Anomalous brain gyrification patterns in major psychiatric disorders: a systematic review and transdiagnostic integration.
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ABSTRACT:
SUBMITTER: Sasabayashi D
PROVIDER: S-EPMC7969935 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Cortical gyrification of the brain represents the folding characteristic of the cerebral cortex. How the brain cortical gyrification changes from childhood to old age in healthy human subjects is still unclear. Additionally, studies have shown regional gyrification alterations in patients with major psychiatric disorders, such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ). However, whether the lifespan trajectory of gyrification over the brain is altered in patients diagnosed with major psychiatric disorders is still unknown. In this study, we investigated the trajectories of gyrification in three independent cohorts based on structural brain images of 881 subjects from age 4 to 83. We discovered that the trajectory of gyrification during normal development and aging was not linear and could be modeled with a logarithmic function. We also found that the gyrification trajectories of patients with MDD, BD and SCZ were deviated from the healthy one during adulthood, indicating altered aging in the brain of these patients.
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Project description:Psychiatric disorders are heritable, polygenic traits, which often share risk alleles and for which nonrandom mating has been suggested. However, despite the potential etiological implications, the scale of nonrandom mating within and across major psychiatric conditions remains unclear.To quantify the nature and extent of nonrandom mating within and across a broad range of psychiatric conditions at the population level.Population-based cohort using Swedish population registers. Participants were all Swedish residents with a psychiatric diagnosis of interest (attention-deficit/hyperactivity disorder, autism spectrum disorder, schizophrenia, bipolar disorder, major depression, generalized anxiety disorder, agoraphobia, social phobia, obsessive-compulsive disorder, anorexia, or substance abuse), along with their mates. Individuals with select nonpsychiatric disorders (Crohn's disease, type 1 and type 2 diabetes mellitus, multiple sclerosis, or rheumatoid arthritis) were included for comparison. General population samples were also derived and matched 1:5 with each case proband. Inpatient and outpatient diagnostic data were derived from the Swedish National Patient Register (1973-2009), with analyses conducted between June 2014 and May 2015.Correlation in the diagnostic status of mates both within and across disorders. Conditional logistic regression was used to quantify the odds of each diagnosis in the mates of cases relative to matched population controls.Across cohorts, data corresponded to 707?263 unique case individuals, with women constituting 45.7% of the full population. Positive correlations in diagnostic status were evident between mates. Within-disorder correlations were marginally higher (range, 0.11-0.48) than cross-disorder correlations (range, 0.01-0.42). Relative to matched populations, the odds of psychiatric case probands having an affected mate were significantly elevated. Differences in the magnitude of observed relationships were apparent by disorder (odds ratio range, 0.8-11.4). The number of comorbidities in a case proband was associated with the proportion of affected mates. These relationships were not apparent or weaker in magnitude among nonpsychiatric conditions (correlation range, -0.03 to 0.17).Nonrandom mating is evident in psychiatric populations both within specific disorders and across the spectrum of psychiatric conditions. This phenomenon may hold important implications for how we understand the familial transmission of these disorders and for psychiatric genetic research.
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Project description:Memory deficits are observed in a range of psychiatric disorders, but it is unclear whether memory deficits arise from a shared brain correlate across disorders or from various dysfunctions unique to each disorder. Connectome-based predictive modeling is a computational method that captures individual differences in functional connectomes associated with behavioral phenotypes such as memory. We used publicly available task-based functional MRI data from patients with schizophrenia (n = 33), bipolar disorder (n = 34), attention deficit hyper-activity disorder (n = 32), and healthy controls (n = 73) to model the macroscale brain networks associated with working, short- and long-term memory. First, we use 10-fold and leave-group-out analyses to demonstrate that the same macroscale brain networks subserve memory across diagnostic groups and that individual differences in memory performance are related to individual differences within networks distributed throughout the brain, including the subcortex, default mode network, limbic network, and cerebellum. Next, we show that diagnostic groups are associated with significant differences in whole-brain functional connectivity that are distinct from the predictive models of memory. Finally, we show that models trained on the transdiagnostic sample generalize to novel, healthy participants (n = 515) from the Human Connectome Project. These results suggest that despite significant differences in whole-brain patterns of functional connectivity between diagnostic groups, the core macroscale brain networks that subserve memory are shared.
