Medication Responders Research Articles

Neuromelanin-Sensitive MRI as Candidate Marker for Treatment Resistance in First-Episode Schizophrenia.

Markers for treatment resistance in schizophrenia are needed to reduce delays in effective treatment. Nigrostriatal hyperdopaminergic function plays a critical role in the pathology of schizophrenia, yet antipsychotic nonresponders do not show increased dopamine function. Neuromelanin-sensitive MRI (NM-MRI), which indirectly measures dopamine function in the substantia nigra, has potential as a noninvasive marker for nonresponders. Increased NM-MRI signal has been shown in psychosis, but has not yet been assessed in nonresponders. In this study, the authors investigated whether nonresponders show lower NM-MRI signal than responders. NM-MRI scans were acquired in 79 patients with first-episode psychosis and 20 matched healthy control subjects. Treatment response was assessed at a 6-month follow-up. An a priori voxel-wise analysis within the substantia nigra tested the relation between NM-MRI signal and treatment response in patients. Fifteen patients were classified as nonresponders and 47 patients as responders. Seventeen patients were excluded, primarily because of medication nonadherence or change in diagnosis. Voxel-wise analysis revealed 297 significant voxels in the ventral tier of the substantia nigra that were negatively associated with treatment response. Nonresponders and healthy control subjects had significantly lower NM-MRI signal than responders. Receiver operating characteristic curve analysis showed that NM-MRI signal separated nonresponders with areas under the curve between 0.62 and 0.85. In addition, NM-MRI signal in patients did not change over 6 months. These findings provide further evidence for dopaminergic differences between medication responders and nonresponders and support the potential of NM-MRI as a clinically applicable marker for treatment resistance in schizophrenia.

One size does not fit all: notable individual variation in brain activity correlates of antidepressant treatment response.

To date, no robust electroencephalography (EEG) markers of antidepressant treatment response have been identified. Variable findings may arise from the use of group analyses, which neglect individual variation. Using a combination of group and single-participant analyses, we explored individual variability in EEG characteristics of treatment response. Resting-state EEG data and Montgomery-Åsberg Depression Rating Scale (MADRS) symptom scores were collected from 43 patients with depression before, at 1 and 12 weeks of pharmacotherapy. Partial least squares (PLS) was used to: 1) identify group differences in EEG connectivity (weighted phase lag index) and complexity (multiscale entropy) between eventual medication responders and non-responders, and 2) determine whether group patterns could be identified in individual patients. Responders showed decreased alpha and increased beta connectivity, and early, widespread decreases in complexity over treatment. Non-responders showed an opposite connectivity pattern, and later, spatially confined decreases in complexity. Thus, as in previous studies, our group analyses identified significant differences between groups of patients with different treatment outcomes. These group-level EEG characteristics were only identified in ~40-60% of individual patients, as assessed quantitatively by correlating the spatiotemporal brain patterns between groups and individual results, and by independent raters through visualization. Our single-participant analyses suggest that substantial individual variation exists, and needs to be considered when investigating characteristics of antidepressant treatment response for potential clinical applicability. https://clinicaltrials.gov, identifier NCT00519428.

Neural and Cognitive Predictors of Stimulant Treatment Efficacy in Medication-Naïve ADHD Adults: A Pilot Diffusion Tensor Imaging Study

Objective: Stimulant medications are the main treatment for Attention Deficit Hyperactivity Disorder (ADHD), but overall treatment efficacy in adults has less than a 60% response rate. This study aimed to identify neural and cognitive markers predictive of longitudinal improvement in response to stimulant treatment in drug-naïve adults with ADHD. Method: We used diffusion tensor imaging (DTI) and executive function measures with 36 drug-naïve adult ADHD patients in a prospective study design. Results: Structural connectivity (measured by fractional anisotropy, FA) in striatal regions correlated with ADHD clinical symptom improvement following stimulant treatment (amphetamine or methylphenidate) in better medication responders. A significant positive correlation was also found between working memory performance and stimulant-related symptom improvement. Higher pre-treatment working memory scores correlated with greater response. Conclusion: These findings provide evidence of pre-treatment neural and behavioral markers predictive of longitudinal treatment response to stimulant medications in adults with ADHD.

