Search

Despite most episodes of low back pain (LBP) being short-lasting, some transition into persistent long-lasting problems. Hence, the need for a deeper understanding of the physiological mechanisms of this is pertinent. Therefore, the aims of the present study are (1) to map pain-induced changes in brain activity and blood gene expression associated with persistent LBP, and (2) to explore whether these brain and gene expression signatures show promise as predictive biomarkers for the development of persistent LBP. The participants will be allocated into three different pain groups (no pain, mild short-lasting, or moderate long-term). One in-person visit, where two blood samples will be collected and sent for RNA sequencing, along with resting 64-channel electro-encephalography measurements before, during, and after a cold pressor test, will be conducted. Thereafter, follow-up questionnaires will be distributed at 2 weeks, 3 months, and 6 months. Recruitment will start during the second quarter of 2024, with expected completion by the last quarter of 2024. The results are expected to provide insight into the relationship between central nervous system activity, gene expression profiles, and LBP. If successful, this study has the potential to provide physiological indicators that are sensitive to the transition from mild, short-term LBP to more problematic, long-term LBP.

Background: Adolescence hosts a sharp increase in the incidence of mental disorders. The prodromal phases are often characterized by cognitive deficits that predate disease onset by several years. Characterization of cognitive performance in relation to normative trajectories may have value for early risk assessment and monitoring. Methods: Youth aged 8 to 21 years (N = 6481) from the Philadelphia Neurodevelopmental Cohort were included. Performance scores from a computerized neurocognitive battery were decomposed using principal component analysis, yielding a general cognitive score. Items reflecting various aspects of psychopathology from self-report questionnaires and collateral caregiver information were decomposed using independent component analysis, providing individual domain scores. Using normative modeling and Bayesian statistics, we estimated normative trajectories of cognitive function and tested for associations between cognitive deviance and psychopathological domain scores. In addition, we tested for associations with polygenic scores for mental and behavioral disorders often involving cognition, including schizophrenia, bipolar disorder, attention-deficit/hyperactivity disorder, and Alzheimer’s disease. Results: More negative normative cognitive deviations were associated with higher general psychopathology burden and domains reflecting positive and prodromal psychosis, attention problems, norm-violating behavior, and anxiety. In addition, better performance was associated with higher joint burden of depression, suicidal ideation, and negative psychosis symptoms. The analyses revealed no evidence for associations with polygenic scores. Conclusions: Our results show that cognitive performance is associated with general and specific domains of psychopathology in youth. These findings support the close links between cognition and psychopathology in youth and highlight the potential of normative modeling for early risk assessment.

Abstract Understanding complex body–brain processes and the interplay between adipose tissue and brain health is important for understanding comorbidity between psychiatric and cardiometabolic disorders. We investigated associations between brain structure and anthropometric and body composition measures using brain magnetic resonance imaging (MRI; n = 24,728) and body MRI (n = 4973) of generally healthy participants in the UK Biobank. We derived regional and global measures of brain morphometry using FreeSurfer and tested their association with (i) anthropometric measures, and (ii) adipose and muscle tissue measured from body MRI. We identified several significant associations with small effect sizes. Anthropometric measures showed negative, nonlinear, associations with cerebellar/cortical gray matter, and brain stem structures, and positive associations with ventricular volumes. Subcortical structures exhibited mixed effect directionality, with strongest positive association for accumbens. Adipose tissue measures, including liver fat and muscle fat infiltration, were negatively associated with cortical/cerebellum structures, while total thigh muscle volume was positively associated with brain stem and accumbens. Regional investigations of cortical area, thickness, and volume indicated widespread and largely negative associations with anthropometric and adipose tissue measures, with an opposite pattern for thigh muscle volume. Self-reported diabetes, hypertension, or hypercholesterolemia were associated with brain structure. The findings provide new insight into physiological body–brain associations suggestive of shared mechanisms between cardiometabolic risk factors and brain health. Whereas the causality needs to be determined, the observed patterns of body–brain relationships provide a foundation for understanding the underlying mechanisms linking psychiatric disorders with obesity and cardiovascular disease, with potential for the development of new prevention strategies.

