Corticospinal tract (CST) degeneration and cortical atrophy are consistent features of amyotrophic lateral sclerosis (ALS). We hypothesised that neurite orientation dispersion and density imaging ...(NODDI), a multicompartment model of diffusion MRI, would reveal microstructural changes associated with ALS within the CST and precentral gyrus (PCG) 'in vivo'.
23 participants with sporadic ALS and 23 healthy controls underwent diffusion MRI. Neurite density index (NDI), orientation dispersion index (ODI) and free water fraction (isotropic compartment (ISO)) were derived. Whole brain voxel-wise analysis was performed to assess for group differences. Standard diffusion tensor imaging (DTI) parameters were computed for comparison. Subgroup analysis was performed to investigate for NODDI parameter differences relating to bulbar involvement. Correlation of NODDI parameters with clinical variables were also explored. The results were accepted as significant where p<0.05 after family-wise error correction at the cluster level, clusters formed with p<0.001.
In the ALS group NDI was reduced in the extensive regions of the CST, the corpus callosum and the right PCG. ODI was reduced in the right anterior internal capsule and the right PCG. Significant differences in NDI were detected between subgroups stratified according to the presence or absence of bulbar involvement. ODI and ISO correlated with disease duration.
NODDI demonstrates that axonal loss within the CST is a core feature of degeneration in ALS. This is the main factor contributing to the altered diffusivity profile detected using DTI. NODDI also identified dendritic alterations within the PCG, suggesting microstructural cortical dendritic changes occur together with CST axonal damage.
Objective markers of disease sensitive to the clinical activity, symptomatic progression, and underlying substrates of neurodegeneration are highly coveted in amyotrophic lateral sclerosis in order ...to more eloquently stratify the highly heterogeneous phenotype and facilitate the discovery of effective disease modifying treatments for patients. Magnetic resonance imaging (MRI) is a promising, non-invasive biomarker candidate whose acquisition techniques and analysis methods are undergoing constant evolution in the pursuit of parameters which more closely represent biologically-applicable tissue changes. Neurite Orientation Dispersion and Density Imaging (NODDI; a form of diffusion imaging), and quantitative Magnetization Transfer Imaging (qMTi) are two such emerging modalities which have each broadened the understanding of other neurological disorders and have the potential to provide new insights into structural alterations initiated by the disease process in ALS. Furthermore, novel neuroimaging data analysis approaches such as Event-Based Modeling (EBM) may be able to circumvent the requirement for longitudinal scanning as a means to comprehend the dynamic stages of neurodegeneration
. Combining these and other innovative imaging protocols with more sophisticated techniques to analyse ever-increasing datasets holds the exciting prospect of transforming understanding of the biological processes and temporal evolution of the ALS syndrome, and can only benefit from multicentre collaboration across the entire ALS research community.
Abstract Background Structural abnormalities across multiple white matter tracts are recognized in people with early psychosis, consistent with dysconnectivity as a neuropathological account of ...symptom expression. We applied advanced neuroimaging techniques to characterize microstructural white matter abnormalities for a deeper understanding of the developmental etiology of psychosis. Methods Thirty-five first-episode psychosis patients, and 19 healthy controls, participated in a quantitative neuroimaging study using neurite orientation dispersion and density imaging, a multishell diffusion-weighted magnetic resonance imaging technique that distinguishes white matter fiber arrangement and geometry from changes in neurite density. Fractional anisotropy (FA) and mean diffusivity images were also derived. Tract-based spatial statistics compared white matter structure between patients and control subjects and tested associations with age, symptom severity, and medication. Results Patients with first-episode psychosis had lower regional FA in multiple commissural, corticospinal, and association tracts. These abnormalities predominantly colocalized with regions of reduced neurite density, rather than aberrant fiber bundle arrangement (orientation dispersion index). There was no direct relationship with active symptoms. FA decreased and orientation dispersion index increased with age in patients, but not control subjects, suggesting accelerated effects of white matter geometry change. Conclusions Deficits in neurite density appear fundamental to abnormalities in white matter integrity in early psychosis. In the first application of neurite orientation dispersion and density imaging in psychosis, we found that processes compromising axonal fiber number, density, and myelination, rather than processes leading to spatial disruption of fiber organization, are implicated in the etiology of psychosis. This accords with a neurodevelopmental origin of aberrant brain-wide structural connectivity predisposing individuals to psychosis.
Objective
To characterize disease evolution in amyotrophic lateral sclerosis using an event‐based model designed to extract temporal information from cross‐sectional data. Conventional methods for ...understanding mechanisms of rapidly progressive neurodegenerative disorders are limited by the subjectivity inherent in the selection of a limited range of measurements, and the need to acquire longitudinal data.
Methods
The event‐based model characterizes a disease as a series of events, each comprising a significant change in subject state. The model was applied to data from 154 patients and 128 healthy controls selected from five independent diffusion MRI datasets acquired in four different imaging laboratories between 1999 and 2016. The biomarkers modeled were mean fractional anisotropy values of white matter tracts implicated in amyotrophic lateral sclerosis. The cerebral portion of the corticospinal tract was divided into three segments.
Results
Application of the model to the pooled datasets revealed that the corticospinal tracts were involved before other white matter tracts. Distal corticospinal tract segments were involved earlier than more proximal (i.e., cephalad) segments. In addition, the model revealed early ordering of fractional anisotropy change in the corpus callosum and subsequently in long association fibers.
Interpretation
These findings represent data‐driven evidence for early involvement of the corticospinal tracts and body of the corpus callosum in keeping with conventional approaches to image analysis, while providing new evidence to inform directional degeneration of the corticospinal tracts. This data‐driven model provides new insight into the dynamics of neuronal damage in amyotrophic lateral sclerosis.
Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely ...understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC.
Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals).
Positive genetic correlation was observed between MD and AD (rgMD-AD = + 0.47, P = 6.6 × 10-10). AC-quantity showed positive genetic correlation with both AD (rgAD-AC quantity = + 0.75, P = 1.8 × 10-14) and MD (rgMD-AC quantity = + 0.14, P = 2.9 × 10-7), while there was negative correlation of AC-frequency with MD (rgMD-AC frequency = -0.17, P = 1.5 × 10-10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10-6). There was no evidence for reverse causation.
This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.
Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD ...and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10
) and African ancestries (rs2066702; P = 2.2 × 10
). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.
Eating disorders and substance use disorders frequently co‐occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest ...associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation rg, twin‐based = 0.23‐0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome‐wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa AN, AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance‐use‐related phenotypes (drinks per week, alcohol use disorder AUD, smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism‐based genetic correlations between eating disorder‐ and substance‐use‐related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = −0.19 to −0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co‐varying for major depressive disorder loci. The patterns of association between eating disorder‐ and substance‐use‐related phenotypes highlights the potentially complex and substance‐specific relationships among these behaviors.
Eating disorders and substance use disorders frequently co‐occur. Using genome‐wide association studies, we found differential patterns of genetic correlations between specific eating disorder‐ and substance‐use‐ related phenotypes. These patterns of association highlight the potentially complex and substance‐specific associations among eating disorder‐ and substance‐use‐related behaviors.
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