Daily-Living Freezing of Gait as Quantified Using Wearables in People With Parkinson Disease: Comparison With Self-Report and Provocation Tests.

Freezing of gait (FOG) is an episodic, debilitating phenomenon that is common among people with Parkinson disease. Multiple approaches have been used to quantify FOG, but the relationships among them have not been well studied. In this cross-sectional study, we evaluated the associations among FOG measured during unsupervised daily-living monitoring, structured in-home FOG-provoking tests, and self-report. Twenty-eight people with Parkinson disease and FOG were assessed using self-report questionnaires, percentage of time spent frozen (%TF) during supervised FOG-provoking tasks in the home while off and on dopaminergic medication, and %TF evaluated using wearable sensors during 1week of unsupervised daily-living monitoring. Correlations between those 3 assessment approaches were analyzed to quantify associations. Further, based on the %TF difference between in-home off-medication testing and in-home on-medication testing, the participants were divided into those responding to Parkinson disease medication (responders) and those not responding to Parkinson disease medication (nonresponders) in order to evaluate the differences in the other FOG measures. The %TF during unsupervised daily living was mild to moderately correlated with the %TF during a subset of the tasks of the in-home off-medication testing but not the on-medication testing or self-report. Responders and nonresponders differed in the %TF during the personal "hot spot" task of the provoking protocol while off medication (but not while on medication) but not in the total scores of the self-report questionnaires or the measures of FOG evaluated during unsupervised daily living. The %TF during daily living was moderately related to FOG during certain in-home FOG-provoking tests in the off-medication state. However, this measure of FOG was not associated with self-report or FOG provoked in the on-medication state. These findings suggest that to fully capture FOG severity, it is best to assess FOG using a combination of all 3 approaches. These findings suggest that several complementary approaches are needed to provide a complete assessment of FOG severity.

Striatal glutamate, subcortical structure and clinical response to first-line treatment in first-episode psychosis patients

IntroductionRecent studies have observed that patients with treatment-resistant schizophrenia as well as patients with schizophrenia who do not respond within a medication trial exhibit excess activity of the glutamate system. In this study we sought to replicate the within-trial glutamate abnormality and to investigate the potential for structural differences and treatment-induced changes to improve identification of medication responders and non-responders. MethodsWe enrolled 48 medication-naïve patients in a 4-week trial of risperidone and classified them retrospectively into responders and non-responders using clinical criteria. Proton magnetic resonance spectroscopy and T1-weighted structural MRI were acquired pre- and post-treatment to quantify striatal glutamate levels and several measures of subcortical brain structure. ResultsPatients were classified as 29 responders and 19 non-responders. Striatal glutamate was higher in the non-responders than responders both pre- and post-treatment (F1,39 = 7.15, p = .01). Volumetric measures showed a significant group x time interaction (t = 5.163, <1%FDR), and group x time x glutamate interaction (t = 4.23, <15%FDR) were seen in several brain regions. Striatal volumes increased at trend level with treatment in both groups, and a positive association of striatal volumes with glutamate levels was seen in the non-responders. ConclusionsCombining anatomic measures with glutamate levels offers the potential to enhance classification of responders and non-responders to antipsychotic medications as well as to provide mechanistic understanding of the interplay between neuroanatomical and neurochemical changes induced by these medications.Ethical statementThe study was approved by the Ethics and Scientific committees of the Instituto Nacional de Neurología y Neurocirugía in Mexico City. All participants over 18 years fully understood and signed the informed consent; in case the patient was under 18 years, informed consent was obtained from both parents. Participants did not receive a stipend.

Changes in the brain structural connectome after a prospective randomized clinical trial of lithium and quetiapine treatment in youth with bipolar disorder

