Towards precision in the diagnostic profiling of patients: leveraging symptom dynamics as a clinical characterisation dimension in the assessment of major depressive disorder

BACKGROUND

International guidelines present overall symptom severity as the key dimension for clinical characterisation of major depressive disorder (MDD). However, differences may reside within severity levels related to how symptoms interact in an individual patient, called symptom dynamics.

AIMS

To investigate these individual differences by estimating the proportion of patients that display differences in their symptom dynamics while sharing the same overall symptom severity.

METHOD

Participants with MDD (n = 73; mean age 34.6 years, s.d. = 13.1; 56.2% female) rated their baseline symptom severity using the Inventory for Depressive Symptomatology Self-Report (IDS-SR). Momentary indicators for depressive symptoms were then collected through ecological momentary assessments five times per day for 28 days; 8395 observations were conducted (average per person: 115; s.d. = 16.8). Each participant's symptom dynamics were estimated using person-specific dynamic network models. Individual differences in these symptom relationship patterns in groups of participants sharing the same symptom severity levels were estimated using individual network invariance tests. Subsequently, the overall proportion of participants that displayed differential symptom dynamics while sharing the same symptom severity was calculated. A supplementary simulation study was conducted to investigate the accuracy of our methodology against false-positive results.

RESULTS

Differential symptom dynamics were identified across 63.0% (95% bootstrapped CI 41.0-82.1) of participants within the same severity group. The average false detection of individual differences was 2.2%.

CONCLUSIONS

The majority of participants within the same depressive symptom severity group displayed differential symptom dynamics. Examining symptom dynamics provides information about person-specific psychopathological expression beyond severity levels by revealing how symptoms aggravate each other over time. These results suggest that symptom dynamics may be a promising new dimension for clinical characterisation, warranting replication in independent samples. To inform personalised treatment planning, a next step concerns linking different symptom relationship patterns to treatment response and clinical course, including patterns related to spontaneous recovery and forms of disorder progression.

Effect of Daily Life Reward Loop Functioning on the Course of Depression

Engagement in activities increases positive affect (Reward Path 1), which subsequently reinforces motivation (Reward Path 2), and hence future engagement in activities (Reward Path 3). Strong connections between these three reward loop components are considered adaptive, and might be disturbed in depression. Although some ecological nomentary assessment (EMA) studies have investigated the cross-sectional association between separate reward paths and individuals' level of depression, no EMA study has looked into the association between individuals' reward loop strength and depressive symptom course. The present EMA study assessed reward loop functioning (5x/day, 28 days) of 46 outpatients starting depression treatment at secondary mental health services and monitored with the Inventory of Depressive Symptomatology-Self-Report (IDS-SR) during a 7-month period. Results of multilevel regression analyses showed significant within-person associations for Reward Path 1 (b = 0.21, p < .001), Reward Path 2 (b = 0.43, p < .001), and Reward Path 3 (b = 0.20, p < .001). Stronger average reward loops (i.e., within-person mean of all reward paths) did not relate to participants' improvement in depressive symptoms over time. Path-specific results revealed that Reward Paths 1 and 2 may have partly opposite effects on depressive symptom course. Together, our findings suggest that reward processes in daily life might be best studied separately and that further investigation is warranted to explore under what circumstances strong paths are adaptive or not.

Statistical power in clinical trials of interventions for mood, anxiety, and psychotic disorders

BACKGROUND

Previous research has suggested that statistical power is suboptimal in many biomedical disciplines, but it is unclear whether power is better in trials for particular interventions, disorders, or outcome types. We therefore performed a detailed examination of power in trials of psychotherapy, pharmacotherapy, and complementary and alternative medicine (CAM) for mood, anxiety, and psychotic disorders.

METHODS

We extracted data from the Cochrane Database of Systematic Reviews (Mental Health). We focused on continuous efficacy outcomes and estimated power to detect predetermined effect sizes (standardized mean difference [SMD] = 0.20-0.80, primary SMD = 0.40) and meta-analytic effect sizes (ESMA). We performed meta-regression to estimate the influence of including underpowered studies in meta-analyses.

