Large-scale evidence for an association between low-grade peripheral inflammation and brain structural alterations in major depression in the BiDirect study

Background: Preliminary research suggests that major depressive disorder (MDD) is associated with structural alterations in the brain; as well as with low-grade peripheral inflammation. However, even though a link between inflammatory processes and altered brain structural integrity has been purported by experimental research, well-powered studies to confirm this hypothesis in patients with MDD have been lacking. We aimed to investigate the potential association between structural brain alterations and low-grade inflammation as interrelated biological correlates of MDD. Methods: In this cross-sectional study, 514 patients with MDD and 359 healthy controls underwent structural MRI. We used voxel-based morphometry to study local differences in grey matter volume. We also assessed serum levels of high-sensitivity C-reactive protein (hsCRP) in each participant. Results: Compared with healthy controls (age [mean ± standard deviation] 52.57 ± 7.94 yr; 50% male), patients with MDD (49.14 ± 7.28 yr, 39% male) exhibited significantly increased hsCRP levels (Z = −5.562, p < 0.001) and significantly decreased grey matter volume in the prefrontal cortex and the insula. Prefrontal grey matter volume reductions were significantly associated with higher hsCRP levels in patients with MDD (x = 50, y = 50, z = 8; t1,501 = 5.15; k = 92; pFWE < 0.001). In the MDD sample, the significant negative association between hsCRP and grey matter appeared independent of age, sex, body mass index, current smoking status, antidepressant load, hospitalization and medical comorbidities. Limitations: This study had a cross-sectional design. Conclusion: The present study highlights the role of reduced grey matter volume and low-grade peripheral inflammation as interrelated biological correlates of MDD. The reported inverse association between peripheral low-grade inflammation and brain structural integrity in patients with MDD translates current knowledge from experimental studies to the bedside.

Computed tomography-based quantification of lesion water uptake identifies patients within 4.5 hours of stroke onset: A multicenter observational study.

OBJECTIVE: Many patients with stroke cannot receive intravenous thrombolysis because the time of symptom onset is unknown. We tested whether computed tomography (CT)-based quantification of water uptake in the ischemic tissue can identify patients with stroke onset within 4.5 hours, the time window of thrombolysis. METHODS: Perfusion CT was used to identify ischemic brain tissue, and its density was measured in native CT and related to the density of the corresponding area of the contralateral hemisphere to quantify lesion water uptake. The optimal cutoff value of water uptake distinguishing stroke onset within and beyond 4.5 hours was calculated in patients with proximal middle cerebral artery occlusion (derivation cohort) with known time of symptom onset. The so-derived cutoff value was validated in a prospective cohort from other stroke centers. RESULTS: Of 178 patients of the derivation cohort, 147 (82.6%) had CT within 4.5 hours. Percentage water uptake was significantly lower in patients with stroke onset within compared to beyond 4.5 hours. The area under the receiver operating characteristic curve for distinguishing these patient groups according to percentage water uptake was 0.999 (95% confidence interval = 0.996-1.000, p < 0.001) with an optimal cutoff value of 11.5%. Applying this cutoff to the validation cohort of 240 patients, sensitivity was 98.6%, specificity 90.5%, positive predictive value 99.1%, and negative predictive value 86.4%. INTERPRETATION: Quantification of brain water uptake identifies stroke patients with symptom onset within 4.5 hours with high accuracy and may guide the decision to use thrombolysis in patients with unknown time of stroke onset. Ann Neurol 2016;80:924-934.

Diagnostic classification of unipolar depression based on resting-state functional connectivity MRI: effects of generalization to a diverse sample.

