Suicide-related behaviors in older patients with new anti-epileptic drug use: data from the VA hospital system

<p>Abstract</p> <p>Background</p> <p>The U.S. Food and Drug Administration (FDA) recently linked antiepileptic drug (AED) exposure to suicide-related behaviors based on meta-analysis of randomized clinical trials. We examined the relationship between suicide-related behaviors and different AEDs in older veterans receiving new AED monotherapy from the Veterans Health Administration (VA), controlling for potential confounders.</p> <p>Methods</p> <p>VA and Medicare databases were used to identify veterans 66 years and older, who received a) care from the VA between 1999 and 2004, and b) an incident AED (monotherapy) prescription. Previously validated ICD-9-CM codes were used to identify suicidal ideation or behavior (suicide-related behaviors cases), epilepsy, and other conditions previously associated with suicide-related behaviors. Each case was matched to controls based on prior history of suicide-related behaviors, year of AED prescription, and epilepsy status.</p> <p>Results</p> <p>The strongest predictor of suicide-related behaviors (N = 64; Controls N = 768) based on conditional logistic regression analysis was affective disorder (depression, anxiety, or post-traumatic stress disorder (PTSD); Odds Ratio 4.42, 95% CI 2.30 to 8.49) diagnosed before AED treatment. Increased suicide-related behaviors were not associated with individual AEDs, including the most commonly prescribed AED in the US - phenytoin.</p> <p>Conclusion</p> <p>Our extensive diagnostic and treatment data demonstrated that the strongest predictor of suicide-related behaviors for older patients newly treated with AED monotherapy was a previous diagnosis of affective disorder. Additional, research using a larger sample is needed to clearly determine the risk of suicide-related behaviors among less commonly used AEDs.</p

Genetic variation and shared biological susceptibility underlying comorbidity in neuropsychiatry

Genetic factors underlying alcoholism, substance abuse, antisocial and violent behaviour, psychosis, schizophrenia and psychopathy are emerging to implicate dopaminergic and cannabinoid, but also monoaminergic and glutamatergic systems through the maze of promoter genes and polymorphisms. Candidate gene association studies suggest the involvement of a range of genes in different disorders of CNS structure and function. Indices of comorbidity both complicate the array of gene-involvement and provide a substrate of hazardous interactivity. The putative role of the serotonin transporter gene in affective-dissociative spectrum disorders presents both plausible genetic variation and complication of comorbidity. The position of genetic variation is further complicated through ethnic, contextual and social factors that provide geometric progressions in the comordity already underlying diagnostic obstacles. The concept of shared biological susceptibilty to two or more disorder conditions of comorbidity seems a recurring observation, e.g., bipolar disorder with alcoholism or schizophrenia with alcohol/substance abuse or diabetes with schizopsychotic disorder. Several lines of evidence seem to suggest that the factors influencing variation in one set of symptoms and those affecting one or more disorders are observed to a marked extent which ought to facilitate the search for susceptibility genes in comorbid brain disorders. Identification of regional genetic factors is awaited for a more compelling outline that ought eventually to lead to greater efficacy of symptom-disorder arrangements and an augmentation of current pharmacological treatment therapies

Cardiac autonomic changes in epilepsy

The term "Epilepsy" encompasses a broad spectrum of medical and social disorders that affect about 65 million people worldwide and is commonly defined as a tendency to suffer recurrent seizures. In patients with epilepsy, ictal discharges that occur in (or propagate to) the anterior cingulate, insular, posterior orbito-frontal, and the pre-frontal cortices, along with the amygdala and hypothalamus play a key role in influencing the autonomic nervous system (ANS) at the cortical level. In turn, this can result in cardiac effects which are widespread and range from subtle changes in heart rate variability (HRV) to ictal sinus arrest, and from QT-interval shortening to atrial fibrillation. In addition, cardiac events are the main hypothesized mechanisms underlying sudden unexpected death in epilepsy (SUDEP), which occurs in absence of a known structural cause. Patients with epilepsy also experience long-lasting changes in the regulation of the ANS and target organs. Heart rate (HR) and HRV can be easily measured/estimated when compared to other biomarkers that are commonly associated with seizures (i.e., long-term EEG), and are therefore potentially valuable biomarkers when it comes to characterizing seizures. In this context, a number of linear and nonlinear analysis techniques have been applied in order to detect and characterize epilepsy-related ANS changes. While the physiological and clinical applicability of nonlinear analyses like fractal and complexity measures of HR dynamics are not yet completely understood, in view of recent experimental findings it is reasonable to assume that such indices highlight abnormal patterns of RR interval behaviour that are not easily detected by commonly used moment statistics of HR variation. These findings may provide new insight regarding physiological and seizure- induced states of the complex brain-heart network underlying epilepsy and related autonomic modifications. A better understanding of the autonomic manifestations of seizures would provide practical added value to clinical epileptologists dealing with differential diagnosis of epilepsy and related disorders, as well as aiding in designing more sensitive seizure detection and prediction algorithms