Abstract Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers—the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Despite most episodes of low back pain (LBP) being short-lasting, some transition into persistent long-lasting problems. Hence, the need for a deeper understanding of the physiological mechanisms of this is pertinent. Therefore, the aims of the present study are (1) to map pain-induced changes in brain activity and blood gene expression associated with persistent LBP, and (2) to explore whether these brain and gene expression signatures show promise as predictive biomarkers for the development of persistent LBP. The participants will be allocated into three different pain groups (no pain, mild short-lasting, or moderate long-term). One in-person visit, where two blood samples will be collected and sent for RNA sequencing, along with resting 64-channel electro-encephalography measurements before, during, and after a cold pressor test, will be conducted. Thereafter, follow-up questionnaires will be distributed at 2 weeks, 3 months, and 6 months. Recruitment will start during the second quarter of 2024, with expected completion by the last quarter of 2024. The results are expected to provide insight into the relationship between central nervous system activity, gene expression profiles, and LBP. If successful, this study has the potential to provide physiological indicators that are sensitive to the transition from mild, short-term LBP to more problematic, long-term LBP. [ABSTRACT FROM AUTHOR]

Long-term potentiation (LTP) is one of the most extensively studied forms of neuroplasticity and is considered the strongest candidate mechanism for memory and learning. The use of event-related potentials and sensory stimulation paradigms has allowed for the translation from animal studies to non-invasive studies of LTP-like synaptic plasticity in humans. Accumulating evidence suggests that synaptic plasticity as measured by stimulus-specific response modulation is reduced in neuropsychiatric disorders such as major depressive disorder (MDD), bipolar disorders and schizophrenia, suggesting that impaired synaptic plasticity plays a part in the underlying pathophysiology of these disorders. This is in line with the neuroplasticity hypothesis of depression, which postulate that deficits in neuroplasticity might be a common pathway underlying depressive disorders. The current study aims to replicate and confirm earlier reports that visual stimulus-specific response modulation is a viable probe into LTP-like synaptic plasticity in a large sample of healthy adults (n = 111). Further, this study explores whether impairments in LTP-like synaptic plasticity is associated with self-reported subclinical depressive symptoms and stress in a healthy population. Consistent with prior research, the current study replicated and confirmed reports demonstrating significant modulation of visual evoked potentials (VEP) following visual high-frequency stimulation. Current results further indicate that reduced LTP-like synaptic plasticity is associated with higher levels of self-reported symptoms of depression and perceived stress. This indicate that LTP-like plasticity is sensitive to sub-clinical levels of psychological distress, and might represent a vulnerability marker for the development of depressive symptoms.

The genetic architecture underlying brainstem regions and how this links to common brain disorders is not well understood. Here, the authors use MRI and GWAS data from 27,034 individuals to identify genetic and morphological brainstem features that influence common brain disorders.

Abstract Background and purpose The ENIGMA‐EEG working group was established to enable large‐scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain. Methods We summarize how we have performed our currently largest genome‐wide association study of oscillatory brain activity in EEG recordings by meta‐analyzing the results across five participating cohorts, resulting in the first genome‐wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta‐analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations. Results We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters. Conclusion The long list of potential challenges to our large‐scale meta‐analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability.

Experience-dependent modulation of the visual evoked potential (VEP) is a promising proxy measure of synaptic plasticity in the cerebral cortex. However, existing studies are limited by small to moderate sample sizes as well as by considerable variability in how VEP modulation is quantified. In the present study, we used a large sample (n = 415) of healthy volunteers to compare different quantifications of VEP modulation with regards to effect sizes and retention of the modulation effect over time. We observed significant modulation for VEP components C1 (Cohen's d = 0.53), P1 (d = 0.66), N1 (d=-0.27), N1b (d=-0.66), but not P2 (d = 0.08), and in three clusters of total power modulation, 2–4 min after 2 Hz prolonged visual stimulation. For components N1 (d=-0.21) and N1b (d=-0.38), as well for the total power clusters, this effect was retained after 54–56 min, by which time also the P2 component had gained modulation (d = 0.54). Moderate to high correlations (0.39≤ρ≤0.69) between modulation at different postintervention blocks revealed a relatively high temporal stability in the modulation effect for each VEP component. However, different VEP components also showed markedly different temporal retention patterns. Finally, participant age correlated negatively with C1 (χ2=30.4), and positively with P1 modulation (χ2=13.4), whereas P2 modulation was larger for female participants (χ2=15.4). There were no effects of either age or sex on N1 and N1b potentiation. These results provide strong support for VEP modulation, and especially N1b modulation, as a robust measure of synaptic plasticity, but underscore the need to differentiate between components, and to control for demographic confounders.