RESULTS

We included 256 reviews with 10 686 meta-analyses and 47 384 studies. Statistical power for continuous efficacy outcomes was very low across intervention and disorder types (overall median [IQR] power for SMD = 0.40: 0.32 [0.19-0.54]; for ESMA: 0.23 [0.09-0.58]), only reaching conventionally acceptable levels (80%) for SMD = 0.80. Median power to detect the ESMA was higher in treatment-as-usual (TAU)/waitlist-controlled (0.49-0.63) or placebo-controlled (0.12-0.38) trials than in trials comparing active treatments (0.07-0.13). Adequately-powered studies produced smaller effect sizes than underpowered studies (B = -0.06, p ⩽ 0.001).

CONCLUSIONS

Power to detect both predetermined and meta-analytic effect sizes in psychiatric trials was low across all interventions and disorders examined. Consistent with the presence of reporting bias, underpowered studies produced larger effect sizes than adequately-powered studies. These results emphasize the need to increase sample sizes and to reduce reporting bias against studies reporting null results to improve the reliability of the published literature.

Identifying mismatch and match between clinical needs and mental healthcare use trajectories in people with anxiety and depression: Results of a longitudinal study

BACKGROUND

Mismatch between need and mental healthcare (MHC) use (under-and overuse) has mainly been studied with cross-sectional designs, not accurately capturing patterns of persistence or change in clinical burden and MHC-use among persons with depressive and/or anxiety disorders.

AIMS

Determining and describing [mis]match of longitudinal trajectories of clinical burden and MHC-use.

METHODS

Six-year longitudinal burden and MHC-use data came from the Netherlands Study of Depression and Anxiety (n=2981). The sample was split into four subgroups: I) no clinical burden but constant MHC use, II) constant clinical burden but no MHC-use, III) changing clinical burden and MHC-use, and IV) healthy non-users. Within subgroups I)-III), specific clinical burden and MHC trajectories were identified (growth mixture modeling). The resulting classes' associations with predisposing, enabling, and need factors were investigated (regression analysis).

RESULTS

Subgroups I-III revealed different trajectories. I) increasing MHC without burden (4.1%). II) slightly increasing (1.9%), strongly increasing (2.4%), and decreasing (9.5%) burden without MHC. III) increasing (41.4%) or decreasing (19.4%) burden and concurrently increasing MHC use (first underuse, then matched care), thus revealing delayed MHC-use. Only having suicidal ideation (p<.001, Cohen's d= .6-1.5) was a significant determinant of being in latter classes compared to underusers (strongly increasing burden without MHC-use).

LIMITATIONS

More explanatory factors are needed to explain [mis]match.

CONCLUSION

Mismatch occurred as constant underuse or as delayed MHC-use in a high-income country (Netherlands). Additionally, no meaningful class revealed constantly matched care on average. Presence of suicidal ideation could influence the probability of symptomatic individuals receiving matched MHC or not.

Comparing the evidential strength for psychotropic drugs: a Bayesian meta-analysis

Approval and prescription of psychotropic drugs should be informed by the strength of evidence for efficacy. Using a Bayesian framework, we examined (1) whether psychotropic drugs are supported by substantial evidence (at the time of approval by the Food and Drug Administration), and (2) whether there are systematic differences across drug groups. Data from short-term, placebo-controlled phase II/III clinical trials for 15 antipsychotics, 16 antidepressants for depression, nine antidepressants for anxiety, and 20 drugs for attention deficit hyperactivity disorder (ADHD) were extracted from FDA reviews. Bayesian model-averaged meta-analysis was performed and strength of evidence was quantified (i.e. BFBMA). Strength of evidence and trialling varied between drugs. Median evidential strength was extreme for ADHD medication (BFBMA = 1820.4), moderate for antipsychotics (BFBMA = 365.4), and considerably lower and more frequently classified as weak or moderate for antidepressants for depression (BFBMA = 94.2) and anxiety (BFBMA = 49.8). Varying median effect sizes (ESschizophrenia = 0.45, ESdepression = 0.30, ESanxiety = 0.37, ESADHD = 0.72), sample sizes (Nschizophrenia = 324, Ndepression = 218, Nanxiety = 254, NADHD = 189.5), and numbers of trials (kschizophrenia = 3, kdepression = 5.5, kanxiety = 3, kADHD = 2) might account for differences. Although most drugs were supported by strong evidence at the time of approval, some only had moderate or ambiguous evidence. These results show the need for more systematic quantification and classification of statistical evidence for psychotropic drugs. Evidential strength should be communicated transparently and clearly towards clinical decision makers.

