Integrative Bayesian analysis of neuroimaging-genetic data with application to cocaine dependence

Role of deep brain stimulation (DBS) in addiction disorders

Background

Addiction disorders pose significant challenges to public health, necessitating innovative treatments. This assesses deep brain stimulation (DBS) as a potential intervention for addiction disorders.

Methods

A literature review was carried out with a focus on the role of DBS in addiction disorders and its future implications in neurosurgical research.

Results

The online literature shows that DBS precisely modulates certain brain regions to restore addiction-related neural circuits and promote behavioral control.

Conclusion

Preclinical evidence demonstrates DBS's potential to rebalance neural circuits associated with addiction, and early clinical trials provide encouraging outcomes in enhancing addiction-related outcomes. Ethical considerations, long-term safety, and personalized patient selection require further investigation.

Prefrontal-habenular microstructural impairments in human cocaine and heroin addiction

The habenula (Hb) is central to adaptive reward- and aversion-driven behaviors, comprising a hub for higher-order processing networks involving the prefrontal cortex (PFC). Despite an established role in preclinical models of cocaine addiction, the translational significance of the Hb and its connectivity with the PFC in humans is unclear. Using diffusion tractography, we detailed PFC structural connectivity with the Hb and two control regions, quantifying tract-specific microstructural features in healthy and cocaine-addicted individuals. White matter was uniquely impaired in PFC-Hb projections in both short-term abstainers and current cocaine users. Abnormalities in this tract further generalized to an independent sample of heroin-addicted individuals and were associated, in an exploratory analysis, with earlier onset of drug use across the addiction subgroups, potentially serving as a predisposing marker amenable for early intervention. Importantly, these findings contextualize a plausible PFC-Hb circuit in the human brain, supporting preclinical evidence for its impairment in cocaine addiction.

Neurite orientation dispersion and density imaging in cocaine use disorder

Cocaine use disorder (CUD) is characterized by a compulsive search for cocaine. Several studies have shown that cocaine users exhibit cognitive deficits, including lack of inhibition and decision-making as well as brain volume and diffusion-based white-matter alterations in a wide variety of brain regions. However, the non-specificity of standard volumetric and diffusion-tensor methods to detect structural micropathology may lead to wrong conclusions. To better understand microstructural pathology in CUD, we analyzed 60 CUD participants (3 female) and 43 non-CUD controls (HC; 2 female) retrospectively from our cross-sectional Mexican SUD neuroimaging dataset (SUDMEX-CONN), using multi-shell diffusion-weighted imaging and the neurite orientation dispersion and density imaging (NODDI) analysis, which aims to more accurately model microstructural pathology. We used Viso values of NODDI that employ a three-compartment model in white (WM) and gray-matter (GM). These values were also correlated with clinical measures, including psychiatric severity status, impulsive behavior and pattern of cocaine and tobacco use in the CUD group. We found higher whole-brain microstructural pathology in WM and GM in CUD patients than controls. ROI analysis revealed higher Viso-NODDI values in superior longitudinal fasciculus, cingulum, hippocampus cingulum, forceps minor and Uncinate fasciculus, as well as in frontal and parieto-temporal GM structures. We also found correlations between significant ROI and impulsivity, onset age of cocaine use and weekly dosage with Viso-NODDI. However, we did not find correlations with psychopathology measures. Overall, although their clinical relevance remains questionable, microstructural pathology seems to be present in CUD both in gray and white matter.

Exploring the relationship between white matter integrity, cocaine use and GAD polymorphisms using Bayesian Model Averaging

Past investigations utilizing diffusion tensor imaging (DTI) have demonstrated that cocaine use disorder (CUD) yields white matter changes, primarily in the corpus callosum. By applying Bayesian model averaging using multiple linear regression in DTI, we demonstrate there may exist relationships between the impaired white matter and glutamic acid decarboxylase (GAD) polymorphisms. This work explored the two-way and three-way interactions between GAD1a (SNP: rs1978340) and GAD1b (SNP: rs769390) polymorphisms and years of cocaine use (YCU). GAD1a was associated with more frontal white matter changes on its own but GAD1b was associated with more midbrain and cerebellar changes as well as a greater increase in white matter changes in the context of chronic cocaine use. The three-way interaction GAD1a|GAD1b|YCU appeared to be roughly an average of the polymorphism two-way interactions GAD1a|YCU and GAD1b|YCU. The three-way interaction demonstrated multiple regions including corpus callosum which featured fewer significant voxel changes, perhaps suggesting a small protective effect of having both polymorphisms on corpus callosum and cerebellar peduncle.

