Wolfgang Huf

Bright-Light Therapy in the Treatment of Mood Disorders

Bright-light therapy (BLT) is established as the treatment of choice for seasonal affective disorder/winter type (SAD). In the last two decades, the use of BLT has expanded beyond SAD: there is evidence for efficacy in chronic depression, antepartum depression, premenstrual depression, bipolar depression and disturbances of the sleep-wake cycle. Data on the usefulness of BLT in non-seasonal depression are promising; however, further systematic studies are still warranted. In this review, the authors present a comprehensive overview of the literature on BLT in mood disorders. The first part elucidates the neurobiology of circadian and seasonal adaptive mechanisms focusing on the suprachiasmatic nucleus (SCN), the indolamines melatonin and serotonin, and the chronobiology of mood disorders. The SCN is the primary oscillator in humans. Indolamines are known to transduce light signals into cells and organisms since early in evolution, and their role in signalling change of season is still preserved in humans: melatonin is synthesized primarily in the pineal gland and is the central hormone for internal clock circuitries. The melatonin precursor serotonin is known to modulate many behaviours that vary with season. The second part discusses the pathophysiology and clinical specifiers of SAD, which can be seen as a model disorder for chronobiological disturbances and the mechanism of action of BLT. In the third part, the mode of action, application, efficacy, tolerability and safety of BLT in SAD and other mood disorders are explored.

Beyond Noise: Using Temporal ICA to Extract Meaningful Information from High-Frequency fMRI Signal Fluctuations during Rest

Analysis of resting-state networks using fMRI usually ignores high-frequency fluctuations in the BOLD signal – be it because of low TR prohibiting the analysis of fluctuations with frequencies higher than 0.25 Hz (for a typical TR of 2 s), or because of the application of a bandpass filter (commonly restricting the signal to frequencies lower than 0.1 Hz). While the standard model of convolving neuronal activity with a hemodynamic response function suggests that the signal of interest in fMRI is characterized by slow fluctuation, it is in fact unclear whether the high-frequency dynamics of the signal consists of noise only. In this study, 10 subjects were scanned at 3 T during 6 min of rest using a multiband EPI sequence with a TR of 354 ms to critically sample fluctuations of up to 1.4 Hz. Preprocessed data were high-pass filtered to include only frequencies above 0.25 Hz, and voxelwise whole-brain temporal ICA (tICA) was used to identify consistent high-frequency signals. The resulting components include physiological background signal sources, most notably pulsation and heart-beat components, that can be specifically identified and localized with the method presented here. Perhaps more surprisingly, common resting-state networks like the default-mode network also emerge as separate tICA components. This means that high-frequency oscillations sampled with a rather T1-weighted contrast still contain specific information on these resting-state networks to consistently identify them, not consistent with the commonly held view that these networks operate on low-frequency fluctuations alone. Consequently, the use of bandpass filters in resting-state data analysis should be reconsidered, since this step eliminates potentially relevant information. Instead, more specific methods for the elimination of physiological background signals, for example by regression of physiological noise components, might prove to be viable alternatives.

The spectral diversity of resting-state fluctuations in the human brain.

In order to assess whole-brain resting-state fluctuations at a wide range of frequencies, resting-state fMRI data of 20 healthy subjects were acquired using a multiband EPI sequence with a low TR (354 ms) and compared to 20 resting-state datasets from standard, high-TR (1800 ms) EPI scans. The spatial distribution of fluctuations in various frequency ranges are analyzed along with the spectra of the time-series in voxels from different regions of interest. Functional connectivity specific to different frequency ranges (<0.1 Hz; 0.1–0.25 Hz; 0.25–0.75 Hz; 0.75–1.4 Hz) was computed for both the low-TR and (for the two lower-frequency ranges) the high-TR datasets using bandpass filters. In the low-TR data, cortical regions exhibited highest contribution of low-frequency fluctuations and the most marked low-frequency peak in the spectrum, while the time courses in subcortical grey matter regions as well as the insula were strongly contaminated by high-frequency signals. White matter and CSF regions had highest contribution of high-frequency fluctuations and a mostly flat power spectrum. In the high-TR data, the basic patterns of the low-TR data can be recognized, but the high-frequency proportions of the signal fluctuations are folded into the low frequency range, thus obfuscating the low-frequency dynamics. Regions with higher proportion of high-frequency oscillations in the low-TR data showed flatter power spectra in the high-TR data due to aliasing of the high-frequency signal components, leading to loss of specificity in the signal from these regions in high-TR data. Functional connectivity analyses showed that there are correlations between resting-state signal fluctuations of distant brain regions even at high frequencies, which can be measured using low-TR fMRI. On the other hand, in the high-TR data, loss of specificity of measured fluctuations leads to lower sensitivity in detecting functional connectivity. This underlines the advantages of low-TR EPI sequences for resting-state and potentially also task-related fMRI experiments.