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Project description:Childhood learning difficulties and developmental disorders are common, but progress toward understanding their underlying brain mechanisms has been slow. Structural neuroimaging, cognitive, and learning data were collected from 479 children (299 boys, ranging in age from 62 to 223 months), 337 of whom had been referred to the study on the basis of learning-related cognitive problems. Machine learning identified different cognitive profiles within the sample, and hold-out cross-validation showed that these profiles were significantly associated with children's learning ability. The same machine learning approach was applied to cortical morphology data to identify different brain profiles. Hold-out cross-validation demonstrated that these were significantly associated with children's cognitive profiles. Crucially, these mappings were not one-to-one. The same neural profile could be associated with different cognitive impairments across different children. One possibility is that the organization of some children's brains is less susceptible to local deficits. This was tested by using diffusion-weighted imaging (DWI) to construct whole-brain white-matter connectomes. A simulated attack on each child's connectome revealed that some brain networks were strongly organized around highly connected hubs. Children with these networks had only selective cognitive impairments or no cognitive impairments at all. By contrast, the same attacks had a significantly different impact on some children's networks, because their brain efficiency was less critically dependent on hubs. These children had the most widespread and severe cognitive impairments. On this basis, we propose a new framework in which the nature and mechanisms of brain-to-cognition relationships are moderated by the organizational context of the overall network.
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Project description:ImportanceDelay discounting is a behavioral economic index of impulsive preferences for smaller-immediate or larger-delayed rewards that is argued to be a transdiagnostic process across health conditions. Studies suggest some psychiatric disorders are associated with differences in discounting compared with controls, but null findings have also been reported.ObjectiveTo conduct a meta-analysis of the published literature on delay discounting in people with psychiatric disorders.Data sourcesPubMed, MEDLINE, PsycInfo, Embase, and Web of Science databases were searched through December 10, 2018. The psychiatric keywords used were based on DSM-IV or DSM-5 diagnostic categories. Collected data were analyzed from December 10, 2018, through June 1, 2019.Study selectionFollowing a preregistered Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol, 2 independent raters reviewed titles, abstracts, and full-text articles. English-language articles comparing monetary delay discounting between participants with psychiatric disorders and controls were included.Data extraction and synthesisHedges g effect sizes were computed and random-effects models were used for all analyses. Heterogeneity statistics, one-study-removed analyses, and publication bias indices were also examined.Main outcomes and measuresCategorical comparisons of delay discounting between a psychiatric group and a control group.ResultsThe sample included 57 effect sizes from 43 studies across 8 diagnostic categories. Significantly steeper discounting for individuals with a psychiatric disorder compared with controls was observed for major depressive disorder (Hedges g = 0.37; P = .002; k = 7), schizophrenia (Hedges g = 0.46; P = .004; k = 12), borderline personality disorder (Hedges g = 0.60; P < .001; k = 8), bipolar disorder (Hedges g = 0.68; P < .001; k = 4), bulimia nervosa (Hedges g = 0.41; P = .001; k = 4), and binge-eating disorder (Hedges g = 0.34; P = .001; k = 7). In contrast, anorexia nervosa exhibited statistically significantly shallower discounting (Hedges g = -0.30; P < .001; k = 10). Modest evidence of publication bias was indicated by a statistically significant Egger test for schizophrenia and at the aggregate level across studies.Conclusions and relevanceResults of this study appear to provide empirical support for delay discounting as a transdiagnostic process across most of the psychiatric disorders examined; the literature search also revealed limited studies in some disorders, notably posttraumatic stress disorder, which is a priority area for research.