Revista Digital Internacional de Psicología y Ciencia Social | Volumen 6 | Número 2 | Julio-Diciembre 2020 | Desafíos contemporáneos en educación y salud

El actual número se titula “Desafíos contemporáneos en educación y salud” y nos permite conocer acerca de los temas de interés para algunos investigadores y la manera en que se han abordado para su estudio. De manera coincidente este número ha sido trabajado en tiempos de pandemia, donde también nos hemos enfrentado a retos ante las nuevas condiciones para adaptarnos a nuevas formas de trabajo, mayoritariamente a distancia y por ahora a lo que parece ser “la nueva normalidad”, y con ello, en algunos meses, estaremos leyendo trabajos que surjan de estos momentos históricos mundiales, sus implicaciones, problemas, alcances y tal vez sus repercusiones.

Modelos neuropsicologicos y neuroimagen de las alteraciones cerebrales ocasionadas por la cocaína

La presente revisión de literatura hace referencia a los modelos que la neuropsicología manifiesta en relación a la drogodependencia, con el propósito de explicar el origen y desarrollo de los trastornos adictivos, respaldados por medio de la neuroimagen. El modelo clásico de la adicción, propuesto por Wikel (1965), el cual fue reformulado por nuevos modelos, entre los más destacados, el modelo basado en la transición entre impulsividad y compulsión de Everitt y Robbins (2005), el modelo de alostasis y estrés de Koob y Le Moal (2001, 2008), y el modelo de la sensibilización al incentivo de Robinson y Berridge (2001, 2003, 2008). De manera alternativa surgió el modelo (I-RISA) de Goldstein y Volkow (2002). Al final se formuló el modelo somático de las drogodependencias propuesto por Verdejo-García y Bechara (2009) y Pérez-García y Bechara (2006). Por último se aborda la recuperación o rehabilitación de la adicción desde una perspectiva neurológica y neuropsicológica.

RADIO-IBAG: RADIOMICS-BASED INTEGRATIVE BAYESIAN ANALYSIS OF MULTIPLATFORM GENOMIC DATA

Technological innovations have produced large multi-modal datasets that include imaging and multi-platform genomics data. Integrative analyses of such data have the potential to reveal important biological and clinical insights into complex diseases like cancer. In this paper, we present Bayesian approaches for integrative analysis of radiological imaging and multi-platform genomic data, wherein our goals are to simultaneously identify genomic and radiomic, i.e., radiology-based imaging markers, along with the latent associations between these two modalities, and to detect the overall prognostic relevance of the combined markers. For this task, we propose Radio-iBAG: Radiomics-based Integrative Bayesian Analysis of Multiplatform Genomic Data, a multi-scale Bayesian hierarchical model that involves several innovative strategies: it incorporates integrative analysis of multi-platform genomic data sets to capture fundamental biological relationships; explores the associations between radiomic markers accompanying genomic information with clinical outcomes; and detects genomic and radiomic markers associated with clinical prognosis. We also introduce the use of sparse Principal Component Analysis (sPCA) to extract a sparse set of approximately orthogonal meta-features each containing information from a set of related individual radiomic features, reducing dimensionality and combining like features. Our methods are motivated by and applied to The Cancer Genome Atlas glioblastoma multiforme data set, where-in we integrate magnetic resonance imaging-based biomarkers along with genomic, epigenomic and transcriptomic data. Our model identifies important magnetic resonance imaging features and the associated genomic platforms that are related with patient survival times.

Substance abuse and white matter: Findings, limitations, and future of diffusion tensor imaging research

Individuals who abuse substances often differ from nonusers in their brain structure. Substance abuse and addiction is often associated with atrophy and pathology of grey matter, but much less is known about the role of white matter, which constitutes over half of human brain volume. Diffusion tensor imaging (DTI), a method for non-invasively estimating white matter, is increasingly being used to study addiction and substance abuse. Here we review recent DTI studies of major substances of abuse (alcohol, opiates, cocaine, cannabis, and nicotine substance abuse) to examine the relationship, specificity, causality, and permanence of substance-related differences in white matter microstructure. Across substance, users tended to exhibit differences in the microstructure of major fiber pathways, such as the corpus callosum. The direction of these differences, however, appeared substance-dependent. The subsample of longitudinal studies reviewed suggests that substance abuse may cause changes in white matter, though it is unclear to what extent such alterations are permanent. While collectively informative, some studies reviewed were limited by methodological and technical approach. We therefore also provide methodological guidance for future research using DTI to study substance abuse.