Meta-analysis: Fact or fiction? How to interpret meta-analyses

Abstract Objectives. Widespread use of increasingly complex statistical methods makes it ever more challenging to adequately assess the results reported and conclusions drawn in meta-analytic research. This paper aims to identify potential fallacies by in-depth examination of recent publications on mood disorders. Methods. Three meta-analyses were selected based on availability of data and representativeness of methods employed. By means of detailed re-analysis, several widespread methodological problems were identified, and the example data were used to illustrate and discuss them. Results. General points addressed include clear formulation of the research question, choice of effect size measures, and general choice of model. Data quality problems like missing data and publication bias are discussed along with methods to deal with them. Furthermore, aspects of meta-analytic modelling like the use of fixed or random effects, data aggregation, as well as the use of subgroups are explained, and issues of excessive complexity and data dredging pointed out. Finally, the benefit of diagnostic tools like confidence bands and the importance of transparency regarding data and methodology for the interpretation of meta-analytic results are highlighted. Conclusions. Practically relevant quality criteria for readers to bear in mind when dealing with meta-analytic publications are summarized in a ten point checklist.

fMRI measurements of amygdala activation are confounded by stimulus correlated signal fluctuation in nearby veins draining distant brain regions

Imaging the amygdala with functional MRI is confounded by multiple averse factors, notably signal dropouts due to magnetic inhomogeneity and low signal-to-noise ratio, making it difficult to obtain consistent activation patterns in this region. However, even when consistent signal changes are identified, they are likely to be due to nearby vessels, most notably the basal vein of rosenthal (BVR). Using an accelerated fMRI sequence with a high temporal resolution (TR = 333 ms) combined with susceptibility-weighted imaging, we show how signal changes in the amygdala region can be related to a venous origin. This finding is confirmed here in both a conventional fMRI dataset (TR = 2000 ms) as well as in information of meta-analyses, implying that “amygdala activations” reported in typical fMRI studies are likely confounded by signals originating in the BVR rather than in the amygdala itself, thus raising concerns about many conclusions on the functioning of the amygdala that rely on fMRI evidence alone.

Fully exploratory network independent component analysis of the 1000 functional connectomes database

The 1000 Functional Connectomes Project is a collection of resting-state fMRI datasets from more than 1000 subjects acquired in more than 30 independent studies from around the globe. This large, heterogeneous sample of resting-state data offers the unique opportunity to study the consistencies of resting-state networks at both subject and study level. In extension to the seminal paper by Biswal et al. (2010), where a repeated temporal concatenation group independent component analysis (ICA) approach on reduced subsets (using 20 as a pre-specified number of components) was used due to computational resource limitations, we herein apply Fully Exploratory Network ICA (FENICA) to 1000 single-subject independent component analyses. This, along with the possibility of using datasets of different lengths without truncation, enabled us to benefit from the full dataset available, thereby obtaining 16 networks consistent over the whole group of 1000 subjects. Furthermore, we demonstrated that the most consistent among these networks at both subject and study level matched networks most often reported in the literature, and found additional components emerging in prefrontal and parietal areas. Finally, we identified the influence of scan duration on the number of components as a source of heterogeneity between studies.

Morphologic and functional evaluations during development, resolution, and relapse of uveitis-associated cystoid macular edema.

Objectives: To describe progression and resolution of uveitis-associated cystoid macular edema (uvCME) using spectral-domain optical coherence tomography and find predictive factors for successful intravitreal triamcinolone acetonide (IVTA) therapy. Methods: Twenty-nine eyes with treatment-naive uvCME were examined before and at 5 scheduled visits within 3 months after intravitreal triamcinolone acetonide administration. Distribution, resolution, relapse, and development of uvCME were evaluated using spectral-domain optical coherence tomography to describe morphology, progression, and relapse according to a standardized reading protocol. Applying repeated measures analysis of variance, morphologic findings were evaluated as predictive factors of the treatment outcome. Results: At baseline, 89.3% presented with focal CME; 65.6% had outer nuclear/Henley’s layer and inner nuclear layer cysts. Following intravitreal triamcinolone acetonide administration, cysts of outer nuclear/Henley’s layer diminished before those of inner nuclear layer (P = 0.0004). Small-pointed subretinal detachment (SRD) resolution synchronized with inner nuclear layer cyst extinction, whereas dome-shaped SRD resolution lagged behind (P = 0.014). Relapses of CME appeared in 71.4% of eyes with parafoveal inner nuclear layer cysts. Cysts of outer nuclear/Henley’s layer were present in an additional 28.6%. None of the eyes developed SRD during CME relapse. The main effect variables “SRD” and “absence of epiretinal membrane” were associated with greater best-corrected visual acuity improvement (P = 0.05 and P = 0.047), whereas the side effect variables “CME duration”, “age,” and “uveitis location” had no additional effect on best-corrected visual acuity. Baseline SRD predicted a relapse-free clinical course within the observational period (P = 0.025). Conclusion: Different morphologic patterns in uvCME may represent different stages in uvCME progression, and initial morphologic appearance can be linked to the clinical prognosis after the treatment.