The goals of the current study were to determine whether topological organization of brain structural networks is altered in youth with bipolar disorder, whether such alterations predict treatment outcomes, and whether they are normalized by treatment. Youth with bipolar disorder were randomized to double-blind treatment with quetiapine or lithium and assessed weekly. High-resolution MRI images were collected from children and adolescents with bipolar disorder who were experiencing a mixed or manic episode (n = 100) and healthy youth (n = 63). Brain networks were constructed based on the similarity of morphological features across regions and analyzed using graph theory approaches. We tested for pretreatment anatomical differences between bipolar and healthy youth and for changes in neuroanatomic network metrics following treatment in the youth with bipolar disorder. Youth with bipolar disorder showed significantly increased clustering coefficient (Cp) (p = 0.009) and characteristic path length (Lp) (p = 0.04) at baseline, and altered nodal centralities in insula, inferior frontal gyrus, and supplementary motor area. Cp, Lp, and nodal centrality of the insula exhibited normalization in patients following treatment. Changes in these neuroanatomic parameters were correlated with improvement in manic symptoms but did not differ between the two drug therapies. Baseline structural network matrices significantly differentiated medication responders and non-responders with 80% accuracy. These findings demonstrate that both global and nodal structural network features are altered in early course bipolar disorder, and that pretreatment alterations in neuroanatomic features predicted treatment outcome and were reduced by treatment. Similar connectome normalization with lithium and quetiapine suggests that the connectome changes are a downstream effect of both therapies that is related to their clinical efficacy.

Neural Predictors of the Antidepressant Placebo Response.

The antidepressant placebo response remains a barrier to the development of novel therapies for depression, despite decades of efforts to identify and methodologically address its clinical correlates. This manuscript reviews recent neuroimaging studies that aim to identify the neural signature of antidepressant placebo response. Data captured in clinical trials have primarily focused on antidepressant efficacy or predicting antidepressant response and have reliably implicated the rostral anterior cingulate cortex (rACC) in antidepressant placebo response, but also in medication response. Imaging and electroencephalography (EEG) experiments specifically interrogating the mechanism of antidepressant placebo response, while few, suggest the reward network, including opiate neurotransmission, is also involved. Therefore, while the rACC is likely involved in the antidepressant placebo response, its observation in isolation is unlikely to prospectively distinguish antidepressant placebo from medication responders. Instead, future studies of antidepressant placebo response should probe the reward network as a whole and incorporate sophisticated computational analytical approaches.

White Matter Indices of Medication Response in Major Depression: A Diffusion Tensor Imaging Study

BackgroundWhile response to antidepressants in major depressive disorder is difficult to predict, characterizing the organization and integrity of white matter in the brain with diffusion tensor imaging (DTI) may provide the means to distinguish between antidepressant responders and nonresponders. MethodsDTI data were collected at 6 sites (Canadian Biomarker Integration Network in Depression-1 [CAN-BIND-1 study]) from 200 (127 women) depressed and 112 (71 women) healthy participants at 3 time points: at baseline, 2 weeks, and 8 weeks following initiation of selective serotonin reuptake inhibitor treatment. Therapeutic response was established by a 50% reduction of symptoms at 8 weeks. Analysis on responders, nonresponders, and control subjects yielded 4 scalar metrics: fractional anisotropy and mean, axial, and radial diffusivity. Region-of-interest analysis was carried out on 40 white matter regions using a skeletonization approach. Mixed-effects regression was incorporated to test temporal trends. ResultsThe data acquired at baseline showed that axial diffusivity in the external capsule, which overlaps the superior longitudinal fasciculus, was significantly associated with medication response. Regression analysis revealed further baseline differences of responders compared with nonresponders in the cingulum regions, sagittal stratum, and corona radiata. Additional group differences relative to control subjects were seen in the internal capsule, posterior thalamic radiation, and uncinate fasciculus. Most effect sizes were moderate (near 0.5), with a maximum of 0.76 in the cingulum-hippocampus region. No temporal changes in DTI metrics were observed over the 8-week study period. ConclusionsSeveral DTI measures of altered white matter specifically distinguished medication responders and nonresponders at baseline and show promise for predicting treatment response in depression.

The More You Take It, the Better It Works: Six-Month Results of a Nalmefene Phase-IV Trial.