Consensus-based guidance for conducting and reporting multi-analyst studies

Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research.

Patients' experience of an ecological momentary intervention involving self-monitoring and personalized feedback for depression

Experts in clinical mental health research count on personalized approaches based on self-monitoring and self-management to improve treatment efficacy in psychiatry. Among other things, researchers expect that Ecological Momentary Interventions (EMI) based on self-monitoring and personalized feedback will reduce depressive symptoms. Clinical trial findings have, however, been conflicting. A recent trial (ZELF-i) investigated whether depression treatment might be enhanced by an add-on EMI with self-monitoring items and feedback focused on positive affect and activities (Do-module) or on negative affect and thinking patterns (Think-module). There was no statistical evidence that this EMI impacted clinical or functional outcomes beyond the effects of regular care, regardless of module content. In apparent contrast, 86% of the participants who completed the intervention indicated they would recommend it to others. In the present study, we used in-depth interviews (n = 20) to better understand the EMI's personal and clinical benefits and downsides. A thematic analysis of the interviews generated six areas of impact with various subthemes. In line with the trial results, few participants reported behavioral changes or symptom improvement over time; the self-assessments mainly amplified momentary mood, in either direction. The most often mentioned benefits were an increase in self-awareness, insight, and self-management (e.g., a stronger sense of control over complaints). Consistently, these domains received the highest ratings in our evaluation questionnaire (n = 89). Furthermore, the EMI instilled a routine into the days of individuals without regular jobs or other activities. Participants reported few downsides. The experiences were rather similar between the two modules. This study suggests that EMI might contribute to health by helping individuals deal with their symptoms, rather than reducing them. Measures on self-awareness, insight, and self-management should be more emphatically involved in future EMI research.

An evaluation of the efficacy of two add-on ecological momentary intervention modules for depression in a pragmatic randomized controlled trial (ZELF-i)

BACKGROUND

Depression treatment might be enhanced by ecological momentary interventions (EMI) based on self-monitoring and person-specific feedback. This study is the first to examine the efficacy of two different EMI modules for depression in routine clinical practice.

METHODS

Outpatients starting depression treatment at secondary mental health services (N = 161; MIDS-DEPRESSION = 35.9, s.d. = 10.7; MAGE = 32.8, s.d. = 12.1; 46% male) participated in a pragmatic randomized controlled trial with three arms. Two experimental groups engaged in 28 days of systematic self-monitoring (5 times per day), and received weekly feedback on either positive affect and activities (Do-module) or negative affect and thinking patterns (Think-module). The control group received no additional intervention. Participants completed questionnaires on depressive symptoms (primary outcome), social functioning, and empowerment before and after the intervention period, and at four measurements during a 6-month follow-up period.

RESULTS

Of the 90 (out of 110) participants who completed the intervention, 86% would recommend it. However, the experimental groups did not show significantly more or faster changes over time than the control group in terms of depressive symptoms, social functioning, and empowerment. Furthermore, the trajectories of the two EMI modules were very similar.

CONCLUSIONS

We did not find statistical evidence that this type of EMI augments the efficacy of regular depression treatment, regardless of module content. We cannot rule out that EMIs have a positive impact on other domains or provide a more efficient way of delivering care. Nonetheless, EMI's promise of effectiveness has not materialized yet.

Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology

OBJECTIVE

One of the promises of the experience sampling methodology (ESM) is that a statistical analysis of an individual's emotions, cognitions and behaviors in everyday-life could be used to identify relevant treatment targets. A requisite for clinical implementation is that outcomes of such person-specific time-series analyses are not wholly contingent on the researcher performing them.