Macular atrophy in patients with long-term anti-VEGF treatment for neovascular age-related macular degeneration

To identify the prevalence and progression of macular atrophy (MA) in neovascular age‐related macular degeneration (AMD) patients under long‐term anti‐vascular endothelial growth factor (VEGF) therapy and to determine risk factors.

Follow-up of pediatric celiac disease: value of antibodies in predicting mucosal healing, a prospective cohort study

BackgroundIn diagnosing celiac disease (CD), serological tests are highly valuable. However, their role in following up children with CD after prescription of a gluten-free diet is unclear. This study aimed to compare the performance of antibody tests in predicting small-intestinal mucosal status in diagnosis vs. follow-up of pediatric CD.MethodsWe conducted a prospective cohort study at a tertiary-care center. 148 children underwent esophohagogastroduodenoscopy with biopsies either for symptoms ± positive CD antibodies (group A; n = 95) or following up CD diagnosed ≥ 1 year before study enrollment (group B; n = 53). Using biopsy (Marsh ≥ 2) as the criterion standard, areas under ROC curves (AUCs) and likelihood-ratios were calculated to estimate the performance of antibody tests against tissue transglutaminase (TG2), deamidated gliadin peptide (DGP) and endomysium (EMA).ResultsAUCs were higher when tests were used for CD diagnosis vs. follow-up: 1 vs. 0.86 (P = 0.100) for TG2-IgA, 0.85 vs. 0.74 (P = 0.421) for TG2-IgG, 0.97 vs. 0.61 (P = 0.004) for DPG-IgA, and 0.99 vs. 0.88 (P = 0.053) for DPG-IgG, respectively. Empirical power was 85% for the DPG-IgA comparison, and on average 33% (range 13–43) for the non-significant comparisons. Among group B children, 88.7% showed mucosal healing (median 2.2 years after primary diagnosis). Only the negative likelihood-ratio of EMA was low enough (0.097) to effectively rule out persistent mucosal injury. However, out of 12 EMA-positive children with mucosal healing, 9 subsequently turned EMA-negative.ConclusionsAmong the CD antibodies examined, negative EMA most reliably predict mucosal healing. In general, however, antibody tests, especially DPG-IgA, are of limited value in predicting the mucosal status in the early years post-diagnosis but may be sufficient after a longer period of time.

One Year Follow-up of Functional Recovery in Neovascular AMD During Monthly Anti-VEGF Treatment

PURPOSE To identify neurosensory recovery, testing different functional variables during monthly intravitreal standard anti-vascular endothelial growth factor (VEGF) therapy in neovascular age-related macular degeneration (AMD). DESIGN Prospective interventional cohort study. METHODS Sixty-four treatment-naïve neovascular AMD patients with subfoveal lesions were treated and examined monthly for distance visual acuity, reading acuity, maximum reading speed, and contrast sensitivity and with microperimetry evaluating the percentage of absolute and relative scotoma and mean central retinal sensitivity weighted by area. Improvements in reading acuity, distance acuity, reading speed, contrast sensitivity, mean central retinal sensitivity, and scotoma area in dependence of age, lesion type, lesion size, and mean central retinal sensitivity were evaluated by a random-slope and random-intercept model. Recovery pattern of parameters was compared by correlating the individual slopes of each variable. RESULTS Initially, a rapid short-term effect of anti-VEGF treatment was documented throughout all functional variables. Progressive functional gain over 1 year was observed for distance visual acuity (P = .011), contrast sensitivity (P ≤ .0001), and mean central retinal sensitivity (P ≤ .0001), but not for reading acuity (P = .31) and maximum reading speed (P = .94). Decrease of absolute scotoma area missed statistical significance over time (P = .053) and also fixation stability did not improve (P = .08). However, lesion size influenced the course of absolute scotoma area (P = .0015), while lesion type had no effect on any visual function variable evaluated. The individual slopes of reading acuity and distance visual acuity showed a moderate correlation; however, all other variables showed only a weak or no significant correlation among each other. CONCLUSION Visual recovery in anti-VEGF therapy is reflected in a characteristic pattern of functional changes over time, whereas distance visual acuity does not seem to comprehensively reflect overall visual function gain.