Background: Alcohol use disorders remain a major health problem. Reduced drinking has been increasingly recognized as a valuable alternative to abstinence. Nalmefene has shown in previous, experimental studies to be a useful tool to aid reduced drinking. However, more data from routine practice settings are needed in order to obtain evidence with high external validity. The aim of this study was to conduct a single-arm phase-IV study with alcohol-dependent outpatients starting with nalmefene for the first time. Here, we present the main effectiveness analysis, scheduled at six months. Methods: This was an observational, multisite, single-arm, phase-IV study conducted among adult alcohol-dependent outpatients who received nalmefene for the first time. The study consisted of four visits: Baseline, 1 month, 6 months, and 12 months. At each visit, drinking variables were obtained from the time-line follow-back regarding the previous month. Satisfaction with medication was also assessed from both patients and professionals with the Medication Satisfaction Questionnaire. A repeated measures mixed model was performed for effective analysis regarding drinking outcomes (reduction in total alcohol consumption and the number of heavy drinking days). Regression analyses were performed in order to find predictors of responses to nalmefene. Results: From a total of 110 patients included, 63 reported data at the six-month visit. On average, patients took nalmefene 69% of days during the month previous to the 6-month assessment. Compared to the one month results, the number of heavy drinking days and total alcohol consumption increased. Still, they were significantly lower than baseline values (outcome evolution over time was from 13.5 to 6.8 to 9.4 days/month, and from 169 to 79 to 116 units/month). A total of 23 patients were considered medication responders. The number of days of taking nalmefene was significantly associated in the regression analysis. Satisfaction was globally high for both professionals and patients and, overall, nalmefene was well-tolerated with no serious adverse events reported. Conclusion: The data provided by this phase-IV study suggest that nalmefene is an effective, well-tolerated treatment for alcohol-dependence in real world, clinical settings.

Methylphenidate selectively modulates one sub-component of the no-go P3 in pediatric ADHD medication responders

Methylphenidate (MPH) has been shown to modulate the amplitude of the no-go P3 component of the event-related potential (ERP; Øgrim, Aasen, & Brunner, 2016). Using group independent component analysis, the no-go P3 from a cued go/no-go task has been separated into two sub-components (Brunner et al., 2013). This study investigated whether sub-components of the no-go P3 could be identified in children with ADHD, and how MPH modulates their amplitudes. ERPs were registered twice (on/off MPH) in 57 children with ADHD classified as medication responders in a four-week medication trial. Two no-go P3 sub-components were identified. In the MPH session, the amplitude of one sub-component, the IC P3no-goearly (mean latency 378 ms, with a central distribution), was significantly larger than at baseline, whereas the other sub-component, the IC P3no-golate (mean latency 428 ms, with a centro-frontal distribution), was not significantly affected. These results add to the literature documenting that the no-go P3 consists of two overlapping phenomena with different functional correlates.

A Machine Learning Approach to Identifying Placebo Responders in Late-Life Depression Trials

Despite efforts to identify characteristics associated with medication-placebo differences in antidepressant trials, few consistent findings have emerged to guide participant selection in drug development settings and differential therapeutics in clinical practice. Limitations in the methodologies used, particularly searching for a single moderator while treating all other variables as noise, may partially explain the failure to generate consistent results. The present study tested whether interactions between pretreatment patient characteristics, rather than a single-variable solution, may better predict who is most likely to benefit from placebo versus medication. Data were analyzed from 174 patients aged 75 years and older with unipolar depression who were randomly assigned to citalopram or placebo. Model-based recursive partitioning analysis was conducted to identify the most robust significant moderators of placebo versus citalopram response. The greatest signal detection between medication and placebo in favor of medication was among patients with fewer years of education (≤12) who suffered from a longer duration of depression since their first episode (>3.47 years) (B = 2.53, t(32) = 3.01, p = 0.004). Compared with medication, placebo had the greatest response for those who were more educated (>12 years), to the point where placebo almost outperformed medication (B = -0.57, t(96) = -1.90, p = 0.06). Machine learning approaches capable of evaluating the contributions of multiple predictor variables may be a promising methodology for identifying placebo versus medication responders. Duration of depression and education should be considered in the efforts to modulate placebo magnitude in drug development settings and in clinical practice.

Predictive Neuroimaging Markers of Psychotherapy Response: A Systematic Review.

Predictive neuroimaging markers of treatment response are increasingly sought in order to inform the treatment of major depressive and anxiety disorders. We review the existing literature regarding candidate predictive neuroimaging markers of psychotherapy response and assess their potential clinical utility. We searched Embase, PsycINFO, and PubMed up to October 2014 for studies correlating pretreatment neuroimaging parameters with psychotherapy response in major depressive and anxiety disorders. Our search yielded 40 eligible studies. The anterior cingulate cortex, amygdala, and anterior insula emerged as potential markers in major depressive disorder and some anxiety disorders. Results across studies displayed a large degree of variability, however, and to date the findings have not been systematically validated in independent clinical cohorts and have not been shown capable of distinguishing between medication and psychotherapy responders. Also limited is the examination of how neuroimaging compares or might add to other prognostic clinical variables. While the extant data suggest avenues of further investigation, we are still far from being able to use these markers clinically. Future studies need to focus on longitudinal testing of potential markers, determining their prescriptive value and examining how they might be integrated with clinical factors.

