Black Dog Institute

, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Neuronal dynamics unfolding within the cerebral cortex exhibit complex spatial and temporal patterns even in the absence of external input. Here we use a computational approach in an attempt to relate these features of spontaneous cortical dynamics to the underlying anatomical connectivity. Simulating nonlinear neuronal dynamics on a network that captures the large-scale interregional connections of macaque neocortex, and applying information theoretic measures to identify functional networks, we find structure-function relations at multiple temporal scales. Functional networks recovered from long windows of neural activity (minutes) largely overlap with the underlying structural network. As a result, hubs in these long-run functional networks correspond to structural hubs. In contrast, significant fluctuations in functional topology are observed across the sequence of networks recovered from consecutive shorter (seconds) time windows. The functional centrality of individual nodes varies across time as interregional couplings shift. Furthermore, the transient couplings between brain regions are coordinated in a manner that reveals the existence of two anticorrelated clusters. These clusters are linked by prefrontal and parietal regions that are hub nodes in the underlying structural network. At an even faster time scale (hundreds of milliseconds) we detect individual episodes of interregional phase-locking and find that slow variations in the statistics of these transient episodes, contingent on the underlying anatomical structure, produce the transfer entropy functional connectivity and simulated blood oxygenation level-dependent correlation patterns observed on slower time scales.

BACKGROUND: The rapid growth in the use of mobile phone applications (apps) provides the opportunity to increase access to evidence-based mental health care. OBJECTIVE: Our goal was to systematically review the research evidence supporting the efficacy of mental health apps for mobile devices (such as smartphones and tablets) for all ages. METHODS: A comprehensive literature search (2008-2013) in MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, PsycINFO, PsycTESTS, Compendex, and Inspec was conducted. We included trials that examined the effects of mental health apps (for depression, anxiety, substance use, sleep disturbances, suicidal behavior, self-harm, psychotic disorders, eating disorders, stress, and gambling) delivered on mobile devices with a pre- to posttest design or compared with a control group. The control group could consist of wait list, treatment-as-usual, or another recognized treatment. RESULTS: In total, 5464 abstracts were identified. Of those, 8 papers describing 5 apps targeting depression, anxiety, and substance abuse met the inclusion criteria. Four apps provided support from a mental health professional. Results showed significant reductions in depression, stress, and substance use. Within-group and between-group intention-to-treat effect sizes ranged from 0.29-2.28 and 0.01-0.48 at posttest and follow-up, respectively. CONCLUSIONS: Mental health apps have the potential to be effective and may significantly improve treatment accessibility. However, the majority of apps that are currently available lack scientific evidence about their efficacy. The public needs to be educated on how to identify the few evidence-based mental health apps available in the public domain to date. Further rigorous research is required to develop and test evidence-based programs. Given the small number of studies and participants included in this review, the high risk of bias, and unknown efficacy of long-term follow-up, current findings should be interpreted with caution, pending replication. Two of the 5 evidence-based mental health apps are currently commercially available in app stores.

The rapid advances and adoption of smartphone technology presents a novel opportunity for delivering mental health interventions on a population scale. Despite multi-sector investment along with wide-scale advertising and availability to the general population, the evidence supporting the use of smartphone apps in the treatment of depression has not been empirically evaluated. Thus, we conducted the first meta-analysis of smartphone apps for depressive symptoms. An electronic database search in May 2017 identified 18 eligible randomized controlled trials of 22 smartphone apps, with outcome data from 3,414 participants. Depressive symptoms were reduced significantly more from smartphone apps than control conditions (g=0.38, 95% CI: 0.24-0.52, p<0.001), with no evidence of publication bias. Smartphone interventions had a moderate positive effect in comparison to inactive controls (g=0.56, 95% CI: 0.38-0.74), but only a small effect in comparison to active control conditions (g=0.22, 95% CI: 0.10-0.33). Effects from smartphone-only interventions were greater than from interventions which incorporated other human/computerized aspects along the smartphone component, although the difference was not statistically significant. The studies of cognitive training apps had a significantly smaller effect size on depression outcomes (p=0.004) than those of apps focusing on mental health. The use of mood monitoring softwares, or interventions based on cognitive behavioral therapy, or apps incorporating aspects of mindfulness training, did not affect significantly study effect sizes. Overall, these results indicate that smartphone devices are a promising self-management tool for depression. Future research should aim to distil which aspects of these technologies produce beneficial effects, and for which populations.