In small, selected samples, an approach combining resting-state functional connectivity MRI and multivariate pattern analysis has been able to successfully classify patients diagnosed with unipolar depression. Purposes of this investigation were to assess the generalizability of this approach to a large clinically more realistic sample and secondarily to assess the replicability of previously reported methodological feasibility in a more homogeneous subgroup with pronounced depressive symptoms. Two independent subsets were drawn from the depression and control cohorts of the BiDirect study, each with 180 patients with and 180 controls without depression. Functional connectivity either among regions covering the gray matter or selected regions with known alterations in depression was assessed by resting-state fMRI. Support vector machines with and without automated feature selection were used to train classifiers differentiating between individual patients and controls in the entire first subset as well as in the subgroup. Model parameters were explored systematically. The second independent subset was used for validation of successful models. Classification accuracies in the large, heterogeneous sample ranged from 45.0 to 56.1% (chance level 50.0%). In the subgroup with higher depression severity, three out of 90 models performed significantly above chance (60.8-61.7% at independent validation). In conclusion, common classification methods previously successful in small homogenous depression samples do not immediately translate to a more realistic population. Future research to develop diagnostic classification approaches in depression should focus on more specific clinical questions and consider heterogeneity, including symptom severity as an important factor.

MR imaging of the brain in large cohort studies: feasibility report of the population- and patient-based BiDirect study.

OBJECTIVES: To describe the implementation and protocol of cerebral magnetic resonance imaging (MRI) in the longitudinal BiDirect study and to report rates of study participation as well as management of incidental findings. METHODS: Data came from the BiDirect study that investigates the relationship between depression and arteriosclerosis and comprises 2258 participants in three cohorts: 999 patients with depression, 347 patients with manifest cardiovascular disease (CVD) and 912 population-based controls. The study program includes MRI of the brain. Reasons for non-participation were systematically collected. Incidental findings were categorized and disclosed according to clinical relevance. RESULTS: At baseline 2176 participants were offered MRI, of whom 1453 (67 %) completed it. Reasons for non-participation differed according to cohort, age and gender with controls showing the highest participation rate of 79 %. Patient cohorts had higher refusal rates and CVD patients a high prevalence of contraindications. In the first follow-up examination 69 % of participating subjects completed MRI. Incidental findings were disclosed to 246 participants (17 %). The majority of incidental findings were extensive white matter hyperintensities requiring further diagnostic work-up. CONCLUSIONS: Knowledge about subjects and sensible definition of incidental findings are crucial for large-scale imaging projects. Our data offer practical and concrete information for the design of future studies. KEY POINTS: • Willingness to participate in MRI is generally high, also in follow-up examinations. • Rates of refusal and prevalence of contraindications differ according to subject characteristics. • Extensive white matter hyperintensities considerably increase the disclosure rates of incidental findings. • MRI workflow requires continuous case-by-case handling by an interdisciplinary team.

Outcome After Thrombectomy and Intravenous Thrombolysis in Patients With Acute Ischemic Stroke: A Prospective Observational Study.

BACKGROUND AND PURPOSE: In patients with ischemic stroke, randomized trials showed a better functional outcome after endovascular therapy with new-generation thrombectomy devices compared with medical treatment, including intravenous thrombolysis. However, effects on mortality and the generalizability of results to routine clinical practice are uncertain. METHODS: In a prospective observational register-based study patients with ischemic stroke treated either with thrombectomy, intravenous thrombolysis, or their combination were included. Primary outcome was the modified Rankin scale score (0 [no symptoms] to 6 [death]) at 3 months. Ordinal logistic regression was used to estimate the common odds ratio as treatment effects (shift analysis). Propensity score matching was applied to compare patients treated either with intravenous thrombolysis alone or with intravenous thrombolysis plus thrombectomy. RESULTS: Among 2650 recruited patients, 1543 received intravenous thrombolysis, 504 underwent thrombectomy, and 603 received intravenous thrombolysis in combination with thrombectomy. Later time-to-treatment was associated with worse outcomes among patients treated with thrombectomy plus thrombolysis. In 241 pairs of propensity score-matched patients with a proximal intracranial occlusion, thrombectomy plus thrombolysis was associated with improved functional outcome (common odds ratio, 1.84; 95% confidence interval, 1.32-2.57), and reduced mortality (15% versus 33%; P<0.0001) compared with intravenous thrombolysis alone. Results were similar in various sensitivity analyses accounting for missing outcome data and different analytic methods. CONCLUSIONS: Results from this large prospective registry show that also in routine clinical care thrombectomy plus thrombolysis compared with thrombolysis alone improved functional outcome and reduced mortality in patients with ischemic stroke. Earlier treatment was associated with better outcomes.

Genetic factors influencing a neurobiological substrate for psychiatric disorders.