Clinical Use of Bone Turnover Markers to Monitor Pharmacologic Fracture Prevention Therapy

Monitoring of drug therapies to prevent fractures is controversial. Measurement of bone turnover markers has the potential to identify those with a suboptimal response to fracture prevention medication within a few months of its commencement. However, given the imprecision of currently commercially available assays of bone turnover markers, many individual persons who are “suboptimal medication responders” are likely to be misclassified as “adequate responders” or vice versa, depending on the cut point chosen to define suboptimal and adequate response. Before bone turnover markers can be recommended for routine use in clinical practice to monitor fracture prevention therapies, three advances are needed: 1) bone marker assays with better precision; 2) research establishing optimal cut points of bone marker levels to distinguish “suboptimal responders” from “adequate responders”; and 3) research establishing the incremental fracture reduction benefit from clinical interventions for “suboptimal responders” identified from bone marker measurements.

Amygdala functional connectivity predicts pharmacotherapy outcome in pediatric bipolar disorder.

The aim of this study was to determine functional connectivity among patients with pediatric bipolar disorder (PBD) who are responders to pharmacotherapy and those who are nonresponders, and learn how they differ from healthy controls (HC) while performing a task that engages affective and cognitive neural systems. PBD participants (n = 34; 13.4 ± 2.3 years) were defined as responders if there was ≥ 50% improvement in Young Mania Rating Scale (YMRS) scores (n = 22) versus nonresponders with < 50% improvement (n = 12) with one of three mood stabilizing medications (divalproex, risperidone, or lamotrigine). HC (n = 14; 14.2 ± 3.1 years) participants also were scanned at baseline and follow-up. During functional magnetic resonance imaging, participants performed a color-matching task in which they had to match the color of positive, negative, or neutral words with colored dots. Independent component analysis was used to identify functionally connected networks across the whole brain, which were subsequently interrogated using region-of-interest analyses to test for group differences. A frontolimbic network was identified that showed impaired functional integration in PBD relative to HC when participants viewed negatively valenced words. PBD medication responders showed greater connectivity of the amygdala into the network before and after treatment compared with nonresponders, with responders showing a pattern more similar to HC than to nonresponders. Regardless of medication type, the degree of amygdala functional connectivity predicted medication response as well as the improvement in YMRS scores across responders and nonresponders. These findings suggest that increased functional integration of the amygdala within the frontolimbic network might be a biomarker of general mood stabilizer medication responsivity in bipolar disorder.

Evaluation of Quantitative EEG by Classification and Regression Trees to Characterize Responders to Antidepressant and Placebo Treatment

The study objective was to evaluate the usefulness of Classification and Regression Trees (CART), to classify clinical responders to antidepressant and placebo treatment, utilizing symptom severity and quantitative EEG (QEEG) data. Patients included 51 adults with unipolar depression who completed treatment trials using either fluoxetine, venlafaxine or placebo. Hamilton Depression Rating Scale (HAM-D) and single electrodes data were recorded at baseline, 2, 7, 14, 28 and 56 days. Patients were classified as medication and placebo responders or non-responders. CART analysis of HAM-D scores showed that patients with HAM-D scores lower than 13 by day 7 were more likely to be treatment responders to fluoxetine or venlafaxine compared to non-responders (p=0.001). Youden’s index γ revealed that CART models using QEEG measures were more accurate than HAM-D-based models. For patients given fluoxetine, patients with a decrease at day 2 in θ cordance at AF2 were classified by CART as treatment responders (p=0.02). For those receiving venlafaxine, CART identified a decrease in δ absolute power at day 7 at the PO2 region as characterizing treatment responders (p=0.01). Using all patients receiving medication, CART identified a decrease in δ absolute power at day 2 in the FP1 region as characteristic of nonresponse to medication (p=0.003). Optimal trees from the QEEG CART analysis primarily utilized cordance values, but also incorporated some δ absolute power values. The results of our study suggest that CART may be a useful method for identifying potential outcome predictors in the treatment of major depression.

