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Etiological Pathways (etiological + pathway)

Distribution by Scientific Domains

Medical Sciences	75%

Selected Abstracts

Covalent modification as a mechanism for the breakdown of immune tolerance to pyruvate dehydrogenase complex in the mouse

HEPATOLOGY, Issue 6 2004
Jeremy M. Palmer
The autoimmune liver disease primary biliary cirrhosis (PBC) is characterized by the breakdown of normal immune self tolerance to pyruvate dehydrogenase complex (PDC). How tolerance is broken to such a central and highly conserved self antigen in the initiation of autoimmunity remains unclear. One postulated mechanism is that reactivity arises to an altered form of self antigen with subsequent cross-reactivity to native self. In this murine study, we set out to examine whether sensitization with a covalently modified form of self PDC can give rise to the pattern of breakdown of B-cell and T-cell tolerance to self PDC seen in PBC patients. The notion that altered self can lead to tolerance breakdown was studied by sensitizing SJL/J mice with a covalently modified (biotinylated) preparation of self murine PDC (mP/O-B). Subsequently, antibody and T-cell reactivities to unmodified self mP/O were studied. Sensitization with mP/O-B elicited high-titre, high-affinity antibody responses reactive with both the mP/O-B immunogen and, importantly, native mP/O. In addition, significant MHC class II restricted splenic T-cell responses to native mP/O (i.e., true autoimmune responses) were seen in mP/O-B sensitized animals. The breakdown of T-cell self tolerance to mP/O was not seen in animals sensitized with irrelevant biotinylated antigens. In conclusion, this study provides evidence to support the concept that exposure to covalently modified self PDC can, in the correct proimmune environment, replicate the full breakdown of B-cell and T-cell immune tolerance to PDC seen in PBC. One potential etiological pathway in PBC therefore could be the breakdown of tolerance to self PDC occurring after exposure to self antigen covalently modified in the metabolically active environment of the liver. Supplementary material for this article can be found on the HEPATOLOGY website (http://interscience.wiley.com/jpages/0270-9139/suppmat/index.html). (HEPATOLOGY 2004;39:1583,1592.) [source]

Are there empirically supported and clinically useful subtypes of alcohol dependence?

ADDICTION, Issue 2006
Victor M. Hesselbrock
ABSTRACT Aims This paper provides an overview of several multidimensional empirically derived typologies of alcohol use disorders that have been derived primarily for research purposes in relation to their clinical utility. Methods Studies using multivariate statistical methods for identifying homogeneous groups of subjects were selected for inclusion. Theoretically based typologies were not included in this review. Results While formal diagnostic criteria typically identify separate categories of alcohol abuse and dependence, several studies using different statistical methods consistently suggest as many as four homogeneous types of alcoholism: a chronic/severe type, a depressed/anxious type, a mildly affected type and an antisocial type. Conclusions Even though the longitudinal outcomes of few empirically derived subtypes have been examined, alcoholism typologies remain a viable and potentially valuable tool for investigating etiological pathways, the effectiveness of treatments and the long-term course of alcohol use disorders. [source]

Association chain graphs: modelling etiological pathways

INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH, Issue 2 2003
Michael Höfler
Abstract Multiple time-dynamic and interrelated risk factors are usually involved in the complex etiology of disorders. This paper presents a strategy to explore and display visually the relative importance of different association pathways for the onset of disorder over time. The approach is based on graphical chain models, a tool that is powerful but still under-utilized in most fields. Usually, the results of these models are displayed using directed acyclic graphs (DAGs). These draw an edge between a pair of variables whenever the assumption of conditional independence given variables on an earlier or equal temporal footing is violated to a statistically significant extent. In the present paper, the graphs are modified in that confidence intervals for the strengths of associations (statistical main effects) are visualized. These new graphs are called association chain graphs (ACGs). Statistical interactions cause ,edges' between the respective variables within the DAG framework (because the assumption of conditional independence is violated). In contrast they are represented as separate graphs within the subsample where the different association chains may work within the ACG framework. With this new type of graph, more specific information can be displayed whenever the data are essentially described only with statistical main- and two-way interaction effects. Copyright © 2003 Whurr Publishers Ltd. [source]

Annotation: What electrical brain activity tells us about brain function that other techniques cannot tell us , a child psychiatric perspective

THE JOURNAL OF CHILD PSYCHOLOGY AND PSYCHIATRY AND ALLIED DISCIPLINES, Issue 5 2007
Tobias Banaschewski
Background:, Monitoring brain processes in real time requires genuine subsecond resolution to follow the typical timing and frequency of neural events. Non-invasive recordings of electric (EEG/ERP) and magnetic (MEG) fields provide this time resolution. They directly measure neural activations associated with a wide variety of brain states and processes, even during sleep or in infants. Mapping and source estimation can localise these time-varying activation patterns inside the brain. Methods: Recent EEG/ERP research on brain functions in the domains of attention and executive functioning, perception, memory, language, emotion and motor processing in ADHD, autism, childhood-onset schizophrenia, Tourette syndrome, specific language disorder and developmental dyslexia, anxiety, obsessive-compulsive disorder, and depression is reviewed. Results:, Over the past two decades, electrophysiology has substantially contributed to the understanding of brain functions during normal development, and psychiatric conditions of children and adolescents. Its time resolution has been important to measure covert processes, and to distinguish cause and effect. Conclusions:, In the future, EEG/ERP parameters will increasingly characterise the interplay of neural states and information processing. They are particularly promising tools for multilevel investigations of etiological pathways and potential predictors of clinical treatment response. [source]