A retrospective meta-analysis of magnetic resonance imaging voxel-based morphometry studies proposed that reduced gray matter volumes in the dorsal anterior cingulate and the left and right anterior insular cortex-areas that constitute hub nodes of the salience network-represent a common substrate for major psychiatric disorders. Here, we investigated the hypothesis that the common substrate serves as an intermediate phenotype to detect genetic risk variants relevant for psychiatric disease. To this end, after a data reduction step, we conducted genome-wide association studies of a combined common substrate measure in four population-based cohorts (n = 2271), followed by meta-analysis and replication in a fifth cohort (n = 865). After correction for covariates, the heritability of the common substrate was estimated at 0.50 (standard error 0.18). The top single-nucleotide polymorphism (SNP) rs17076061 was associated with the common substrate at genome-wide significance and replicated, explaining 1.2% of the common substrate variance. This SNP mapped to a locus on chromosome 5q35.2 harboring genes involved in neuronal development and regeneration. In follow-up analyses, rs17076061 was not robustly associated with psychiatric disease, and no overlap was found between the broader genetic architecture of the common substrate and genetic risk for major depressive disorder, bipolar disorder, or schizophrenia. In conclusion, our study identified that common genetic variation indeed influences the common substrate, but that these variants do not directly translate to increased disease risk. Future studies should investigate gene-by-environment interactions and employ functional imaging to understand how salience network structure translates to psychiatric disorder risk.

White matter hyperintensities are not associated with cognitive decline in early Parkinson's disease - The DeNoPa cohort.

BACKGROUND: Small vessel disease and white matter hyperintensities (WMH) as its surrogate marker are known to predict cognitive decline in the elderly. However, the influence of vascular lesions on cognitive impairment in Parkinson's disease (PD) has been discussed controversial so far. The Aim of this study was to evaluate the predictive role of volume and location of white matter hyperintensities (WMH) on cognitive decline in de novo PD patients. METHODS: 108 diagnosed drug-naïve PD patients (64 ±â€¯9 years, 38% women) from the DeNoPa Cohort underwent extensive neuropsychological testing with re-testing in 24-month later. Movement Disorder Society criteria for the classification of mild cognitive impairment (MCI) and dementia in PD were applied. Participants that declined from normal cognition or MCI at baseline to MCI or dementia at 24-month follow-up (FU) or from MCI to dementia at 24-month FU were defined as "converters". Subjects with stable cognitive level or improved cognitive status were classified as "non-converters". Magnetic resonance imaging (MRI) was performed, and the extent of WMH was assessed as global volume and as WMH load within cholinergic pathways using the Cholinergic Pathways Hyperintensities Scale. We compared Parkinson's disease subjects with age-matched, neurologically healthy controls. RESULTS: At total of 29 (27%) patients met the criteria for MCI at baseline, whereas 79 (73%) patients had no cognitive impairment. During the 24-month FU 33 patients showed cognitive decline ("converter") compared to 75 "non-converters". Multivariable logistic regression revealed no significant differences between "cognitively impaired" and "cognitively non-impaired" patients and participants of the control group at baseline or between "converter" and "non-converter" regarding the extent of WMH globally or within cholinergic pathways. CONCLUSIONS: We could not identify global or localized WMH load as predictive markers of cognitive decline in de novo PD patients indicating that cerebral small vessel disease is not a critical modifier of cognitive function in early PD.

Gray matter correlates of pressure pain thresholds and self-rated pain sensitivity: a voxel-based morphometry study.

Individual differences in sensitivity to pain are large and have clinical and scientific importance. Although heavily influenced by situational factors, they also relate to genetic factors and psychological traits, and are reflected by differences in functional activation in pain-related brain regions. Here, we used voxel-based morphometry to investigate if individual pain sensitivity is related to local gray matter volumes. Pain sensitivity was determined using (1) index finger pressure pain thresholds (PPTs) and (2) pain intensity ratings of imagined painful situations as assessed by the Pain Sensitivity Questionnaire (PSQ) in 501 population-based subjects participating in the BiDirect Study. Pain Sensitivity Questionnaire scores were positively associated with gray matter in 2 symmetrical clusters, with a focus on the parahippocampal gyrus, extending to the hippocampus, fusiform gyrus, BA19, putamen, and insula (P < 0.05 corrected), but the effect was small (R = 0.045-0.039). No negative associations with the PSQ and no associations with the PPT reached significance. Parahippocampal activation during pain and altered parahippocampal gray matter in chronic pain have been reported, which would be consistent with positive associations with PSQ scores. Alternatively, associations of PSQ scores with the parahippocampal and fusiform gray matter could relate to the visual imagination of painful situations required by the PSQ, not to pain sensitivity itself. Regarding PPTs, the present data obtained in a large sample strongly suggest an absence of associations of this parameter with gray matter volume. In conclusion, the present results argue against a strong association between pain sensitivity and local gray matter volumes.