The cortex is a complex system, characterized by its dynamics and architecture, which underlie many functions such as action, perception, learning, language, and cognition. Its structural architecture has been studied for more than a hundred years; however, its dynamics have been addressed much less thoroughly. In this paper, we review and integrate, in a unifying framework, a variety of computational approaches that have been used to characterize the dynamics of the cortex, as evidenced at different levels of measurement. Computational models at different space-time scales help us understand the fundamental mechanisms that underpin neural processes and relate these processes to neuroscience data. Modeling at the single neuron level is necessary because this is the level at which information is exchanged between the computing elements of the brain; the neurons. Mesoscopic models tell us how neural elements interact to yield emergent behavior at the level of microcolumns and cortical columns. Macroscopic models can inform us about whole brain dynamics and interactions between large-scale neural systems such as cortical regions, the thalamus, and brain stem. Each level of description relates uniquely to neuroscience data, from single-unit recordings, through local field potentials to functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and magnetoencephalogram (MEG). Models of the cortex can establish which types of large-scale neuronal networks can perform computations and characterize their emergent properties. Mean-field and related formulations of dynamics also play an essential and complementary role as forward models that can be inverted given empirical data. This makes dynamic models critical in integrating theory and experiments. We argue that elaborating principled and informed models is a prerequisite for grounding empirical neuroscience in a cogent theoretical framework, commensurate with the achievements in the physical sciences.

People with severe mental illness (schizophrenia, bipolar disorder or major depressive disorder) die up to 15 years prematurely due to chronic somatic comorbidities. Sedentary behavior and low physical activity are independent yet modifiable risk factors for cardiovascular disease and premature mortality in these people. A comprehensive meta‐analysis exploring these risk factors is lacking in this vulnerable population. We conducted a meta‐analysis investigating sedentary behavior and physical activity levels and their correlates in people with severe mental illness. Major electronic databases were searched from inception up to April 2017 for articles measuring sedentary behavior and/or physical activity with a self‐report questionnaire or an objective measure (e.g., accelerometer). Random effects meta‐analyses and meta‐regression analyses were conducted. Sixty‐nine studies were included (N=35,682; 39.5% male; mean age 43.0 years). People with severe mental illness spent on average 476.0 min per day (95% CI: 407.3‐545.4) being sedentary during waking hours, and were significantly more sedentary than age‐ and gender‐matched healthy controls (p=0.003). Their mean amount of moderate or vigorous physical activity was 38.4 min per day (95% CI: 32.0‐44.8), being significantly lower than that of healthy controls (p=0.002 for moderate activity, p&lt;0.001 for vigorous activity). People with severe mental illness were significantly less likely than matched healthy controls to meet physical activity guidelines (odds ratio = 1.5; 95% CI: 1.1‐2.0, p&lt;0.001, I 2 =95.8). Lower physical activity levels and non‐compliance with physical activity guidelines were associated with male gender, being single, unemployment, fewer years of education, higher body mass index, longer illness duration, antidepressant and antipsychotic medication use, lower cardiorespiratory fitness and a diagnosis of schizophrenia. People with bipolar disorder were the most physically active, yet spent most time being sedentary. Geographical differences were detected, and inpatients were more active than outpatients and those living in the community. Given the established health benefits of physical activity and its low levels in people with severe mental illness, future interventions specifically targeting the prevention of physical inactivity and sedentary behavior are warranted in this population.