The brain underpinnings of schizophrenia and bipolar disorders are multidimensional, reflecting complex pathological processes and causal pathways, requiring multivariate techniques to disentangle. Furthermore, little is known about the complementary clinical value of brain structural phenotypes when combined with data on cognitive performance and genetic risk. Using data-driven fusion of cortical thickness, surface area, and gray matter density maps (GMD), we found six biologically meaningful patterns showing strong group effects, including four statistically independent multimodal patterns reflecting co-occurring alterations in thickness and GMD in patients, over and above two other independent patterns of widespread thickness and area reduction. Case-control classification using cognitive scores alone revealed high accuracy, and adding imaging features or polygenic risk scores increased performance, suggesting their complementary predictive value with cognitive scores being the most sensitive features. Multivariate pattern analyses reveal distinct patterns of brain morphology in mental disorders, provide insights on the relative importance between brain structure, cognitive and polygenetic risk score in classification of patients, and demonstrate the importance of multivariate approaches in studying the pathophysiological substrate of these complex disorders. Keywords: Multimodal MRI, Clinical prediction, Classification, Brain structure, Schizophrenia, Bipolar disorder, Cognition, Polygenic risk

The brain is the most complex of human organs, and the pathophysiology underlying abnormal brain function in psychiatric disorders is largely unknown. Despite the rapid development of diagnostic tools and treatments in most areas of medicine, our understanding of mental disorders and their treatment has made limited progress during the last decades. While recent advances in genetics and neuroscience have a large potential, the complexity and multidimensionality of the brain processes hinder the discovery of disease mechanisms that would link genetic findings to clinical symptoms and behavior. This applies also to schizophrenia, for which genome-wide association studies have identified a large number of genetic risk loci, spanning hundreds of genes with diverse functionalities. Importantly, the multitude of the associated variants and their prevalence in the healthy population limit the potential of a reductionist functional genetics approach as a stand-alone solution to discover the disease pathology. In this review, we outline the key concepts of a “biophysical psychiatry,” an approach that employs large-scale mechanistic, biophysics-founded computational modelling to increase transdisciplinary understanding of the pathophysiology and strive toward robust predictions. We discuss recent scientific advances that allow a synthesis of previously disparate fields of psychiatry, neurophysiology, functional genomics, and computational modelling to tackle open questions regarding the pathophysiology of heritable mental disorders. We argue that the complexity of the increasing amount of genetic data exceeds the capabilities of classical experimental assays and requires computational approaches. Biophysical psychiatry, based on modelling diseased brain networks using existing and future knowledge of basic genetic, biochemical, and functional properties on a single neuron to a microcircuit level, may allow a leap forward in deriving interpretable biomarkers and move the field toward novel treatment options.

The precise neurobiological processes underlying cerebral cortical thinning in aging and psychiatric illnesses remain undetermined, yet aging‐ and synaptic dysfunction‐related loss of synapses are potentially important mechanisms. We used long‐term potentiation‐like plasticity of the visual evoked potential as an index of synaptic function in the cortex and hypothesized that plasticity at baseline would be negatively associated with future cortical thinning in healthy adults and in adults with bipolar disorder type II. Thirty‐two healthy adults and 15 adults with bipolar disorder type II underwent electroencephalography‐based measurement of visual evoked potential plasticity and 3T magnetic resonance imaging of the brain at baseline and a follow‐up brain scan on average 2.3 years later. The relationships between visual evoked potential plasticity at baseline and longitudinal cortical thickness changes were examined using Freesurfer and the Permutation Analysis of Linear Models tool. The analyses showed a negative association between the plasticity of the N1 visual evoked potential amplitude at baseline and thinning rate in the medial and lateral parietal and medial occipital cortices in healthy adults and in the right medial occipital cortex in the total sample of healthy adults and adults with bipolar disorder type II, indicating greater thinning over time in subjects with less N1 plasticity (pFWER <.05). Although preliminary, the results indicate an association between visual evoked potential plasticity and the future rate of cortical thinning in healthy adults and in bipolar disorder type II, supporting the hypothesis that cortical thinning might be related to synaptic dysfunction. [ABSTRACT FROM AUTHOR]