Diagnostic Value of Diffusion Tensor Imaging and Positron Emission Tomography in Early Stages of Frontotemporal Dementia.

BACKGROUND: Due to suboptimal sensitivity and specificity of structural and molecular neuroimaging tools, the diagnosis of behavioral variant frontotemporal dementia (bvFTD) remains challenging. OBJECTIVE: Investigation of the sensitivity of diffusion tensor imaging (DTI) and fluorodeoxyglucose positron emission tomography (FDG-PET) to detect cerebral alterations in early stages of bvFTD despite inconspicuous conventional MRI. METHODS: Thirty patients with early stages of bvFTD underwent a detailed neuropsychological examination, cerebral 3T MRI with DTI analysis, and FDG-PET. After 12 months of follow-up, all patients finally fulfilled the diagnosis of bvFTD. Individual FDG-PET data analyses showed that 20 patients exhibited a "typical" pattern for bvFTD with bifrontal and/or temporal hypometabolism (bvFTD/PET+), and that 10 patients showed a "non-typical"/normal pattern (bvFTD/PET-). DTI data were compared with 42 healthy controls in an individual and voxel-based group analysis. To examine the clinical relevance of the findings, associations between pathologically altered voxels of DTI or FDG-PET results and behavioral symptoms were estimated by linear regression analyses. RESULTS: DTI voxel-based group analyses revealed microstructural degeneration in bifrontal and bitemporal areas in bvFTD/PET+ and bvFTD/PET- groups. However, when comparing the sensitivity of individual DTI data analysis with FDG-PET, DTI appeared to be less sensitive. Neuropsychological symptoms were considerably related to neurodegeneration within frontotemporal areas identified by DTI and FDG-PET. CONCLUSION: DTI seems to be an interesting tool for detection of functionally relevant neurodegenerative alterations in early stages of bvFTD, even in bvFTD/PET- patients. However, at a single subject level, it seems to be less sensitive than FDG-PET. Thus, improvement of individual DTI analysis is necessary.

Effects of Different Exercise Strategies and Intensities on Memory Performance and Neurogenesis.

It is well established that physical exercise affects both hippocampal neurogenesis and memory functions. Until now, distinctive effects of controlled and voluntary training (VT) on behavior and neurogenesis as well as interactions between exercise intensity, neurogenesis and memory performance are still elusive. The present study tested the impact of moderate controlled and VT on memory formation and hippocampal neurogenesis and evaluated interactions between exercise performance, learning efficiency and proliferation of progenitor cells in the hippocampus. Our data show that both controlled and VT augmented spatial learning and promoted hippocampal neurogenesis. Regression analysis revealed a significant linear increase of the amount of new hippocampal neurons with increased exercise intensity. Regression analysis of exercise performance on retention memory performance revealed a quadratic, inverted u-shaped relationship between exercise performance and retention of spatial memory. No association was found between the amount of newborn neurons and memory performance. Our results demonstrate that controlled training (CT), if performed with an appropriate combination of speed and duration, improves memory performance and neurogenesis. Voluntary exercise elevates neurogenesis dose dependently to high levels. Best cognitive improvement was achieved with moderate exercise performance.

Sample heterogeneity in unipolar depression as assessed by functional connectivity analyses is dominated by general disease effects.

