hypercellularity volume fraction (restriction spectrum imaging-FLAIR volume fraction, restriction spectrum imaging-contrast-enhanced volume fraction, ADC-FLAIR volume fraction, ADC-contrast-enhanced volume fraction) and intensities (restriction spectrum imaging-FLAIR 90th percentile, restriction spectrum imaging-contrast-enhanced 90th percentile, ADC-FLAIR 10th percentile, ADC-contrast-enhanced 10th percentile) within the contrast-enhanced and FLAIR hyperintensity VOIs were calculated. The association of diffusion imaging metrics, contrast-enhanced volume, and FLAIR hyperintensity volume with progression-free survival and overall survival was evaluated by using Cox proportional hazards models. RESULTS: Among the diffusion metrics, restriction spectrum imaging-FLAIR volume fraction was the strongest prognostic metric of progression-free survival (P = .036) and overall survival (P = .007) in a multivariate Cox proportional hazards analysis, with higher values indicating earlier progression and shorter survival. Restriction spectrum imaging-FLAIR 90th percentile was also associated with overall survival (P = .043), with higher intensities, indicating shorter survival. None of the ADC metrics were associated with progression-free survival/overall survival. Contrast-enhanced volume exhibited a trend toward significance for overall survival (P = .063). CONCLUSIONS: Restriction spectrum imaging-derived cellularity in FLAIR hyperintensity regions may be a more robust prognostic marker than ADC and conventional imaging for early progression and poorer survival in patients with glioblastoma. However, future studies with larger samples are needed to explore its predictive ability.
Subject(s)
Brain Neoplasms/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Glioblastoma/diagnostic imaging , Adult , Brain Neoplasms/classification , Brain Neoplasms/pathology , Disease Progression , Disease-Free Survival , Female , Glioblastoma/classification , Glioblastoma/pathology , Humans , Male , Middle Aged , Prognosis , Proportional Hazards Models , Retrospective StudiesABSTRACT
BACKGROUND AND PURPOSE: The entorhinal cortex, a critical gateway between the neocortex and hippocampus, is one of the earliest regions affected by Alzheimer disease-associated neurofibrillary tangle pathology. Although our prior work has automatically delineated an MR imaging-based measure of the entorhinal cortex, whether antemortem entorhinal cortex thickness is associated with postmortem tangle burden within the entorhinal cortex is still unknown. Our objective was to evaluate the relationship between antemortem MRI measures of entorhinal cortex thickness and postmortem neuropathological measures. MATERIALS AND METHODS: We evaluated 50 participants from the Rush Memory and Aging Project with antemortem structural T1-weighted MR imaging and postmortem neuropathologic assessments. Here, we focused on thickness within the entorhinal cortex as anatomically defined by our previously developed MR imaging parcellation system (Desikan-Killiany Atlas in FreeSurfer). Using linear regression, we evaluated the association between entorhinal cortex thickness and tangles and amyloid-ß load within the entorhinal cortex and medial temporal and neocortical regions. RESULTS: We found a significant relationship between antemortem entorhinal cortex thickness and entorhinal cortex (P = .006) and medial temporal lobe tangles (P = .002); we found no relationship between entorhinal cortex thickness and entorhinal cortex (P = .09) and medial temporal lobe amyloid-ß (P = .09). We also found a significant association between entorhinal cortex thickness and cortical tangles (P = .003) and amyloid-ß (P = .01). We found no relationship between parahippocampal gyrus thickness and entorhinal cortex (P = .31) and medial temporal lobe tangles (P = .051). CONCLUSIONS: Our findings indicate that entorhinal cortex-associated in vivo cortical thinning may represent a marker of postmortem medial temporal and neocortical Alzheimer disease pathology.