Background. The diagnostic usefulness of electrophysiological methods in assessing disorders of consciousness (DoC) remains to be established on an individual patient level, and there is need to determine what constitutes robust experimental paradigm to elicit electrophysiological indices of covert cognitive capacity. Objectives. Two tasks encompassing active and passive conditions were explored in an event-related potentials (ERP) study. The task robustness was studied in healthy controls, and their utility to detect covert signs of command-following on an individual patient level was investigated in patients in a minimally conscious state (MCS). Methods. Twenty healthy controls and 20 MCS patients participated. The active tasks included (1) listening for a change of pitch in the subject’s own name (SON) and (2) counting SON, both contrasted to passive conditions. Midline ERPs are reported. Results. A larger P3 response was detected in the counting task compared to active listening to pitch change in the healthy controls. On an individual level, the counting task revealed a higher rate of responders among both healthy subjects and MCS patients. Conclusion. ERP paradigms involving actively counting SON represent a robust paradigm in probing for volitional cognition in minimally conscious patients and add important diagnostic information in some patients.

Background and Hypothesis The auditory cortex (AC) may play a central role in the pathophysiology of schizophrenia and auditory hallucinations (AH). Previous schizophrenia studies report thinner AC and impaired AC function, as indicated by decreased N100 amplitude of the auditory evoked potential. However, whether these structural and functional alterations link to AH in schizophrenia remain poorly understood. Study Design Patients with a schizophrenia spectrum disorder (SCZspect), including patients with a lifetime experience of AH (AH+), without (AH−), and healthy controls underwent magnetic resonance imaging (39 SCZspect, 22 AH+, 17 AH−, and 146 HC) and electroencephalography (33 SCZspect, 17 AH+, 16 AH−, and 144 HC). Cortical thickness of the primary (AC1, Heschl's gyrus) and secondary (AC2, Heschl's sulcus, and the planum temporale) AC was compared between SCZspect and controls and between AH+, AH−, and controls. To examine if the association between AC thickness and N100 amplitude differed between groups, we used regression models with interaction terms. Study Results N100 amplitude was nominally smaller in SCZspect (P =.03, d = 0.42) and in AH− (P =.020, d = 0.61), while AC2 was nominally thinner in AH+ (P =.02, d = 0.53) compared with controls. AC1 thickness was positively associated with N100 amplitude in SCZspect (t = 2.56, P =.016) and AH− (t = 3.18, P =.008), while AC2 thickness was positively associated with N100 amplitude in SCZspect (t = 2.37, P =.024) and in AH+ (t = 2.68, P =.019). Conclusions The novel findings of positive associations between AC thickness and N100 amplitude in SCZspect, suggest that a common neural substrate may underlie AC thickness and N100 amplitude alterations. [ABSTRACT FROM AUTHOR]

Long-term potentiation (LTP) is one of the most extensively studied forms of neuroplasticity and is considered the strongest candidate mechanism for memory and learning. The use of event-related potentials and sensory stimulation paradigms has allowed for the translation from animal studies to non-invasive studies of LTP-like synaptic plasticity in humans. Accumulating evidence suggests that synaptic plasticity as measured by stimulus-specific response modulation is reduced in neuropsychiatric disorders such as major depressive disorder (MDD), bipolar disorders and schizophrenia, suggesting that impaired synaptic plasticity plays a part in the underlying pathophysiology of these disorders. This is in line with the neuroplasticity hypothesis of depression, which postulate that deficits in neuroplasticity might be a common pathway underlying depressive disorders. The current study aims to replicate and confirm earlier reports that visual stimulus-specific response modulation is a viable probe into LTP-like synaptic plasticity in a large sample of healthy adults (n = 111). Further, this study explores whether impairments in LTP-like synaptic plasticity is associated with self-reported subclinical depressive symptoms and stress in a healthy population. Consistent with prior research, the current study replicated and confirmed reports demonstrating significant modulation of visual evoked potentials (VEP) following visual high-frequency stimulation. Current results further indicate that reduced LTP-like synaptic plasticity is associated with higher levels of self-reported symptoms of depression and perceived stress. This indicate that LTP-like plasticity is sensitive to sub-clinical levels of psychological distress, and might represent a vulnerability marker for the development of depressive symptoms. [ABSTRACT FROM AUTHOR]

Maternal brain adaptations occur in response to pregnancy, but little is known about how parity impacts white matter and white matter ageing trajectories later in life. Utilising global and regional brain age prediction based on multi‐shell diffusion‐weighted imaging data, we investigated the association between previous childbirths and white matter brain age in 8,895 women in the UK Biobank cohort (age range = 54–81 years). The results showed that number of previous childbirths was negatively associated with white matter brain age, potentially indicating a protective effect of parity on white matter later in life. Both global white matter and grey matter brain age estimates showed unique contributions to the association with previous childbirths, suggesting partly independent processes. Corpus callosum contributed uniquely to the global white matter association with previous childbirths, and showed a stronger relationship relative to several other tracts. While our findings demonstrate a link between reproductive history and brain white matter characteristics later in life, longitudinal studies are required to establish causality and determine how parity may influence women's white matter trajectories across the lifespan. [ABSTRACT FROM AUTHOR]