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Project description:Postpartum psychiatric disorders are heritable, but how genetic liability varies by other significant risk factors is unknown. We aimed to (1) estimate associations of genetic risk scores (GRS) for major depression (MD), bipolar disorder (BD), and schizophrenia (SCZ) with postpartum psychiatric disorders, (2) examine differences by prior psychiatric history, and (3) compare genetic and familial risk of postpartum psychiatric disorders. We conducted a nested case-control study based on Danish population-based registers of all women in the iPSYCH2012 cohort who had given birth before December 31, 2015 (n = 8850). Cases were women with a diagnosed psychiatric disorder or a filled psychotropic prescription within one year after delivery (n = 5829 cases, 3021 controls). Association analyses were conducted between GRS calculated from Psychiatric Genomics Consortium discovery meta-analyses for MD, BD, and SCZ and case-control status of a postpartum psychiatric disorder. Parental psychiatric history was associated with postpartum psychiatric disorders among women with previous psychiatric history (OR, 1.14; 95% CI 1.02-1.28) but not without psychiatric history (OR, 1.08; 95% CI: 0.81-1.43). GRS for MD was associated with an increased risk of postpartum psychiatric disorders in both women with (OR, 1.44; 95% CI: 1.19-1.74) and without (OR, 1.88; 95% CI: 1.26-2.81) personal psychiatric history. SCZ GRS was only minimally associated with postpartum disorders and BD GRS was not. Results suggest GRS of lifetime psychiatric illness can be applied to the postpartum period, which may provide clues about distinct environmental or genetic elements of postpartum psychiatric disorders and ultimately help identify vulnerable groups.
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Project description:It has recently been proposed that a single dimension, called the p factor, can capture a person's liability to mental disorder. Relevant to the p hypothesis, recent genetic research has found surprisingly high genetic correlations between pairs of psychiatric disorders. Here, for the first time, we compare genetic correlations from different methods and examine their support for a genetic p factor. We tested the hypothesis of a genetic p factor by applying principal component analysis to matrices of genetic correlations between major psychiatric disorders estimated by three methods-family study, genome-wide complex trait analysis, and linkage-disequilibrium score regression-and on a matrix of polygenic score correlations constructed for each individual in a UK-representative sample of 7 026 unrelated individuals. All disorders loaded positively on a first unrotated principal component, which accounted for 57, 43, 35, and 22% of the variance respectively for the four methods. Our results showed that all four methods provided strong support for a genetic p factor that represents the pinnacle of the hierarchical genetic architecture of psychopathology.
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Project description:BackgroundNonprofessional carers who provide support to an individual with a psychiatric or neurological disorder will often themselves experience symptoms of stress, anxiety, or low mood, and they perceive that they receive little support. Internet-based interventions have previously been found to be effective in the prevention and treatment of a range of mental health difficulties in carers.ObjectiveThis review seeks to establish the status of internet-based interventions for informal (nonprofessional) carers of people with psychiatric or neurological disorders by investigating (1) the number and quality of studies evaluating the efficacy or effectiveness of internet-based carer interventions and (2) the impact that such interventions have on carer mental health, as well as (3) how internet-based interventions compare with other intervention types (eg, face-to-face treatment).MethodsA systematic literature search was conducted in January 2019 using the EMBASE (1974-present), Ovid MEDLINE (1946-present), PsychARTICLES, PsychINFO (1806-present), and Global Health (1973-present) databases, via the Ovid Technologies database. Search terms included carer, caregiver, online, technology, internet-based, internet, interactive, intervention, and evaluation. Studies selected for inclusion in this review met the following predetermined criteria: (1) delivering an intervention aimed primarily at informal carers, (2) carers supporting individuals with psychiatric disorders, stroke, dementia, or brain injury, (3) the intervention delivered to the carers was primarily internet based, (4) the study reported a pre- and postquantitative measure of carer depression, anxiety, stress, burden, or quality of life, (5) appeared in a peer-reviewed journal, and (6) was accessible in English.ResultsA total of 46 studies were identified for inclusion through the detailed search strategy. The search was conducted, and data were extracted independently by 2 researchers. The majority of studies reported that 1 or more measures relating to carer mental health improved following receipt of a relevant intervention, with interventions for carers of people with traumatic brain injury showing a consistent link with improved outcomes.ConclusionsStudies investigating internet-based interventions for carers of individuals with diverse psychiatric or neurological difficulties show some evidence in support of the effectiveness of these interventions. In addition, such interventions are acceptable to carers. Available evidence is of varying quality, and more high-quality trials are needed. Further research should also establish how specific intervention components, such as structure or interactivity, contribute to their overall efficacy with regard to carer mental health.
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