Subject(s)
Alzheimer Disease/pathology , Amyloid/analysis , Entorhinal Cortex/pathology , Neurofibrillary Tangles/pathology , Aged , Alzheimer Disease/diagnostic imaging , Amyloidosis/pathology , Autopsy , Entorhinal Cortex/diagnostic imaging , Female , Humans , Magnetic Resonance Imaging , MaleABSTRACT
The most recent genome-wide association studies (GWAS) of schizophrenia (SCZ) identified hundreds of risk variants potentially implicated in the disease. Further, novel statistical methodology designed for polygenic architecture revealed more potential risk variants. This can provide a link between individual genetic factors and the mechanistic underpinnings of SCZ. Intriguingly, a large number of genes coding for ionotropic and metabotropic receptors for various neurotransmitters-glutamate, γ-aminobutyric acid (GABA), dopamine, serotonin, acetylcholine and opioids-and numerous ion channels were associated with SCZ. Here, we review these findings from the standpoint of classical neurobiological knowledge of neuronal synaptic transmission and regulation of electrical excitability. We show that a substantial proportion of the identified genes are involved in intracellular cascades known to integrate 'slow' (G-protein-coupled receptors) and 'fast' (ionotropic receptors) neurotransmission converging on the protein DARPP-32. Inspection of the Human Brain Transcriptome Project database confirms that that these genes are indeed expressed in the brain, with the expression profile following specific developmental trajectories, underscoring their relevance to brain organization and function. These findings extend the existing pathophysiology hypothesis by suggesting a unifying role of dysregulation in neuronal excitability and synaptic integration in SCZ. This emergent model supports the concept of SCZ as an 'associative' disorder-a breakdown in the communication across different slow and fast neurotransmitter systems through intracellular signaling pathways-and may unify a number of currently competing hypotheses of SCZ pathophysiology.
Subject(s)
Receptors, Ionotropic Glutamate/genetics , Receptors, Metabotropic Glutamate/genetics , Schizophrenia/genetics , Brain/metabolism , Dopamine/metabolism , Dopamine and cAMP-Regulated Phosphoprotein 32/metabolism , Genetic Predisposition to Disease/genetics , Genome-Wide Association Study , Genotype , Humans , Multifactorial Inheritance/genetics , Polymorphism, Single Nucleotide/genetics , Receptors, Ionotropic Glutamate/metabolism , Receptors, Metabotropic Glutamate/metabolism , Risk Factors , Signal Transduction/genetics , Synaptic Transmission/genetics , gamma-Aminobutyric Acid/metabolismABSTRACT
Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case-control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen's d=-0.232; P=3.50 × 10-7) and thalamus (d=-0.148; P=4.27 × 10-3) and enlarged lateral ventricles (d=-0.260; P=3.93 × 10-5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.
Subject(s)
Bipolar Disorder/physiopathology , Brain/physiopathology , Adult , Brain/anatomy & histology , Case-Control Studies , Female , Humans , Magnetic Resonance Imaging/methods , Male , Middle Aged , Organ Size/physiology , Retrospective StudiesABSTRACT
BACKGROUND: Magnetic resonance imaging (MRI) is emerging as a robust, noninvasive method for detecting and characterizing prostate cancer (PCa), but limitations remain in its ability to distinguish cancerous from non-cancerous tissue. We evaluated the performance of a novel MRI technique, restriction spectrum imaging (RSI-MRI), to quantitatively detect and grade PCa compared with current standard-of-care MRI. METHODS: In a retrospective evaluation of 33 patients with biopsy-proven PCa who underwent RSI-MRI and standard MRI before radical prostatectomy, receiver-operating characteristic (ROC) curves were performed for RSI-MRI and each quantitative MRI term, with area under the ROC curve (AUC) used to compare each term's ability to differentiate between PCa and normal prostate. Spearman rank-order correlations were performed to assess each term's ability to predict PCa grade in the radical prostatectomy specimens. RESULTS: RSI-MRI demonstrated superior differentiation of PCa from normal tissue, with AUC of 0.94 and 0.85 for RSI-MRI and conventional diffusion MRI, respectively (P=0.04). RSI-MRI also demonstrated superior performance in predicting PCa aggressiveness, with Spearman rank-order correlation coefficients of 0.53 (P=0.002) and -0.42 (P=0.01) for RSI-MRI and conventional diffusion MRI, respectively, with tumor grade. CONCLUSIONS: RSI-MRI significantly improves upon current noninvasive PCa imaging and may potentially enhance its diagnosis and characterization.