METHODS

To evaluate this, we crowdsourced the analysis of one individual patient's ESM data to 12 prominent research teams, asking them what symptom(s) they would advise the treating clinician to target in subsequent treatment.

RESULTS

Variation was evident at different stages of the analysis, from preprocessing steps (e.g., variable selection, clustering, handling of missing data) to the type of statistics and rationale for selecting targets. Most teams did include a type of vector autoregressive model, examining relations between symptoms over time. Although most teams were confident their selected targets would provide useful information to the clinician, not one recommendation was similar: both the number (0-16) and nature of selected targets varied widely.

CONCLUSION

This study makes transparent that the selection of treatment targets based on personalized models using ESM data is currently highly conditional on subjective analytical choices and highlights key conceptual and methodological issues that need to be addressed in moving towards clinical implementation.

From laboratory to life: associating brain reward processing with real-life motivated behaviour and symptoms of depression in non-help-seeking young adults

BACKGROUND

Depression has been associated with abnormalities in neural underpinnings of Reward Learning (RL). However, inconsistencies have emerged, possibly owing to medication effects. Additionally, it remains unclear how neural RL signals relate to real-life behaviour. The current study, therefore, examined neural RL signals in young, mildly to moderately depressed - but non-help-seeking and unmedicated - individuals and how these signals are associated with depressive symptoms and real-life motivated behaviour.

METHODS

Individuals with symptoms along the depression continuum (n = 87) were recruited from the community. They performed an RL task during functional Magnetic Resonance Imaging and were assessed with the Experience Sampling Method (ESM), completing short questionnaires on emotions and behaviours up to 10 times/day for 15 days. Q-learning model-derived Reward Prediction Errors (RPEs) were examined in striatal areas, and subsequently associated with depressive symptoms and an ESM measure capturing (non-linearly) how anticipation of reward experience corresponds to actual reward experience later on.

RESULTS

Significant RPE signals were found in the striatum, insula, amygdala, hippocampus, frontal and occipital cortices. Region-of-interest analyses revealed a significant association between RPE signals and (a) self-reported depressive symptoms in the right nucleus accumbens (b = -0.017, p = 0.006) and putamen (b = -0.013, p = .012); and (b) the quadratic ESM variable in the left (b = 0.010, p = .010) and right (b = 0.026, p = 0.011) nucleus accumbens and right putamen (b = 0.047, p < 0.001).

CONCLUSIONS

Striatal RPE signals are disrupted along the depression continuum. Moreover, they are associated with reward-related behaviour in real-life, suggesting that real-life coupling of reward anticipation and engagement in rewarding activities might be a relevant target of psychological therapies for depression.

Different Aspects of the Neural Response to Socio-Emotional Events Are Related to Instability and Inertia of Emotional Experience in Daily Life: An fMRI-ESM Study

Emotions are fundamentally temporal processes that dynamically change over time. This temporal nature is inherently involved in making emotions adaptive by guiding interactions with our environment. Both the size of emotional changes across time (i.e., emotional instability) and the tendency of emotions to persist across time (i.e., autocorrelation of emotional experience, emotional inertia) are key features of a person’s emotion dynamics, and have been found central to maladaptive functioning and psychopathology as well as linked to social functioning. However, whether different (neural) mechanisms are underlying these dynamics as well as how they are related to the processing of (socio-) emotional information is to date widely unknown. Using a combination of Experience Sampling methods (ESMs) and fMRI (involving a social feedback paradigm), we examine how emotional instability and inertia in everyday life are associated with different aspects of the neural response to socio-emotional events. The findings indicate that while emotional instability is connected to the response of the core salience network (SN), emotional inertia is associated to responses in the parahippocampal gyrus (PHG) and lateral orbitofrontal cortex (lOFC). This is the first study showing that different aspects of the neural response to socio-emotional events are associated with different aspects of the temporal dynamics of emotion in real life.