BACKGROUND: Behavioural brain reserve is a property of the central nervous system related to sustained and complex mental activity which can lead to differential expression of brain injury. Behavioural brain reserve has been assessed using autobiographical data such as education levels, occupational complexity and mentally stimulating lifestyle pursuits. So far there have been several epidemiological reports but no systematic review to put conflicting results into context. Our aim was to quantitatively review evidence for the effect of brain reserve on incident dementia. METHOD: Cohort studies of the effects of education, occupation, premorbid IQ and mental activities on dementia risk were of interest. Abstracts were identified in MEDLINE (1966-September 2004), CURRENT CONTENTS (to September, 2004), PsychINFO (1984-September 2004), Cochrane Library Databases and reference lists from relevant articles. Twenty-two studies met inclusion criteria. Key information was extracted by both reviewers onto a standard template with a high level of agreement. Studies were combined through a quantitative random-effects meta-analysis. RESULTS: Higher brain reserve was associated with a lowered risk for incident dementia (summary odds ratio, 0.54; 95% confidence interval, 0.49-0.59). This effect was found over a median of 7.1 years follow-up and resulted from integrating data across more than 29000 individuals. Notably, increased complex mental activity in late life was associated with lower dementia rates independent of other predictors; a dose-response relationship was also evident between extent of complex mental activities in late life and dementia risk. CONCLUSIONS: This study demonstrates robust evidence that complex patterns of mental activity in the early, mid- and late-life stages is associated with a significant reduction in dementia incidence. Randomized control trials based on brain-reserve principles are now required.

The potential of smartphone apps to improve quality and increase access to mental health care is increasingly clear. Yet even in the current global mental health crisis, real-world uptake of smartphone apps by clinics or consumers remains low. To understand this dichotomy, this paper reviews current challenges surrounding user engagement with mental health smartphone apps. While smartphone engagement metrics and reporting remains heterogeneous in the literature, focusing on themes offers a framework to identify underlying trends. These themes suggest that apps are not designed with service users in mind, do not solve problems users care most about, do not respect privacy, are not seen as trustworthy and are unhelpful in emergencies. Respecting these current issues surrounding mental health app engagement, we propose several solutions and highlight successful examples of mental health apps with high engagement. Further research is necessary to better characterise engagement with mental health apps and identify best practices for design, testing and implementation.

Importance: Personalized treatment choices would increase the effectiveness of internet-based cognitive behavioral therapy (iCBT) for depression to the extent that patients differ in interventions that better suit them. Objective: To provide personalized estimates of short-term and long-term relative efficacy of guided and unguided iCBT for depression using patient-level information. Data Sources: We searched PubMed, Embase, PsycInfo, and Cochrane Library to identify randomized clinical trials (RCTs) published up to January 1, 2019. Study Selection: Eligible RCTs were those comparing guided or unguided iCBT against each other or against any control intervention in individuals with depression. Available individual patient data (IPD) was collected from all eligible studies. Depression symptom severity was assessed after treatment, 6 months, and 12 months after randomization. Data Extraction and Synthesis: We conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD network meta-regression. Main Outcomes and Measures: Patient Health Questionnaire-9 (PHQ-9) scores. Results: Of 42 eligible RCTs, 39 studies comprising 9751 participants with depression contributed IPD to the IPD network meta-analysis, of which 8107 IPD were synthesized. Overall, both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term. Guided iCBT was associated with more effectiveness than unguided iCBT (mean difference [MD] in posttreatment PHQ-9 scores, -0.8; 95% CI, -1.4 to -0.2), but we found no evidence of a difference at 6 or 12 months following randomization. Baseline depression was found to be the most important modifier of the relative association for efficacy of guided vs unguided iCBT. Differences between unguided and guided iCBT in people with baseline symptoms of subthreshold depression (PHQ-9 scores 5-9) were small, while guided iCBT was associated with overall better outcomes in patients with baseline PHQ-9 greater than 9. Conclusions and Relevance: In this network meta-analysis with IPD, guided iCBT was associated with more effectiveness than unguided iCBT for individuals with depression, benefits were more substantial in individuals with moderate to severe depression. Unguided iCBT was associated with similar effectiveness among individuals with symptoms of mild/subthreshold depression. Personalized treatment selection is entirely possible and necessary to ensure the best allocation of treatment resources for depression.