Subject(s)
Magnetic Resonance Imaging/methods , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/pathology , Aged , Humans , Image Processing, Computer-Assisted , Male , Middle Aged , Neoplasm Grading , Neoplasm Staging , Prostatic Neoplasms/surgery , ROC Curve , Retrospective Studies , Tumor BurdenABSTRACT
BACKGROUND: First-episode psychosis (FEP) patients show structural brain abnormalities. Whether the changes are progressive or not remain under debate, and the results from longitudinal magnetic resonance imaging (MRI) studies are mixed. We investigated if FEP patients showed a different pattern of regional brain structural change over a 1-year period compared with healthy controls, and if putative changes correlated with clinical characteristics and outcome. METHOD: MRIs of 79 FEP patients [SCID-I-verified diagnoses: schizophrenia, psychotic bipolar disorder, or other psychoses, mean age 27.6 (s.d. = 7.7) years, 66% male] and 82 healthy controls [age 29.3 (s.d. = 7.2) years, 66% male] were acquired from the same 1.5 T scanner at baseline and 1-year follow-up as part of the Thematically Organized Psychosis (TOP) study, Oslo, Norway. Scans were automatically processed with the longitudinal stream in FreeSurfer that creates an unbiased within-subject template image. General linear models were used to analyse longitudinal change in a wide range of subcortical volumes and detailed thickness and surface area estimates across the entire cortex, and associations with clinical characteristics. RESULTS: FEP patients and controls did not differ significantly in annual percentage change in cortical thickness or area in any cortical region, or in any of the subcortical structures after adjustment for multiple comparisons. Within the FEP group, duration of untreated psychosis, age at illness onset, antipsychotic medication use and remission at follow-up were not related to longitudinal brain change. CONCLUSIONS: We found no significant longitudinal brain changes over a 1-year period in FEP patients. Our results do not support early progressive brain changes in psychotic disorders.
Subject(s)
Bipolar Disorder/pathology , Cerebral Cortex/pathology , Psychotic Disorders/pathology , Schizophrenia/pathology , Adolescent , Adult , Antipsychotic Agents/therapeutic use , Bipolar Disorder/drug therapy , Case-Control Studies , Disease Progression , Female , Follow-Up Studies , Humans , Linear Models , Longitudinal Studies , Magnetic Resonance Imaging , Male , Middle Aged , Norway , Psychotic Disorders/drug therapy , Schizophrenia/drug therapy , Young AdultABSTRACT
The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.
Subject(s)
Brain/pathology , Schizophrenia/pathology , Adult , Brain/diagnostic imaging , Brain Mapping , Case-Control Studies , Female , Functional Laterality , Humans , Image Processing, Computer-Assisted , Longitudinal Studies , Magnetic Resonance Imaging , Male , Middle Aged , Neuroimaging , Prospective Studies , Schizophrenia/geneticsABSTRACT
OBJECTIVES: The boom in computer use and concurrent high rates in musculoskeletal complaints and carpal tunnel syndrome (CTS) among users have led to a controversy about a possible link. Most studies have used cross-sectional designs and shown no association. The present study used longitudinal data from two large complementary cohorts to evaluate a possible relationship between CTS and the performance of computer work. SETTINGS AND PARTICIPANTS: The Cosali cohort is a representative sample of a French working population that evaluated CTS using standardised clinical examinations and assessed self-reported computer use. The PrediCTS cohort study enrolled newly hired clerical, service and construction workers in several industries in the USA, evaluated CTS using symptoms and nerve conduction studies (NCS), and estimated exposures to computer work using a job exposure matrix. PRIMARY AND SECONDARY OUTCOME MEASURES: During a follow-up of 3-5â years, the association between new cases of CTS and computer work was calculated using logistic regression models adjusting for sex, age, obesity and relevant associated disorders. RESULTS: In the Cosali study, 1551 workers (41.8%) completed follow-up physical examinations; 36 (2.3%) participants were diagnosed with CTS. In the PrediCTS study, 711 workers (64.2%) completed follow-up evaluations, whereas 31 (4.3%) had new cases of CTS. The adjusted OR for the group with the highest exposure to computer use was 0.39 (0.17; 0.89) in the Cosali cohort and 0.16 (0.05; 0.59) in the PrediCTS cohort. CONCLUSIONS: Data from two large cohorts in two different countries showed no association between computer work and new cases of CTS among workers in diverse jobs with varying job exposures. CTS is far more common among workers in non-computer related jobs; prevention efforts and work-related compensation programmes should focus on workers performing forceful hand exertion.
Subject(s)
Carpal Tunnel Syndrome/etiology , Computers , Occupational Diseases/etiology , Occupational Exposure/statistics & numerical data , Adult , Carpal Tunnel Syndrome/epidemiology , Carpal Tunnel Syndrome/physiopathology , Carpal Tunnel Syndrome/prevention & control , Cohort Studies , Female , Follow-Up Studies , Hand Strength , Humans , Incidence , Male , Occupational Diseases/epidemiology , Occupational Diseases/physiopathology , Occupational Diseases/prevention & control , Occupational Exposure/prevention & control , Posture , Risk Factors , United States/epidemiologyABSTRACT
We investigated the genetic overlap between Alzheimer's disease (AD) and Parkinson's disease (PD). Using summary statistics (P-values) from large recent genome-wide association studies (GWAS) (total n=89 904 individuals), we sought to identify single nucleotide polymorphisms (SNPs) associating with both AD and PD. We found and replicated association of both AD and PD with the A allele of rs393152 within the extended MAPT region on chromosome 17 (meta analysis P-value across five independent AD cohorts=1.65 × 10(-7)). In independent datasets, we found a dose-dependent effect of the A allele of rs393152 on intra-cerebral MAPT transcript levels and volume loss within the entorhinal cortex and hippocampus. Our findings identify the tau-associated MAPT locus as a site of genetic overlap between AD and PD, and extending prior work, we show that the MAPT region increases risk of Alzheimer's neurodegeneration.