Self-monitoring and personalized feedback based on the experiencing sampling method as a tool to boost depression treatment: a protocol of a pragmatic randomized controlled trial (ZELF-i)

BACKGROUND

Depression is a leading cause of disability worldwide. To reduce the societal burden and improve quality of life for individual patients, treatments for depression need to be optimized. There is a particular need for person-tailored interventions that reinforce self-management of patients. Systematic self-monitoring and personalized feedback through the Experience Sampling Method (ESM) could provide such a person-tailored, empowering intervention that enhances treatment outcomes. The primary aim of this study is to investigate the efficacy of self-monitoring and personalized feedback as an add-on tool in the treatment of depressive complaints in a natural setting.

METHODS

The ZELF-i study is a pragmatic multi-site randomized controlled trial (RCT). We aim to recruit 150 individuals with depressive symptoms aged between 18 and 65 years, who have an intake for outpatient basic or specialized treatment at a mental health care organization in the North of the Netherlands. After the intake, participants will be randomly allocated to one of three study arms: two experimental groups engaging in 28 days of systematic self-monitoring (5 times per day) and receiving weekly personalized feedback on positive affect and activities ("Do"-module) or on negative affect and thinking patterns ("Think"-module), and a control group receiving no additional intervention. Self-report inventories of depressive symptoms, psychosocial functioning and feelings of empowerment will be administered before and after the intervention period, and at follow-up measurements at 1, 2, 3 and 6 months. The patient-experienced utility of the intervention will be investigated by a combination of quantitative and qualitative research methods.

DISCUSSION

The present study is the first to examine the effects of add-on self-monitoring and personalized feedback on depressive complaints in clinical practice. It is also the first to evaluate two different ESM modules targeted at both of depression's core symptoms. Lastly, it is the first study that uses a combination of qualitative and quantitative methods to evaluate the patient-experienced utility of ESM with personalized feedback as an intervention for depression. Results of the present study may improve treatment for depression, if the intervention is found to be effective.

TRIAL REGISTRATION

Dutch Trial Register, NTR5707 , registered prospectively 1 February 2016.

Associations between genetic risk, functional brain network organization and neuroticism

Neuroticism and genetic variation in the serotonin-transporter (SLC6A4) and catechol-O-methyltransferase (COMT) gene are risk factors for psychopathology. Alterations in the functional integration and segregation of neural circuits have recently been found in individuals scoring higher on neuroticism. The aim of the current study was to investigate how genetic risk factors impact functional network organization and whether genetic risk factors moderate the association between neuroticism and functional network organization. We applied graph theory analysis on resting-state fMRI data in a sample of 120 women selected based on their neuroticism score, and genotyped two polymorphisms: 5-HTTLPR (S-carriers and L-homozygotes) and COMT (rs4680-rs165599; COMT risk group and COMT non-risk group). For the 5-HTTLPR polymorphism, we found that subnetworks related to cognitive control show less connections with other subnetworks in S-carriers compared to L-homozygotes. The COMT polymorphism moderated the association between neuroticism and functional network organization. We found that neuroticism was associated with lower efficiency coefficients in visual and somatosensory-motor subnetworks in the COMT risk group compared to the COMT non-risk group. The findings of altered topology of specific subnetworks point to different cognitive-emotional processes that may be affected in relation to the genetic risk factors, concerning emotion regulation in S-carriers (5-HTTLPR) and emotional salience processing in COMT risk carriers.

Associations Between Daily Affective Instability and Connectomics in Functional Subnetworks in Remitted Patients with Recurrent Major Depressive Disorder