OBJECTIVES: To synthesise the available evidence on interventions designed to improve individual resilience. DESIGN: A systematic review and meta-analysis METHODS: The following electronic databases were searched: Ovid Medline, Ovid EMBASE, PsycINFO, Ovid Cochrane and WHO Clinical Trials Registry in order to identify any controlled trials or randomised controlled trials (RCTs) examining the efficacy of interventions aimed at improving psychological resilience. Pooled effects sizes were calculated using the random-effects model of meta-analysis. OUTCOME MEASURES: Valid and reliable measures of psychological resilience. RESULTS: Overall, 437 citations were retrieved and 111 peer-reviewed articles were examined in full. Seventeen studies met the inclusion criteria and were subject to a quality assessment, with 11 RCTs being included in the final meta-analysis. Programmes were stratified into one of three categories (1) cognitive behavioural therapy (CBT)-based interventions, (2) mindfulness-based interventions or (3) mixed Interventions, those combining CBT and Mindfulness training. A meta-analysis found a moderate positive effect of resilience interventions (0.44 (95% CI 0.23 to 0.64) with subgroup analysis suggesting CBT-based, mindfulness and mixed interventions were effective. CONCLUSIONS: Resilience interventions based on a combination of CBT and mindfulness techniques appear to have a positive impact on individual resilience.

BACKGROUND: Despite growing interest and urges by leading experts for the routine collection of patient reported outcome (PRO) measures in all general care patients, and in particular cancer patients, there has not been an updated comprehensive review of the evidence regarding the impact of adopting such a strategy on patients, service providers and organisations in an oncologic setting. METHODS: Based on a critical analysis of the three most recent systematic reviews, the current systematic review developed a six-method strategy in searching and reviewing the most relevant quantitative studies between January 2000 and October 2011 using a set of pre-determined inclusion criteria and theory-based outcome indicators. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system was used to rate the quality and importance of the identified publications, and the synthesis of the evidence was conducted. RESULTS: The 27 identified studies showed strong evidence that the well-implemented PROs improved patient-provider communication and patient satisfaction. There was also growing evidence that it improved the monitoring of treatment response and the detection of unrecognised problems. However, there was a weak or non-existent evidence-base regarding the impact on changes to patient management and improved health outcomes, changes to patient health behaviour, the effectiveness of quality improvement of organisations, and on transparency, accountability, public reporting activities, and performance of the health care system. CONCLUSIONS: Despite the existence of significant gaps in the evidence-base, there is growing evidence in support of routine PRO collection in enabling better and patient-centred care in cancer settings.

Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen’s d=−0.293; P=1.71 × 10−21), left fusiform gyrus (d=−0.288; P=8.25 × 10−21) and left rostral middle frontal cortex (d=−0.276; P=2.99 × 10−19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.

It has been suggested that certain types of work may increase the risk of common mental disorders, but the exact nature of the relationship has been contentious. The aim of this paper is to conduct the first comprehensive systematic meta-review of the evidence linking work to the development of common mental health problems, specifically depression, anxiety and/or work-related stress and to consider how the risk factors identified may relate to each other. MEDLINE, PsychInfo, Embase, the Cochrane Collaboration and grey literature databases were systematically searched for review articles that examined work-based risk factors for common mental health problems. All included reviews were subjected to a quality appraisal. 37 review studies were identified, of which 7 were at least moderate quality. 3 broad categories of work-related factors were identified to explain how work may contribute to the development of depression and/or anxiety: imbalanced job design, occupational uncertainty and lack of value and respect in the workplace. Within these broad categories, there was moderate level evidence from multiple prospective studies that high job demands, low job control, high effort-reward imbalance, low relational justice, low procedural justice, role stress, bullying and low social support in the workplace are associated with a greater risk of developing common mental health problems. While methodological limitations continue to preclude more definitive statements on causation between work and mental disorders, there is now a range of promising targets for individual and organisational-level interventions aimed at minimising mental health problems in the workplace.