Subject(s)
Alzheimer Disease/genetics , Parkinson Disease/genetics , tau Proteins/genetics , Aged , Aged, 80 and over , Alleles , Apolipoproteins E/genetics , Brain/pathology , Chromosomes, Human, Pair 17 , Female , Genetic Loci , Genetic Pleiotropy , Genome-Wide Association Study , Humans , Male , Middle Aged , Polymorphism, Single NucleotideABSTRACT
BACKGROUND: Standard magnetic resonance imaging (MRI) of the prostate lacks sensitivity in the diagnosis and staging of prostate cancer (PCa). To improve the operating characteristics of prostate MRI in the detection and characterization of PCa, we developed a novel, enhanced MRI diffusion technique using restriction spectrum imaging (RSI-MRI). METHODS: We compared the efficacy of our novel RSI-MRI technique with standard MRI for detecting extraprostatic extension (EPE) among 28 PCa patients who underwent MRI and RSI-MRI prior to radical prostatectomy, 10 with histologically proven pT3 disease. RSI cellularity maps isolating the restricted isotropic water fraction were reconstructed based on all b-values and then standardized across the sample with z-score maps. Distortion correction of the RSI maps was performed using the alternating phase-encode technique. RESULTS: 27 patients were evaluated, excluding one patient where distortion could not be performed. Preoperative standard MRI correctly identified extraprostatic the extension in two of the nine pT3 (22%) patients, whereas RSI-MRI identified EPE in eight of nine (89%) patients. RSI-MRI correctly identified pT2 disease in the remaining 18 patients. CONCLUSIONS: In this proof of principle study, we conclude that our novel RSI-MRI technology is feasible and shows promise for substantially improving PCa imaging. Further translational studies of prostate RSI-MRI in the diagnosis and staging of PCa are indicated.
Subject(s)
Magnetic Resonance Imaging/methods , Prostate/diagnostic imaging , Prostatic Neoplasms/diagnostic imaging , Aged , Gadolinium , Humans , Male , Middle Aged , Neoplasm Staging , Prostate/pathology , Prostate-Specific Antigen , Prostatectomy , Prostatic Neoplasms/pathology , Prostatic Neoplasms/surgery , RadiographyABSTRACT
BACKGROUND AND PURPOSE: Robust, automated segmentation algorithms are required for quantitative analysis of large imaging datasets. We developed an automated method that identifies and labels brain tumor-associated pathology by using an iterative probabilistic voxel labeling using k-nearest neighbor and Gaussian mixture model classification. Our purpose was to develop a segmentation method which could be applied to a variety of imaging from The Cancer Imaging Archive. MATERIALS AND METHODS: Images from 2 sets of 15 randomly selected subjects with glioblastoma from The Cancer Imaging Archive were processed by using the automated algorithm. The algorithm-defined tumor volumes were compared with those segmented by trained operators by using the Dice similarity coefficient. RESULTS: Compared with operator volumes, algorithm-generated segmentations yielded mean Dice similarities of 0.92 ± 0.03 for contrast-enhancing volumes and 0.84 ± 0.09 for FLAIR hyperintensity volumes. These values compared favorably with the means of Dice similarity coefficients between the operator-defined segmentations: 0.92 ± 0.03 for contrast-enhancing volumes and 0.92 ± 0.05 for FLAIR hyperintensity volumes. Robust segmentations can be achieved when only postcontrast T1WI and FLAIR images are available. CONCLUSIONS: Iterative probabilistic voxel labeling defined tumor volumes that were highly consistent with operator-defined volumes. Application of this algorithm could facilitate quantitative assessment of neuroimaging from patients with glioblastoma for both research and clinical indications.