Remitted patients with major depressive disorder (rMDD) often report more fluctuations in mood as residual symptomatology. It is unclear how this affective instability is associated with information processing related to the default mode (DMS), salience/reward (SRS), and frontoparietal (FPS) subnetworks in rMDD patients at high risk of recurrence (rrMDD). Sixty-two unipolar, drug-free rrMDD patients (⩾2 MDD episodes) and 41 healthy controls (HCs) were recruited. We used experience sampling methodology to monitor mood/cognitions (10 times a day for 6 days) and calculated affective instability using the mean adjusted absolute successive difference. Subsequently, we collected resting-state functional magnetic resonance imaging data and performed graph theory to obtain network metrics of integration within (local efficiency) the DMS, SRS, and FPS, and between (participation coefficient) these subnetworks and others. In rrMDD patients compared with HCs, we found that affective instability was increased in most negative mood/cognition variables and that the DMS had less connections with other subnetworks. Furthermore, we found that rrMDD patients, who showed more instability in feeling down and irritated, had less connections between the SRS and other subnetworks and higher local efficiency coefficients in the FPS, respectively. In conclusion, rrMDD patients, compared with HCs, are less stable in their negative mood and these dynamics are related to differences in information processing within- and between-specific functional subnetworks. These results are a first step to gain a better understanding of how mood fluctuations in real life are represented in the brain and provide insights into the vulnerability profile of MDD.

Personalized Feedback on Symptom Dynamics of Psychopathology: A Proof-of-Principle Study

Background and Objectives

In the proposed symptom network approach to psychopathology, psychiatric disorders are assumed to result from the (causal) interplay between symptoms. By implementing this approach we explored whether individual feedback on symptom dynamics complements current categorical classification and treatment. The aim of this proof-of-principle case-study was to explore the feasibility, acceptability and usability of this transdiagnostic approach.

Methods

A female patient, aged 67, suffering from treatment resistant anxious and depressive symptoms was treated in our tertiary outpatient clinic for old age psychiatry. She participated in ecological momentary assessments (EMA), which involved intensive repeated measurements of mood and context-related items during two weeks. Visualizations of the interplay between the items were provided by network graphs and were discussed with the patient.

Results

Network graphs were discussed with the patient. For example, it was hypothesized and discussed with the patient that feeling relaxed increased physical activity, causing physical discomfort in the following hours. Physical discomfort caused stress as its symptoms resembled her feared somatic anxiety symptoms. This increased the patient's insight that stress, expressed as somatic symptoms, played a central role in her panic disorder. This started a dialogue on how to cope with stress caused by somatic (anxiety) symptoms and provided a rationale for the patient to start an interoceptive exposure intervention she had repeatedly refused before.

Limitations

The observed symptom dynamics may not be generalizable to any other random two weeks.

Conclusions

Personalized diagnosis of psychopathology incorporating complex symptom dynamics is feasible and a promising addition to current categorical diagnostic systems and could guide intervention selection. This merits further exploration.

Citation bias and selective focus on positive findings in the literature on the serotonin transporter gene (5-HTTLPR), life stress and depression

BACKGROUND

Caspi et al.'s 2003 report that 5-HTTLPR genotype moderates the influence of life stress on depression has been highly influential but remains contentious. We examined whether the evidence base for the 5-HTTLPR-stress interaction has been distorted by citation bias and a selective focus on positive findings.

METHOD

A total of 73 primary studies were coded for study outcomes and focus on positive findings in the abstract. Citation rates were compared between studies with positive and negative results, both within this network of primary studies and in Web of Science. In addition, the impact of focus on citation rates was examined.

RESULTS

In all, 24 (33%) studies were coded as positive, but these received 48% of within-network and 68% of Web of Science citations. The 38 (52%) negative studies received 42 and 23% of citations, respectively, while the 11 (15%) unclear studies received 10 and 9%. Of the negative studies, the 16 studies without a positive focus (42%) received 47% of within-network citations and 32% of Web of Science citations, while the 13 (34%) studies with a positive focus received 39 and 51%, respectively, and the nine (24%) studies with a partially positive focus received 14 and 17%.

CONCLUSIONS

Negative studies received fewer citations than positive studies. Furthermore, over half of the negative studies had a (partially) positive focus, and Web of Science citation rates were higher for these studies. Thus, discussion of the 5-HTTLPR-stress interaction is more positive than warranted. This study exemplifies how evidence-base-distorting mechanisms undermine the authenticity of research findings.