OBJECTIVES: Combinations of resting-state fMRI and machine-learning techniques are increasingly employed to develop diagnostic models for mental disorders. However, little is known about the neurobiological heterogeneity of depression and diagnostic machine learning has mainly been tested in homogeneous samples. Our main objective was to explore the inherent structure of a diverse unipolar depression sample. The secondary objective was to assess, if such information can improve diagnostic classification. MATERIALS AND METHODS: We analyzed data from 360 patients with unipolar depression and 360 non-depressed population controls, who were subdivided into two independent subsets. Cluster analyses (unsupervised learning) of functional connectivity were used to generate hypotheses about potential patient subgroups from the first subset. The relationship of clusters with demographical and clinical measures was assessed. Subsequently, diagnostic classifiers (supervised learning), which incorporated information about these putative depression subgroups, were trained. RESULTS: Exploratory cluster analyses revealed two weakly separable subgroups of depressed patients. These subgroups differed in the average duration of depression and in the proportion of patients with concurrently severe depression and anxiety symptoms. The diagnostic classification models performed at chance level. LIMITATIONS: It remains unresolved, if subgroups represent distinct biological subtypes, variability of continuous clinical variables or in part an overfitting of sparsely structured data. CONCLUSIONS: Functional connectivity in unipolar depression is associated with general disease effects. Cluster analyses provide hypotheses about potential depression subtypes. Diagnostic models did not benefit from this additional information regarding heterogeneity.

The Association of Lesion Location and Sleep Related Breathing Disorder in Patients with Acute Ischemic Stroke.

BACKGROUND AND AIMS: Sleep related breathing disorders (SRBD) are common in patients with ischemic stroke and are associated with poor outcome. SRBD after stroke were assumed to be a direct consequence of injury of specific central nervous system structures. However, whether specific locations of ischemic infarcts cause SRBD is yet unknown. We therefore investigated the association of ischemic lesion location with SRBD. METHODS: Patients with acute ischemic stroke treated on our stroke unit were included in a prospective observational study. All patients underwent magnetic resonance imaging (MRI) and polygraphy in the acute phase after stroke. SRBD was defined by an apnea-hypopnea index (AHI) ≥10. MRI were evaluated using standardized maps to depict voxel-wise probability distribution of infarction for patients with and without SRBD. Groups were compared using logistic regression analysis. RESULTS: Of 142 patients included, 86 (59%) had a SRBD. Age, body mass index and prevalence of arterial hypertension were significantly higher in patients with SRBD. There was no statistically significant association between any lesion location and SRBD. CONCLUSION: We found no association of lesion location and SRBD in stroke patients, whereas established risk factors for SRBD, known from general population, were significantly associated with SRBD. Given the high prevalence of SRBD in stroke patients, these findings suggest that cerebral ischemia facilitates the occurrence of SRBD in patients with pre-existing risk factors rather than causing it by damaging specific central nervous system structures. Our findings can be used to identify stroke patients who might benefit from polygraphy screening.

Volume transition analysis: a new approach to resolve reclassification of brain tissue in repeated MRI scans.

BACKGROUND: Variability in brain tissue volumes derived from magnetic resonance images is attributable to various sources. In quantitative comparisons it is therefore crucial to distinguish between biologically and methodically conditioned variance and to take spatial accordance into account. NEW METHOD: We introduce volume transition analysis as a method that not only provides details on numerical and spatial accordance of tissue volumes in repeated scans but also on voxel shifts between tissue types. Based on brain tissue probability maps, mono- and bidirectional voxel shifts can be examined by explicitly separating volume transitions into source and target. We apply the approach to a set of subject data from repeated intra-scanner (one week and 30 month interval) as well as inter-scanner measurements. RESULTS: In all measurement scenarios, we found similar inter-class transitions of 9.9-15.9% of intracranial volume. The percentage of monodirectional net volume transition however increases from 0.3% in short term intra-scanner to 1.6% in long term intra-scanner and 9.3% in inter-scanner comparisons. COMPARISON WITH EXISTING METHODS: Unlike most routinely used variability measures volume transition analysis is able to monitor reclassifications and thus to quantify not only balanced flows but also the amount of monodirectional net flows between tissue classes. The approach is independent from group analysis and can thus be applied in as few as two images. CONCLUSIONS: The proposed method is an easily applicable tool that is useful in discovering intra-individual brain changes and assists in separating biological from technical variance in structural brain measures.