Subject(s)
Algorithms , Brain Neoplasms/pathology , Glioblastoma/pathology , Image Processing, Computer-Assisted/methods , Neuroimaging/methods , Archives , Humans , Magnetic Resonance Imaging/methodsABSTRACT
Converging evidence implicates immune abnormalities in schizophrenia (SCZ), and recent genome-wide association studies (GWAS) have identified immune-related single-nucleotide polymorphisms (SNPs) associated with SCZ. Using the conditional false discovery rate (FDR) approach, we evaluated pleiotropy in SNPs associated with SCZ (n=21,856) and multiple sclerosis (MS) (n=43,879), an inflammatory, demyelinating disease of the central nervous system. Because SCZ and bipolar disorder (BD) show substantial clinical and genetic overlap, we also investigated pleiotropy between BD (n=16,731) and MS. We found significant genetic overlap between SCZ and MS and identified 21 independent loci associated with SCZ, conditioned on association with MS. This enrichment was driven by the major histocompatibility complex (MHC). Importantly, we detected the involvement of the same human leukocyte antigen (HLA) alleles in both SCZ and MS, but with an opposite directionality of effect of associated HLA alleles (that is, MS risk alleles were associated with decreased SCZ risk). In contrast, we found no genetic overlap between BD and MS. Considered together, our findings demonstrate genetic pleiotropy between SCZ and MS and suggest that the MHC signals may differentiate SCZ from BD susceptibility.
Subject(s)
Bipolar Disorder/genetics , Genetic Pleiotropy/genetics , HLA Antigens/genetics , Multiple Sclerosis/genetics , Schizophrenia/genetics , Female , Follow-Up Studies , Genetic Predisposition to Disease , Genome-Wide Association Study , Genotype , Humans , Male , Polymorphism, Single NucleotideABSTRACT
While many studies have reported that individual differences in personality traits are genetically influenced, the neurobiological bases mediating these influences have not yet been well characterized. To advance understanding concerning the pathway from genetic variation to personality, here we examined whether measures of heritable variation in neuroanatomical size in candidate regions (amygdala and medial orbitofrontal cortex) were associated with heritable effects on personality. A sample of 486 middle-aged (mean=55 years) male twins (complete MZ pairs=120; complete DZ pairs=84) underwent structural brain scans and also completed measures of two core domains of personality: positive and negative emotionality. After adjusting for estimated intracranial volume, significant phenotypic (r(p)) and genetic (r(g)) correlations were observed between left amygdala volume and positive emotionality (r(p)=.16, p<.01; r(g)=.23, p<.05, respectively). In addition, after adjusting for mean cortical thickness, genetic and nonshared-environmental correlations (r(e)) between left medial orbitofrontal cortex thickness and negative emotionality were also observed (r(g)=.34, p<.01; r(e)=-.19, p<.05, respectively). These findings support a model positing that heritable bases of personality are, at least in part, mediated through individual differences in the size of brain structures, although further work is still required to confirm this causal interpretation.
Subject(s)
Amygdala/anatomy & histology , Frontal Lobe/anatomy & histology , Personality/genetics , Female , Genetic Variation , Humans , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Male , Middle Aged , Organ Size , PhenotypeABSTRACT
BACKGROUND: Pre- and perinatal adversities may increase the risk for schizophrenia and bipolar disorder. Hypoxia-related obstetric complications (OCs) are associated with brain anatomical abnormalities in schizophrenia, but their association with brain anatomy variation in bipolar disorder is unknown. METHOD: Magnetic resonance imaging brain scans, clinical examinations and data from the Medical Birth Registry of Norway were obtained for 219 adults, including 79 patients with a DSM-IV diagnosis of bipolar disorder (age 29.4 years, s.d. = 11.8 years, 39% male) and 140 healthy controls (age 30.8 years, s.d. = 12.0 years, 53% male). Severe hypoxia-related OCs throughout pregnancy/birth and perinatal asphyxia were each studied in relation to a priori selected brain volumes (hippocampus, lateral ventricles and amygdala, obtained with FreeSurfer), using linear regression models covarying for age, sex, medication use and intracranial volume. Multiple comparison adjustment was applied. RESULTS: Perinatal asphyxia was associated with smaller left amygdala volume (t = -2.59, p = 0.012) in bipolar disorder patients, but not in healthy controls. Patients with psychotic bipolar disorder showed distinct associations between perinatal asphyxia and smaller left amygdala volume (t = -2.69, p = 0.010), whereas patients with non-psychotic bipolar disorder showed smaller right hippocampal volumes related to both perinatal asphyxia (t = -2.60, p = 0.015) and severe OCs (t = -3.25, p = 0.003). No associations between asphyxia or severe OCs and the lateral ventricles were found. CONCLUSIONS: Pre- and perinatal hypoxia-related OCs are related to brain morphometry in bipolar disorder in adulthood, with specific patterns in patients with psychotic versus non-psychotic illness.