Depression and anxiety often emerge for the first time during youth. The school environment provides an ideal context to deliver prevention programs, with potential to offset the trajectory towards disorder. The aim of this review was to provide a comprehensive evaluation of randomised-controlled trials of psychological programs, designed to prevent depression and/or anxiety in children and adolescents delivered in school settings. Medline, PsycINFO and the Cochrane Library were systematically searched for articles published until February 2015. Eighty-one unique studies comprising 31,794 school students met inclusion criteria. Small effect sizes for both depression (g=0.23) and anxiety (g=0.20) prevention programs immediately post-intervention were detected. Small effects were evident after 12-month follow-up for both depression (g=0.11) and anxiety (g=0.13). Overall, the quality of the included studies was poor, and heterogeneity was moderate. Subgroup analyses suggested that universal depression prevention programs had smaller effect sizes at post-test relative to targeted programs. For anxiety, effect sizes were comparable for universal and targeted programs. There was some evidence that externally-delivered interventions were superior to those delivered by school staff for depression, but not anxiety. Meta-regression confirmed that targeted programs predicted larger effect sizes for the prevention of depression. These results suggest that the refinement of school-based prevention programs have the potential to reduce mental health burden and advance public health outcomes.

BACKGROUND: Various psychological interventions are effective for reducing symptoms of anxiety when used alone, or as an adjunct to anti-anxiety medications. Recent studies have further indicated that smartphone-supported psychological interventions may also reduce anxiety, although the role of mobile devices in the treatment and management of anxiety disorders has yet to be established. METHODS: We conducted a systematic review and meta-analysis of all randomized clinical trials (RCTs) reporting the effects of psychological interventions delivered via smartphone on symptoms of anxiety (sub-clinical or diagnosed anxiety disorders). A systematic search of major electronic databases conducted in November 2016 identified 9 eligible RCTs, with 1837 participants. Random-effects meta-analyses were used to calculate the standardized mean difference (as Hedges' g) between smartphone interventions and control conditions. RESULTS: Significantly greater reductions in total anxiety scores were observed from smartphone interventions than control conditions (g=0.325, 95% C.I.=0.17-0.48, p<0.01), with no evidence of publication bias. Effect sizes from smartphone interventions were significantly greater when compared to waitlist/inactive controls (g=0.45, 95% C.I.=0.30-0.61, p<0.01) than active control conditions (g=0.19, 95% C.I.=0.07-0.31, p=0.003). LIMITATIONS: The extent to which smartphone interventions can match (or exceed) the efficacy of recognised treatments for anxiety has yet to established. CONCLUSIONS: This meta-analysis shows that psychological interventions delivered via smartphone devices can reduce anxiety. Future research should aim to develop pragmatic methods for implementing smartphone-based support for people with anxiety, while also comparing the efficacy of these interventions to standard face-to-face psychological care.

It is commonly suggested that a female preponderance in depression is universal and substantial. This review considers that proposition and explanatory factors. The view that depression rates are universally higher in women is challenged with exceptions to the proposition helping clarify candidate explanations. 'Real' and artefactual explanations for any such phenomenon are considered, and the contribution of sex role changes, social factors and biological determinants are overviewed. While artefactual factors make some contribution, it is concluded that there is a higher order biological factor (variably determined neuroticism, 'stress responsiveness' or 'limbic system hyperactivity') that principally contributes to the gender differentiation in some expressions of both depression and anxiety, and reflects the impact of gonadal steroid changes at puberty. Rather than conclude that 'anatomy is destiny' we favour a diathesis stress model, so accounting for differential epidemiological findings. Finally, the impact of gender on response to differing antidepressant therapies is considered briefly.