Identifying brain processes involved in the risk and development of mental disorders is a major aim. We recently reported substantial interindividual heterogeneity in brain structural aberrations among patients with schizophrenia and bipolar disorder. Estimating the normative range of voxel‐based morphometry (VBM) data among healthy individuals using a Gaussian process regression (GPR) enables us to map individual deviations from the healthy range in unseen datasets. Here, we aim to replicate our previous results in two independent samples of patients with schizophrenia (n1 = 94; n2 = 105), bipolar disorder (n1 = 116; n2 = 61), and healthy individuals (n1 = 400; n2 = 312). In line with previous findings with exception of the cerebellum our results revealed robust group level differences between patients and healthy individuals, yet only a small proportion of patients with schizophrenia or bipolar disorder exhibited extreme negative deviations from normality in the same brain regions. These direct replications support that group level‐differences in brain structure disguise considerable individual differences in brain aberrations, with important implications for the interpretation and generalization of group‐level brain imaging findings to the individual with a mental disorder. [ABSTRACT FROM AUTHOR]

Stimulus response modulation (SRM) of sensory evoked potentials represents a promising method as a non‐invasive index of long‐term potentiation (LTP)‐like synaptic plasticity in the human sensory cortices. As of today, however, no consensus exists regarding which experimental parameters elicit the most robust SRM response. The aim of the current study was twofold; firstly, we aimed to replicate former studies demonstrating visual SRM in healthy adults. Second, we integrated visual and auditory stimuli within the same SRM recording session to assay potential cross‐modal associations. Such an association between modalities would strengthen the assumption that the SRM effect reflects common mechanisms underlying synaptic plasticity rather than reflecting modality‐specific phenomena. A replication of previous findings showing robust potentiation of the visual evoked potential was evident, supporting the majority of previous work using similar paradigms, lending further support to the notion that high‐frequent visual stimulation is a viable probe into LTP‐like synaptic plasticity in the human visual cortex. The auditory evoked potentials (AEPs) did not, however, fully replicate previous work, though a significant increase of temporally later AEP components was found. In contrast to our hypothesis, there were no significant within‐subject cross‐modality correlations between the visual and auditory SRM. This lack of significant association might suggest that auditory and visual SRM depend on different mechanisms, and that further SRM studies on non‐invasive LTP‐like synaptic plasticity should focus on optimizing paradigms within the visual modality. [ABSTRACT FROM AUTHOR]

The brain is the most complex of human organs, and the pathophysiology underlying abnormal brain function in psychiatric disorders is largely unknown. Despite the rapid development of diagnostic tools and treatments in most areas of medicine, our understanding of mental disorders and their treatment has made limited progress during the last decades. While recent advances in genetics and neuroscience have a large potential, the complexity and multidimensionality of the brain processes hinder the discovery of disease mechanisms that would link genetic findings to clinical symptoms and behavior. This applies also to schizophrenia, for which genome-wide association studies have identified a large number of genetic risk loci, spanning hundreds of genes with diverse functionalities. Importantly, the multitude of the associated variants and their prevalence in the healthy population limit the potential of a reductionist functional genetics approach as a stand-alone solution to discover the disease pathology. In this review, we outline the key concepts of a "biophysical psychiatry," an approach that employs large-scale mechanistic, biophysics-founded computational modelling to increase transdisciplinary understanding of the pathophysiology and strive toward robust predictions. We discuss recent scientific advances that allow a synthesis of previously disparate fields of psychiatry, neurophysiology, functional genomics, and computational modelling to tackle open questions regarding the pathophysiology of heritable mental disorders. We argue that the complexity of the increasing amount of genetic data exceeds the capabilities of classical experimental assays and requires computational approaches. Biophysical psychiatry, based on modelling diseased brain networks using existing and future knowledge of basic genetic, biochemical, and functional properties on a single neuron to a microcircuit level, may allow a leap forward in deriving interpretable biomarkers and move the field toward novel treatment options. [ABSTRACT FROM AUTHOR]