Depressive Symptoms and the Experience of Pleasure in Daily Life: An Exploration of Associations in Early and Late Adolescence

Although loss of pleasure (i.e., anhedonia) is one of the two core symptoms of depression, very little research has examined the relation between depressive symptoms and the experience of pleasure in daily life. This exploratory study in two population-based adolescent samples aimed to examine how depressive symptoms and anhedonia specifically were related to (1) the proportion and intensity of positive events, (2) mean and variability of positive affect (PA), (3) reactivity to positive events, and (4) reactivity to PA (i.e., whether PA elicits positive events). We used Experience Sampling to measure positive events and PA several times a day during 6 to 14 days in early (N = 284) and late (N = 74) adolescents. Results showed that depressive symptoms were related to a lower proportion and intensity of positive events, lower mean PA, and higher variability in PA regardless of sex and stage of adolescence. No clear evidence was found for differential reactivity to positive events or to PA. Anhedonia was not associated with most daily life experiences of pleasure. Our findings, though preliminary, suggest that although adolescents with many depressive symptoms experience less positive events and lower PA, they are able to enjoy pleasurable events to the same extent as individuals with fewer depressive symptoms.

A Population Based Study of the Genetic Association between Catecholamine Gene Variants and Spontaneous Low-Frequency Fluctuations in Reaction Time

The catecholamines dopamine and noradrenaline have been implicated in spontaneous low-frequency fluctuations in reaction time, which are associated with attention deficit hyperactivity disorder (ADHD) and subclinical attentional problems. The molecular genetic substrates of these behavioral phenotypes, which reflect frequency ranges of intrinsic neuronal oscillations (Slow-4: 0.027-0.073 Hz; Slow-5: 0.010-0.027 Hz), have not yet been investigated. In this study, we performed regression analyses with an additive model to examine associations between low-frequency fluctuations in reaction time during a sustained attention task and genetic markers across 23 autosomal catecholamine genes in a large young adult population cohort (n = 964), which yielded greater than 80% power to detect a small effect size (f² = 0.02) and 100% power to detect a small/medium effect size (f² = 0.15). At significance levels corrected for multiple comparisons, none of the gene variants were associated with the magnitude of low-frequency fluctuations. Given the study’s strong statistical power and dense coverage of the catecholamine genes, this either indicates that associations between low-frequency fluctuation measures and catecholamine gene variants are absent or that they are of very small effect size. Nominally significant associations were observed between variations in the alpha-2A adrenergic receptor gene (ADRA2A) and the Slow-5 band. This is in line with previous reports of an association between ADRA2A gene variants and general reaction time variability during response selection tasks, but the specific association of these gene variants and low-frequency fluctuations requires further confirmation. Pharmacological challenge studies could in the future provide convergent evidence for the noradrenergic modulation of both general and time sensitive measures of intra-individual variability in reaction time.

Filling the gap: relationship between the serotonin-transporter-linked polymorphic region and amygdala activation

The alleged association between the serotonin-transporter-linked polymorphic region (5-HTTLPR) and amygdala activation forms a cornerstone of the common view that carrying the short allele of this polymorphism is a potential risk factor for affective disorders. The authors of a recent meta-analysis showed that this association is statistically significant (Hedges's g = 0.35) but warned that estimates might be distorted because of publication bias. Here, we report a replication study of this relationship in 120 participants. We failed to find an association of 5-HTTLPR variation with amygdala activation during a widely used emotional-face-matching paradigm. Moreover, when we conducted a meta-analysis that included unpublished studies and data from the current study, the pooled meta-analytic effect size was no longer significant (g = 0.20, p = .06). These findings cast doubt on previously reported substantial effects, suggesting that the 5-HTTLPR-amygdala association is either much smaller than previously thought, conditional on other factors, or nonexistent.

Mental health problems are associated with low-frequency fluctuations in reaction time in a large general population sample. The TRAILS study

BACKGROUND

Increased intra-subject reaction time variability (RT-ISV) as coarsely measured by the standard deviation (RT-SD) has been associated with many forms of psychopathology. Low-frequency RT fluctuations, which have been associated with intrinsic brain rhythms occurring approximately every 15-40s, have been shown to add unique information for ADHD. In this study, we investigated whether these fluctuations also relate to attentional problems in the general population, and contribute to the two major domains of psychopathology: externalizing and internalizing problems.