IMPORTANCE: Self-guided internet-based cognitive behavioral therapy (iCBT) has the potential to increase access and availability of evidence-based therapy and reduce the cost of depression treatment. OBJECTIVES: To estimate the effect of self-guided iCBT in treating adults with depressive symptoms compared with controls and evaluate the moderating effects of treatment outcome and response. DATA SOURCES: A total of 13 384 abstracts were retrieved through a systematic literature search in PubMed, Embase, PsycINFO, and Cochrane Library from database inception to January 1, 2016. STUDY SELECTION: Randomized clinical trials in which self-guided iCBT was compared with a control (usual care, waiting list, or attention control) in individuals with symptoms of depression. DATA EXTRACTION AND SYNTHESIS: Primary authors provided individual participant data from 3876 participants from 13 of 16 eligible studies. Missing data were handled using multiple imputations. Mixed-effects models with participants nested within studies were used to examine treatment outcomes and moderators. MAIN OUTCOMES AND MEASURES: Outcomes included the Beck Depression Inventory, Center for Epidemiological Studies-Depression Scale, and 9-item Patient Health Questionnaire scores. Scales were standardized across the pool of the included studies. RESULTS: Of the 3876 study participants, the mean (SD) age was 42.0 (11.7) years, 2531 (66.0%) of 3832 were female, 1368 (53.1%) of 2574 completed secondary education, and 2262 (71.9%) of 3146 were employed. Self-guided iCBT was significantly more effective than controls on depressive symptoms severity (β = -0.21; Hedges g = 0.27) and treatment response (β = 0.53; odds ratio, 1.95; 95% CI, 1.52-2.50; number needed to treat, 8). Adherence to treatment was associated with lower depressive symptoms (β = -0.19; P = .001) and greater response to treatment (β = 0.90; P < .001). None of the examined participant and study-level variables moderated treatment outcomes. CONCLUSIONS AND RELEVANCE: Self-guided iCBT is effective in treating depressive symptoms. The use of meta-analyses of individual participant data provides substantial evidence for clinical and policy decision making because self-guided iCBT can be considered as an evidence-based first-step approach in treating symptoms of depression. Several limitations of the iCBT should be addressed before it can be disseminated into routine care.

This systematic review and meta-analysis investigated the association between consumption of ultraprocessed food and noncommunicable disease risk, morbidity and mortality. Forty-three observational studies were included (N = 891,723): 21 cross-sectional, 19 prospective, two case-control and one conducted both a prospective and cross-sectional analysis. Meta-analysis demonstrated consumption of ultraprocessed food was associated with increased risk of overweight (odds ratio: 1.36; 95% confidence interval [CI], 1.23-1.51; P < 0.001), obesity (odds ratio: 1.51; 95% CI, 1.34-1.70; P < 0.001), abdominal obesity (odds ratio: 1.49; 95% CI, 1.34-1.66; P < 0.0001), all-cause mortality (hazard ratio: 1.28; 95% CI, 1.11-1.48; P = 0.001), metabolic syndrome (odds ratio: 1.81; 95% CI, 1.12-2.93; P = 0.015) and depression in adults (hazard ratio: 1.22; 95% CI, 1.16-1.28, P < 0.001) as well as wheezing (odds ratio: 1.40; 95% CI, 1.27-1.55; P < 0.001) but not asthma in adolescents (odds ratio: 1.20; 95% CI, 0.99-1.46; P = 0.065). In addition, consumption of ultraprocessed food was associated with cardiometabolic diseases, frailty, irritable bowel syndrome, functional dyspepsia and cancer (breast and overall) in adults while also being associated with metabolic syndrome in adolescents and dyslipidaemia in children. Although links between ultraprocessed food consumption and some intermediate risk factors in adults were also highlighted, further studies are required to more clearly define associations in children and adolescents. STUDY REGISTRATION: Prospero ID: CRD42020176752.

Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.