Prediction of Placebo Response in 2 Clinical Trials of Lisdexamfetamine Dimesylate for the Treatment of ADHD

To search for predictors of placebo response in clinical trials of lisdexamfetamine dimesylate for the treatment of DSM-IV-TR-defined attention-deficit/hyperactivity disorder (ADHD) in children and adults. We used data from 2 clinical trials: (1) a 4-week, phase 3, multicenter, randomized, double-blind, forced-dose, parallel-group study of children aged 6 to 12 years with ADHD (n = 290) and (2) a 4-week, randomized, double-blind, placebo-controlled, parallel-group, forced-dose titration study in adult subjects, aged 18-55 years with ADHD (n = 420). Response and remission were defined using the ADHD Rating Scale-IV and the Clinical Global Impressions-Improvement scale. Symptom remission was inversely correlated with baseline severity in both children and adults (P < .001), with less robust effects seen for response. The time to response and remission was delayed in adult subjects prescribed placebo versus lisdexamfetamine dimesylate, while response time in children was also significantly slower with placebo versus lisdexamfetamine dimesylate (P < .01). We found little evidence that demographic factors, prior pharmacotherapy, the emergence of adverse events during the trial, or changes in ADHD symptoms from the screening to baseline assessments predicted placebo response. Certain comorbid medical symptoms reduced the response and remission rates to placebo in children (P < .001) and adults (P < .001). In both children and adults, baseline symptom severity was the most consistent predictor of remission with placebo while the temporal profile of response reliably differentiated placebo from medication responders. Placebo effects are most likely to be minimized in shorter trials enrolling more severely impaired subjects. The impact of medical and psychiatric comorbidities on placebo response merits further investigation. clinicaltrials.gov identifiers NCT00556296 and NCT00334880.

Open-label study of high (30 mg) and moderate (20 mg) dose escitalopram for the treatment of obsessive–compulsive disorder

This study sought to investigate the efficacy of escitalopram at different dosages for the treatment of obsessive-compulsive disorder (OCD). Thirty individuals were enrolled in a 16-week, open-label trial of escitalopram and randomly assigned to the 20 or 30 mg study arm. Study measures assessing OCD symptoms, anxiety, depression, and quality of life were administered at baseline and weeks 2, 4, 8, 12, and 16. For the 23 study completers, pretreatment and posttreatment analyses revealed significant improvements (P<0.05) on clinician-rated and self-rated measures of OCD symptoms, quality of life, anxiety, and depression. Approximately half of the sample (n = 12) satisfied full medication response criteria and less than one-quarter (n = 5) were partial medication responders. Intention-to-treat analyses showed similar improvements (P<0.05) on all study measures. At study completion, a superior responder rate and more improvement on the Yale-Brown Obsessive Compulsive Scale (P<0.05) was reported for those in the 30 versus 20 mg study arm. The difference between the two groups, however, disappeared when initial differences in baseline depression and anxiety scores were used as analysis covariates. These results suggest that the 30 mg (vs. 20 mg) dose of escitalopram may provide a superior reduction in OCD symptoms for those sufferers with comorbid depression and/or anxiety.