METHODS

RT was monitored throughout a self-paced sustained attention task (duration: 9.1 ± 1.2 min) in a Dutch population cohort of young adults (n=1455, mean age: 19.0 ± 0.6 years, 55.1% girls). To characterize temporal fluctuations in RT, we performed direct Fourier Transform on externally validated frequency bands based on frequency ranges of neuronal oscillations: Slow-5 (0.010-0.027 Hz), Slow-4 (0.027-0.073 Hz), and three additional higher frequency bands. Relative magnitude of Slow-4 fluctuations was the primary predictor in regression models for attentional, internalizing and externalizing problems (measured by the Adult Self-Report questionnaire). Additionally, stepwise regression models were created to investigate (a) whether Slow-4 significantly improved the prediction of problem behaviors beyond the RT-SD and (b) whether the other frequency bands provided important additional information.

RESULTS

The magnitude of Slow-4 fluctuations significantly predicted attentional and externalizing problems and even improved model fit after modeling RT-SD first (R(2) change=0.6%, P<.01). Subsequently, adding Slow-5 explained additional variance for externalizing problems (R(2) change=0.4%, P<.05). For internalizing problems, only RT-SD made a significant contribution to the regression model (R(2)=0.5%, P<.01), that is, none of the frequency bands provided additional information.

CONCLUSIONS

Low-frequency RT fluctuations have added predictive value for attentional and externalizing, but not internalizing problems beyond global differences in variability. This study extends previous findings in clinical samples of children with ADHD to adolescents from the general population and demonstrates that deconstructing RT-ISV into temporal components can provide more distinctive information for different domains of psychopathology.

Diagnosing autism spectrum disorders in adults: the use of Autism Diagnostic Observation Schedule (ADOS) module 4

Autism Diagnostic Observation Schedule (ADOS) module 4 was investigated in an independent sample of high-functioning adult males with an autism spectrum disorder (ASD) compared to three specific diagnostic groups: schizophrenia, psychopathy, and typical development. ADOS module 4 proves to be a reliable instrument with good predictive value. It can adequately discriminate ASD from psychopathy and typical development, but is less specific with respect to schizophrenia due to behavioral overlap between autistic and negative symptoms. However, these groups differ on some core items and explorative analyses indicate that a revision of the algorithm in line with Gotham et al. (J Autism Dev Disord 37: 613-627, 2007) could be beneficial for discriminating ASD from schizophrenia.

Age-related increase in inferior frontal gyrus activity and social functioning in autism spectrum disorder

BACKGROUND

Hypoactivation of the inferior frontal gyrus during the perception of facial expressions has been interpreted as evidence for a deficit of the mirror neuron system in children with autism. We examined whether this dysfunction persists in adulthood, and how brain activity in the mirror neuron system relates to social functioning outside the laboratory.

METHODS

Twenty-one adult males with autism spectrum disorders and 21 typically developing subjects matched for age, sex, and IQ were scanned in three conditions: observing short movies showing facial expressions, performing a facial movement, and experiencing a disgusting taste. Symptom severity and level of social adjustment were measured with the Autism Diagnostic Observation Schedule and the Social Functioning Scale.

RESULTS

Inferior frontal gyrus activity during the observation of facial expressions increased with age in subjects with autism, but not in control subjects. The age-related increase in activity was associated with changes in gaze behavior and improvements in social functioning. These age-related neurocognitive improvements were not found in a group of individuals with schizophrenia, who had comparable levels of social functioning.

CONCLUSIONS

The results of this cross-sectional study suggest that mirror neuron system activity augments with age in autism and that this is accompanied by changes in gaze behavior and improved social functioning. It is the first demonstration of an age-related neurocognitive improvement in autism. Increased motor simulation may contribute to the amelioration in social functioning documented in adolescence and adulthood. This finding should encourage the development of new therapeutic interventions directed at emotion simulation.