Disease Biomarkers in Multiple Sclerosis

Multiple sclerosis (MS) is an autoimmune disorder of the brain and spinal cord that predominantly affects white matter. MS has a variable clinical presentation and has no 'diagnostic' laboratory test; this often results in delays to definite diagnosis. In confronting the disease, early diagnosis and appropriate, timely therapeutic intervention are critical factors in ensuring favorable long-term outcomes. The availability of reliable biomarkers could radically alter our management of MS at critical phases of the disease spectrum. Identification of markers that could predict the development of MS in high-risk populations would allow for intervention strategies that may prevent evolution to definite disease. Work with anti-myelin antibodies and the ongoing analysis of microarray gene expression have thus far not yielded biomarkers that predict future disease development. Similarly, extensive studies with serum and cerebrospinal fluid (CSF) have not yielded a disease-specific and sensitive diagnostic biomarker for MS. Establishment of disease diagnosis always leads to questions about long-term prognosis because in an individual patient the natural history of the disease is clinically unpredictable. Biomarkers that correlate with myelin loss, spinal cord disease, grey matter and subcortical demyelination need to be developed in order to accurately predict the disease course. The bulk of effort in biomarker development in MS has been concentrated in the area of monitoring disease activity. At present, a disease 'activation' panel of CSF biomarkers would include the following: interleukin-6 or its soluble receptor, nitric oxide and nitric oxide synthase, osteopontin, and fetuin-A. Although disease activity in MS is predominantly inflammatory, disease progression is likely to be the result of neurodegeneration. Therefore, the roles of proteins indicative of neuronal, axonal, and glial loss such as neurofilaments, tau, 14-3-3 proteins, and N-acetylaspartate are all under investigation, as are proteins affecting remyelination and regeneration, such as Nogo-A. With the increasing awareness of cognition dysfunction in MS, molecules such as apolipoprotein and proteins in the amyloid precursor protein pathway implicated in dementia are also being examined. Serum biomarkers that help monitor therapeutic efficacy such as the titer of antibody to beta-interferon, a first-line medication in MS, are established in clinical practice. Ongoing work with biomarkers that reflect drug bioavailability and factors that distinguish between medication responders and nonresponders are also under investigation. The discovery of new biomarkers relies on applying advances in proteomics along with microarray gene and antigen analysis and will hopefully result in the establishment of specific biomarkers for MS.

EEG coherence in girls with Attention-Deficit/Hyperactivity Disorder: Stimulant effects in good responders

This study investigated the effects of stimulants on EEG coherence in girls with Attention-Deficit/Hyperactivity Disorder (AD/HD). Twenty girls with AD/HD (aged 7–12) and 20 age- and sex-matched controls had an eyes-closed resting electroencephalogram (EEG) recorded from 21 electrode sites. Coherence was calculated from eight intrahemispheric electrode pairs (four in each hemisphere), and eight interhemispheric electrode pairs, for the delta, theta, alpha and beta frequency bands. AD/HD participants were tested twice: first, prior to medication being prescribed, and second, six months later on a therapeutic dose of a stimulant. With intrahemispheric coherences at short-medium inter-electrode distances, AD/HD girls off-medication had reduced lateralisation in the delta, theta and alpha bands. They also had reduced lateralisation in the theta band for longer inter-electrode distances, and increased frontal interhemispheric coherences in all frequency bands. Medication had no impact on the laterality anomalies, but produced novel increases in intrahemispheric coherences at short-medium inter-electrode distances, which reached significance in the delta band and approached significance in the alpha band. However, these increased coherences remained indistinguishable from control levels. Reduced hemispheric lateralisations found in these AD/HD participants illustrate cortical abnormalities consistent with maturational lag explanations. The widespread elevated frontal interhemispheric coherences found in these AD/HD girls could reflect the narrow profile of female medication responders identified in clinical settings. The lack of substantial coherence medication effects in good clinical responders supports a previous medication study with AD/HD boys, and suggests that these coherence anomalies reflect structural, rather than solely functional, differences in brain development in AD/HD.

Antidepressant medicationsv.cognitive therapy in people with depression with or without personality disorder

There is conflicting evidence about comorbid personality pathology in depression treatments. To test the effects of antidepressant drugs and cognitive therapy in people with depression distinguished by the presence or absence of personality disorder. Random assignment of 180 out-patients with depression to 16 weeks of antidepressant medication or cognitive therapy. Random assignment of medication responders to continued medication or placebo, and comparison with cognitive therapy responders over a 12-month period. Personality disorder status led to differential response at 16 weeks; 66% v. 44% (antidepressants v. cognitive therapy respectively) for people with personality disorder, and 49% v. 70% (antidepressants v. cognitive therapy respectively) for people without personality disorder. For people with personality disorder, sustained response rates over the 12-month follow-up were nearly identical (38%) in the prior cognitive therapy and continuation-medication treatment arms. People with personality disorder withdrawn from medication evidenced the lowest sustained response rate (6%). Despite the poor response of people with personality disorder to cognitive therapy, nearly all those who did respond sustained their response. Comorbid personality disorder was associated with differential initial response rates and sustained response rates for two well-validated treatments for depression.